ENTERIC BACTERIAL AND HEAVY METALS’ LOAD AND HEALTH …

ENTERIC BACTERIAL AND HEAVY METALS’ LOAD AND HEALTH STATUS OF

FISHES FROM RIVER RAVI, PAKISTAN

By

Hafiz Abdullah Shakir

A THESIS FOR THE PARTIAL FULFILLMENT OF THE

REQUIREMENT OF THE DEGREE OF

DOCTORATE IN ZOOLOGY

Supervisor

Prof. Dr. Javed Iqbal Qazi Ph.D (Pak.) Post. Doc. (UK)

Department of Zoology

University of the Punjab, Lahore

2012

In The Name

OF

ALLAH

The Most Merciful !

The Most Beneficent !

The Most Gracious !

“In all that Allah has provided for you, seek the higher value and don’t

forget to seek your share of this world. Do good as Allah have done

good to you; and don’t spread corruption in the world. Allah loves not

the agent of corruption”.

(Al-Quran)

GOLDEN SAYING

OF

HOLY PROPHET

(PBUH)

“By research we mean to see what everybody has seen, and to

think what nobody has thought. He who goes in search of

knowledge is God’s path”.

(Al-Hadith)

CERTIFICATE BY THE RESEARCH SUPERVISOR

This is to certify that research work described in this thesis entitled “Enteric bacterial and

heavy metals’ load and health status of fishes from river Ravi, Pakistan” is the original

work of the author and has been carried out under my direct supervision. I have personally

gone through all the data/results/materials reported in the manuscript and certify their

correctness/authenticity. I further certify that the material included in thesis has not been used

in part or full in a manuscript already submitted or in the process of submission in

partial/complete fulfillment of the award of any other degree from any other institution. I also

certify that the thesis has been prepared under my supervision according to the prescribed

format and I endorse its evaluation for the award of Ph.D. degree through the official

procedures of the University.

(Prof. Dr. Javed Iqbal Qazi) Research Supervisor

DEDICATIONS

TO

REVEREND PARENTS &

FAMILY

WITH WHOSE EFFORTS, GUIDANCE, LOVE AND

PRAYERS, I HAVE BEEN ABLE TO REACH THIS STAGE

OF MY LIFE

CONTENTS

CONTENTS

TITLE PAGE #

ACKNOWLEDGEMENT I

SUMMARY III

1. INTRODUCTION

1

2. REVIEW OF LITERATURE 10

2.1 HEAVY METALS CONTAMINATION OF FRESHWATER RESOURCES 11

2.2 EFFECTS OF METAL POLLUTION ON FISH 13

2.3 HUMAN HEALTH IMPLICATIONS OF METALS EXPOSED FISH 18

2.4 ENTERIC BACTERIAL LOADS OF FISH FROM POLLUTED WATER 23

2.5 REMEDIAL ROLE OF FISH GUT BACTERIA AGAINST METALS INGESTION 25

2.6 SITUATION OF THE RIVER RAVI IN THE STUDY AREA

27

3. MATERIALS AND METHODS 30

3.1 STUDY AREA 30

3.1.1 SITE A: LAHORE SIPHON (CONTROL) 32

3.1.2 SITE B: SHAHDERA 32

3.1.3 SITE C: SUNDER 32

3.1.4 SITE D: BALLOKI 33

TITLE PAGE #

3.2 SAMPLING OF WATER, RIVER BED SEDIMENT AND FISHES FROM

THE STUDY LOCATIONS

33

3.2.1 WATER SAMPLING 33

3.2.2 COLLECTION AND PRESERVATION OF SEDIMENT SAMPLING 34

3.2.3 SAMPLING OF FISHES 34

3.2.3.1 BIOMETRIC DATA OF SAMPLED FISH SPECIES 35

3.2.3.2 DISSECTION OF THE FISHES AND PROCESSING OF

TISSUES FOR DETAILED ANALYSES

36

3.2.1.1 PHYSICO-CHEMICAL ANALYSIS OF RIVER RAVI

WATER

36

3.2.1.1.1 TEMPERATURE 37

3.2.1.1.2 DISSOLVED OXYGEN 37

3.2.1.1.3 TOTAL SUSPENDED SOLIDS 37

3.2.1.1.4 TOTAL DISSOLVED SOLIDS 37

3.2.1.1.5 TOTAL HARDNESS AS CaCO3 38

3.2.1.1.6 CALCIUM HARDNESS AS CaCO3 38

3.2.1.1.7 MAGNESIUM HARDNESS 39

3.2.1.1.8 TOTAL ALKALINITY 39

3.2.1.1.9 CHLORIDE 39

3.2.1.1.10 AMMONIA 40

3.2.1.1.11 PHOSPHATE 41

3.2.1.1.12 SULPHATE 42

TITLE PAGE #

3.2.1.1.13 NITRATE 43

3.2.1.1.14 NITRITE 44

3.3 PROXIMATE ANALYSIS OF THE FISHES’ MUSCLES 45

3.3.1 MOISTURE CONTENT 45

3.3.2 ASH CONTENT 45

3.3.3 CRUDE PROTEIN 45

3.3.4 FAT EXTRACTION 45

3.3.5 TOTAL CARBOHYDRATES 46

3.4 BIOCHEMICAL ANALYSES OF FISHES’ MUSCLES 46

3. 4.1 PREPARATION OF FISH TISSUE EXTRACT IN ICE COLD

SALINE

46

3.4.1.1 ESTIMATION OF TOTAL CARBOHYDRATES 46

3.4.1.2 SOLUBLE PROTEIN CONTENTS 47

3.4.2 PREPARATION OFMUSCLE TISSUE HYDROLYZATE IN SODIUM HYDROXIDE FOR DETERMINATION OF TOTAL

PROTEIN

48

3.4.3 PREPARATION OF ETHANOL EXTRACT OF MUSCLE

TISSUES FORDETERMINATION OF CHOLESTEROL, TOTAL

LIPIDS AND NUCLEIC ACIDS

48

3.4.3.1 ESTIMATION OF CHOLESTEROL 49

3.4.3.2 ESTIMATION OF TOTAL LIPID 49

3.4.3.3 EXTRACTION OF NUCLEIC ACID 50

3.4.3.3.1 ESTIMATION OF RNA 51

3.4.3.3.2 ESTIMATION OF DNA 51

TITLE PAGE #

3.5 HEAVY METALS RESISTANT BACTERIA FROM GUT CONTENTS OF

THE FISHES

57

3.5.1 HEAVY METALS RESISTANT BACTERIAL COLONY FORMING

UNIT (C.F.U.)

57

3.5.2 SELECTION AND PURE CULTURING OF THE BACTERIAL

ISOLATES

60

3.5.3 DETERMINATION OF MINIMUM INHIBITORY

CONCENTRATIONS (MIC)

60

3.5.4 PHENOTYPIC CHARACTERISTICS OF SELECT BACTERIAL

ISOLATES

63

3.5.4.1 GRAM STAINING 63

3.5.4.2 MOTILITY DETECTION (HANGING DROP METHOD) 64

3.5.4.3 ENDOSPORE STAINING 64

3.5.4.4 OXIDASE TEST 65

3.5.4.5 CATALASE TEST 65

3.5.5 BACTERIAL ENZYMES ACTIVITIES 65

3.5.5.1 PROTEASE ACTIVITY 65

3.5.5.2 CELLULASE ACTIVITY 65

3.5.5.3 AMYLASE ACTIVITY 66

3.5.6 GENOTYPIC IDENTIFICATION OF THE SELECT BACTERIAL

ISOLATES

67

3.5.6.1 ISOLATION OF GENOMIC DNA 67

TITLE PAGE #

3.5.6.2 VISUALIZATION OF THE GENOMIC DNA EXTRACTS

ON AGAROSE GEL ELECTROPHORESIS

67

3.5.6.3 16S RDNA GENE AMPLIFICATION 68

3.5.6.4 PCR OPERATING PROGRAMME 69

3.5.6.5 PCR PRODUCT ANALYSIS 69

3.5.6.6 PURIFICATION OF DNA FROM GEL BAND 69

3.5.6.7 ANALYSIS OF PURIFIED DNA FOR SEQUENCING

THE GENE

70

3.6 DETERMINATION OF METALS CONTENTS OF RIVER WATER, RIVER

BED SEDIMENT AND THE FISHES’ ORGANS

70

3.6.1 METALS IN WATER SAMPLES 70

3.6.2 DETERMINATION OF METALS CONTENT OF RIVER BED

SEDIMENT

71

3.6.3 DETERMINATION OF METALS CONTENTS OF DIFFERENT

TISSUES OF THE FISHES

71

3.6.3.1 METAL ANALYSIS OF THE PREPARED SAMPLES ON

ATOMIC ABSORPTION SPECTROPHOTOMETER

72

3.6.4 TRANSPORT OF FISH MUSCLES FOR ICP ANALYSIS TO UK 72

3.6.4.1 SAMPLE PREPARATION FOR DETERMINATION OF

METALS AND MINERALS CONTENTS OF THE FISHES’

MUSCLES BY ICP-OES

73

3.6.4.2 STANDARD SOLUTIONS AND PREPARATION 73

3.6.4.3 SAMPLE ANALYSIS – ICP 74

TITLE PAGE #

3.7 FATTY ACID ANALYSIS OF THE FISHES’ MUSCLES AND SKIN: 75

3.7.1CHEMICALS 75

3.7.2 ANALYSIS OF SAMPLES’ FATTY ACIDS 80

3.7.3 GAS CHROMATOGRAPH ANALYTICAL PROCEDURE 80

3.7.4 FATTY ACID IDENTIFICATION 81

3.8 STATISTICAL ANALYSIS 81

4. RESULTS 82

4.1 PHYSICO-CHEMICAL PARAMETERS OF THE RIVER WATERS AT

FOUR SAMPLING LOCALITIES

82

4.2 BIOMETRIC DATA OF THE SAMPLED FISH SPECIES 92

4.2.1 LENGTH AND WEIGHT OF SPECIMEN 92

4.2.2 MORPHOMETERIC STUDY OF THE SAMPLED FISH SPECIES 93

4.3 PROXIMATE ANALYSES OF THE FISHES’ MUSCLES 106

4.4 BIOCHEMICAL ANALYSIS OF THE FISHES MUSCLES 113

4.5 HEAVY METALS’ RESISTANT BACTERIAL COLONY FORMING UNIT

(C.F.U.) AND ISOLATION FROM THE FISHES’ GUT CONTENT

128

4.5.1 MINIMUM INHIBITORY CONCENTRATION (MIC) AND

MULTIPLE METAL RESISTANCES OF THE BACTERIAL

ISOLATES

143

4.5.2 BIOCHEMICAL CHARACTERIZATION OF THE SELECT

BACTERIAL ISOLATES

184

4.5.3 IDENTIFICATION OF THE BACTERIAL ISOLATES BY PCR

AMPLIFICATION AND SEQUENCING OF THE 16S RDNA

187

TITLE PAGE #

4.6 METALS ANALYSES OF WATER, RIVER BED SEDIMENTS AND

DIFFERENT ORGANS/TISSUES OF THE FISHES

222

4.6.1 METALS CONCENTRATION OF THE RIVER WATER SAMPLES 222

4.6.1.1 CADMIUM 223

4.6.1.2 CHROMIUM 223

4.6.1.3 COPPER 223

4.6.1.4 IRON 224

4.6.1.5 LEAD 224

4.6.1.6 ZINC 224

4.6.1.7 MANGANESE 224

4.6.1.8 NICKEL 225

4.6.1.9 MERCURY 225

4.6.2 METALS CONCENTRATIONS IN THE RIVER BED SEDIMENTS 230

4.6.2.1 CADMIUM 231


4.6.2.3 COPPER 231

4.6.2.4 IRON 231

4.6.2.5 LEAD 231

4.6.2.6 ZINC 232


4.6.2.8 NICKEL 232

4.6.2.9 MERCURY 232

TITLE PAGE #

4.6.3 BIOACCUMULATION OF METALS IN DIFFERENT ORGANS OF

THE FISHES

237

4.6.3.1 CADMIUM 237


4.6.3.3 COPPER 239

4.6.3.4 IRON 240

4.6.3.5 LEAD 241

4.6.3.6 ZINC 242


4.6.3.8 NICKEL 244

4.6.3.9 MERCURY 245

4.6.4 METALS ACCUMULAION IN MUSCLE OF THE FISHES 272

4.7 FATTY ACID PROFILES OF THE FISHES MUSCLES

281

5. DISCUSSION 300

5.1 PHYSICO-CHEMICAL PARAMETERS OF THE SAMPLING LOCALITIES 301

5.2 BIOMETRIC DATA OF SAMPLED FISH SPECIES 305

5.3 PROXIMATE ANALYSIS OF THE FISHES’ MUSCLES 308

5.4 BIOCHEMICAL ANALYSES OF THE FISHES’ MUSCLES 309

5.5 HEAVY METALS’ RESISTANT BACTERIA FROM GUT CONTENTS OF THE

FISHES

314

TITLE PAGE #

5.6 HEAVY METAL CONCENTRATION IN WATER, SEDIMENT AND FISHES’

ORGAN

322

5.7 FATTY ACID ANALYSIS 336

5.8 CONCLUSION

339

6. REFERENCES 343

7. PUBLICATIONS 402

i

ACKNOWLEDGEMENT

All praise to Almighty Allah, the most merciful, the Creator of universe, without whose

consent and consecration nothing would ever be imaginable, who bestowed me with courage

to dedicate to research and contribute something towards the benefit of humanity.. I am

absolutely beholden by my Lord’s generosity in this effort.

I offer my sincere words of thanks to the Holy Prophet Hazrat Muhammad

(PBUH) for enlighten my conscience with the essence of faith in Allah, who is forever torch

of guidance and knowledge.

This piece of acknowledgement gives me immense pleasure and unique opportunity

to feel myself elated and elevated to extend my profound sense of gratitude and gratefulness

to my sincere attributes to my gracious, highly learned, praiseworthy and dignified research

supervisor Prof. Dr. Javed Iqbal Qazi for his inspiring supervision, tremendous

cooperation, observant pursuit, constant encouragement, valuable comments, inspiring

suggestions and positive criticism throughout the completion of this research work and

extreme patience with my work which proved to be a panacea in the completion of this

dissertation. I have no adequate words to admire his tenderness and devotion to spread

knowledge and promote innovation.

I am also grateful to Prof. Dr. Muhammad Akhtar, Chairman, Department of

Zoology, University of the Punjab Lahore, for providing opportunity for research. His sweet

smile, evergreen personality, support and corporation encourage me to complete my work.

ii

No words can adequately express the depth of my gratitude to Dr. Abdul Shakoor

Chaudhry, whose admirable guidance, stimulation, devotion and affectionate behavior

helped me to complete the part of present work at School of Agriculture, Rural and Food

Development, Newcastle University, Newcastle Upon Tyne, UK.

I want to make confession that words, selected with all the wordly wisdom,

articulated with tremendous sophistication and presented with beauty, can never encompass

and fathom the depth of my heartiest thanks to my Parent’s love and care and to my brother

and sisters who always wish to see me glittering on skies of success. I acknowledge to my

wife from the core of heart. I am nothing without their prayers, their cares and their shares in

my success.

I would never forget the bright memories with my lab fellows Dr. Bano, Ms. Zahida

Nasreen, Ms. Saima Shahzad, Faiza Jabeen, Sumaira Aslam, Ali Hussain, Awais

Ibrahium, Sharoon Danial and Hira. Very thanks for nice company, and sharing my highs

and lows, invalueable support during research period.

I am highly indebted to all members of field staff/ fishermens during the tedious

sampling periods who rendered their service during sampling.

It would be injustice not to express my feeling for my lab staff Mr. Muhammad

Ramzan, Muhammad Mohsin, Faisal Shahzad and Nouman Butt for assistance, co-

operation during my laboratory work and provided pleasant environment in Lab.

I would like to extend my appriciation to the Higher Education Commission (HEC),

Pakistan for funding (Scholarship) under the “Indigenous Ph.D. 5000 Fellowship program”

and “IRSIP” to support this research at University of the Punjab, Pakistan and Newcastle

University, UK.

(Hafiz Abdullah Shakir)

iii

SUMMARY

Untreated industrial and domestic sewage waters of big cities in many developing

countries are posing public health threats as well as damaging the natural soil and aquatic

habitats and their biota. One such alarming area is represented by a stretch of river Ravi

while passing through the second biggest city of Pakistan, Lahore. In about 90 Km study

stretch of river Ravi, dozens of pumping stations bring untreated effluents containing

discharges of domestic and small industrial units’ origins of diverse categories to the river

Ravi. While some drains also pour untreated industrial effluents directly to the river.

Consequently, the river while its course through the city Lahore becomes heavily laiden with

organic loads of domestic and certain industrial efflents’origins, pesticidal runoff from

agricultural and urban areas and heavy and other metals from certain industries. The intensity

of these pollutants is seen by the dark colour and pungent smell of the river water just at start

of the downstream locations. Fish fauna of the river has been affected highly negatively. Was

planned for sampling and studying three fish species viz., Cirrhinus(C) mrigala, Labeo(L)

rohita and Catla(C) catla from four locations of the river, namely Siphon, Shahdera, Sunder

and Balloki designated here as A, B, C and D, respectively. The upstream site A is relatively

less polluted, while before the site B much of the urban effluents contaminate the river water.

Up to site C the river receives further load of the domestic and industrial pollutants.

However, at site D the physico-chemical parameters of the river recover to some extent.

iv

Sampling of the fishes, river water and bed sediment were done twice a year representing

both low and high flow seasons. The present study reports physico-chemical parameters of

sampled water, metals concentration in water and river bed sediment, proximate,

biochemical, bacteriological, metals bioaccumulation and fatty acid analyses of the sampled

fish species.

One water sample was preserved after adding 5 ml of HNO3 per liter for heavy metal

analysis and the other stored for studying physico-chemical parameters. River bed sediments

were also sampled and preserved for heavy metal analysis. Nine specimen of a given fish

species of select range of weight were transported from netted fishes from each site during

both low and high flow seasons. In laboratory, after morphometeric measurements, the fish

specimen were dissected under aseptic condition. Fish tissues/organs (gills, eyes, kidney,

heart, liver, scales, skin, intestine and muscles) were stored separately in freezer at -20 ºC.

While gut contents were stored in sterile saline solution at 4 ºC. Standard methods were used

for estimation of total suspended solid and total dissolved solids and reported as mg/L.

Stannous chloride colorimetric method was used for the phospahate estimation while

sulphate and nitrite contents were analysed by EDTA titrimetric and diazotization methods,

respectively. Phenoldisulfonic acid method was used for the estimation of nitrate. For

proximate analyses of the fishes’ muscles; moisure contents were determined by freeze

drying at -50 ºC, ash contents by iginition in furnance, crude protein by Kjeldahl nitrogen, fat

extract by soxhlet apparatus and carbohydrate by extracting all parameters from one hundred.

For muscle biochemistry, total carbohydrates, total and soluble proteins, total lipid,

cholesterol and RNA and DNA were determined according to the methods of Dubios et al.

(1956). Folin-Ciocalteu method (Lowry et al., 1951), Zollner and Kirsch (1962), Folsch

(1957) and Schneider (1957), respectively. From serially diluted (in 0.9 % saline) gut

contents from intestines of three sampled fishes, Cu, Pb, Cr and Hg resistant bacteria were

v

isolated and proceeded for determination of MIC against these metals. Acid digested samples

of waters, river bed sediment and fish tissues/organs (Skin, liver, kidney, scale, heart, gills,

eyes and intestine) were analyzed for the levels of Cr, Cd, Cu, Mn, Pb, Ni, Zn, Hg and Fe

using atomic absorption spectrophotometers. While fishes’ muscles acid digested samples

were analyzed for Na, Ca, K, P, Mg, Cd, Cr, Cu, Mn, Pb, Ni, Zn and Fe using Varian Vista-

MPX CCD Inductively coupled plasma optical emission spectroscopy (ICP-OES Varian Inc,

Australia). Fatty acid profile of the sampled fishes’ muscles after fat extraction (soxhlet

apparatus) were determined using gas chromatography. The peaks of chromatograms were

identified corresponding to 52 FAME standards peaks.

The study part of the river appeared to be polluted as indicated by the higher values of

total suspended solids (908 mg/l) and sulphates (963 mg/l) in waters samples in comparison

to the respective suggested safer values of 150 and 600 mg/l, respectively for drinking water

according to the National Environmental Quality Standards. Dissolved oxygen decreased to

3.8 mgO2/l at site C during low flow. The decreases in dissolved oxygen were found at site B

down to 17.78 and 14.34 %, while 27.34 and 22.35 % for site C and 21.03 and 18.06 % for

site D during low and high flow seasons, respectively when compared with corresponding

values at the upstream less polluted site A. The nitrite contents increased at site B (229 and

290 %), C (524 and 771 %) and D (388 and 617 %) when compared with nitrite contents of

waters sampled from site A (1.12 and 0.53 mg/L) during low and high flow seasons,

respectively. Similarly, at site C during low flow phosphate, chloride and ammonia showed

421 %, 353 % and 259 % increases, respectively over the respective values for the site A.

Weight of sampled fish specimen ranged from 369 to 965 g and 358 to 948 g for C. mrigala;

364 to 879 g and 321 to 898 g for L. rohita, and 350 to 875 and 316 to 902 for C. catla

during low and high flow seasons, respectively. Length of the specimen ranged from 33.5 to

45.2 cm and 33.2 to 45.4 cm in C. mrigala; 32.5 to 42.7 cm and 31.7 to 42.2 cm in L. rohita,

vi

and 29.8 to 40.9 cm and 30.4 to 42.2 cm in C. catla during low and high flow seasons,

respectively. In the present study, growth coefficient (b) measured highest upto 3.19 and 3.16

for C. mrigala; 3.21 and 3.17 for L. rohita and 3.16 and 3.11 for C. catla at site A (upstream)

during high and low seasons, respectively. While lowest values for the corresponding fish

species down to 3.08 and 3.07, 3.08 and 3.06, and 3.03 and 3.01 appeared at site C during

high and low flow seasons, respectively. Mean ‘K’ range was found to be greater than 1 for

L. rohita (1.03-1.18 g/cm3) and C. Catla (1.19-1.27 g/cm

3) but for C. mrigala it fluctuated

between 0.97 to 1.05 g/cm3 during both low and high flow seasons. C. mrigala was highest in

standard length, post orbital length and dorsal fin length but lowest in eye diameter and

mouth gap. Whereas, L. rohita was highest in pectoral fin length and caudal fin length but

lowest in mouth width, dorsal fin length, pelvic fin length and anal fin length. C. catla was

highest in head length, eye diameter, mouth width, mouth gap, pelvic fin length, anal fin

length and caudal fin length but lowest in standard length, post orbital length and pectoral fin

length. All three species showed increased crude protein contents and reduced moisture,

carbohydrates, fat and ash contents at downstream sampling sites. C. catla was highest in

carbohydrates (3.63 %) and ash (1.13 %) contents but lowest in moisture (73.51 %). Whereas

L. rohita was highest in crude protein (20.29 %) and fat contents (1.85 %) but lowest in ash

(0.91 %) and carbohydrates (3.05 %) contents. The, crude protein (19.57 %), carbohydrates

(3.05 %) and fat contents (1.62 %) were lowest in C. mrigala.

The total and soluble proteins and DNA contents of the fishes’ muscles showed

increasing, while carbohydrate, total lipids, cholesterol and RNA contents decreasing trends

alongstream sampling sites during both flow seasons. Carbohydrates contents (45.86 mg/g),

cholesterol (1.79 mg/g) and RNA (6.13 mg/g) approached highest levels at site A, while

these parameters decreased to lowest levels with values up to16.87, 0.62 and 5.56 mg/g,

respectively at site C. Whereas total protein (16.87 mg/g), soluble protein (95.86 mg/g) and

vii

DNA (1.47 mg/g) were highest at site C. Lowest levels of these parameters with respective

values of 112.94, 49.87 and 1.40 mg/g were observed at site A.

One hundred and twenty three metals (copper, chromium, mercury and lead) resistant

bacteria were isolated from serially diluted gut contents of three fish species. Highest

bacterial strains were isolated from gut contents of L. rohita (38.21 % and 38.33 %) than C.

catla (33 % and 28 %) and C. mrigala (29 % and 33 %) during high and low flow seasons,

respectively. Colony forming units decreased along stream sampling sites up to site C. While

at site D, values of the parameter increased in comparison with corresponding value at site C.

All the isolates showed multi metal resistance ranging from 250 to 1000 µg/ml for Cu2+

, 350

to 1400 µg/ ml for Pb2+

, 10 to 70 µg/ ml for Hg2+

and 350 to 1650 µg/ ml for Cr6+

. Forty five

isolates which showed growth in the presence of 750 to1000 µg, 1100 to 1400 µg, 45 to 70

µg, 1100 to 1650 µg/ml of Cu2+

, Pb2+

, Hg2+

and Cr6+

, respectively were selected for further

characterization and identification. After 16S rDNA nucleotide sequence, BLAST showed

homology of the select isolates with twelve genera Aeromonas, Bacillus, Oceanimonas,

Obesumbacterium, Buttiauxella, Enterobacter, Exiguobacterium, Klebsiella, Serratia,

Raoultella, Citrobacter and Achromobacter.

The mean metal concentrations in water samples were in order of: Fe >Zn >Mn> Cr>

Cu >Ni > Hg > Pb > Cd, whereas in sediment, the metals were in the order of: Fe > Zn > Mn

> Cu > Cr > Ni > Hg > Pb > Cd. Mean metals concentration in water and sediment samples

appeared significantly higher during low flow than high flow season at all sites. Highest

values of cadmium (0.17 mg/l), chromium (7.29 mg/l), copper (4.78 mg/l), iron (52.50 mg/l),

lead (2.24 mg/l), zinc (43.62 mg/l), manganese (13.72 mg/l), nickel (3.59 mg/l) and mercury

(2.52 mg/l) concentrations appeared at site C during low flow season. While all the studied

metals concentrations in water were found higher than respective National Environmental

Quality Standards’ (NEQS) permissible limit.

viii

The concentration of metals in river bed sediment samples were higher than in water

samples. The cadmium content ranged from 0.17 to 2.34 mg/kg, chromium from 9.70 to

67.94 mg/kg, copper from 15.95 to 73.47 mg/kg, iron from 91.85 to 384.15 mg/kg, lead from

0.75 to 5.80 mg/kg, zinc from 134.66 to 402.30 mg/kg, manganese from 13.93 to 137.23

mg/kg, nickel from 2.65 to 31.17 mg/kg and mercury from 1.02 to 20.15 mg/kg during both

low and high flow seasons.

Mean metals (Cd, Cr, Cu, Fe, Pb, Zn, Mn, Ni and Hg) concentrations in

tissues/organs (eyes, gills, heart, intestine, kidney, liver, scale and skin) of C. mrigala, L.

rohita and C. catla from the select sampling sites during low and high flow season of river

indicated that cadmium accumulation pattern was in the order of: kidney > liver > intestine

> scale > heart > eyes > skin > gills. The highest cadmium accumulation was recorded in

L. rohita (0.17 mg/kg) than C. catla (0.15 mg/kg) and C. mrigala (0.15 mg/kg). The mean

highest chromium bioaccumulation 5.39 mg/kg was measured at site C than D, B and A

during both low and high flow seasons. Highest chromium accumulation was recorded in C.

mrigala (3.59 mg/kg) followed by C. catla (3.28 mg/kg) and L. rohita (2.99 mg/Kg). Copper

bioaccumulation in the fishes’ tissues was in the order of kidney > liver > intestine > heart

> scale > skin > gills > eyes. Highest copper bioaccumulation occured in C. mrigala (6.84

mg/kg) than C. catla (6.79 mg/kg) and L. rohita (6.74 mg/kg). Mean highest iron

concentration was measured at site C than D, B and A during both low and high flow

seasons. The mean highest bioaccumulation among three sampled species ranged from 0.27

to 0.53 mg/kg in L. rohita and from 0.25 to 0.47 in L. rohita at site A than from 1.77 to 3.01

mg/kg in C. catla and from 1.43 to 2.14 in L. rohita at site B, from 4.07 to 6.66 in C. catla

and from 3.52 to 6.33 mg/kg in C. catla at site C, from 2.55 to 4.58 mg/kg in C. catla and

from 2.12 to 3.82 mg/kg in L. rohita at site D during low and high flow seasons, respectively.

Zinc accumulation pattern in the fish tissue was in order of: kidney >liver >heart > intestine

ix

> scale > eyes > gills > skin. The highest manganese accumulation in the fishes’ tissues

was recorded in C. mrigala (8.36 mg/kg) than L. rohita (8.15 mg/kg) and C. catla (7.30

mg/kg). Highest nickel bioaccumulation in fish organs was measured at site C than D, B and

A during both low and high flow seasons. The mercury bioaccumulation pattern in fish tissue

was in order of: liver > kidney > intestine > heart > scale > eyes >skin >gills. Highest

mercury accumulation was recorded in C. mrigala (1.54 mg/kg) than C. catla (1.52 mg/kg)

and L. rohita (1.50 mg/kg).

Fish muscles showed mean highest concentration of Ca (14032 mg/kg), K (3953

mg/kg), Na (5190 mg/kg), Mg (667 mg/kg), P (10079 mg/kg) at site C than 10042, 6736 and

3793 mg/kg for Ca, 3682, 3314 and 2796 mg/kg for K, 4446, 3873 and 3171 mg/kg for Na,

601, 624 and 573 mg/kg for Mg, 8319, 6768 and 5323 mg/kg for P at site B, D and A,

respectively. All macro elements’ mean concentrations were higher for Ca (10663 mg/kg), K

(3607 mg/kg), Na (4515 mg/kg), Mg (659 mg/kg) and P (8513 mg/kg) during low flow than

the corresponding values of 6638, 3266, 3825, 573 and 6732 mg/kg during high flow. The

pattern among the sites was site C > site B>site D> site A, excepting the Mg. The order of

mean concentration of these element was Ca>P>Na>K>Mg.

The pattern of metal bioaccumulation in the fishes’ muscles among the sites was site

C > site D > site B > site A, except for cadmium, chromium and copper. The order of mean

concentration of these element was Zn > Fe> Mn >Cu > Cr > Pb > Ni > Cd. Fishes’ muscles

sampled from site C accumulated higher Cd (434, 300, 467 %), Cr (323, 282, 438 %), Cu

(72, 65, 77 %), Pb (1656, 1450, 1626 %), Mn (299, 336, 374 %), Ni (473, 620, 386 %), Zn

(116, 121, 122 %) and Fe contents(58, 75, 78 %) as compared with the corresponding values

for fish species C. mrigala, L. rohita and C. catla collected from the upstream site (A) during

low flow season. In the present study, Zn accumulation (22.73-48.96 mg/Kg) was highest in

muscles among the studied minerals at different sites. Mn ranged from 2.25-9.75 mg/Kg in

x

the fishes’ muscles. Manganese permissible limits of (0.01 mg/kg) rendered the present level

of the metal toxic for the fish as well as for fish consumers. Cr concentrations ranged from

0.95 to 3.65 mg/kg which is above the level at which human consumption is advised.. More

bioaccumulation of Cr occurred during low flow season. Copper (2.96-5.03 mg/kg) was

within permissible limit (30 mg/kg).The Pb bioaccumulation in muscles ranged from 0.17 to

2.85 mg/kg and appeared above the permissible limits (2 mg/kg) in fish for human

consumption. In short, chromium, lead, manganese and mercury concentrations in the

sampled fishes’ muscles were much higher than the WHO recommended permissible limits.

In the present study, twelve kinds of saturated fatty acids (SFA), fifteen

monounsaturated fatty acids (MUFA) and eleven polyunsaturated fatty acids (PUFA) were

analyzed in fishes’ muscle. The highest total SFA up to 57.09 % in muscles of the sampled

fishes appeared at site C than B (54.75 %), D (53.52 %) and A (50.85 %). Whereas the

reverse situation was found for total PUFA at site C (5.98 %) followed by D (7.36 %), B

(8.90 %) and A (11.87 %). The total MUFA were higher at site A with descending order for

site C, B and D. Total PUFA showed a decreasing trend from upstream to downstream and

decrease between high and low flow seasons, respectively for each of the three fish species:

L. rohita from 10.76 to 9.85%, C. mrigala from 9.64 to 8.12% and C.catla from 7.71 to

7.30%. . Whereas at site C the values showed further reductions up to 9.28 and 5.46 % for L.

rohita, 7.51 and 6.14 % for C. mrigala and 4.43 and 3.05 % for C. catla, during high and low

flow seasons, respectively. The total ω3 were lower than total ω6 long chain PUFA at all

sites during both low and high flow seasons. The higher ω3/ ω6 ratio was observed in C.

catla than L. rohita and C. mrigala muscle samples. Conclusively, all the parameters

reported in the present study expressed drastic effects of industrial and domestic effluents at

the first two downstream locations as many of the parameters defining growth and health

status of the fishes such as heavy metals concentrations, saturated fatty acids, total and

xi

soluble protein increased to varying magnitudes, whereas the amount of polyunsaturated fatty

acids decreased following the effects of urban pollutants. However, Coming further 25Km

downstream at site C the pollutant pollution dilute due to Q.B link water canal between site C

and D, the highly distributed both biotic and abiotic parameters tended to recover

approximating their corresponding upstream levels. Based upon this biphasic trend of the

studied parameters, a model of urban pollutants intrusion loads and recovery of river’s

physico-chemical and biotic components has been indicated.

xii

LIST OF TABLES Table Title Page

No.

3.1 Different strengths of the salts of respective metals mixed with

separately autoclaved concentrated solution of nutrient agar to prepare

media of varying metals ions’ concentrations

59

3.2 Preparation of nutrient broth containing concentrations of the metals’

ions, employed in the experiments of MIC

61

3.3 Composition of cellulase selective agar media

66

3.4 ICP-OES operational settings during analysis of muscle samples

74

3.5 GC gradient for separation and quantification of fatty acids

81

4.1 Means (mg/L, unless mentioned otherwise) of physico-chemical

parameters of waters with their standard error of means and

significance of different alongstream sites and flow seasons of the

river.

85

4.2 Means (mg/L, unless otherwise mentioned) of physico-chemical

parameters of the river waters sampled from different alongstream

sites (Siphon (upstream =A); Shahdera =B; Sunder =C; and Head

balloki =D) during Low and High flow seasons.

87

4.3 Means of weight, total length and condition factor with their standard

error of means (SEM) and significance of the different alongstream

sites, flow seasons and sampled species.

95

4.4 Means of weight, total length and condition factor with their standard

error of means (SEM) and significance of the sampled fish species

from different alongstream sites (Siphon (upstream =A); Shahdera =B;

Sunder =C; and Head balloki =D) during low and high flow seasons.

96

4.5 Weight vs total length regression equations with significance for three

sampled fish species from four sampling sites (Siphon (upstream =A);

Shahdera =B; Sunder =C; and Head balloki =D) during low and high

flow seasons of the river.

97

4.6 Means of morphometric parameters with their standard error of means

(SEM) and significance of sampling sites, flow seasons and fish

species.

104

xiii

Table Title Page

No.

4.7 Mean morphometric parameters with their standard error of means

(SEM) of the sampled fish species from four sampling sites (Siphon

(upstream =A); Shahdera =B; Sunder =C; and Head balloki =D)

during low and high flow seasons of the river.

105

4.8 Proximate parameters (%) with their standard error of means (SEM)

and significance for sampling sites, flow seasons and sampled fish

species from the river.

108

4.9 Proximate parameters (%) with their standard error of means (SEM)

and significance of sampled fish species netted from four selected

sampling sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and

Head balloki =D) and two flow seasons of the river.

109

4.10 Means of biochemical parameters (mg/g) of muscles with standard

error of means and significance (SEM) for sampling sites, flow

seasons and fish species.

117

4.11 Means of biochemical parameters (mg/g) of muscles of three fish

species of different alongstream sites (Siphon (upstream =A);

Shahdera =B; Sunder =C; and Head balloki =D) during low and high

flow seasons of the river with standard error of means (SEM) and

significance.

118

4.12 Protocol established for assigning code number to the bacterial

isolates.

130

4.13 Colony forming units (C.F.U) from the gut contents of the fish species

sampled from site A (Siphon) during low flow season on different

metal containing nutrient agar media and colonies’ morphologies of

pure cultures of the bacteria.

131


sampled from site A (Siphon) during high flow season on different



132


sampled from site B (Shahdera) during low flow season on different



133


sampled from site B (Shahdera) during high flow season on different



134

xiv

Table Title Page

No.


sampled from site C (Sunder) during low flow season on different



135


sampled from site C (Sunder) during high flow season on different



136


sampled from site D (Balloki) during low flow season on different



137


sampled from site D (Balloki) during high flow season on different



138

4.21 Determination of minimum inhibitory concentrations (MIC) of Pb2+

ions for the bacterial isolates. Growths (O.D600nm) were raised with 2

% inoculations in the metal containing nutrient broths and incubate at

37 ºC for 24 hrs.

144

4.22 Determination of minimum inhibitory concentrations (MIC) of Cu2+



37 ºC for 24 hrs.

153

4.23 Determination of minimum inhibitory concentrations (MIC) of Hg2+



37 ºC for 24 hrs.

162

4.24 Determination of minimum inhibitory concentrations (MIC) of Cr6+



37 ºC for 24 hrs.

171

4.25 Biochemical characterization of the select bacterial isolates. All

bacteria maintained rod shaped cell morphology.

185

4.26 Relatedness of the nucleotides sequences of the subject isolates with

classified bacteria on the bases of 16S rDNA blast homology.

218

xv

Table Title Page

No.

4.27 Mean concentrations (mg/l) of heavy metals in waters samples for

alongstream locations and flow seasons with standard error of means

and significance.

226

4.28 Mean concentration (mg/l) of heavy metals in waters sampled from

different alongstream locations (Siphon (upstream =A); Shahdera =B;

Sunder =C; and Head balloki =D) during low and high flow seasons of

the river.

227

4.29 Mean concentration (mg/kg of dried bed sediment) of heavy metals in

sediment with their standard error of means (SEM) and significance

for alongstream locations and flow seasons of the river Ravi.

233

4.30 Mean concentration (mg/kg of dried bed sediment) of heavy metals in

sediment with their standard error of means (SEM) and significance

sampled from different alongstream locations (Siphon (upstream) =A;

Shahdera =B; Sunder =C; and balloki =D) during low and high flow

seasons of the river Ravi.

234

4.31 Means of metals’ concentrations for sampling sites, flow seasons, fish

species and fishes organs with standard error of means (SEM) and

significance (P).

247

4.32 Means±SD of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish

organs of the fish species sampled during two flow seasons from the

selected upstream sampling site A (siphon).

248

4.33 Means of metals (Zn, Mn, Ni, Hg) concentrations in fish organs of the

fish species sampled during two flow seasons from the selected

upstream sampling site A (siphon) with standard deviation (SD).

249

4.34 Means±SD of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish

organs of the fish species sampled during two flow seasons from the

selected downstream sampling site B (shahdera).

250

4.35 Means±SD of metals (Zn, Mn, Ni, Hg) concentrations in fish organs

of the fish species sampled during two flow seasons from the selected

downstream sampling site B (shahdera).

251

4.36 Means of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish organs of

the fish species sampled during two flow seasons from the selected

downstream sampling site C (sunder) with standard deviation (SD).

252

xvi

Table Title Page

No.



downstream sampling site C (sunder) with standard deviation (SD).

253

4.38 Means of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish organs of

the fish species sampled durign two flow seasons from the selected

downstream sampling site D (head Balloki) with standard deviation

(SD).

254



downstream sampling site D (head Balloki) with standard deviation

(SD).

255

4.40 Means of metals concentrations standard error of means (SEM) and

significance) in fish organs of sampled fish species during two flow

seasons from the selected sampling sites.

256

4.41 Mean macro elements concentration in muscles for sampling sites,

flow seasons and fish species with their standard error of means

(SEM) and significance (P).

275

4.42 Mean macro elements’ bioaccumulation (mg/Kg dried weight) in

muscles of three fish species sampled from different alongstream

locations (siphon (upstream) = A; Shahdera= B; Sunder=C; and head

balloki =D) during low and high flow seasons.

276

4.43 Mean Standard error of means (SEM) with significance P indicated by

*, ** and *** represent significance at P<0.05, P<0.01 and P<0.001

respectively for minerals concentration in muscles of selected fish

species from four river sampling sites with two flow seasons.

277

4.44 Mean heavy metals concentration in muscles concentration in muscles

for sampling sites, flow seasons and fish species with their standard

error of means (SEM) and significance (P).

278

4.45 Mean heavy metals (mg/Kg dried weight) bioaccumulation in muscles

of three fish species sampled from different alongstream locations

(siphon (upstream) = A; Shahdera= B; Sunder=C; and head balloki

=D) during low and high flow seasons.

279

4.46 Mean Standard error of means (SEM) with significance P indicated by

*, ** and *** represent significance at P<0.05, P<0.01 and P<0.001

respectively for metals concentration in muscles of selected fish

species from four river sampling sites with two flow seasons.

280

xvii

Table Title Page

No.

4.47 Means of total fatty acid composition of muscles with standard error

of means (SEM) and significance for sampling sites, flow seasons and

fish species.

284

4.48 Mean fatty acid profiles of Cirrhinus mrigala (Mori) for four

downstream river flow sites (Siphon = A; Shahdera = B; Sunder = C

and Balloki = D) with standard error of means (SEM) and significance

(P).

285

4.49 Fatty acid profiles of Cirrhinus mrigala (Mori) for two flow season of

river Ravi with standard error of means (SEM) and significance (P).

286

4.50 Mean fatty acid profile of Cirrhinus mrigala (Mori) with standard

error of means (SEM) and significance (P) for four alongstream sites

(Siphon = A; Shahdera = B; Sunder =C and Balloki=D) with two flow

season.

287

4.51 Mean fatty acid profiles of Labeo rohita (Rohu) for four downstream

river flow sites (Siphon = A; Shahdera = B; Sunder = C and Balloki =

D) with standard error of means (SEM) and significance (P).

288

4.52 Fatty acid profiles of Labeo rohita (Rohu) for two flow season of river

Ravi with standard error of means (SEM) and significance (P).

289

4.53 Mean fatty acid profile of Labeo rohita (Rohu) with two flow season

from four downstream river flow sites (Siphon: site A; Shahdera: site

B; Sunder: site C; head bolloki: site D) with standard error of means


290

4.54 Mean fatty acid profiles of Catla catla (thaila) for four downstream

river flow sites (Siphon = A; Shahdera = B; Sunder = C and Balloki =

D) with standard error of means (SEM) and significance (P).

291

4.55 Fatty acid profiles of Catla catla (Thaila) for two flow season of river

Ravi with standard error of means (SEM) and significance (P).

292

4.56 Mean fatty acid profile of Catla catla (Thaila) with two flow season

from four downstream river flow sites (Siphon: site A; Shahdera: site

B; Sunder: site C; head bolloki: site D) with standard error of means


293

4.57 Means of total fatty acid composition of muscles with standard error

of means (SEM and significance for sampled fish species from

selected four sites with two flow seasons of river Ravi.

294

xviii

Table Title Page

No.

4.58 Mean of Standard error of means (SEM) with significance *, ** and

*** indicated by *, ** and *** represent significance at P<0.05,

P<0.01 and P<0.001 respectively for Saturated fatty acids in muscles

of selected fish species from four river sampling sites with two flow

seasons.

295



P<0.01 and P<0.001 respectively for Monounsaturated fatty acid in

muscles of selected fish species from four river sampling sites with

two flow seasons.

296



P<0.01 and P<0.001 respectively for polyunsaturated fatty acid in

muscles of selected fish species from four river sampling sites with

two flow seasons.

297

xix

LIST OF FIGURES

Fig. Title Page

No.

3.1 Map of the river Ravi Lahore stretch showing four study sites and major

urban pollution inlets

31

3.2 Standard curve for total carbohydrates (Phenol sulfuric acid method).

53

3.3 Protein standard curve (Lowry method).

54

3.4 DNA standard curve (Schneider Method).

55

3.5 RNA standard curve (Orcinol method).

56

3.6 Peaks of Standards used for quantification of muscle fatty acid profile.

79

4.1 Means±SD of physico-chemical parameters of the river waters sampled

from different alongstream sites (Siphon (upstream) =A; Shahdera =B;

Sunder =C; and Head balloki =D) during low and high flow seasons of the

river Ravi.

89

4.2 Percent difference of physico-chemical parameters of the river waters

sampled from downstream sites (Shahdera =B; Sunder =C; and Head

balloki =D) from the corresponding values of water sampled from

upstream site = Siphon (A) during low and high flow seasons of the river

Ravi.

91

4.3 Relationship between log Length (cm) and log wet weight (g) in Cirrinus

mrigala sampled from sampling site = A (Siphon) upstream during low

(left side) and high (right side) flow seasons.

98


mrigala sampled from sampling site = B (Shahdera) during low (left side)

and high (right side) flow seasons.

98


mrigala sampled from sampling site = C (Sunder) during low (left side)


99


mrigala sampled from sampling site = D (Balloki) during low (left side)


99

xx

Fig. Title Page

No.

4.7 Relationship between log Length (cm) and log wet weight (g) in Labeo

rohita sampled from sampling site = A (Siphon) upstream during low (left

side) and high (right side) flow seasons.

100


rohita sampled from sampling site = B (Shahdera) upstream during low


100


rohita sampled from sampling site = C (Sunder) upstream during low (left


101


rohita sampled from sampling site = D (Balloki) upstream during low


101

4.11 Relationship between log Length (cm) and log wet weight (g) in Catla

catla sampled from sampling site = A (Siphon) upstream during low (left


102


catla sampled from sampling site = B (Shahdera) upstream during low


102


catla sampled from sampling site = C (Sunder) upstream during low (left


103


catla sampled from sampling site = D (Balloki) upstream during low (left


103

4.15 Proximate analyses of muscle of Cirrhinus mrigala from different

alongstream sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and

Head balloki =D) during low and high flow seasons of the river Ravi.

110

4.16 Proximate analyses of muscle of Labeo rohita from different alongstream

sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and Head balloki

=D) during low and high flow seasons of the river Ravi.

111

4.17 Proximate analyses of muscle of Catla catla from different alongstream

sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and Head balloki

=D) during low and high flow seasons of the river Ravi.

112

xxi

Fig. Title Page

No.

4.18 Biochemical parameters (mg/g) with standard deviations (Bars) of muscle

of Cirrhinus mrigala sampled from alongstream sites (Siphon (upstream)

=A; Shahdera =B; Sunder =C; and Head balloki =D) during low and high

flow of the river Ravi.

119

4.19 Biochemical parameters (mg/g) with standard deviations (Bars) of muscle

of Labeo rohita sampled from alongstream sites (Siphon (upstream) =A;

Shahdera =B; Sunder =C; and Head balloki =D) during low and high flow

of the river Ravi.

120

4.20 Biochemical parameters (mg/g) with standard deviations (Bars) muscle of

Catla catla sampled from alongstream sites (Siphon (upstream) =A;

Shahdera =B; Sunder =C; and Head balloki =D) during low and high flow

of the river Ravi.

121

4.21 Mean biochemical parameters (mg/g) with standard deviation (Bar) of

muscle of Cirrhinus mrigala sampled during low and high flow season of

the river Ravi.

122

4.22 Biochemical parameters (mg/g) with standard deviation (Bar) of muscle

of Labeo rohita sampled during low and high flow season of the river

Ravi.

123

4.23 Mean biochemical parameters (mg/g) with standard deviation (Bar) of

muscle of Catla catla sampled during low and high flow season of the

river Ravi.

124

4.24 Percent difference of biochemical parameters of muscle of Cirrhinus

mrigala (Mori) sampled from downstream sites (Shahdera =B; Sunder

=C; and Head balloki =D) from the corresponding values of fish sampled

from upstream site = Siphon (control) during low and high flow seasons

of the river Ravi.

125

4.25 Percent difference of biochemical parameters of muscle of Labeo rohita


balloki =D) from the corresponding values of fish sampled from upstream

site = Siphon (control) during low and high flow seasons of the river Ravi.

126

4.26 Percent difference of biochemical parameters of muscle of Catla catla


balloki =D) from the corresponding values of fish sampled from upstream

site = Siphon (control) during low and high flow seasons of the river Ravi.

127

xxii

Fig. Title Page

No.

4.27 Colony forming units (C.F.U.) of Cu2+

(250 µg/ml of nutrient agar)

resistant bacterial isolates from gut content of Labeo rohita sampled from

different sites and during the two flow season from the river Ravi.

139



resistant bacterial isolates from gut content of Cirrhinus mrigala sampled

from different sites and during the two flow season from the river Ravi.

139



resistant bacterial isolates from gut content of Catla catla sampled from


139

4.30 Colony forming units (C.F.U.) of Pb2+




140





140




different sites and during the two flow season from the river Ravi

140

4.33 Colony forming units (C.F.U.) of Cr6+




141





141





141

4.36 Colony forming units (C.F.U.) of Hg2+




142





142

xxiii

Fig. Title Page

No.




different sites and during the two flow season from the river Ravi

142

4.39 MIC of Cu for the selected bacteria isolated from gut contents of the fish

species sampled from four sites (Siphon (upstream) =A; Shahdera =B;

Sunder =C; and Head balloki =D) during both low (red bars) and high

(blue bars) flow seasons of the river Ravi.

180

4.40 MIC of Pb for the selected bacteria isolated from gut contents of sampled

fish species sampled from four sites (Siphon (upstream) =A; Shahdera

=B; Sunder =C; and Head balloki =D) during both low and high flow

seasons of the river Ravi.

181

4.41 MIC of Hg for the selected bacteria isolated from gut contents of the fish

species sampled from four sites (Siphon (upstream) =A); Shahdera =B;

Sunder =C; and Head balloki =D) during both low and high flow seasons

of the river Ravi.

182

4.42 MIC of Cr for the selected bacteria isolated from gut contents of the fish

species sampled from four sites (Siphon (upstream) =A); Shahdera =B;

Sunder =C; and Head balloki =D) during both low and high flow seasons

of the river Ravi.

183

4.43 Percent difference of heave metal contents of waters sampled from

downstream sites (Shahdera =B; Sunder =C; and balloki =D) from the

corresponding values of fish sampled from upstream site = Siphon

(control) during low and high flow seasons of the river Ravi.

229

4.44 Percent difference of heave metal contents of river bed sediments sampled

from downstream sites (Shahdera =B; Sunder =C; and balloki =D) from

the corresponding values of fish sampled from upstream site = Siphon


236

4.45 Means of Cd concentrations in different organs of the Cirrhinus mrigala

sampled during the low and high flow seasons from alongstream sites of

river Ravi with their standard deviations (SD).

257

4.46 Means of Cr concentrations in different organs of the Cirrhinus mrigala



257

4.47 Means of Cu concentrations in different organs of the Cirrhinus mrigala



258

xxiv

Fig. Title Page

No.

4.48 Means of Fe concentrations in different organs of the Cirrhinus mrigala



258

4.49 Means of Pb concentrations in different organs of the Cirrhinus mrigala



259

4.50 Means of Zn concentrations in different organs of the Cirrhinus mrigala



259

4.51 Means of Mn concentrations in different organs of the Cirrhinus mrigala



260

4.52 Means of Ni concentrations in different organs of the Cirrhinus mrigala



260

4.53 Means of Hg concentrations in different organs of the Cirrhinus mrigala



261

4.54 Means of Cd concentrations in different organs of the Labeo rohita



262

4.55 Means of Cr concentrations in different organs of the Labeo rohita



262

4.56 Means of Cu concentrations in different organs of the Labeo rohita



263

4.57 Means of Fe concentrations in different organs of the Labeo rohita



263

4.58 Means of Pb concentrations in different organs of the Labeo rohita



264

xxv

Fig. Title Page

No.

4.59 Means of Zn concentrations in different organs of the Labeo rohita



264

4.60 Means of Mn concentrations in different organs of the Labeo rohita



265

4.61 Means of Ni concentrations in different organs of the Labeo rohita



265

4.62 Means of Hg concentrations in different organs of the Labeo rohita



266

4.63 Means of Cd concentrations in different organs of the Catla catla sampled

during the low and high flow seasons from alongstream sites of river Ravi

with their standard deviations (SD).

267

4.64 Means of Cr concentrations in different organs of the Catla catla sampled



267

4.65 Means of Cu concentrations in different organs of the Catla catla sampled



268

4.66 Means of Fe concentrations in different organs of the Catla catla sampled



268

4.67 Means of Pb concentrations in different organs of the Catla catla sampled



269

4.68 Means of Zn concentrations in different organs of the Catla catla sampled



269

4.69 Means of Mn concentrations in different organs of the Catla catla



270

xxvi

Fig. Title Page

No.

4.70 Means of Ni concentrations in different organs of the Catla catla sampled



270

4.71 Means of Hg concentrations in different organs of the Catla catla sampled



271

4.72 Means of total fatty acid composition of muscles in Cirrhinus mrigala

from selected four sites with two flow seasons of river Ravi.

298

4.73 Means of total fatty acid composition of muscles in Labeo rohita from

selected four sites with two flow seasons of river Ravi.

298

4.74 Means of total fatty acid composition of muscles in Catla catla from

selected four sites with two flow seasons of river Ravi. 299

Chapter 1 Introduction

1

INTRODUCTION

Freshwater resources represent only 3 % of the entire water resources of the earth

(Wilson and Carpenter, 1999). Water is vital not only for survivals of living organisms but

also for anthropogenic activities like domestic, agricultural and industrial needs (Bartram and

Balance, 1996; WHO, 2005). Utilization of freshwater resources are as old as human

civilizations (Gleick et al., 2002). Rivers are important components of freshwater

ecosystems. Accessibility to these natural water bodies has been a directional factor in the

development of various civilizations (Benjamin et al., 1996). Human social and cultural

evolution started in those areas where ample quantity of good quality freshwater was

available (Gupta et al., 2006). Accordingly, historic and major cities are located along rivers’

sides. Several rivers such as Ganges, Nile and Indus have been the life lines for ancient

civilizations (Wichelns and Oster, 2006). Rivers have been providing food, water for

drinking and irrigation, soil fertility and transport to humans. While the cities in return have

been dumping their solid and water wastes into them. Initially these wastes were of domestic

origin to whom soon joined the industrial activities.

In developing countries, heavy industrial developments and intensive agricultural

practices, albirt needed to meet the needs of increasing populations, have been contaminating

rivers, directly/indirectly through effluents loaded with different chemicals without

considering environmental protective measures (Pandey, 2006). Anthropogenic activities can

degrade water quality depending upon the intensity and duration of contribution from point


2

and non point sources (Tarvainen et al., 1997). Easily recognized industrial or other units

directly discharging objectionable effluents into water bodies point sources of pollution

(Cornell et al., 1999; Fang et al., 2005). While non point sources pour pollutants in rivers

after rainfall from gaseous and suspended particles in air, from industrial emission, through

surface runoff fertilizers, pesticides and soil improving agents deposited on soil surface

including both urban and agricultural areas (Choi and Blood, 1999; Davis et al., 2001;

Kyriakeas and Watzin, 2006). Continuous release of toxicants from point and non-point

sources is putting the aquatic ecosystem under stress (Dural et al., 2006). Downstream

ecology of rivers moving across cities and industrial areas are facing harsh dreadful

conditions; higher losses in biotic integrity and many of these freshwater resources have

become unsafe for human consumption (Gafny et al., 2000; Lima-Junior et al., 2006).

Most of the developing countries do not have infrastructure to implement the water

quality standards for controlling water pollution (Hinrichsen et al., 1998). For these reasons,

needs of awareness about the effects of anthropogenic pollution on freshwater ecosystems

has gradually increased. River pollution has become a matter of concern over the last decades

(Mahmood, 2003; Begum et al., 2005; Vutukuru, 2005).There are numerous drastic effects of

many organic, heavy metals and microorganisms’ load on health and diversity of aquatic

fauna and flora and ecological balance of the recipient environment (Ashraj, 2005; Vosyliene

and Jankaite, 2006; Farombi et al., 2007). Besides long list of pollutants, natural aquatic

systems may extensively be contaminated with heavy metals released from domestic,

industrial and other man made activities (Farombi et al., 2007). All metals become toxic if

their concentration exceeds the permissible levels (Wright and Welbourn, 2002). Heavy

metals’ effects become more evident among aquatic organisms at higher trophic levels

(Devlin, 2006; Rasmussen et al., 2008). In aquatic medium, metals are present either in

dissolved forms which are bioavailable and highly toxic or remain bound with suspended


3

particles which are comparatively less toxic to aquatic organisms (Morrison et al., 1990).

Heavy metals’ availability depend upon pH, total hardness, turbidity and flow rate of rivers

(Wright and Welbourn, 2002; Caruso et al., 2003).

In ecological language, fish are irreplaceable bio-indicators of any type of and extent

of damage to aquatic environment. Among animal species, fishes that cannot escape from the

detrimental effects of aquatic pollutants are the inhabitants of specific microhabitat within

inter connected river system (Olaifa et al., 2004). Anthropogenic activities strongly influence

the distribution, migration, colonization and re-colonization of fishes (Magalhaes et al.,

2002).

Fish species are unique among the vertebrates by having two prominent routes of

metal acquisition, i.e., from the diet and from the polluted water itself (Bury et al., 2003).

The metals are absorbed into blood and transported to various organs of fish (Nussey et al.,

2000) and potentially lead to bio-magnification (Chale, 2002; Javed, 2004a; Fernandes et al.,

2008). Metals bind with cellular components including protein and nucleic acids and

interfere with metabolic activities (Zhang and Casey, 1996) that may lead to neurotoxic,

genotoxic, mutagenic and teratogenic effects. Depending upon the nature, diversity and

levels of the pollutants a water system is receiving, the exposed organisms are influenced

varyingly ranging form behavioral adjustment through disturbed physiological responses,

depressed growth up to drastic developmental abnormalities and death due to toxigenic

effects rendered by specific pollutants (Sehgal and Saxena, 1986; Das, 2007). Levels of

metals in different organs of fish are considered important indices for highlighting the

pollution state of the sediment and its biota and associated health implication for the

consumers. (Farkas et al., 2002; Mendil et al., 2005). Accumulation of heavy metals in

different organs exhibit different patterns (Jezierska and Witeska, 2007) which are highly


4

influenced by spatial and seasonal variations (Nussey et al., 2000, Avenant-Oldewage and

Marx, 2000; Farkas et al., 2002; Besser et al., 2007).

Under certain environmental conditions, heavy metals may bioaccumulate upto toxic

concentrations and cause ecological damage (Unlu et al., 1996). Levels of heavy metals’

bioaccumulation depend on type of species, trophic level, flow season, metal type, and

distance from the metal source (Wright and Welbourn, 2002; Asuquo et al., 2004; Terra et

al., 2008). Heavy metals or their metabolites exerts deleterious effects by inhibiting growth

rate of fish (Hayat et al., 2007), gonads maturation (El-Boray et al., 2003), changing

spawning behaviour, duration and number of eggs per spawn (Barakat, 2004) affecting

adversely on egg and embryo viability (Speranza et al., 1997), survival of fry (Norberg-king,

1989; Barakat, 2004), reducing the development and survival especially at the beginning of

exogenous feeding (Stominska and Jezierska, 2000) and inducing degenerative changes in

muscles (El-Nemaki and Abuzinadah, 2003). In addition to the detrimental effects on biota of

such pollutants’ exposed habitats, consumption of the contaminated organisms by humans is

alarming too. As it is well known that recalcitrant pollutants become concentrated as they

move from lower to higher trophic levels. This biomagnification unfortunately affects

humans adversely who generally represent higher trophic level.

On one hand, Pakistan is among water stressed countries facing water scarcity (World

Bank, 2005) and have shortage of 40 million acre feet (MAF) of water that will increase over

151 MAF by the year 2025 (Mirjat and Chandio, 2001). This scarcity of water needs

protection and improvement of existing freshwater resources. On the other hand,

indiscriminate urbanization and industrialization in developing countries are putting the

aquatic resources under threat of degradation. Pakistan is also among those developing

countries where aquatic resources are facing the severe degradation from industrial,

municipal and agriculture sources (UNIDO, 2000). With rapid increase in urbanization and


5

industrialization in Pakistan, the water pollution is a very serious issue as the industrial and

domestic effluents containing bulk quantities of toxic heavy metals, organic pollutants and

bacterial loads are being continuously discharged into the rivers and streams of the province

Punjab. About 80 % of urban and industrial growth is restricted to major cities of Pakistan

viz., Karachi, Lahore, Faisalabad, Hyderabad, Multan, Sialkot, Gujrawala, Rawalpindi,

Peshawar and Kasur (Aftab et al., 2000). The polluted water has been presenting serious

threats to aquatic life and breeding grounds of indigenous fish species which are near to

extinction in the rivers of Punjab. Damage to soil and crops in the rivers’ irrigated areas is

obvious. Further, the livestock consuming such contaminated water has also been adversely

affected. (Javed and Mahmood, 2000a; Javed, 2005).

Heavy discharge of metals and their compounds has adversely affected fishes of the

river system of Pakistan in general and of the province Punjab in particular (Javed, 2005).

The river Ravi originates in the mid Himalayas of Himachal Prasesh, India from the glaciers

from where it follows the north western path in India. The river Ravi is trans-boundary river

entering Pathankot at Chaundh and forms a boundary between India and the state of Jammu

and Kashmir for 23 miles and then enters in Pakistan through the village Tadyal, Kot Naina,

Shakargarh Tehsil of Sialkot. Just after entering in Pakistan, the Ujh river joins it. River Ravi

while flowing through Lahore (the second largest city of Pakistan) becomes just like a

wastewater carrier with high discharge variation of 270-81000 ft3/sec. The flow in river Ravi

is highly variable and seasonal variation in waste water is less as compared to river water

fluctuations which results in higher concentration of contaminants during low flow period of

the river. Most of the waste water is discharged in the river between start of the Lahore city

and a downstream point named Balloki headworks (Ahmad and Ali, 1998). River Ravi

receives untreated domestic and industrial wastewaters from the city of Lahore through a

number of discharge points. There are more than seven pumping stations along the river


6

discharging the municipal and scattered small industrial sewages of Lahore city into the river.

Further, there are two drains namely Hudiara and Deg Nullah which dispose off industrial

effluents into the river Ravi. Hudiara drain is one of the major sources of pollution for the

river. The drain enters in Pakistan loaded with pollutants of around 100 industries located

adjacent to its 55 Km Indian side. Then more than 112 industries discharge effluents into the

drain as it travels 63 Km through the Punjab, Pakistan. Deg Nullah carries the effluents from

Kala Shah Kaku industrial complex, which has more than 149 industrial units. Some

industries on Lahore-Sheikhupura road also discharge their wastewater into the drain (Saeed

and Bahzad, 2006). The untreated industrial effluents are adding reasonable amount of toxic

metals into the river Ravi (Rauf et al., 2009b). Pollution in river Ravi is the highest of all the

rivers in Pakistan. Consequently the river fauna, especially the fishes have been drastically

affected (Jabeen et al., 2012). Some incipient work has indicated heavy metal deposition in

the fish. However, information regarding the effects of such pollutants on the growth,

biochemical parameters including fatty acid composition and bioaccumulation pattern of

heavy metals in the fishes of the subject river are lacking. Different studies have shown that

presence of those bacteria which are not part of normal flora of the gastrointestinal tract of

fish is a direct result of association of fish with the degree of contamination in water. Such

bacteria can survive and multiply in fish gastrointestinal tract with residency lasting from a

few days to a few weeks (Gibbon, 1934; Geldreich and Clarke, 1966; Reasoner, 1974).

Possible consequences of this association may be either infection of fish or fish acting as a

source of diseases in fish consumers or handlers (Pal and Dasgupta, 1992).

On the other hand thriving of heavy metals resistant bacteria might had been involved

in metals’ detoxification processes and affecting growth of the fishes. Importance of

protection, management and restoration of aquatic resources for ensuring sustainable

domestic, agricultural and industrial purposes has been realized all over the world (Nakamura


7

et al., 2005). Effluents’ metals removing methods such as precipitation, chemical reduction

or oxidation, ion exchange filtration, electrochemical treatment, membrane technologies,

reverse osmosis and evaporation recovery (Ahluwalia and Goyal, 2007) may be ineffective

or expensive especially when the metal concentrations are in the range of 1-100 mg/l

(Nourbakhsh et al., 1994). Metal resistant bacteria found in fish develop the capabilities to

protect themselves from heavy metals by various methods such as uptake, adsorption,

oxidation, reduction, methylation and their potential bioremediational use has been

documented throughout the world (Toroglu et al., 2009; Shakoori et al., 2010; Kumar et al.,

2011; Wei and Wee., 2011). It is very alarming that general local public considers riverine

fish more health promoting. Owing to this falsification, river caught fish is sold at higher

price as compared to cultured fish. Albeit the consumers are taking meat bound pollutants

such as heavy metals and other recalcitrant pollutants.

The present study was designed, keeping in view environmental problems of river

Ravi, to study effects of heavy metals’ pollutants and enteric bacterial load on nutritionally

and economically important three fish species. Effects of bacterial and heavy metals

pollutants were assessed by studying river captured fish from specified up and downstream

locations. The water, sediment and fish of given locations were investigated for various

ecological parameters. Biogenic uptake and localization of heavy metals and prevalence of

metal resistant bacteria in the gut contents of the fishes as function of urban up and

downstream locations are being reported first time for the subject river. For this purpose,

samplings of representative fishes; thaila, Catla catla (surface feeder); rohu, Labeo rohita

(column feeder) and mori, Cirrinus marigala (bottom feeder) from four locations viz.,

Siphon (upstream), Shahdara, Sundar and Baloki (downstream) were accomplished during

low (Nov.- Dec. 2009) and high (Sep.- Ocb. 2010) flow seasons of the river Ravi. To assess

physico-chemical parameters, levels of various heavy metals concentrations in river water


8

and bed sediment and the associated effects on growth and metals bioaccumulation in the

fishes of river Ravi during its passage from the city Lahore and to report isolation of Cu, Pb,

Hg and Cr resistant bacteria from gut contents of the fishes, main objectives of the present

investigation were as follows:.

To record biometric data of the sampled fishes.

To determine the proximate analysis (moisture, ash, crude protein, fat and

carbohydrate content) of fishes’ muscles.

To determine total carbohydrates, total protein, soluble protein, cholesterol, total

lipid, DNA and RNA contents of the muscle of sampled fishes, photometrically.

To isolate the enteric Cu, Pb, Cr and Hg resistant bacteria of the different fish species.

To identify representative bacterial isolates by their 16S rDNA gene sequencing.

To determine the heavy metals (Cd, Cr, Cu, Pb, Zn, Fe, Mn, Hg, Ni) bioaccumulation

in skin, gills, eyes, liver, heart, kidney, scales and intestine of the sampled fishes by

atomic absorption spectrophotometer.

To determine the macro elements (Na, K, Ca, Mg, P) in muscles of the sampled fishes

by ICP-OCS.

To determine the heavy metals (Cd, Cr, Cu, Pb, Zn, Mn, Fe, Ni) in muscles of the

sampled fish species by Inductively Coupled Plasma Optical Emission Spectroscopy

(ICP-OES).

To determine the fatty acids composition of muscles of sampled fish species by Gas

chromatography.

In short, the present study describes effects of heavy metal pollutants on the riverine

fishes. The heavy metals carrying and transferring nature of the fishes in conjunction to

Lahore urban pollutants loads to the river are mentioned with emphasis on up and

downstream locations. Considerable metals’ resistant bacterial diversity isolated and


9

preserved during the course of this study is likely to prove valuable in future for

rehabilitating biota of the river Ravi following the development of effluents’ treatment

bioremediation processes. Outcomes of this study further the understandings required for

rehabilitation of drastically affected aquatic fauna and the river Ravi itself.

Chapter 2 Review of Literature

10

REVIEW OF LITERATURE

Pollution refers to harmful contaminants introduced into an environment by humans.

Water pollution results by release of different wastes into aquatic system including those

coming through industrial and domestic drainage systems. Depending upon the amount and

nature of the pollutants and of course the rate of water turnover, they may damage the aquatic

biota immediately or exert harmful effects after long term exposure. Rivers have served the

mankind with water, for drinking and agricultural practices, food and soil fertilization. In

fact, they have been decisive for shaping the human civilizations. Thus many oldest

civilizations had originated along rivers’ banks. Highly populated cities then started to dump

their wastes directly into these ‘blood vessels’ and industrial development poisoned them

further. Consequently, the developing countries’ rivers got polluted while saluting bigger

cities on their ways. The urban pollutants’ loads have rendered the rivers highly unsuitable

for the natural biota. Pollutants are of diverse kinds while owing to the frame of this study

addressing heavy metals and bacterial contaminations with special reference to their effects

of riverine fishes the present review is an account of the following subtopics:

2.1. Heavy metals’ contamination of freshwater resources

2.2 Effects of metal pollution on fish

2.3. Human health implications of metals’ exposed fish:

2.4 Enteric Bacterial loads of fish from polluted water

2.5 Remedial role of fish gut bacteria against metals’ ingestion


11

2.6 Situation of the river Ravi in the study area

2.1. Heavy metals’ contamination of freshwater resources:

Natural aquatic systems may extensively be contaminated with heavy metals released

from domestic, industrial and other man made activities. Heavy metals are characterized

with specific gravity of > 5 and represent severe pollutants of industrial origin which along

with other urban and rural household wastes are discharged into aquatic systems. Many of

such pollutants are toxic to aquatic life (Wicklund-Glynn, 1991; Velez and Montoro, 1998;

Ouyang et al., 2005). There are numerous sources of domestic and industrial effluents that

lead to heavy metals’ enrichment of water, sediments and fish species in rivers. Major

contributors to heavy metal pollution are tanneries, food, textile, pottery, electroplating,

metal finishing, mining, photographic, dyeing, printing, ceramic, beverages, paint, chemical

and pharmaceutical industries of a given region (Azzaoui et al., 2002; Vutukuru, 2003).

Metals are non-biodegradable and once discharged into water bodies, they can either

be adsorbed and/or accumulate in aquatic organisms and sediment in mud. Heavy metals in

river bed sediments can be used as an evidence for anthropogenic impact on aquatic

ecosystem. The sediment may contain higher concentrations of minerals and heavy metals

than water (Ali et al., 2010). Concentrations of heavy metals vary in water and sediment

depending upon particular metals or salts thereof, nature of accompanying substances and

physico-chemical attributers of water and sediment themselves. Sediment may adsorb

concentration of metals significantly higher than those found in water, where even the metals

may be well below the limit of detection. Chale (2002) reported that in Lake Tanganyika, the

levels of heavy metals in water were low, while the concentration of copper, lead, zinc and

cadmium in inshore sediments were much higher than in offshore sediments. He et al. (1998)

investigated that water and sediment contamination due to effluent discharge in river Le An,

China affected aquatic ecosystem. Wang et al. (2005) reported that mobility, toxicity and


12

bioavailability of metals (Cd, Cu, Co, Ni, Mn, Pb) in sediment were not only dependent on

their concentration but also on physico-chemical characteristics of water in which they occur.

Physico-chemical parameters adversely affect the heavy metals’ content in sediment.

Widianarko et al. (2000) computed relationship between metal contaminations in aquatic

biota and sediments with particular reference to physico - chemical properties and reported

that pH of sediment showed significant correlation with pH of water. In river Mooi, alkalinity

and hardness increased the toxicity of metals in sediments. Lowering the pH (below 6.5)

released large amounts of toxic metals from sediments to water (Van Aardt and Erdmann,

2004). Aquatic organisms have tendency to accumulate heavy metals from surrounding

water, sediments and food (Labonne et al., 2001; Goodwin et al., 2003). Toxicities of Cd, Cr,

Cu, Fe, Pb, Zn, Mn and Ni have been correlated with temporal variations due to variability in

water discharge and suspending solid load (Jain et al., 2005). Once the heavy metals enter in

the aquatic medium, bioaccumulation may occur in fish tissues by means of biosorption and

metabolic processes (Carpene et al., 1990; Wicklund-Glynn, 1991). Bioaccumulation usually

occurs slowly in aquatic medium and subtle physiological effects go unnoticed until changes

in population structure, as a result of, at least in part, altered reproduction become apparent.

Studies from laboratory and the field experiments have revealed that heavy metals’

bioaccumulation is mainly dependent upon metals’ concentration in ambient water and

exposure period. While feeding habits, metabolism rate, age, length and weight of the

exposed organisms, environmental conditions, physico-chemical characteristics of water and

season do influence the metals uptake to varying degrees (Kargin, 1996; Jezierska and

Witeska, 2001; Canli and Atli, 2003; Papagiannis et al., 2004; Dural et al., 2007; Tawari-

Fufeyin and Ekaye, 2007). Concentrations of heavy metals are generally higher in the

organisms than in water. pH and total hardness of water have a vast influence on the metal

toxicity/bioaccumulation in fish (Erickson et al., 1996, 1998).


13

2.2 Effects of metal pollution on fish:

Effects of pollutants in water bodies can be studied through biological and chemical

analyses. Chemical features of water provide quantitative data of the important pollutants.

Whereas biological analyses give direct information about the bioavailability, nature/level of

pollutants, their detrimental effects on living organisms and possibilities of controlling the

deteriorative agents. Koukal et al. (2004), for example, reported loss of aquatic life

associated with poor water quality in term of unsuitable dissolved oxygen, ammonia, and

turbidity contents and metal toxicity in polluted rivers Fez and Sebou, Morocco. Heavy

metals’ contaminations exert devastating effects on the ecological balance of recipient

environment and diversity of aquatic organisms (Vosyliene and Jankaite, 2006; Farombi et

al., 2007). Physiological, metabolic and even structural systems of organisms can be

impaired when exposed to various metals’ pollutants discharged in water bodies (Javed,

2003; Das et al., 2012; Singh et al., 2012). Heavy metals have received considerable

attention of researchers due to their accumulation and toxicity in biota of aquatic ecosystems

(Sinha et al., 2002; Staniskiene et al., 2006; Vinodhini and Narayanan, 2008). Fish are often

at the top of aquatic food chains and thus may concentrate large amounts of some metals

from the water leading to their biomagnifications (Mansour and Sidky, 2002; Mendil and

Uluozlo, 2007; Fernandes et al., 2007). Such pollutants may enter fish bodies in three

possible ways; through the topical absorption by the body surface, gills and ingestion of

contaminated food (Pourang, 1995; Vincent et al., 2002; Sarnowski, 2003). Bioaccumulation

of metals can only take place if the rate of uptake by an organism exceeds the rate of

elimination (Specie and Hamelink, 1985). When concentration levels of heavy metals

increase beyond the levels required by the organism either due to their excess amounts or

longer persistent in water, they act in acute and chronic toxic manners, respectively (Gulfaraz

et al., 2001; Pandey et al., 2005; Murugan et al., 2008). Water pollution with heavy metals or


14

their metabolites has been reported to exert deleterious effects by inhibiting growth rate of

fish (Jezierska and Witeska, 2001; Hayat et al., 2007), affecting negatively gonads’

maturation and reproduction (Farag et al., 1995; El-Boray et al., 2003), changing spawning

behaviour, duration and number of eggs per spawn (Barakat, 2004), affecting adversely the

egg and embryo viability (Speranza et al., 1997), survival of fry (Norberg-king, 1989;

Barakat, 2004), reducing the development and fish survival, especially at the beginning of

exogenous feeding (Stominska and Jezierska, 2000) and inducing degenerative changes in

muscles (El-Nemaki and Abuzinadah, 2003). Heavy metals may cause, in general, cytotoxic,

mutagenic and carcinogenic effects in animals (More et al., 2003). Municipal and industrial

toxicants, such as metals pose serious risk to many fish species and are regarded to be

cytotoxic, mutagenic and carcinogenic (More et al., 2003).

As has been described above too, metals affect fish morphology, growth, feeding,

biochemical processes, and physiology including reproduction (Kuz’mina, 2011; Yousafzai

and Shakoori, 2011) and cause detrimental effects on health and wellbeing of the animal.

(Vosyliene and Jankaite, 2006). Fish growth has been considered as biomarker for riverine

pollution because it integrates majority of the detrimental effects. Kerambrun et al. (2011)

reported the field situation about the reduction in growth and energetic status of juvenile fish

Scophthalmus maximus (turbot) and referred their decreased over-winter survival in

contaminated nursery ground. In fish, the weight is considered to be function of length

(Weatherley and Gill, 1987). If the fish retains the same shape and its specific gravity

remains unchanged during lifetime, it is growing isometrically and the value of exponent “b”

would be exactly 3.0 (Ricker, 1975). A value of the parameter significantly larger or smaller

than 3.0 indicates allometric growth. A value less than 3.0 shows that the fish becomes

lighter (negative allometric) while greater than 3.0 indicates that the fish becomes heavier

(positive allometric) for a particular length (Wootton, 1998). The specific gravity of the flesh


15

of the fish is known to undergo changes but Le Cren (1951) indicated that the density of the

fish might be maintained in the surrounding water by means of swim bladder. The change in

weight, therefore, is due to changes in form and not in specific gravity. Most fishes do not

conform with the cube law because they change their shape with growth (Martin, 1949; Ali et

al., 2000). The exponent “b” may have value significantly lower or higher than 3.0. The

value of “b” may vary with feeding (Le Cren, 1951), state of maturity (Frost, 1945), sex (Hile

and Jobes, 1940) and further more between different populations of a species (Hile, 1936;

Jhingran, 1952) indicating taxonomic differences in small populations.

Understanding of growth profile(s) of fish is very important for predictable fishery

management. The growth curve generally resumes a sigmoid shape, which may vary for the

same fish at different seasons or for the same fish from different localities. Metals stressed

fish reduce feeding uptake in start for short toxicant exposure (Kuz’mina, 2011) but feed

uptake may increase when exposure is prolonged. Reduced food consumption and

assimilation have been correlated with catabolic processes exceeding the anabolic and

resulting to reduce growth of the exposed fish species, Cirrhinus mrigala, Catla catla and

Labeo rohita (Hussain et al., 2010, 2011). Various authors have reported detrimental effects

of heavy metals on fishes’ growth. For example, Paul and Atchison (1979) described

measurable growth difference in yellow perch (Perca flavescens) showing significant

correlation with cadmium levels. James et al. (2003) described dose dependent reductions in

the rate of food intake and conversion efficiency, gonad weight, fertility in an ornamental

fish, Xiphophorus helleri following exposure to sublethal concentration of copper. Likewise,

James et al. (2008) reported that copper accumulation caused significant reduction in specific

growth rate and reproductive performance of Carassius auratus and Xiphophorus helleri.

Regarding the effects of lead, Naz et al. (2008) have reported that Catla catla, Labeo rohita,


16

Cirrhinus mrigala showed significantly lower weights, fork and total lengths following

exposure to sublethal levels of Pb.

Bioaccumulations of metals in different fish organs vary from species to species and

are responsive of different conditions (Andreji et al., 2006; Yilmaz, 2006). Concentrations of

metals in skin and gills reflect their levels found in water where the fish lives. Whereas

concentrations in liver and kidney represent storage/excrection of metals (Romeo et al.,

1999). Jabeen and Chaudhry (2010b) reported highest metals’ (Zn, Pb, Mn, Cr) load on gills

followed by liver, skin and muscles. Allen-Gill and Martynov (1995) described that low

levels of copper and zinc in fish muscles reflected low levels of the heavy metals in food and

binding proteins in the tissue. Canli and Kalay (1998) determined the concentrations of

cadmium and chromium in the gills, liver and muscles of Cyprinus carpio, Barbus capito and

Chondrostoma regium caught from the Seyhan river system. Liver and gills showed higher

metal concentrations than muscle tissue. Gbem et al. (2001) exposed Clarias gariepinus to

tannery effluent and found dose and time dependent accumulation of lead, copper and zinc.

They found higher levels of the metals in the liver followed by gills and gut. Akhtar et al.

(2005) revealed high bioaccumulation of metals (Cd, Cr, Cu, Fe and Zn) in fishes, Cyprinus

carpio, Labeo calbaso, Labeo dero and Puntius sophore netted from Korang and Sohan river,

Pakistan. Ploetz et al. (2007) also reported highest levels of cadmium, lead, copper, zinc and

iron in livers of the fishes Sparus aurata, Dicentrachus labrax, Mugil cephalus and

Scomberomorus cavalla. Likewise, Yilmaz et al. (2007) reported maximum and minimum

accumulations of cadmium, cobult and copper in the livers and muscles tissues, respectively

of Leuciscus cephalus and Lepornis gibbosus. Higher levels of heavy metals such as lead and

chromium in liver relative to other tissues has been attributed to their affinity and strong

coordination with metallothionein protein (Ikem et al., 2003). Recently, comparable results


17

have also been reported by Rauf et al. (2009a) showing highest tendency of fish liver for

accumulating cadmium and chromium.

All heavy metals are harmful metallic pollutants and their bioaccumulation tendencies

appear a function of differences in species, gender and environmental determinants. Different

organs of fish species and different metals show different orders of metal bioaccumulation. In

Labeo rohita accumulation of heavy metals has been reported in a sequence of liver > kidney

> gills > muscles while for Ctenopharyngodon idella, it was gills > liver > kidney > muscle

(Malik et al., 2010). Yousafzai and Shakoori (2008) reported the order of metal accumulation

in gills of Tor putitora from river Indus as Zn > Pb > Ni > Cu > Cr. The accumulation pattern

of heavy metals followed a sequence of Fe > Al >Mn > As >Ni >Si > Cd in Cepoeta tinca

and Capoeta capoeta collected from Kizilirmak and Delice rivers, Turkey (Akbulut and

Tuncer, 2011). The order of bioaccumulation was Zn > Cu > Pb > Ni > Cr in liver of Tor

putitora from river Indus (Yausafzai et al., 2009a). Alhashemi et al. (2011) reported the

accumulation of metals in female Barbus grypus and Barbus sharpeyi were higher than their

respective metals.

Metal bioaccumulation in fish also depends upon their trophic level. Yousafzai et al.

(2010) suggested that omnivorous fish (Labeo dyocheilus) may bioaccumulate more heavy

metals than the carnivorous fish (Wallago attu) netted from Indus river, Pakistan. While have

recently documented that the carnivorous (Rita rita, Mystus sperata and Wallago attu) fish

showed higher accumulation of metals than the herbivorous (Catla catla, Labeo rohita and

Cirrhina mrigala) fish species (Jabeen et al., 2012). The differing conclusions of the above

two studies in terms of omnivorous and carnivous fish species’ differences for the heavy

metals’ bioaccumulation levels might be attributed to the differences of the trophic level in

the food chain, locations and species. In fact, heavy metals’ concentration in aquatic medium

and the inhabitant organisms depends on site as well as season. The spatial and temporal


18

variation were studied by Ahmad et al. (2010) who reported that Pb, Cd, Ni, Cu and Cr

varied seasonally with highest Pb concentrations in Gudusia chapra during monsoon, in

contrast, Cd concentrations were lowest in Cirrhinus riba during post monsoon in Buriganga

river, Bangladesh. Kumar et al (2011) reported higher concentrations of heavy metals in pre

monsoon period than monsoon season in river Kerala, India. In short, varying levels of heavy

metals’ concentrations and their bioaccumulation of freshwater fish species have been

attributed to differences in metal concentrations, chemical characteristics of water, ecological

needs, metabolism, feeding patterns and seasonal variations (Javed and Hayat, 1998;

Chattopadhyay et al., 2002; Papagiannis et al., 2004; Vinodhini and Narayanan, 2008).

2.3. Human health implications of metals’ exposed fish:

Freshwater fish constitute a great food potential for human population. Fish products

comprise an important ingredient in the human diet to enhance the nutritional requirements

of the population. Fish is widely used throughout the world because it has low saturated fat

contents and provides many benefits such as lowering blood cholesterol level. Fish contains

significant amounts of essential amino acids, especially lysine which is low in cereals.

Therefore, fish protein can be used to complement the important amino acids and also overall

protein quality of a mixed diet (FAO, 2005). Fishes are not merely a rich source of high

quality of protein, minerals and essential vitamins but they also provide nutritionally valuable

lipids and fatty acids. In short, fishes are the richest source of an essentially healthy diet.

Therefore it is very important to know the impacts of water pollution on the health and

growth of these animals. Changes in aquatic medium cause several physiological and

compositional changes in fish. Industrial and municipal effluents are the main culprits for

undesirable changes in water quality, metabolism, biochemistry and physiology of inhabitant

fish (Wilson and Taylor, 1993; Fang et al., 2012; Navaraj and Yasmin, 2012; Tetreault et al.,

2012).


19

Alterations in biochemical composition of muscles as response of pollutants’ stress

have been reported by researchers (Bhathar et al., 2004; Yausafzai and Shakoori, 2009b).

Biochemical profiles are commonly used as stress indicators. Biological changes in fish

related to exposure of contaminants are called “Biomarker” (Peakall, 1994). Among

prominent biomarkers, the physiological variables such as serum levels of different

metabolities (Adams et al., 1990; Di Giulio et al., 1995), ions (Martinez and Souza, 2002),

levels of hormones (Hedayati and Safahieh, 2011) and biochemical variables (De la Tore et

al., 2000; Yousafzai and Shakoori, 2009b) have been well documented. Investigation of

biochemical parameters can be especially useful to help identify target organ of toxicity as

well as general health status of organism and has been advocated to present early warning of

potentially damaging changes in stressed organisms (Jacobson-Kram and Keller, 2001).

Different studies have revealed that heavy metals alter physiological activities and

biochemical parameters of different tissues of fishes (Basa and Usha Rani, 2003; Garg et al.,

2009; Yousafzai and Shakoori, 2009b). Previous studies have shown that certain metals can

cause either increases or decreases in the levels of protein, glucose, cholesterol, lipids and

enzyme activity depending on metal type, fish species, water quality and length of exposure

(Gopal et al., 1997; Vaglio and Landriscina, 1999; Monteiro et al., 2005). Healthy animals

exposed directly to potentially contaminated environments have frequently been used as field

models. (Parrot et al., 2000; Olsen et al., 2001; Pyle et al., 2001; Camargo and Martinez,

2006). Most biochemical defences respond to cellular injury by elevation in the amounts of

defences through self-regulating signal transduction mechanisms (Safahieh et al., 2010).

Firat and Kargm (2010) studied the serum biochemistry of Nile tilapia (Oreochromis

niloticus) exposed to the individual and combined heavy metals (Zn and Cd) and found

decrease in cholesterol levels. Heavy metals pollutants do disturb metabolic rhythms of

exposed organisms and cause drastic changes in biochemical parameters as metals can bind


20

with amino acid and SH groups of proteins and therefore, enzymes’ activities may be

inhibited due to active site being either denatured or distorted (Di Giulio et al., 1993, 1995).

Sobha et al. (2007) studied impact of short term acute metal toxicity on biochemical

constituents in freshwater fish, Catla catla and found significantly elevated levels of glucose,

while decreases in glycogen, total protein, lipid and free amino acids suggesting that the fish

exposed to heavy metal effluent would not had the expected nutritive value.

In the last few decades, there have been several outbreaks of metals’ intoxification.

The termed “Minamata disease”, took place in Japan in the 1950s. The unnoticed existence

of methylmercury in sea fish was mysterious at first, since the source was inorganic mercury

compound discharged into the Bay by the Minamata chemical company (Japan). The missing

link between inorganic mercury in Bay water and methylmercury in sea fish was bridged

only after extensive research since the 1950s addressing the bioaccumulation of heavy metals

in fish from surrounding environment. There have been many cases of poisonings caused by

Minamata disease. One study estimated about 3300 suspected cases and about 1000 human

deaths. This was the first known case where the natural bioaccumulation of toxic material

(methylmercury) in fish killed about hundreds of people and genetically damaged a large

population. Genetic defects were observed in babies whose mothers had consumed the

contaminated fish from the Bay. The Minamata incident was followed by a more tragic

report of Hg-poisoning from Iraq in 1972 where 450 villagers died after eating wheat, which

had been dusted with mercury-containing pesticides. These two tragic events boosted the

awareness of heavy metals as pollutants (Tsubaki et al., 1978; Kudo and Miyahara, 1991;

Rani et al., 2012).

In spite of detrimental effects of toxicants in fish consumers, fish meat is considered

a rich source of omega (ω)3 and omega (ω)6 long chain polyunsaturated fatty acids (PUFA)

which are cardio-protective (Sanderson et al., 2002), anti-atherosclerotic, antithrombotic and


21

anti-arrythmitic (Givens et al., 2006). The main PUFA like arachidonic (C: 20: 4 ω6) acid

(AA), eicosapentaenoic acid (EPA) (C: 20:5 ω3) and docosahexaenoic acid (DHA) (C: 22: 6

ω6) are not synthesised in human body but their inclusion in human body is essential. Thus

they must be supplied through diet (Holub and Holub, 2004; Gonza’lez et al., 2006;

Kolanowski and Laufenberg, 2006). Studies on human newborns and non-human primates

showed that AA is a precusor of important biological products like epoxides iso-prostanes,

anandamide and AA- ethanolamide of prostaglandins (Galli and Marangoni, 1997). Whereas

DHA is essential for normal functional development of brain and retina where it has crucial

role in maintaining the structure and function of the excitable membranes of these tissues,

particularly in premature infants. It is found in the phosphoglycerides of cellular membranes

in high concentration (Montano et al., 2001). EPA are precursors for the eicosanoids which

have a wide range roles in physiological actions like cardiovascular tone, renal and neural

function, reproduction, blood clotting, inflammation and immune responses (Connor,

2000).Standard recommendation for daily dietary intake of DHA/EPA are 0.5 g for infants,

and an average of 1g/day for adults and patients (Kris-Etherton et al., 2001). Therefore, these

PUFA are considered beneficial for human health and dictate the need of consumption of fish

and its products (Sargent, 1997). Water salinity has been demonstrated to have vital role in

fatty acid compositions particularly PUFA and ω 3/ ω6 ratio was much lower in fish living in

freshwater than salt water (Steffens, 1997). The ω6 and ω3 fatty acid contents are higher in

riverine fish (Labeo rohita) than in farmed cultured freshwater fish (Sharma et al., 2010).

Nutritionists suggested the ratio of ω6/ ω3 should be 5 for daily dietary intake and the

addition of ω3 could prevent the concerned diseases (Moreira et al., 2001). The variations in

fatty acids composition in freshwater and marine fish species should not only be considered

with respect to species habitat but also based on their natural diet, especially whether a

species is herbivorous, carnivorous or omnivorous (Sargent et al., 1995). Apart from that,


22

fatty acid composition of different individuals of the same species can vary because of

differences in their diet, size, age, gender, environmental conditions and geographical

locations to a certain extent (Inhamuns and Franco, 2008).Although PUFA composition may

vary among different species of both sea and freshwater fishes (Rahman et al., 1995) but it is

found in reasonable amounts as compared to beef and chicken (Calder, 2004). Furthermore,

fatty acid contents may also vary in fish species on seasonal basis. Kandemir and Polat

(2007) reported the seasonal variation of fatty acid in muscle and liver of fish, Oncorhynchus

mykiss (rainbow trout) reared in Derbent Dam lake. The seasonal change in saturated and

unsaturated fatty acid contents also appeared to be area dependent. Water quality influence

the fatty acid composition of muscles and fish needs polyunsaturated fatty acids to provide

tolerance against seasonal variations (Lee et al., 1986; Rasoarahona et al., 2005). Toxic

heavy metals in fish can damage the positive effects of the ω3 fatty acids present in fish and

their beneficial effects on heart disease risk (Chan and Egeland, 2004).This may be

manifested through reductions of the polyunsaturated fatty acids in the flash of pollutants

exposed fish. As for example, Konar et al. (2010) documented significant decrease in PUFA

after exposure of cadmium compared to control in rainbow trout (Oncorhynchus mykiss).

While, Choi et al. (2002) associated earlier reduction in PUFA with pollutant induction of

prostaglandin biosynthesis pathway. Likewise, decrease in PUFA after chromium treatment

compared to control group has also been reported by Coban and Yilmaz (2011) in Cyprinus

carpio (common carp).

Heavy metals may affect the organisms directly by accumulating in their organs or

indirectly threaten the health of many species at top of food chain especially birds and

humans (Unlu and Gumgum, 1993; Wright and Mason, 1999). Metal bioaccumulation

impacts are largely attributed to differences in uptake for various metals in different fish

species. Accumulation of heavy metals in aquatic organisms can pose a long lasting effect on


23

biogeochemical cycling in the ecosphere. Due to insidious nature of metal accumulation it

would be too late to apply preventive measures to reduce the pollutants effects (Kumar and

Mathur, 1991). These information necessitate prompt efforts for saving the water resources

from the metals’ toxicants as well as other pollutants including microbial contaminations.

2.4 Enteric Bacterial loads of fish from polluted water:

Both limnetic and lentic fresh water resources harbour a variety of microorganisms

reflective of natural habitats as well as anthropogenic intrusions. Aquatic microbial

populations’ dynamics do experience great fluctuations while respecting to variations in

different environmental determinants. Whereas the microbial populations within the digestive

tract of fish are dense and much higher than those in the surrounding water indicating that the

digestive tract provides favourable ecological niches for these organisms. (Cahill, 1990;

Mickeniene and Syyokiene, 2001). The gastrointestinal microflora of fish appears to be

simpler than that of endotherms, the predominant bacterial genera/species isolated from most

fish guts have been aerobes and facultative anaerobes (Cahill, 1990; Sakata, 1990). Typical

numbers of bacterial pollutions in fish intestines have been reported as 108

per gram aerobic

and facultative anaerobic heterotrophic bacteria and approximately 105 per gram anaerobic

bacteria (Sugita et al., 1988, 1991). The bacterial flora of gastrointestinal tract, in general,

represent a very important and diversified enzymatic potential (Bairagi et al., 2002; Saha et

al., 2006). Mondal et al. (2008) have described microbial source of digestive enzymes such

as amylases, cellulases and proteases in various fresh water fishes and commented that the

enzymes producing bacteria isolated from the digestive tract can be used as probiotic while

formulating aqua feeds. Similar results for enzymes producing bacteria in seven freshwater

teleosts of different feeding habits, namely Labeo rohita (rohu); Catla catla (Thaila);

Cirrhinus mrigala (Mori); Labeo bata (bata); Labeo calbasu (orange-fin labeo);

Oreochromis niloticus (Nile tilapia); and Anabas testudineus (climbing perch) with emphasis


24

of distinct microbial sources of digestive enzymes apart from the endogenous sources in fish

digestive tracts have been reported by Mondal et al. (2008). Enzyme producing bacteria in

fish intestine may be correlated with their feeding habit. Being an herbivorous fish species,

occurrence of protease, amylase and cellulase producing bacterial population is noteworthy

in the digestive tract of Labeo rohita (rohu); Catla catla (thaila) and Cirrhinus mrigala

(mori). Several studies have suggested that intestinal bacteria may be nutritionally beneficial

to fish (Hamid et al., 1979; Campbell and Buswell, 1983; MacDonald, et al., 1986) or that

they participate in preventing colonization of fish intestine by pathogenic bacteria

(Westerdahl et al., 1991; Olsson et al., 1992). The intestinal microflora of freshwater and sea

water fish species harbors different microorganisms comprising an obligatory part of all the

trophic relations (Yoshimizu et al., 1976; Sakata, 1990) and vary with life stage, diet and

environment (Nayak, 2010; Tapia-Paniagua et al., 2010; Dhanasiri et al., 2011).

Apart from symbiotic microorganisms, referred to above, in the fishes’ guts, bacterial

populations reflecting their anthropogenic origin might be isolated from the gut contents.

Demonstration of presence of specific pollutant resist bacteria in the gut contents of fish may

indicate contamination of the concerned aquatic habitats with the specific pollutants of

industrial origins. Microorganisms exhibit, in general, sensitivity to toxic substances while

many microorganisms resist some of the heavy metals at high toxic levels. The resistance

may be mediated by genetic factors, binding by cell surface slime and/or oxidative

detoxification and production of chelating substances (Gadd and White, 1993; Mickeniene

and Syyokiene, 2001). Animal sensitive to given toxic substances, depending upon their

availability may ingest/feed on resistant microorganisms to the particular toxicants. Such

organisms may recruit the pollutants resistant microbes in the gut for in entero

detoxification/remediation of the substances came there along with the food. Conversely,

toxic substances may lead to death of sensitive but essential microorganisms in digestive


25

tract of animals such animals may die from a disorder of the activity of the digestive system

due to the deaths of symbiotic microbes at concentrations of the pollutants which may be

declared sub-lethal otherwise (Pokarzlewskii, 1981; Mickeniene and Syyokiene, 2001).

Heavy metals generally exert inhibitory actions on microorganisms by blocking essential

functional groups, displacing essential metal ions or modifying the active conformations of

biological molecules (Wood and Wang, 1983; Doelman et al., 1994). Nevertheless, it is clear

that elevated levels of heavy metals can alter the qualitative as well as the quantitative

structure of a microbial community (Duxbury, 1981; Hiroki, 1994). Presence of heavy metals

resistant and the pollutants remedifying bacteria is not uncommon in industrially polluted

soils and waters. Large number of studies have reported them and suggested possible and

demonstrated too their role in bioremediation (Pattanapipitpaisal et al., 2001; Vitti et al.,

2003; Bhakta et al., 2012). The influence of environmental factors on the diversity of fish gut

bacterial communities is poorly known. Several studies have tended to demonstrate that

bacterial functional diversity in natural systems may be driven by environmental conditions

(Horner-Devine et al., 2004), nutrient availability (Leflaive et al., 2008), pollutants’ stress

(Ramussen and Sorensen, 2001) and seasons (Sala et al., 2006, 2008).

2.5. Remedial role of fish gut bacteria against metals’ ingestion:

Removal of heavy metal ions from industrial and domestic polluted waters may be

achieved through a variety of ways centered, in general, on the chemical and physical nature

of these pollutants. Such procedures include precipitation, ion exchange, chemical extraction,

electrolytic techniques, leaching hydrolysis, excavation and land filling (Baleen and Kemila,

1997). Use of conventional chemical methods for treating metal bearing effluents may not be

economically feasible. While, possibility of employing biological treatment or

bioremediation techniques as alternate methods for the treatment of contaminated waters has

been advocated by biologist as quite feasible. Among the microorganisms, bacteria are


26

generally the first category to be exposed to heavy metals present in the environment. In

addition to enhancing food conversion efficiency the gut resident microorganisms might be

of bioremediational potential against heavy metals’ ingestion (White et al., 1997). Bacteria

exhibit a number of metabolism dependent and independent mechanisms for tolerating heavy

metals (Gadd and White, 1993; Bruins et al., 2000). Contrary to the general belief that metal

resist bacteria arose in response to anthropogenic exposures of metals it is being suggested

now that such resistances arose soon after life began in a world, already polluted by volcanic

activities and other geological sources. (Gupta and Kumar, 2012). Bacteria develop heavy

metal resistance mostly for their own survivals. It is well known that bacteria exposed to high

levels of heavy metals in their environment have adapted to the stresses by developing

various resistance mechanisms. They remove toxic metal ions via: adsorption to cell surface

(Mullen et al., 1989; Ahmed et al., 2005); complexation with exopolysaccharides (Scott and

Palmer, 1988), binding with bacterial cell envelopes (Flatau et al., 1987), intracellular

accumulation (Laddaga and Silver, 1985), extracellular precipitation of metals as phosphates,

carbonates and/or sulfides; (Aiking et al., 1985), biosynthesis of metallothioneins and other

proteins that trap metals (Higham et al., 1984), transformation to volatile compounds via

methylation or ethylation, oxidation or reduction to a less toxic form (Robinson and

Touvinen, 1984), physical exclusion of electronegative components in membranes and

extracellular polymeric substances (EPS); energy-dependent metal efflux systems; and

intracellular sequestration with low molecular weight and cysteine-rich proteins (Gadd, 1990;

Silver, 1996). These mechanisms could be utilized for detoxification and removal of heavy

metals from polluted environment or to convert them to less toxic or completely benign

forms. Bioremediation can be effective where environmental conditions permit microbial

growth and their needed activities (Vidali, 2001; Trivedi et al., 2007; Luo et al., 2008).

Owing to the well established role of metals bioremediation of several microorganisms in


27

certain natural environments, the humans assisted locations and the successes from

bioreactors (Elangovan et al., 2006; Goulhen et al., 2006; Viamajala et al., 2007). Coupled

with the information regarding presence of facultative anaerobic to aerobic bacteria in gut of

the fishes (Lesel, 1981; Sugita et al., 1991; Zmyslowska et al., 2000) it appears plausible to

consider occurrence of the metals remediational activities of certain enteric bacteria for their

own survival primarily and secondarily to protect their host from the respective toxic effects.

Although such information are difficult to find in the literature but isolation of metal resistant

bacteria from guts of fishes support the hypothesis.

2.6 Situation of the river Ravi in the study area:

In Pakistan, freshwater pollution is exemplified by the river Ravi that flows through

Lahore, the second largest city of the country. Due to improper disposal of domestic and

industrial effluents, the river Ravi while passing through the city Lahore had been

contaminated excessively with myriad of pollutants for the last several decades. Regarding

the nature of pollutants, heavy metals such as Pb, Cu, Hg and Cr etc. can be enlisted on the

top. The river bed can be speculated for harboring and concentrating many of the pollutants

subterraneously. The river topography is such that it receives chemicals from pesticides and

fertilizers when it passes through most of the fertile land. Pearce et al. (1998) reported water

quality of various sites of the river Ravi and mentioned that heavy metals were absorbed by

heavier sediment particles and deposited on the river bed rather passing down the system as

suspended particles. Ahmad and Ali (1998) reported that total dissolved solid (TDS) were

higher at Balloki (downstream) than at Lahore Siphon (upstream) which reflected the effect

of aquatic pollution due to discharge of municipal and industrial wastes from Lahore and

nearby industrial areas. Javed (1999) reported increasing concentrations of cadmium, iron,

manganese, nickel, lead and zinc in water samples from Shahdera bridge to Balloki

headworks of river Ravi as a result of heavy discharges from the river tributaries. Javed and


28

Mahmood (2000b) have demonstrated that heavy metals’ toxicity in plankton showed

considerable variation due to variable discharges of untreated industrial and domestic

sewages in to river Ravi stretch from Shahdera to Balloki headworks. Mahmood (2003)

while analyzing concentration of metals in river Ravi from Balloki headworks to Sidhnai

barrage (downstream) found that lead accumulation was higher in gills and liver of fish than

the levels measured in kidney and muscle. Nickel concentration was maximum in liver

followed by that in gills, kidney and muscles. Fish procured from Balloki headworks had

more metals in their bodies as compared to those captured from Sidhnai barrage. Likewise,

Ubaidullah et al. (2004a) determined considerable metal contamination variations in

planktonic biomass of river Ravi stretch from Balloki headworks to Sidhnai barrage. Rauf

and Javed (2007) also reported detrimental effects of copper toxicity on plankton biota of the

river Ravi stretch from Lahore siphon to Balloki headwork (downstream). These authors

commented that plankton had a greater tendency to accumulate copper than the level found in

water. Javed (2005) reported the concentrations of heavy metals zinc, lead, iron, nickel and

manganese in sediments and organs of different fish species of river Ravi from Balloki

headworks to Sidhnai barrage. This comparable study showed that fish specimens viz., Catla

catla, Labeo rohita and Cirrhina mrigala at Balloki Headworks accumulated significantly

higher quantities of iron and nickel in their bodies than those captured from Sidhnai Barrage.

Levels of the pollutants attained by the fish showed direct relationship with the intensity of

metal pollution in the sediment and water. Rauf et al. (2009a) reported that the fish at Balloki

Headworks showed higher accumulation of cadmium in their bodies than those captured

from Shadera and Lahore Siphon. While chromium showed more or less same levels at the

three sampling stations. In another study, Rauf et al. (2009b) reported heavy metal

contamination in the sediment of river Ravi (Lahore Siphon to Balloki headworks). They

found highest concentration of copper in Taj Company nulla, while minimum concentration


29

of cadmium was observed at Lahore Siphon. The contaminated sediments which have

accumulated the pollutants over the years in the river bed could act as secondary source of

pollution to the overlying water column in the river. Jabeen et al. (2012) reported that

toxicity of metals fluctuated significantly in sampling fish species at all the three sampling

stations viz. Shahdara bridge, Balloki headworks and Sidhnai barrage with season. And. the

health status of river Ravi at three main public fishing sites, with respect to eco-toxicity of

Al, As, Ba, Cr, Ni and Zn was above the recommended permissible standards.

Above referred literature summarizes detrimental effects of industrial and sewage

pollutions on the fish species in the polluted river. Fish thriving in heavy metal polluted

waters might had metal resistant and/or detoxifying resident bacteria in their guts. Regarding

the Lahore urban contaminated segment of the river Ravi, this work aimed to study health

status of three species of fishes representing bottom, column and surface feeders with special

reference to titre of fatty acid contents, muscle biochemistry, metals bioaccumulation and

occurrence of heavy metals resistant bacteria in their gut contents for seeking information

about entero-metals detoxification processes. The information worked out in course of the

present study add to the earlier evaluations on the river pollution due to Lahore (second

largest city of Pakistan) urban stresses and health status of the three fish species viz., Labeo

rohita, Catla catla and Cirrhinus mrigala on one hand, while on the other hand dictates for

strict environmental legislation required for rehabilitation of drastically affected aquatic

fauna and the river Ravi itself.

Chapter 3 Materials and Methods

30

MATERIALS AND METHODS

This study pertains to Lahore segment of river Ravi and demonstrates effects of domestic

and industrial effluents’ loads, in terms of growth, various biochemical parameters, fatty

acids composition, heavy metals bioaccumulation and certain bacterial profiles, on three

inhabitants fish species viz., Cirrhinus (C) mrigala, Labeo (L) rohita and Catla (C) catla.

Water, sediment and the fish samples were collected from three alongstream polluted

sites (B, C and D) and compared with the samples collected from a less polluted upstream

site A (Control) of the river Ravi.

3.1 Study area:

During its course through Lahore, the second largest and an industrial city of

Pakistan, the river Ravi gets heavily contaminated with industrial as well as domestic

origin effluents. Major domestic sewage pumping stations and industrial effluents inlets

are shown in fig. 3.1. As can been seen from this figure, fishes were sampled from four

localities.


31

Fig. 3.1 Map of the river Ravi Lahore stretch showing four study sites and major urban pollution inlets


32

Following is brief description of the sampling sites;

3.1.1 Site A: Lahore Siphon (Control):

This upstream sampling site situated near village Talwara Par (31° 41΄ N and

74° 25΄ E) was least disturbed as regards as the urban pollutants and characterized with

relatively good water quality. Marala Ravi Link canal joins the river Ravi approximately

15 Km upstream of this sampling site which diverts the water from river Chenab to

minimize anthropogenic impacts on water quality of river Ravi to some extent. No point

source of pollution at this site or above was identified after entering the river in Pakistan,

however, it does receive some contaminants from agricultural runoff which may be

considered non-point source(s) of pollution. The less polluted site is upstream away from

industrial complexes and human activities of the city Lahore. The river bed sediment at

this site was made of predominantly sand, whereas the water had turbid, did not allow

determination of its surface current.

3.1.2 Site B: Shahdera:

This downstream sampling site is situated near old Ravi Bridge, Lahore (31° 36΄

N and 74° 18΄ E) where it receives untreated municipal sewage effluent of Lahore city

from three major pumping stations (North East (on the left side of river flow), Shad bagh

(left side) and Shahdera Gauging Station (right side) between the sites A and B. This site

was under considerable stress also due to solid waste dumping on the banks of river

where the urbanized overcrowded towns are located. The bed of the river at this site was

muddy and sandy and its water was blackish, smelly and slow moving, especially during

low flow season.

3.1.3 Site C: Sunder:

This sampling site is situated near village Nano Dogar (31° 21΄N and 74° 3΄E).

Between sampling site B and site C, there are four major pumping stations, discharging

untreated municipal wastewater of Lahore city in to the river Ravi. Furthermore, there are

two drains (Hudiara and Deg Nullah) which dispose off industrial effluents into this


33

segment of the Ravi. Hudiara drain is one of the major sources of pollution for the river.

It enters in Pakistan loaded with pollutants of around 100 industries located adjacent to

the Hudiara drain on the 55 Km Indian side and more than 112 industries located next to

the drain as it travels 63 km through the Punjab, Pakistan. Deg Nullah carries the

effluents from Kala Shah Kaku industrial complex, which has more than 149 industrial

units. Some industries on Lahore-Sheikhupura road also discharge their wastewater into

the drain (Saeed and Bahzad, 2006). Inflows of polluted upstream domestic sewage water

plus effluents of these drains together make the river segment a highly polluted site. The

bed of river was mosaic of mud and sand. The water was blackish, especially during low

flow and had objectionable odour. The speed of current was slow.

3.1.4 Site D: Balloki:

This downstream site is located near Head Balloki (31° 13΄ N and 73° 52΄ E).

Qadirabad (Q.B) link canal joins the river Ravi downstream between site C and site D.

No point source of pollution between site C and D was identified, however, it does

receive some non-point pollution including contaminants from agricultural runoff. The

bed of the river at this site consisted chiefly of sand. The water was turbid.

3.2 Sampling of water, river bed sediment and fishes from the study locations

3.2.1 Water sampling:

At each described site sampling was done from three sub-sampling loci at more or

less equal distances from each other within a radius of 40 metre representing mid of the

river. Duplicate water samples were collected by dipping screw caped bottles at about

30-40 cm below the water surface during low (November- December, 2009.) and high

(September- October, 2010) flows of the river. The sampling locations were approaching

with the help of a wooden boat. The bottle was opened at the mensional depth filled with

inflowing water without trapping any bubble and again closed by the cap before taking it

out from the water. The samples were properly labeled immediately at the sampling point

to record site, subsite, purpose, date and time of the sampling. One water sample collected


34

from each sub-site was used for determining different physico-chemical parameters later

in the lab while the other was employed to assess heavy metals contents. For this purpose

5 ml HNO3 (55 %) per litre of a sample water were added immediates at the sampling site

to prevent metal adsorption along the inner surface of the sampling bottle. All the water

samples were then transported to the laboratory in the cool box and stored at 4°C in

refrigerator till further use.

3.2.2 Collection and preservation of sediment sampling:

Sediment samples of low and high flow seasons of the river Ravi were collected

from the three sub-sampling sites during the periods described in section 3.2.1. A steel

pipe (2½ inch diameter) was pressed with huge pressure through the water column to

obtain a sample of river bed sediment which was subsequently shifted in glass bottles.

After labeling the glass containers (site, subsite, date and time) duplicate samples of each

sub-site were transported to the laboratory. In the laboratory, the sediment samples were

dried at 105°C in an electric oven for 24 hours. The dried samples were passed through

standard sieve to remove large particles. Dried river bed sediment samples were stored in

labeled closed polythene bags for heavy metals analysis later.

3.2.3 Sampling of fishes:

Fish specimen of thaila, Catla (C) catla (surface feeder); rohu, Labeo (L) rohita

(column feeder) and mori, Cirrhinus (C) mirgala (bottom feeder) weighing from 250 g to

1000 g were collected from the selected as describe above during the low and high flows

of river Ravi. Gill nets locally called as patti of about 6 feet wide and 40 feet long with a

cork line at the top rope and metal line with the ground nylon rope made locally were

used by professional local fishermen. The nets were set at sampling site approximately 3-

4 hours before sunset and lifted 1-2 hours after sunrise. Two groups, each comprising of

two fishermen, who were recruited for sampling shared a single gill net while employing

two wooden boats to reduce unnecessary disturbance and stress for the fishes, motor-

driven boats were not used. Six wooden boats representing three teams of the fishermen


35

collected the fishes with the help of three gill nets at each collection. Nine fish specimen

each of the three species of comparable size range for a given collection were saved. The

selected fish specimens were washed with water, kept in separate polythene bags placed

on ice and immediately transported to the laboratory. In the laboratory the fish specimen

were processed for biometric, proximate, biochemical, bacteriological, heavy metals and

fatty acid analyses as described in section 3.2.3.1, 3.3, 3.4, 3.5, 3.6 and 3.7 respectively.

3.2.3.1 Biometric data of sampled fish species:

Taxonomic identification of fishes collected from the described locations of the

river Ravi was verified on the basis of morphometric characteristics up to the species

level. Fish species were identified following regional identification key (Mirza, 2003).

Each fish specimen was subjected to morphometric studies on the day of sampling.

Morphometric parameters of each specimen were determined using scale, length

measuring tray, length measuring tape, vernier caliper and electronic digital top-pan

balance (Chyo, Japan). The wet weight of each fish after blot-drying excess water in the

body and total length i.e., from the tip of the snout to distal end of the caudal fin ray were

recorded. The relationship between wet weight (W) in g and total length (L) in cm was

established as:

W= aLb

or

in linear form (Regression equation):

Log W=log a +b log L

Where

a =intercept = regression coefficient

b = slope = growth factor/growth coefficient.

Condition factor (K) were calculated by standard relation (Carlender, 1970)

K= (W x 100)/ (TL)3


36

Following morphometric characters were also measured and associated with size, locality

and flow season of sampling

Standard length i.e., from head to start of tail

Post operculum length i.e., from end of fleshy operculum to longest caudal fin ray

Head length i.e., from snout tip to most posterior edge of fleshy operculum

Eye diameter

Mouth width

Mouth gap

Dorsal fin length

Pectoral fin length

Pelvic fin length

Anal fin length

Caudal fin length

3.2.3.2 Dissection of the fishes and Processing of tissues for detailed analyses:

External surface of each fish specimen was wiped with 95 % ethanol soaked

cotton swab. Then the fish specimens were dissected under aseptic condition by using

sterilized forceps, scissors and scalpel. From the intestine of each specimen, 1g of gut

contents were squeezed out and placed in 9 ml autoclaved saline solution (0.9 %) in

labeled glass tubes and stored at 4 °C till further use. Liver, kidney, heart, eyes, pieces of

skin, muscles and intestine and gills of both sides were incised carefully, washed with

distilled water and shifted in marked polythene bags which were stored at -20 ºC till

further use.

3.2.1.1 Physico-chemical analysis of the river Ravi water:

Standard methods (APHA, 1985) were followed for estimation of various

physico-chemical parameters of the water samples. Analytical grade chemicals and

reagents of described trades were used for the analyses.


37

3.2.1.1.1 Temperature:

River’s water temperature was measured at each sampling site at the time of water

sampling by using ordinary centigrade thermometer.

3.2.1.1.2 Dissolved oxygen:

Dissolved oxygen (DO) of waters samples were determined by Winklers’s method

(APHA, 1985). Two hundred fifty ml of water sampled from a sub-site was taken in

reagent bottle. Add 1 ml of MnSO4 (360 g MnSO4 dissolved in one liter distilled water) at

bottom of the bottle and shake well. Then 1 ml alkaline KI (500 g NaOH and 135 g Kl

dissolved in one liter distilled water) and 1 ml conc. H2SO4 was added at the top of the

solution and shake properly. This mixture is considered a stock. From this stock solution,

50 ml solution were proceeded for titration against Na2S2O3 (0.025 N) till appearance of

pale yellow colour. Then again titrate after addition of few drops of starch solution (2 g

starch and 0.05 g NaOH dissolved in 100 ml distilled water and boiled) as indicator until

the colour become disappear and record the volume of Na2S2O3 used.

O2 in water (mg/l) = (ml) sample totalofAmount

0.698 x 200 x used OSNa ofAmount 322

3.2.1.1.3 Total suspended solids:

One hundred ml of a water sample collected from a sub-site was filtered through

a preweigh, labeled Whatman filter paper 541. The filtrate on the filter paper was dried in

an electric oven at 105 ºC for 1-2 hours and weighed after cooling in a desiccator. Total

suspended solids of the water sample were then calculating and reported as mg/L of the

water samples.

3.2.1.1.4 Total Dissolved Solids:

For this parameter too, 100 ml of a water sample was filtered through the

Whatman filter paper and the filtrate was shifted in a pre-weighed evaporating china dish.

The water filtrate was then subjected to dryness on a water bath (80 ºC). The china dish

was then kept in oven at 105 ºC for one hour and weighed after cooling in a desiccator.


38

Total dissolved solids were weighed, calculated and reported as mg/L of the water

samples.

3.2.1.1.5 Total hardness as CaCO3:

Total hardness of the water samples was estimated by EDTA titrimetric method

(APHA, 1985). A given water sample was well mixed and then its 25 ml were diluted to

50 ml with distilled water in a flask and mixed thoroughly again. Then 3 ml of ammonia-

ammonium chloride buffer pH 10 (67.5 g NH4Cl in 570 ml Conc. NH4OH and diluted to

1 litre) and 2-3 drops of Eriochrome Black-T (0.5 g sodium salt of 1-(1-hydrpxy-2-

naphthylazo)-5-nitro-2-naphthanol-4-sulfonic acid dye in 100 ml triethanolamine)

indicator were added in the flask and titrated against 0.01 M EDTA with continuous

slowly stirring until reddish tinge color changed to bluish purple (violet) colour.

Total hardness was calculated as;

Total hardness (mg/L) = Ca + Mg (as CaCO3) = (ml) Sample

1000 x 100 x M x V

Where

V is volume of EDTA used

M is molarity of EDTA (0.01 M)

1000 is to convert milliliter (ml) in litre (L)

100 is the molecular weight of CaCO3

3.2.1.1.6 Calcium hardness as CaCO3:

Calcium hardness of the water samples was also estimated by EDTA titrimetric

method (APHA, 1985). Twenty five ml of properly mixed given water sample were

diluted to 50 ml with distilled water. Then 3 ml of KOH buffer pH 12.5 (20 % W/V KOH

solution) and 0.2 g of murexide (NH4C8H4N5O6, or C8H5N5O6.NH3) indicator were added

to the diluted sample. The resulting reddish colour solution in the flask was titrated

against EDTA (0.01 M) with continuous slowly stirring until the reddish colour turned

into bluish purple (violet) colour.


39

Calcium hardness in the water sample was calculated as;

Ca hardness as CaCO3 (mg/L) = (ml) Sample

1000 x 100 x M x V

Where

V is volume of EDTA used

M is molarity of EDTA (0.01 M)

1000 is to convert milliliter (ml) in litre (L)

100 is the molecular weight of CaCO3

3.2.1.1.7 Magnesium Hardness:

The amount of magnesium hardness in water sample was calculated as;

Mg hardness (mg/L) = Total hardness (Mg + Ca) as CaCO3 – Ca hardness as CaCO3

3.2.1.1.8 Total alkalinity:

The total alkalinity of the water samples was estimated by titrimetric method

(APHA, 1985). Accordingly, 1-2 drops of methyl orange indicator were added in 25 ml of

a water sample in a flask. Contents of the flask were titrated against H2SO4 (0.02 N)

solution until red colour changed into pink/orange colour.

Total alkalinity of the water sample was calculated as;

Total alkalinity as CaCO3 (mg/L) = (ml) Sample

1000 x V x E x N

Where

N is normality of H2SO4

E is equivalent weight of CaCO3

V is the volume of the H2SO4 solution used during titration.

1000 is to convert the millimeter (ml) into litre (L)

3.2.1.1.9 Chloride:

Chloride content of the water samples was estimated by Argentometric method

(APHA, 1985). In this method, water samples were titrated against standard AgNO3


40

titrant. Twenty five ml of a given water sample were diluted to 50 ml with distilled water

in a glass flask followed by the addition of H2SO4 (0.02 N) exactly in the amount that was

used for determination of total alkalinity (section 3.2.1.1.8). Then 2-3 drops of 2 %

potassium chromate (K2CrO4) were added as an indicator and titrated against AgNO3

(0.0141 N) solution until the appearance of pinkish yellow colour.

Chloride present in water sample was calculated as;

Amount of chloride (mg/L) = 100(ml) Sample

35.5x NA x

Where

A is the volume of AgNO3 used in titration.

N is the normality of AgNO3

3.2.1.1.10 Ammonia:

Ammonia in the water samples was determined by Nessler’s method (APHA,

1985). Nessler’s reagent was prepared by dissolving 34.9 g of KI and 45.5 g of HgI2 in

100 ml of distilled water in a labeled glass flask. In another flask, KOH (112 g) was

dissolved in 200 ml distilled water and kept at room temperature. The two solutions were

mixed and the total volume was made up to 1000 ml with distilled water. The mixture

was allowed to stand for 2-3 days to settle down the precipitate before use.

Standard curve was prepared by using standard solution of ammonia. For this

purpose, 0.01 mg NH3/ml solution was prepared by ten fold dilution of standard solution

of ammonia. From this solution 2.0, 4.0, 6.0, 8.0 and 10.0 ml were transferred in separate

250 ml volumetric flasks. A blank was also prepared by using 75 ml of distilled water.

Solution in each flask was diluted to 75 ml with distilled water and then 5.0 ml of

Nessler’s reagent was added to each flask. After 30 minutes optical density (absorbance)

of each solution was measured at 420 nm wavelength on a spectrophotometer against

blank. The absorbance of each standard solution was plotted against the NH3

concentration on a graph to prepare a standard curve.


41

A given water sample was treated with the 5 ml Nessler’s reagent as described

above for the preparation of standard curve and the absorbance recorded. To find the mg

ammonia, optical density (absorbance) of a given water sample was plotted on standard

curve.

The quantity of ammonia in water sample was determined by the following formula:

Ammonia (mg/L)= (ml) Sample

1000 x ammonia mg

Where

mg of ammonia was read from the calibration curve

3.2.1.1.11 Phosphate:

Stannous chloride colorimetric method (APHA, 1985) was used for the estimation

of phosphate. A standard stock phosphate (500 μg/ml) solution was prepared by

dissolving 0.7164 g of anhydrous KH2PO4 in 1.0 litre of distilled water. This standard

stock solution was diluted 10 times to make a concentration of 50 μg/ml of phosphate.

In case of coloured water sample, 1 drop of phenolphthalein indicator and a few

drops of conc. H2SO4 solution were added to discharge the pink colour. In routine

analyses, 50 ml of a water sample and 50 ml distilled water were taken in glass flasks

labeled as test and blank, respectively. Then 2.0 ml of 10 % ammonium molybdate

solution and about 5 drops of 10 % stannous chloride solution were added to the contents

of each flask. The colour developed was measured after 10 minutes at 690 nm wavelength

on a spectrophotometer against blank. Calibration curve was prepared by plotting

absorbance of different amount of PO4-3

- P prepared by diluting the standard stock

solution and then treated as described above for test and blank samples. Absorbance of a

given test sample was read for the value of P from the standard curve and then

concentration of phosphate content of the water sample was calculated by the following

formula.


42

mg P/L = (x) =(ml) volumeSample

1000 x curve) std. from (reading P mg

While the PO43-

concentrations were calculated by the following equation:

31

(x) x 95 L)(mg/ PO -3

4

Where (x) is mg of P/L, 95 is the molecular weight of PO43-

and 31 is the atomic weight

of P.

3.2.1.1.12 Sulphate:

Ethylene Diamine Tetraacetic Acid (EDTA) titrimetric method (APHA, 1985) as used for

the estimation of sulphate contents in water samples. Accordingly, 25 ml of a given water

sample, was mixed in a flask with an amount of 0.02 N HCl solution equivalent to the

volume of 0.02 N H2SO4 that was used during the determination of total alkalinity

(section 3.2.1.1.8). The mixture was boiled in water bath for 1 hour and then mixture was

cooled to room temperature. Then 5 ml of 0.02 M BaCl2, 1 ml of 0.02 M MgCl2 solutions,

a few drops of Eriochrome Black – T (EBT) indicator were added to the flask. After

mixing the contents of the flask well, 2 to 4 ml of ammonia-ammonium chloride buffer

pH 10 (67.5 g NH4Cl in 570 ml conc. NH4OH and diluted to 1 litre) were added to obtain

brick red colour. The mixture was titrated against 0.01 M EDTA until the colour changed

from red to violet blue. A blank containing only distilled water (without HCl) was also

titrated against the EDTA.

The net EDTA volume used (Z) was calculated as;

Z = B - H- A

Where B is volume of EDTA used for Blank, H is volume of EDTA used for total

hardness, and A is volume of EDTA used for sample. The sulphate ( -2

4SO ) concentration

was then calculated by the following equation:

(ml) samle of Volume

Mx1000 x 96xZ L)(mg/ SO -2

4


43

Where

M is molarity of EDTA (0.01 M) and 96 is the molecular weight of SO42-

3.2.1.1.13 Nitrate:

Phenoldisulfonic acid method (APHA, 1985; Garg et al., 2000) was used for the

estimation of Nitrate content in the water samples. Volume of silver sulfate (Ag2SO4)

equal to the volume of 0.02 N H2SO4 used for the determination of total alkalinity

(section 3.2.1.1.8) was added in volumetric flask labeled test containing 100 ml of water

sample. The blank flask contained 100 ml of distilled water. Contents of the flasks were

heated for a few minutes, neutralized to pH 7 and evaporated to dryness on water bath.

The residue was mixed with 2 ml of phenoldisulfonic acid, followed by the addition of 20

ml of distilled water and 7 ml of concentrated NH4OH. The contents were allowed to

react till the development of maximum yellow color.

Absorbance was then read at 420 nm against the blank. Nitrite concentration was

estimated from the standard curve. For preparation of standard curve, 50 ml stock nitrate

solution (100 mg/L) was kept in the boiling water bath until dryness. The residue was

dissolved with 2 ml phenoldisulfonic acid reagent and diluted to 500 ml with distilled

water to make a solution of 10 μg N/ml. Different quantities viz., 0.1, 0.5, 0.7, 1.0, 1.5,

2.0, 3.5, 6.0, 10, 15 and 30 ml of the standard nitrate solution were taken in separate 100

ml labeled glass flasks, to which 2 ml phenoldisulfonic acid and 7 ml of concentrated

NH4OH was added. A blank was prepared from the same volume of phenoldisulfonic acid

and NH4OH.

Absorbance of different standards were read against the blank at 420 nm

wavelength by using spectrophometer. The calibration curve was prepared by plotting the

absorbances against the amounts of nitrate. Corresponding value of absorbance of a

sample was calculated from the standard curve. The amount of nitrate was then calculated

as follow


44

43.4(ml) volumesample

1000 x (mg) Nitrate L)(mg/ Nitrate x

Where

Nitrate (mg) was calculated from standard curve, 4.43 is the factor for the

conversion of nitrogen (NO3-N) into nitrate (NO-3) and is obtained by dividing the

molecular weight of nitrate (62) by the atomic weight of nitrogen (14).

3.2.1.1.14 Nitrite:

Nitrite in water sample was estimated by Diazotization method (APHA, 1985).

Fifty ml of a given water sample was taken in glass flask (test) and 50 ml of distilled

water in blank flask. Contents of the flasks were neutralized to pH 7. Then 1 ml of

sulfanilic acid was added and pH adjusted to 1.4. In this mixture, 1 ml of 2 M sodium

acetate buffer solution and 1 ml of α-nepthylamine hydrochloride were added. The

contents were mixed was pH readjusted at 2.5 and allowed to stand for 20-30 minutes.

The reddish purple color was then measured at 520 nm wavelength against the blank.

Stock solution was prepared by dissolving 0.246 g anhydrous NaNO3 in one litre

of distilled water to form nitrite stock solution of 0.05 mg N/ml. This stock solution was

further diluted by dissolving its 10 ml in distilled water to make 1 litre solution (0.5 μg

N/ml). Different quantities, viz., 0.0, 0.1, 0.2, 0.4, 0.7, 1.4, 1.7, 2.0 and 2.5 ml of the

diluted solution were taken in separate flasks and diluted up to 50 ml with distilled water

and then same volume of reagents were added as describe above.

Optical density was determined against the blank at 520 nm wavelength by using

spectrophotometer. A graph was plotted between optical densities and the known values

of nitrite. The nitrite concentrations in milligram was derived from the standard curve by

plotting absorbance of each sample against different concentrations of sodium nitrite and

nitrite concentration (mg/L) was then calculated as follow;

285.3(ml) volumesample

1000 x (mg) Nitrite L)(mg/ Nitrite x


45

Where 3.285 is the factor for the conversion of nitrogen (NO2-N) into nitrite

(NO-2) and is obtained by dividing the molecular weight of nitrite (46) by the atomic

weight of nitrogen (14).

3.3 Proximate analysis of the fishes’ muscles

3.3.1 Moisture content:

Moisture contents were determined by using Lyo Lab G Freeze Dryer at – 50 °C for 72

h.

100sample muscle dried ofWeight

sample dried freeze of Weight - sample muscle wet ofWeight (%)content Moisture x

3.3.2 Ash Content:

Known weights of muscle samples were taken in a clean, oven dried, weighed

crucible and ignited in an electric furnace at 550 °C for determination of ash content

according to the following formula:

100sample dried freeze ofWeight

ash of Weight (%)content Ash x

3.3.3 Crude Protein:

Freeeze dried muscle samples were analyzed by CN analyzer for determination of

nitrogen contents. Crude protein content was estimated by Kjeldahl nitrogen using 6.25

conversion factor.

3.3.4 Fat extraction:

Total crude fat was extracted from freeze dried fish muscle tissues with the help of

soxhlet appperatus. Cleaned Soxhlet flasks were placed in an oven at 100 C for 15 min

to remove any moisture and then placed in a desiccator for cooling. Each flask was

weighed and identified. The thimbles were tarred and ground freeze dried fish muscle

samples was put into them. The Soxhlet extractors with reflux condensors and the

previously weighed flasks were fitted on to their stands. The thimbles were placed into

the extractors and petroleum ether (boiling point = 40 – 60 °C, Fisher Limited UK) was

added. The flasks were heated on a uniform heat for 6 h to extract the crude fat from the


46

muscle samples. The flasks were removed from the extractors and left in an oven at 60

C for 1 h to evaporate any excess petroleum ether. The flasks were then cooled in a

desiccator and re-weighed. The following formula was used to calculate the percentage

of fat extracted.

Fat extracted % = 100 sample mussel dried of Wt.

flask of wt.Initial -fat flask with of wt.Final

3.3.5 Total carbohydrates:

Total carbohydrate of fishes’ muscle tissues were determined by subtracting the %

values of moisture, ash, crude protein and fat contents from 100 (Plummer, 1994).

Total carbohydrates (%) = 100 – (moisture + ash + crude protein + fat)

3.4 Biochemical analyses of fishes’ muscles

3. 4.1 Preparation of the tissue extract in ice cold saline:

Fish muscle tissue extract in ice cold saline was prepared as describe by Anwar et

al. (2004). Frozen fish muscles were cut with razor, thawed with distilled water and

blotted with blotting paper. One g of blot dried muscle of each fish was homogenized in 4

ml of ice-cold saline (0.89 % NaCl) solution with the help of a motor driven homogenizer

at 8000 rpm for 4 minutes. The homogenate was centrifuged at 4900 rpm for 45 minutes

at 5 ºC in a refrigerated centrifuge to get a clear saline supernatant. The clear supernatant

was separated and used for determination of the total carbohydrates and soluble

protein in fish tissue of sampled specimen.

3.4.1.1 Estimation of total carbohydrates:

Total carbohydrates contents in fish muscles were also determined by following

the method of Dubios et al. (1956). Fish tissue saline extract was diluted by mixing

distilled water in the ratio of 1: 100 (Fish tissue saline extract 0.1 ml with 9.9 ml of

distilled water). Then 1 ml of the diluted fish tissue saline extract and 1 ml of distilled

water were taken in test tubes labeled as sample and blank, respectively. Each sample was

proceeded in duplicate. For each test 0.5 ml of 5 % aqueous phenol solution was added


47

followed by rapid addition of 2.5 ml of concentrated sulfuric acid. The tubes were

allowed to stand for 10 minutes and then placed in water bath at 30 °C for 15 minutes.

Six standard dilutions containing 10, 20, 30, 40, 50 and 60 μg sucrose/ ml distilled

water were prepared from Standard stock solution of sucrose (100 μg sucrose/ml distilled

water) in labeled test tubes. One ml of each of the dilutions was proceeded in the same

manner described above. Optical densities were then measured with the help of

spectrophometer at 492 nm against blank. Standard curve was plotted expressing the

optical density (absorbance) at ordinate and concentrations of standards dilutions at

abscissa. Curve value was calculated by regression equation (Fig. 3.2) and carbohydrate

of muscle sample was calculated as;

Total carbohydrate contents (mg/g) =1000xw

dfxthxCVxAx

Where

Ax= absorbance of sample

CV= curve value from standard curve= 91.44 µg

th=volume of total homogenate (ml)

df=dilution factor

w=weight of wet muscle tissue used for preparing the homogenate

3.4.1.2 Soluble Protein contents:

Soluble protein contents of fish muscle tissue was estimated by Folin-Ciocalteu

method (Lowry et al., 1951). Saline extract 0.4 ml was treated with 2 ml of Folin-

Ciocalteu mixture (Solution A; 0.4 % sodium hydroxide and 2 % sodium carbonate,

Solution B; 2 % sodium potassium tartarate and solution C; 1 % copper sulphate. Folin-

Ciocalteu mixture was prepared by mixing 50 ml of solution A, 0.5 ml of solution B and

0.5 ml of solution C). Each test was proceeded in duplicate. The test as well as blank

tubes kept at room temperature for 15 minutes. Then 0.2 ml of diluted Folin-Ciocalteu

reagent (1:4) was added in test tube and mixed well. The tubes were again incubated at


48

room temperature but for 45 minutes. Six standard dilutions containing 50, 100, 150, 250,

300 and 350 g of the protein/ml of water were prepared in a labeled test tubes from a

protein standard stock solution (1 mg bovine serum albumin/ml of distilled water) and

proceeded as described above for the test sample. Optical density of each reaction was

measured at 750 nm by spectrophometer against blank for which 0.4 ml distilled water

was treated with reagents. Standard curve was plotted expressing the optical density

(absorbance) at ordinate and concentrations of standards dilutions at abscissa. Curve

value was calculated by regression equation (Fig. 3.3) and soluble protein contents of fish

muscle tissue were calculated as;

Soluble protein (mg/g) =1004.0 xwx

dfxCVxAxa

Ax = optical density (Absorbance) of sample

df = dilution factor

a = amount of the extract assayed

w = weight of tissue used for the preparation of the homogenate

CV = curve value by standard curve = 280.99 g

3.4.2 Preparation of muscle tissue hydrolyzate in Sodium hydroxide for

determination of total protein:

Frozen muscle tissue 0.5 g was thawed and homogenized in 4 ml ice-cold 0.5 N

sodium hydroxide solution with the help of motor driven homogenizer at 8000 rpm for 4

minutes. Total Protein contents of the tissue were determined by Folin-Ciocalteu method

(Lowry et al., 1951) as detailed in section 3.4.1.2.

3.4.3 Preparation of ethanol extract of muscle tissues for determination of

cholesterol, total lipids and nucleic acids:

Of a given muscle tissue, 0.5 g was boiled in 3 ml ethanol in caped tubes which

were kept in a boiling water bath for one hour. The tubes were then incubated at 37 ºC for

an overnight period. The contents were then centrifuged at 2000 rpm for 10 minutes. The


49

pellets were used for nucleic acid extraction, while the clear ethanol supernatant was

decanted in labeled vials and evaporated at 70 ºC in oven. The yellowish dried residue

containing lipid and cholesterol components was dissolved in 0.5 ml of chloroform and

used for analysis of total lipids (Zollner and Kirsch, 1962) and cholesterol (Folch et al.,

1957).

3.4.3.1 Estimation of Cholesterol:

Cholesterol was determined by the method of Folch et al. (1957). Accordingly,

0.1 ml of ethanol extract, 0.1 ml of standard solution (1 mg of cholesterol in 1 ml of

glacial acetic acid) and 0.1 ml of glacial acetic acid were dispensed in tubes labeled as

test, standard and blank, respectively. Then following the addition of 3 ml of glacial

acetic acid in each tube and the contents were vortex mixed. This was followed by the

addition of 0.3 ml of colour reagent (250 mg of FeCl3.6H2O in 100 ml of 85%

orthophosphoric acid). After vortex mixing, 3 ml of concentrated H2SO4 were added and

the contents were allowed to stand at room temperature for 10 minutes. Optical densities

(absorbance) of sample and standard were recorded against the blank at 560 nm by using

spectrophotometer. The cholesterol content of fish muscle were then calculated as;

Cholesterol (mg/g) = 100

200

xwxAs

xthxAx

Where;

Ax = absorbance of sample

As = absorbance of standard

th = volume of total homogenate

w= wet weight of tissue used to prepare the extract

3.4.3.2 Estimation of total lipid:

Total lipid contents of fish muscle were estimated by the method of Zollner and

Kirsch (1962). Accordingly, 0.05 ml ethanol extract, 0.05 ml standard solution and 0.05

ml distilled water were added in test tubes labeled as sample, standard and blank,


50

respectively. The standard solution was prepared by dissolving 1 mg olive oil in 100 ml

of 95 % ethyl alcohol. Following the addition of 1.00 ml of conc. H2SO4/tube, the

mixtures were heated for 20 minutes in boiling water bath and cooled for 20 minutes in

cold water. Then 2 ml of colour reagent (0.0608 g of vanillin/50 ml of H3PO4) was added

in each test tube and opitical densities were measure against the blank at 530 nm by using

spectrophometer. Total lipid contents were estimated by the following formula;

Total lipid contents (mg/g) = wxAs

xthxAx 10

Where

Ax = absorbance of the sample

As = absorbance of standard

th = volume of total homogenate

w = weight of tissue used to prepared the homogenate

3.4.3.3 Extraction of Nucleic acids:

Pellets obtained after the ethanol extracts (section 3.4.3) were processed for

extraction of nucleic acids as adopted by Shakoori and Ahmad (1973). The pellets were

suspended in 2 ml of boiling ethyl alcohol and incubated in a water bath at 80 ºC for 3

minutes. The contents were then centrifuged at 5000 rpm for 5 minutes and the pellets

were washed by ethyl alcohol and suspended in boiling methyl alcohol ether mixture

(3:1) and incubated at 80 ºC for 3 minutes in a water bath. The contents of each test tube

were centrifuged again at 5000 rpm for 5 minutes and the pellet was washed with methyl

alcohol ether mixture. The pellets were dried in desiccators under vacuum at room

temperature for 8 days. The NaOH pellets were used as desiccant. The dried pellets were

soaked in ice water in a refrigerator for one and half hour. Then 2 ml of 20 % ice cold

perchloric acid solution was added. The tubes were placed at 4 ºC for 24 hours and then

centrifuged at 5000 rpm for 5 minutes and the supernatant was separated carefully for

RNA estimation. The residual pellets were re-suspended in hot (70-80 ºC) perchloric acid


51

(10 %) solution. After mixing thoroughly, the tubes were placed in incubator for half an

hour at 80 ºC followed by centrifugation at 5000 rpm for 5 minutes. The hot perchloric

acid supernatants were used for the estimation of DNA.

3.4.3.3.1 Estimation of RNA:

RNA estimation were proceeded by orcinol reagent (Schneider, 1957). To 0.2 ml

of supernatant and 0.2 ml of 20 % perchloric acid for a given sample and blank,

respectively, 1.8 ml of distilled water and 2 ml of orcinal reagent (add 1% orcinol and 3-4

drops of 10 % FeCl3 in concentrated HCl) were added. After vertex mixing, the tubes

were covered by aluminum foil caps and kept in boiling water for 15 minutes. Then the

test tubes were cooled in cold water for 15 minutes and optical density measured at 660

nm against blank. Eight standard dilutions containing 50, 100, 150, 200, 250, 300, 350

and 400 g RNA/ml were prepared from standard stock solution (1 mg RNA rabbit liver/

ml of distilled water) and proceeded similarly as described above. The standard curve

were plotted by taking standard dilutions concentration at abscissa and optical density at

ordinate. Curve value was calculated by regression equation (Fig. 3.5). RNA content of

the samples were calculated as;

RNA (g/g) =wxth

dfxCVxAs

Where

As = absorbance of sample

CV = curve value from standard curve = 385.49g

df = dilution factor

th = total volume of homogenate

w = wet weight of tissue used to prepare the extract

3.4.3.3.2 Estimation of DNA:

DNA were estimated by the method of Schneider (1957). The test tubes labeled as

blank and test were dispensed with 0.5 ml of 10 % perchloric acid and 0.5 ml hot


52

perchloric acid tissue extract, respectively. Then 0.5 ml of distilled water, 2 ml of

diphenylamine reagent (1 % diphenyl amine in glacial acetic acid) and 3.75 ml of

concentrated H2SO4 were added in each test tube. The test tubes were covered by

aluminum foil caps and kept in boiling water for 10 minutes. Following cooling the test

tubes to room temperature, optical density was read at 600 nm against blank by using

spectrophotometer. Eight standard dilutions concentration of 50, 100, 150, 200, 250, 300,

350 and 400 g DNA/ml were prepared from the standard stock solution (1 mg Calf

thymus DNA/ ml of water) proceeded as mentioned above. The standard curve was

plotted by taking standard dilutions concentration at abscissa and optical density at

ordinate. Curve value was calculated by regression equation (Fig. 3.4). DNA in the

sample was calculated as;

DNA (g/g) =wxth

dfxCVxAs

Where

As = Absorbance of sample

CV = Curve value from standard curve = 890.45 g

df = Dilution factor

th = Total volume of homogenate

w = wet weight of tissue used to prepare the extract


53

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 20 40 60 80 100

Sucrose concentration (ug)

Ab

so

rban

ce (

op

tical

den

sit

y)

Absorbance (Optical density) = 0.0125 + 0.0108 Concentration (µg)

R2 = 0.998

Support

Absorbance = 1

Then

Standard curve value (CV) = 91.44 µg

Fig. 3.2 Standard curve for total carbohydrates (Phenol sulfuric acid method)


54

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 50 100 150 200 250 300

Protein concentration (ug)

Ab

sorb

an

ce (

Op

tica

l d

ensi

ty)


R2 = 0.956

Support

Absorbance = 1

Then


Fig. 3.3 Protein standard curve (Lowry method)


55

0

0.1

0.2

0.3

0.4

0.5

0.6

0 50 100 150 200 250 300 350 400 450 500 550

DNA Concentration (ug)

Ab

so

rban

ce (

Op

tical

den

sit

y)


R2 = 0.982

Support

Absorbance = 1

Then


Fig. 3.4 DNA standard curve (Schneider Method)


56

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 50 100 150 200 250 300 350 400

RNA Concentration (ug)

Ab

so

rban

ce (

Op

tical

den

sit

y)


R2 = 0.987

Support

Absorbance = 1

Then


Fig. 3.5 RNA standard curve (Orcinol method)


57

3.5 Heavy metals resistant bacteria from gut contents of the fishes:

3.5.1 Heavy metals resistant bacterial colony forming unit (CFU) :

One g of fresh gut contents of a given fish were mixed with 9 ml of sterilized 0.9

% saline as describe in section 3.2.3.2, Then second dilution (1:100) was prepared by

mixing 1 ml from first dilution with 9 ml of sterilized saline solution and third dilution

(1:1000) was prepared by mixing 1 ml from the second dilution with 9 ml of sterilized

saline solution.

For isolation of heavy metals resistant bacteria, chromium, lead, mercury and

copper incorporated nutrient agar media were employed. For this purpose solutions of

different strengths of these metals were prepared to represent a given strength of a metal

ions/100 ml of distilled water. Solutions of varying strengths of the metals were prepared

to represent concentrations ranging from 10 to 350 µg of a given metal ions/ ml of

nutrient agar. Nutrient agar was prepared by dissolving 28 g of the provided medium

(Oxoid) in 900 ml of distilled water. Then to prepare medium of a given strength

appropriate amount of separately autoclaved solution of a given metal and nutrient agar

were allowed to cool around 50 ºC before mixing together and poured to pre-sterilized

petri plates. Details of preparation of nutrient agar media of varying concentrations of the

heavily metals are given in the table 3.1. Initially nutrient agar media containing 100

µg/ml of Hg, Cu, Pb and Cr ions were prepared. Dilutions of the gut contents of the fishes

were then spread on the solidified metal incorporated nutrient agar media. For this

purpose, 0. 1 ml of a given gut content dilution was spread over the surface of about 20

ml solidified metal containing nutrient agar plate. Growth of the bacterial colonies was

observed after 24 hours of incubation at 37 °C. Colony forming unit (CFU) for a given

fish gut content were then calculated as follow.

C.F.U./ml of gut content = factordilutionmlsizeInoculum

platescoloniesofNo

)(

/.


58

Application of 100 µg of metals ions/ ml of media proved too toxic in case of Hg

while excessive bacterial growth appeared for the remaining metals’ ions. This

observation necessitated construction of nutrient agar media of lower and higher

concentrations of Hg and Cu, Pb and Cr ions, respectively. Therefore different dilutions

of the gut contents and concentrations of the metal ions (µg/ml) of the nutrient agar media

were tried till the appearance of bacterial colonies in the range of 30 to 300 per plate for a

given sample were obtained. Data of C.F.U. for a given fish species representing a given

site and flow season were then pooled to calculate mean C.F.U.±SD values.


59

Table 3.1 Different strengths of the salts of respective metals mixed with separately

autoclaved concentrated solution of nutrient agar to prepare media of varying

metals ions’ concentrations.

Metal Salt used Amount of the

salt/100 ml of

distilled water

Amount of the

nutrient agar/900 ml

of distilled water

µg of metal

ions/ ml of

medium

Hg HgCl2

135.36 mg 28 g 100

67.68 mg 28 g 50

40.61 mg 28 g 30

13.54 mg 28 g 10

Cu CuSO4

251.17 mg 28 g 100

502.34 mg 28 g 200

627.93 mg 28 g 250

Cr K2CrO4 373.47 mg 28 g 100

746.94 mg 28 g 200

1120.41 mg 28 g 300

1307.15 mg 28 g 350

Pb Pb(CH3COO)2.3H2

O

183.08 mg 28 g 100

366.16 mg 28 g 200

549.24 mg 28 g 300

640.78 mg 28 g 350


60

3.5.2 Selection and pure culturing of the bacterial isolates:

Following the inoculation of the fishes’ gut contents of the metals containing

nutrient agar media and incubation at 37 ºC for 24 hours, different bacterial colonies were

recognized solely based upon their morphogies. Then of the different types of the

bacterial colonies obtained from gut contents of a given fish species sampled from given

site and during a given flow season, only that/those colonies were selected for pure

culturing and further study which were obtained from all the nine specimen of a given

fish species. For such growths a representative and well isolated colony for each category

from a given metal incorporated nutrient agar plate was picked up with sterilized wire

loop, streaked on the respective metal incorporated nutrient agar medium and incubated at

37 ºC for 24 hours. Colonial characteristics such as configuration, margin, elevation,

surface, colour, size, consistency and opacity were recorded. The isolated and distinct

colonies were sub-cultured by streaking on nutrient agar without metal solution and

incubated at 37 ºC for 24 hours. And then a well separated colony representative of a

given category as streaked again on respective metal incorporated nutrient agar medium

for purification. Restreaking of bacterial growth from nutrient agar to metal containing

medium was accomplished by employing the same concentration of metal ions/ml of the

nutrient agar, on which C.F.U. were measured within the range of 30-300 colonies/plate.

Following the incubation, a well separated representative colony was considered a pure

culture and preserved after cultivating on nutrient agar slant with layering of sterile

paraffin oil for further use.

3.5.3 Determination of minimum inhibitory concentrations (MIC):

In order to determine the maximum resistance of the bacterial isolates, minimum

inhibitory concentrations (MIC) of mercury, copper, lead and chromium were

determined. The bacteria were inoculated to nutrient broths containing different amounts

of the metals’ ions (table 3.2).


61

Table 3.2 Preparation of nutrient broth containing concentrations of the metals’

ions, employed in the experiments of MIC.

Metal

ions

Salt used Amount of the

salt dissolved in

0.9 ml of

distilled water

Amount of

nutrient broth

dissolve in 4 ml

of distilled water

Inoculum µg of the

metal

ions/ml of

medium

Hg2+

HgCl2

0.067 mg 65 mg 0.1 ml 10

0.101 mg 65 mg 0.1 ml 15

0.135 mg 65 mg 0.1 ml 20

0.169 mg 65 mg 0.1 ml 25

0.203 mg 65 mg 0.1 ml 30

0.236 mg 65 mg 0.1 ml 35

0.270 mg 65 mg 0.1 ml 40

0.304 mg 65 mg 0.1 ml 45

0.338 mg 65 mg 0.1 ml 50

0.371 mg 65 mg 0.1 ml 55

0.405 mg 65 mg 0.1 ml 60

0.439 mg 65 mg 0.1 ml 65

0.473 mg 65 mg 0.1 ml 70

0.506 mg 65 mg 0.1 ml 75

Pb2+

Pb(CH3COO)2.

3H2O

3.200 mg 65 mg 0.1 ml 350

4.118 mg 65 mg 0.1 ml 450

5.033 mg 65 mg 0.1 ml 550

5.948 mg 65 mg 0.1 ml 650

6.405 mg 65 mg 0.1 ml 700

6.863 mg 65 mg 0.1 ml 750

7.320 mg 65 mg 0.1 ml 800

7.778 mg 65 mg 0.1 ml 850

8.235 mg 65 mg 0.1 ml 900

8.693 mg 65 mg 0.1 ml 950

9.150 mg 65 mg 0.1 ml 1000

9.608 mg 65 mg 0.1 ml 1050

10.069 mg 65 mg 0.1 ml 1100

10.523 mg 65 mg 0.1 ml 1150

10.980 mg 65 mg 0.1 ml 1200

11.438 mg 65 mg 0.1 ml 1250

11.895 mg 65 mg 0.1 ml 1300

12.353 mg 65 mg 0.1 ml 1350

12.810 mg 65 mg 0.1 ml 1400

Continued……..


62

Metal Salt used Amount of the

salt dissolved in

0.9 ml of

distilled water

Amount of

nutrient broth

dissolve in 4 ml

of distilled water

Inoculum µg of the

metal

ions/ml of

medium

Cu2+

CuSO4 3.138 mg 65 mg 0.1 ml 250

4.393 mg 65 mg 0.1 ml 350

5.020 mg 65 mg 0.1 ml 400

5.648 mg 65 mg 0.1 ml 450

6.275 mg 65 mg 0.1 ml 500

6.903 mg 65 mg 0.1 ml 550

7.530 mg 65 mg 0.1 ml 600

8.158 mg 65 mg 0.1 ml 650

8.785 mg 65 mg 0.1 ml 700

9.413 mg 65 mg 0.1 ml 750

10.040 mg 65 mg 0.1 ml 800

10.668 mg 65 mg 0.1 ml 850

11.299 mg 65 mg 0.1 ml 900

11.923 mg 65 mg 0.1 ml 950

12.550 mg 65 mg 0.1 ml 1000

Cr6+

K2CrO4 6.528 mg 65 mg 0.1 ml 350

8.393 mg 65 mg 0.1 ml 450

10.258 mg 65 mg 0.1 ml 550

12.123 mg 65 mg 0.1 ml 650

13.055 mg 65 mg 0.1 ml 700

13.988 mg 65 mg 0.1 ml 750

14.92 mg 65 mg 0.1 ml 800

15.853 mg 65 mg 0.1 ml 850

16.785 mg 65 mg 0.1 ml 900

17.718 mg 65 mg 0.1 ml 950

18.650 mg 65 mg 0.1 ml 1000

19.583 mg 65 mg 0.1 ml 1050

20.519 mg 65 mg 0.1 ml 1100

21.448 mg 65 mg 0.1 ml 1150

22.38 mg 65 mg 0.1 ml 1200

23.313 mg 65 mg 0.1 ml 1250

24.245 mg 65 mg 0.1 ml 1300

25.178 mg 65 mg 0.1 ml 1350

26.110 mg 65 mg 0.1 ml 1400

27.043 mg 65 mg 0.1 ml 1450

27.975 mg 65 mg 0.1 ml 1500

28.908 mg 65 mg 0.1 ml 1550

29.840 mg 65 mg 0.1 ml 1600

30.773 mg 65 mg 0.1 ml 1650


63

Culture of the bacterial isolates were revived by inoculating a loop full of a given

bacterial isolate’s growth from nutrient agar slant in 5 ml of nutrient broth and incubating

at 37 ºC for 24 hrs. Growth of a given bacterial isolate was then inoculated in the metal

containing broth as shown in table 3.2. The inoculated tubes were incubated at 37 ºC for

24 hrs. Optical densities of the cultures were then determined at 600 nm and compared

with control growth of a given bacterium i.e., in nutrient broth without metal. MIC for a

given bacterial isolate was then determined as the minimum amount of a given metal

ions/ ml which inhibited growth of a given bacterial isolate.

3.5.4 Phenotypic Characteristics of select bacterial isolates:

Out of one hundred and twenty three bacterial isolates, Forty five strains were

selected for genotypic and phenotypic chacterization. They were selected on the basis of

their higher levels of metal tolerance. Thus the isolates which showed growth in the

presence of 750-1000, 1100-1400, 45-70 and 1100-1650 of Cu2+

, Pb2+

, Hg2+

and Cr6+

respectively were processed for their phenotypic and genotypic characterizations and

identification. The select bacterial isolates were also preserved in the form of glycerol

stocks by adding 20 % of sterile glycerol to overnight grown cultures. The glycerol stocks

were deposited to the conservatory of microbial biotechnology laboratory, Department of

Zoology, University of the Punjab, Lahore, Pakistan.

The bacterial isolates from nutrient agar slants were revived in nutrient broth. The

broth cultures were employed for determination of Gram’s reaction, motility (hanging

drop method), endospore, and oxidase and catalse activities according to the procedures

described by Benson (1994). Following is a brief description of the procedures employed

for determination of phenotypic characteristics of the bacteria.

3.5.4.1 Gram Staining:

Smear of a given bacterial culture was made on a labeled and clean glass slide, air

dried and heat fixed. Then crystal violet stain (solution A: 13.87 g of crystal violet

dissolved in 200 ml of 95 % ethanol, solution B: 8 g of ammonium oxalate dissolved in


64

800 ml distilled water. Then solution A and B was mixed and allowed to stand overnight

and then filtered) was applied to this smear for 20 seconds and washed off with distilled

water for 2 seconds. Now Gram’s iodine solution (2g of potassium iodide and 1g of

iodine crystals dissolved in 300 ml of distilled water) was added to the smear and left for

1 minute. This step was followed by the addition of decolorizing agent i.e., 95 % ethanol.

This decolorizing agent was immediately after 10-20 seconds washed off by distilled

water. Lastly, saffranine stain (10 ml of 2.5 % saffranine in 95 % ehanol/100ml of

distilled water) was added for 20 seconds and then the smear washed off by distilled

water (Benson, 1994). Slide was then dried with blotting paper and examined under a

compound microscope.

3.5.4.2 Motility Detection (Hanging drop method):

A small amount of vaseline was placed near each corner of a glass cover slip with

the help of a sterilized tooth pick. Then a small drop of fresh culture with the help of

sterilized loop was placed on centre of the cover slip. Concave depression glass slide was

pressed against vaseline on cover glass slip positioning the culture droplet in center of the

slide cavity and quickly inverted (Benson, 1994). The slide was then examined under a

compound microscope.

3.5.4.3 Endospore Staining:

Bacterial smear was made, air dried and heat fixed. The smear was covered with a

piece of filter paper and saturated it with 0.5 % aqueous solution of malachite green and

the slide was kept over boiling water bath for 5 min. Additional stain was added when

required and after the 5 minutes, the filter paper was removed and the slide allowed to

cool sufficiently. It was then washed with water for 30 sec and subsequently stained with

saffranin (10 ml of 2.5 % saffranin in 95 % ehanol/100ml of distilled water) for 20 sec.

The stained smear was rinsed with distilled water for 10-20 sec. dried with blotting paper

and observed under microscope (Benson, 1994).


65

3.5.4.4 Oxidase Test:

A few drops of freshly prepared oxidase reagent (0.1 g of tetramethyl-p-

phenylenediamine dihydrochloride in 10 ml of distilled water) was added on a piece of

filter paper in a clean Petri plate. Using a glass rod, a colony of the test organism was

removed and smeared on the filter paper. Appearance of purple colour indicated a

positive test (Benson, 1994).

3.5.4.5 Catalase Test:

Three ml of 3 % aqueous solution of H2O2 was taken in a sterilized test tube. With

the help of a glass rod, a sufficient amount of test organism from its colony was removed

and immersed in H2O2 solution. Active bubbling showed a positive test (Benson, 1994).

3.5.5 Bacterial enzymes activities:

The bacteria isolates were recovered from the gut contents of the fishes, to asses

their digestive role for the nutritive material of the fish had in their intestines. The

bacteria were screened for protease, cellulase and amylase activities according to the

following methods;

3.5.5.1 Protease activity:

Protease activity of the selected bacterial isolates was assessed by following the

method of Montville (1983). Protease medium (1 % casein, 1 % gelatin in a solution of

1.5 % agar) was autoclaved in a routine way and then dispensed into sterile petriplates in

an amount of 20 ml/plates. The bacterial isolates were spot inoculated on the petriplates

and incubated at 37 ºC. After 48 hrs, the petriplates were then stained for 15 minutes with

commassie blue R-250 staining solution and destained with destaining solution containing

methanol, acetic acid and water (in ratio of 9:2:9 v/v/v). Protease activity was assessed as

positive for a clear zone around a bacterial colony.

3.5.5.2 Cellulase activity:

Cellulase selective agar medium was prepared according to the composition giver

below (Ogbonna et al., 1994) with slight modification made by Saeed (2005). After


66

autoclaved the medium, it poured into sterilized petriplates as mentioned above. Then

bacterial isolates were inoculated on the plates. Plates were placed in incubator at 37ºC.

After 24 hours of incubation freshly prepared Gram’s iodine solution was added on the

plates. Appearing of the clear zones around bacterial colonies indicated clearance of

cellulose from that region due to the production of cellulase exoenzymes (Kasana et al.,

2008).

Table 3.3 Composition of cellulase selective agar media

Ingredient Quantity (g/100 ml of medium)

Glucose 1.0

NH4H2PO4 5.0

K2HPO4 1.0

NaCl 5.0

MgSo4.7H2O 0.02

Cellulose 10.0

Yeast Extract 5.0

Agar agar 1.5

3.5.5.3 Amylase activity:

To assess the starch hydrolyzing ability of the select bacterial isolates method of

Pommerville (2007) was adapted. Accordingly, 10 % solution of soluble starch has

steamed for 1 hour. Then 20 ml of this solution was added to 100 ml of melted nutrient

agar and poured in sterilized petriplates. The isolates were inoculated on the petriplates

and incubated at 37ºC. After 24 hrs. of the incubation several drops of Gram’s iodine

solution were prepared on to the surface of the starch agar medium. Clear zone in

surrounding a bacterial colony expressed positive results, while blue black colour

approaching a give colony indicated negative results for the exoamylase activity of a

given bacterial colony/isolate.


67

3.5.6 Genotypic identification of the select bacterial isolates:

3.5.6.1 Isolation of genomic DNA:

Three ml overnight incubated (37 ºC) cultures in nutrient broth were used for

isolation of genomic DNA. 1.5 ml culture of a given bacterium was taken in eppendrof

and centrifuged for 5 min. at 13.2 x 103

rpm. Supernatant was discarded and the

remaining 1.5 ml culture was taken in the same eppendrof. After again centrifuging for 5

min. at 13.2 x 103

rpm, the supernatant was discarded. Then 400 µl of CTAB buffer were

added to the pellet. Content were mixed well properly followed by the addition of 150 µl

of solution II and the eppendrof was incubate at 60 ºC for 2 hrs. Then 500 µl of PCI

solution was added and mixed by gentle inverting the eppendrof for 2 minutes and the

contents were centrifuged for 10 min. at 13.2 x 103 rpm. After centrifugation, aqueous

phase (supernatant) was carefully transferred to the fresh labeled eppendrof by avoiding

picking of lower layer (because it contain protein fraction) followed by addition of 300 µl

of absolute ethanol in supernatant, mixed by gentle vortexing and left at room

temperature for 10 minutes and then for 20 minutes at -20 ºC. The eppendrof was then

centrifuged at 13.2 x 103 rpm for 5 minutes and the supernatant was discarded while the

pellet was washed with 1 ml of 70 % ethanol. After centrifugation at 13.2 x 103 rpm for 5

minutes the supernatant was discarded. Pellets in eppendrof was air dried (complete

ethanol removal is necessary for PCR).DNA was re-suspended in 50 µl deionized

distilled water. The contents were mixed properly, vortexing was avoided to save the

DNA from damage or denaturing at this stage.

3.5.6.2 Visualization of the genomic DNA extracts on agarose gel electrophoresis:

Agarose (1 %) was made by heating 1 g of agarose in 100 ml of 0.5x TAE buffer

in a 250 ml flask until the agarose was completely dissolved. Bubbles present in the

solution were removed by gently tapping the flask on table top, and the gel was allowed

to cool down. Meanwhile, the gel comb was adjusted on one side of the gel cassette.


68

When the temperature of the gel was about 55 ºC, ethidium bromide (1 µl/10 ml of gel)

was added and mixed in the gel and the gel was immediately poured in to gel casette.

After solidifying the gel, the comb was carefully removed and the gel cassette was placed

in gel tank. The gel tank was filled with 0.5x TAE buffer till the gel cassette got slightly

dipped under TAE buffer. DNA marker (5 µl) was loaded into the first well of the gel

with the help of micro-pipette. Then 10 µl of a given DNA extract was pipetted out with

the help of micropipette and was placed on a strip of parafilm paper and mixed with 3 µl

of 6x DNA loading dye. The 13 µl mixture was then loaded in a well. After loading all

the samples in the wells, gel tank was connected with power supply taking care that the

negative pole remained towards the wells. The current of battery was adjusted at 70 V and

power supply was switched on. After 30 minutes the power supply was switched off and

the gel removed out from the gel tank. The gel was observed in gel documentation

apparatus under UV and a photograph was taken for keeping in record of DNA bands,

3.5.6.3 16S rDNA gene amplification:

Bacterial 16S rDNA gene was amplified by using the bacterial 16S rDNA

universal primers, 27 forward (AGAGTTTGATCMTGGCTCAG) and 1492 reverse

(TACGG[Y]TACCTTGTTACGACTT). For an amplification of the gene of a given

bacterial isolate a 50 µl reaction mixture was processed with the following condition;

DNA extract as template = 5 µl

10x PCR buffer = 5 µl

25 mM MgCl2 = 5 µl

10 pM forward primer = 5 µl

10 pM reverse primer = 5 µl

1 mM dNTPs = 5 µl

2 U/µl Taq DNA polymerase = 2 µl

dH2O = 18µl

Total reaction volume = 50 µl


69

3.5.6.4 PCR operating programme:

After the initial denaturation for 5 min at 95 ºC, there were 35 cycles consisting of

denaturation at 94 ºC for 45 sec, annealing at 53 ºC for 45 sec, extension at 72 ºC for 1

min and final extension at 72 ºC for 7 min and then the PCR tubes were held at 4 C for

infinite time.

3.5.6.5 PCR product analysis:

PCR products were analyzed by 1 % (w/v) agarose gel containing ethidium

bromide electrophoresis in 0.5x TAE buffer as described above. The PCR products were

loaded along with 3 µl of 6x DNA loading dye.

3.5.6.6 Purification of DNA from Gel Band:

Following the completion of electrophores, the DNA containing fragment of the

gel was excised with the help of a clean scalpel allowing minimizes gel volume to come

with. The gel slice was placed into a pre-weighed 1.5 ml microcentrifuge tube and the

tube was weighed, to record the weight of the gel slice. Then binding buffer was added to

the gel slice in 1:1ratios (volume: weight) e.g. 100 µl of the binding buffer was added to a

100 mg agarose gel slice containing the amplified gene. The gel mixture was incubated at

50-60 °C in an incubator for 10 min or until the gel slice was completely dissolved.

Contents of the tube were mixed by inversion after every few minutes to facilitate the

melting process. Before processing to the next step it was ensured that the gel was

completely dissolved. To the GeneJETTM

purification column, up to 800 µl of the

solubilized gel solution was transferred at a time and the columns were centrifuged for 1

min. The flow through was discarded and the column placed back into the same

collection tube. The process was repeated tilll the whole amount of solublized gel was

purified. Then 100 µl of binding buffer was added to the GeneJETTM

purification column.

After centrifugation for 1 min, the flow through was discarded and the column placed

back into the same collection tube. To the GeneJETTM

purification column, 700 µl of

wash buffer was added and after centrifugation for 1 min, the flow through was discarded


70

and the column placed back into the same collection tube. The GeneJETTM

purification

column was centrifuged for an additional 1 min to completely remove the residual wash

buffer. The GeneJETTM

purification column was transfered into a clean 1.5 ml

microcentrifuge tube. And to the center of the purification column membrane, 25-50 µl

(depending upon weight of the sliced gel and hence the size of amplicon) of Elution

Buffer was added and the column centrifuged for 1 min. Finally, the GeneJETTM

purification column was discarded and the purified DNA stored at -20 °C till further use.

3.5.6.7 Analysis of purified DNA for sequencing the gene:

The Purified DNA was analyzed by 1 % (w/v) agarose gel electrophoresis in 0.5x

TAE buffer with ethidium bromide as described above, to verify purification and to assess

concentration of the amplicons. The purified 16S rDNA amplicons were then sequenced

commercially. The sequenced file obtained from the sequencing facility of CAMB,

Pakistan were then Blast by using NCBI BLAST (www.ncbi.nlm.nih.gov) and the

bacterial isolates were identified on the bases of % similarities to the sequences of

classified bacteria already submitted to the databases.

3.6 Determination of metals’ contents of river water, river bed sediment and the

fishes’ organs

3.6.1 Metals in water samples:

One hundred ml of a water sample, collected from each sub-site of a given

location were transferred in labeled 250 ml volumetric flask for acid digestion by the

method described by Du Preez and Steyn (1992) as modified by Yousafzai and Shakooki

(2008). Accordingly, 5 ml of HNO3 (55 %) were added in each flask and the mixture

evaporated on a hot plate (200-250 °C) to about 20-25 ml. The flask was then removed

from hot plate and cooled to room temperature. Ten ml of perchloric acid (70 %) and 5 ml

of HNO3 (55 %) were added. to the flask and the mixture was heated on the hot plate

(200-250 °C) till the conversion of the dense brown fumes into white fumes which

indicated completion digestion of the sample. During this process addition of few glass

http://www.ncbi.nlm.nih.gov/


71

beads is advisable, especially for the mixtures showing vigorous bunying at the start.The

mixture was evaporated up to the volume of 0.5 ml. Digested water sample of each flask

was cooled and diluted up to 20 ml with distilled water by properly rinsing the digestion

flask. The diluted sample was filted through Whatman No. 541 filter paper. The filtrate

was stored in properly washed labeled vials until the metal concentration could be

determined by atomic absorption spectrophotometer.

3.6.2 Determination of metals content of river bed sediment:

One g of the dried river bed sediment sample were transferred to a labeled 250 ml

volumetric flask for acid digestion according to a method described by Du Preez and

Steyn (1992) with slight modification made by Yousafzai and Shakooki (2008). Add 5 ml

nitric acid (55 %) and 1 ml perchloric acid (70 %) in each flash in fume cupboard as first

dose and samples were kept for overnight at room temperature. Then add 5 ml nitric acid

and 4 ml perchloric acid as a second dose to each flask next day and then few glass beads

were added to prevent pumping. Flasks were placed on hot plate to digest the dried river

bed sediment and evaporated the mixture at 200-250 ºC. Turning of dense brown fumes in

to white fumes escape out from the flask were indicated the completion of digestion

process. Then further evaporate the clear solution up to 0.5 ml clear solution. Digested

sample from each flask were cooled and diluted up to 20 ml with distilled water by

properly rinsing of the digestion flasks and filter by using filter paper Whatman No. 541.

Filtrate were stored in properly labeled vials until the metal concentration could be

determined by atomic absorption spectrophotometer.

3.6.3 Determination of metals contents of different tissues of the fishes:

Frozen fish tissues (gills, scales, intestine, skin) samples were thawed, rinsed in

distilled water and blotted on blotting paper. Then whole eyes, kidney, liver and heart

tissues were shifted into respective labeled pre-weighed glass vials and kept in oven at

105 °C till constant weight for a given tissue whereas only a few scales were process.

While some portions of gills, intestine and skin were acid digested. Weight of each tissue


72

was recorded after cooling the vial in a desiccator. Thus known weight of a given dried

fish tissue samples was digested according to the method and procedural details outlined

above in section 3.6.2 and the filtrates were stored in properly washed labeled vials until

the metal concentration could be determined by atomic absorption spectrophotometer.

3.6.3.1 Metal analysis of the prepared samples on atomic absorption

spectrophotometer:

All the prepared samples (water, sediment and fish tissues) were analyzed for the

metals such as Cd, Cr, Cu, Pb and Ni by using Fast Sequential Atomic Absorption

Spectrometer (Varian Spectra AA-240). While Mn and Fe concentrations were

determined using Pye Unicam Atomic absorption spectrophotometer. Whereas the Hg

and Zn were measured using variant atomic absorption spectrophotometer (variant AAS-

1275). For each element (1000 μg/ml; single standard solution of Cd, Cr, Cu, Fe, Hg, Mn,

Ni, Pb and Zn A. R., 99.9 %) were purchased from BDH (England). Different diluted

working standard solutions were prepared stepwise from the stock solution (1000 μg/ml).

Standard curves were prepared for different metals between working standard solutions

concentration verses their corresponding absorbances (optical density). Optical density

(OD) of samples (water, sediment and fish tissues) were calibrated against the standard

curves to find out the concentration of metals present in the analyzed samples. Metal

concentration were expressed in mg/l for water and mg/kg for sediment and the fish

tissues.

3.6.4 Transport of fish muscles for ICP analysis to UK:

Frozen fish muscle samples were transported in dry ice to the Newcastle

University, UK by the prior authorization of the secretary of State for DEFRA under

regulation 4, products of Animals Origin Regulation in July, 2011. Muscles samples were

stored at -20 °C on arrival and processed for freeze drying and ground after few days.


73

3.6.4.1 Sample preparation for determination of metals and minerals contents of the

fishes’ muscles by ICP-OES:

All activities regarding sample preparation were done in a fume cupboard. One g of

ground freeze dried muscle sample and 10 ml of 55 % nitric acid (trace metal grade,

purchased from Fisher scientific (Loughborough,UK) were shifted in volumetric flasks

(250 ml) and kept for overnight at room temperature. Next day, flasks were placed on hot

plate to digest the tissues. Each sample mixture was evaporated at 200-250 ºC until a

clear solution was obtained. The solution was then evaporated up to 0.5 ml. Emergence of

dense white fumes after brown fumes from the flask indicated completion of the digestion

process. The digested samples were cooled and diluted up to 10 ml with distilled water by

properly rinsing the digestion flasks and filtered through Whatman filter paper 1. Finally,

the solution filtrate was transferred into plastic screw-cap container (20 ml) and put in a

refrigerator until ICP analysis. All muscle samples were analyzed for macro (Na, K, P,

Ca, Mg) and trace (Cd, Cr, Cu, Pb, Mn, Ni, Zn and Fe) elements by using ICP and

reported in milligram per kilogram dry weight.

3.6.4.2 Standard solutions and preparation:

Ca, Zn, Ni, Cu solutions (May & Baker Ltd, UK), Mg (NO3)2, Mn (NO3)2, Fe

(NO3)2, Pb (NO3)2 solutions, Cd (Cadmium coarse powder), Cr (chromium (III) chloride

95%), Na (sodium chloride 99.5%) (BDH chemicals, UK), P (sodium phosphate ≥99%)

(Sigma-Aldrich, Gillingham, UK), BDH chemicals, UK), K (potassium chloride 99.8%)

(Fisher Scientific, Loughborough, UK) were used to prepare standard solutions. The

standard stock (1000 ppm) solutions were diluted into different concentrations. After

determining the optical density of each standard solution’s dilutions by ICP-OES

machine, standard curves were calibrated on ICP Expert software integrated into the

machine.


74

3.6.4.3 Sample analysis – ICP:

A Varian Vista-MPX CCD Inductively coupled plasma optical emission

spectroscopy (ICP-OES Varian Inc, Australia) machine integrated to ICP Expert software

installed in a computer was calibrated over the relevant concentrations of individually

certified standards before sample analysis. Most of the setting was controlled

automatically by the softwares.

Table 3.4 ICP-OES operational settings during analysis of muscle samples

Parameter Plasma

(L/min)

Auxiliary

gas

(L/min.)

Mass flow

controller

MFC

(L/min.)

Power

(KW)

Pump

(rpm)

Time

(sec.)

Purge 22.5 2.25 0.9 0,0 0 15

Delay 22.5 2.25 0.0 0.0 0 10

Ignite 1.5 1.50 0.0 2.0 50 5

Run 15.0 1.50 0.9 1.2 7 5


75

3.7 Fatty acid analysis of muscle and skin tissues of the fishes:

3.7.1Chemicals:

Methanol:toluene:

Methanol:toluene solution was prepared in a ratio of 4:1 v/v. Thus 400 ml of

methanol and 100 ml of toluene were measured in separated volumetric cylinders,

transferred into a labelled glass Duran bottle which was tightly closed and stored at room

temperature.

Potassium chloride:

Five % potassium chloride (KCl; >99%; Sigma-Aldrich, Gillingham, UK)

solution in distilled water was used. To prepare the solution, 50g of potassium chloride

were weighed and diluted in water using a 1L volumetric flask. The mixture was stirred

on a magnetic stirrer for 30 min. at room temperature to ensure complete dissolution of

the KCl.

Acetyl chloride:

Acetyl chloride was purchased from Fisher Scientific (Loughborough, UK)

52 fatty acid methyl esters (FAME) standards:

A 52 FAME standards (GLC-463, 100mg) was purchased from Nu-Check Prep,

Inc. Minnesota, USA. The ampule containing 100 mg of 52 FAMEs standard was

centrifuged to ensure the recovery of the standard and then 1ml of hexane was added to

the ampule. This gave the concentration of individual FAME in the standard ranging from

1 – 4 %. Next, a 100 µl of the standard in hexane was transferred into a screw-cap brown

vial (0.3 ml gewindflasche fixed insert-amber, VWR UK) and dried under nitrogen

pressure to remove the hexane. After that, 200 µl of toluene was added into the vial and

processed used for standard analysis.


76

25.0 30.0 35.0 40.0 45.0 50.0 min

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

2.25uV(x1,000)

0

50

100

150

200

250

300

350

400

C

Column Temp.(Setting)Chromatogram

25

.67

1

30

.81

6

35

.52

7

40

.40

8

43

.46

64

3.8

57

44

.84

2

47

.84

6

49

.32

0

Continued………..


77

52.5 55.0 57.5 60.0 62.5 65.0 min

-0.25

0.00

0.25

0.50

0.75

1.00

1.25

uV(x10,000)

0

50

100

150

200

250

300

350

400

C


52

.18

7

53

.40

6

55

.62

2

57

.43

3

59

.58

2

61

.17

3

62

.21

9

62

.78

8

64

.79

8

66

.39

0



78

70.0 72.5 75.0 77.5 80.0 82.5 min

0.00

0.25

0.50

0.75

1.00

uV(x10,000)

0

50

100

150

200

250

300

350

400

C


68

.25

6

69

.04

66

9.2

32

69

.53

26

9.8

61

70

.59

1

71

.64

47

1.8

73

72

.77

7

73

.59

5

75

.04

9

75

.46

2

76

.42

2

76

.85

87

7.1

86

80

.53

1

82

.73

0



79

82.5 85.0 87.5 90.0 92.5 95.0 min

0.0

1.0

2.0

3.0

4.0

5.0

6.0

uV(x1,000)

0

50

100

150

200

250

300

350

400

C


82

.73

0

84

.14

88

4.4

40

84

.67

8

86

.50

4

87

.86

7

89

.42

3

92

.63

3

94

.19

4

95

.90

6

96

.84

8

Fig. 3.6 Peaks of Standards used for quantification of muscle fatty acid profile


80

3.7.2 Analysis of samples’ fatty acids:

Total crude fat from freeze dried muscles of the fishes was extracted as describe in

section 3.3.4. The already extracted crude fat of the muscle tissue was employed for the fatty

acid analysis. Crude extract fat of each sample was used for the analysis of fatty acids. Fatty

acids were extracted and derivatised from the fat samples by using a modified version of the

method described by Sukhija and Palmquist (1988) and followed by Jabeen and Chudhry

(2011). A given fat sample in extraction flask was thawed with 1 ml of toluene and vortexed

by using personal biovortex V-1 plus (peQLab,UK). Then 0.5 ml toluene fat mixture was

taken into a soveril tube (washed with DeCon 90 and left for dry). About 1.7 ml of methanol:

toluene (4:1) solution was added and then the contents were vortex mixed. Then 250 μ l

acetyl chloride was added very slowly in the fume cupboard using a gilson pipette. The

samples were vortexed again for 30 sec. and the tubes were placed in a heating block

(Techne Dri BlockR BD-3D) at 100°C for one hour. After that the samples were then

removed from the heating block and left to cool for 20 min before adding 5 ml of 5 %

potassium chloride solution. These tubes were then gently shake before centrifugation at

1000 g for 5 min at 4°C. The top layer/supernatant (FAME) was then removed from each

tube carefully using a Gilson pipette and transferred to a brown glass vial with a glass insert

(Chromacol Ltd., Hertfordshire). These vials were refrigerated (4 °C) until the samples were

analysed by gas chromatograph

3.7.3 Gas Chromatograph analytical procedure:

Analysis of fatty acid methyl esters was carried out with a GC (Shimadzu, GC-2014, Kyoto,

Japan) using a Varian CP-SIL 88 fused silica capillary column (30m x 0.25 mmlD x 0.25 μ

film thickness). Purified helium was used as a carrier gas with a head pressure of 109.9 KPa

and a column flow of 0.31 ml/min. FAME peaks were detected by flame ionization detection

(FID). A split injection system was used with an auto injector (Shimadzu, AOC-20i) with a


81

split ratio of 89.9 and an injector temperature of 250 °C. The detector temperature was 275

°C. one μl of a sample was injected at an initial temperature of 50 °C which was held for 1

min. The column temperature was then raised at a rate of 2 °C/min to 188 °C where it was

held for 10 min. The temperature was then increased at the same rate to 240 °C where it was

held for 44 min, giving a final gradient with a 150 min total run time and then returned to the

initial temperature as shown in the following table.

Table 3.5 GC gradient for separation and quantification of fatty acids

Rate (°C/min) Temperature (°C) Holding (min)

- 50 1

2 188 10

2 240 44

Total runtime 150 minutes

3.7.4 Fatty acid identification:

The fatty acids methyl esters (FAMEs) were identified by comparing the retention time of the

samples appropriately with 52 standards’ fatty acids’ methyl esters. The relative percentage

of the area was obtained by using the following equation;

Z = 100Y

X

Where Z = % of the fatty acid quantified

X = Peak area of the quantified fatty acid methyl ester

Y= Total peaks areas of all the individual fatty acids chromatogram

3.8 Statistical analysis:

The data were statistically analysed by using general linear model in Minitab software

to find the effect of either site or season or site x season interaction. The effect of these

factors were declared highly significant if P <0.001, very significant if P<0.01 and significant

if P<0.05. Turkey’s post-hoc test was used if there were more than two means to compare for

their significant differences at P< 0.05.

Chapter 4 Results

82

RESULTS

4.1 Physico-chemical parameters of the river waters at four sampling localities:

Mean values of various physico-chemical parameters of waters sampled from the

four localities of the Lahore stretch of river Ravi during high as well as low flow seasons

are presented in table 4.1. All the parameters showed highly significant (P<0.001)

difference between seasons and along stream sites. Mean highest temperature (24.23 °C),

total dissolved solids (692 mg/l), total suspended solids (802 mg/l), nitrite (5.80 mg/l),

nitrate (8.30 mg/l), phosphate (7.24 mg/l), chloride (232.98 mg/l), ammonia (1.08 mg/l)

and sulphate (821.33 mg/l) were measured at site C. All the parameters showed higher

values during the low flow than high flow season, except temperature and dissolved

oxygen (table.4.1). The parameters, except temperature, dissolved oxygen, total

alkalinity, Ca, Mg and total harnesses, and ammonia showed site x season interaction

downstream to the confluence of effluent drains and urban sewage to the river (table 4.2).

Furthermore, all the parameters, except total suspended solids and sulphate, fell within

permissible ranges of National Environmental Quality Standard (NEQS) for municipal

and liquid industrial effluents in Pakistan.

Mean water temperature ranged from 24.10 to 24.93 °C downstream during high

flow and 22.87 to 23.53 °C during low flow season. The site C showed maximum

temperature (24.93 °C) during high flow season. The water temperature increased at site

B (1.88 and 2.37 %), C (2.89 and 3.44 %) and D (-0.17 and 1.37 %) during low and high

flow season in comparison with water temperature at site A (Fig. 4.2). Dissolved oxygen

decreased up to 3.8 mgO2/l at site C during low flow. Dissolved oxygen decreased at site

Chapter 4 Results

83

B (17.78 and 14.34 %), C (27.34 and 22.35 %) and D (21.03 and 18.06 %) during low

and high flow seasons as compared with site A (less polluted site). However, its values at

site A (upstream) were not significantly different at both seasons. Total dissolved solids

(TDS) significantly varied downstream and showed higher values during low than the

high flow season. The highest value of TDS up to 948 mg/l at site C was 63 % higher in

comparison with that of the upstream location A during low flow. Lowest total suspended

solid (TSS) material with a value of 213.0 mg/l was recorded at site A during low flow,

while highest value of the parameter (908 mg/l) was found for the site C during high flow

season (Fig. 4.1). These values are much higher than the recommended value of 150 mg/l

by NEQS. Total alkalinity (239.7 to 318 mg/l and 176.3 to 253.7 mg/l) and hardness

(210.3 to 306.7 mg/l and 156.3 to 271.3 mg/l) significantly increased at downstream

locations during both low and high flow seasons, respectively than the corresponding

values for the upstream location A (table 4.2, Fig. 4.1). Nitrite and nitrate contents

increased among the downstream sites during low flow as compared to high flow season.

The nitrite content for the site C appeared 90 % higher than the value obtained for the site

B during low flow season. The nitrite contents increased at site B (229 and 290 %), C

(524 and 771 %) and D (388 and 617 %) during low and high flow seasons when

compared with the corresponding nitrite contents of water sampled from site A during

low and high flow seasons, respectively. Furthermore, the nitrate contents of the water

samples were, in general, higher than their nitrites. Phosphate contents increased along

the downstream sampling sites. So that at site B, C and D the elevations were 304 and

530 %, 421 and 830 % and 66 and 197 % respectively during low and high flow seasons

in comparison with corresponding values for the site A. Phosphate, chloride and ammonia

at site C during low flow showed 421 %, 353 % and 259 % increases, respectively over

the respective values for the site A (Fig. 4.2). Sulphate contents were higher in waters

sampled at site C (60.6 %) and D (31.8 %) during low flow as compared to the value of

Chapter 4 Results

84

600 mg/l proposed by NEQS. The parameter, however, did not significantly differ during

low and high flow seasons but at the site A (table 4.2).

Chapter 4 Results

85

Table 4.1 Means (mg /L, unless mentioned otherwise) of physico-chemical parameters of waters with their standard error of means

and significance of different alongstream sites and flow seasons of the river.

Physico-chemical parameters Temp. (ºC) DO TDS TSS TA Ca-hd. Mg-hd T. hd

Sampling sites

Site A: (Siphon Control) 23.48c 5.30

a 372.3

d 283.5

d 208.0

d 132.5

c 50.83

c 183.3

d

Site B: (Shahdera) 23.98b

4.47b

470.7c 494.0

c 230.5

c 150.7

c 57.00

b 207.7

c

Site C: (Sunder) 24.23a

3.98d

692.3a

802.0a

256.7b

175.0b

61.00b 236.0

b

Site D: (Head Balloki) 23.63c

4.27c

550.7b

638.2b 285.8

a 220.2

a 68.83

a 289.0

a

SEM and Significance 0.049*** 0.031*** 10.203*** 8.025*** 3.224*** 3.798*** 1.349*** 4.310***

Flow Seasons

High 24.53a 4.64

a 307.1

b 640.3a 214.1

b 149.4

b 54.83

b 204.2

b

Low 23.13b

4.37b 735.9

a 468.6

b 276.4

a 189.8

a 64.00

a 253.8

a


Values within the same column earmarked with same superscripit did not differ significantly from each other (P>0.05)

Here *,** and *** represent significance at P<0.05, P<0.01 and P<0.001 respectively (Minitab 16 General linear model)

Abbreviations:

Temp.: Temperature,

DO: Dissolved oxygen,

TDS: Total dissolves solid

TSS: Total suspended solid

TA: Total alkalinity

Ca-hd: Ca hardness

Mg-hd: Mg hardness

T. hd: Total hardness

Continued……………..

Chapter 4 Results

86

Physico-chemical parameters Nitrite Nitrate Phosphate Chloride Ammonia Sulphate

Sampling sites

Site A: Siphon (Control) 0.83d 2.75

d 1.13

d 46.35

d 0.28

d 357.92

d

Site B: Shahdera 2.88c

6.37c 5.31

b 133.48

c 0.67

b 567.00

c

Site C: Sunder 5.80a

8.30a 7.24

a 232.98

a 1.08

a 821.33

a

Site D: Head Balloki 4.63b

7.47b 2.31

c 174.13

b 0.47

c 705.25

b

SEM and Significance 0.106*** 0.130*** 0.141*** 3.495*** 0.020*** 12.300***

Flow Seasons

High 2.75b

4.02b 3.23

b 110.25

b 0.53

b 528.83

b

Low 4.31a

8.42a 4.77

a 183.23

a 0.71

a 696.92

a




Chapter 4 Results

87

Table 4.2 Means (mg /L, unless otherwise mentioned) of physico-chemical parameters of the river waters sampled from different

alongstream sites (Siphon (upstream =A); Shahdera =B; Sunder =C; and Head balloki =D) during Low and High flow seasons.

Sites

Seasons

A B C D SEM With Significance

Low High Low High Low high Low High

Physico-chemical Parameters Temperature (ºC) 22.87

e 24.10

c 23.30

d 24.67

ab 23.53

d 24.93

a 22.83

e 24.43

b 0.068

Dissolved oxygen 5.23a 5.37

a 4.30

c 4.63

b 3.80

f 4.17

e 4.13

e 4.40

d 0.044

total dissolve solid 580.0c 164.7

g 674.7

b 266.7

f 948.0

a 436.7

d 741.0

b 360.3

e 14.429**

total suspended solid 213.0f 354.0

e 424.0

d 564.0

c 695.3

b 908.7

a 542.0

c 734.3

b 11.349*

total alkalinity 239.7cd

176.3f 259.7

c 201.3

e 288.3

b 225.0

d 318.0

a 253.7

c 4.560

Ca hardness 156.3cd

108.7e 170.3

c 131.0

de 198.0

b 152.0

cd 234.3

a 206.0

b 5.371

Mg hardness 54.00cd

47.67d 62.33

bc 51.67

d 67.33

ab 54.67

cd 72.33

a 65.33

ab 1.908

total hardness 210.3cd

156.3e 232.7

c 182.7

de 265.3

b 206.7

cd 306.7

a 271.3

b 6.095

Nitrite (NO2) 1.12f

0.53f

3.68d 2.07

e 6.98

a 4.62

c 5.47

b 3.80

d 0.149***

Nitrate (NO3) 3.86f

1.63g 8.62

c 4.12

ef 11.17

a 5.43

d 10.05

b 4.88

de 0.183***

Phosphate 1.60ef 0.66

f 6.46

b 4.16

c 8.34

a 6.14

b 2.66

d 1.96

de 0.200**

Chloride 63.20f 29.50

g 167.47

c 99.50

e 286.17

a 179.80

c 216.07

b 132.20

d 4.943***

Ammonia 0.34ef 0.22

f 0.75

c 0.60

d 1.22

a 0.94

b 0.55

d 0.36

e 0.027

Sulphate (SO42-

) 386.67e 329.17

e 646.33

c 487.67

d 963.67

a 679.00

c 791.00

b 619.50

c 17.392***

Values within the same rows earmarked with same superscripit did not differ significantly from each other (P>0.05)


Chapter 4 Results

88

22

23

24

25

26

A B C D

Sampling SitesT

emp

erat

ure

(°C

)

Low Flow High Flow

3

3.5

4

4.5

5

5.5

6

A B C DSampling Sites

Dis

solv

e o

xy

gen

(m

g/l

)

Low Flow High Flow

100

250

400

550

700

850

1000

A B C D

Sampling Sites

To

tal

dis

solv

e so

lid

(m

g/l

)

Low Flow High Flow

100

250

400

550

700

850

1000


To

tal

Su

spen

ded

So

lid

(mg

/l)

Low flow High Flow

150

200

250

300

350


To

tal

alk

alin

ity

(m

g/l

)

Low Flow High Flow

50

100

150

200

250


Ca

har

dn

ess

(mg

/l)

Low Flow High Flow

40

50

60

70

80


Mg

Har

dn

ess

(mg

/l)

Low Flow High Flow

100

150

200

250

300

350


To

tal

har

dn

ess

(mg

/l)

Low Flow High Flow

Continued……..

Chapter 4 Results

89

0

1.5

3

4.5

6

7.5

A B C DSampling sites

Nit

rite

(m

g/l

)

Low Flow High Flow

0

2

4

6

8

10

12


Nit

rate

(m

g/l

)

Low Flow High Flow

0

2

4

6

8

10


Ph

osp

hat

e (m

g/l

)

Low Flow High Flow

0

50

100

150

200

250

300

A B C D

Sampling Sites

Ch

lori

de

(mg

/l)

Low Flow High Flow

0

0.3

0.6

0.9

1.2

1.5

A B C D

Sampling Sites

Am

mo

nia

(m

g/l

)

Low Flow High Flow

0

200

400

600

800

1000

A B C D

Sampling Sites

Su

lph

ate

(mg

/l)

Low Flow High Flow

Fig. 4.1 Means±SD of physico-chemical parameters of the river waters sampled

from different alongstream sites (Siphon (upstream) =A; Shahdera =B; Sunder =C;

and Head balloki =D) during low and high flow seasons of the river Ravi.

Chapter 4 Results

90

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

B C D

Sampling Sites

Tem

per

ature

Low Flow High Flow

-30%

-25%

-20%

-15%

-10%

-5%

0%B C D

Sampling sites

Dis

solv

e o

xy

gen

Low flow High flow

0%

50%

100%

150%

200%

B C D

Sampling Sites

To

tal

dis

solv

ed

so

lid

Low flow High flow

0%

50%

100%

150%

200%

250%

B C D

Sampling Sites

Tota

l S

usp

ended

Solid

Low flow High flow

0%

10%

20%

30%

40%

50%

B C D

Sampling Sites

Tota

l al

kal

inity

Low flow High flow

0%

20%

40%

60%

80%

100%

B C D

Sampling Sites

Ca

har

dnes

s

Low flow High flow

0%

10%

20%

30%

40%

B C DSampling Sites

Mg

hard

ness

Low Flow High Flow

0%

20%

40%

60%

80%

B C D

Sampling Sites

Tota

l H

ardnes

s

Low Flow High Flow

Continued……………..

Chapter 4 Results

91

0%

200%

400%

600%

800%

B C D

Sampling Sites

Nitri

te

Low Flow High Flow

0%

50%

100%

150%

200%

250%

B C D

Sampling Sites

Nit

rate

Low Flow High Flow

0%

200%

400%

600%

800%

B C D

Sampling Sites

Phosp

hat

e

Low Flow High Flow

0%

200%

400%

600%

B C D

Sampling Sites

Ch

lori

de

Low Flow High Flow

0%

100%

200%

300%

400%

B C D

Sampling Sites

Am

monia

Low Flow High Flow

0%

50%

100%

150%

B C DSampling Sites

Su

lph

ate

Low Flow High Flow

Fig. 4.2 Percent difference of physico-chemical parameters of the river waters

sampled from downstream sites (Shahdera =B; Sunder =C; and Head balloki =D)

from the corresponding values of water sampled from upstream site = Siphon (A)

during low and high flow seasons of the river Ravi.

Chapter 4 Results

92

4.2 Biometric data of the sampled fish species:

4.2.1 Length and weight of specimen:

Table 4.3 presents total length and wet weight data, which were not significantly

different (P>0.05) at different sites (A, B, C and D) and flow seasons. Significance

differences (P<0.001) were observed for total length among the fish species. Mean weights

ranged from 636 to 650 g and 650 to 665 g for C. mrigala; 627 to 649 g and 634 to 647 g for

L. rohita, and 621 to 641 g and 633 to 643 g for C. catla during high and low flow seasons,

respectively. Mean total lengths ranged from 39.5 to 40.3 cm and 39.5-40.2 cm in C.

mrigala; 37.7 to 38.1 cm and 37.4 to 39.5 cm in L. rohita, and 36.5 to 36.8 cm and 36.7 to

37.2 cm in C. catla during low and high flow seasons, respectively (table 4.3). High degree

of correlation between total lengths and weights of all three fish species was indicated by

their higher values of correlation coefficient (r). Values of ‘r2’ approaching the digit 1

depicted high precision in regression equations (Table 4.5, Fig 4.3-4.14). Growth coefficient

(b) ranged from 3.08 to 3.19 and 3.07 to 3.16 for C. mrigala; 3.08 to 3.21 and 3.06 to 3.17

for L. rohita, and 3.03 to 3.16 and 3.01 to 3.11 for C. catla during high and low flow seasons,

respectively. In the present study, ‘b’ measured highest upto 3.19 and 3.16 for C. mrigala;

3.21 and 3.17 for L. rohita and 3.16 and 3.11 for C. catla at site A (upstream) during high

and low seasons, respectively. While lowest values for the corresponding fish species i.e.

3.08 and 3.07, 3.08 and 3.06, and 3.03 and 3.01 appeared at site C during high and low flow

seasons, respectively (Table 4.5, Fig. 4.3-4.14)

Condition factor (K) significantly differed for differences in fish species, sites and

seasons. The factor values were 1.00, 1.16 and 1.24 for C. mrigala, L. rohita and C. catla,

respectively (Table 4.3). Mean ‘K’ range was found to be greater than 1 for L. rohita (1.03-

1.18 g/cm3) and C. Catla (1.19-1.27 g/cm

3) but for C. mrigala ‘K’ fluctuated between 0.97 to

1.05 g/cm3 during both low and high flow seasons (table 4.5).

Chapter 4 Results

93

4.2.2 Morphometeric study of the sampled fish species:

Results of morphometric parameters of the fish species sampled from four selected

sampling sites during low and high flow seasons are represented in tables 4.6. All the

morphometric parameters did not differ significantly among sampling sites and the two flow

seasons. While regarding the comparison among the fish species, all the parameters except

pectoral fin length (PFL), differed significantly (P<0.001).

C. mrigala was highest in standard length (33.02 cm), post orbital length (32.99 cm),

dorsal fin length (6.93 cm) but lowest in eye diameter (1.05 cm) and mouth gap (1.73 cm).

Whereas L. rohita was highest in pectoral fin length (6.00 cm) and caudal fin length (7.75

cm) but lowest in mouth width (2.16), dorsal fin length (6.36 cm), pelvic fin length (4.91 cm)

and anal fin length (5.02 cm). C. catla was highest in head length (8.74 cm), eye diameter

(1.25 cm), mouth width (3.38 cm), mouth gap (3.14 cm), pelvic fin length (6.08 cm), anal fin

length (6.31 cm) and caudal fin length (9.81 cm) but lowest in standard length (27.43 cm),

post orbital length (26.22 cm) and pectoral fin length (5.91 cm) (Table 4.6).

Standard lengths ranged from 32.20 to 33.98 cm in C. mrigala, 30.12 to 30.97 cm in

L. rohita and 27.0 to 27.81 cm in C. catla. Post orbital lengths spanned from 32.43 to 33.44

cm in C. mrigala, 30.42 to 31.19 cm in L. rohita and 25.83 to 26.57 cm in C. catla.

Whilehead lengths ranged from 6.68 to 6.81 cm in C. mrigala, 6.60 to 6.78 cm in L. rohita

and 8.38 to 9.19 cm in C. catla. Eye diameters measured from 1.05-1.07 cm in C. mrigala,

1.08 to 1.16 cm in L. rohita and 1.24 to 1.26 cm in C. catla. Mouth widths ranged from 2.84

to 2.92 cm,, 2.08 to 2.26 cm and 3.19 to 3.5 cm in C. mrigala, L. rohita and C. catla

respectively (table 4.7). Mouth gaps measured from 1.71 to 1.75 cm, 1.72 to 1.97 cm and

2.92 to 3.24 cm in C. mrigala, L. rohita and C. catla respectively. Dorsal fin lengths ranged

from 6.87 to 7.0 cm in C. mrigala, 6.29 to 6.42 cm in L. rohita and 6.47 to 6.60 cm in C.

catla. Pectoral fin lengths spanned from 5.84 to 6.03 cm in C. mrigala, 5.89 to 6.14 cm in L.

Chapter 4 Results

94

rohita and 5.8 to 5.99 cm in C. catla. Pelvic fin length 5.41 to 5.64 cm, 4.67 to 5.19 cm and

6.02 to 6.14 cm in C. mrigala, L. rohita and C. catla, respectively. Anal fin lengths 5.6 to

5.81 cm in C. mrigala, 4.86 to 5.33 cm in L. rohita and 6.26 to 6.38 cm in C. catla. Caudal

fin lengths spanned from 6.27 to 7.43 cm in C. mrigala, 7.58 to 7.84 cm in L. rohita and 9.32

to 10.34 cm in C. catla. Values of all the morphomeric parameters were higher during low

flow than high flow season for all species but site x season x species interaction were non

significant (table 4.7).

Chapter 4 Results

95

Table 4.3 Means of weight, total length and condition factor with their standard error

of means (SEM) and significance of the different alongstream sites, flow seasons and

sampled species.

Weight

(W) g

Total Length

(TL) cm

Condition Factor (K)

g/cm3

Sampling sites

Site A: Siphon (Control) 636a

38.26a

1.11b

Site B: Shahdera 643a

38.24a

1.13b

Site C: Sunder 647a

38.02a

1.15a

Site D: Head Balloki 637a

38.06a

1.13ab

SEM and Significance 24.812 0.491 0.007***

Seasons

High flow 637a

38.13a

1.12b

Low flow 645a

38.16a

1.14a

SEM and Significance 17.545 0.347 0.005*

Species

Cirrhinus mrigala 651a

39.91a

1.00c

Labeo rohita 637a

37.68b

1.16b

Catla catla 634a 36.84

b 1.24

a

SEM and Significance 21.488 0.425*** 0.006***

Values within the same column earmarked with same superscripit did not differ significantly

from each other (P>0.05)

Here *,** and *** represent significance at P<0.05, P<0.01 and P<0.001 respectively

(Minitab 16 General linear model)

Chapter 4 Results

96

Table 4.4 Means of weight, total length and condition factor with their standard error of means (SEM) and significance of

the sampled fish species from different alongstream sites (Siphon (upstream =A); Shahdera =B; Sunder =C; and Head

balloki =D) during low and high flow seasons.

Sites A B C D SEM With Significance

Seasons Low High Low High Low High Low High Site x Season

Cirrhinus mrigala

Biometric Data Weight 650

a 650

a 665

a 636

a 662

a 649

a 652

a 643

a 60.778

Length 40.31a

40.16a 39.94

a 39.84

a 39.49

a 39.46

a 40.19

a 39.89

a 1.203

Condition Factor 0.97c 0.98

bc 1.02

abc 0.98

bc 1.05

a 1.03

ab 0.98

bc 0.99

bc 0.016

Labeo rohita


a 627

a 645

a 636

a 647

a 641

a 636

a 628

a 60.778

Length 37.72a

37.61a

38.09a

37.53a

37.69a

37.60a

37.71a

37.44a

1.203

Condition Factor 1.15a

1.15a

1.14a

1.17a

1.18a

1.18a

1.16a

1.17a

0.016

Catla catla


a 621

a 639

a 638

a 643

a 641

a 634

a 627

a 60.778

Length 36.73a

37.03a

36.78a 37.22

a 36.72

a 37.13

a 36.48

a 36.66

a 1.203

Condition Factor 1.24ab

1.19b

1.25ab

1.21b

1.27a

1.22ab

1.27a

1.24ab

0.016

Values within the same rows earmarked with same superscript did not differ significantly from each other (P>0.05)


Chapter 4 Results

97

Table 4.5 Weight vs total length regression equations with significance for three sampled fish species from four sampling

sites (Siphon (upstream =A); Shahdera =B; Sunder =C; and Head balloki =D) during low and high flow seasons of the

river. Site Flow

Season

Weight (g) Range

(Mean± SEM)

Length (cm) Range

(Mean± SEM)

Condition factor (K) g/cm3

Range (Mean± SEM)

Regression equation

Log W=Loga + bLogL

Exponential

equation Wt=a(TL)b

R P

Cirrhinus mrigala

A Low 413-965 (650±61.3) 34.5-45.2 (40.3±1.19) 0.92-1.04 (0.97±0.014) Log W = - 2.28 + 3.16Log L Wt = 0.00531(TL)

3.16 0.980 <0.001

High 358-903 (650±62.0) 33.3-44.9 (40.2±1.26) 0.91-1.03 (0.98±0.012) Log W = - 2.31 + 3.19Log L Wt = 0.00485(TL)3.19

0.990 <0.001

B Low 410-917 (665±61.8) 34.2-44.9 (39.9±1.22) 0.93-1.07 (1.02±0.013) Log W = - 2.20 + 3.13Log L Wt = 0.00628(TL)

3.14 0.985 <0.001


0.982 <0.001

C Low 409-935 (662±63.1) 33.5-44.3 (39.5±1.25) 0.98-1.10 (1.05±0.013) Log W = - 2.10 + 3.07Log L Wt = 0.00800(TL)

3.07 0.985 <0.001


0.995 <0.001

D Low 369-907 (652±64.4) 33.9-44.5 (40.2±1.30) 0.88-1.05 (0.98±0.016) Log W = - 2.24 + 3.14Log L Wt = 0.00581(TL)

3.14 0.975 <0.001


0.990 <0.001

Labeo rohita


3.17 0.985 <0.001


0.952 <0.001


3.15 0.989 <0.001


0.971 <0.001


3.06 0.989 <0.001


0.995 <0.001


3.11 0.985 <0.001


0.948 <0.001

Catla catla


3.11 0.984 <0.001


0.988 <0.001


3.08 0.988 <0.001


0.990 <0.001


3.01 0.986 <0.001


0.993 <0.001


3.05 0.960 <0.001


0.993 <0.001

Chapter 4 Results

98

y = 3.1624x - 2.2749

R2 = 0.9804

2.60

2.68

2.76

2.84

2.92

3.00

1.53 1.55 1.57 1.59 1.61 1.63 1.65log L (cm)

log

W (

g)

y = 3.1895x - 2.314

R2 = 0.9904

2.54

2.63

2.72

2.81

2.90

2.99

1.51 1.54 1.57 1.60 1.63 1.66Log L (cm)

Lo

g W

(g

)

Fig. 4.3 Relationship between log Length (cm) and log wet weight (g) in Cirrinus

mrigala sampled from sampling site = A (Siphon) upstream during low (left side) and

high (right side) flow seasons.

y = 3.1309x - 2.202

R2 = 0.9853

2.60

2.69

2.78

2.87

2.96

1.52 1.55 1.58 1.61 1.64 1.67log L (cm)

log

W (

g)

y = 3.1707x - 2.2823

R2 = 0.982

2.56

2.63

2.70

2.77

2.84

2.91

2.98

1.52 1.56 1.60 1.64Log L (cm)

Lo

g W

(g

)


mrigala sampled from sampling site = B (Shahdera) during low (left side) and high

(right side) flow seasons.

Chapter 4 Results

99

y = 3.0734x - 2.0967

R2 = 0.9848

2.59

2.67

2.75

2.83

2.91

2.99

1.52 1.56 1.60 1.64log L (cm)

log

W (

g)

y = 3.0831x - 2.119

R2 = 0.9949

2.56

2.66

2.76

2.86

2.96

1.51 1.56 1.61 1.66

Log L (cm)

Lo

g W

(g

)


mrigala sampled from sampling site = C (Sunder) during low (left side) and high (right

side) flow seasons.

y = 3.14x - 2.2358

R2 = 0.9751

2.56

2.66

2.76

2.86

2.96

1.52 1.55 1.58 1.61 1.64log L (cm)

log

W (

g)

y = 3.146x - 2.24

R2 = 0.9902

2.56

2.63

2.70

2.77

2.84

2.91

2.98

1.52 1.55 1.58 1.61 1.64 1.67

Log L (cm)

Log W

(g)


mrigala sampled from sampling site = D (Balloki) during low (left side) and high (right

side) flow seasons.

Chapter 4 Results

100

y = 3.1679x - 2.2034

R2 = 0.9845

2.55

2.65

2.75

2.85

2.95

1.50 1.53 1.56 1.59 1.62

log L (cm)

log

W (

g)

y = 3.2049x - 2.2635

R2 = 0.9521

2.50

2.59

2.68

2.77

2.86

2.95

1.50 1.52 1.54 1.56 1.58 1.60 1.62log L (cm)

log W

(g)

Fig. 4.7 Relationship between log Length (cm) and log wet weight (g) in Labeo rohita

sampled from sampling site = A (Siphon) upstream during low (left side) and high


y = 3.1453x - 2.1736

R2 = 0.9894

2.55

2.63

2.71

2.79

2.87

2.95

1.50 1.53 1.56 1.59 1.62 1.65log L (cm)

log

W (

g)

y = 3.1664x - 2.1937

R2 = 0.9712

2.52

2.61

2.70

2.79

2.88

2.97

1.50 1.52 1.54 1.56 1.58 1.60 1.62log L (cm)

log

W (

g)


sampled from sampling site = B (Shahdera) upstream during low (left side) and high


Chapter 4 Results

101

y = 3.0631x - 2.028

R2 = 0.9889

2.60

2.70

2.80

2.90

3.00

1.51 1.54 1.57 1.60 1.63log L (cm)

log

W (

g)

y = 3.0806x - 2.0567

R2 = 0.9928

2.58

2.68

2.78

2.88

2.98

1.50 1.53 1.56 1.59 1.62 1.65log L (cm)

log

W (

g)


sampled from sampling site = C (Sunder) upstream during low (left side) and high


y = 3.1115x - 2.1118

R2 = 0.985

2.59

2.68

2.77

2.86

2.95

1.51 1.53 1.55 1.57 1.59 1.61 1.63log L (cm)

log

W (

g)

y = 3.1294x - 2.1377

R2 = 0.9484

2.50

2.58

2.66

2.74

2.82

2.90

2.98

1.49 1.52 1.55 1.58 1.61 1.64

log L (cm)

log

W (

g)


sampled from sampling site = D (Balloki) upstream during low (left side) and high


Chapter 4 Results

102

y = 3.1091x - 2.0767

R2 = 0.984

2.53

2.60

2.67

2.74

2.81

2.88

2.95

1.47 1.50 1.53 1.56 1.59 1.62log L (cm)

log

W (

g)

y = 3.1595x - 2.1756

R2 = 0.9883

2.49

2.58

2.67

2.76

2.85

2.94

1.47 1.50 1.53 1.56 1.59 1.62log L (cm)

log

W (

g)

Fig. 4.11 Relationship between log Length (cm) and log wet weight (g) in Catla catla

sampled from sampling site = A (Siphon) upstream during low (left side) and high


y = 3.0829x - 2.0325

R2 = 0.9875

2.55

2.65

2.75

2.85

2.95

1.47 1.50 1.53 1.56 1.59 1.62

log L (cm)

log

W (

g)

y = 3.0998x - 2.076

R2 = 0.9896

2.54

2.61

2.68

2.75

2.82

2.89

2.96

1.49 1.52 1.55 1.58 1.61 1.64

log L (cm)

log

W (

g)


sampled from sampling site = B (Shahdera) upstream during low (left side) and high


Chapter 4 Results

103

y = 3.0138x - 1.9188

R2 = 0.9859

2.57

2.66

2.75

2.84

2.93

1.48 1.51 1.54 1.57 1.60 1.63log L (cm)

log

W (

g)

y = 3.0311x - 1.9621

R2 = 0.9931

2.54

2.64

2.74

2.84

2.94

1.48 1.51 1.54 1.57 1.60 1.63log L (cm)

log

W (

g)


sampled from sampling site = C (Sunder) upstream during low (left side) and high


y = 3.0537x - 1.9792

R2 = 0.9603

2.55

2.65

2.75

2.85

2.95

1.46 1.49 1.52 1.55 1.58 1.61log L (cm)

log

W (

g)

y = 3.1038x - 2.0696

R2 = 0.9932

2.53

2.60

2.67

2.74

2.81

2.88

2.95

1.48 1.51 1.54 1.57 1.60 1.63log L (cm)

log

W (

g)


sampled from sampling site = D (Balloki) upstream during low (left side) and high


Chapter 4 Results

104

Table 4.6 Means of morphometric parameters with their standard error of means (SEM) and significance of sampling sites, flow

seasons and fish species.

SL POL HL ED MW MG DFL PFL PeFL AFL CFL

Sampling sites

Site A: Siphon (Control) 30.47 30.07 7.44 1.15 2.84 2.22 6.66 5.96 5.56 5.75 8.18

Site B: Shahdera 30.38 29.99 7.44 1.15 2.84 2.29 6.62 5.98 5.51 5.69 8.22

Site C: Sunder 30.16 29.87 7.33 1.15 2.83 2.29 6.60 5.96 5.52 5.70 8.37

Site D: Head Balloki 30.28 30.03 7.33 1.14 2.73 2.22 6.57 5.88 5.44 5.61 8.11

SEM and Significance 0.446 0.436 0.099 0.008 0.067 0.061 0.067 0.062 0.060 0.060 0.095

Seasons

High flow 30.16 29.87 7.29 1.14 2.80 2.23 6.58 5.91 5.45 5.64 8.07

Low flow 30.49 30.12 7.48 1.15 2.82 2.28 6.64 5.99 5.56 5.74 8.37

SEM and Significance 0.316 0.309 0.070* 0.006 0.048 0.043 0.048 0.044 0.042 0.042 0.067**

Fish Species

Cirrhinus mrigala 33.02 32.99 6.74 1.05 2.88 1.73 6.93 5.94 5.53 5.73 7.09

Labeo rohita 30.52 30.76 6.67 1.14 2.16 1.89 6.36 6.00 4.91 5.02 .7.7

Catla catla 3.772 26.22 8.74 1.25 3.38 3.14 6.54 5.91 6.08 6.31 9.81

SEM and Significance 0.387*** 0.378*** 0.086*** 0.007*** 0.058*** 0.053*** 0.058*** 0.054 0.052*** 0.052*** 0.082***

Values within the same column earmarked with same superscript did not differ significantly from each other (P>0.05)


Abbrevations:

SL=standard length; POL=post orbital length; HL=head length; ED=eye diameter; MW=mouth width; MG=mouth gap; DFL= dorsal fin

length; PFL=pectoral fin length; PeFL=pelvic fin length; AFL= anal fin length; CFL=caudal fin length.

Chapter 4 Results

105

Table 4.7 Mean morphometric parameters with their standard error of means (SEM) of the sampled fish species from four sampling

sites (Siphon (upstream =A); Shahdera =B; Sunder =C; and Head balloki =D) during low and high flow seasons of the river.

Species Sites A B C D SEM With Significance

Seasons Low High Low High Low High Low High Site x Season C

irrh

inu

s m

rigala

Standard length 33.98 33.18 32.89 32.96 32.62 32.20 33.36 32.99 1.093

Post operculum length 33.44 33.33 32.99 32.67 32.62 32.43 33.30 33.17 1.069

Head length 6.81 6.71 6.81 6.74 6.72 6.68 6.74 6.71 0.242

Eye diameter 1.05 1.05 1.06 1.05 1.06 1.05 1.06 1.07 0.019

Mouth width 2.92 2.89 2.89 2.84 2.89 2.88 2.89 2.86 0.165

Mouth gap 1.71 1.72 1.73 1.71 1.74 1.74 1.75 1.72 0.150

dorsal fin length 7.00 6.94 6.97 6.91 7.00 6.87 6.91 6.87 0.165

pectoral fin length 6.03 6.00 5.92 5.84 6.02 5.96 5.86 5.84 0.152

pelvic fin length 5.53 5.41 5.64 5.48 5.64 5.56 5.49 5.47 0.146

Anal fin length 5.81 5.73 5.76 5.60 5.80 5.76 5.69 5.67 0.147

caudal fin length 6.98 6.27 7.12 6.94 7.43 6.94 7.28 6.74 0.232

La

beo

ro

hit

a

Standard length 30.93 30.51 30.97 30.31 30.59 30.32 30.41 30.12 1.093


Head length 6.69 6.66 6.78 6.61 6.62 6.60 6.74 6.68 0.242

Eye diameter 1.16 1.15 1.16 1.15 1.15 1.11 1.15 1.08 0.019

Mouth width 2.24 2.23 2.26 2.17 2.13 2.12 2.08 2.08 0.165

Mouth gap 1.87 1.72 1.94 1.89 1.97 1.90 1.93 1.89 0.150




Anal fin length 5.33 5.00 5.13 4.94 5.11 4.92 4.88 4.86 0.147


Ca

tla

catl

a

Standard length 27.22 27.00 27.71 27.47 27.81 27.43 27.43 27.37 1.093


Head length 9.19 8.56 9.02 8.68 8.92 8.42 8.72 8.38 0.242

Eye diameter 1.26 1.25 1.25 1.24 1.25 1.25 1.25 1.24 0.019

Mouth width 3.42 3.33 3.43 3.44 3.46 3.50 3.26 3.19 0.165

Mouth gap 3.17 3.12 3.24 3.19 3.19 3.18 3.08 2.92 0.150




Anal fin length 6.33 6.28 6.38 6.33 6.34 6.26 6.29 6.28 0.147


Chapter 4 Results

106

4.3 Proximate analyses of the fishes’ muscles:

Proximate parameters, in general, differed significantly (P<0.01) when the

comparison was made among the sampling sites, seasons and fish species (table 4.8).

While the crude protein, ash contents, moisture, fat contents and carbohydrates showed

non significant (P>0.05) differences when the data were processed for interaction of sites

x seasons x fish species (table 4.9).

The trend of changes in proximate analyses appeared responsive to the

downstream locations; crude protein contents of the muscles showed increases while

moisture, carbohydrate, fat and ash contents decreased up to site C during both low and

high flow seasons. The downstream declining trends of the parameters stabilized more or

less at site D, rather showed a recovery as compared to the values obtained for the site C.

All three species showed increases in crude protein contents and reductions in moisture,

carbohydrates, fat and ash contents at the downstream sampling sites (table 4.8). C. catla

was highest in carbohydrates (3.63 %) and ash (1.13 %) contents but lowest in moisture

(73.51 %). Whereas L. rohita was highest in crude protein (20.29 %) and fat contents

(1.85 %) but lowest in ash (0.91 %) and carbohydrates (3.05 %) contents. The crude

protein (19.57 %), carbohydrates (3.05 %) and fat contents (1.62 %) were found lowest in

case of C. mrigala (table 4.8).Crude protein contents when compared with the values at

site A, increased up to 6.05 % and 26.64 %, 6.22 % and 4.02 %, 24.66 % and 6.69 % in

C. mrigala, 8.04 % and 25.86 %, 13.91% and 3.83%, 23.97 % and 7.33 % in L. rohita,

5.94 % and 26.10 %, 13.90 % and 3.58 %, 23.71 % and 11.91 % in C. catla at site B, C

and D during low and high flow seasons, respectively (table 4.9). Total ash and

carbohydrates also expressed positive correlation with total fats. Fat contents appeared

highest in C. mrigala up to 1.64 % and 1.63 % (Fig. 4.15), for L. rohita up to 1.97 % and

1.96 % (Fig. 4.16) and for C. calta up to 1.78 % and 1.77 % (Fig. 4.17) at site A during

low and high flow respectively. Moisture contents ranged from 72.32 to 75.86 %, 71.55

to 75.36 % and 71.42 to 74.92 % in muscles of C. mrigala, L. rohita, C. catla,

Chapter 4 Results

107

respectively. C. mrigala muscles’ carbohydrate contents folds decreased at site B, C and

D in comparison with control (site A) up to 0.91, 0.74, 0.85 and 0.90, 0.76, 0.82, L.

rohita 0.92, 0.88, 0.93 and 0.91, 0.90, 0.92, C. catla 0.96, 0.81, 0.92 and 0.94, 0.83, 0.90

folds during low and high flow season respectively.

Chapter 4 Results

108

Table 4.8 Proximate parameters (%) with their standard error of means (SEM) and significance for sampling sites, flow seasons and

sampled fish species from the river.

Moisture Crude protein Fat Ash Carbohydrates

Sampling sites

Site A: Siphon (Control) 75.26a

18.19d

1.79a

1.18a 3.58

a

Site B: Shahdera 74.89a

19.07c

1.69bc

1.04b

3.31b

Site C: Sunder 71.96c

22.68a

1.66c

0.78c

2.92d


19.93b

1.74ab

1.06b 3.18

c

SEM and Significance 0.167*** 0.165*** 0.016*** 0.019*** 0.028***

Seasons

High 74.29a 19.56

b 1.75

a 1.08

a 3.32

a

Low 73.81b

20.37a 1.69

b 0.96

b 3.17

b

SEM and Significance 0.118** 0.117*** 0.011** 0.013*** 0.020***

Species

Cirrhinus mrigala 74.75a

19.57b

1.62c

1.01b

3.05b

Labeo rohita 73.90b

20.29a 1.85

a 0.91

c 3.05

b

Catla catla 73.51b 20.05

ab 1.69

b 1.13

a 3.63

a

SEM and Significance 0.145*** 0.143** 0.014*** 0.016*** 0.024***



Chapter 4 Results

109

Table 4.9 Proximate parameters (%) with their standard error of means (SEM) and significance of sampled fish species netted

from four selected sampling sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and Head balloki =D) and two flow seasons of

the river.

Sites

Seasons

A B C D

Low High Low High Low high Low High SEM With Significance

Cirrhinus mrigala

Proximate composition Moisture 75.63

a 75.86

a 75.03

a 75.67

a 72.32

b 72.89

b 75.18

a 75.43

a 0.409

Crude Protein 18.17b

17.64b

19.27b

18.35b

23.01a

21.99a

19.30b

18.82b

0.404

Fat content 1.64a 1.63

a 1.55

a 1.66

a 1.57

a 1.61

a 1.62

a 1.70

a 0.039

Ash content 1.15ab

1.28a

1.05abc

1.10ab

0.59d

0.79cd

1.02bc

1.13ab

0.046

Carbohydrates 3.42ab

3.60a 3.12

bc 3.23

abc 2.52

e 2.74

de 2.89

cde 2.94

cd 0.068

Labeo rohita


a 75.36

a 74.54

a 75.18

a 71.55

b 71.62

b 73.38

ab 74.44

a 0.409

Crude Protein 18.41bc

18.27c

19.89bc

18.97bc

23.17a

22.65a

20.97ab

19.61bc

0.404

Fat content 1.97a

1.96ab

1.76ab

1.87ab

1.75b

1.79ab

1.85ab

1.89ab

0.039

Ash content 0.92ab

1.05a

0.88ab

0.93ab

0.73b

0.93ab

0.86ab

0.99a

0.046


3.37a

2.95b

3.06ab

2.81b

3.03ab

2.96b

3.09ab

0.068

Catla catla


a 74.92

a 74.14

ab 74.78

a 71.42

c 71.99

bc 72.76

abc 73.38

abc 0.409

Crude Protein 18.35d 17.88

d 19.44

cd 18.52

d 23.14

a 22.12

ab 20.90

abc 20.01

bcd 0.404

Fat content 1.78a

1.77a

1.62a

1.73a 1.60

a 1.64

a 1.63

a 1.75

a 0.039

Ash content 1.27ab

1.40a

1.13bc

1.18abc

0.73d

0.93cd

1.17abc

1.23ab

0.046


4.04a

3.69abc

3.80ab

3.12d

3.34cd

3.56abc

3.65bc

0.068



Chapter 4 Results

110

70

71

72

73

74

75

76


Mois

ture

(%

)

Low flow High flow

0

5

10

15

20

25


Cru

de

pro

tein

(%

)

Low flow High flow

0

1

2

3

4

A B C DSampling site

Car

bo

hy

dra

te

(%)

Low flow High flow

1.45

1.5

1.55

1.6

1.65

1.7


Lip

ids

(%

)

Low flow High flow

0

0.2

0.4

0.6

0.8

1

1.2

1.4


Ash

(%

)

Low flow High flow

Fig. 4.15 Proximate analyses of muscle of Cirrhinus mrigala from different

alongstream sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and Head

balloki =D) during low and high flow seasons of the river Ravi.

Chapter 4 Results

111

73.5

74

74.5

75

75.5

A B C D

Sampling sites

Mo

istu

re

(%)

Low flow High flow

18

18.5

19

19.5

20

20.5

21

A B C D

Sampling sites

Cru

de

pro

tein

(%

)

Low flow High flow

c

2.4

2.6

2.8

3

3.2

3.4

A B C D

Sampling sites

Carb

oh

yd

rate

(%

)

Low flow High flow

1.6

1.7

1.8

1.9

2

A B C D

Sampling Sites

Lip

ids

(%)

Low flow High flow

0

0.25

0.5

0.75

1

A B C D

Sampling sites

Ash

(%

)

Low flow High flow

Fig. 4.16 Proximate analyses of muscle of Labeo rohita from different alongstream

sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and Head balloki =D)


Chapter 4 Results

112

69

70

71

72

73

74

75


Mois

ture

(%

)

Low flow High flow

0

5

10

15

20

25


Cru

de

pro

tein

(%

)

Low flow High flow

0

1

2

3

4


Car

bo

hy

dra

te

(%)

Low flow High flow

1.5

1.55

1.6

1.65

1.7

1.75

1.8


Lip

ids

(%)

Low flow High flow

0

0.25

0.5

0.75

1

1.25

1.5


Ash

(%

)

Low flow High flow

Fig. 4.17 Proximate analyses of muscle of Catla catla from different alongstream

sites (Siphon (upstream) =A; Shahdera =B; Sunder =C; and Head balloki =D)


Chapter 4 Results

113

4.4 Biochemical analysis of the fishes muscles:

Mean values of various biochemical parameters of muscle tissues of the sampled

fish species are presented in table 4.10. All the parameters showed significant differences

(P<0.001) for seasons, downstream sites and fish species, except the DNA content. The

biochemical parameters, except carbohydrates, total and soluble protein showed non

significant site x season x species interactions downstream to the confluence of industrial

effluents drains and domestic sewage to the river (table 4.11).

Trend of changes in biochemical parameters appeared responsive to the

downstream locations; total and soluble proteins and DNA contents of the muscles

showed increases while carbohydrate, total lipids, cholesterol and RNA contents

decreased up to site C during both low and high flow seasons. These changes in the

biochemical parameters stabilized more or less at site D and rather showed a recovery

trend as compared to the values obtained for the site C (table 4.11).

Muscle mean carbohydrate ranged between 16. 87 – 45.86 mg/g, total protein

112.94 – 219.44 mg/g, soluble protein 49.87 – 95.86 mg/g, total lipids 18.61 – 26.30

mg/g, cholesterol 0.62 – 1.79 mg/g, DNA 1.40 – 1.47 mg/kg and RNA 5.56 – 6.13 mg/g

when the data of three fish species, four sampling sites and two flow season were pooled

together (table 4.11). Carbohydrates contents (45.86 mg/g), cholesterol (1.79 mg/g) and

RNA (6.13 mg/g) approached levels highest at site A, while these parameters decreased

to lowest levels with values up to 16.87, 0.62 and 5.56 mg/g, respectively at site C.

Whereas total protein (16.87 mg/g), soluble protein (95.86 mg/g) and DNA (1.47 mg/g)

were highest at site C. Lowest value of these parameters with respective values of 112.94,

49.87 and 1.40 mg/g were observed at site A (table 4.11).

L. rohita was highest in total lipids (23.56 mg/g) and cholesterol (1.26 mg/g) but

lowest in carbohydrates (25.87 mg/g) and RNA (5.65 mg/g) contents. Whereas C. catla

was lowest in total protein (131.33 mg/g), soluble protein (59.95 mg/g), total lipids (20.81

mg/g), cholesterol (1.07 mg/g), DNA (1.38 mg/g) and RNA (5.67 mg/g) but highest in

Chapter 4 Results

114

carbohydrates contents (32.67 mg/g) (table 4.15). Total protein (208.28 mg/g), soluble

protein (82.40 mg/g), DNA (1.49 mg/g) and RNA (6.09 mg/g) contents were highest in C.

mrigala. Total protein contents increased in C. mrigala (56.82 mg/g, 96.94 mg/g and

58.58 mg/g), L. rohita (19.15 mg/g, 61.06 mg/g and 38.31 mg/g) and C. catla (36.44

mg/g, 145.15 mg/g and 91.55 mg/g) during low flow than the value of the parameter

obtained during high flow season for C. mrigala (55.57 mg/g, 112.65 mg/g and 65.58

mg/g), L. rohita (15.09 mg/g, 53.88 mg/g and 38.88 mg/g) and C. catla (39.24 mg/g,

125.48 mg/g and 89.80 mg/g) at site B, C and D, respectively (Fig. 4.18-4.20). The

increment in total protein contents of muscle of C. mrigala appeared 56.82, 96.94 and

58.58 % and 55.57, 112.65 and 65.58 % higher for the site B, C and D as compared to the

corresponding values of the parameter at site A during low and high flow seasons,

respectively (Fig. 4.24). The increment in total protein contents of muscle of L. rohita

appeared 19.16, 61.06 and 38.31 % and 15.09, 53.88 and 38.88 % higher for the site B, C

and D as compared to the corresponding values of the parameter at site A during low and

high flow seasons, respectively (Fig. 4.25). The increment in total protein contents of

muscle of C. catla appeared 36.44, 145.15 and 91.55 % and 39.24, 125.48 and 89.80 %

higher for the site B, C and D as compared to the corresponding values of the parameter

at site A during low and high flow seasons, respectively (Fig. 4.26). Soluble protein

contents of the muscles of fishes also increased for the downstream localities. Soluble

protein content in muscle of C. mrigala (40.88 mg/g,103.78 mg/g and 79.52 mg/g), L.

rohita (9.64 mg/g, 40.63 mg/g and 7.55 mg/g) and C. catla (40.72 mg/g, 137.18 mg/g and

61.33 mg/g) during low flow were higher than the corresponding values of C. mrigala

(33.15 mg/g, 107.36 mg/g and 79.52 mg/g), L. rohita (30.89 mg/g, 62.61 mg/g and 41.12

mg/g) and C. catla (38.63 mg/g, 141.78 mg/g and 57.04 mg/g) during high flow at site, B,

C and D, respectively. Soluble proteins showed elevations of 40.88, 103.78 and 76.00 %

in C. mrigala, 40.72, 137.18 and 61.33 % in C. catla and 9.64, 40.63 and 7.55 % in L.

rohita for the sites B, C and D, respectively during low flow season over the

Chapter 4 Results

115

corresponding values obtained for the site A (control). The increases in the protein

content of fish muscles from the downstream locations were comparable during both the

low and high flow seasons in the three fish species (Fig. 4.18-4.20).

DNA content of muscle tissues increased up to 0.99, 0.94 and 0.96;,0.92, 0.82 and

0.84 ; and 0.97, 0.90 and 0.95 folds during low flow season .at sites B, C and D for the

fishes C. mrigala, L. rohita and C.catla, respectively. While during high flow season, the

corresponding fluctuations in the parameter were 0.98, 0.94 and 0.95; 0.93, 0.89 and 0.89;

and 0.96, 0.95 and 0.95 folds in comparison with the values of the parameter for site A.

The DNA content, which increased upto 8.40, 11.45 and 9.92 % in C.catla during low

flow at sites B, C and D, respectively when compared to the value of the parameter for

site A could show an elevation of only 0.74% for the site C during high flow season

(Fig.4.20). C. mrigala showed DNA elevation upto 2.76, 6.21 and 3.45 % during low

flow at sites B, C and D, respectively when compared to the value of the parameter for

site A but could increased only up to 2.03 % at site B while reduced by 2.70 % at site C

and remained unaffected at site D during low flow season (Fig. 4.18). However, L. rohita

showed 9.79, 11.89 and 7.69 % increased during low flow and 7.19, 1.44 and 2.16 %

during high flow season (Fig. 4.17).

The remaining four biochemical parameters showed variable decreases for the

muscles sampled from the downstream locations as compared to their respective values

obtained for the site A. The decreases in carbohydrates, total lipids, cholesterol and RNA

contents in general appeared intensified during low season (Fig 4.21-4.23). Total lipids

contents of muscle decreased in C. mrigala (0.89, 0.71 and 0.87 folds), L. rohita (0.93,

0.66 and 0.83 folds) and C. catla (0.84, 0.70 and 0.75 folds) at sites B, C and D,

respectively when compared to the value of the parameter for site A during low flow

season. than C. mrigala The corresponding decreases for high flow season were 0.87,

0.73 and 0.86 folds, 0.92, 0.71 and 0.85 folds and 0.86, 0.73 and 0.81 folds for C.

mrigala, L. rohita and C. catla respectively. Cholesterol and RNA contents decreased at

Chapter 4 Results

116

downstream sampling sites during low as well as high flow seasons. Cholesterol and

RNA contents respectively ranged from 0.52-1.48 mg/g and 5.81-6.17 mg/g in C.

mrigala, 0.62-1.60 mg/g and 5.04-6.17 mg/g in L. rohita and 0.33- 1.99 mg/g and 5.33-

5.91 mg/g during low flow season. While for high flow the corresponding parameters

ranged 0.66-1.68 mg/g and 5.81-6.17 mg/g in C. mrigala, 1.17-1.76 mg/g and 5.56-6.22

mg/g in L. rohita and 0.43-2.05 mg/g and 5.62-5.94 mg/g in C. catla. Reductions in

muscle carbohydrate ranged from 27.95 to 77.06 % and from 28.57 to 74.21 % in C.

mrigala, from 37.43 to 63.12 % and from 32.43 to 53.47 % in L. rohita and from 25.27 to

61.82 % and from 23.22 to 46.70 % in C. catla during low and high flow season

respectively for the sampling sites B, C and D as compared to the value of the parameter

obtained at site A during low and high flow seasons, respectively (Fig. 4.18-4.20) .Total

lipids showed reductions from 10.83 to 28.92 % and from 12.86 to 27.40 % in C.

mrigala, from 7.10 to 34.41 and from 7.79 to 28.66 % in L. rohita and from 15.57 to

29.55 % and from 13.62 to 26.77 % in C. catla during low and high flow season

respectively for the sampling sites B, C and D as compared to the value of the parameter

obtained at site A during low and high flow seasons, respectively (Fig. 4.24-4.28).

Cholesterol content of the muscle tissues expressed decrements, from 17.68 to 68.29 %

and from 17.86 to 60.71 % in C. mrigala, from 23.75 to 61.25 % and from 14.29 to 33.52

% in L. rohita and from 43.72 to 83.42 % and from 41.46 to 79.02 % in C. catla during

low and high flow seasons respectively for the sampling sites B, C and D as compared to

the value of the parameter obtained at site A during low and high flow seasons,

respectively. RNA reduced from 0.65 to 5.83 % and from 2.20 to 5.65 % in C. mrigala,

from 8.43 to 18.31 % and from 6.91 to 10.61 % in L. rohita and from 2.71 to 9.81 % and

from 3.54 to 5.39 % in C. catla during low and high flow season respectively for the

sampling sites B, C and D as compared to the value of the parameter obtained at site A

during low and high flow seasons, respectively (table 4.11).

Chapter 4 Results

117

Table 4.10 Means of biochemical parameters (mg/g) of muscles with standard error of means and significance (SEM) for sampling

sites, flow seasons and fish species.

Carbohydrates Total

Protein

Soluble

Protein

Total

Lipids

Cholesterol DNA RNA

Sampling sites

Site A: Siphon (Control) 45.86a 112.94

d 49.87

d 26.30

a 1.79

a 1.40

a 6.13

a


155.19c

65.13c

23.36b

1.30b 1.47

a 5.88

b

Site C: Sunder 16.870d 219.44

a 95.86

a 18.61

d 0.62

d 1.47

a 5.56

c


180.67b

75.40b

21.82c 0.89

c 1.46

a 5.63

c

SEM and Significance 0.361*** 1.623*** 0.524*** 0.385*** 0.020*** 0.020 0.032***

Flow Seasons

High 32.00a 161.68

b 68.33

b 23.59

a 1.23

a 1.42

b 5.90

a

Low 27.31b

172.44a 74.80

a 21.46

b 1.06

b 1.47

a 5.70

b

SEM and Significance 0.255*** 1.148*** 0.370*** 0.273*** 0.014*** 0.014* 0.023***

Species

Cirrhinus mrigala 30.43b

208.28a 82.40

a 23.20

a 1.12

b 1.49

a 6.09

a

Labeo rohita 25.87c

161.56b 72.35

b 23.56

a 1.26

a 1.48

a 5.65

b

Catla catla 32.67a 131.33

c 59.95

c 20.81

b 1.07

b 1.38

b 5.67

b

SEM and Significance 0.313*** 1.406*** 0.453*** 0.334*** 0.018*** 0.018*** 0.028***

Values within the same column earmarked with same superscript did not differ significantly from each other (P>0.05)


Chapter 4 Results

118

Table 4.11 Means of biochemical parameters (mg/g) of muscles of three fish species of different alongstream sites (Siphon (upstream

=A); Shahdera =B; Sunder =C; and Head balloki =D) during low and high flow seasons of the river with standard error of means

(SEM) and significance.

Fish

species

Sites

Seasons

A B C D

Low

High

Low

High

Low

High

Low

High

SEM With Significance

Biochemical Parameters (mg/g) C

irrh

inu

s

mri

gala

Carbohydrate 47.51

b 54.95

a 19.91

d 22.48

d 10.90

e 14.17

e 34.23

c 39.25

c 0.885**

Total Protein 139.27c 128.35

c 218.40

b 199.67

b 274.28

a 272.93

a 220.86

b 212.52

b 3.976*

Soluble Protein 54.79e 51.47

e 77.19

c 68.53

d 111.65

a 106.73

a 96.43

b 92.40

b 1.282***

Total Lipids 25.66ab

27.92a 22.88

bc 24.33

ab 18.24

d 20.27

cd 22.24

bc 24.02

bc 0.944

Cholesterol 1.64a 1.68

a 1.35

b 1.38

ab 0.52

e 0.66

de 0.81

cd 0.91

c 0.500

DNA 1.48a 1.45

a 1.51

a 1.49

a 1.44

a 1.54

a 1.48

a 1.50

a 0.050

RNA 6.17abc

6.37a 6.13

abc 6.23

ab 5.81

c 6.01

abc 5.90

bc 6.08

abc 0.079

Lab

eo r

oh

ita

Carbohydrate 38.20b

42.49a

17.58f 22.26

de 14.09

g 19.77

ef 23.90

d 28.71

c 0.885**

Total Protein 129.22ef

122.57f

153.98d

141.06de

208.12a

188.61b

178.72dc

170.22c

3.976*

Soluble Protein 66.58e

51.24f

73.00c

67.07de

93.63a

83.32b

71.61cde

72.31cd

1.282***


28.37a

24.35b

26.16ab

17.19e

20.24de

21.76d

24.20bc

0.944

Cholesterol 1.60ab

1.76a

1.22c

1.51b

0.62e

1.17c

0.91d

1.27c

0.500

DNA 1.43bc

1.39c

1.57a

1.49abc

1.60a

1.41bc

1.54ab

1.42bc

0.050

RNA 6.17a

6.22a

5.65b

5.79b

5.04c

5.56b 5.18

c 5.56

b 0.079

Catl

a c

atl

a

Carbohydrate 44.71a

47.32a

26.21d

31.06c

17.07e

25.22d 33.41

c 36.33

b 0.885**

Total Protein 81.18e

77.03e 110.76

d 107.26

d 199.01

a 173.69

b 155.50

c 146.20

c 3.976*

Soluble Protein 39.54f 35.59

f 55.64

d 49.34

e 93.78

a 86.05

b 63.79

c 55.89

d 1.282***


25.70a

20.23bcd

22.20abc

16.88d

18.82cd

17.87cd

20.85bcd

0.944

Cholesterol 1.99a

2.05a

1.12b 1.20

b 0.33

d 0.43

d 0.67

c 0.77

c 0.500

DNA 1.31a

1.35a

1.42a

1.36a 1.46

a 1.34

a 1.44

a 1.36

a 0.050

RNA 5.91a

5.94a 5.75

a 5.73

ab 5.33

c 5.62

abc 5.43

bc 5.66

ab 0.079



Chapter 4 Results

119

0

10

20

30

40

50

60


Carb

oh

yd

rate

(m

g/g

)

Low Flow High Flow

0

50

100

150

200

250

300


To

tal

Pro

tein

(m

g/g

)

Low Flow High Flow

0

20

40

60

80

100

120

A B C D

Sampling Sites

So

lub

le P

rote

in (

mg

/Kg

)

Low Flow High Flow

0

5

10

15

20

25

30


Tota

l lipid

s (m

g/K

g)

Low Flow High Flow

t

0

0.5

1

1.5

2

A B C D

Sampling Sites

Ch

lost

ero

l (m

g/K

g)

Low Flow High Flow

0

0.4

0.8

1.2

1.6

A B C D

Sampling Sites

DN

A (

mg

/Kg

)

Low Flow High Flow

0

1.1

2.2

3.3

4.4

5.5

6.6

A B C D

Sampling Sites

RN

A (

mg

/Kg

)

Low Flow High Flow

Fig. 4.18 Biochemical parameters (mg/g) with standard deviations (Bars) of muscle

of Cirrhinus mrigala sampled from alongstream sites (Siphon (upstream) =A;

Shahdera =B; Sunder =C; and Head balloki =D) during low and high flow of the

river Ravi.

Chapter 4 Results

120

0

10

20

30

40

50


Car

bohydra

te (

mg/K

g)

Low Flow High Flow

t

0

50

100

150

200

250


To

tal P

rote

in (

mg

/Kg

)

Low Flow High Flow

0

20

40

60

80

100


So

lub

le P

rote

in (

mg

/Kg

)

Low Flow High Flow

0

5

10

15

20

25

30

35


Tota

l L

ipid

s (m

g/K

g)

Low Flow High Flow

0

0.5

1

1.5

2


Ch

lost

ero

l (m

g/K

g)

Low Flow High Flow

0

0.45

0.9

1.35

1.8


DN

A (

mg

/Kg

)

Low Flow High Flow

0

1

2

3

4

5

6

7


RN

A (

mg

/Kg

)

Low Flow High Flow

Fig. 4.19 Biochemical parameters (mg/g) with standard deviations (Bars) of muscle

of Labeo rohita sampled from alongstream sites (Siphon (upstream) =A; Shahdera

=B; Sunder =C; and Head balloki =D) during low and high flow of the river Ravi.

Chapter 4 Results

121

.

0

10

20

30

40

50


Carb

oh

yd

rate

(m

g/K

g)

Low Flow High Flow

0

50

100

150

200


Tota

l P

rote

in (

mg/K

g)

Low Flow High Flow

0

20

40

60

80

100


So

lub

le P

rote

in (

mg

/Kg

)

Low Flow High Flow

0

5

10

15

20

25

30


To

tal L

ipid

s (m

g/K

g)

Low Flow High Flow

0

0.5

1

1.5

2

2.5


Ch

lost

ero

l (m

g/K

g)

Low Flow High Flow

0

0.4

0.8

1.2

1.6


DN

A (

mg

/Kg

)

Low Flow High Flow

0

1

2

3

4

5

6

7

A B C D

Sampling Sites

RN

A (

mg

/Kg

)

Low Flow High Flow

Fig. 4.20 Biochemical parameters (mg/g) with standard deviations (Bars) muscle of

Catla catla sampled from alongstream sites (Siphon (upstream) =A; Shahdera =B;

Sunder =C; and Head balloki =D) during low and high flow of the river Ravi.

Chapter 4 Results

122

0

50

100

150

200

250

Carbohydrates Total protein Soluble protein Total lipids

Low flow High flow

0

1

2

3

4

5

6

7

Cholesterol DNA RNA

Low Flow High Flow

5

Fig. 4.21 Mean biochemical parameters (mg/g) with standard deviation (Bar) of

muscle of Cirrhinus mrigala sampled during low and high flow season of the river

Ravi.

Chapter 4 Results

123

0

25

50

75

100

125

150

175


Low flow High flow

0

1

2

3

4

5

6

7

Cholesterol DNA RNA

Low Flow High Flow

Fig. 4.22. Mean biochemical parameters (mg/g) with standard deviation (Bar) of

muscle of Labeo rohita sampled during low and high flow season of the river Ravi.

Chapter 4 Results

124

0

20

40

60

80

100

120

140

160


Low flow High flow

0

1

2

3

4

5

6

7

Cholesterol DNA RNA

Low Flow High Flow

Fig. 4.23 Mean biochemical parameters (mg/g) with standard deviation (Bar) of

muscle of Catla catla sampled during low and high flow season of the river Ravi.

Chapter 4 Results

125

-80%

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

B C D

Sampling sites

Car

bo

hy

dra

tes

Low Flow High Flow

0%

30%

60%

90%

120%

B C DSampling Sites

To

tal

Pto

tein

Low Flow High Flow

0%

25%

50%

75%

100%

125%

B C DSampling Sites

So

lub

le P

rote

in

Low Flow High Flow

-30%

-25%

-20%

-15%

-10%

-5%

0%

B C D

Sampling Sites

To

tal

Lip

ids

Low Flow High Flow

-70%

-60%

-50%

-40%

-30%

-20%

-10%

0%

B C D

Sampling Sites

Ch

ole

ster

ol

Low Flow High Flow

-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

7%

B C D

Sampling Sites

DN

A

Low Flow High Flow

-6%

-5%

-4%

-3%

-2%

-1%

0%

B C D

Sampling Sites

RN

A

Low Flow High Flow

Fig. 4,24 Percent difference of biochemical parameters of muscle of Cirrhinus

mrigala (Mori) sampled from downstream sites (Shahdera =B; Sunder =C; and

Head balloki =D) from the corresponding values of fish sampled from upstream site

= Siphon (control) during low and high flow seasons of the river Ravi.

Chapter 4 Results

126

-65%

-52%

-39%

-26%

-13%

0%

B C D

Sampling Sites

Car

bo

hy

dra

tes

Low Flow High Flow

0%

8%

16%

24%

32%

40%

48%

56%

64%

B C DSampling Sites

To

tal

Pro

tein

Low Flow High Flow

0%

10%

20%

30%

40%

50%

60%

B C DSampling Sites

So

lub

le P

rote

in

Low Flow High Flow

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

B C D

Sampling Sites

To

tal

Lip

ids

Low Flow High Flow

-63%

-54%

-45%

-36%

-27%

-18%

-9%

0%

B C D

Sampling Sites

Ch

oest

ero

l

Low Flow High Flow

0%

2%

4%

6%

8%

10%

12%

B C DSampling Sites

DN

A

Low Flow High Flow

-20%

-16%

-12%

-8%

-4%

0%

B C D

Sampling Sites

RN

A

Low Flow High Flow

Fig. 4.25 Percent difference of biochemical parameters of muscle of Labeo rohita


from the corresponding values of fish sampled from upstream site = Siphon


Chapter 4 Results

127

-64%

-48%

-32%

-16%

0%

B C D

Sampling Sites

Carb

oh

yd

rate

s

Low Flow High Flow

0%

30%

60%

90%

120%

150%

B C DSampling Sites

To

tal

Pro

tein

Low Flow High Flow

0%

30%

60%

90%

120%

150%

B C DSampling Sites

So

lub

le P

rote

in

Low Flow High Flow

-30%

-25%

-20%

-15%

-10%

-5%

0%

B C D

Sampling Sites

To

tal

Lip

ids

Low Flow High Flow

-84%

-70%

-56%

-42%

-28%

-14%

0%

B C D

Sampling Sites

Ch

ole

stero

l

Low Flow High Flow

-2%

0%

2%

4%

6%

8%

10%

12%

B C D

Sampling Sites

DN

A

Low Flow High Flow

-10%

-8%

-6%

-4%

-2%

0%

B C D

Sampling Sites

RN

A

Low Flow High Flow

Fig. 4.26 Percent difference of biochemical parameters of muscle of Catla catla


from the corresponding values of fish sampled from upstream site = Siphon


Chapter 4 Results

128

4.5 Heavy metals’ resistant bacterial colony forming unit (C.F.U.) and isolation from

the fishes’ gut content:

Mean colony forming units (C.F.U.) of the gut contents following inoculations on

Cu, Cr, Pb and Hg incorporated nutrient agar ranged from 1.21 x 105 /g to 29.9 x 10

5 /g

and 0.69 x 105 /g to 27.6 x 10

5 /g of gut contents of Labeo rohita, while from 0.99 x 10

5

/g to 19.9 x 105 /g and 1.16 x 10

5 /g to 24.9 x 10

5 /g of gut contents of Cirrhinus mrigala

and 0.56 x 105 /g to 24.30 x 10

5 /g and 0.91 x 10

5 /g to 30.2 x 10

5 /g of gut contents of

Catla catla during low and high flow seasons, respectively (Table 4.13 to 4.19).

Decreases in C.F.U. appeared, more or less, responsive to the downstream locations up to

site C (Sunder) during low and high flow seasons (Fig. 4.27 to 4.38). These changes in

the C.F.U. then tended to stabilize at site D (Balloki) as compared to the values obtained

for the site C. The C. F. U. at site A (29.9 x 105 /g) for L. rohita were higher than C. catla

(24.3 x 105 /g) and C. mrigala (17.5 x 10

5 /g) during low flow season. Further, the highest

C.F.U. of gut contents of C. catla, L. rohita and C. mrigala at site B were up to 21.2 x 105

/g, 21.1 x 105 /g and 15.4 x 10

5 /g, at site C decreased up to 2.02 x 10

5 /g, 2.22 x 10

5 /g

and 2.02 x 105 /g and at site D up to 2.01 x 10

5 /g, 2.54 x 10

5 /g and 2.01 x 10

5 /g of gut

contents respectively during low flow season (table 4.13). The C.F.U. at site A ranged

from 11.2 x 105 /g to 30.2 x 10

5 /g, 16.2 x 10

5 /g to 27.6 x 10

5 /g and 13.2 x 10

5 /g to 24.9

x 105 /g, at site C ranged from 0.91 x 10

5 /g to 11.3 x 10

5 /g, 0.69 x 10

5 /g to 1.54 x 10

5 /g

and 1.04 x 105 /g to 1.89 x 10

5 /g of gut contents of C. catla, L. rohita and C. mrigala

during high flow season respectively (table 4.14). In the present study, one hundred and

twenty three metals’ resistant bacteria were isolated from gut contents of three fish

species sampled from the four sampling sites during low and high flow seasons of the

river Ravi. The isolates’ colonial characteristics are shown in tables 4.13 to 4.19. Majority

(78 %) of the isolates’ colonies had round configuration when cultivated on metal

incorporated agar media. Highest number of bacterial strains were isolated from gut

contents of Labeo rohita (38.21 % and 38.33 %) as compared to Catla catla (33 % and 28

Chapter 4 Results

129

%) and Cirrhinus mrigala (29 % and 33 %) sampled during high and low flow seasons,

respectively. Site wise descending orders with respect to different metals of the isolates

appeared as site D (9) > site A (8) > site B (6) = site C (6) from copper incorporated

medium, site D (9) = site A (9) > site B (8) = site C (8) from lead incorporated medium,

site B (8) = site C (8) > site A (7)=site D (7) from chromium incorporated medium and

for site C (8) > site A(7) = site B (7) > site D from Hg incorporated medium cumulating

the data of both low and high flow seasons. Sixty three and sixty metals resistant bacteria

were isolated during high and low flow seasons respectively (Fig. 4.27 to 4.38).

Pure culturing of a representative bacterial colony for that/those colonies which appeared

from all the specimen of a species collected from a given site during a given season was

established according to the standard protocols. The bacterial isolates were then allotted

code numbers with three alphabet and one numerical prefixes to represent their source of

isolation in terms of the fish species, collection site and flow season etc. as explained in

table 4.12. A bacterial isolate was streaked on its sample inoculation metal incorporated

agar media. After incubation at 37 C for 24 hrs morphological characteristics of well

separated colonies were recorded and have been presented in tables 4.13 to 4.19. Colonial

characteristics of 123 bacterial isolates can be seen from these tables.

Chapter 4 Results

130

Table 4.12 Protocol established for assigning code number to the bacterial isolates.

Prefixes indicating Example of

Code Site Flow season Fish species Specimen No.

Siphon Low Rohu (Labeo rohita) 5 ALR5

Siphon Low Mori (Cirrhinus mrigala) 6 ALM6

Siphon Low Thaila (Catla catla) 8 ALT8

Siphon High Rohu (Labeo rohita) 7 AHR7

Siphon High Mori (Cirrhinus mrigala) 9 AHM9

Siphon High Thaila (Catla catla) 4 AHT4

Shahdera Low Rohu (Labeo rohita) 8 BLR8

Shahdera Low Mori (Cirrhinus mrigala) 8 BLM8

Shahdera Low Thaila (Catla catla) 2 BLT2

Shahdera High Rohu (Labeo rohita) 5 BHR5

Shahdera High Mori (Cirrhinus mrigala) 5 BHM5

Shahdera High Thaila (Catla catla) 6 BHT6

Sunder Low Rohu (Labeo rohita) 2 CLR2

Sunder Low Mori (Cirrhinus mrigala) 4 CLM4

Sunder Low Thaila (Catla catla) 2 CLT2

Sunder High Rohu (Labeo rohita) 3 CHR3

Sunder High Mori (Cirrhinus mrigala) 7 CHM7

Sunder High Thaila (Catla catla) 2 CHT2

Balloki Low Rohu (Labeo rohita) 1 DLR1

Balloki Low Mori (Cirrhinus mrigala) 1 DLM1

Balloki Low Thaila (Catla catla) 9 DLT9

Balloki High Rohu (Labeo rohita) 4 DHR4

Balloki High Mori (Cirrhinus mrigala) 2 DHM2

Balloki High Thaila (Catla catla) 3 DHT3

Chapter 4 Results

131

Table No. 4.13 Colony forming units (C.F.U.) from the gut contents of the fish species sampled from site A (Siphon) during low flow

season on different metal containing nutrient agar media and colonies’ morphologies of pure cultures of the bacteria.

Fish

species

Metal

C.F.U.

(x105)±SD

/g

Colony Characteristics

Isolates

code Configuration Margin Elevation Surface Colour Size (mm) Consistency Opacity

Labeo

rohita

Cu (250 µg/ml) 19.8±2.76 ALR5-3 Round Smooth Convex Shinny White 2.2 Mucoid opaque

Pb (350 µg/ml)

20.1±3.81 ALR7-5 Round Smooth Convex Dull Off-white 2.0 Viscous Opaque

29.9±2.86 ALR2-1 Round Smooth Convex Shinny White 1.0 Mucoid opaque

Cr (350 µg/ml) 23.4±6.05 ALR5-1 Round Smooth Convex Shinny White 2.0 Mucoid Opaque

Hg (10 µg/ml) 14.3±4.11 ALR3-4 Irregular Smooth Flat Dull Off-white 3.0 Viscous opaque

Cirrhinus

mrigala

Cu (250 µg/ml) 17.5±2.55 ALM6-2 Round Wavy Convex Shinny Red 2.0 Mucoid Opaque

Pb (350 µg/ml) 12.3±3.94 ALM1-1 Irregular Smooth Raised Dull White 3.0 Butyrous opaque

Cr (350 µg/ml) 18.9±4.03 ALM9-1 Round Smooth Raised

Smooth

and

shinny

Orangish

red 3.0 Butyrous Translucent

Hg (10 µg/ml)

15.4±5.82 ALM3-1 Round Smooth Slightly

convex Shinny Offwhite 1.0 Butyrous Translucent

19.9±4.98 ALM9-1 Round with

raised margin Smooth Raised Shinny

Offwhite

and clear 3.0 Butyrous Translucent

Catla

catla

Cu (250 µg/ml) 24.3±3.41 ALT8-2 Round Smooth Convex Dull White 2.0 Viscous Opaque

Pb (350 µg/ml) 23.2±5.43 ALT4-5 Irregular Wavy Flat Shinny Off-white 3.0 Mucoid Transparent

Cr (350 µg/ml) 20.2±3.11 ALT6-1 Round Smooth Convex Shinny Yellow 2.0 Mucoid Opaque

Hg (10 µg/ml) 12.3±3.44 ALT3-1 Round Smooth Raised Shinny White 1.0 Butyrous Opaque

Chapter 4 Results

132

Table No. 4.14 Colony forming units (C.F.U) from the gut contents of the fish species sampled from site A (Siphon) during high flow


Fish

species Metal

C.F.U.

(x105)±S

D/g


Isolates

code Configuration Margin Elevation Surface Colour

Size

(mm) Consistency Opacity

Labeo

rohita

Cu (250 µg/ml) 27.6±3.64 AHR7-5 Round Smooth Raised Shinny Off-white 2.0 Butyrous Opaque

18.9±2.90 AHR6-1 Round Smooth Convex Shinny White 3.0 Mucous Opaque

Pb (350 µg/ml)

19.8±2.96 AHR8-5 Round Smooth Raised Shinny Off-white 2.0 Mucous Opaque

26.2±3.97 AHR4-2 Irregular Irregular Flat Dull White 3.0 Dry Opaque

21.2±3.56 AHR4-1 Irregular Irregular Raised Shinny Off-white 4.0 Dry to mucoid Translucent

Cr (350 µg/ml) 25.6±5.56 AHR4-1 Round Smooth Convex Shinny White 1.0 Mucous Opaque

Hg (10 µg/ml) 16.2±4.52 AHR3-2 Round Smooth Raised Shinny Off white 2.0 Butyrous

Opaque +

transparent

margin

Cirrhinus

mrigala

Cu (250 µg/ml) 21.2±2.29 AHM9-1 Round Smooth Convex Shinny Offwhite 1.0 Butyrous

nucleoid Transparent

Pb (350 µg/ml) 24.9±4.51 AHM7-1 Round Smooth Convex Shinny Offwhite 2.0 Mucous/butter Opaque

Cr (350 µg/ml) 23.1±5.32 AHM3-1 Round Smooth Convex Shinny Offwhite 1.0 Butyrous Transparent

21.4±4.28 AHM4-2 Spreading Wavy Flat Spongy White 2.0 Viscous Opaque

Hg (10 µg/ml) 13.2±3.41 AHM4-1 Round Smooth Raised Shinny Offwhite 1.0 Butyrous Translucent

Catla

catla

Cu (250 µg/ml) 30.2±2.59 AHT4-4 Round Smooth Raised Shinny Offwhite 2.0 Viscous Opaque

24.1±2.94 AHT3-2 Round Irregular Flat Smooth White 1.5 Spongy Opaque

Pb (350 µg/ml) 19.1±3.71 AHT7-6 Irregular Wavy Flat Dull White 3.0 Dry Opaque

Cr (350 µg/ml) 24.1±4.37 AHT5-5 Irregular Irregular Raised Smooth Yellow 7.0 Butyrous Opaque

Hg (10 µg/ml) 11.2±2.75 AHT8-1 Round Smooth Raised Shinny Off-white 3.0 Mucous Opaque

Chapter 4 Results

133

Table No. 4.15 Colony forming units (C.F.U.) from the gut contents of the fish species sampled from site B (Shahdera) during low

flow season on different metal containing nutrient agar media and colonies’ morphologies of pure cultures of the bacteria.

Fish

species Metal

C.F.U.(x105)±

SD/g


Isolates


Size


Labeo

tohita

Cu(250 µg/ml) 9.6±1.62 BLR8-1 Round Smooth Raised Shinny Offwhite 3.0 Butyrous Opaque

Pb(350 µg/ml) 1.46±0.23 BLR6-1 Round Smooth Raised Shinny Offwhite 2.0 Mucoid Opaque

Cr(350 µg/ml) 21.1±4.56 BLR8-3 Round Smooth Convex shinny Yellow 1.0 Butyrous Opaque

17.8±3.71 BLR6-5 Round Smooth Flat Dull White 1.0 Dry Opaque

Hg (10 µg/ml)

2.17±0.46 BLR6-10 Round Smooth Raised Shinny Offwhite 1.5 Mucoid Opaque

1.88±0.39 BLR5-1 Irregular and

spreading Irregular Flat Spongy White 2.5 Viscous Opaque

1.56±0.34 BLR8-2 Round Smooth Raised Shinny Offwhite

to whitish 2.0 Butyrous Translucent

Cirrhinus

mrigala

Cu (250µg/ml) 14.5±2.80 BLM8-2 Concentric

irregular Irregular Flat Shinny

Off-white

to garish 3.5 Butyrous Translucent

Pb (350 µg/ml)

1.82±0.44 BLM4-1 Round Smooth Raised Shinny Offwhite

to yellow 2.0 Mucoid Opaque

0.99±0.32 BLM5-1 Irregular and

spreading Wavy Flat Dull White 2.0 Dry Translucent

Cr (350 µg/ml) 15.4±3.05 BLM8-1 Round Smooth Convex Shinny Yellow 1.0 Butyrous Opaque

Hg (10 µg/ml) 1.42±0.31 BLM9-1 Irregular Smooth Flat Shinny White 2.6 Mucoid Opaque

Catla

catla

Cu(250 µg/ml) 21.2±3.51 BLT2-1 Round Smooth Flat Shinny White 2.0 Mucoid Opaque

Pb(350 µg/ml) 1.42±0.39 BLT7-3 Irregular Wavy Convex Dull White 3.0 Butyrous Opaque

Cr(350 µg/ml) 19.9±5.36 BLT5-2 Round Smooth Convex Shinny Offwhite 1.5 Butyrous Translucent

Hg (10 µg/ml) 1.02±0.54 BLT6-2 Round Smooth Raised Shinny Yellow 2.0 Viscous Opaque

Chapter 4 Results

134

Table No. 4.16 Colony forming units (C.F.U) from the gut contents of the fish species sampled from site B (Shahdera) during high


Fish

species

Metal

C.F.U.

(x105)± SD

/g


Isolates


Size


Labeo

rohita

Cu(250 µg/ml) 24.7±4.46 BHR5-2 Round Smooth Raised Shinny Grayish 3.0 Butyrous Translucent

Pb(350 µg/ml) 15.5±3.59 BHR7-2 Round Smooth Raised Shinny Offwhite 2.0 Mucoid Opaque

Cr(350 µg/ml) 19.6±4.44 BHR2-1 Round with

raised margin Smooth Raised Spongy White 1.0 Butyrous Opaque

Hg (10 µg/ml) 9.9±3.04 BHR1-1 Round Smooth Raised Shinny Offwhite 3.0 Butyrous Translucent

Cirrhinus

mrifala

Cu(250 µg/ml) 23.9±4.20 BHM5-1 Round Smooth Raised Shinny Yellowish

offwhite 2.5 Butyrous Translucent

Pb(350 µg/ml)

20.1±4.69 BHM1-1 Irregular

margin Rough Convex Dull

Whitish to

offwhite 2.0 Dry Translucent

19.7±3.57 BHM9-2 Filamentous Branchi

ng Raised Shinny Offwhite 4.0 Dry Opaque

Cr(350 µg/ml) 18.3±4.17 BHM6-1 Round Smooth Convex Shinny Offwhite 2.0 Butyrous Opaque

Hg (10 µg/ml) 10.3±2.70 BHM6-2 Round Smooth Raised Shinny White 1.0 Mucous Opaque

Catla

catla

Cu(250 µg/ml) 27.5±4.17 BHT6-1 Round Smooth Raised Shinny Offwhite 3.0 Viscous Opaque

Pb(350 µg/ml) 27.7±3.60 BHT3-4

Round with

raised margin Smooth

Raised

convex Shinny

Offwhite +

yellow

nucleus

2.0 Mucoid Opaque

24.1±4.34 BHT1-6 Concentric Wavy Flat Dull Offwhite 5.0 Dry Opaque

Cr(350 µg/ml)

17.9±4.56 BHT3-1 Round Smooth Raised Shinny

Offwhite +

yellowish

nucleus

7.0 Butyrous Opaque

20.2±3.84 BHT7-2 Round with

raised margin Smooth Raised Smooth Milky white 2.0 Butyrous Opaque

Hg (10 µg/ml) 8.7±2.52 BHT6-1 Round Smooth Convex Shinny White 2.0 Mucous Opaque

Chapter 4 Results

135

Table No. 4.17 Colony forming units (C.F.U) from the gut contents of the fish species sampled from site C (Sunder) during low flow


Fish

species

Metal

C.F.U.

(x105)± SD

/g

Colony characteristics

Isolates


Size


Labeo

rohita

Cu(250 µg/ml) 1.92±0.64 CLR2-1 Irregular Smooth Flat Dull White 2.0 Butyrous Opaque

Pb(350 µg/ml) 1.21±0.35 CLR3-3 Round Smooth Convex Shinny White 1.0 Butyrous Opaque

2.22±0.43 CLR7-1 Round Smooth Raised Shinny Off-white 3.0 mucoid Opaque

Cr(350 µg/ml) 1.55±0.43 CLR8-1 Round Smooth Convex Shinny Yellow 1.0 Mucoid Transparent

Hg (10 µg/ml) 2.21±0.52 CLR4-2 Irregular Wavy Convex Dull White 2.4 Viscous Opaque

Cirrhinus

mrifala

Cu(250 µg/ml) 1.56±0.44 CLM4-1 Irregular and

spreading Lobate Flat Rough White 2.5 Dry Opaque

Pb(350 µg/ml) 1.36±0.58 CLM6-2 Round Smooth Raised Shinny Yellow 2.0 mucoid Opaque

Cr(350 µg/ml) 1.12±0.54 CLM4-1 Round Wavy Flat Shinny Off-white 1.0 Viscous Opaque

1.92±0.50 CLM6-3 Round Smooth Convex Shinny White 3.0 Dry Opaque

Hg (10 µg/ml) 1.99±0.35 CLM4-10 Round Smooth Convex Rough White 2.0 Mucoid Opaque

Catla catla

Cu(250 µg/ml) 2.02±0.55 CLT2-2 Round Smooth Convex Shinny White 3.0 Butyrous Opaque

Pb(350 µg/ml) 1.93±0.71 CLT3-1 Round Smooth Convex Shinny Offwhite 1.5 Mucoid Opaque

Cr (350 µg/ml) 0.56±0.20 CLT8-1 Irregular and

spreading Lobate Flat Dry White 3.0 Dry Opaque

Hg (10 µg/ml)

1.52±0.31 CLT3-3 Round with

raised margin Smooth Raised Shinny Offwhite 0.5 Butyrous

Opaque

centre

1.88±0.40 CLT3-2 Round +

irregular

Irregula

r Flat Spongy White 2.0 Viscous Opaque

Chapter 4 Results

136

Table No. 4.18 Colony forming units (C.F.U) from the gut contents of the fish species sampled from site C (Sunder) during high flow


Fish

species Metal

C.F.U. (x105)±

SD /g

Isolates

code

Colony characteistics

Configuration Margin Elevatio

n Surface Colour

Size


Labeo

rohita

Cu(250 µg/ml) 1.34±0.33 CHR3-1 Irregular and

spreading Lobate Flat Shinny White 2.0 Butyrous Opaque

Pb(350 µg/ml) 1.41±0.36 CHR4-4 Round Smooth Raised Shinny Whitish to

yellow 1.0 Mucoid Translucent

Cr(350 µg/ml) 1.54±0.39 CHR3-2

Round with

raised margin Wavy Convex Spongy Milky white 1.0 Viscous Opaque

1.35±0.41 CHR3-1 Round Smooth Convex Shinny White 3.0 Mucoid Opaque

Hg (10 µg/ml)

0.69±0.26 CHR3-2 Round Smooth Raised Dull White 1.0 Viscous Opaque

1.04±0.37 CHR9-1 Round Smooth Convex Shinny

White with

yellow

centre

3.0 Mucoid Opaque

Cirrhinus

mrigala

Cu(250 µg/ml) 1.66±0.46 CHM7-1 Round Smooth Raised Dull White 1.0 Mucoid opaque

Pb(350 µg/ml) 1.16±0.19 CHM5-2 Round Smooth Raised

convex Shinny Offwhite 2.0 Butyrous Opaque

Cr (350 µg/ml) 1.89±0.51 CHM1-2 Round Smooth Raised Shinny Offwhite 4.0 Viscous Opaque

Hg (10 µg/ml) 1.24±0.40 CHM1-1 Round Smooth Convex Dry White 2.0 Butyrous opaque

Catla

catla

Cu(250 µg/ml)

1.92±0.51 CHT2-2 Round Smooth Raised Shinny Offwhite 3.0 Butyrousq Opaque

2.22±0.41 CHT6-1 Round Smooth Raised Shinny Grayish 1.0 Butyrous Opaque

Pb(350 µg/ml) 1.66±0.41 CHT9-1

Round with

raised margin Irregular raised Dull White 2.0 Dry Opaque

0.91±0.44 CHT3-2 Round Smooth Raised Shinny Offwhite 2.0 Mucoid Translucent

Cr (350 µg/ml) 1.68±0.36 CHT3-2 Irregular and

spreading Irregular Flat Shinny Offwhite 2.0 Viscous Opaque

Hg (10 µg/ml) 11.3±3.50 CHT2-1 Round Smooth Raised Shinny White 2.0 Mucoid Opaque

Chapter 4 Results

137

Table No. 4.19 Colony forming units (C.F.U.) from the gut contents of the fish species sampled from site D (Balloki) during low flow


Fish

species Metal

C.F.U.

(x105)± SD /g


Isolates

code Configuration Margin Elevation Surface Colour Size (mm) Consistency Opacity

Labeo

rohita

Cu(250 µg/ml) 2.54±0.72 DLR1-5 Round Smooth Convex Shinny White 2.0 Mucoid Opaque

Pb(350 µg/ml) 1.48±0.50 DLR3-1

Round with

raised margin Irregular Convex Shinny

Offwhite to

yellow 3.0 Butyrous Opaque

2.21±0.78 DLR8-1 Round Smooth Convex Dull Off-white 2.0 Butyrous Opaque

Cr(350 µg/ml) 1.63±0.32 DLR1-3 Irregular Wavy Flat Shinny White 4.0 Mucoid Opaque

1.81±0.40 DLR4-3 Round Smooth Flat Dull White 3.0 Butyrous Opaque

Hg (10 µg/ml) 1.67±0.62 DLR10-1 Round Smooth Convex Shinny Offwhite 1.5 Butyrous Translucent

Cirrhinus

mrigala

Cu(250 µg/ml)

1.65±0.44 DLM1-2 Round Smooth Raised Shinny Offwhite to

grayish 1.5 Mucoid Translucent

1.71±0.46 DLM6-2 Round Smooth Flat Shinny White 2.0 Butyrous Opaque

Pb(350 µg/ml) 2.01±0.54 DLM4-3 Round Smooth Convex Shinny White 2.0 Mucoid Opaque

Cr (350 µg/ml) 1.45±0.38 DLM3-1 Irreugular and

spreading Lobate Flat Dull White 2.0 Dry Opaque

Hg (10 µg/ml) 2.01±0.42 DLM2-2 Round with

radiating Irregular Raised Shinny Offwhite 1.0 Butyrous Opaque

Catla catla

Cu(250 µg/ml) 1.23±0.33 DLT9-2 Round Smooth Raised Shinny Offwhite to

clear 0.5 Butyrous Transparent

Pb(350 µg/ml) 1.65±0.37 DLT5-1 Round Smooth Convex Shinny Offwhite to

yellow 1.5 Mucoid Opaque

Cr (350 µg/ml) 1.29±0.30 DLT3-1 Complex Irregular Flat Smooth White 1.0 Viscous Opaque

Hg (10 µg/ml) 1.55±0.38 DLT8-1 Round Smooth Raised Shinny Offwhite to

clear 0.5 Butyrous Transparent

Chapter 4 Results

138

Table No. 4.20 Colony forming units (C.F.U) from the gut contents of the fish species sampled from site D (Balloki) during high


Fish

species

Metal C.F.U.

(x105)± SD

/g


Isolates

code

Configuration Margin Elevation Surface Colour Size (mm) Consistency Opacity

Labeo

rohita

Cu(250 µg/ml) 20.9±3.00 DHR4-2 Round Smooth Convex Dull White 1.0 Butyrous Transparent

15.9±2.66 DHR5-1 Round Smooth Convex Shinny Grayish 0.5 Butyrous Transparent

Pb(350 µg/ml) 17.6±3.15 DHR1-1 Round Smooth Raised Shinny Whitish 3.0 Butyrous Translucent

14.5±3.08 DHR5-3 Round Smooth Convex Shinny Offwhite

to yellow

4.0 Mucoid Opaque

11.2±1.59 DHR2-2 Round Irregular Raised

convex

Shinny White 5.0 Butyrous Opaque

Cr (350 µg/ml) 11.23±2.96 DHR1-5 Round Smooth Raised Shinny Offwhite 3.0 Butyrous Translucent

15.6±3.54 DHR6-4 Round Smooth Raised Shinny Offwhite 3.0 Butyrous Translucent

Hg (10 µg/ml) 13.9±4.23 DHR8-2 Round Smooth Flat Shinny Offwhite 2.5 Butyrous Opaque

Cirrhinus

mrigala

Cu(250 µg/ml) 22.1±4.13 DHM2-1 Round Smooth Convex Shinny Offwhite 5.0 Butyrous Opaque

Pb(350 µg/ml) 15.4±2.95 DHM6-2 Round Smooth Raised

convex

Shinny White 3.0 Mucous Opaque

Cr(350 µg/ml) 13.2±3.30 DHM5-1 Irregular and

spreading

Irregular Flat Shinny White 3.0 Viscous Opaque

Hg (10 µg/ml) 12.2±2.85 DHM6-1 Round Irregular Flat Shinny Offwhite 3.0 Butyrous Opaque

Catla catla

Cu(250 µg/ml) 15.9±3.93 DHT3-1 Round Smooth Rasied Shinny Offwhtie 2.0 Viscous Opaque

9.7±2.27 DHT9-2 Irregular and

spreading

Lobate Raised Shinny Offwhite

to whitish

3.0 Butyrous Opaque

Pb(350 µg/ml) 17.7±2.81 DHT6-1 Round with

raised margin

Smooth Flat Dull White 5.0 Dry Translucent

Cr(350 µg/ml) 12.3±3.17 DHT6-2 Round Lobate Flat Shinny White 3.0 Viscous Opaque

Hg (10 µg/ml) 11.8±3.41 DHT9-1 Round Smooth Raised Shinny Offwhite 1.0 Butyrous Translucent

Chapter 4 Results

139

0

5

10

15

20

25

30

35

ALR5-3 AHR7-5 AHR6-1 BLR8-1 BHR5-2 CLR2-1 CHR3-1 DLR1-5 DHR4-2 DHR5-1

Low flow High flow Low flow High flow Low flow High flow Low flow High flow

A B C D

Sampling sites

CF

U (

x1

05

)/g

Fig. 4.27 Colony forming units (C.F.U.) of Cu

2+ (250 µg/ml of nutrient agar)

resistant bacterial isolates from gut content of Labeo rohita sampled from different

sites and during the two flow season from the river Ravi.

0

5

10

15

20

25

30

ALM6-2 AHM9-1 BLM8-2 BHM5-1 CLM4-1 CHM7-1 DLM1-2 DLM6-2 DHM2-1



C.F

.U.(

x1

05

)/g

Fig. 4.28 Colony forming units (C.F.U.) of Cu

2+ (250 µg/ml of nutrient agar)

resistant bacterial isolates from gut content of Cirrhinus mrigala sampled from


0

5

10

15

20

25

30

35

ALT8-2 AHT4-4 AHT3-2 BLT2-1 BHT6-1 CLT2-2 CHT2-2 CHT6-1 DLT9-2 DHT3-1 DHT9-2

Low

flow

High flow Low

flow

High

flow

Low

flow

High flow Low

flow

High flow

A B Cu D

Sampling Sites

C.F

.U.(

x10

5)/

g

Fig. 4.29 Colony forming units (C.F.U.) of Cu2+


resistant bacterial isolates from gut content of Catla catla sampled from different

sites and during the two flow season from the river Ravi.

Chapter 4 Results

140

05

101520253035

ALR7-5

ALR2-1

AH

R8-5

AH

R4-2

AH

R4-1

BLR6-1

BHR

7-2

CLR3-3

CLR7-1

CHR

4-4

DLR3-1

DLR8-1

DH

R1-1

DH

R5-3

DH

R2-2

Low flow High flow Low

flow

High

flow

Low flow High

flow

Low flow High flow

A B C D

Sampling Sites

C.F

.U.

(x10

5)/

g

Fig. 4.30 Colony forming units (C.F.U.) of Pb

2+ (350 µg/ml of nutrient agar) resistant

bacterial isolates from gut content of Labeo rohita sampled from different sites and

during the two flow season from the river Ravi.

0

5

10

15

20

25

30

ALM1-1 AHM7-1 BLM4-1 BLM5-1 BHM1-1 BHM9-2 CLM6-2 CHM5-2 DLM4-2 DHM6-2


A B C D

Sampling Sites

C.F

.U (

x105)/

g

Ti

Fig 4.31 Colony forming units (C.F.U.) of Pb


bacterial isolates from gut content of Cirrhinus mrigala sampled from different sites

and during the two flow season from the river Ravi.

0

5

10

15

20

25

30

35

ALT4-5 AHT7-6 BLT7-3 BHT3-4 BHT1-6 CLT3-1 CHT9-1 CHT3-2 DLT5-1 DHT6-1


A B C D

Sampling Sites

C.F

.U.(

x1

05

)/g

Fig 4.32 Colony forming units (C.F.U.) of Pb


bacterial isolates from gut content of Catla catla sampled from different sites and


Chapter 4 Results

141

0

5

10

15

20

25

30

35

ALR5-1 AHR4-1 BLR8-3 BLR6-5 BHR2-1 CLR8-1 CHR3-2 CHR3-1 DLR1-3 DLR4-3 DHR1-5 DHR6-4


A B C D

Samling Sites

C.F

.U (

x105)/

g

Fig. 4.33 Colony forming units (C.F.U.) of Cr




0

5

10

15

20

25

30

ALM9-1 AHM3-1 AHM4-2 BLM8-1 BHM6-1 CLM4-1 CLM6-3 CHM1-2 DLM3-1 DHM5-1

Low flow High flow Low flow High

flow

Low flow High

flow

Low flow High

flow

A B C D

Sampling Sites

C.F

.U (

x10

5)/

g

Fig. 4.34 Colony forming units (C.F.U.) of Cr




0

5

10

15

20

25

30

ALT6-1 AHT5-5 BLT5-2 BHT3-1 BHT7-2 CLT8-1 CHT3-2 DLT3-1 DHT6-2



C.F

.U.

(x10

5)/

g

Fig. 4.35 Colony forming units (C.F.U.) of Cr6+

(350 µg/ml of nutrient agar) resistant



Chapter 4 Results

142

0

36

9

12

1518

21

ALR3-4 AHR3-2 BLR6-1 BLR5-1 BLR8-2 BHR1-1 CLR4-2 CHR3-2 CHR9-1 DLR10-

1

DHR8-2

Low

flow

High

flow

Low flow High

flow

Low

flow

High flow Low

flow

High

flow

A B C D

Sampling Sites

C.F

.U.

(x105)/

g

Fig. 4.36 Colony forming units (C.F.U.) of Hg




0

5

10

15

20

25

ALM3-1 ALM9-1 AHM4-1 BLM9-1 BHM6-2 CLM4-1 CHM1-1 DLM2-2 DHM6-1


A B C D

Sampling Sites

C.F

.U.

(x105)/

g





0

4

8

12

16

ALT3-1 AHT8-1 BLT6-2 BHT6-1 CLT3-3 CLT3-2 CHT2-1 DLT8-1 DHT9-1


A B C D

Sampling Sites

C.F

.U.

(x10

5)/

g





Chapter 4 Results

143

4.5.1 Minimum inhibitory concentration (MIC) and multiple metal resistances of the

bacterial isolates:

The bacterial isolates were proceeded for determination of their minimum

inhibitory concentration (MIC) against different metals. It appeared that the metals

resistant potential of the bacteria ranged from 250 to 1000 µg/ml for Cu2+

, 350 to 1400

µg/ ml for Pb2+

, 10 to 70 µg/ ml for Hg2+

and 350 to 1650 µg/ ml for Cr6+

(Tables 4.20 to

4.23). Forty five isolates which showed growth in the presence of 750 to 1000 µg, 1100 to

1400 µg, 45 to 70 µg and 1100 to 1650 µg/ml of Cu2+

, Pb2+

, Hg2+

and Cr6+

, respectively

were selected for the further characterization and identification (Fig. 4.39 to 4.42). Out of

forty five selected isolates, 20, 13 and 12 represented isolation from Labeo rohita, Catla

catla and Cirrhinus mrigala, respectively. Site wise order of the select isolates 12 and 7

for site D during high and low flow seasons respectively. While isolates selected of site A

was 7 and 1 during high and low flow seasons respectively. Wherease isolates selected of

site C was 7 and 3 during high and low flow seasons respectively. The equal numbers of

isolates (4) selected during both low and high flow seasons (Fig. 4.39 to 4.42). Of the

total 45 select bacteria 2.23, 20 and 17 % isolates appeared resistant against Cu2+

ions up

to 1000, 950 and 900 µg/ml, respectively. While 2.23, 8.89 and 15.56 % were resistant

against 1400, 1350 and 1300 µg/ml of Pb2+

ions, respectively. In case of Hg 4.45, 2.23

and 13.34 % of the isolates expressed resistance up to presence of 70, 65 and 60 µg of the

metal ions/ml, respectively. For Cr, 11.12, 11.12 and 13.34 % of the isolates were

resistant to the presence of 1650, 1600 and 1550 µg/ml, respectively (Fig. 4.39 to 4.42).

Chapter 4 Results

144

Table 4.21 Determination of minimum inhibitory concentrations (MIC) of Pb2+

ions for the bacterial isolates. Growths (O.D600nm)

were raised with 2 % inoculations in the metal containing nutrient broths and incubate at 37 ºC for 24 hrs.

Isolate code Concentration of Pb µg/ml of nutrient broth

700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

ALR7-5 0.050

±0.022

0.020

±0.009 MIC - - - - - - - - - - - -

ALR2-1 0.067

±0.018

0.023

±0.019 MIC - - - - - - - - - - - -

AHR8-5 0.383

±0.053

0.300

±0.093

0.255

±0.030

0.094

±0.038

0.168

±0.063

0.120

±0.079

0.087

±0.016

0.072

±0.009

0.017

±0.022

0.009

±0.006

0.011

±0.001 MIC - - -

AHR4-2 0.482

±0.088

0.179

±0.078

0.287

±0.075

0.095

±0.040

0.276

±0.091

0.044

±0.029

0.116

±0.025

0.279

±0.047

0.150

±0.037

0.021

±0.019

0.011

±0.008 MIC - - -

AHR4-1 0.289

±0.077

0.306

±0.086

0.246

±0.046

0.279

±0.063

0.400

±0.077

0.161

±0.053

0.189

±0.033

0.277

±0.061

0.239

±0.037

0.061

±0.006

0.013

±0.001 MIC - - -

ALM1-1 0.116

±0.008

0.087

±0.016

0.032

±0.016 MIC - - - - - - - - - - -

AHM7-1 0.278

±0.016

0.195

±0.024

0.089

±0.093

0.094

±0.006

0.140

±0.039

0.067

±0.016

0.050

±0.025

0.007

±0.004 MIC - - - - - -

ALT4-5 0.189

±0.033

0.046

±0.014

0.018

±0.093 MIC - - - - - - - - - - -

AHT7-6 0.256

±0.031

0.172

±0.037

0.172

±0.039

0.149

±0.042

0.255

±0.061

0.173

±0.023

0.148

±0.071

0.106

±0.024

0.087

±0.016

0.025

±0.013

0.017

±0.006 MIC - - -

BLR6-1 0.601

±0.016

0.612

±0.063

0.450

±0.039

0.277

±0.062

0.313

±0.187

0.391

±0.096

0.406

±0.040

0.261

±0.057

0.155

±0.048

0.117

±0.102

0.064

±0.036

0.018

±0.007

0.004

±0.002 MIC -

BHR7-2 0.432

±0.047

0.334

±0.015

0.516

±0.069

0.266

±0.045

0.083

±0.022

0.111

±0.018

0.087

±0.016

0.055

±0.013

0.017

±0.006

0.011

±0.009 MIC - - - -

BLM4-1 0.416

±0.025

0.210

±0.030

0.144

±0.033

0.205

±0.023

0.251

±0.023

0.177

±0.030

0.187

±0.016

0.082

±0.023

0.067

±0.031

0.039

±0.022

0.012

±0.009 MIC - - -

BLM5-1 0.266

±0.045

0.371

±0.039

0.201

±0.063

0.150

±0.025

0.200

±0.003

0.126

±0.024

0.110

±0.016

0.151

±0.039

0.045

±0.047

0.015

±0.008 MIC - - - -

BHM1-1 0.395

±0.117

0.411

±0.018

0.255

±0.030

0.144

±0.033

0.268

±0.078

0.120

±0.079

0.137

±0.055

0.072

±0.022

0.027

±0.008

0.021

±0.016

0.005

±0.004 MIC - - --

Continued………...

Chapter 4 Results

145


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

BHM9-2 0.047

±0.018

0.023

±0.005 MIC - - - - - - - - - - - -

BLT7-3 0.054

±0.015

0.012

±0.002 MIC - - - - - - - - - - - --

BHT3-4 0.486

±0.139

0.400

±0.124

0.382

±0.071

0.221

±0.016

0.189

±0.033

0.116

±0.008

0.067

±0.013

0.010

±0.011 MIC - - - - -

BHT1-6 0.355

±0.202

0.388

±0.062

0.167

±0.064

0.061

±0.053

0.144

±0.030

0.070

±0.027

0.036

±0.028

0.083

±0.022

0.032

±0.016

0.011

±0.003

0.002

±0.001 MIC - - -

CLR3-3 0.066

±0.017

0.033

±0.017

0.015

±0.004 MIC - - - - - - - - - - -

CLR7-1 0.140

±0.023

0.071

±0.039

0.013

±0.011 MIC - - - - - - -- - - - -

CHR4-4 0.511

±0.078

0.622

±0.078

0.290

±0.078

0.216

±0.116

0.179

±0.047

0.144

±0.030

0.218

±0.008

0.177

±0.014

0.111

±0.018

0.070

±0.027

0.012

±0.006 MIC - - -

CLM6-2 0.040

±0.023

0.012

±0.006 MIC - - - - -- - - - - - - -

CHM5-2 0.508

±0.057

0.372

±0.086

0.389

±0.062

0.434

±0.063

0.305

±0.025

0.188

±0.014

0.156

±0.081

0.093

±0.059

0.071

±0.039

0.016

±0.010

0.012

±0.008

0.011

±0.002 MIC - -

CLT3-1 0.186

±0.045

0.160

±0.054

0.177

±0.014

0.218

±0.103

0.105

±0.021

0.034

±0.018

0.073

±0.034

0.059

±0.021

0.027

±0.009

0.012

±0,009 MIC - - - -

CHT9-1 0.383

±0.030

0.378

±0.094

0.261

±0.014

0.178

±0.008

0.172

±0.010

0.178

±0.025

0.087

±0.023

0.033

±0.011

0.013

±0.008

0.005

±0.001

0.010

±0.006 MIC - - -

CHT3-2 0.251

±0.054

0.288

±0.094

0.273

±0.040

0.210

±0.049

0.127

±0.009

0.217

±0.079

0.127

±0.016

0.068

±0.014

0.065

±0.004

0.044

±0.003

0.042

±0.004

0.014

±0.002

0.005

±0.001 MIC -

DLR3-1 0.506

±0.054

0.300

±0.077

0.356

±0.070

0.305

±0.030

0.322

±0.041

0.144

±0.025

0.218

±0.057

0.177

±0.035

0.111

±0.016

0.070

±0.033

0.012

±0.013

0.009

±0.001 MIC - -

DLR8-1 0.057

±0.054

0.020

±0.013 MIC - - - - - - - - - - - -

DHR1-1 0.405

±0.086

0.317

±0.016

0.392

±0.047

0.250

±0.023

0.199

±0.056

0.156

±0.030

0.189

±0.008

0.133

±0.014

0.138

±0.018

0.106

±0.027

0.034

±0.006

0.010

±0.005 MIC - -


Chapter 4 Results

146


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

DHR5-3 0.612

±0.063

0.500

±0.063

0.172

±0.047

0.212

±0.032

0.260

±0.054

0.155

±0.032

0.205

±0.010

0.083

±0.022

0.123

±0.029

0.035

±0.004

0.009

±0.004 MIC - - -

DHR2-2 0.366

±0.284

0.355

±0.202

0.388

±0.062

0.167

±0.064

0.155

±0.032

0.201

±0.016

0.061

±0.053

0.106

±0.023

0.034

±0.025

0.062

±0.008

0.032

±0.016

0.011

±0.003

0.006

±0.004 MIC -

DLM4-2 0.067

±0.018

0.029

±0.014 MIC - - - - - -- - - - - - -

DHM6-2 0.667

±0.141

0.273

±0.071

0.190

±0.032

0.155

±0.045

0.094

±0.006

0.034

±0.025

0.006

±0.001 MIC - - - - - - -

DLT5-1 0.687

±0.016

0.511

±0.078

0.622

±0.078

0.285

±0.086

0.190

±0.063

0.128

±0.040

0.145

±0.031

0.049

±0.023

0.028

±0.024

0.020

±0.002

0.011

±0.002 MIC - - -

DHT6-1 0.633

±0.124

0.678

±0.033

0.510

±0.016

0.369

±0.028

0.173

±0.071

0.111

±0.018

0.190

±0.032

0.053

±0.005

0.029

±0.031

0.016

±0.007 MIC - - - -

ALR5-1 0.032

±0.016

0.032

±0.005

0.0145

±0.008 MIC - -- - - - - - - - - -

AHR4-1 0.1105

±0.018

0.057

±0.027

0.012

±0.010 MIC - - - - - - - - - - --

ALM9-1 0.429

±0.038

0.255

±0.061

0.323

±0.030

0.386

±0.064

0.203

±0.038

0.178

±0.078

0.068

±0.042

0.074

±0.019

0.033

±0.014

0.010

±0.002 MIC - - - -

AHM3-1 0.384

±0.102

0.287

±0.077

0.389

±0.095

0.110

±0.018

0.117

±0.036

0.110

±0.049

0.106

±0.089

0.054

±0.030

0.060

±0.009

0.016

±0.006

0.011

±0.011 - - - -

AHM4-2 0.289

±0.032

0.277

±0.062

0.132

±0.049

0.075

±0.015

0.048

±0.008

0.008

±0.006 MIC - - - - - - - -

ALT6-1 0.047

±0.013

0.016

±0.006 MIC - - - - - -- - - - - - -

AHT5-5 0.533

±0.049

0.625

±0.070

0.4

±0.078

0.110

±0.049

0.249

±0.053

0.132

±0.049

0.081

±0.021

0.228

±0.023

0.128

±0.006

0.078

±0.034

0.013

±0.008 MIC - - -

BLR8-3 0.344

±0.045

0.249

±0.053

0.217

±0.028

0.198

±0.047

0.127

±0.041

0.027

±0.009

0.012

±0.008

0.005

±0.005 MIC - - - - - -

BLR6-5 0.276

±0.031

0.210

±0.018

0.106

±0.024

0.072

±0.023

0.095

±0.024

0.043

±0.016

0.015

±0.008 MIC - - - - -- - -


Chapter 4 Results

147


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

BHR2-1 0.426

±0.040

0.428

±0.165

0.253

±0.192

0.280

±0.069

0.170

±0.026

0.115

±0.024

0.478

±0.069

0.026

±0.008

0.01

±0.003 MIC - - - - -

BLM8-1 0.389

±0.063

0.218

±0.029

0.150

±0.039

0.332

±0.013

0.186

±0.074

0.128

±0.086

0.12

±0.044

0.213

±0.107

0.018

±0.004

0.005

±0.005 MIC - - - -

BHM6-1 0.288

±0.076

0.276

±0.090

0.139

±0.024

0.1

±0.033

0.204

±0.037

0.052

±0.002

0.069

±0.025

0.012

±0.012

0.005

±0.003 MIC - - - - -

BLT5-2 0.0905

±0.018

0.057

±0.013

0.015

±0.005 MIC - - - - - - - - - - -

BHT3-1 0.709

±0.082

0.304

±0.009

0.443

±0.016

0.255

±0.062

0.323

±0.030

0.195

±0.024

0.366

±0.030

0.239

±0.039

0.187

±0.016

0.105

±0.054

0.278

±0.065

0.178

±0.107

0.023

±0.016

0.014

±0.010 MIC

BHT7-2 0.516

±0.041

0.300

±0.002

0.245

±0.047

0.236

±0.028

0.111

±0.063

0.052

±0.013

0.021

±0.011

0.007

±0.006 MIC - - - - - -

CLR8-1 0.067

±0.030

0.024

±0.008 MIC - - - - - - - - - - - -

CHR3-2 0.287

±0.075

0.164

±0.048

0.200

±0.016

0.269

±0.076

0.275

±0.063

0.133

±0.014

0.161

±0.023

0.066

±0.033

0.082

±0.009

0.048

±0.004

0.026

±0.007

0.013

±0.002

0.031

±0.040 MIC -

CHR3-1 0.508

±0.079

0.356

±0.047

0.446

±0.018

0.155

±0.048

0.072

±0.008

0.309

±0.047

0.081

±0.024

0.106

±0.023

0.087

±0.016

0.093

±0.040

0.071

±0.037

0.013

±0.011

0.01

±0.003 MIC -

CLM4-1 0.073

±0.010

0.021

±0.003 MIC - - - - - - - - - - - -

CLM6-3 0.045

±0.018

0.020

±0.012 MIC - - -- - - - - - - - - -

CHM1-2 0.416

±0.054

0.382

±0.053

0.307

±0.037

0.155

±0.048

0.055

±0.014

0.033

±0.006

0.01

±0.004 MIC - - - - - - -

CLT8-1 0.365

±0.031

0.217

±0.008

0.129

±0.024

0.071

±0.022

0.21

±0.030

0.078

±0.016

0.054

±0.031

0.028

±0.036

0.011

±0.003 MIC - - - - -

CHT3-2 0.429

±0.039

0.327

±0.006

0.3

±0.018

0.162

±0.071

0.036

±0.028

0.178

±0.016

0.054

±0.031

0.065

±0016

0.018

±0.006

0.014

±0.008 MIC - - - -

DLR1-3 0.436

±0.045

0.361

±0.054

0.227

±0.035

0.383

±0.071

0.407

±0.037

0.261

±0.040

0.235

±0.076

0.085

±0.014

0.036

±0.010

0.041

±0.040 MIC - - - -


Chapter 4 Results

148


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

DLR4-3 0.106

±0.011

0.077

±0.013

0.03

±0.013 MIC - - - - - - - - - - -

DHR1-5 0.490

±0.047

0.609

±0.066

0.427

±0.069

0.384

±0.068

0.266

±0.045

0.370

±0.039

0.200

±0.063

0.137

±0.008

0.115

±0.008

0.088

±0.014

0.016

±0.006 MIC - -

DHR6-4 0.256

±0.031

0.131

±0.018

0.088

±0.049

0.134

±0.031

0.111

±0.032

0.058

±0.010

0.110

±0.018

0.014

±0.010

0.027

±0.022

0.007

±0.002 MIC - - - -

DLM3-1 0.191

±0.018

0.254

±0.035

0.338

±0.022

0.234

±0.054

0.281

±0.024

0.308

±0.081

0.183

±0.069

0.038

±0.025

0.127

±0.022

0.007

±0.002 MIC - - - -

DHM5-1 0.6005

±0.016

0.611

±0.063

0.149

±0.039

0.277

±0.062

0.313

±0.187

0.391

±0.096

0.406

±0.040

0.155

±0.048

0.205

±0.023

0.067

±0.031

0.035

±0.011

0.009

±0.006 MIC - -

DLT3-1 0.218

±0.008

0.110

±0.018

0.139

±0.039

0.136

±0.023

0.271

±0.037

0.222

±0.047

0.093

±0.040

0.065

±0.047

0.019

±0.014 MIC - - - - -

DHT6-2 0.277

±0.062

0.278

±0.221

0.226

±0.148

0.127

±0.085

0.105

±0.041

0.060

±0.053

0.025

±0.006

0.013

±0.007 MIC - - - - -

ALR3-4 0.016

±0.006 MIC - - - - -- - - - - - - - -

AHR3-2 0.110

±0.018

0.101

±0.106

0.111

±0.032

0.058

±0.010

0.054

±0.031

0.016

±0.006

0.006

±0.001 MIC - - - - - - -

ALM3-1 0.182

±0.022

0.155

±0.045

0.074

±0.033

0.217

±0.008

0.064

±0.068

0.072

±0.023

0.071

±0.006

0.043

±0.016

0.006

±0.004 MIC - - - - -

ALM9-1 0.222

±0.015

0.150

±0.039

0.074

±0.033

0.195

±0.024

0.019

±0.005

0.067

±0.031

0.026

±0.008

0.006

±0.004

0.0045

±0.004 MIC - - - - -

AHM4-1 0.181

±0.087

0.143

±0.030

0.217

±0.008

0.187

±0.001

0.110

±0.018

0.143

±0.077

0.134

±0.016

0.056

±0.031

0.033

±0.025

0.005

±0.003 MIC - - - -

ALT3-1 0.018

±0.004

0.006

±0.004 MIC - - - - - - - - - - - -

AHT8-1 0.031

±0.003

0.051

±0.055 MIC

- - - - - - - - - - - -

BLR6-1 0.195

±0.024

0.156

±0.031

0.15

±0.040

0.145

±0.030

0.200

±0.032

0.245

±0.047

0.076

±0.031

0.013

±0.013 MIC - - - - -


Chapter 4 Results

149


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

BLR5-1 0.155

±0.045

0.073

±0.067

0.121

±0.077

0.047

±0.006

0.036

±0.028

0.012

±0.006 MIC - - - - - - - -

BLR8-2 0.156

±0.031

0.161

±0.024

0.198

±0.047

0.182

±0.022

0.155

±0.045

0.095

±0.024

0.053

±0.004

0.017

±0.007 MIC - - - - - -

BHR1-1 0.084

±0.025

0.049

±0.009

0.019

±0.005

0.089

±0.047

0.078

±0.016

0.041

±0.013

0.012

±0.013 MIC - - - - - - -

BLM9-1 0.015

±0.004 MIC - - - - - - - - - - - - -

BHM6-2 0.009

±0.001 MIC - - - - -- - - - - - - - -

BLT6-2 0.008

±0.001 MIC - - - - - - - - - - - - -

BHT6-1 0.017

±0.009 MIC - - - - - - - - - - - - -

CLR4-2 0.0145

±0.003 MIC - - - - - - - - - - - - -

CHR3-2 0.004

±0.009 MIC - - - - - - - - - - - - -

CHR9-1 0.013

±0.004 MIC - - - - - - -- - - - - - -

CLM4-1 0.199

±0.002

0.172

±0.071

0.167

±0.063

0.105

±0,021

0.199

±0.098

0.155

±0.045

0.081

±0.012

0.132

±0.021

0.115

±0.032

0.072

±0.012

0.033

±0.009

0.004

±0.000 MIC - -

CHM1-1 0.017

±0.018

0.015

±0.004 MIC - - - - - - - - - - - -

CLT3-3 0.128

±0.008

0.100

±0.016

0.083

±0.026

0.133

±0.021

0.108

±0.011

0.089

±0.016

0.024

±0.011

0.014

±0.008

0.006

±0.002 MIC - - - - -

CLT3-2 0.131

±0.022

0.088

±0.049

0.100

±0.016

0.058

±0.011

0.014

±0.003

0.007

±0.003 MIC - - - - - - - -

CHT2-1 0.012

±0.018 MIC - - - - - - - - - - - - -


Chapter 4 Results

150


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

DLR10-1 0.161

±0.024

0.208

±0.127

0.200

±0.016

0.177

±0.021

0.110

±0.027

0.061

±0.016

0.057

±0.024

0.087

±0.018

0.016

±0.004

0.005

±0.000 MIC - - - -

DHR8-2 0.256

±0.047

0.416

±0.041

0.154

±0.046

0.266

±0.098

0.189

±0.024

0.188

±0.033

0.155

±0.012

0.093

±0.011

0.098

±0.021

0.033

±0.013

0.004

±0.000 MIC - - -

DLM2-2 0.183

±0.008

0.156

±0.078

0.078

±0.062

0.072

±0.014

0.087

±0.021

0.01

±0.004

0.07

±0.009

0.017

±0.011 MIC - - - - - -

DHM6-1 0.106

±0.024

0.105

±0.010

0.087

±0.016

0.024

±0.016

0.014

±0.026

0.016

±0.004 MIC - - - - - - - -

DLT8-1 0.172

±0.071

0.110

±0.018

0.205

±0.010

0.144

±0.033

0.167

±0.016

0.184

±0.040

0.083

±0.008

0.033

±0.025

0.014

±0.010

0.005

±0.004 MIC - - - -

DHT9-1 0.664

±0.800

0.110

±0.018

0.166

±0.045

0.266

±0.046

0.336

±0.010

0.06

±0.023

0.032

±0.016

0.032

±0.005

0.031

±0.014 MIC - - - - -

ALR5-3 0.018

±0.004 MIC - -- - - - - - - - - - -- -

AHR7-5 0.482

±0.022

0.322

±0.156

0.243

±0.111

0.260

±0.053

0.293

±0.135

0.278

±0.062

0.156

±0.031

0.110

±0.018

0.033

±0.025

0.032

±0.025

0.007

±0.016 MIC - - -

AHR6-1 0.013

±0.006 MIC - - - - - - - - - - - - -

ALM6-2 0.015

±0.004 MIC - - - - - - - - - - - - -

AHM9-1 0.294

±0.072

0.150

±0.039

0.081

±0.023

0.026

±0.008 MIC - - - - - - - - - -

ALT8-2 0.009

±0.004 MIC - - - - - - - - - - - - -

AHT4-4 0.072

±0.070

0.025

±0.008 MIC - - - - - - - - - - -- -

AHT3-2 0.511

±0.078

0.832

±0.219

0.831

±0.064

0.722

±0.063

0.504

±0.085

0.288

±0.078

0.427

±0.165

0.322

±0.156

0.143

±0.030

0.070

±0.039

0.055

±0.045

0.041

±0.018 MIC - -

BLR8-1 0.017

±0.008 MIC - - - - - - - - - - - -- -


Chapter 4 Results

151


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

BHR5-2 0.011

±0.003 MIC - - - - - - - - - - - - -

BLM8-2 0.671

±0.148

0.506

±0.071

0.732

±0.076

0.776

±0.141

0.555

±0.016

0.504

±0.085

0.299

±0.064

0.215

±0.025

0.107

±0.013

0.082

±0.009

0.039

±0.010 MIC - - -

BHM5-1 0.037

±0.008

0.027

±0.008

0.007

±0.002 MIC - - - - - - - - - - -

BLT2-1 0.008

±0.001 MIC - - - - - - - - - - - - -

BHT6-1 0.833

±0.063

0.671

±0.148

0.832

±0.063

0.665

±0.170

0.663

±0.151

0.617

±0.086

0.377

±0.094

0.31

±0.124

0.298

±0.189

0.167

±0.064

0.087

±0.016

0.032

±0.016 MIC - -

CLR2-1 0.010

±0.002 MIC - - - - -- - - - - - - - -

CHR3-1 0.726

±0.071

0.722

±0.220

0.610

±0.018

0.508

±0.107

0.437

±0.071

0.322

±0.014

0.321

±0.157

0.198

±0.047

0.167

±0.064

0.093

±0.024

0.070

±0.039 MIC - - -

CLM4-1 0.485

±0.139

0.421

±0.093

0.322

±0.014

0.321

±0.157

0.215

±0.024

0.155

±0.014

0.167

±0.064

0.104

±0.008

0.066

±0.017

0.070

±0.039

0.016

±0.006 MIC - - -

CHM7-1 0.293

±0.117

0.399

±0.046

0.277

±0.092

0.143

±0.030

0.1

±0.003

0.105

±0.054

0.078

±0.065

0.038

±0.022

0.013

±0.006 MIC - - - -- -

CLT2-2 0.016

±0.006 MIC - - - - - - - - - - - - -

CHT2-2 0.333

±0.141

0.371

±0.086

0.188

±0.033

0.072

±0.070

0.193

±0.135

0.195

±0.024

0.088

±0.093

0.093

±0.006

0.095

±0.024

0.055

±0.021

0.020

±0.001 MIC - - -

CHT6-1 0.188

±0.064

0.116

±0.025

0.065

±0.047

0.016

±0.006 MIC - - - - - - - - - -

DLR1-5 0.304

±0.025

0.465

±0.047

0.309

±0.016

0.246

±0.018

0.199

±0.018

0.177

±0.014

0.127

±0.009

0.082

±0.022

0.070

±0.008

0.044

±0.014

0.015

±0.002 MIC - - -

DHR4-2 0.285

±0.010

0.239

±0.098

0.294

±0.039

0.154

±0.069

0.103

±0.046

0.077

±0.008

0.048

±0.014

0.027

±0.008 MIC - - - - - -

DHR5-1 0.437

±0.071

0.394

±0.054

0.415

±0.024

0.338

±0.085

0.167

±0.063

0.194

±0.103

0.081

±0.023

0.033

±0.014 MIC - - - - - -


Chapter 4 Results

152


700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 1300 1350 1400

DLM1-2 0.11

±0.016

0.082

±0.022

0.042

±0.015 MIC - - - - - - - - - - -

DLM6-2 0.025

±0.010 MIC - - - - - - - - - - - - -

DHM2-1 0.099

±0.017

0.044

±0.013 MIC - - - - - - - - - - - -

DLT9-2 0.371

±0.086

0.188

±0.033

0.072

±0.070

0.077

±0.014

0.026

±0.008 MIC - - - - - - - - -

DHT3-1 0.778

±0.141

0.421

±0.229

0.21

±0.033

0.267

±0.078

0.199

±0.046

0.127

±0.009

0.145

±0.059

0.082

±0.022

0.060

±0.022

0.032

±0.028 MIC - - - -

DHT9-2 0.18

±0.083

0.081

±0.024

0.038

±0.025 MIC - - - - - - - - - -

Values = means±SD

- = no growth

Chapter 4 Results

153

Table 4.22 Determination of minimum inhibitory concentrations (MIC) of Cu2+



Isolate Code Concentration of Cu µg/ml of nutrient broth

500 550 600 650 700 750 800 850 900 950 1000 1050

ALR7-5 0.048

±0.021

0.026

±0.008 MIC - - - - - - - - -

ALR2-1 0.018

±0.007

0.014

±0.011 MIC - - - - - - - - -

AHR8-5 0.306

±0.024

0.256

±0.047

0.199

±0.018

0.177

±0.014

0.133

±0.063

0.033

±0.025

0.015

±0.005 MIC - - - -

AHR4-2 0.155

±0.033

0.087

±0.078

0.066

±0.061

0.025

±0.009

0.053

±0.004

0.014

±0.001

0.009

±0.009 MIC - - - -

AHR4-1 0.22

±0.016

0.195

±0.024

0.084

±0.054

0.060

±0.053

0.025

±0.009

0.026

±0.020 MIC - - - - -

ALM1-1 0.036

±0.028

0.078

±0.016

0.022

±0.013 MIC - - - - - - - -

AHM7-1 0.043

±0.028

0.023

±0.008 MIC - - - - - - - - -

ALT4-5 0.033

±0.014

0.014

±0.009 MIC - - - - - - - - -

AHT7-6 0.07

±0.027

0.059

±0.011

0.012

±0.005 MIC - - - - - - - -

BLR6-1 0.232

±0.093

0.271

±0.006

0.178

±0.048

0.136

±0.018

0.067

±0.049

0.033

±0.030

0.006

±0.001 MIC - - - -

BHR7-2 0.200

±0.016

0.310

±0.018

0.175

±0.083

0.182

±0.069

0.112

±0.015

0.035

±0.027

0.018

±0.004

0.008

±0.006 MIC - - -

BLM4-1 0.288

±0.045

0.261

±0.039

0.200

±0.016

0.127

±0.041

0.093

±0.037

0.017

±0.005 MIC - - - - -

BLM5-1 0.306

±0.024

0.23

±0.025

0.235

±0.089

0.161

±0.072

0.087

±0.016

0.083

±0.057

0.016

±0.006

0.012

±0.008 MIC - - -

BHM1-1 0.105

±0.023

0.106

±0.012

0.033

±0.025

0.061

±0.008

0.032

±0.016

0.011

±0.003

0.009

±0.009 MIC - - - -


Chapter 4 Results

154


500 550 600 650 700 750 800 850 900 950 1000 1050

BHM9-2 0.044

±0.033

0.043

±0.015

0.041

±0.018

0.008

±0.006 MIC - - - - - - -

BLT7-3 0.044

±0.014

0.020

±0.012 MIC - - - - - - - - -

BHT3-4 0.176

±0.031

0.083

±0.057

0.026

±0.018

0.015

±0.011 MIC - - - - - - -

BHT1-6 0.056

±0.016

0.055

±0.048

0.012

±0.001 MIC - - - - - - - -

CLR3-3 0.031

±0.016

0.012

±0.005 MIC - - - - - - - - -

CLR7-1 0.035

±0.008

0.02

±0.001 MIC - - - - - - - - -

CHR4-4 0.037

±0.023

0.026

±0.024

0.009

±0.005 MIC - - - - - - - -

CLM6-2 0.043

±0.016

0.015

±0.004 MIC - - - - - - - - -

CHM5-2 0.234

±0.030

0.208

±0.015

0.099

±0.033

0.081

±0.023

0.044

±0.014

0.017

±0.008

0.011

±0.003 MIC - - - -

CLT3-1 0.181

±0.020

0.124

±0.028

0.168

±0.062

0.067

±0.049

0.033

±0.030

0.005

±0.003 MIC - - - - -

CHT9-1 0.218

±0.029

0.128

±0.008

0.166

±0.033

0.084

±0.011

0.076

±0.032

0.055

±0.017

0.032

±0.016

0.009

±0.004 MIC - - -

CHT3-2 0.188

±0.014

0.155

±0.081

0.092

±0.059

0.070

±0.039

0.016

±0.010

0.011

±0.008 MIC - - - - -

DLR3-1 0.304

±0.025

0.200

±0.016

0.059

±0.011

0.07

±0.027

0.041

±0.036

0.007

±0.003 MIC - - - - -

DLR8-1 0.038

±0.007

0.010

±0.002 MIC - - - - - - - - -

DHR1-1 0.172

±0.008

0.131

±0.020

0.182

±0.069

0.1125

±0.015

0.035

±0.027

0.043

±0.031

0.015

±0.006

0.006

±0.004 MIC - - -


Chapter 4 Results

155


500 550 600 650 700 750 800 850 900 950 1000 1050

DHR5-3 0.227

±0.022

0.116

±0.057

0.110

±0.018

0.049

±0.022

0.033

±0.030

0.016

±0.010

0.012

±0.001

0.009

±0.004 MIC - - -

DHR2-2 0.192

±0.008

0.139

±0.103

0.087

±0.016

0.105

±0.054

0.189

±0.032

0.101

±0.033

0.054

±0.031

0.09

±0.017

0.033

±0.030

0.006

±0.001 MIC -

DLM4-2 0.038

±0.021

0.025

±0.006 MIC - - - - - - - - -

DHM6-2 0.143

±0.030

0.070

±0.039

0.055

±0.045

0.041

±0.018 MIC - - - - - - -

DLT5-1 0.250

±0.054

0.181

±0.020

0.149

±0.038

0.111

±0.032

0.058

±0.010

0.054

±0.031

0.016

±0.006

0.021

±0.012

0.006

±0.001 MIC - -

DHT6-1 0.150

±0.008

0.111

±0.032

0.195

±0.024

0.071

±0.006

0.043

±0.016

0.011

±0.001

0.010

±0.002 MIC - - - -

ALR5-1 0.008

±0.008 MIC - - - - - - - - - -

AHR4-1 0.02

±0.011 MIC - - - - - - - - - -

ALM9-1 0.454

±0.014

0.299

±0.064

0.288

±0.078

0.157

±0.057

0.115

±0.040

0.067

±0.030

0.017

±0.006 MIC - - - -

AHM3-1 0.535

±0.013

0.499

±0.078

0.388

±0.078

0.207

±0.013

0.125

±0.026

0.026

±0.018 MIC - - - - -

AHM4-2 0.039

±0.010

0.009

±0.004 MIC - - - - - - - - -

ALT6-1 MIC - - - - - - - - - - -

AHT5-5 0.256

±0.063

0.148

±0.023

0.112

±0.013

0.060

±0.025

0.04

±0.024

0.036

±0.011

0.015

±0.005 MIC - - - -

BLR8-3 0.079

±0.013

0.052

±0.010

0.027

±0.008

0.016

±0.006 MIC - - - - - - -

BLR6-5 0.161

±0.039

0.102

±0.028

0.057

±0.016

0.018

±0.008 MIC - - - - - - -


Chapter 4 Results

156


500 550 600 650 700 750 800 850 900 950 1000 1050

BHR2-1 0.093

±0.024

0.115

±0.024

0.032

±0.016 MIC - - - - - - - -

BLM8-1 0.156

±0.016

0.033

±0.017

0.026

±0.020 MIC - - - - - - - -

BHM6-1 0.166

±0.030

0.043

±0.003

0.018

±0.006 MIC - - - - - - - -

BLT5-2 0.01

±0.011 MIC - - - - - - - - - -

BHT3-1 0.617

±0.086

0.5

±0.079

0.3545

±0.062

0.193

±0.040

0.322

±0.156

0.099

±0.033

0.070

±0.039

0.016

±0.006

0.006

±0.004 MIC - -

BHT7-2 0.059

±0.024

0.015

±0.008 MIC - - - - - - - - -

CLR8-1 0.029

±0.013 MIC - - - - - - - - - -

CHR3-2 0.499

±0.093

0.371

±0.069

0.193

±0.040

0.322

±0.156

0.099

±0.033

0.070

±0.039

0.018

±0.003 MIC - - - -

CHR3-1 0.444

±0.171

0.383

±0.102

0.248

±0.021

0.193

±0.040

0.022

±0.001

0.07

±0.027

0.012

±0.012 MIC - - - -

CLM4-1 0.014

±0.006 MIC - - - - - - - - - -

CLM6-3 0.014

±0.009 MIC - - - - - - - - - -

CHM1-2 0.094

±0.038

0.087

±0.016

0.049

±0.022

0.037

±0.023

0.011

±0.004 MIC - - - - - -

CLT8-1 0.186

±0.011

0.110

±0.018

0.033

±0.025

0.014

±0.007 MIC - - - - - - -

CHT3-2 0.084

±0.017

0.026

±0.008 MIC - - - - - - - - -

DLR1-3 0.116

±0.006

0.088

±0.014

0.066

±0.014

0.102

±0.029

0.043

±0.016

0.015

±0.008

0.017

±0.007 MIC - - - -


Chapter 4 Results

157


500 550 600 650 700 750 800 850 900 950 1000 1050

DLR4-3 0.085

±0.035 MIC - - - - - - - - - -

DHR1-5 0.018

±0.007

0.110

±0.018

0.117

±0.040

0.206

±0.040

0.123

±0.031

0.041

±0.013

0.019

±0.003

0.026

±0.008

0.005

±0.004 MIC - -

DHR6-4 0.35

±0.055

0.322

±0.156

0.158

±0.052

0.070

±0.039

0.075

±0.017

0.041

±0.018

0.015

±0.005 MIC - - - -

DLM3-1 0.188

±0.033

0.116

±0.008

0.103

±0.035

0.472

±0.191

0.032

±0.016

0.007

±0.006 MIC - - - - -

DHM5-1 0.160

±0.053

0.117

±0.036

0.087

±0.016

0.060

±0.009

0.032

±0.016

0.015

±0.008 MIC - - - - -

DLT3-1 0.081

±0.023

0.044

±0.014

0.017

±0.008

0.011

±0.003 MIC - - - - - - -

DHT6-2 0.083

±0.002

0.135

±0.106 MIC - - - - - - - - -

ALR3-4 0.038

±0.007 MIC - - - - - - - - - -

AHR3-2 0.027

±0.009

0.005

±0.004 MIC - - - - -- - - - -

ALM3-1 0.059

±0.023

0.030

±0.012

0.011

±0.004 MIC - - - - - - - -

ALM9-1 0.116

±0.025

0.030

±0.018

0.015

±0.006 MIC - - - - - - - -

AHM4-1 0.221

±0.016

0.188

±0.033

0.200

±0.016

0.143

±0.030

0.093

±0.024

0.087

±0.016

0.01

±0.003 MIC - - - -

ALT3-1 0.005

±0.005 MIC - - - - - - - - - -

AHT8-1 0.015

±0.004 MIC - - - - - - - - - -

BLR6-1 0.410

±0.062

0.509

±0.075

0.387

±0.063

0.222

±0.017

0.322

±0.029

0.127

±0.022

0.044

±0.030

0.022

±0.015

0.010

±0.002 MIC - -


Chapter 4 Results

158


500 550 600 650 700 750 800 850 900 950 1000 1050

BLR5-1 0.194

±0.025

0.093

±0.024

0.070

±0.039

0.015

±0.008 MIC - - - - - - -

BLR8-2 0.058

±0.048

0.015

±0.006

0.007

±0.003 MIC - - - - - - - -

BHR1-1 0.014

±0.010

0.007

±0.006 MIC - - - - - - - - -

BLM9-1 0.071

±0.069 MIC - - - - - - - - - -

BHM6-2 0.015

±0.008 MIC - - - - - - - - - -

BLT6-2 0.017

±0.008 MIC - - - - - - - - - -

BHT6-1 0.021

±0.004

0.007

±0.003 MIC - - - - - - - - -

CLR4-2 0.02

±0.001

0.061

±0.083 MIC - - - - - - - - -

CHR3-2 0.007

±0.001 MIC - - - - - - - - - -

CHR9-1 0.079

±.086 MIC - - - - - - - - - -

CLM4-1 0.188

±0.033

0.111

±0.016

0.104

±0.022

0.036

±0.021

0.034

±0.019

0.007

±0.006 MIC - - - - -

CHM1-1 0.096

±0.118 MIC - - - - - - - - - -

CLT3-3 0.195

±0.024

0.081

±0.023

0.049

±0.025

0.016

±0.007 MIC - - - - - - -

CLT3-2 0.055

±0.045

0.025

±0.008

0.01

±0.001 MIC - - - - - - - -

CHT2-1 0.033

±0.017

0.0115

±0.001 MIC - - - - - - - - -


Chapter 4 Results

159


500 550 600 650 700 750 800 850 900 950 1000 1050

DLR10-1 0.461

±0.039

0.218

±0.023

0.316

±0.025

0.172

±0.036

0.273

±0.040

0.132

±0.013

0.065

±0.021

0.022

±0.011

0.005

±0.004 MIC - -

DHR8-2 0.367

±0.031

0.474

±0.034

0.355

±0.061

0.222

±0.017

0.331

±0.032

0.182

±0.022

0.08

±0.057

0.021

±0.004

0.012

±0.001 MIC - -

DLM2-2 0.014

±0.010

0.016

±0.007 MIC - - - - - - - - -

DHM6-1 0.022

±0.015 MIC - - - - - - - - - -

DLT8-1 0.216

±0.010

0.378

±0.016

0.278

±0.062

0.150

±0.039

0.122

±0.017

0.087

±0.051

0.009

±0.010 MIC - - - -

DHT9-1 0.316

±0.039

0.489

±0.078

0.377

±0.077

0.138

±0.037

0.070

±0.039

0.050

±0.039

0.041

±0.018

0.015

±0.008 MIC - - -

ALR5-3 0.017

±0.002 MIC - - - - - - - - - -

AHR7-5 0.021

±0.086

0.007

±0.078

0.113

±0.037

0.076

±0.016

0.043

±0.018

0.018

±0.005

0.005

±0.001 MIC - - - -

AHR6-1 0.02

±0.040

0.061

±0.053 MIC - - - - - - - - -

ALM6-2 0.007

±0.053 MIC - - - - - - - - -

AHM9-1 0.665

±0.134

0.85

±0.099

0.305

±0.120

0.175

±0.081

0.182

±0.086

0.023

±0.023 MIC - - - - -

ALT8-2 0.050

±0.003 MIC - - - - - - - - - -

AHT4-4 0.375

±0.191

0.495

±0.219

0.126

±0.048

0.021

±0.004 MIC - - - - - - -

AHT3-2 0.301

±0.059

0.342

±0.081

0.406

±0.050

0.277

±0.015

0.082

±0.086

0.034

±0.023 MIC - - - - -

BLR8-1 0.428

±0.090

0.267

±0.157

0.219

±0.002

0.293

±0.086

0.234

±0.127

0.176

±0.079

0.015

±0.017 MIC - - - -


Chapter 4 Results

160


500 550 600 650 700 750 800 850 900 950 1000 1050

BHR5-2 0.642

±0.169

0.405

±0.038

0.184

±0.074

0.126

±0.024

0.099

±0.030

0.006

±0.004 MIC - - - - -

BLM8-2 0.775

±0.142

0.262

±0.102

0.110

±0.049

0.199

±0.018

0.082

±0.022

0.071

±0.006

0.134

±0.014

0.067

±0.049

0.009

±0.004 MIC - -

BHM5-1 0.256

±0.121

0.227

±0.086

0.188

±0.096

0.42

±0.025 MIC - - - - - - -

BLT2-1 0.007

±0.001 MIC - - - - - - - - -- -

BHT6-1 0.110

±0.049

0.149

±0.053

0.082

±0.022

0.221

±0.064

0.174

±0.071

0.065

±0.047

0.038

±0.038

0.026

±0.008 MIC - - -

CLR2-1 0.009

±0.001 MIC - - - - - - - - - -

CHR3-1 0.781

±0.305

0.227

±0.149

0.333

±0.141

0.177

±0.078

0.088

±0.014

0.023

±0.016

0.011

±0.006 MIC - - - -

CLM4-1 0.422

±0.062

0.334

±0.139

0.120

±0.016

0.149

±0.088

0.1

±0.031

0.022

±0.012 MIC - - - - -

CHM7-1 0.552

±0.145

0.273

±0.212

0.340

±0.168

0.106

±0.040

0.023

±0.015 MIC - - - - - -

CLT2-2 0.012

±0.002

0.009

±0.001 MIC - - - - - - - - -

CHT2-2 0.870

±0.141

0.943

±0.066

0.394

±0.071

0.388

±0.220

0.371

±0.086

0.188

±0.033

0.072

±0.070

0.093

±0.006

0.033

±0.025 MIC - -

CHT6-1 0.555

±0.140

0.711

±0.080

0.273

±0.072

0.11

±0.017

0.026

±0.008 MIC - - - - - -

DLR1-5 0.166

±0.030

0.089

±0.032

0.137

±0.055

0.195

±0.101

0.128

±0.136

0.082

±0.024

0.016

±0.007

0.022

±0.014 MIC - - -

DHR4-2 0.110

±0.049

0.199

±0.018

0.082

±0.022

0.070

±0.008

0.133

±0.030

0.032

±0.016 MIC - - - - -

DHR5-1 0.511

±0.095

0.288

±0.078

0.427

±0.165

0.322

±0.156

0.143

±0.030

0.060

±0.053

0.07

±0.027

0.014

±0.009 MIC - - -


Chapter 4 Results

161


500 550 600 650 700 750 800 850 900 950 1000 1050

DLM1-2 0.098

±0.047

0.126

±0.024

0.099

±0.030

0.016

±0.010

0.015

±0.005

0.015

±0.009 MIC - - - - -

DLM6-2 0.018

±0.012 MIC - - - - - - - - - -

DHM2-1 0.139

±0.103

0.087

±0.016

0.088

±0.033

0.087

±0.094

0.008

±0.006 MIC - - - - - -

DLT9-2 0.499

±0.063

0.371

±0.086

0.188

±0.033

0.072

±0.070

0.026

±0.007

0.010

±0.002 MIC - - - - -

DHT3-1 0.620

±0.077

0.566

±0.156

0.532

±0.049

0.388

±0.062

0.188

±0.033

0.072

±0.007

0.093

±0.006

0.033

±0.025

0.032

±0.016

0.006

±0.004 MIC -

DHT9-2 0.421

±0.062

0.187

±0.098

0.237

±0.023

0.138

±0.008

0.018

±0.008 MIC - - - - - - Values = means±SD

- = no growth

Chapter 4 Results

162

Table 4.23 Determination of minimum inhibitory concentrations (MIC) of Hg2+



Isolate Code Concentration of Hg µg/ml of nutrient broth

20 25 30 35 40 45 50 55 60 65 70 75

ALR7-5 0.026

±0.008

0.006

±0.001

MIC - - - - - - - - -

ALR2-1 0.09

±0.006

0.046

±0.026

0.009

±0.004 MIC - - - - - - - -

AHR8-5 0.181

±0.008

0.167

±0.064

0.087

±0.016

0.115

±0.040

0.032

±0.016

0.013

±0.007 MIC - - - - -

AHR4-2 0.234

±0.031

0.128

±0.055

0.057

±0.018

0.04

±0.027

0.022

±0.015

0.017

±0.006 MIC - - - - -

AHR4-1 0.204

±0.040

0.150

±0.023

0.054

±0.031

0.043

±0.015

0.006

±0.004 MIC - - - - - -

ALM1-1 0.115

±0.012

0.067

±0018

0.017

±0.002 MIC - - - - - - - -

AHM7-1 0.15

±0.040

0.070

±0.030

0.055

±0.006

0.021

± 0.006 MIC - - - - - - -

ALT4-5 0.067

±0.016

0.017

±0.006 MIC - - - - - - - - -

AHT7-6 0.166

±0.032

0.088

±0.001

0.033

±0.018

0.013

±0003 MIC - - - - - - -

BLR6-10 0.232

±0.062

0.133

±0.030

0.077

±0.049

0.081

±0.023

0.013

±0.011 MIC - - - - - -

BHR7-2 0.096

±0.028

0.056

±0.047

0.038

±0.009

0.015

±0.008

0.017

±0.009

0.004

±0.001 MIC - - - - -

BLM4-1 0.149

±0.037

0.282

±0.022

0.11

±0.017

0.054

±0.016

0.017

±0.008 MIC - - - - - -

BLM5-1 0.193

±0.056

0.189

±0.123

0.081

±0.024

0.087

±0.016

0.095

±0.040

0.033

±0.017

0.011

±0.003 MIC - - - -

BHM1-1 0.205

±0.038

0.103

±0.039

0.039

±0.008

0.017

±0.006

0.008

±0.005 MIC - - - - - -


Chapter 4 Results

163


20 25 30 35 40 45 50 55 60 65 70 75

BHM9-2 0.305

±0.010

0.188

±0.064

0.116

±0.025

0.017

±0.008

0.024

±0.013 MIC - - - - - -

BLT7-3 0.059

±0.024

0.0155

±0.008 MIC - - - - - - - - -

BHT3-4 0.266

±0.045

0.144

±0.033

0.167

±0.016

0.184

±0.040

0.083

±0.008

0.033

±0.025

0.014

±0.010

0.005

±0.004 MIC - - -

BHT1-6 0.227

±0.069

0.081

±0.024

0.087

±0.016

0.056

±0.016

0.016

±0.007 MIC - - - - - -

CLR3-3 0.076

±0.032

0.013

±0.013 MIC - - - - - - - - -

CLR7-1 0.07

±0.027

0.017

±0.008 MIC - - - - - - - - -

CHR4-4 0.256

±0.047

0.156

±0.031

0.065

±0.047

0.054

±0.031

0.016

±0.006 MIC - - - - - -

CLM6-2 0.166

±0.030

0.043

±0.003

0.018

±0.006 MIC - - - - - - - -

CHM5-2 0.288

±0.077

0.127

±0.041

0.26

±0.041

0.043

±0.001

0.025

±0.006

0.038

±0.004

0.016

±0.006 MIC - - - -

CLT3-1 0.260

±0.040

0.138

±0.037

0.087

±0.016

0.01

±0.004

0.07

±0.027

0.017

±0.008 MIC - - - - -

CHT9-1 0.150

±0.039

0.109

±0.016

0.116

±0.038

0.036

±0.021

0.009

±0.006 MIC - - - - - -

CHT3-2 0.405

±0.085

0.487

±0.078

0.177

±0.049

0.156

±0.031

0.061

±0.054

0.022

±0.015

0.016

±0.006 MIC - - - -

DLR3-1 0.254

±0.034

0.160

±0.025

0.094

±0.025

0.027

±0.009

0.014

±0.003 MIC - - - - - -

DLR8-1 0.014

±0.010

0.007

±0.007 MIC - - - - - - - - -

DHR1-1 0.128

±0.024

0.056

±0.043

0.096

±0.119

0.012

±0.006

0.007

±0.002 MIC - - - - - -


Chapter 4 Results

164


20 25 30 35 40 45 50 55 60 65 70 75

DHR5-3 0.110

±0.033

0.081

±0.023

0.043

±0.018

0.018

±0.005

0.005

±0.006 MIC - - - - - -

DHR2-2 0.405

±0.035

0.356

±0.047

0.169

±0.072

0.238

±0.007

0.080

±0.057

0.013

±0.009 MIC - - - - -

DLM4-2 0.014

±0.004

0.016

±0.010 MIC - - - - - - - - -

DHM6-2 0.219

±0.002

0.293

±0.086

0.234

±0.127

0.176

±0.079

0.014

±0.006

0.008

±0.010 MIC - - - - -

DLT5-1 0.195

±0.024

0.244

±0.033

0.120

±0.016

0.149

±0.088

0.1

±0.031

0.082

±0.022

0.022

±0.012

0.006

±0.001 MIC - - -

DHT6-1 0.417

±0.102

0.441

±0.025

0.25

±0.040

0.156

±0.031

0.056

±0.031

0.01

±0.004 MIC - - - - -

ALR5-1 0.038

±0.010

0.014

±0.007 MIC - - - - - - - - -

AHR4-1 0.037

±0.025

0.023

±0.006 MIC - - - - - - - - -

ALM9-1 0.129

±0.081

0.171

±0.022

0.155

±0.062

0.139

±0.039

0.053

±0.017

0.016

±0.006

0.009

±0.008 MIC - - - -

AHM3-1 0.255

±0.030

0.094

±0.038

0.167

±0.063

0.12

±0.079

0.087

±0.016

0.071

±0.022

0.016

±0.006

0.009

±0.001 MIC - - -

AHM4-2 0.158

±0.041

0.072

±0.021

0.02

±0.001 MIC - - - - - - - -

ALT6-1 0.117

±0.022

0.181

±0.023

0.038

±0.006 MIC

- - - - - - - -

AHT5-5 0.405

±0.040

0.427

±0.165

0.188

±0.064

0.143

±0.030

0.087

±0.016

0.033

±0.014

0.012

±0.004

0.005

±0.003 MIC - - -

BLR8-3 0.305

±0.023

0.195

±0.024

0.084

±0.054

0.060

±0.053

0.026±

0.020 MIC - - - - - -

BLR6-5 0.25

±0.028

0.205

±0.007

0.101

±0.003

0.038

±0.037

0.016

±0.010 MIC - - - - - -


Chapter 4 Results

165


20 25 30 35 40 45 50 55 60 65 70 75

BHR2-1 0.244

±0.045

0.178

±0.016

0.066

±0.061

0.042

±0.004

0.044

±0.060 MIC - - - - - -

BLM8-1 0.304

±0.022

0.223

±0.016

0.172

±0.023

0.108

±0.015

0.044

±0.033 MIC - - - - - -

BHM6-1 0.039

±0.023

0.038

±0.008

0.015

±0.009

0.011

±0.001 MIC - - - - - - -

BLT5-2 0.043

±0.018

0.008

±0.006 MIC - - - - - - - - -

BHT3-1 0.145

±0.031

0.076

±0.031

0.076

±0.031

0.059

±0.023

0.010

±0.004

0.019

±0.006 MIC - - - - -

BHT7-2 0.091

±0.009

0.070

±0.008

0.008

±0.006 MIC - - - - - - - -

CLR8-1 0.065

±0.007

0.031

±0.012 MIC - - - - - - - - -

CHR3-2 0.069

±0.040

0.065

±0.031

0.030

±0.002

0.021

±0.017

0.003

±0.000 MIC - - - - - -

CHR3-1 0.362

±0.070

0.177

±0.049

0.184

±0.071

0.11

±0.016

0.017

±0.008 MIC - - - - - -

CLM4-10 0.067

±0.016

0.067

±0.018

0.015

±0.008 MIC - - - - - - - -

CLM6-3 0.048

±0.020

0.025

±0.018 MIC - - - - - - - - -

CHM1-2 0.199

±0.018

0.121

±0.159

0.084

±0.086

0.038

±0.009 MIC - - - - - - -

CLT8-1 0.244

±0.045

0.187

±0.031

0.116

±0.025

0.023

±0.012 MIC - - - - - - -

CHT3-2 0.31

±0.016

0.178

±0.047

0.528

±0.039

0.026

±0.008 MIC - - - - - - -

DLR1-3 0.216

±0.025

0.106

±0.024

0.091

±0.057

0.045

±0.031

0.012

±0.005 MIC - - - - - -


Chapter 4 Results

166


20 25 30 35 40 45 50 55 60 65 70 75

DLR4-3 0.033

±0.030

0.023

±0.006 MIC - - - - - - - - -

DHR1-5 0.5

±0.062

0.371

±0.086

0.188

±0.033

0.11

±0.017

0.065

±0.031

0.038

±0.022

0.020

±0.012 MIC - - - -

DHR6-4 0.210

±0.033

0.182

±0.022

0.101

±0.017

0.067

±0.049

0.007

±0.002

0.011

±0.003 MIC - - - - -

DLM3-1 0.243

±0.030

0.299

±0.077

0.405

±0.038

0.099

±0.033

0.070

±0.039

0.015

±0.008 MIC - - - - -

DHM5-1 0.101

±0.017

0.107

±0.007

0.093

±0.040

0.132

±0.018

0.110

±0.018

0.044

±0.017 MIC - - - - -

DLT3-1 0.192

±0.028

0.255

±0.061

0.093

±0.024

0.070

±0.039

0.016

±0.006 MIC - - - - - -

DHT6-2 0.110

±0.030

0.064

±0.019

0.039

±0.023

0.012

±0.005 MIC - - - - - - -

ALR3-4 0.006

±0.004 MIC - - - - - - - - - -

AHR3-2 0.056

±0.043

0.096

±0.119

0.012

±0.006

0.007

±0.002 MIC - - - - - - -

ALM3-1 0.237

±0.071

0.210

±0.033

0.113

±0.025

0.016

±0.006

0.005

±0.004 MIC - - - - - -

ALM9-1 0.227

±0.022

0.148

±0.039

0.067

±0.016

0.031

±0.012

0.009

±0.003 MIC - - - - - -

AHM4-1 0.211

±0.031

0.088

±0.014

0.049

±0.022

0.018

±0.004

0.013

±0.002

0.006

±0.004 MIC - - - - -

ALT3-1 0.01

±0.003 MIC - - - - - - - - - -

AHT8-1 0.014

±0.006 MIC - - - - - - - - - -

BLR6-1 0.177

±0.078

0.115

±0.024

0.056

±0.031

0.013

±0.002

0.006

±0.001 MIC - - - - - -


Chapter 4 Results

167


20 25 30 35 40 45 50 55 60 65 70 75

BLR5-1 0.127

±0.007

0.070

±0.023

0.022

±0.014

0.011

±0.006

0.013

±0.011 MIC - - - - - -

BLR8-2 0.109

±0.047

0.088

±0.080

0.033

±0.030

0.051

±0.005

0.008

±0.002 MIC - - - - - -

BHR1-1 0.183

±0.085

0.109

±0.016

0.03

±0.014 MIC - - - - - - - -

BLM9-1 0.005

±0.003 MIC - - - - - - - - - -

BHM6-2 0.025

±0.021 MIC - - - - - - - - - -

BLT6-2 0.015

±0.004 MIC - - - - - - - - - -

BHT6-1 0.016

±0.006 MIC - - - - - - - - - -

CLR4-2 0.009

±0.001 MIC - - - - - - - - - -

CHR3-2 0.01

±0.003 MIC - - - - - - - - - -

CHR9-1 0.016

±0.008 MIC - - - - - - - - - -

CLM1-1 0.427

±0.165

0.188

±0.064

0.143

±0.030

0.022

±0.001

0.07

±0.027

0.006

±0.003 MIC - - - - -

CHM1-1 0.006

±0.003 MIC - - - - - - - - -- -

CLT3-3 0.143

±0.030

0.060

±0.053

0.106

±0.024

0.041

±0.013

0.019

±0.003

0.005

±0.004 MIC - - - - -

CLT3-2 0.184

±0.056

0.065

±0.047

0.055

±0.014

0.014

±0.005

0.015

±0.008 MIC - - - - - -

CHT2-1 0.006

±0.001 MIC - - - - - - - - - -


Chapter 4 Results

168


20 25 30 35 40 45 50 55 60 65 70 75

DLR10-1 0.181

±0.023

0.134

±0.016

0.072

±0.070

0.110

±0.018

0.07

±0.017

0.012

±0.005 MIC - - - - -

DHR8-2 0.087

±0.078

0.087

±0.047

0.016

±0.006

0.025

±0.010

0.012

±0.005 MIC - - - - - -

DLM2-2 0.087

±0.078

0.066

±0.061

0.025

±0.009

0.033

±0.025

0.008

±0.007 MIC - - - - - -

DHM6-1 0.087

±0.047

0.037

±0.023

0.026

±0.024

0.009

±0.005 MIC - - - - - - -

DLT8-1 0.188

±0.014

0.155

±0.081

0.092

±0.059

0.070

±0.039

0.016

±0.010

0.011

±0.008 MIC - - - - -

DHT9-1 0.175

±0.083

0.182

±0.069

0.112

±0.015

0.035

±0.027

0.018

±0.004

0.007

±0.002 MIC - - - - -

ALR5-3 0.069

±0.049

0.015

±0.008 MIC - - - - - -- - - -

AHR7-5 0.301

±0.086

0.272

±0.056

0.299

±0.093

0.187

±0.016

0.099

±0.046

0.112

±0.014

0.064

±0.017

0.033

±0.017 MIC - - -

AHR6-1 0.008

±0.004 MIC - - - - - - - - - -

ALM6-2 0.026

±0.008

0.013

±0.011 MIC - - - - - - - - -

AHM9-1 0.589

±0.094

0.405

±0.038

0.289

±0.076

0.200

±0.063

0.137

±0.008

0.115

±0.008

0.088

±0.014

0.024

±0.017 MIC - - -

ALT8-2 0.016

±0.006 MIC - - - - - - - - - -

AHT4-4 0.301

±0.059

0.454

±0.103

0.159

±0.036

0.166

±0.063

0.081

±0.023

0.008

±0.006 MIC - - - - -

AHT3-2 0.354

±0.062

0.266

±0.077

0.077

±0.049

0.129

±0.081

0.134

±0.031

0.139

±0.039

0.237

±0.044

0.016

±0.006 MIC - - -

BLR8-1 0.521

±0.064

0.172

±0.071

0.283

±0.071

0.407

±0.037

0.211

±0.031

0.151

±0.042

0.077

±0.017

0.029

±0.023

0.006

±0.004 MIC - -


Chapter 4 Results

169


20 25 30 35 40 45 50 55 60 65 70 75

BHR5-2 0.288

±0.079

0.344

±0.097

0.552

±0.014

0.384

±0.086

0.446

±0.018

0.155

±0.048

0.121

±0.077

0.081

±0.024

0.087

±0.016

0.033

±0.017

0.009

±0.004 MIC

BLM8-2 0.267

±0.078

0.205

±0.118

0.227

±0.149

0.193

±0.056

0.240

±0.073

0.150

±0.054

0.078

±0.016

0.032

±0.016 MIC - - -

BHM5-1 0.285

±0.136

0.289

±0.079

0.074

±0.042

0.062

±0.023

0.01

±0.003 MIC - - - - - -

BLT2-1 0.006

±0.004 MIC - - - - - - - - - -

BHT6-1 0.444

±0.172

0.566

±0.158

0.5

±0.095

0.277

±0.062

0.278

±0.221

0.226

±0.148

0.071

±0.006

0.052

±0.041

0.014

±0.009 MIC - -

CLR2-1 0.006

±0.004 MIC - - - - - - - - - -

CHR3-1 0.508

±0.081

0.333

±0.141

0.344

±0.157

0.267

±0.078

0.361

±0.103

0.077

±0.017

0.029

±0.023 MIC - - - -

CLM4-1 0.552

±0.014

0.138

±0.006

0.144

±0.064

0.168

±0.062

0.080

±0.025

0.026

±0.008

0.01

±0.003 MIC - - - -

CHM7-1 0.222

±0.015

0.198

±0.018

0.11

±0.017

0.034

±0.043

0.013

±0.011 MIC - - - - - -

CLT2-2 0.017

±0.006 MIC - - - - - - - - - -

CHT2-2 0.601

±0.110

0.544

±0.158

0.149

±0.039

0.277

±0.062

0.151

±0.042

0.067

±0.031

0.051

±0.019

0.021

±0.011 MIC - - -

CHT6-1 0.333

±0.172

0.162

±0.071

0.077

±0.049

0.208

±0.030

0.205

±0.069

0.065

±0.047

0.012

±0.006 MIC - - - -

DLR1-5 0.332

±0.141

0.156

±0.031

0.188

±0.014

0.127

±0.022

0.055

±0.030

0.016

±0.006 MIC

- - - - -

DHR4-2 0.299

±0.093

0.360

±0.022

0.427

±0.085

0.269

±0.084

0.322

±0.156

0.438

±0.056

0.287

±0.078

0.138

±0.037

0.055

±0.014

0.014

±0.009 MIC -

DHR5-1 0.421

±0.170

0.283

±0.040

0.128

±0.093

0.187

±0.141

0.07

±0.075

0.082

±0.078

0.033

±0.006 MIC - - - -


Chapter 4 Results

170


20 25 30 35 40 45 50 55 60 65 70 75

DLM1-2 0.777

±0.070

0.684

±0.040

0.611

±0.093

0.467

±0.141

0.509

±0.075

0.487

±0.078

0.138

±0.006

0.061

±0.054

0.022

±0.015 MIC - -

DLM6-2 0.057

±0.021

0.025

±0.008 MIC - - - - - - - - -

DHM2-1 0.684

±0.040

0.555

±0.140

0.489

±0.110

0.521

±0.108

0.272

±0.069

0.116

±0.025

0.054

±0.031

0.022

±0.014 MIC - - -

DLT9-2 0.360

±0.022

0.427

±0.085

0.499

±0.061

0.537

±0.148

0.362

±0.070

0.177

±0.049

0.184

±0.049

0.11

±0.071

0.017

±0.016 MIC - -

DHT3-1 0.145

±0.047

0.177

±0.066

0.060

±0.022

0.023

±0.015

0.016

±0.006 MIC - - - - - -

DHT9-2 0.5115

±0.078

0.245

±0.123

0.199

±0.109

0.095

±0.040

0.194

±0.025

0.07

±0.008

0.077

±0.030

0.011

±0.001 MIC - - -

Values = means±SD

- = no growth

Chapter 4 Results

171

Table 4.24 Determination of minimum inhibitory concentrations (MIC) of Cr6+



Isolate Code Concentration of Cr µg/ml of nutrient broth

1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

ALR7-5 0.17

±0.071

0.125

±0.064 MIC - - - - - - - - -

ALR2-1 0.058

±0.018

0.026

±0.007 MIC - - - - - - - - -

AHR8-5

0.271

±0.070

0.301

±0.059

0.087

±0.016

0.105

±0.054

0.205

±0.005

0.103

±0.121

0.165

±0.047

0.541

±0.121

0.027

±0.022

0.004

±0.001 MIC -

AHR4-2 0.205

±0.041

0.200

±0.016

0.220

±0.019

0.214

±0.023

0.136

±0.025

0.077

±0.049

0.132

±0.015

0.081

±0.023

0.035

±0.021

0.014

±0.010 MIC -

AHR4-1 0.248

±0.071

0.281

±0.067

0.304

±0.055

0.15

±0.040

0.167

±0.031

0.070

±0.039

0.099

±0.018

0.033

±0.014

0.041

±0.018

0.011

±0.003 MIC -

ALM1-1 0.118

±0.021

0.106

±0.023

0.125

±0.064 MIC - - - - - - - -

AHM7-1 0.228

±0.023

0.171

±0.037

0.06

±0.023

0.032

±0.016

0.032

±0.005

0.031

±0.014

0.012

±0.005 MIC - - - -

ALT4-5 0.017

±0.005

0.015

±0.004 MIC - - - - - - - - -

AHT7-6 0.345

±0.019

0.287

±0.077

0.222

±0.141

0.170

±0.039

0.084

±0.011

0.076

±0.032

0.055

±0.017

0.016

±0.006

0.019

±0.015 MIC - -

BLR6-1 0.266

±0.046

0.281

±0.067

0.370

±0.039

0.405

±0.038

0.335

±0.149

0.229

±0.146

0.082

±0.022

0.058

±0.018

0.026

±0.007 MIC - -

BHR7-2 0.380

±0.045

0.261

±0.039

0.282

±0.057

0.193

±0.040

0.094

±0.038

0.087

±0.016

0.049

±0.022

0.037

±0.023

0.011

±0.003

0.009

±0.002 MIC -

BLM4-1 0.389

±0.063

0.409

±0.059

0.235

±0.053

0.081

±0.054

0.127

±0.022

0.11

±0.017

0.043

±0.031

0.035

±0.021

0.009

±0.004 MIC - -

BLM5-1 0.327

±0.040

0.251

±0.067

0.245

±0.047

0.236

±0.028

0.111

±0.063

0.052

±0.013

0.021

±0.011

0.007

±0.006 MIC - - -


Chapter 4 Results

172


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

BHM1-1 0.166

±0.030

0.089

±0.032

0.137

±0.055

0.195

±0.101

0.128

±0.136

0.082

±0.024

0.038

±0.009

0.014

±0.010

0.010

±0.002 MIC - -

BHM9-2 0.009

±0.010 MIC - - - - - - - - - -

BLT7-3 0.028

±0.036

0.011

±0.003 MIC - - - - - - - - -

BHT3-4 0.072

±0.037

0.017

±0.008 MIC - - - - - - - - -

BHT1-6 0.149

±0.053

0.082

±0.022

0.221

±0.064

0.174

±0.071

0.065

±0.047

0.038

±0.008

0.026

±0.008

0.010

±0.002 MIC - - -

CLR3-3 0.085

±0.007

0.012

±0.012 MIC - - - - - - - - -

CLR7-1 0.063

±0.013

0.014

±0.007 MIC - - - - - - - - -

CHR4-4 0.305

±0.023

0.348

±0.146

0.105

±0.054

0.591

±0.150

0.067

±0.049

0.496

±0.184

0.025

±0.005

0.005

±0.001 MIC - - -

CLM6-2 0.078

±0.016

0.041

±0.013

0.013

±0.007 MIC - - - - - - - -

CHM5-2 0.249

±0.053

0.064

±0.008

0.122

±0.094

0.121

±0.064

0.043

±0.016

0.049

±0.037

0.011

±0.004

0.016

±0.006 MIC - - -

CLT3-1 0.177

±0.076

0.133

±0.063

0.033

±0.025

0.109

±0.032

0.078

±0.034

0.110

±0.018

0.012

±0.002

0.005

±0.003 MIC - - -

CHT9-1 0.166

±0.017

0.033

±0.015

0.093

±0.006

0.145

±0.047

0.103

±0.036

0.069

±0.018

0.110

±0.018

0.026

±0.008

0.010

±0.002 MIC - -

CHT3-2 0.315

±0.037

0.216

±0.025

0.123

±0.008

0.277

±0.061

0.32

±0.066

0.205

±0.010

0.321

±0.046

0.182

±0.073

0.088

±0.011

0.011

±0.003 MIC -

DLR3-1 0.150

±0.039

0.033

±0.030

0.006

±0.004 MIC - - - - - - - -

DLR8-1 0.07

±0.027

0.017

±0.006 MIC - - - - - - - - -


Chapter 4 Results

173


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

DHR1-1 0.233

±0.078

0.196

±0.025

0.185

±0.064

0.057

±0.042

0.014

±0.008 MIC - - - - - -

DHR5-3 0.254

±0.033

0.175

±0.019

0.287

±0.052

0.299

±0.093

0.126

±0.048

0.029

±0.007

0.013

±0.008 MIC - - - -

DHR2-2 0.199

±0.033

0.195

±0.101

0.205

±0.026

0.044

±0.030

0.028

±0.018

0.037

±0.008

0.027

±0.008

0.007

±0.002 MIC - - -

DLM4-2 0.149

±0.023

0.009

±0.004 MIC - - - - - - - - -

DHM6-2 0.278

±0.016

0.155

±0.061

0.528

±0.139

0.020

±0.004 MIC - - - - - - -

DLT5-1 0.188

±0.033

0.16

±0.054

0.070

±0.039

0.104

±0.024

0.045

±0.031

0.110

±0.018

0.041

±0.018

0.01

±0.003 MIC

- - -

DHT6-1 0.515

±0.089

0.382

±0.087

0.288

±0.078

0.422

±0.047

0.371

±0.086

0.188

±0.033

0.072

±0.070

0.025

±0.008

0.017

±0.006 MIC - -

ALR5-1 0.021

±0.007 MIC - - - - - - - - - -

AHR4-1 0.012

±0.002 MIC - - - - - - - - - -

ALM9-1 0.273

±0.040

0.178

±0.049

0.106

±0.024

0.041

±0.013

0.013

±0.007 MIC - - - - - -

AHM3-1 0.261

±0.039

0.143

±0.030

0.110

±0.018

0.027

±0.006

0.016

±0.006

0.010

±0.002 MIC - - - - -

AHM4-2 MIC - - - - - - - - - - -

ALT6-1 0.008

±0.003 MIC - - - - - - - - - -

AHT5-5 0.188

±0.033

0.15

±0.040

0.167

±0.031

0.070

±0.039

0.099

±0.018

0.033

±0.014

0.041

±0.018

0.011

±0.003 MIC - - -

BLR8-3 0.110

±0.018

0.07

±0.002

0.025

±0.010

0.009

±0.001 MIC - - - - - - -


Chapter 4 Results

174


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

BLR6-5 0.012

±0.001 MIC - - - - - - - - - -

BHR2-1 0.010

±0.002 MIC - - - - - - - - - -

BLM8-1 0.044

±0.017

0.034

±0.016

0.048

±0.005 MIC - - - - - - - -

BHM6-1 0.041

±0.018

0.007

±0.006 MIC - - - - - - - - -

BLT5-2 0.005

±0.001 MIC - - - - - - - - - -

BHT3-1 0.221

±0.016

0.488

±0.080

0.418

±0.024

0.279

±0.064

0.388

±0.062

0.154

±0.016

0.166

±0.062

0.093

±0.024

0.070

±0.039

0.014

±0.009 MIC -

BHT7-2 0.034

±0.031

0.007

±0.004 MIC - - - - - - - - -

CLR8-1 0.002

±000 MIC - - - - - - - - - -

CHR3-2 0.254

±0.062

0.207

±0.037

0.160

±0.101

0.104

±0.055

0.033

±0.006

0.01

±0.004 MIC - - - - -

CHR3-1 0.309

±0.016

0.315

±0.118

0.215

±0.102

0.118

±0.113

0.054

±0.047

0.014

±0.008 MIC - - - - -

CLM4-1 0.021

±0.002 MIC - - - - - - - - - -

CLM6-3 0.012

±0.005 MIC - - - - - - - - - -

CHM1-2 0.06

±0.024

0.071

±0.022

0.014

±0.009

0.007

±0.001

0.006

±0.005 MIC - - - - - -

CLT8-1 0.11

±0.047

0.105

±0.025

0.088

±0.014

0.026

±0.011

0.012

±0.011 MIC - - - - - -

CHT3-2 0.423

±0.030

0.272

±0.069

0.156

±0.031

0.065

±0.047

0.054

±0.031

0.009

±0.004 MIC - - - - -


Chapter 4 Results

175


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

DLR1-3 0.289

±0.078

0.178

±0.078

0.094

±0.038

0.137

±0.055

0.221

±0.061

0.071

±0.037

0.02

±0.001

0.009

±0.004 MIC - - -

DLR4-3 0.008

±0.001 MIC - - - - - - - - - -

DHR1-5 0.216

±0.025

0.160

±0.025

0.139

±0.039

0.087

±0.016

0.039

±0.008

0.037

±0.023

0.01

±0.003 MIC - - - -

DHR6-4 0.052

±0.041

0.017

±0.006

0.059

±0.023

0.012

±0.004

0.006

±0.006 MIC - - - - - -

DLM3-1 0.167

±0.016

0.116

±0.025

0.065

±0.031

0.055

±0.045

0.041

±0.018

0.022

±0.014 MIC - - - - -

DHM5-1 0.372

±0.085

0.216

±0.025

0.193

±0.040

0.080

±0.025

0.073

±0.019

0.006

±0.004 MIC - - - - -

DLT3-1 0.082

±0.009

0.039

±0.010

0.020

±0.004

0.005

±0.004 MIC - - - - - - -

DHT6-2 0.041

±0.018

0.008

±0.006 MIC

- - - - - - - - -

ALR3-4 0.095

±0.014

0.022

±0.005 MIC - - - - - - - - -

AHR3-2 0.005

±0.001

0.032

±0.003

0.01

±0.001

0.002

±0.003 MIC - - - - - - -

ALM3-1 0.082

±0.004

0.048

±0.007

0.026

±0.004

0.009

±0.002 MIC - - - - - - -

ALM9-1 0.173

±0.037

0.506

±0.121

0.541

±0.022

0.027

±0.004

0.004

±0.001 MIC - - - - - -

AHM4-1 0.295

±0.018

0.410

±0.015

0.333

±0.045

0.266

±0.022

0.082

±0.018

0.110

±0.008

0.07

±0.017

0.033

±0.006

0.008

±0.001 MIC - -

ALT3-1 0.421

±0.101

0.352

±0.121

0.171

±0.078

0.007

±0.002 MIC - - - - - - -

AHT8-1 0.323 ±

.098

0.825

±0.092

0.231

±0.078

0.016

±0.005 MIC - - - - - - -


Chapter 4 Results

176


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

BLR6-1 0.132

±0.023

0.081

±0.021

0.035

±0.010

0.014

±0.002 MIC - - - - - - -

BLR5-1 0.16

±0.018

0.110

±0.016

0.034

±0.008

0.008

±0.001 MIC - - - - - - -

BLR8-2 0.132

±0.016

0.165

±0.006

0.01

±0.004

0.018

±0.003 MIC - - - - - - -

BHR1-1 0.105

±0.004

0.528

±0.127

0.020

±0.004 MIC - - - - - - - -

BLM9-1 0.012

±0.002

0.85

±0.102

0.351

±0.027

0.016

±0.005 MIC - - - - - - -

BHM6-2 0.245

±0.010

0.341

±0.12

0.43

±0.16

0.011

±0.002 MIC - - - - - - -

BLT6-2 0.212

±0.013

0.138

±0.021

0.170

±0.01

0.045

±0.008

0.012

±0.002 MIC - - - - - -

BHT6-1 0.178

±0.057

0.195

±0.039

0.134

±0.044

0.037

±0.004

0.01

±0.001 MIC - - - - - -

CLR4-2 0.212

±0.024

0.090

±0.016

0.116

±0.027

0.074

±0.003

0.006

±0.001 MIC - - - - - -

CHR3-2 0.189

±0.018

0.110

±0.025

0.037

±0.011

0.011

±0.004 MIC - - - - - - -

CHR9-1 0.321

±0.064

0.240

±0.098

0.176

±0.056

0.104

±0.003

0.025

±0.008 MIC - - - - - -

CLM4-1 0.040

±0.018

0.022

±0.008

0.017

±0.003

0.012

±0.008

0.016

±0.008

0.007

±0.001 MIC - - - - -

CHM1-1 0.123

±0.029

0.077

±0.019

0.063

±0.014

0.007

±0.001 MIC - - - - - - -

CLT3-3 0.060

±0.02

0.013

±0.004

0.007

±0.001 MIC - - - - - - - -

CLT3-2 0.077

±0.006

0.067

±0.005

0.029

±0.007

0.005

0.004 MIC - - - - - - -


Chapter 4 Results

177


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

CHT2-1 0.212

±0.102

0.115

±0.043

0.037

±0.012

0.016

±0.008 MIC - - - - - - -

DLR10-1 0.208

±0.121

0.172

±0.078

0.110

±0.018

0.200

±0.021

0.249

±0.121

0.195

±0.087

0.182

±0.058

0.106

±0.069

0.033

±0.009

0.012

±0.002 MIC -

DHR8-2 0.051

±0.012

0.015

±0.008

0.017

±0.008 MIC - - - - - - - -

DLM2-2 0.068

±0.014

0.062

±0.013

0.019

±0.005 MIC - - - - - - - -

DHM6-1 0.232

±0.11

0.065

±0.032

0.043

±0.021

0.010

±0.006 MIC - - - - - - -

DLT8-1 0.213

±0.056

0.144

±0.08

0.110

±0.043

0.055

±0.032

0.014

±0.009 MIC - - - - - -

DHT9-1 0.110

±0.040

0.033

±0.015

0.014

±0.002

0.009

±0.002 MIC - - - - - - -

ALR5-3 0.017

±0.009 MIC - - - - - - - - - -

AHR7-5 0.110

±0.043

0.067

±0.032

0.06

±0.001

0.044

±0.023

0.022

±0.014 MIC - - - - - -

AHR6-1 0.016

±0.006 MIC - - - - - - - - - -

ALM6-2 0.043

±0.012

0.015

±003 MIC - - - - - - - - -

AHM9-1 0.013

±0.007

0.005

±0.001 MIC - - - - - - - - -

ALT8-2 0.01

±0.001 MIC - - - - - - - - - -

AHT4-4 0.011

±0.004 MIC - - - - - - - - - -

AHT3-2 0.322

±0.156

0.143

±0.030

0.217

±0.008

0.177

±0.014

0.110

±0.018

0.07

±0.027

0.011

±0.006 MIC - - - -


Chapter 4 Results

178


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

BLR8-1 0.011

±0.004 MIC - - - - - - - - - -

BHR5-2 0.017

±0.002 MIC - - - - - - - - - -

BLM8-2 0.11

±0.017

0.07

±0.027

0.036

±0.028

0.055

±0.017

0.015

±0.008

0.008

±0.007 MIC - - - - -

BHM5-1 0.037

±0.023

0.015

±0.005 MIC - - - - - - - - -

BLT2-1 0.048

±0.004

0.022

±0.011 MIC - - - - - - - - -

BHT6-1 0.181

±0.082

0.172

±0.023

0.159

±0.087

0.106

±0.024

0.033

±0.025

0.093

±0.006

0.036

±0.021 MIC - - - -

CLR2-1 0.025

±0.009

0.02

±0.004 MIC - - - - - - - - -

CHR3-1 0.162

±0.071

0.074

±0.033

0.036

±0.028

0.078

±0.016

0.041

±0.013 MIC - - - - - -

CLM4-1 0.128

±0.008

0.128

±0.086

0.07

±0.027

0.059

±0.011

0.012

±0.005 MIC - - - - - -

CHM7-1

0.039

±0.010

0.051

±0.040 MIC - - - - - - - - -

CLT2-2 0.025

±0.010

0.016

±0.006 MIC - - - - - - - - -

CHT2-2 0.082

±0.022

0.071

±0.006

0.178

±0.048

0.078

±0.065

0.078

±0.034

0.009

±0.004 MIC - - - - -

CHT6-1 0.014

±0.003 MIC - - - - - - - - - -

DLR1-5 0.298

±0.089

0.199

±0.076

0.172

±0.015

0.110

±0.034

0.189

±0.21

0.052

±0.013

0.029

±0.11 MIC - - - -

DHR4-2 0.078

±0.189

0.017

±0.018 MIC - - - - - - - - -


Chapter 4 Results

179


1150 1200 1250 1300 1350 1400 1450 1500 1550 1600 1650 1700

DHR5-1 0.006

±0.001 MIC - - - - - - - - - -

DLM1-2 0.037

±0.023

0.010

±0.002 MIC - - - - - - - - -

DLM6-2 0.026

±0.004

0.016

±0.003 MIC - - - - - - - - -

DHM2-1 0.013

±0.004 MIC - - - - - - - - - -

DLT9-2 0.014

±0.007 MIC - - - - - - - - - -

DHT3-1 0.089

±0.047

0.072

±0.023

0.027

±0.009

0.009

±0.001 MIC - - - - - - -

DHT9-2 0.016

±0.003

0.008

±0.001 MIC - - - - - - - - - Values = means±SD

- = no growth

Chapter 4 Results

180

700

750

800

850

900

950

1000

AH

R8

-5

AH

R4

-1

AH

R7

-5

AL

M9

-1

AH

M3

-1

AH

M4

-1

AH

T5

-5

AH

T3

-2

BL

R6

-1

BL

R6

-10

BH

R7

-2

BL

M4

-1

BL

M5

-1

BH

M1

-1

BH

T3

-1

BH

T6

-1

CH

R3

-1

CH

R3

-1

CL

M4

-1

CL

M4

-10

CH

M5

-2

CH

M7

-1

CL

T3

-1

CH

T9

-1

CH

T3

-2

CH

T2

-2

DL

R3

-1

DL

R1

-5

DL

R1

-3

DL

R1

0-1

DH

R1

-5

DH

R6

-4

DH

R1

-1

DH

R5

-3

DH

R2

-2

DH

R4

-2

DH

R5

-1

DH

R8

-2

DL

M3

-1

DH

M5

-1

DL

T5

-1

DL

T8

-1

DH

T6

-1

DH

T3

-1

DH

T9

-1


Cu

(u

g/m

l)

Fig. 4.39 MIC of Cu for the selected bacteria isolated from gut contents of the fish species sampled from four sites (Siphon

(upstream) =A; Shahdera =B; Sunder =C; and Head balloki =D) during both low (red bars) and high (blue bars) flow seasons of the

river Ravi.

Chapter 4 Results

181

1050

1100

1150

1200

1250

1300

1350

1400

AH

R8

-5

AH

R4

-1

AH

R7

-5

AL

M9

-1

AH

M3

-1

AH

M4

-1

AH

T5

-5

AH

T3

-2

BL

R6

-1

BL

R6

-10

BH

R7

-2

BL

M4

-1

BL

M5

-1

BH

M1

-1

BH

T3

-1

BH

T6

-1

CH

R3

-1

CH

R3

-1

CL

M4

-1

CL

M4

-10

CH

M5

-2

CH

M7

-1

CL

T3

-1

CH

T9

-1

CH

T3

-2

CH

T2

-2

DL

R3

-1

DL

R1

-5

DL

R1

-3

DL

R1

0-1

DH

R1

-5

DH

R6

-4

DH

R1

-1

DH

R5

-3

DH

R2

-2

DH

R4

-2

DH

R5

-1

DH

R8

-2

DL

M3

-1

DH

M5

-1

DL

T5

-1

DL

T8

-1

DH

T6

-1

DH

T3

-1

DH

T9

-1


Pb

(u

g/m

l)

Fig. 4.40 MIC of Pb for the selected bacteria isolated from gut contents of sampled fish species sampled from four sites (Siphon

(upstream =A); Shahdera =B; Sunder =C; and Head balloki =D) during both low and high flow seasons of the river Ravi.

Chapter 4 Results

182

40

45

50

55

60

65

70

AH

R8

-5

AH

R4

-1

AH

R7

-5

AL

M9

-1

AH

M3

-1

AH

M4

-1

AH

T5

-5

AH

T3

-2

BL

R6

-1

BL

R6

-10

BH

R7

-2

BL

M4

-1

BL

M5

-1

BH

M1

-1

BH

T3

-1

BH

T6

-1

CH

R3

-1

CH

R3

-1

CL

M4

-1

CL

M4

-10

CH

M5

-2

CH

M7

-1

CL

T3

-1

CH

T9

-1

CH

T3

-2

CH

T2

-2

DL

R3

-1

DL

R1

-5

DL

R1

-3

DL

R1

0-1

DH

R1

-5

DH

R6

-4

DH

R1

-1

DH

R5

-3

DH

R2

-2

DH

R4

-2

DH

R5

-1

DH

R8

-2

DL

M3

-1

DH

M5

-1

DL

T5

-1

DL

T8

-1

DH

T6

-1

DH

T3

-1

DH

T9

-1


Hg (

ug/m

l)

Fig. 4.41 MIC of Hg for the selected bacteria isolated from gut contents of the fish species sampled from four sites (Siphon

(upstream) =A); Shahdera =B; Sunder =C; and Head balloki =D) during both low and high flow seasons of the river Ravi.

Chapter 4 Results

183

1050

1150

1250

1350

1450

1550

1650

AH

R8

-5

AH

R4

-1

AH

R7

-5

AL

M9

-1

AH

M3

-1

AH

M4

-1

AH

T5

-5

AH

T3

-2

BL

R6

-1

BL

R6

-10

BH

R7

-2

BL

M4

-1

BL

M5

-1

BH

M1

-1

BH

T3

-1

BH

T6

-1

CH

R3

-1

CH

R3

-1

CL

M4

-1

CL

M4

-10

CH

M5

-2

CH

M7

-1

CL

T3

-1

CH

T9

-1

CH

T3

-2

CH

T2

-2

DL

R3

-1

DL

R1

-5

DL

R1

-3

DL

R1

0-1

DH

R1

-5

DH

R6

-4

DH

R1

-1

DH

R5

-3

DH

R2

-2

DH

R4

-2

DH

R5

-1

DH

R8

-2

DL

M3

-1

DH

M5

-1

DL

T5

-1

DL

T8

-1

DH

T6

-1

DH

T3

-1

DH

T9

-1

A B C D

Sampling Sites

Cr

(ug/m

l)

Fig. 4.42 MIC of Cr for the selected bacteria isolated from gut contents of the fish species sampled from four sites (Siphon

(upstream) =A); Shahdera =B; Sunder =C; and Head balloki =D) during both low and high flow seasons of the river Ravi.

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184

4.5.2 Biochemical characterization of the select bacterial isolates:

Out of the forty five isolates, twenty two bacterial isolates were Gram positive and twenty

three were Gram negative. All the strains were rods shaped cell morphology. Thirty two

isolate were endospore formers. While thirty seven isolates were motile and eight non motile

(Table 4.25). All the isolates showed positive catalase test, except three isolates. Thirty

isolate showed positive oxidase test. Thirty isolates showed positive amylase test. While

thirty two isolates showed both cellulose and protease activities. 33 %., 29 % and 29 %

isolates did not expressed amylase, cellulose and protease activities respectively. Whereas

22.isolates expressed the three digestive exoenzymes concomittantly (table 4.25).

Chapter 4 Results

185

Table 4.25 Biochemical characterization of the select bacterial isolates. All bacteria maintained rod shaped cell

morphology

Isolate Code Biochemical characteristics

Gram’s staining Endospore Motility Oxidase Catalase Amylase Cellulase Protease

AHR8-5 - + + + + + + +

AHR4-1 + + + - + + + +

BHR7-2 - - + + + + + +

BLR6-1 - - + + + + + +

BHM1-1 + + + - + - - +

BLM4-1 - + + + + - + -

BLM5-1 + + + - + + + +

CHM5-2 - + + + + + + +

CHT9-1 + + + - + + + +

CHT3-2 - - - - + - - -

CLT3-1 + + + - + + + +

DHR1-1 - - - - + - - -

DHR5-3 - + + + + + + -

DHR2-2 + + + - + + + +

DHT6-1 + + + - + + + +

DLT5-1 - - + + + - - -

DLR3-1 + + + - + + + +

AHM3-1 + + + - + - + +

ALM9-1 + + + + - + + +

AHT5-5 + + + - + + + +

Chapter 4 Results

186

Isolate Code Biochemical characteristics

Gram’s staining Endospore Motility Oxidase Catalase Amylase Cellulase Protease

BHT3-1 - + + + + + + +

CHR3-1 + + + - + + + +

DHR1-5 - + + + + + + +

DHR6-4 + + + - + - + +

DHM5-1 + + + - + + + +

DLM3-1 + + + - + + + +

DLR1-5 + + + - + + - +

DLR1-3 + + + - + + + -

AHR7-5 - + + + + + + -

AHT3-2 + + + - + + + +

BHT6-1 - - + - + - + +

CHR3-1 - - + - + - - -

CHM7-1 + + + - + + + -

CLM4-1 + + + - + + + +

CHT2-2 - - - + + - + +

DHR4-2 - - - - + - - -

DHR5-1 - - - + - - - -

DHT3-1 - - - - + - + +

DLR10-1 - + + + + + + +

AHM4-1 - - - - + + - +

BLR6-10 - - + + - - - +

CLM4-10 - + + - + + - -

DHR8-2 + + + - + + + +

DHT9-1 - + - - + - - +

DLT8-1 + + + - + + - -

Chapter 4 Results

187

4.5.3 Identification of the bacterial isolates by PCR amplicaion and sequencing of the

16S rDNA:

DNA samples were amplified after optimizing the PCR conditions. Using the universal

forward and reverse primers, PCR products of 1500 bp were obtained, purified and

sequenced.

AHR8-5

TGGTACAACCGCGGTATAATACTTTTTTCTATATATCTTCACTAATTGGGAGCCA

CAACAACAAAATAAAGTCGGCCCCTCCCCCCCCCTTCGCTCTTGGGGGGGGAGG

AGCTATAATATTTTTTTTTTGGGGGGGGATTAAATTTAAAGGTTGCGCGGCTACC

ATGCAAGTCGAGCGGCAGCGGGAAAGTAGCTTGCTACTTTTGCCGGCGAGCGGC

GGACGGGTGAGTAATGCCTGGGGATCTGCCCAGTCGAGGGGGATAACTACTGGA

AACGGTAGCTAATACCGCATACGCCCTACGGGGGAAAGCAGGGGACCTTCGGGC

CTTGCGCGATTGGATGAACCCAGGTGGGATTAGCTAGTTGGTGAGGTAACGGCT

CACCAAGGCGACGATCCCTAGCTGGTCTGAGAGGATGATCAGCCACACTGGAAC

TGAGACACGGTCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATG

GGGGAAACCCTGATGCAGCCATGCCGCGTGTGTGAAGAAGGCCTTCGGGTTGTA

AAGCACTTTTCAGCGAGGAGGAAAGGTTGGTAGCTAATAACTGCCAGCTGTGAC

GTTACTCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGGTAATAC

GGAGGGTGCAAGCGTTAATCGGAAATTACTGGGGCCGTAAAGCGCACGCAAGGC

GGTTTGGAATAAGTTAGATGTGAAAGCCCCCGGGGCTCAACCTGGAATTTGCCA

TTTAAAACTTGTCCAGCCTAGGAGTTCTTGTTAGAAGGGGGGTTAGGAACTTCCA

GGTGTAGCGGCTGAATTGCCGTAGAGTATCTTGGCAGGTAATACCGGTGGCGAA

GGTGGCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGGAGCAA

ACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGTCGATTTGGAGGCT

GTGTCCTTGAGACGTGGCTTCCGGAGCTAACGCGTTAAATCGACCGCCTGGGGA

GTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGCCCGCACAAGCGGTG

GAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTGGCCTTGACATGT

CTGGAATCCTGTAGAGATACGGGAGTGCCTTCGGGAATCAGAACACAGGTGCTG

CATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCG

CAACCCCTGTCCTTTGTTGCCAGCACGTAATGGTGGGAACTCAAGGGAGACTGC

CGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACG

GCCAGGGCTACACACGTGCTACAATGGCGCGTACAGAGGGCTGCAAGCTAGCGA

TAGTGAGCGAATCCCAAAAAGCGCGTCGTAGTCCGGATTGGAGTCTGCAACTCG

ACTCCGTGAAGTCGGAATCGCTAGTAATCGCAAATCAGAATGTTGCGGTGAATA

CGTTCCCGGGCCTTGTACACACCGCCGTCACACCATGGGAGTGGGTTGCACCAG

AAGTAGATAGCTTAACCTTCGGGAGGGCGTTTACCATCGGTGTGATTTCAGGACA

CGGGGG

AHR4-1

TGCCCTTGGCGGCGTGCCTAATACATGCAAGTCGAGCGGATCGATGGGAGCTTG

CTCCCTGAGATCAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCTGTAA

GACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATAACTCAGTTCCTCGC

Chapter 4 Results

188

ATGAGGAACTGTTGAAAGGTGGCTTCTAGCTACCACTTACAGATGGACCCGCGG

CGCATTAACTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCGTAGCCGA

CCTGAGAGGGTGATCGGGCACACTGGGACTGAGACACGGCCCAGACTCCTACGG

GAGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAACAACGC

CGCGTGAGTGAAGAAGGTTTTCGGATCGTAAAACTCTGTTGTTAGGGAAGAACA

AGTGCCGTTCGAATAGGGCGGCACCTTGGACGGTACCTAACCAGAAAGCCACGG

CTTACTACGTGCCAGCAGCCGCGGTAATACGTAAGTGGCAAGCGTTGTCCAGAA

TTATTGGGCGTAAAGCGCGCGCAAGTGGTTTCTTAAGTCTGATGTGAAAGCCCAC

GGCTCAACCGTGGAGGGTCATTGGAAACTGGGGAACTTGAGTGCAGAAGAGGA

AAGTGGAATTCCAAGTGTAGCGGTGAAATGCGTTAGATATTTGGAGGAACACCA

GTGCGAGCGACTTCTGTCTGTACTGACCTGAGCCGAAGCTAACTGACACCTGAG

GGCGGGGAAAGCGTGGGGGAAGCAAAACAAGGATTAGATTACCCTTGGTAGTTC

CACGCCGTAAACGATGAGTGCTAAGTGTTAGAGGGTTTCCGCCCCTTTAGTGCTG

CAGCTAACGCATTAAGCACTCCGCCTTGGGGAGTACGGTCGCAAGACTGAAACT

CAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAA

GCAACGCGAAGAACCTTACCAGGTCTTGACATCCTCTGACAACCCTAGAGATAG

GGCTTTCCCCTTCGGGGGACAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCG

TGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTG

CCAGCATTCAGTTGGGCACTCTAAGATGACTGCCGGTGACAAACCGGAGGAAGG

TGGGGATGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTGCTAC

AATGGACGGTACAAAGGGCAGCGAGACCGCGAGGTTTAGCCAATCCCATAAAA

CCGTTCTCAGTTCGGATTGCAGGCTGCAACTCGCCTGCATGAAGCTGGAATCGCT

AGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACAC

CGCCCGTCACACCACGAGAGTTTGTAACACCCGAAGTCGGTGAGGTAACCTTTT

GGAGCCAGCCGCCTTAAAGTGGAACAGACGGGCTTGC

BHR7-2

CTTCACATGGGCGGCAAGCCTACCATGCAGTCGAGCGGCAGCGGGAAGTAGCTT

GCTACTTTTGCCGGCGAGCGGCGGACGGGTGAGTAATGCCTGGGGATCTGCCCA

GTCGAGGGGGATAACAGTTGGAAACGACTGCTAATACCGCATACGCCCTACGGG

GGAAAGGAGGGGACCTTCGGGCCTTTCGCGATTGGATGAACCCAGGTGGGATTA

GCTAGTTGGTGGGGTAATGGCTCACCAAGGCGACGATCCCTAGCTGGTCTGAGA

GGATGATCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAG

CAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCCATGCCGCGTGTG

TGAAGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAAGGTTGGCGC

CTAATACGTGTCAACTGTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCCGT

GCCAGCAGCCGCGGTAATACGGGAGGGTGCAAGCGTTAATCGGAATTACTGGGC

GTAAAGCGCACGCAGGCGGTTGGGATAAGTTAGATGTGAAAGCCCCGGGGCTCA

CCTGGGAATTGCATTTAAACTGTCCAGCTAGAGTTCTTGTAGAGGGGGGTAGAAT

TCCAGGTGTAGCGGTGAAATGCGTTAGAGAATCTGGAGGAATACCGGTTGGCGA

AGGCGGCCCCTGGAAAAAGACTGACCGCTCCAGGTGCCGAAGCGTGGGGGGAG

CAAACCAGGATTTAGAATACCCTGGTTAACGGTGGCGAAGGCGGCCCCCTTGAC

AAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGGATTAGATACC

CTGGTAGTCCACGCCGTAAACGATGTCGATTTGGAGGCTGTGTCCTTGAGACGTG

GCTTCCGGAGCTAACGCGTTAAATCGACCGCCTGGGGAGTACGGCCGCAAGGTT

AAAACTCAAATGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAA

TTCGATGCAACGCGAAGAACCTTACCTGGCCTTGACATGTCTGGAATCCTGTAGA

GATACGGGAGTGCCTTCGGGAATCAGAACACAGGTGCTGCATGGCTGTCGTCAG

Chapter 4 Results

189

CTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGTCCTTT

GTTGCCAGCACGTAATGGTGGGAACTCAAGGGAGACTGCCGGTGATAAACCGGA

GGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGGCCAGGGCTACACAC

GTGCTACAATGGCGCGTACAGAGGGCTGCAAGCTAGCGATAGTGAGCGAATCCC

AAAAAGCGCGTCGTAGTCCGGATCGGAGTCTGCAACTCGACTCCGTGAAGTCGG

AATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGCCTTGT

ACACACCGCCCGTCACACCATGGGAGTGGGTTGCACCAGAAGTAGATAGCTTAA

CCTTCGGGAGGGCGTTTACCATCGGTGTGATTCATGACCCGGA

BLR6-1

TGGCCGGGGGGGGCAGGCCTCACTCATGCAAGTCGAGCGGCAGCGGGAAAGTA

GCTTGCTACTTTTGCCGGCGAGCGGCGGACGGGTGAGTAATGCCTGGGAAATTG

CCCAGTCGAGGGGGATAACAGTTGGAAACGACTGCTAATACCGCATACGCCCTA

CGGGGGAAAGCAGGGGACCTTCGGGCCTTGCGCGATTGGATATGCCCAGGTGGG

ATTAGCTTGTTGGTGAGGTAATGGCTCACCAAGGCGACGATCCCTAGCTGGTCTG

AGAGGATGATCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGG

CAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCCATGCCGCGT

GTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAAGGTTGA

TGCCTAATACGTATCAGCTGTGACGTTACTCGCAGAAGAAGCACCGGCTAACTC

CGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGG

GCGTAAAGCGCACGCAGGCGGTTGGATAAGTTAGATGTGAAAGCCCCGGGCTCA

ACCTGGGAATTGCATTTAAAACTGTCCAGCTAGAGTCTTGTAGAGGGGGGTAGA

ATTTCCAAGTGTAGCGGTGAAAATGCGTAGAAGATTCTGGAGGAATACCGGGTG

GGCGGAAGGCGGCCCCCTGGACAAAAGACTGACCGCCTCAGGTTGCGAAAGCGT

GGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGTCGAT

TTGGAGGCTGTGTCCTTGAGACGTGGCTTCCGGAGCTAACGCGTTAAATCGACCG

CCTGGGGAGTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCA

CAAGCGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTGGC

CTTGACATGTCTGGAATCCTGTAGAGATACGGGAGTGCCTTCGGGAATCAGAAC

ACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCC

GCAACGAGCGCAACCCCTGTCCTTTGTTGCCAGCACGTAATGGTGGGAACTCAA

GGGAGACTGCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCATCAT

GGCCCTTACGGCCAGGGCTACACACGTGCTACAATGGCGCGTACAGAGGGCTGC

AAGCTAGCGATAGTGAGCGAATCCCAAAAAGCGCGTCGTAGTCCGGATCGGAGT

CTGCAACTCGACTCCGTGAAGTCGGAATCGCTAGTAATCGCAAATCAGAATGTT

GCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTG

GGTTGCACCAGAAGTAGATAGCTTAACCTTCGGGAGGGCGTTTACCATCGGGGT

GATTCCAGACAG

BHM1-1

CCAGAAGTGGCGCGTGCTATAATGCAGTCGAGCGGACAGAAGGGAGCTTGCTCC

CGGATGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCTGTAAGACT

GGGATAACTCCGGGAAACCGGAGCTAATACCGGATAGTTCCTTGAACCGCATGG

TTCAAGGATGAAAGACGGTTTCGGCTGTCACTTACAGATGGACCCGCGGCGCAT

TAGCTAGTTGGTGGGGTAATGGCTCACCAAGGCGACGATGCGTAGCCGACCTGA

GAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGC

AGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCGTG

Chapter 4 Results

190

AGTGATGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGGGAAGAACAAGTGCG

AGAGTAACTGCTCGCACCTTGACGGTACCTAACCAGAAAGCCACGGCTAACTAC

GTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAATTATTGGG

CGTAAAGGGCTCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAC

CCGGGGAGGGTCATTGGGAAACTGGGAAACTTGAGTGCAGAAGAGGAGAGTGG

AATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGGAGGAACACCAGTGGCGA

AGGCGACTCTCTGGTCTGTAACTGACCGCTGAGGAGCCGTAACTTGACGCTGAG

AAGCGAAAGCGTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCACGCCGT

AAACGATGAGTGCTAAGTGTTAGGGGGTTTCCGCCCTTTAGTGCTGCAGCTAACG

CATTAAGCACTCCGCCTGGGGAGTACGGTCGCAAGACTGAAACTCAAAGGAATT

GACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAA

GAACCTTACCAGGTCTTGACATCCTCTGACAACCCTAGAGATAGGGCTTTCCCTT

CGGGGACAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATG

TTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTCAGT

TGGGCACTCTAAGGTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGT

CAAATCATCATGCCCCTTATGACCTGGGCTACACACGTGCTACAATGGACAGAA

CAAAGGGCTGCAAGACCGCAAGGTTTAGCCAATCCCATAAATCTGTTCTCAGTTC

GGATCGCAGTCTGCAACTCGACTGCGTGAAGCTGGAATCGCTAGTAATCGCGGA

TCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACC

ACGAGAGTTTGCAACACCCGAAGTCGGTGAGGTAACCTTTATGGAGCCAGCCGC

CGAAGGTGGGGCAGATGATTTGT

BLM4-1

CTTTCCTTGGGCGGCAAGCCTAACACATGCAAGTCGAGCGGCAGCGGGAAAGTA

GCTTGCTACTTTTGCCGGCGAGCGGCGGACGGGTGAGTAATGCCTGGGAAATTG


CGGGGGAAAGCAGGGGACCTTCGGGCCTTGCGCGATTGGATATGCCCAGGTGGG

ATTAGCTTGTTGGTGAGGTAATGGCTCACCAAGGCGACGATCCCTAGCTGGTCTG



GTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAAGGCTGA

TGCCTAATACGCATCAGCTGTGACGTTACTCGCAGAAGAAGCACCGGCTAACTC




ATTCCAGGTGTAGCGGTGAAATGCGTAGAAGATCTGGAGGAATACCGGTGGGCG

AAGGCGGCCCCCGGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGGAGC

AAACAGGATTAGATAACCCTGGTAGTCCACGCCGTAAACGATGTCGATTTGGAG

GCTGTGTCCTTGAGACGTGGCTTCCGGAGCTAACGCGTTAAATCGACCGCCTGGG

GAGTACGGCCGCAAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCACAAG

CGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTGGCCTTGA

CATGTCTGGAATCCTGTAGAGATACGGGAGTGCCTTCGGGAATCAGAACACAGG

TGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAAC

GAGCGCAACCCCTGTCCTTTGTTGCCAGCACGTAATGGTGGGAACTCAAGGGAG

ACTGCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCC

TTACGGCCAGGGCTACACACGTGCTACAATGGCGCGTACAGAGGGCTGCAAGCT

AGCGATAGTGAGCGAATCCCAAAAAGCGCGTCGTAGTCCGGATCGGAGTCTGCA

ACTCGACTCCGTGAAGTCGGAATCGCTAGTAATCGCAAATCAGAATGTTGCGGT

Chapter 4 Results

191

GAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTG

CACCAGAAGTAGATAGCTTAACCTTCGGGAGGGCGTTTACCACGGTGTGATTCC

AGACCGGA

BLM5-1

TGGCGGCGTGCCGGCGTGCCTAATACATGCCAGTCGAGCGGACAGATGGGAGCT

TGCTCCCTGATGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCTGT

AAGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATGCTTGTTTGAACC

GCATGGTTCAAACATAAAAGGTGGCTTCGGCTACCACTTACAGATGGACCCGCG

GCGCATTAGCTAGTTGGTGAGGTAATGGCTCACCAAGGCGACGATGCGTAGCCG

ACCTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACG

GGAGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACG

CCGCGTGAGTGATGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGGGAAGAAC

AAGTACCGTTCGAATAGGGCGGTACCTTGACGGTACCTAACCAGAAAGCCACGG

CTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGGA

ATTATTGGGCGTAAAGGGCTCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCC

CGGCTCAACCGGGGAGGGTCATTGGAAACTGGGGAACTTGAGTGCAGAAGAGG

AGAGTGGAATTCCACGTGTAGCGGTGAATTGCGTAGAGATGGTGGAGGAACACC

AGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGAGCGAAAGCGTGG

GGAGGCGAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAGTGCT

AAGTGTTAGGGGGTTTCCGCCCCTTAGTGCTGCAGCTAACGCATTAAGCACTCCG

CCTGGGGAGTACGGTCGCAAGACTGAAACTCAAAGGAATTGACGGGGGCCCGC

ACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGG

TCTTGACATCCTCTGACAATCCTAGAGATAGGACGTCCCCTTCGGGGGCAGAGTG

ACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCC

GCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTCAGTTGGGCACTCTAAGG

TGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCC

CCTTATGACCTGGGCTACACACGTGCTACAATGGACAGAACAAAGGGCAGCGAA

ACCGCGAGGTTAAGCCAATCCCACAAATCTGTTCTCAGTTCGGATCGCAGTCTGC

AACTCGACTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGG

TGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTTGTAA

CACCCGAAGTCGGTGAGGTAACCTTTTAGGAGCCAGCCGCCGAAGGTTGGACAG

TTGAAAATGT

CHM5-2

TGGCCTGTGCTGCAAGCCTAACACATGCAAGTCGAGCGGCAGCGGGAAAGTAGC

TTGCTACTTTTGCCGGCGAGCGGCGGACGGGTGAGTAATGCCTGGGGATCTGCCC

AGTCGAGGGGGATAACAGTTGGAAACGACTGCTAATACCGCATACGCCCTACGG

GGGAAAGGAGGGGACCTTCGGGCCTTTCGCGATTGGATGAACCCAGGTGGGATT

AGCTAGTTGGTGGGGTAATGGCTCACCAAGGCGACGATCCCTAGCTGGTCTGAG

AGGATGATCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCA

GCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCCATGCCGCGTGT

GTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAAGGTTGGCG

CCTAATACGTGTCAACTGTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCCG

TGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGC

GTAAAGCGCACGCAGGCGGTTGGATAAGTTAGATGTGAAAGCCCCGGGCTCAAC

CTGGGAATTGCATTTAAAACTGTCCAGCTAGAGTCTTGTAGAGGGGGGTAGAAT

Chapter 4 Results

192

TCCAGGTGTAGCGGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGGCGAA

GGCGGCCCCTGGGACGTCGCCCCCCTTGACAAAGACTGACGCTCAGGTGCGAAA

GCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGT

CGATTTGGAGGCTGTGTCCTTGAGACGTGGCTTCCGGAGCTAACGCGTTAAATCG

ACCGCCTGGGGAGTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCC

CGCACAAGCGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACC

TGGCCTTGACATGTCTGGAATCCTTAAGAGATGCGGGGAGTGCCTTCGGGAATC

AGAACACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAA

GTCCCGCAACGAGCGCAACCCCTGTCCTTTGTTGCCAGCACGTAATGGTGGGAA

CTCAAGGGAGACTGCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGT

CATCATGGCCCTTACGGCCAGGGCTACACACGTGCTACAATGGCGCGTACAGAG

GGCTGCAAGCTAGCGATAGTGAGCGAATCCCAAAAAGCGCGTCGTAGTCCGGAT

CGGAGTCTGCAACTCGACTCCGTGAAGTCGGAATCGCTAGTAATCGCGAATCAG

AATGTCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGG

GAGTGGGTTGCACCAGAAGTAGATAGCTTAACCTTCGGGAGGGCGTTTACCATC

GGTGTGATCCATGACCCGG

CHT9-1

CGTAGCATCTCCGCTTTCGTCTTAATGCATACTATGTCGAGCGGACAGATGGGAG

CTTGCTCCCTGATGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCTG

TAAGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATGGTTGTCTGAAC

CGCATGGTTCAGACATAAAAGGTGGCTTCGGCTACCACTTACAGATGGACCCGC

GGCGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCGACGATGCGTAGCC

GACCTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTAC

GGGAGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAAC

GCCGCGTGAGTGATGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGGGAAGAA

CAAGTGCCGTTCAAATAGGGCGGCACCTTGACGGTACCTAACCAGAAAGCCACG

GCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGA

ATTATTGGGCGTAAAGGGCTCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCC

CGGCTCAACCGGGGAGGGTCATTGGAAACTGGGGAACTTGAGTGCAGAAGAGG

AGAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGGTGGAGGACCACC

AGTGGCGAAGGTGACTCTCTGGTCTGTTACTGACGCTGAGGAGCGAAAGCGTGG

GGAGCGAACAGAATTAGAATCCAGGTGGAGCGAAAGGCGACCTTCTGGTCTTGT

AACTGGACGCTGAGGAGGCGAAAAGCTTGGGGGAAGCGGAACCAGGAATTAGA

TACCCTTGGTAGTCCACGCCGTAAAACGATGAGTGCTAAGTGGTTAGGGGGGTTT

TCCGCCCCTTTAGTGCTGCAGCTAACGCATTAAGCACTCCCGCCTGGGGGAGTAC

GGTCGCAAGACTGAAAATTCAAAGGAAATTGAACGGGGGCCCGCACAAAGCGG

TGGAGCATGTGGTTTAAATTGAAAGCAACGCGAAGGAACCTTACCAGGTCTTGA

CATCCTCTGACAATCCTAGAGATAGGACGTCCCCTTCGGGGGCAGAGTGACAGG

TGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAAC

GAGCGCAACCCTTGATCTTAGTTGCCAGCATTCAGTTGGGCACTCTAAGGTGACT

GCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTA

TGACCTGGGCTACACACGTGCTACAATGGACAGAACAAAGGGCAGCGAAACCG

CGAGGTTAAGCCAATCCCACAAATCTGTTCTCAGTTCGGATCGCAGTCTGCAACT

CGACTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAA

TACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTGGTAACACC

CGAAGTCGGTGAGGTAACCTTTAAGGAGCCAGCCGCTCGAAGATTGGAACAGGA

AGCATTGGA

Chapter 4 Results

193

CHT3-2

TCCCCTGGGCGGCAGGCCTAACACATGCAAGTCGAGCGGTAGCACAAGAGAGCT

TGCTCTCTGGGTGACGAGCGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCTG

ATGGAGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATGACGTCTTCGGA

CCAAAGTGGGGGACCTTCGGGCCTCACGCCATCAGATGTGCCCAGATGGGATTA

GCTAGTAGGTGGGGTAATGGCTCACCTAGGCGACGATCTCTAGCTGGTCTGAGA

GGATGACCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAG

CAGTGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTA

TGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGAGGAGGAAGGCATTGGGT

TAATAACCTTAGTGATTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCCGTGC

CAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTA

AAGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGAGCTTAACTTG

GGAACTGCATTTGAAACTGGCCAGCTAGAGTCTTGTAGAAGGGGGGTAGAATTC

CAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGC

GGCCCCTGGGACAAAGACTGACCGCTCAGGTGCGAAAGCGGTGGGGGGAGCAA

ACAGGATTAGGAAAGCGGCCCCTTGGACAAAAGACTGACGCTTCAGGTGCGAAA

GCGTTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCTGTAAACGATG

TCGACTTGGAGGTTGTGCCCTTGAGGCGTGGCTTCCGGAGCTAACGCGTTAAGTC

GACCGCCTGGGGAGTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGC

CCGCACAAGCGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTAC

CTACTCTTGACATCCAGAGAATTTGCTAGAGATAGCTTAGTGCCTTCGGGAACTC

TGAGACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTTGTGAAATGTTGGGTTAAG

TCCCGCAACGAGCGCAACCCTTATCCTTTGTTGCCAGCGAGTAATGTCGGGAACT

CAAAGGAGACTGCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCA

TCATGGCCCTTACGAGTAGGGCTACACACGTGCTACAATGGCATATACAAAGAG

AAGCGAACTCGCGAGAGCAAGCGGACCTCATAAAGTATGTCGTAGTCCGGATTG

GAGTCTGCAACTCGACTCCATGAAGTCGGAATCGCTAGTAATCGTAGATCAGAA

TGCTACGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGA

GTGGGTTGCAAAAGAAGTAGGTAGCTTAACCTTCGGGAGGGCGCTTACTACATT

GTGATCTATGACCCGG

CLT3-1

AGGGGCGTGGGGCGGCGTGCCTAATACATGCAAGTCGAGCGAATGGATTAAGAG

CTTGCTCTTATGAAGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCC

CATAAGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATAACATTTTGA

ACCGCATGGTTCGAAATTGAAAGGCGGCTTCGGCTGTCACTTATGGATGGACCC

GCGTCGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCGTAG

CCGACCTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCT

ACGGGAGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCA

ACGCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAG

AACAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCA

CGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCG

GAATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAGC

CCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGAAACTTGAGTGCAGAAGA

GGAAAGTGGAAATTCCATGTGTAGCGGTGAAATGCGTAGAAGATATGGAGGAAC

CACCAGTGGCGAAAGGCGACTTTCTGGTCTTGTAACTGACCACTGGAGGCCGCG

AAAGCCGTGGGGGGAGCAAACCAGGATTAGAATACCCCACCAGTGGCGGAGGC

Chapter 4 Results

194

GACTTTCTTGTCTGTAACTGACATTGAGGCGCGAAAGCGTGGGGAGCAATCAGC

ATTAGATACTCTGCTAGTCCACGCCGTAAACGATGAGTGCTAAGTGTTAGAGGGT

TTCCTCCCTTTAGTGCTGAAGTTAACGCATTAAGCACTCCGCCTGGGGAGGTACG

GCCGCCAAGGCTGAAACTCAAAGGAAATGACGGGGGCCCGCACCAAAGCGGTG

GAGGCATGTGGTTTAATTCGAAAGCAACGCGGAGGAACCCTTACCAGGTCTTGA

CTTCCTCTTGACCAACCCTAGAGATAGGGGTTCTCCTTCGGGAGCAGAGTTACCA

GTGGTGCATTGTTGTTGTCAGCCTGTGTTGTGAGATGGTGGGTTAAGTCCCGCAA

CGAGCGCCACCCTTGATTTTAGTTGCCCTCAATAAGTTGGGCACTTTAAAGTGAC

TGCCGGTGACCAACCGGAGGAAGGTGGGGAAGAAGTCAAATCATCCTGCCCCTT

ATTACCTTGGGTACACCCGTGGTACAATGGACGGTACAAAGAGCTGCAAGACCC

CGAGGTGGAGCTAATTTCATAAAACCGTTCTCAGTTTGGATTGTAGGCTGCAACT

CGCCTACATGAAGCTGGAATCGCTAGTAAACGCGGATCAGCATGCCGCGGTGAA

TACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTTGTAACACC

CGAAGGCGGTGGGGTAACCCTTTTGGAGCCAGCCGCCTAAGGTGGACCAGATGA

TTT

DHR1-1

CCCTCCCCCTGCCTAAAGCCCTCACTGTGCCAGTCGACCTGGTGCTGGGCTGCCT

GCTCCTGGTGAGTTCGTGTCGCGGGAGTTTATGTCTGGGAGCTGTGTGATATATG

GTGATTCTACTGCATCTGAGCTAATACCGCATAACGTCTTCGGACCAAAGAGGG

GGACCTTCGGGCCTCTTGCCATCAGATGTGCCCAGATGGGATTAGCTAGTAGGTG

AGGTAATGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGAGAGGATGACCAGC

CACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAGCAGTGGGGAAT

ATTGCACAATGGGCGCAAGCCTGATGCAGCCTTGCCGCGTGTATGAAGAAGGCC

TTCGGGTTGTAAAGTACTTTCAGCGAGGAGGAAGGCATTGTGGTTAATAACCCG

CAGTGATTGACGTTTACTCGCAGAAGAAGCACCGGGCTAACTCCCGTGCCAGCA

GCCGCGGTAATACGGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGC

GGCCACGCAGGCGTGTCTGTCAAGGTCGGATGTGAAATCCCCGGGGCTCAACCT

GGGGAACTGCATTTCGAAACTGGCTAGGCTAGAGTCTTGGTAGAGGGGGGTAGA

ATTCCAGGTGGTAGCGGTGAAAAGGCGTAGGTTAAGTCCCGCAACGAGCGCAAC

CCCTATCCTTTTTTGCCAGCTGTTCGGCCGGGAATTCAAAGGAGACTGCCAGTGA

TAAACTGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGAGTAGG

GCTACACACGTGCTACAATGGCGCATACAAAGAGAAGCGACCTCGCGAGAGCA

AGCGGACCTCATAAAGTGCGTCGTAGTCCGGATCGGAGTCTGCAACTCGACTCC

GTGAAGTCGGAATCGCTAGTAATCGTAGATCAGAATGCTACGGTGAATACGATC

CCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCAAAAGAAGT

AGGTAGCTTAACTCTCGCTCGGGCGCAAACACTTTTTTTCTTTCCCCACAACGTGT

AGT

DHR5-3

CCGGTGGCGAAGGCGGCCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGG

CGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGTC

GATTTGGAGGCTGTGTCCATTGAGACGTGGCTTCCGGAGCTAACGCGTTAAATCG

ACCGCCTGGGGAGTACGGCCGCAAAGGTTAAAACTCAAATGAATTGACGGGGGC

CCGCACAAGCGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTAC

CTGGCCTTGACATGTCTGGGATCCTGCAGAGATGCGGGAGTGCCTTCGGGAATC

AGAACACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAA

Chapter 4 Results

195

GTCCCGCAACGAGCGCAACCCCTGTCCTTTGTTGCCAGCACGTAATGGTGGGAA

CTCAAGGGAGACTGCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGT

CATCATGGCCCTTACGGCCAGGGCTACACACGTGCTACAATGGCGCGTACAGAG

GGCTGCAAGCTAGCGATAGTGAGCGAATCCCAAAAAGCGCGTCGTAGTCCGGAT

CGGAGTCTGCAACTCGACTCCGTGAAGTCGGAATCGCTAGTAATCGCGAATCAG

AATGTCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGG

GAGTGGGTTGCACCAGAAGTAGATAGCTTAACCTTCGGGAGGGCGTTTACCATC

GGTGTGATTCCAAGAACCCGGTCTCGCGTGGCTGCAAGCCTAACACATGCAAGT

CGAGCGGCAGCGGGAAAGTAGCTTGCTACTTTTGCCGGCGAGCGGCGGACGGGT

GAGTAATGCCTGGGGATCTGCCCAGTCGAGGGGGATAACAGTTGGAAACGACTG

CTAATACCGCATACGCCCTACGGGGGAAAGGAGGGGACCTTCGGGCCTTTCGCG

ATTGGATGAACCCAGGTGGGATTAGCTAGTTGGTGGGGTAATGGCTCACCAAGG

CGACGATCCCTAGCTGGTCTGAGAGGATGATCAGCCACACTGGAACTGAGACAC

GGTCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAAC

CCTGATGCAGCCATGCCGCGTGTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTT

CAGCGAGGAGGAAAGGTTGGCGCCTAATACGTGTCAACTGTGACGTTACTCGCA

GAAGAAGCACCGGCTAACTCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCA

AGCGTTAATCGGAATTACTGGGCGTAAAGCGCACGCAGGCGGTTGGATAAGTTA

GATGTGAAAGCCCCGGGCTCAACCTGGGAATTGCATTTTAAAACTGTCCAGCTA

GAGTCTTGTAGAGGGGGGTAGAATTCCAAGGTGTAGCGGTGAAATGCGTAGAGA

TCTGGAGGAATACCGGTGGGCGAAAGCGGCCCCCTGGACAAAGAACTGACGCCT

CAGGTGGCGAAAGCGGTGGGGACTAGCAAAACAGGATTAGAGATACCCTTGGTA

DHR2-2

AGGACCGTGGGCGGCGTGCCTAATACATGCAAGTCGAGCGAATGGATTAAGAGC

TTGCTCTTATGAAGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCC

ATAAGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATAACATTTTGAA

CCGCATGGTTCGAAATTGAAAGGCGGCTTCGGCTGTCACTTATGGATGGACCCGC

GTCGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCGTAGCC



GCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAA

CAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCACG

GCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGA

ATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAGCCCC

ACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGGAGACTTGAGTGCAGAAGAG

GAAAGTGGATTTCCATGTGTAGCGGTGAAATGCGTAGAGATATGGAGGAACCAC

CAGTGGCGAAAGGCGACTTTTCTGGTTTGTAACTGACACTGAGGCCGCGAAGAG

CGCGAAGAGCAACTTTCTGTTCTGTAACTGACCACTGAGGCGCGAAAGCGTGGG

AAGCCAATCAGCATTAGATACCCTGGTAGTCACCGCCGTAAACGATGAGTGCTC

AGTGGTTATGACGGTTTCCTCCCCTTTCAGTGCTGAAGTTAACAGCATTCAGCAC

TTCCGCCTGGGGAGTACGGCCGGCCAGGCTGAAACTCAAAGGAATTGACGGGGG

CCCGCACCAAGCGGTGGAGCATGTGGTTTAATTTGAAGCCACCCGAAGAACCTT

ACCCAGTCTTGACATCCTCTGACAACCCTAGAGATAGGGCTTCTCCTTTGGGAGC

AGAGTGACCGGTGGTGCATGGTTGTTGTCCGCTCGTGTCGTGAGATGTTGGGTTA

AGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCATCATTAAGTTGGGCACT

CTAAGGTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCAT

CATGCCCCTTATGACCTGGGCTACACACGTGCTACAATGGACGGTACAAAGAGC

Chapter 4 Results

196

TGCAAGACCGCGAGGTGGAGCTAATCTCATAAAACCGTTCTCAGTTCGGATTGTA

GGGTGCAACTCGCCTACATGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATG

CCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAG

TTTGTAACACCCGAAGTCGGTGGGGGAACCTTTTTGGAGCCAGCCGCCTAAGGT

GCACCAGAAGATGTG

DHT6-1

CCGAAGTGGGCGGCGTGCCTAATACATGCAAGTCGAGCGGACAGATGGGAGCTT

GCTCCCTGATGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCTGTA

AGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATGGTTGTCTGGACCG

CATGGTTCAGACATAAAAGGTGGCTTCGGCTACCACTTACAGATGGACCCGCGG

CGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCGACGATGCGTAGCCGA

CCTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGG

GAGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGC

CGCGTGAGTGATGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGGGAAGAACA

AGTGCCGTTCAAATAGGGCGGCACCTTGACGGTACCTAACCAGAAAGCCACGGC

TAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAAT

TATTGGGCGTAAAGGGCTCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCG

GCTCAACCGGGGAGGGTCATTGGAAACTGGGGAACTTGAGTGCAGAAGAGGAG

AGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGGAGGAACACCAGT

GGCGAAGGCGACTCCTCTGGTTCTTGTAACTGACCGCTGAGGAGCGAAAAAGTC

GACTTCTCTGGTTCTGTAACTGACGCTGAGGAGCGAAAGCGTGGGGAGCGAACA

GGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAGTGCTAAGTGTTAGGG

GGTTTCCGCCCCTTAGTGCTGCAGCTAACGCATTAAGCACTCCGCCTGGGGAGTA

CGGTCGCAAGACTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGG

AGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTCTTGACATCCT

CTGACAATCCTAGAGATAGGACGTCCCCTTCGGGGGCAGAGTGACAGGTGGTGC

ATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGC

AACCCTTGATCTTAGTTGCCAGCATTCAGTTGGGCACTCTAAGGTGACTGCCGGT

GACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACCT

GGGCTACACACGTGCTACAATGGACAGAACAAAGGGCAGCGAAACCGCGAGGT

TAAGCCAATCCCACAAATCTGTTCTCAGTTCGGATCGCAGTCTGCAACTCGACTG

CGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTT

CCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTTGTAACACCCGAAG

TCGGTGAGGTACCTTATAGGAGCCAGCCGCCGAAGGTGGGACAGATGATTGG

DLT5-1

GTGATGGGTTGATTCAAGCCTCTCCATGCAAGTCGAGCGGTAGCACAGAGAGCT

TGCTCTCGGGTGACGAGCGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCTGA

TGGAGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCGCAAGAC

CAAAGTGGGGGACCTTCGGGCCTCATGCCATCAGATGTGCCCAGATGGGATTAG

CTAGTAGGTGGGGTAATGGCTCACCTAGGCGACGATCCCTAGCTGGTCAGATGG

GATTAGCTAGTAGGTGGGGTAATGGCTCACCTAGGCGACGATCCCTAGCTGGTCT

GAGAGGATGACCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGA

GGCAGCAGTGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGC

GTGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGAGGAGGAAGGCGT

TAAGGTTAATAACCTTGGTGATTGACGTTACTCGCAGAAGAAGCACCGGCTAAC

Chapter 4 Results

197

TCCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACT

GGGCGTAAAGCGCACGCAGGCGGTCTGTCAAGTCGGATGTGAAATCCCCGGGCT

CAACCTGGGAACTGCATTCGAAACTGGCAGGCTAGAGTCTTGTAGAGGGGGGTA

GAATTCCAGGTGTAGCGGTGAAATGCGTAGAGAATCTGGAGGAATACCGGTGGG

CGAAAGCGGCCCCTTGGACAAAAACTGACCCCTCAGGTGGCGAAAGCGTGGGGT

GGCGAAAGCGTGGACCTCTGGACAAAAGACTGACGCTCAGGTGCGGAAGCGTG

GGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGTCGACT

TGGAGGTTGTGCCCTTGAGGCGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGC

CTGGGGAGTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCAC

AAGCGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTACTCT

TGACATCCAGAGAACTTAGCAGAGATGCTTTGGTGCCTTCGGGAACTCTGAGAC

AGGTGCTGCATGGCTGTCGTCAGCTCGTGTTGTGAAATGTTGGGTTAAGTCCCGC

AACGAGCGCAACCCTTATCCTTTGTTGCCAGCGATTCGGTCGGGAACTCAAAGG

AGACTGCCAGTGATAAACTGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGC

CCTTACGAGTAGGGCTACACACGTGCTACAATGGCATATACAAAGAGAAGCGAC

CTCGCGAGAGCAAGCGGACCTCATAAAGTATGTCGTAGTCCGGATTGGAGTCTG

CAACTCGACTCCATGAAGTCGGAATCGCTAGTAATCGTAGATCAGAATGCTACG

GTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTT

GCAAAAGAAGTAGGTAGCTTRAACCTTCGGGAGGGCGCTACTAGATTTGGATCC

AATGCCCCCGG

DLR3-1

GGGACCTTGGGGGCGTGTCTAATACATGCAAGTCGAGCGGACAGATGGGAGCTT


AGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATGCTTGTTTGAACCG

CATGGTTCAAACATAAAAGGTGGCTTCGGCTACCACTTACAGATGGACCCGCGG

CGCATTAGCTAGTTGGTGAGGTAATGGCTCACCAAGGCAACGATGCGTAGCCGA




AGTACCGTTCAAATAGGGCGGTACCTTGACGGTACCTAACCAGAAAGCCACGGC


TATTGGGCGTAAAGGGCTCGCAGGCGGTTCCTTAAGTCTGATGTGAAAGCCCCC

GGCTCAACCGGGGAGGGTCATTGGGAAACTGGGGAACTTGAGTGCAGAAGAGG

AGAGTGGAATTTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGGGAGGAACAC

CAGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGAGCGAAAGCGGT

GGGGGGAGCGAACAGGACGACTCTCCTGGTCTTTAACTGACGCTGAGGAGCGAA

AGCGTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGAT

GAGTGCTAAGTGTTAAGGGGGTTTCCGCCCCTTAGTGCTGCAGCTAACGCATTAA

GCACTCCGCCTGGGGAGTACGGTCGCAAGACTGAAACTCAAAGGAATTGACGGG

GGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCT

TACCAGGTCTTGACATCCTCTGACAATCCTAGAGATAGGACGTCCCCTTCGGGGG

CAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTT

AAGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTCAGTTGGGCAC

TCTAAGGTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCA

TCATGCCCCTTATGACCTGGGCTACACACGTGCTACAATGGACAGAACAAAGGG

CAGCGAAACCGCGAGGTTAAGCCAATCCCACAAATCTGTTCTCAGTTCGGATCG

CAGTCTGCAACTCGACTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCA

Chapter 4 Results

198

TGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAG

AGTTTGTAACACCCGAAGTCGGTGAGGTAACCTTTATGGAGCCAGCCGCCGAAG

GTGGACCAGTTGGATTTGG

AHM3-1

AGGCGTGGCGGCGTGCCTAATACATGCAAGTCGAGCGAATGGATTGAGAGCTTG

CTCTCTTGAAGTTAGCGGCGGACGGGTGAGTAACACGTGGGTACCCTGCCCATA

AGACTGGGATACCTCCGGGAAACCGGGGCTAATACCGGATAATATTTTGAACTG

CATGGTTCGAAATTGAAAGGCGGCTTCGGCTGTCACTTATGGATGGACCCGCGTC

GCATTAGCTAGTTGGTGAGGTAACGGCTCACCAGGGCAACGATGCGTAGCCGAC

CTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGG

AGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACAGAACCACGCCG

CGTGAGTGATGAATGCTTTCAGGTCGTAGATCTCTGTTGTTAGGGAAGAACAAGT

GCTAGTTGTATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCACGGCTAA

CTACGTGCCAGCAGCCGCGGTTATACGTAGGTGGCAAGCGTTATCCGGAATTATT

GCGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAACGCCCACGGTCT

CACCGGTGGAGGGCTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGAATGT

GGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATATGGAGGAACACCATTGGC

GAAGGCATCTTTCTGGTCTTGTAACTGACCTTGAGGCGCGAAAGCGTTGGGGAG

CAAACTGACACTGAGGAGCGAAAGCGTGGGGGGCAAACAGGATTAGATACCCT

GGTAGTCCACGCCGTAAACGATGAGTGCTAAGTGTTAGAGGGTTTCCGCCCTTTA

GTGCTGCAGTTAACGCATTAAGCACTCCGCCTGGGGAGTACGGTCGCAAGACTG

AAACTCAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAAT

TCGAAGCAACGCGAAGAACCTTACCAGGTCTTGACATCCTCTGACAATCCCTAG

AGATAGGAGGTTCTCCCTTCGGGAGCAGAGTGACAGGTGGTGCATGGTTGTCGT

CAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGATC

TTAGTTGCCATCATTTAGTTGGGCACTCTAAGGTGACTGCCGGTGACAAACCGGA

GGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACAC

GTGCTACAATGGACAGGTACAAAGAGCAGCAAGACCGCGAGGGTGGAGCTAAT

CTCATAAAACCGTTCTCAGTTCGGATTGTAGGCTGCAACTCGCCTACATGAAGCT

GGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCT

TGTACACACCGCCCGTCACACCACGAGAGGTGGTAACACCCGAAGTCGGTGGGG

TAACCTTATTGGAGCCAGCCGCTTAAAGTGGGACAAGATGATTGG

ALM9-1

ACGGGAAGTGGCGGCGTGCCTAATACATGCAAGTCGAGCGCAGGAAATCGACG

GAACCCTTCGGGGGGAAGTCGACGGAATGAGCGGCGGACGGGTGAGTAACACG

TAAAGAACCTGCCCTCAGGTCTGGGATAACCACGAGAAATCGGGGCTAATACCG

GATGGGTCATCGGACCGCATGGTCCGAGGATGAAAGGCGCTTCGGCGTCGCCTG

GGGATGGCTTTGCGGTGCATTAGCTAGTTGGTGGGGTAATGGCCCACCAAGGCG

ACGATGCATAGCCGACCTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGG

CCCAGACTCCTACGGGAGGCAGCAGTAGGGAATCTTCCACAATGGACGAAAGTC

TGATGGAGCAACGCCGCGTGAACGATGAAGGCCTTCGGGTCGTAAAGTTCTGTT

GTAAGGGAAGAACAAGTGCCGCAGGCAATGGCGGCACCTTGACGGTACCTTGCG

AGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAG

CGTTGTCCGGAATTATTGGGCGTAAAGCGCGCGCAGGCGGCCTCTTAAGTCTGAT

GTGAAAGCCCCCGGCTCAACCGGGGAGGGCCATTGGAAACTGGGAGGCTTGAGT

Chapter 4 Results

199

ATAGGAGAGAAGAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGG

AGGAACACCAGTGGCGAAGGCGACTCCTTTGGCTTATACTGACGCTGAGGCGCG

TAACTTGACGCTGAGGCCGCGAAAAGCCGTGGGGTGAGCCAACCAGGATTAGAT

ACCCTGGTAGTTCCACGCCGTAAACCGATGAGTGCTAGGTGTTGGGAGGGTTTCC

GCCCTTCAGTGCTGAAGCTAACGCATTAAGCACTCCGCCTGGGGAGTACGGTCG

CAAGGCTGAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGAGCATG

TGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAAACTCTTGACATCCCCCCTG

ACCGGTACAGAGATGTACCTTCCCCTTCGGGGGCAGGGGTGACAGGTGGTGCAT

GGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAA

CCCTTGTCCTTAGTTGCCACCATTCAGTTGGGCACTCTAAGGAGACTGCCGGTGA

CAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGAGTTGG

GCTACACACGTGCTACAATGGACGGTACAAAGGGCAGCGAAGCCGCGAGGTGG

AGCCAATCCCAGAAAGCCGTTCTCAGTTCGGATTGCAGGCTGCAACTCGCCTGC

ATGAAGTCGGAATCGCTAGTAATCGCAGGTCAGCATACTGCGGTGAATACGTTC

CCGGGCCTTGCACACACCGCCCGTCACACCACGAGAGTGGTAACACCCGAAGTC

GGTGAGGTAACCGCAAGGAGCCAGCCGCCGAAGGTGACAAGAGATTG

AHT5-5

ATTAAAATGGCGGCGTGCCTAATACATGCAAGTCGAGCGAACTGATTAGAAGCT

TGCTTCTATGACGTTAGCGGCGGACGGGTGAGTAACACGTGGGCAACCTGCCTG

TAAGACTGGGATAACTCCGGGAAACCGGAGCTAATACCGGATAACATTTTCTCTT

GCATAAGAGAAAATTGAAAGATGGTTTCGGCTATCACTTACAGATGGGCCCGCG

GTGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCATAGCCG

ACCTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACG

GGAGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACG

CCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAAC

AAGTACAAGAGTAACTGCTTGTACCTTGACGGTACCTAACCAGAAAGCCACGGC

TAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAAT

TATTGGGCGTAAAGCGCGCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCAC

GGCTCAACCGTGGAGGGTCATTGGAAACTGGGGAACTTGAGTGCAGAAGAGAA

AAGCGGAATTCCACGTGTAGCGGTGAATTGCGTAGAGATTGTGGAGGAACACCA

GTGGCGAAGGCGGCTTTTTGGTTCTGTAACTGACGCTGAGGCCGCGAAAGCGTG

GGGCTTTTTGGGTTCTGTTAACTGACGCTGAGGGCGGCGAAAGCGGTGGGGGAG

CAAACAGGATTAGATACCCTTGGTAGTCCACGCCGTAAACGATGAGTGCTAAGT

GTTAGAGGGTTTCCGCCCTTTAGTGCTGCAGCTAACGCATTAAGCACTCCGCCTG

GGGAGTACGGTCGCAAGACTGAAACTCAAAGGAATTGACGGGGGCCCGCACAA

GCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTCTT

GACATCCTCTGACAACTCTAGAGATAGAGCGTTCCCCTTCGGGGGACAGAGTGA

CAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCG

CAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTTAGTTGGGCACTCTAAGGT

GACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCC

CTTATGACCTGGGCTACACACGTGCTACAATGGATGGTACAAAGGGCTGCAAGA

CCGCGAGGTCAAGCCAATCCCATAAAACCATTCTCAGTTCGGATTGTAGGCTGC

AACTCGCCTACATGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGG

TGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTTGTAA

CACCCGAAGTCGGTGGGGTAACCTTTATGGAGCCAGCCGCCTAAGGTGGGACAG

ATGATT TG

Chapter 4 Results

200

BHT3-1

AATCCGCTGGCGGCAGGCCTAACACATGCAAGTCGAGCGGCAGCGGGAAAGTA

GCTTGCTACTTTTGCCGGCGAGCGGCGGACGGGTGAGTAATGCCTGGGGATCTG


CGGGGGAAAGGAGGGGACCTTCGGGCCTTTCGCGATTGGATGAACCCAGGTGGG

ATTAGCTAGTTGGTGGGGTAATGGCTCACCAAGGCGACGATCCCTAGCTGGTCTG



GTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAAGGTTGG

CGCCTAATACGTGTCAACTGTGACGTTACTCGCAGAAGAAGCACCGGCTAACTC




ATTCCAGGTGTAGCGGTGAAATGCGTAGAGATTTGGAGGAATACCGGGTGGGCG

AAGCGGCCCCCTGGACAAAGACTGACGCTCAGTTGCTGGACAAAAAGAACTGAC

GCTCCAGGTGCGGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTTC

CACGCCGTAAACGATGTCGATTTGGAGGGCTGTGTCCCTTGAGACGTGGCTTCCG

GAGCTAACGCGTTAAATCGACCGCCTGGGGAGTACGGCCGCAAGGTTAAAACTC

AAATGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGATG

CAACGCGAAGAACCTTACCTGGCCTTGACATGTCTGGAATCCTGCAGAGATGCG

GGAGTGCCTTCGGGAATCAGAACACAGGTGCTGCATGGCTGTCGTCAGCTCGTG

TCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCCTGTCCTTTGTTGCC

AGCACGTAATGGTGGGAACTCAAGGGAGACTGCCGGTGATAAACCGGAGGAAG

GTGGGGATGACGTCAAGTCATCATGGCCCTTACGGCCAGGGCTACACACGTGCT

ACAATGGCGCGTACAGAGGGCTGCAAGCTAGCGATAGTGAGCGAATCCCAAAA

AGCGCGTCGTAGTCCGGATCGGAGTCTGCAACTCGACTCCGTGAAGTCGGAATC

GCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGCCTTGTACAC

ACCGCCCGTCACACCATGGGAGTGGGTTGCACCAGAAGTAGATAGCTTAACCTT

CGGGAGGGCGTTTACCACGGTGTGATCCAAGAACTTTGA

CHR3-01

TGGGACTGGGCGGCGTGCCTAATACATGCAAGTCGAGCGAATGGATTAAGAGCT

TGCTCTTATGAAGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCCA

TAAGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATAACATTTTGAAC

CGCATGGTTCGAAATTGAAAGGCGGCTTCGGCTGTCACTTATGGATGGACCCGC

GTCGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCGTAGCC



GCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAA

CAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCCACG

GCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGA

ATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAGCCCA

CGGCTCAACCGTGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAGAGGA

AAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATTATGGAGGAACACCA

GTGGGCGAAGGCGACTTTCTGGTTCTGTAACTGACCACTGCTGTCTGTACCTGAC

ACTGAGGCGCGAAGCGTGGGGAGCAATCAGAATTAGATATCCTGGTAGTCAAGG

CCGTAAACGATGAGTGCTAAGTGTTAGAGGGTTTCCGCCCTTTAGTGCTGAAGTT

Chapter 4 Results

201

AACGCATTAAGCACTCCGCCTGGGGAGTACGGCCGCAAGGCTGAAACTCAAAGG

AATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACG

CGAAGAACCCTTACCAGGTCTTGACATCCTCTGACAACCCTAGAGATAGGGCTTC

TCCTTCGGGAGCAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGA

GATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCATCATT

TAGTTGGGCACTCTAAGGTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATG

ACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTGCTACAATGGACG

GTACAAAGAGCTGCAAGACCGCGAGGTGGAGCTAATCTCATAAAACCGTTCTCA

GTTCGGATTGTAGGCTGCAACTCGCCTACATGAAGCTGGAATCGCTAGTAATCGC

GGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCA

CACCACGAGAGTTTGTAACACCCGAAGTCGGTGGGGTAACCTTTTTGGAGCCAG

CCGCCTAAGGTGGGACAGA AAATGG

DHR1-5

ATTCGATGGCGGCAAGCCTAACACATGCAAGTCGAGCGGCAGCGGGAAAGTAG

CTTGCTACTTTTGCCGGCGAGCGGCGGACGGGTGAGTAATGCCTGGGGATCTGCC

CAGTCGAGGGGGATAACTACTGGAAACGACTGCTAATACCGCATACGCCCTACG

GGGGAAAGGAGGGGACCTTCGGGCCTTGCGCGATTGGATGAACCCAGGTGGGAT

TAGCTAGTTGGTGAGGTAATGGCTCACCAAGGCGACGATCCCTAGCTGGTCTGA

GAGGATGATCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGC

AGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCCATGCCGCGTG

TGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAAGGATGCT

GGCTAATATCCAGCATCTGTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCC

GTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGG

CGTAAAGCGCACGCAGGCGGTTGGATAAGTTAGATGTGAAAGCCCCGGGCTCAA

CCTGGGAATTGCATTTAAAACTGTCCAGCTAGAGTCTTGTAGAGGGGGGGTAGA

ATTCCAGGTGTAGCGGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCCG

AAGGCGGCCCCCTTGGACAAAAGACTGACGCCTCAGTTGCGAACGAAGGCCGGC

CCTCCCTGGACAAAAGGACTGACGCTCCAGGTGGCGGAAAGCGTGGGGGAGCA

AACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGTCGATTTGGAGGC

TGTGTCCCTTGAGACGTGGCTTCCGGAGCTAACGCGTTAAATCGACCGCCTGGGG

AGTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCACAAGCG

GTGGAGCATGTGGTATACGGGAGTGCCTTCGGGAATCAGAACACAGGTGCTGCA

TGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCA

ACCCCTGTCCTTTGTTGCCAGCACGTAATGGTGGGAACTCAAGGGAGACTGCCG

GTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGGC

CAGGGCTACACACGTGCTACAATGGCGCGTACAGAGGGCTGCAAGCTAGCGATA

GTGAGCGAATCCCAAAAAGCGCGTCGTAGTCCGGATCGGAGTCTGCAACTCGAC

TCCGTGAAGTCGGAATCGCTAGTAATCGCAAATCAGAATGTTGCGGTGAATACG

TTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCACCAGA

A GTAGATAGCTTAACCTTCGGGAGGGCGTTTACCACGGTGTGATTCATGACTGG

DHR6-4

TCATTTGCAACGTCGAGCGGACAGAAGGGAGCTTGCTCCCGGATGTTAGCGGCG

GACGGGTGAGTAACACGTGGGTAACCTGCCTGTAAGACTGGGATAACTCCGGGA

AACCGGAGCTAATACCGTGGACCCGCGGCGCATTAGCTAGTTGGTGGGGTAATG

Chapter 4 Results

202

GCTCACCAAGGCGACGATGCGTAGCCGACCTGAGAGGGTGATCGGCCACACTGG

GACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTAGGGAATCTTCCGCA

ATGGACGAAAGTCTGACGGAGCAACGCCGCGTGAGTGATGAAGGTTTTCGGATC

GTAAAGCTCTGTTGTTAGGGAAGAACAAGTGCGAGAGTAACTGCTCGCACCTTG

ACGGTACCTAACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATA

CGTAGGTGGCAAGCGTTGTCCGGAATTATTGGGCGTAAAGGGCTCGCAGGCGGT

TTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAACCGGGGAGGGTCATTGGAAAC

TGGGAAACTTGAGTGCAGAAGAGGAGAGTGGAATTCCACGTGTAGCGGTGAAAT

GCGTAGAGATGTGGAGGAACACCAGTGGCCGAAGGCGACTCCTCTGGTCTGTAA

CTGACGCTGAGGAGCGAAAGCGTGGGGGAGGCGAACAGGATTAGAATACCCTG

GTAGTCCACGCCGTAAACGATGGAGTGCTAAGTGTTAGGGGGTTTCCGCCCCCTT

AGTGGCCTGCAGCTACCGCATAAAGCACTCCGCCTGGGGGAGATACGTTCGCAA

GACTGAAATCTCAAAGGGAATTGACGGGGGCCCGCACAAAGCGCGGCTTCAATC

CGGGGAGGTTCATTGAAAACTGGGAAACTTGAGTGCAGAAGAGGAGAGTGGCA

AATCCCACGTGTAGCGGTGGAATGCGTTAGAGATGTGGAGGAACACCAGTGGGC

GAAGGCGACTCTCTGGTCTGTAAACTGACGCTGAGGAGCGAAAGCGTGGGGGAG

CGAAACAGGATTAGATACCCTGGTAGTTCCACGCCGTAAAACGATGAGTGCTAA

GTGTTAAGGGGGGTTTCCGCCCCTTAGTGCTGCAGCTAACGCATTAAGCACTCCG

CCTGGGGAGTACGGTCGCAAGACTGAAACTCAAAAGGAAATGACGGGGGCCCG

CACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAG

GTCTTGACATCCTCTGACAACCCTAGAGATAGGGCTTTCCCTTCGGGGACAGAGT

GACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCC

CGCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTTAGTTGGGCACTCTAAG

GTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGC

CCCTTATGACCTGGGCTACACACGTGCTACAATGGACAGAACAAAGGGCTGCAA

GACCGCAAGGTTTAGCCAATCCCATAAATCTGTTCTCAGTTCGGATCGCAGTCTG

CAACTCGACTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCG

GTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTTGTA

ACACCCGAAGTCGGTGAGGTAACCTTTATGGAGCCAGCCGCCGAAGGTGGGGCA

GATGATTG

DHM5-1

GTTCCCTTGGGGCGGGGGTTGCCTAATACATGCAAGTCGAGCGAATGGATTAAG

AGCTTGCTCTTATGAAGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTG

CCCATAAGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATAACATTTT

GAACTGCATGGTTCGAAATTGAAAGGCGGCTTCGGCTGTCACTTATGGATGGAC

CCGCGTCGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCGT

AGCCGACCTGAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTC

CTACGGGAGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGC

AACGCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAA

GAACAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTAACCAGAAAGCC

ACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCC

GGAATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCTGATGTGAAAG

CCCACGGCTCACCCGTGGAGGGTCATTGGAAACTGGGAGACTTGAGTGCAGAAG

AGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATTATGGAGGAAC

ACCAGTGGCCGAGGGCGACTTTCTGGTCTGTAACTGACACTGAAGGCGCGGAAA

GCGTGGGGGAGCAAACAGGATTAGAATACCCTGGTTAGTCCACCGCCGTAAACG

ATGGAGTGCTAAGTGTTAGAGGGTTTCCGCCCTTTAGTGCCTGAAGTTACCGCAT

Chapter 4 Results

203

TAAGCACTCCGCCTGGGGAGTACGGCCGCAAGGCTGAAACTCAAAGGAATTGAC

GGGGGCCCGCACAAGGCGTGTGGAGACATGGTGGTTGTGTATGCGGTGAAATGC

GTTGAGAGAATAACTGACAGAACAATCCAAGTGGCGAATGGCCGACCTTCCTGT

TCTGTAGCTGACACTGAGGCGCGAAAGCGTGGGGGAGCAATCAGGATTAGATAC

CCTGGTAGTACCACGCCGTAAACGATGAGTGCTAAAGTGTTAGAGGGTTTCCGC

CCTTTAGTGCTGAAGTTAAACGCATTAAGCACTCCGCCTGGGGAGTACGGCCGC

AAGGGCTGAAACTCAAAAGGAATTGACGGGGGCCCGCACAAGCGGTGGAGCAT

GTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTCTTGACATCCTCTGAA

AACCCTAGAGATAGGGCTTCTCCTTCGGGAGCAGAGTGACAGGTGGTGCATGGT

TGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCC

TTGATCTTAGTTGCCATCATTAAGTTGGGCACTCTAAGGTGACTGCCGGTGACAA

ACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACCTGGGCT

ACACACGTGCTACAATGGACGGTACAAAGAGCTGCAAGACCGCGAGGTGGAGC

TAATCTCATAAAACCGTTCTCAGTTCGGATTGTAGGCTGCAACTCGCCTACATGA

AGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGG

GCCTTGTACACACCGCCCGTCACACCACGAGAGTTTGTAACACCCGAAGTCGGT

GGGGTAACCTTTTTGGAGCCAGCCGCCTAAGGTGGGACACTTTAG

DLM3-1

CCAACTTGGGCGGCGTGCCTAATACATGCAAGTCGAGCGGACAGATGGGAGCTT


AGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATGCTTGTTTGAACCG

CATGGTTCAAACATAAAAGGTGGCTTCGGCTACCACTTACAGATGGACCCGCGG

CGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCGTAGCCGA




AGTGCCGTTCAAATAGGGCGGCACCTTGACGGTACCTAACCAGAAAGCCACGGC


TATTGGGCGTAAAGGGCTCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCG

GGCTCAACCGGGGAGGGTCATTGGAAACTGGGGAACTTGAGTGCAGAAGAGGA

GAGTGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGGAGGAACACCAG

TGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGAGCGAAAGCGGTGGG

GGAGCGGACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGAGTGCTA

AGTGTTAGGGGGTTTCCGCCCCTTAGTGCTGCAGCTAACGCATTAAGCACTCCGG

CCCTGGGGAGGTACGGTCTCTTAAGTCTGATGTGAAAGCCCCCGGCTCAACCGG

GGAGGGTTCATTGGAAATTGGGGAACTTGAGTGCAGAAAGAAGGAGAAGTGGA

ATTCCACGTGTAAGCCGGTGAAATGCGTAGAGAATGTGGAGCAAACACCCAGTG

GTCGAATGGCGGACTCTTCCTGGTTCTGTAAACTGACGCTGATGAGCGAAAGCGT

GGGGGAGCGAAACATGGATCAGATATCTTGGTAGTCCACGCCGTAAACGATGAG

TGCTAAGTGTTAGGGGGTTTCCGCCCCTTAGTGCTGCAGCTAACGCATTAAGCAC

TCCGCCTGGGGAGTACGGTCGCAAGACTGAAACTCAAAGGAATTGACGGGGGCC

CGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACC

AGGTCTTGACATCCTCTGACACCCCTAGAGATAGGGCTTCCCCTTCGGGGGCAGA

GTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGT

CCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTCAGTTGGGCACTCTA

AGGTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCAT

GCCCCTTATGACCTGGGCTACACACGTGCTACAATGGACAGAACAAAGGGCAGC

Chapter 4 Results

204

GAGACCGCGAGGTTAAGCCAATCCCACAAATCTGTTCTCAGTTCGGATCGCAGT

CTGCAACTCGACTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCC

GCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTT

GTAACACCCGAAGTCGGTGAGGTAACCTTTATGGAGCCAGCCGCCGAAGGTGGG

ACAAGAAGATTT

DLR1-5

TTTTGGGCGGCGTGCCTAATACATGCAAGTCGAGCGGATCTTTCAAAAGCTTGCT

TTTTGAAGGTCAGCGGCGGACGGGTGAGTAACACGTGGGCAACCTGCCTGTGAG

ACTGGGATAACTTCGGGAAACCGGAGCTAATACCGGATAATATAAGGAACCTCG

CATGGTTCTTTATTGAAAGATGGTTTCGGCTATCACTCACAGATGGGCCCGCGGC

GCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCGACGATGCGTAGCCGAC


AGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGATGGAGCAACGCCG

CGTGAGCGATGAAGGCCTTCGGGTCGTAAAGCTCTGTTGTTAGGGAAGAACAAG

TGCCGAGAGTAACTGCTCGGCACCTTGACGGTACCTAACCAGAAAGCCACGGCT

AACTACGTGCCAGCAGCCGCGGTTATACGTTAGGTGGCAAGCGTTGTCCGGAAT

TATTGGGGCGGTAAAGCGCGGCGCAGGTGGTCCTTTAAGTCTGATGTGGAAAGC

CCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGGGACTTGAGGTGCAGAAG

AGGAAAGTGGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATTTGGAGGAACA

CAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACACTGGAGGCCCACGGCTCA

ATCCGTGGGAGGGTTCATTGGAAACTGGGGGACTTGAGTTGCAGGAAGAGGAAA

GTGGAATTCCAAGTGTAGGCGGTGGAAATGCGTAGAGATTTGGAGGCACACCAG

TGGGCGAAGGCGACTTTCCTGGTCTGTAACTGACACTGAGGCGCGGAAAGCGTG

GGGGAGCAAACAGGATTAGATACCCTGGTAGTACACGCCGTAAACGATGAGTGC

TAAAGTGTTAGAGGGGTTTTCCTGCCCTTTAGTGCTGCAGCTAACGCATTAAGCA

CTCCGCCTGGGGAGTACGGTCGCAAGACTGAAACTCAAAGGAATTGACGGGGGC

CCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTAC

CAGGTCTTGACATCCTCTGACACTCCTAGAGATAGGGATTTCCCCTTCGGGGGAC

AGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTA

AGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTCAGTTGGGCACT

CTAAGATGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCAT

CATGCCCCTTATGACCTGGGCTACACACGTGCTACAATGGACGGTACAAAG

GGCAGCAAAACCGCGAGGTCGAGCCAATCCCATAAAACCGTTCTCAGTTCGGAT

TGCAGGCTGCAACTCGCCTGCATGAAGCCGGAATCGCTAGTAATCGCGGATCAG

CATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACG

AGAGTTTGTAACACCCGAAGTCGGTGGGGTAACCTTTTGGAGCCAGCCGCCTAA

GGTGGGACAGATGATTG

DLR1-3

ATTGGGGCGGCGTGCCTAATACATGCAAGTCGAGCGAACTGATTAGAAGCTTGC

TTCTATGACGTTAGCGGCGGACGGGTGAGTAACACGTGGGCAACCTGCCTGTAA

GACTGGGATAACTTCGGGAAACCGAAGCTAATACCGGATAGGATCTTCTCCTTC

ATGGGAGATGATTGAAAGATGGTTTCGGCTATCACTTACAGATGGGCCCGCGGT

GCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATGCATAGCCGAC


Chapter 4 Results

205

AGGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCC

GCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTGTTGTTAGGGAAGAACAA

GTACGAGAGTAACTGCTCGTGCCTTGACGGTACCTAACCAGAAAGCCACGGCTA

ACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCAGGAATT

ATTTGGGCGTAAAGCGCGCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCAC

GCGCGAAGAACCTTACCAGGTCTTGACATCCTCTGACAACTCTAGAGATAGAGC

GTTCCCCTTCGGGGGACAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGT

CGTGAGATGTTGGGTTAAGTCCTCGCAACGAGCGCAACCCTTGCATCTTAGTTGC

CAGCATTCAGTTGGGCAGCTCTAAGGTGACTGCCGGTGACAAACCGTGAGGAAG

GTGGGGATGACGTCAAATCATCATGCCCCTTATCACCTGGGCTACACACGTGCTA

CAATGGATGGTACAAAGGGCTGCAAGACCGCGAGGTCAAGCCAATCCCATAAA

ACCATTCTCAGTTCGGATTGTAGGCTGCAACTCGCCTACATGAAGCTGGAATCGC

TAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACA

CCGCCCGTCACACCACGAGAGTTTGTAACACCCGAAGTCGGTGGAG

TAACCGTAAGGAGCTAGCCGCCTAAGGTGGACCGTTCAG

AHR7-5

TCTTGGGGGGCAGGCCTAACACATGCAAGTCGAGCGGCAGCGGGAAAGTAGCTT

GCTACTTTTGCCGGCGAGCGGCGGACGGGTGAGTAATGCCTGGGGATCTGCCCA

GTCGAGGGGGATAACAGTTGGAAACGACTGCTAATACCGCATACGCCCTACGGG

GGAAAGGAGGGGACCTTCGGGCCTTTCGCGATTGGATGAACCCAGGTGGGATTA

GCTAGTTGGTGAGGTAATGGCTCACCAAGGCGACGATCCCTAGCTGGTCTGAGA

GGATGATCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAG

CAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCCATGCCGCGTGTG

TGAAGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAAGGTTGGTAG

CGAATAACTGCCAGCTGTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCCGT

GCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCG

TAAAGCGCACGCAGGCGGTTGGATAAGTTAGATGTGAAAGCCCCGGGCTCAACC

TGGGAATTGCATTTAAAACTGTCCAGCTAGAGTTCTTGTAGAGGGGGGTAGAATT

CCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGATATACCGGTGGCGAAGG

CGGCCCCCTGGACACAGACCTGACGCTCAGGGTGCGAAAGCGTGGGGGGGAGC

AAACAGGATTAGATTACCATAAGTTAGATGTGAAAGCCCCGGGCTCAACCTGGG

AATTGCATTTAAAACTGTCCAGCTAGAGTCTTGTAGAGGGGGGTAGAATTCCAG

GTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCC

CCCTGGACAAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGGAT

TAGATAACCCTGGTAGTCCACGCCGTAAACGATGTCGATTTGGAGGCTGTTGTCC

TTGAGACGTGGCTTCCGGAGCTAACGCGTTAAATCGACCGCCTGGGGAGTACGG

CCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCACAAGCGGTGGAGC

ATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTGGCCTTGACATGTCTGG

AATCCCTAAGAGATTGGGGAGTGCCTTCGGGAATCAGAACACAGGTGCTGCATG

GCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAAC

CCCTGTCCTTTGTTGCCAGCACGTAATGGTGGGAACTCAAGGGAGACTGCCGGTG

ATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGGCCAG

GGCTACACACGTGCTACAATGGCGCGTACAGAGGGCTGCAAGCTAGCGATAGTG

AGCGAATCCCAAAAAGCGCGTCGTAGTCCGGATCGGAGTCTGCAACTCGACTCC

GTGAAGTCGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTC

CCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCACCAGAAGT

AGATAGCTTAACCTTCGGGAGGGCGTTTACCATGAGTGGTTCCAAAACAGA

Chapter 4 Results

206

AHT3-2

GATTTTGGGCGGGCGTTGCCTAATTCATGCAAGTCGAGGCGGAATTGGAATTAA

GAGCTTTGGCTCTTTTTTGAAGTTAACCGGCCCAAAGGAGGTTAAAAAACACCGT

TGGGGGAAAACCTCCCCCCAAAAAAGGGGGGGGATAAATCCCGGGAAAAAAAC

CGGGGGATTAAAAAATATATATTTTTTTTCAGTTCGATGCATGCACGGCTCACTG

AGTCATGTACTGCAGCTGAGTCATAGAGAACGATCCATTGACGTCATGCGTAGA

TATATGGAGGAATATCAGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTG

AGGCTCGAAAGCGTGGGTAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCG

TAAACGATGAGTGCTAAGTGTTTGAGGGTTTCCGCCCTTTCAGTGCTGCAGTTAA

CGCATTAAAGCACTCCGCCTGGGGAGTACGGACCGCCAAGGTCTGAAACTCAAA

TGGAATTGACGGGGGACCCGCCACCAAAGCGGTGGAGCAATTGTGGTTTAATTC

GAACCAACCGCGAAAAAACCTTACCCAAGTCTTGCACATCCTTTGACCACTCTAA

GAGATAGAGCATTCTCCTTCGGGGACAGAGTAGACAGGTGGTGCATGGTTGTCG

TCCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGA

TTACTAGTTGCCAGCATTGAGTTGGGCAACTCATAGTGAGACTGCCGGTGACAA

ACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACTTGGGCT

ACACACGTGCTACAATGGATGGTACAACGAGCAGCGAAACTCGCGAGGTGTAAG

CGAATCTTCTTAAAGCCATTCTCAGTTCGGATTGTAGGCTGCAACTCGCCTACAT

GGAAGCCGGAATCGCTAGTAATCGCGGATCAGCACGCCGCGGTGAATACGTTCC

CGGGTCTTGTACACACCGCCCGTCACACCACGAGAGTTTGTAACACCCAAAGTC

GGTGAGGTAACCTTACGGAGCCAGCCGCCTAAGGTGGACCAGATGATTTTGT

BHT6-1

CTTGGCGGCAGGCCTAACACATGCAAGTCGAACGGTAGCACAGAGAGCTTGCTC

TCGGGTGACGAGTGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCTGATGGAG

GGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCGCAAGACCAAAG

AGGGGGACCTTCGGGCCTCTTGCCATCAGATGTGCCCAGATGGGATTAGCTAGT

AGGTGGGGTAACGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGAGAGGATGA

CCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAGCAGTGG

GGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGA

AGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGCGATAAGGTTAATA

ACCTTGTCGATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGTGCCAGC

AGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAGC

GCACGCAGGCGGTCTGTCAAGTCGGATGTGAAATCCCCGGGCTCAACCTGGGAA

CTGCATTCGAAACTGGCAGGCTGGGAGTCTTGTAGAGGGGGGGTAGAATTCCAG

GTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCCGGTGGCCGAAGGCGG

CCCCCTGGGACAAAGACTGACCGCTCCAGGTGGCGAAAGCGTGGGGGAGCAAA

CAGGATTAGAATACCCTGGTAGTCCACGCTGTAAACGATGTCCGACTTGGAGGTT

GTTCCCTTGAGGAGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCCGCCTGGGG

GAGTACGGCCCGCAAGGTTAAAACTCGTCAAGTCGGATGTGAAATCCCCGGGCT

CAAACTGGGAACTGCATTCGAAACTGGCAGGCTGGAGTCTTGTAGAGGGGGGTA

GAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCG

AAGGCGGCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCA

AACAGGATTAGATACCCTGGTAGTCCACGCTGTAAACGATGTCGACTTGGAGGT

TGTTCCCTTGAGGAGTGGCTTCCGGAGCTAACGCGTTAAAGTCGACCGCCTGGGG


GTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTACTCTTGACA

Chapter 4 Results

207

TCCACGGAACTTAGCAGAGATGCTTTGGTGCCTTCGGGAACCGTGAGACAGGTG

CTGCATGGCTGTCGTCAGCTCGTGTTGTGAAATGTTGGGTTAAGTCCCGCAACGA

GCGCAACCCTTATCCTTTGTTGCCAGCGATTCGGTCGGGAACTCAAAGGAGACTG

CCAGTGATAAACTGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTAC

GAGTAGGGCTACACACGTGCTACAATGGCATATACAAAGAGAAGCGACCTCGCG

AGAGCAAGCGGACCTCATAAAGTATGTCGTAGTCCGGATTGGAGTCTGCAACTC

GACTCCATGAAGTCGGAATCGCTAGTAATCGTGGATCAGAATGCCACGGTGAAT

ACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCAAA

AGAAGTAGGTAGCTTAACCTTCGGGAGGGCGCTTACCACTTTTGGATCCAAAATT

G

CHR3-1

CTTTTGGGGGCAGACTTTCACATGCAAGTCGAGCGGTAGCACAGGAGAGCTTGC

TCTCTGGGTGACGAGCGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCTGATG

GAGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCTTCGGACCA

AAGTGGGGGACCTTCGGGCCTCACGCCATCAGATGTGCCCAGATGGGATTAGCT

AGTAGGTGGGGTAATGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGAGAGGA

TGACCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAGCAG

TGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTGTGA

AGAAGGCCTTCGGGTTGTAAAGCACTTTCAGCGAGGAGGAAGGGTAGTGTGTTA

ATAGCACATTGCATTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCCGTGCC

AGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAA

AGCGCACGCAGGCGGTTTGTTAAGTCAGATGTGAAATCCCCGCGCTTAACGTGG

GAACTGCATTTGAAACTGGCAAGCTAGAGTCTTGTAGAGGGGGGTAGAATTCCA

GGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGGCGAAGGCG

GCCCCCTGGACAAAGACTGACGCTCAGGTGGCGAAAGCGTGGGGGAGCAAACA

GGATTAGAATACCCTGGTAGTCCACGCTGTAAACGATGTCGACTTGGAGGTTGTG

CCCTTGAGGCGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTGGGGAGTA

CGGCCCGCAAGGTTAAAACTCAAATGAATTGGACGGGGGCCCGCTCCCCGCGCT

TAACGTGGGAACTGCATTTGAAACTGGCAAGCTAGAGTCTTGTAGAGGGGGGTA

GAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCG

AAGGCGGCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCA

AACAGGATTAGATACCCTGGTAGTCCACGCCTGTAAACGATGTCGACTTGGAGG

TTGTGCCCTTGAGGCGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTGGGG



TCCAGAGAATTCGCTAGAGATAGCTTAGTGCCTTCGGGAACTCTGAGACAGGTG


GCGCAACCCTTATCCTTTGTTGCCAGCACGTAATGGTGGGAACTCAAAGGAGACT

GCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTA

CGAGTAGGGCTACACACGTGCTACAATGGCGTATACAAAGAGAAGCGAACTCGC

GAGAGCCAGCGGACCTCATAAAGTACGTCGTAGTCCGGATCGGAGTCTGCAACT

CGACTCCGTGAAGTCGGAATCGCTAGTAATCGTAGATCAGAATGCTACGGTGAA

TACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCAA

AAGAAGTAGGTAGCTTAACCTTCGGGAGGGCGCTACTAGTGGTTGATTCCAGGA

CTTG

Chapter 4 Results

208

CHM7-1

CGCATTCTGTAGAAGGCGTGCCTAATACATGCAAGTCGAGCGGACAGATGGGAG

CTTGCTCCCTGATGTTAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCTG

TAAGACTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATGCTTGTTTGAAC

CGCATGGTTCAAACATAAAAGGTGGCTTCGGCTACCACTTACAGATGGACCCGC

GGCGCATTAGCTAGTTGGTGAGGTAATGGCTCACCAAGGCAACGATGCGTAGCC



GCCGCGTGAGTGATGAAGGTTTTCGGATCGTAAAGCTCTGTTGTTAGGGAAGAA

CAAGTGCCGTTCAAATAGGGCGGCACCTTGACGGTACCTAACCAGAAAGCCACG

GCTAACTACGTGCCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGG

AATTATTGGGCGTAAAGGGCTCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCC

CCGGCTCAACCGGGGGAGGGTCATTGGAAACTGGGGAACTTGAGTGCAGAAGA

GGAGAGTGGAATTCCGAACAGGAATTAAGATAGCCTGGTTAGGTCCACGCCGTA

AAAATGATGACGGCTAAAGTGTTAGGGGGTTTCCGCCCCTTAGTGCTGCAGCTA

ACGCATTAAGCACTCCCGCCTGGGGAGTACGGTCGGCAAGACTGAAACTCAAAG

GAATTGAACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAA

CGCGAAGAACCTTACCAGGTCTTGACATCCTCTGACAATCCTAGAGATAGGACG

TCCCCTTCGGGGGCAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGT

GAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCA

TTCAGTTGGGCACTCTAAGGTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGA

TGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTGCTACAATGGA

CAGAACAAAGGGCAGCGAAACCGCGAGGTTAAGCCAATCCCACAAATCTGTTCT

CAGTTCGGATCGCAGTCTGCAACTCGACTGCGTGAAGCTGGAATCGCTAGTAATC

GCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGT

CACACCACGAGAGTTTGTAACACCCGAAGTCGGTGAGGTAACCTTTTAGGAGCC

AGCCGCCGAAGGTGGGACCAGCACATGGT

CLM4-1

CCCTTGGCGGCGTGCCTAATACATGCAAGTCGAGCGGACCGACGGGAGCTTGCT

CCCTTAGGTCAGCGGCGGACGGGTGAGTAACACGTGGGTAACCTGCCTGTAAGA

CTGGGATAACTCCGGGAAACCGGGGCTAATACCGGATGCTTGATTGAACCGCAT

GGTTCAATCATAAAAGGTGGCTTTTAGCTACCACTTGCAGATGGACCCGCGGCGC

ATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCGACGATGCGTAGCCGACCT

GAGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGA

GGCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGC

GTGAGTGATGAAGGTTTTCGGATCGTAAAACTCTGTTGTTAGGGAAGAACAAGT

ACCGTTCGAATAGGGCGGTACCTTGACGGTACCTAACCAGAAAGCCACGGCTAA

CTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTGTCCGGAATTAT

TGGGCGTAAAGCGCGCGCAGGCGGTTTCTTAAGTCTGATGTGAAAGCCCCCGGC

TCAACCGGGGAGGGTCATTGGGAAACTGGGGAACTTGAGTGCAGAAGAGGAGA

GTGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGGAGGAACACCAGTG

GCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGCGCGAAAGCGTGGGGGA

GCGAACAGGATTAGATACCCTGGTAGTCCCCGCCGTAAACGATGAGTGCTAGGT

GTTAGAGGGTTTCCGCCCTTTAGTGCTGCAGCAAACGCATTAAGCACTCCGCCTG

GGGGAGGTACGGTCGCAAGACTGGGAGGGTCATTGGAAACTGGGGAACTTGAGT

GCAGAAGAGGAGAATGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTG

Chapter 4 Results

209

GAGGAACACCAGTGGCGAAGGCGACTCTCTGGTCTGTAACTGACGCTGAGGACG

CGAAAGCGTGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAAC

GATGAGTGCTAAAGTGTTAGAGGGTTTCCGCCCTTTAGTGCTGCAGCAAACGCAT

TAAGCACTCCGCCTGGGGAGTACGGTCGCAAGACTGAAACTCAAAGGAATTGAC

GGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAA

CCTTACCAGGTCTTGACATCCTCTGGCAACCCTAGAGATAGGGCTTCCCCTTCGG

GGGCAGAGTGACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTG

GGTTAAGTCCCGCAACGAGCGCAACCCTTGATCTTAGTTGCCAGCATTCAGTTGG

GCACTCTAAGGTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAA

ATCATCATGCCCCTTATGACCTGGGCTACACACGTGCTACAATGGGCAGAACAA

AGGGCAGCGAAGCCGCGAGGCTAAGCCAATCCCACAAATCTGTTCTCAGTTCGG

ATCGCAGTCTGCAACTCGACTGCGTGAAGCTGGAATCGCTAGTAATCGCGGATC

AGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCA

CGAGAGTTTGTAACACCCGAAGTCGGTGAGGTAACCTTTTGGAGCCAGCCGCCG

AAGGTGGGACAGAAATTG

CHT2-2

CTGGCGGGCAGGCCTAACACATGCAAGTCGGGCGGTAGCACAGAGAGCTTGCTC

TCGGGTGACGAGCGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCTGATGGAG

GGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCGCAAGACCAAAG

TGGGGGACCTTCGGGCCTCATGCCATCAGATGTGCCCAGATGGGATTAGCTAGT

AGGTGGGGTAATGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGAGAGGATGA

CCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAGCAGTGG

GGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGAAGA

AGGCCTTCGGGTTGTAAAGTACTTTCAGCGAGGAGGAAGGCATTAAGGTTAATA

ACCTTAGTCGATTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCCGTGCCAG

CAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGTAAAG

CGCACGCAGGCGGTCTGTTAAGTCAGATGTGAAATCCCCGGGCTCAACCTGGGA

ACTGCATTTGAAACTGGCAGGCTTGAGTCTTGTAGAGGGGGGTAGAATTCCAGG

TGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGAAGGCGGCCC

CCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGGATTA

GATACCCTGGTAGTCCACCGCTGTAAACGATGTCGACTTGGAGGTTGTTCCCTTG

AGGAGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTGGGGAGTACCGGCG

CAAGGTTAGAAGCTGCATTCGAAACTGGCAGGCTTGAGTCTTGTAGAGGGAGGT

AGAATTCCAGGTGTAGCGGTGAAATGCGTAAGAGATCTGGAGGAATACCGGTGG

CGAAGGCGGCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGGG

AGCCAACAGGATTAGATACCTTGGTAGTCCACGCTGTAAACCGATGTCGACTTG

GAGGTTGTTCCCTTGAAGGAGTGGCTTCCGGAGCTAACGCGTTAAAGTCGACCG

CCTGGGGAGTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCA

CAAGCGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTACT

CTTGACATCCAGAGAACTTAGCAGAGATGCTTTGGTTGCCTTCGGGAACTCTGAG

ACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTTGTGAAATGTTGGGTTAAGTCCC

GCAACGAGCGCAACCCTTATCCTTTGTTGCCAGCGATTCGGTCGGGAACTCAAA

GGAGACTGCCAGTGATAAACTGGAGGAAGGTGGGGATGACGTCAAGTCATCATG

GCCCTTACGAGTAGGGCTACACACGTGCTACAATGGCATATACAAAGAGAAGCG

ACCTCGCGAGAGCAAGCGGACCTCATAAAGTATGTCGTAGTCCGGATTGGAGTC

TGCAACTCGACTCCATGAAGTCGGAATCGCTAGTAATCGTAGATCAGAATGCTA

CGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGG

Chapter 4 Results

210

GTTGCAAAAGAAGTAGGTAGCTTAACCTTCGGGAGGGCGCTTACCACTTTGTGG

ATTCATGACTTG

DHR4-2

ATTAAGTACACGGTTGACCTACCTTGTCACGTCATCCTATCCATTGGTATTGTGAT

CCACGCTGTGCAGCCCGGATGCCTGATATCCCGTGATGCCGTCCGACAAAGTGG

ATACTGCTGCCACGCGGCATACTGAGTAGGTCTGATGCTTTAGCTGACTTCTGGG

CTCTGCCCGTCTTTTGAATAATGGAATCAGTTACAATCATGAAGCGGGTTAAAGG

CAAACAACTCTTCCCGCCCTTATGCGAACGCTGCCAGCCAGGAAACCCTGTTTTT

TCATGCCCCCCGTGGGGGTTCCCGGGGAAACTTTCGAAATGGATCAACCCTAAT

AAACCTCCACCGAATTATTCAAGGCTTAGGGGCCTTATTTTCGGCCCACAAAAAC

GGGGATTCTGACAAGTTCGTTATTGTTAAAAACACCATCCAAATTACTGATGGGA

GGCCGTGGAACCCCCCCCAATCCCCAATTTAATTCTTTTCCATATTTTGAAAGGA

AAATGCCGAAAGGTTTTTCTTTTGTTTTTTTGCCGGACCGCGTACCCAGCATGCTT

TTTGGGTTTAGTTAACCCCGGTTAAGGGATCCACGAGTACCGGCAATCAGCGGA

AAACGAATAACGGCCGGCTGCGGGTAATGCCTGTTATAGGCAAGGGTATCTTTG

ACCAATTTAGTAATACTACCCTTTCTGGATTAAAACTGGGAAGCGTTTTTAAGCT

TGTAACTGGGAACTGCATTCGGAACTGGCAAGCTAGAGTCTTGTAGAGGGGGGT

AGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGC

GAAGGGCGGCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGC

AAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGTCGACTTAGAGG

TTGTTCCCTTGAGGAGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTGGGG



TCCAGAGAATTCGCTAGAGATAGCTTAGTGCCTTCGGGAACTCTGAGACAGGTG


GCGCAACCCTTATCCTTTGTTGCCAGCGGTTCGGCCGGGAACTCAAAGGAGACT

GCCAGTGATAAACTGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTA

CGAGTAGGGCTACACACGTGCTACAATGGCGCATACAAAGAGAAGCGACCTCGC

GAGAGCAAGCGGACCTCATAAAGTGCGTCGTAGTCCGGATCGGAGTCTGCAACT

CGACTCCGTGAAGTCGGAATCGCTAGTAATCGTAGATCAGAATGCTACGGTGAA

TACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCAA

AAGAAGTAGGTAGCTTAACTCTTGGCTCAGAGCTACGTTAGAGGGGACCCCTAA

CAACCCGG

DHR5-1

CCGGTGATTGGCAGGGTAATCTTCTCCTAGTGGTCCGATCGTGGCACAAGAGAG

CGTTGCTCTCTGGGTGACGAGCGGCGGACGGGTGAGTAATGTCTGGGAAACTGC

CTGTATGGAGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATGATGTCTT

CGGACCAAAGTGGGGGACCTTCGGGCCTCACGCCATCAGATGTGCCCAGATGGG

ATTAGCTAGTAGGTGGGGTAATGGCTCACCTAGGCGACGATCTCTAGCTGGTCTG

AGAGGATGACCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAG

GCAGCAGTGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCG

TGTATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGAGGAGGAAGGCATT

GTGGTTAATAACCACAGTGATTGACGTTACTCGCAGAAGAAGCACCGGCTAACT

CCGTGCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTG

Chapter 4 Results

211

GGCGTAAAGCGCACGCAGGCGGTTGATTAAGTCAGATGTGAAATCCCCGAGCTT

AACTTGGGAACTGCATTTGAAACTGGTCAGCTAGAGTCTTGTAGAGGGGGGTAG

AATTCCAAGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCGGTGGCGA

AGGCGGCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAA

ACAGGATTAGATACCCTGGTAGTCCACGCTGTAAACGATGTCGACTTGGAGGTT

GGTGCCCTTGAGGCGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTGGGG

GAGTACGGCCGCAGGAACTGCATTTGAAACTGGTCAGCTAGAGTCTTGTAGAGG

GGGGTAGAATTCCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCG

GTGGCGAAGGCGGCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGG

GGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCTGTAAACGATGTCGACTT

GGAGGTTGTGCCCTTGAGGCGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGC

CTGGGGAGTACGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCAC

AAGCGGTGGAGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTACTCT

TGACATCCAGAGAATTTGCCAGAGATGCCTTAGTGCCTTCGGGAACTCTGAGAC

AGGTGCTGCATGGCTGTCGTCAGCTCGTGTTGTGAAATGTTGGGTTAAGTCCCGC

AACGAGCGCAACCCTTATCCTTTGTTGCCAGCACGTAATGGTGGGAACTCAAAG

GAGACTGCCGGTGATAAACCGGAGGAAGGTGGGGATGACGTCAAGTCATCATGG

CCCTTACGAGTAGGGCTACACACGTGCTACAATGGCATATACAAAGAGAAGCGA

ACTCGCGAGAGCAAGCGGACCTCATAAAGTATGTCGTAGTCCGGATTGGAGTCT

GCAACTCGACTCCATGAAGTCGGAATCGCTAGTAATCGTAGATCAGAATGCTAC

GGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGG

TTGCAAAAGAAGTAGGTAGCTTAACCTTCGGGAGGGCGCTTACCTAATAGGCG

DHT3-1

TTGAACGCTGGCCGGCAGGCCTAACACATGCAAGTCGAACGGTAGCACAGAGAG

CTTGCTCTCGGGTGACGAGTGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCT

GATGGAGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCGCAAG

ACCAAAGAGGGGGACCTTCGGGCCTCTTGCCATCAGATGTGCCCAGATGGGATT

AGCTAGTAGGTGGGGTAACGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGAG

AGGATGACCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCA

GCAGTGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGT

ATGAAGAAGGCCTTCGGGTTGTAAAGTACTTTCAGCGGGGAGGAAGGCGATAAG

GTTAATAACCTTGTCGATTGACGTTACCCGCAGAAGAAGCACCGGCTAACTCCGT

GCCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCG

TAAAGCGCACGCAGGCGGTCTGTCAAGTCGGATGTGAAATCCCCGGGCTCAACC

TGGGAACTGCATTCGAAACTGGCAGGCTGGGAGTCTTGTAGAGGGGGGTAGAAT

TCCAGGTGTAGCGGTGAAATGCGTAGAGATTCTGGAGGAATACCGGTGGCGAAG

GCGGCCCCCTGGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGGAGCAA

ACAGGATTAGATACCCTGGTAGTCCCACGCCTTGTAAACGATGTTCGACTTGGAG

GTTGTTCCCTTGAGGAGATGGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTTG

GGGAGTACGGCCGCAACCCCGGGCTCCAACCTGGGAACCTGCATTCGAAACTGG

CAGGCTGGAGTCCTTGTAGAGGGGGGTAGAATTCCAGGTGTAGCGGTGAAATGC

GTAGAGATTCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGGACAAAAGACT

GACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTC

CACGCTGTAAACGATGTCGACTTGGAGGTTGTTCCCTTGAGGAGTGGCTTCCGGA

GCTAACGCGTTAAGTCGACCGCCTGGGGAGTACGGCCGCAAGGTTAAAACTCAA

ATGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGATGCA

ACGCGAAGAACCTTACCTACTCTTGACATCCACGGAACTTAGCAGAGATGCTTTG

Chapter 4 Results

212

GTGCCTTCGGGAACCGTGAGACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTTGT

GAAATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATCCTTTGTTGCCAGCG

ATTCGGTCGGGAACTCAAAGGAGACTGCCAGTGATAAACTGGAGGAAGGTGGG

GATGACGTCAAGTCATCATGGCCCTTACGAGTAGGGCTACACACGTGCTACAAT

GGCATATACAAAGAGAAGCGACCTCGCGAGAGCAAGCGGACCTCATAAAGTAT

GTCGTAGTCCGGATTGGAGTCTGCAACTCGACTCCATGAAGTCGGAATCGCTAGT

AATCGTGGATCAGAATGCCACGGTGAATACGTTCCCGGGCCTTGTACACACCGC

CCGTCACACCATGGGAGTGGGTTGCAAAAGAAGTAGGTAGCTTAACCTTCGGGA

GGGCGCTTACCACTTTGTGATACAGAAATTGG

DLR10-1

TTTCCACGTGTCTTCTCATAGCGGTCCGATCGTTTTGCCGGTTCTGCCAGCTTGTT

TATTCAGACAGGCGGGAGCCGCTTTCTGAGCCATGATCGACTCTAGGGAGGCTTC

TCTACGGCGTAGCTAATACCGCATACGCCCTACGGGGGAAAGCAGGGGATCGCA

AGACCTTGCACTATTGGAGCGGCCGATATCGGATTAGCTAGTTGGTGGGGTAAC

GGCTCACCAAGGCGACGATCCGTAGCTGGTTTGAGAGGACGACCAGCCACACTG

GGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGAC

AATGGGGGAAACCCTGATCCAGCCATCCCGCGTGTGCGATGAAGGCCTTCGGGT

TGTAAAGCACTTTTGGCAGGAAAGAAACGTCGCGGGTTAATACCCCGGGGAACT

GACGGTACCTGCAGAATAAGCACCGGCTAACTACGTGCCAGCAGCCGCGGTAAT

ACGTAGGGTGCAAGCGTTAATCTGGAATTACTGGGCGTAAAGCGTGCGCGGGCG

GATTCGGAAAGAAATGATGTGAAATCCCAGAGCTTAACTTTGGAACTGTCATTTT

TAACTACCGGAGCTAGAGTGTGTCAGAGGGAGGTGGCAATTCCGCGATAGTTAG

CAGTTGAAATGCGTAGATATGCGGAAGGAACACCGAATGGCGAGAGGCAGCCTC

CTGGGATAACCACTGTACTGCTTCATGCCACGAAAGCGTGGAGGAGCAAACAGG

ATTGAGAATACCCTGGTAGTCCAGGCCCTAAACGATGTCAACTAGACATGTTGG

GCGTCGTAGCAGTGAAATGCGTAGATTATGCGGAGGAACACCGATGGCGAAGGC

AGCCTCCTGGGATAACACTGACGCTCCATGCACGAAAGCGTGGGGAGCAAACAG

GATTAGATAGCCCTGGTAGTCCACGCCCCTAAACGATGTCAATCTAGCTGTTGGG

GCCTTCCGGGCCTTGGTAGACGCAGCTAACGCGTGAAGTTGACCGCCTGGGGAG

TACGGTCGCAAGATTAAAACTCAAAGGAATTGACGGGGACCCCGCACAAGCGGT

GGATGATGTGGATTAATTCGATGCAACGCGAAAAACCTTACCTACCCTTGACATG

TCTGGAATCCTGAAGAGATTTAGGAGTGCTCGCAAGAGAACCGGAACACAGGTG

CTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGA

GCGCAACCCTTGTCATTAGTTGCTACGAAAGGGCACTCTAATGAGACTGCCGGTG

ACAAACCGGAGGAAGGTGGGGATGACGTCAAGTCCTCATGGCCCTTATGGGTAG

GGCTTCACACGTCATACAATGGTCGGGACAGAGGGTCGCCAACCCGCGAGGGGG

AGCCAATCCCAGAAACCCGATCGTAGTCCGGATCGCAGTCTGCAACTCGACTGC

GTGAAGTCGGAATCGCTAGTAATCGCGGATCAGCATGTCGCGGTGAATACGTTC

CCGGGTCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTTTACCAGAAGT

AGTTAGCCTAACCGCAAGGAGGGCGATTACCTTTGGGTGGACCCAAAGAACCG

AHM4-1

TATCAATGGGCGGCAGGCCTAACACATGCAAGTCGAGCGGTAGCACAGGAGAG

CTTGCTCTCTGGGTGACGAGCGGCGGACGGGTGAGTAATGTCTGGGAAACTGCC

TGATGGAGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCTTCG

Chapter 4 Results

213

GACCAAAGAGGGGGACCTTCGGGCCTCTTGCCATCAGATGTGCCCAGATGGGAT

TAGCTAGTAGGTGAGGTAATGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGA

GAGGATGACCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGC

AGCAGTGGGGAATATTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTG

TATGAAGAAGGGCCTTCGGGTTGTAAAGTACTTTCAGCGAGGAGGAAGGCATTG

TGGTTAATAACCGCAGTGATTGACGTTACTCGCAGAAGAAGCACCGGCTAACTC

CGTGCCAGCAGCCGCGGTAATACGGAGGGGTGCAAGCGTTTAATCGGAATTACT

GGGGCGTTAAAGCGCACGCAGGCGGTCTGTCAAGTCGGATGGTGAAATCCCCGG

GCCTCAACCTGGGGAACTGCATTCGAAACTGGCAGGGCTAGAGTCTTGTAGAGG

GGGGGTAGAATTCCAGGGTGTAGCGGTTGAAATGCGTAGAGATCTGGAGGGAAT

ACCGGGTGGCGAAGGCGGCCCCCCTGGACAAAGACCTGACGCTCAGGGTGCGA

AAGCGTGGGGGAGCAACACAGGATTAGCATACCCTCTGGGTTAGTCCACTGCCG

TACAACGAATGCTCGACATTTTGGAGGTTGTTCCTCCTTTGAGGAAGTGGCTCTC

TCGCAGACTAACTCGAAACTGGCAGGCTAGAGTCTTGTAGAGGGGGGTAGAATT

CCAGGTGTAGCGGTGAAATGCGTAGAGATCTGGAGGAATACCCGGTGGCGAAGG

CGGCCCCCTGGACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACA

GGATTAGATACCCTGGTAGTCCACGCCAGTAAACGATGTCGACTTGGAGGTTGTT

CCCTTGAGGAGTGGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTGGGGAGTA

CGGCCGCAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCACAAGCGGTGG

AGCATGTGGTTTAATTCGATGCAACGCGAAGAACCTTACCTACTCTTGACATCCA

GAGAATTCGCTAGAGATAGCTTAGTGCCTTCGGGAACTCTGAGACAGGTGCTGC

ATGGCTGTCGTCAGCTCGTGTTGTGAAATGTTGGGTTAAGTCCCGCAACGAGCGC

AACCCTTATCCTTTGTTGCCAGCGGTTCGGCCGGGAACTCAAAGGAGACTGCCA

GTGATAAACTGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGAG

TAGGGCTACACACGTGCTACAATGGCGCATACAAAGAGAAGCGACCTCGCGAGA

GCAAGCGGACCTCATAAAGTGCGTCGTAGTCCGGATCGGAGTCTGCAACTCGAC

TCCGTGAAGTCGGAATCGCTAGTAATCGTAGATCAGAATGCTACGGTGAATACG

TTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCAAAAGA

AGTAGGTAGCTTAACCTTCGGGAGGGCGCTTACCACTTTGTGATTCATGACCACG

GA

BLR6-10

GAATTTGGGGGGCAGGCCTAACACATGCAAGTCGAGCGGTAGCACAGAGAGCTT

GCTCTCGGGTGACGAGCGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCTGAT

GGAGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCGCAAGACC

AAAGTGGGGGACCTTCGGGCCTCATGCCATCAGATGTGCCCAGATGGGATTAGC

TAGTAGGTGGGGTAATGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGAGAGG

ATGACCAGCCACACTGGAACTGAGACACGGTCCAGACTCCTACGGGAGGCAGCA

GTGGGGAATATTGCACAATGGGCGCAAGCCCTGATGCAGCCATGCCGCGTGTAT

GAAGAAGGCCTTCGGGTTTGTAAAGTACTTTCAGCGAGGAGGAAGGCGTTAAGG

TTAATAACCTTGGCGATTGACGTTACTCGCAGAAGAAGCACCGGCTAACTCCGTG

CCAGCAGCCGCGGTAATACGGAGGGTGCAAGCGTTAATCGGAATTACTGGGCGT

AAAGCGCACGCAGGCGGTCTGTCAAGTTCGGATGTTGAAATCCCCGGGGCTCAA

CCTGGGAACTGCATTCTGAAACTGGGCAGGCTAGAGTCCTTGTAGAGGGGGGGG

ATAGAACTTCTCAGGTTGATAGCGGCTGAAATGCGTTAGAGATCTGGGAGGAAT

TACCCGGTTTGGCGAAGGCGGCCCCTCTTGGACAAAGACTGACGCTCATGGTGC

GAAATGCCCGTGGGGATGCCAAACAGGATTAGATACTCCTCTGCAATTCGAAAC

TTGGCAGGCCTAGAAGTTCTTGTAGAAGGGGGGGTAGAAATTCCAGGTGGTAGC

Chapter 4 Results

214

GGTGAAATGCGTAGAGGATCTGGAGGAATACCGGTGGCGAAGGCGGCCCCCTGG

ACAAAGACTGACGCTCAGGTGCGAAAGCGTGGGGAGCAAACAGGATTAGATAC

CCTGGTAGTCCACGCCGTAAACGATGTCGACTTGGAGGTTGTGCCCTTGAGGCGT

GGCTTCCGGAGCTAACGCGTTAAGTCGACCGCCTGGGGAGTACGGCCGCAAGGT

TAAAACTCAAATGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTA

ATTCGATGCAACGCGAAGAACCTTACCTACTCTTGACATCCAGAGAACTTAGCA

GAGATGCTTTGGTGCCTTCGGGAACTCTGAGACAGGTGCTGCATGGCTGTCGTCA

GCTCGTGTTGTGAAATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATCCTT

TGTTGCCAGCGGTCCGGCCGGGAACTCAAAGGAGACTGCCAGTGATAAACTGGA

GGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGAGTAGGGCTACACAC

GTGCTACAATGGCATATACAAAGAGAAGCGACCTCGCGAGAGCAAGCGGACCTC

ATAAAGTATGTCGTAGTCCGGATTGGAGTCTGCAACTCGACTCCATGAAGTCGG

AATCGCTAGTAATCGTAGATCAGAATGCTACGGTGAATACGTTCCCGGGCCTTGT

ACACACCGCCCGTCACACCATGGGAGTGGGTTGCAAAAGAAGTAGGTAGCTTAA

CCTTCGGGAGGGCGCTTACCAACTTTGTGATTCAAAAAAAATG

CLM4-10

TGGGCGGGCAGGCCTAACACATGCAAGTCGAACGGTAGCACATAGGAGCTTGCT

CCTTGGGTGACGAGTGGCGGACGGGTGAGTAATGTCTGGGAAACTGCCCGATGG

AGGGGGATAACTACTGGAAACGGTAGCTAATACCGCATAACGTCGCAAGACCAA

AGAGGGGGACCTTCGGGCCTCTTGCCATCGGATGTGCCCAGATGGGATTAGCTA

GTAGGTGGGGTAACGGCTCACCTAGGCGACGATCCCTAGCTGGTCTGAGAGGAT

GACCAGCCACACTGGAACTGAGACACTGTCCAGACTCCTACGGGAGGCAGCAGT

GGGGAATATTTGCACAATGGGCGCAAGCCTGATGCAGCCATGCCGCGTGTATGA

AGAAGGCCTTCAGACTGACGCTCAGGTGCGAAAGCTTGGGGACCAAACAGGATT

AGATACCCTGGTAGTCCACGCCGTAAACGATGTCGACTTGGAGGTTGTGCCCTTG

ACGCGTGGCTTCCTGAGCTAACGCGTTAAGTCGACCGCCTGGGGAGTACGGCCG

CAAGGTTAAAACTCAAATGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGT

GGTTTAATTCGATGCAACGCGAAGAACCTTACCTACTCTTGACATCCAGAGAACT

TAGCAGAGATGCTTTGGTGCCTTCGGGAACTCTGAGACAGGTGCTGCATGGCTGT

CGTCAGCTCGTGTTGTGAAATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTA

TCCTTTGTTGCCAGCGGTTCGGCCGGGAACTCAAAGGAGACTGCCAGTGATAAA

CTGGAGGAAGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGAGTAGGGCTA

CACACGTGCTACAATGGCATATACAAAGAGAAGCGACCTCGCGAGAGCAAGCG

GACCTCATAAAGTATGTCGTAGTCCGGATTGGAGTCTGCAACTCGACTCCATGAA

GTCGGAATCGCTAGTAATCGTGGATCAGAATGCCACGGTGAATACGTTCCCGGG

CCTTGTACACACCGCCCGTCACACCATGGGAGTGGGTTGCAAAAGAAGTAGGTA

GCTTAACCTTCGTTAGAGCTCTACTATTTGTTTTACCCGCGTAAA

DHR8-2

ACCTTTTGTGAGACTGCTTTATTGTAGTTTAAGACACGGAGCGGATGCGCGACCT

GTGGGTAACCTACCCATAAGACTGGGATAACTCCGGGAAACCGGGGCTAATACC

GGATAATATTTTGAACTGCATAGTTCGAAATTGAAAGGCGGCTTCGGCTGTCACT

TATGGATGGACCCGCGTCGCATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGG

CGACGATGCGTAGCCGACCTGAGAGGGTGATCGGCCACACTGGGACTGAGACAC

GGCCCAGACTCCTACGGGAGGCAGCAGTAGGGGATCTTCCGCAATGGACGAAAG

TCTGACGGAGCAACGCCGCGTGAGTGATGAAGGCTTTCGGGTCGTAAAACTCTG

Chapter 4 Results

215

TTGTTAGGGAAGAACAAGTGCTAGTTGAATAAGCTGGCACCTTGACGGTACCTA

ACCAGAAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGTGGC

AAGCGTTATCCGGAATTATTGGGCGTAAAGCGCGCGCAGGTGGTTTCTTAAGTCT

GATGTGAAAGCCCACGGCTCAACCGTGGAGGGTCATTGGAAACTGGGAGACTTG

AGTGCAGAAGAGGAAAGTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGATA

TGGAGGAACACCAGTGGCGAAGGCGACTTTCTGGTCTGTAACTGACACTGAGGC

GCGAAAGCGTGGGGAGCAAATCGGATTAGATACCCTGGTAGTCCACGCCGTAAA

CGATGAGTGCTAAGTGTTAGAGGGTTTCCGCCCTTTAGTGCTGAAGTTAACGCAT

TAAGCACTCCGCCTGGAATTCCATGTGTAGCGGTGAAATGCGTAGAGAATATGG

AGGAACACCAGTGGCGAAAGCGACTTTCTGTTTCTGTAACTGACACTGAGGCGC

GAAAGCGTGGGGAGCAAACAGGATTAGAATACCCTGGTAGTCCACGCCGTAAAC

GATGAGTGGCTAAAGTGTTAGAGGGTTTCCGCCCATTTAGTGGCCTGGAAGTTAA

ACGGCAATTAAGGCACTCCGCCCTGGGGAGTAACCGGCCGGCAAGGCTGAAACT

CAAAAGGAAATTGACCGGGGGCCCCGCACAAGCGGTGGAGCATGTGGTTTAATT

CGAAGCAAACGCGAAGAAACCTTACCAGGTCTTGACATCCTCTGACAACCCTAG

AGATAGAGCTTCTCCTTCGGGAGCAGAGTGACAGGTGGTGCATGGTTGTCGTCA

GCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGATCTT

AGTTGCCATCATTAAGTTGGGCACTCTAAGGTGACTGCCGGTGACAAACCGGAG

GAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACG

TGCTACAATGGACGGTACAAAGAGCTGCAAGACCGCGAGGTGGAGCTAATCTCA

TAAAACCGTTCTCAGTTCGGATTGTAGGCTGCAACTCGCCTACATGAAGCTGGAA

TCGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTAC

ACACCGCCCGTCACACCACGAGAGTTTGTAACACCCGAAGTCGGAGAGGATGAT

CAGGGTCCAGATTGTACCGTAGGGAGTCGGACCCCAGA

DHT9-1

GGGGGGCGGCCTAATACTGCAGTCGAGCGGTTGCATGGGAGCTTGGTCCTCTGG

GTGACCGGCGCAGACGGGTGTGTATGTCTGGGCCTGGCCTGATGGTGGGGTATC

TCCGGGGACCGGGGCTTTTACCGATTACCGTCTTCACCGCATGGATGGGGACCTT

CGGCCCTCTTGCCCTGTCATTTGCCGATAGAGCATTATCTAATTAGCTAGGTAGT

GACTCACCTGCTCAACGATGCAACGATGGTCTGAGGAGATGACAGGCCGATCTG

CCACTGAGACACTGACCCACCTCCTACAGTCCGACGGAAGGCAGCATATTGCAA

TCTGCGCCCATGCATGATGCTCTCATGCAGCGTGTATGAGTAAGGCCTGCAGGCT

GTCAAGTCGTTTCACTCTGTAGTAAGGCAAGATCATTTATTACCTCAATGATTGA

CCTCCCTCACAGAACATGCACCGAATGACTCCGTTACATACGTCCCAGCAATCCC

GATGGTACATACGTGGATAGCATTTTCTGGAATTAATGCGCATAAAGGCCGCCTA

TCTAGTCTGATGTGACTGATGTGAACTCCCCTGCTCACTCCTTTAGAGTCTTTGAA

GACTAGAGTCTACGTAAAGTGCGGATAGAAAATACGTGGAATTACCATGTTGAT

ATGCGTGAATTCTTGGAAGAAATTCCGAGGTAGCCCAGTGGCCCACGTCGACTTT

ACTCGTTATGCTAACTGACCTAAAGCTCGGGAAGCTAGCGGGAATTAAACTGCC

TGATATCCCTAGTCAGTCACGACTGTCAACTTATGAGTGTCGTATCTCTTTGAAG

GAGTGTCTCCGTTAATAGAAGAGGTCTATAGGGAGGCTGGAATCATGTGAAATG

CGTAGAGATCTGGAGGAATACCGGTGGCGAAAGGCGGCCCCTGGACATAGACCT

GACGCTCAGGTGCGAAAGCGTGGGTAGCAAACAGGATTAGATACCCTGGTAAGT

CCACGCCGTAAACGAATGTCGACATTGGAGGTTGTTCCCTTCGAGGACGTGGCAT

TCCGGAGCTAACGCGTTAAGTCGATCCGCCTGGGGAGTACGGCCGCAAGGTTAA

AACTCAAATGAATTGACGGGGGCCCGCACAAGCGGTGGAGCATGTGGTTTAATT

CGATGCAACGCGAAGAACCTTACCTACTCTTGACATCCACAGAATTCGGCAGAG

Chapter 4 Results

216

ATACCTTAGTGCCTTCGGGAACTCTGAGACAGGTGCTGCATGGCTGTCGTCAGCT

CGTGTTGTGAAATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATCCTTTGT

TGCCAGCGGTTCGGCCGGGAACTCAAAGGAGACTGCCAGTGATAAACTGGAGGA

AGGTGGGGATGACGTCAAGTCATCATGGCCCTTACGAGTAGGGCTACACACGTG

CTACAATGGCGCATACAAAGAGAAGCGACCTCGCGAGAGCAAGCGGACCTCAT

AAAGTGCGTCGTAGTCCGGATCGGAGTCTGCAACTCGACTCCGTGAAGTCGGAA

TCGCTAGTAATCGTAGATCAGAATGCTACGGTGAATACGTTCCCGGGCCTTGTAC

ACACCGCCCGTCACACCATGGGAGTGGGTTGCAAAAGAAGTAGGTAGCTTAACC

TTCGGGAGGGCGCTCCTAAGGGGGACCAAAAAAAGG

DLT8-1

CCACTAGGCGGCGTGCCTAATACATGCAAGTCGAGCGGACTTATAAAGCTTGCTT

TTTAAGTTAGCGGCGGACGGGTGAGTAACACGTGGGCAACCTGCCTGTAAGACT

GGGATAACTTCGGGAAACCGGAGCTAATACCGGATAATCCTTTTCTACTCATGTA

GAGAAGTCTGAAAGACGGCATCACGCTGTCACTTACAGATGGGCCCGCGGCGCA

TTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCGACGATGCGTAGCCGACCTG

AGAGGGTGATCGGCCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAG

GCAGCAGTAGGGAATCTTCCGCAATGGACGAAAGTCTGACGGAGCAACGCCGCG

TGAGTGATGAAGGTTTTCGGATCGTAAAACTCTGTTGTTAGGGAAGAATAAGTAT

GAGAGTAACTGCTCGTACCTTGACGGTACCTAACCAGAAAGCCACGGCTAACTA

CGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTTGTCCGGAATTTATTG

GGCGTAAAGCGCGCGCAGGCGGTCCTTTAAGTCTGATGTGAAAGCCCACGGCTC

AACCGTGGAGGGTCATTGGAAACTGGGGGACTTGGAGTGCAGAAGAGAAGAGT

TGGAATTCCACGTGTAGCGGTGAAATGCGTAGAGATGTGGGAGGAACACCAGTG

GGCGAAGGCGACTCTCTTTTGGTCTGTAACTGACGCTGAGGAGCGTCAGAAAAG

TCGTTGGGGCAGGCAAAAGCAAGGCATTAAGATACCCTTGGGTTATGTTCCCAA

CGCCCGTTAAACGAATGAATGTGCTTAAGTGGTTAAGAGGGGTTTCCCGCTCCTT

TAGTTGCTGCAAGCAAAACGCATTCAAGCAACTCCAGCCATGGGGAAGTAACGG

TCCGCAAAGGCTGAAAACTCACAAAGAGAATTGAACGGGGGCCCGCACCAAGC

CGGTTGGAGCATGTGGGTTTAATTCGAAGCAACGCGAAAGAACCTTACCAGGTC

TTGACATCTCCTGACAATCCTAGAGATAGGACGTTCCCCTTCGGGGGACAGGGTG

ACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCC

GCAACGAGCCGCAACCCTTGATCTTAGTTGCCAGCATTCAGTTGGGCACTCTAAG

GTGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGC

CCCTTATGACCTGGGCTACACACGTGCTACAATGGATGGTACAAAGGGCAGCAA

AACCGCGAGGTCGAGCAAATCCCATAAAACCATTCTCAGTTCGGATTGTAGGCT

GCAACTCGCCTACATGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCCGC

GGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCACGAGAGTTTGT

AACACCCGAAGTCGGTGGGGTAACCTTTTTGGAGCCAGCCGCCTAAGGTGGGAT

AGATGAATTGG

Chapter 4 Results

217

16S rDNA nucleotide sequences BLAST showed homology with twelve bacterial genera i.e.,

Aeromonas, Bacillus, Oceanimonas, Obesumbacterium, Buttiauxella, Enterobacter,

Exiguobacterium, Klebsiella, Serratia, Raoultella, Citrobacter and Achromobacter. Twenty

one isolates showed homology with Bacillus, Eight with Aeromonas, four with Buttiauxella.

While the genera Klebsiella, Obesumbacterium and Raoultella were represented by two

isolates/genus. One of the isolates showed comparable levels of relatedness on the bases of

16S rDNA BLAST with each genera Oceanimonas, Enterobacter, Exiguobacterium,

Serratia, Citrobacter and Achromobacter (Table 4.26). All the Bacillus and Aeromonas

members expressed positive amylase, cellulase and protease activities. While Buttiauxella

and Obesumbacterium showed results of negative amylase, cellulose and protease tests

(Table 4.24).

Chapter 4 Results

218

Table 4.26 Relatedness of the nucleotides sequences of the subject isolates with classified bacteria on the bases of 16S rDNA blast

homology.

Sr No. Isolate

Code

Accession

Query ID Description Total

Score

Max.

Ident.

1. AHR8-5 NR 044845.1 lcl|3969 Aeromonas veronii 16S ribosomal RNA, complete

sequence

2455 97 %

2. AHR4-1 NR 025241.1 lcl|41525 Bacillus aquimaris strain TF-12 16S ribosomal RNA,

partial sequence

2351 96 %

3. BHR7-2 NR 074844.1 lcl|31601 Aeromonas salmonicida subsp. salmonicida A449 strain

A449 16S ribosomal RNA, complete sequence

2672 99 %

4. BLR6-1 NR. 043638.1

lcl|35299 Aeromonas hydrophila strain CCM 7232; ATCC 7966

16S ribosomal RNA, complete sequence

2564 99 %

5. BHM1-1 NR 041794.1 lcl|38617 Bacillus safensis strain FO-036b 16S ribosomal RNA,

partial sequence

2527 98 %

6. BLM4-1 NR 036911.2 lcl|60291 Aeromonas media strain RM 16S ribosomal RNA,

partial sequence

2617 99 %

7. BLM5-1 NR 102783.1 lcl|27303 Bacillus subtilis subsp. subtilis str. 168 strain 168 16S

ribosomal RNA, complete sequence

2628 99 %

8. CHM5-2 NR 025295.1 lcl|28561 Aeromonas salmonicida subsp. smithia strain AS20/1/1

16S ribosomal RNA, partial sequence

2529 98 %

9. CHT9-1 NR 075005.1 lcl|2177 Bacillus amyloliquefaciens FZB42 strain FZB42 16S


2556 99 %

10. CHT3-2 NR 025334.1 lcl|46625 Obesumbacterium proteus strain 42 16S ribosomal

RNA, partial sequence

2635 98 %

11. CLT3-1 NR 074453.1 lcl|64129 Bacillus anthracis str. Ames strain Ames 16S ribosomal

RNA, complete sequence

2482 98 %

12. DHR1-1 NR 036919.1 lcl|18105 Buttiauxella noackiae strain NSW 11 16S ribosomal


1547 97 %

Continued…………

http://www.ncbi.nlm.nih.gov/nucleotide/343206253?report=genbank&log$=nucltop&blast_rank=1&RID=XKZS0DN801S

http://www.ncbi.nlm.nih.gov/nucleotide/219857652?report=genbank&log$=nucltop&blast_rank=1&RID=XM04X8XD01N

Chapter 4 Results

219

Sr No. Isolate

Code

Accession


Score

Max.

Ident.

13. DHR5-3 NR 026089.1 lcl|30967 Aeromonas bestiarum strain CIP 7430 16S ribosomal


2716 99 %

14. DHR2-2 NR 074540.1 lcl|33319 Bacillus cereus ATCC 14579 strain ATCC 14579 16S


2532 98 %

15. DHT6-1 NR 075005.1 lcl|34107 Bacillus amyloliquefaciens FZB42 strain FZB42 16S


2724 99 %

16. DLT5-1 NR 102493.1 lcl|48987 Enterobacter aerogenes KCTC 2190 strain KCTC 2190


2716 99 %

17. DLR3-1 NR 042638.1 lcl|37517 [Brevibacterium] halotolerans strain DSM 8802 16S


2713 99 %

18. AHM3-1 EF210291

lcl|39675 Bacillus thuringiensis serovar finitimus strain BGSC

4B2 16S ribosomal RNA gene, partial sequence

2476 98 %

19. ALM9-1 NR 042424.1 lcl|17013 Exiguobacterium mexicanum strain 8N 16S ribosomal


2409 98 %

20. AHT5-5 NR 024691.1 lcl|18835 Bacillus flexus strain IFO15715 16S ribosomal RNA,

partial sequence

2722 99 %

21. BHT3-1 NR 026089.1 lcl|34849 Aeromonas bestiarum strain CIP 7430 16S ribosomal


2510 98 %

22. CHR3-1 NR 074453.1 lcl|1151 Bacillus anthracis str. Ames strain Ames 16S ribosomal


2543 98 %

23. DHR1-5 NR 043885.1 lcl|48119 Aeromonas bivalvium strain 868E 16S ribosomal RNA,

partial sequence

2544 98 %

24. DHR6-4 NR 074977.1 lcl|64753 Bacillus pumilus SAFR-032 strain SAFR-032 16S


2958 98 %

25. DHM5-1 NR 074540.1 lcl|57597 Bacillus cereus ATCC 14579 strain ATCC 14579 16S


2969 98 %

26. DLM3-1 NR 075016.1 lcl|65307 Bacillus atrophaeus 1942 strain 1942 16S ribosomal


3099 99 %

http://www.ncbi.nlm.nih.gov/nucleotide/219856872?report=genbank&log$=nucltop&blast_rank=1&RID=XM0JWWMU01S

Chapter 4 Results

220

Continued…………

Sr No. Isolate

Code

Accession


Score

Max.

Ident.

27. DLR1-5 NR 040852.1 lcl|21237 Bacillus horikoshii strain DSM8719 16S ribosomal


2790 98 %

28. DLR1-3 NR 074290.1 lcl|711 Bacillus megaterium QM B1551 strain QM B1551 16S


1987 99 %

29. AHR7-5 NR 025945.2 lcl|20523 Aeromonas allosaccharophila strain CECT 4199 16S

ribosomal RNA, partial sequence

2942 99 %

30. AHT3-2 NR 028682.1 lcl|2329 Granulicatella elegans ATCC 700633 strain B1333 16S


1282 96 %

31. BHT6-1 NR 1/2982.1 lcl|11363 Klebsiella oxytoca KCTC 1686 strain KCTC 1686 16S


3167 99 %

32. CHR3-1 NR 037112.1 lcl|59525 Serratia proteamaculans strain 4364 16S ribosomal


3178 99 %

33. CHM7-1 NR 024696.1 lcl|50711 Bacillus vallismortis strain DSM11031 16S ribosomal


2412 98 %

34. CLM4-1 NR 074923.1 lcl|13511 Bacillus licheniformis DSM 13 = ATCC 14580 strain

ATCC 14580; DSM 13 16S ribosomal RNA, complete

sequence

316/ 99 %

35. CHT2-2 NR 102983.1 lcl|62021 Raoultella ornithinolytica B6 strain B6 16S ribosomal


3100 99 %

36. DHR4-2 NR 025328.1 lcl|65519 Buttiauxella brennerae strain S1/6-571 16S ribosomal


1513 99 %

37. DHR5-1 NR 025334.1 lcl|55203 Obesumbacterium proteus strain 42 16S ribosomal


3063 100 %

38. DHT3-1 NR 102982.1 lcl|42073 Klebsiella oxytoca KCTC 1686 strain KCTC 1686 16S


3136 99 %

39. DLR10-1 NR 042021.1 lcl|24351 Achromobacter denitrificans strain DSM 30026 16S


2530 99 %

40. AHM4-1 NR 041968.1 lcl|42179 Buttiauxella agrestis ATCC 33320 strain DSM 4586

16S ribosomal RNA, partial sequence

2888 99 %

41. BLR6-10 NR 044799.1 lcl|11805 Enterobacter aerogenes KCTC 2190 strain KCTC 2190


2772 99 %

Chapter 4 Results

221

Sr No. Isolate

Code

Accession


Score

Max.

Ident.

42. CLM4-10 NR 028894.1 lcl|28165 Citrobacter freundii strain DSM 30039 16S ribosomal


1976 99 %

43. DHR8-2 NR 074926.1 lcl|60641 Bacillus weihenstephanensis KBAB4 strain KBAB4


2711 99 %

44. DHT9-1 NR 025329.1 lcl|62415 Buttiauxella ferragutiae strain DSM 9390 16S

ribosomal RNA, partial sequence

1380 99 %

45. DLT8-1 NR 044546.1 lcl|4051 Bacillus nealsonii strain DSM 15077 16S ribosomal


2377 96 %

Chapter 4 Results

222

4.6 Metals analyses of water, river bed sediments and different organs/tissues of the

fishes:

4.6.1 Metals concentration of the river water samples:

Table 4.26 shows that mean heavy metals’ concentrations were highly significant

(P<0.001) different for waters sampled from different sites and flow seasons. All metals’

concentration increased up to site C, and then they not only, stabilized in water sampled

from site D rather showed a small recovery as compared to third study location. Levels of

cadmium (0.14 mg/l), chromium (5.24 mg/l), copper (4.41 mg/l), iron (51.48 mg/l), lead

(2.04 mg/l), zinc (41.48 mg/l), manganese (10.12 mg/l), nickel (3.18 mg/l) and mercury

(2.11 mg/l) concentrations were highest at site C than the corresponding values of 0.03,

1.01, 2.68, 30.20, 0.15, 11.81, 2.25, 0.39 and 0.13 mg/l obtained for the water sampled

from site A (table 4.27). The trend of the metals’ concentration was significantly higher

during low flow than high flow seasons. When data of concentration of the metals for the

waters sampled from the different sampling sites and during flow seasons were pooled up

it appeared that the cadmium content varied between 0.07 to 0.10, chromium from 2.26 to

3.71, copper from 3.38 to 3.77, iron from 37.01 to 42.53, lead from 0.94 to 1.14, zinc

from 22.12 to 25.16, manganese from 4.29 to 6.52, nickel from1.20 to 1.53 and mercury

from 0.87 to 1.19 mg/l from low flow to high flow season (table 4.28).

The mean heavy metals concentrations with their significances for site x season

interaction are presented in table 4.27. All metals’ concentrations significantly differed at

different sampling sites in different flow seasons. All metals’ concentrations were higher

than respective National Environmental Quality Standards (NEQS) proposed limits for

each metal. Following is a metal wise brief account of the river waters sampled from the

different alongstream sites and flow seasons.

Chapter 4 Results

223

4. 6.1.1 Cadmium:

Cadmium content of the river water measured as 0.03 mg/l during low flow and

0.02 mg/l during high flow season at site A, which increased up to 167, 467 and 334 %

during low flow and 200, 450 and 300 % during high flow at site B, C and D, respectively

(Fig. 4.43). However, cadmium concentrations appeared, in general, below the NEQS

recommended limit (0.1 mg/l), except for waters sampled from sites C and D. Water of

site C showed 41 and 9 % higer Cd contents than NEQS recommended limit (0.1 mg/l)

during low and high flow seasons, respectively. While water of site D expressed 23

%increased level of the metal during low flow season and during high flow, the value of

metal fell within NEQS limit (0.1 mg/l).

4. 6.1.2 Chromium:

Chromium concentrations were found as 1.13 mg/l and 0.89 mg/l at sit A which

increased up to 122 and 162 % at site B, 545 and 258 % at site C and 244 and 197 % at

site D during low and high flow season respectively (Fig. 4.43). Water samples of the

sites A, B, C and D during low flow season showed 12, 60, 86 and 74 % higher than

NEQS recommended limit (1.0 mg/l). While water samples showed 57, 69 and 62 % at

site B, C and D higher than NEQS recommended limit (1.0 mg/l) during high flow

seasons, respectively.

4. 6.1.3 Copper:

Copper concentrations appeared up to 64, 72, 79 and 75 % during low flow and

62, 69, 75 and 73 % during high flow in water sampled from sites A, B, C and D,

respectively in comparison with NEQS recommended value (1.0 mg/l). Copper

concentrations were 2.76 mg/l and 2.61 mg/l at site A which increased up to 27.54 and

21.46 % at site B, 73.19, 55.17 % at site C and 45.65 and 41.76 % at site D for waters

sampled during low and high flow season, respectively (Fig. 4.43).

Chapter 4 Results

224

4.6.1.4 Iron:

Iron contents increased up to 14, 59 and 42 % and 20, 85 and 37 % at sites B, C

and D, respectively as compared with corresponding values of 33.06 mg/l and 27.33 mg/l

for waters sampled from site A during low and high flow seasons, respectively (Fig.

4.43). Water iron concentrations were 94 and 93 % at site A, 95 and 94 % at site B, 96

and 96 % at site C and 96 and 95 % at site D higher than NEQS proposed value of 2.0

mg/l.

4.6.1.5 Lead:

Lead concentrations for waters sampled at the site A during low and high flow

seasons were 0.18 mg/l and 0.13 mg/l, respectively. The metal contents increases up to

350 and 423 % at site B, 1144 and 1308 % at site C and 644 and 769 %, at site D during

low and high flow seasons, respectively when compared with corresponding Pb levels of

the water sampled from site A (Fig. 4.43). The Pb concentration fell within NEQS limit

(0.5 mg/l) only upstream at site A. The river waters sampled from sites B, C and D during

low and high flow seasons had 38 and 27 % at site B, 77 and 73 % at site C and 63 and 56

% at site D higher Pb contents respectively than the corresponding value of NEQS (0.5

mg/l).

4.6 .1.6 Zinc:

Zinc contents of the water samples appeared up to 60, 68, 89 and 83 % higher

during low flow and 55, 64, 87 and 79 % higher during high flow seasons at sites A, B, C

and D, respectively than recommended NEQS value (5 mg/l). The metals contents were

25,252 and 135 % and 24, 251 and 114 % during low and high flow season, respectively

at site B, C and D, respectively in comparison with corresponding values of 12.40 mg/l

and 11.22 mg/l for the site A (Fig. 4.43).

4. 6.1.7 Manganese:

Manganese concentrations in waters sampled from site A were found as 1.49 mg/l

and 1.44 mg/l during low and high flow seasons, respectively. . These concentrations

Chapter 4 Results

225

increased up to 60 and 24 % at site B, 502 and 195 % at site C, 182 and 158 % at site D

during low and high flow seasons of the river, respectively (Fig. 4.43). The manganese

contents appeared higher than NEQS value (1.5 mg/l) upto 34, 59, 89 and 77 % during

low flow for the sampling site A, B, C and D and 32, 45, 77 and 74 % during high flow

season, for the sampling site A, B, C and D respectively.

4.6.1.8 Nickel:

Nickel concentrations were 0.44 mg/l and 0.35 mg/l of the river waters at site A,

which increased up to 25, 716 and 250 % during low flow and 46, 691 and 234 % during

high flow seasons at site B, C and D respectively (Fig. 4.43). Nickel contents of waters

sampled from sites A and B fell within range of NEQS limit (1.0 mg/l), while those

sampled from sites C and D which attained 72 and 35 % during low flow and 63 and 15

% during high flow seasons as compared to the NEQS value (1.0 mg/l).

4. 6.1.9 Mercury:

Mercury concentration of waters sampled from sites B, C and D were much higher

than the values for the upstream site A as well as NEQS limit. The highest increase was

observed at site C. The metal concentration measured as 0.14 mg/l and 0.12 mg/l at site A

which increased up to 107 and 25 % at site B, 1700 and 1317 % at site C and 1185 and

1177 % at site D during low and high flow seasons, respectively (Fig. 4.43). Mercury

concentrations appeared 93 and 92 % at site A, 97 and 93 % at site B, 100 and 99 % at

site C and 99 and 99 at site D higher during low and high flow season, respectively than

the NEQS recommended value (0.01 mg/l).

Chapter 4 Results

226

Table 4.27 Mean concentrations (mg/l) of heavy metals in waters samples for alongstream locations and flow seasons with standard

error of means and significance. Trace metals in water Cd Cr Cu Fe Pb Zn Mn Ni Hg

Sampling sites

Site A: Siphon (Control) 0.03d

1.01d

2.68d

30.20d

0.15d

11.81d

2.25d 0.39

d 0.13

d


2.42c

3.35c 35.26

c 0.75

c 14.68

c 3.19

c 0.53

c 0.22

c


5.24a

4.41a

51.48a

2.04a

41.48a

10.12a

3.18a

2.11a


3.27b

3.86b

42.14b

1.24b

26.58b

6.06b 1.35

b 1.66

b

SEM and Significance 0.002*** 0.036*** 0.023*** 0.563*** 0.023*** 0.422*** 0.224*** 0.022*** 0.017***

Seasons

High 0.07 b

2.26 b

3.38b

37.01b

0.94b

22.12b

4.29b 1.20

b 0.87

b

Low 0.10a

3.71a 3.77

a 42.53

a 1.14

a 25.16

a 6.52

a 1.53

a 1.19

a




Chapter 4 Results

227

Table 4.28 Mean concentration (mg/l) of heavy metals in waters sampled from different alongstream locations (Siphon (upstream

=A); Shahdera =B; Sunder =C; and Head balloki =D) during low and high flow seasons of the river.

Sites

Seasons

A B C D

Low High Low High Low high Low High SEM With Significance

Heavy metals in Water

Cd 0.03f

0.02f

0.08d

0.06e

0.17a

0.11c

0.13b 0.08

d 0.003***

Cr 1.13f

0.89f

2.51de

2.33e

7.29a

3.19c 3.89

b 2.64

d 0.052***

Cu 2.76f

2.61f

3.52d 3.17

e 4.78

a 4.05

b 4.02

b 3.70

c 0.032***

Fe 33.06d

27.33e

37.66c

32.85d

52.50a

50.46ab

46.89b

37.40c 0.796**

Pb 0.18f 0.13

f 0.81

e 0.68

e 2.24

a 1.83

b 1.34

c 1.13

d 0.032***

Zn 12.40f

11.22f

15.50e

13.86ef 43.62

a 39.34

b 29.12

c 24.04

d 0.597*

Mn 2.28c

2.21c

3.64c 2.74

c 13.72

a 6.51

b 6.43

b 5.70

b 0.316***

Ni 0.44ef

0.35f

0.55e 0.51

e 3.59

a 2.77

b 1.54

c 1.17

d 0.031***

Hg 0.14e

0.12e

0.29d

0.15e 2.52

a 1.70

b 1.80

b 1.52

c 0.024***

Values within the same rows earmarked with same superscripts did not differ significantly from each other (P>0.05)


Chapter 4 Results

228

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Cad

miu

m

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B C D

Sampling Sites

Ch

rom

ium

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Sampling Sites

Co

pp

er

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Iro

n

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Lead

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Zin

c

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Chapter 4 Results

229

0%

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B C DSampling Sites

Mag

nes

e

Low Flow High Flow

0%

150%

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450%

600%

750%

B C D

Sampling Sites

Nic

kel

Low Flow High Flow

0%

500%

1000%

1500%

2000%

B C D

Sampling Sites

Merc

ury

Low Flow High Flow

Fig. 4.43 Percent increase of heave metal contents of waters sampled from

downstream sites (Shahdera =B; Sunder =C; and balloki =D) from the

corresponding values of water sampled from upstream site A (Siphon =control)


Chapter 4 Results

230

4.6.2 Metals concentrations in the river bed sediments:

Heavy metal concentrations worked out as mg/Kg of dried sediment differed

significant (P<0.001) in the river bed’s sediments sampled from different sites and during

high and low flow seasons. All the analyzed metals’ concentration increased up to site C,

and then, more or less, stabilized for the sediment sampled at site D. The metals’

concentrations appeared significantly higher during low flow than high flow season at all

the sites (table 4.29). Mean cadmium (2.00 mg/kg), chromium (54.28 mg/kg), copper

(68.85 mg/kg), iron (369.32 mg/kg), lead (5.33 mg/kg), zinc (351.54 mg/kg), manganese

(105.59 mg/kg), nickel (28.50 mg/kg) and mercury (17.94 mg/kg) concentrations were

highest at site C than (0.20, 0.57 and 1.16 mg/kg), (10.91, 28.73 and 43.37 mg/kg),

(17.16, 36.54 and 50.27 mg/kg), (100.12, 177.07 and 255.49 mg/kg), (0.89, 1.63 and 2.68

mg/kg), (141.74, 176.17 and 233.43 mg/kg), (15.30, 27.99 and 62.32 mg/kg), (2.96, 5.56

and 19.95 mg/kg) and (1.07, 2.03 and 13.68 mg/kg) respectively at site A, B and D

respectively (table 4.29).

During flow seasons, the cadmium content ranged from 1.13 to 0.84 mg/kg,

chromium from 39.35 to 29.29 mg/kg, copper from 46.70 to 39.71 mg/kg, iron from

239.01 to 211.98 mg/kg, lead from 2.88 to 2.38 mg/kg, zinc from 245.14 to 206.30

mg/kg, manganese from 63.35 to 42.26 mg/kg, nickel from 15.88 to 12.61 mg/kg and

mercury from 9.89 to 7.47 mg/kg during low flow to high flow seasons of river Ravi

(table 4.29).

The mean heavy metals concentration with their significance (site x season

interaction) were presented in table 4.30. All metals concentrations were significantly

different in different sampling sites in different flow season except iron.

Following is a brief metal wise account of the river of bed sediment samples

representing four along stream sites and the low and high flow seasons of the river

Chapter 4 Results

231

4.6.2.1 Cadmium:

Cadmium content measured as 0.23 mg/kg during low flow and 0.17 mg/kg

during high flow at site A, which increased up to 191, 917 and 457 % during low flow

and 182, 877 and 512 % during high flow seasons at the sites B, C and D, respectively

(Fig. 4.44).

4.6.2.2 Chromium:

Mean chromium concentrations were 12.12 and 9.70 mg/kg at sit A during low

and high flow seasons, respectively. The metals contents increased up to 165 and 161 %

at site B, 461 and 319 % at site C and 273 and 329 % at site D during low and high flow

seasons, respectively (Fig. 4.44).

4.6.2.3 Copper:

Copper concentrations were 18.37 and 15.95 mg/kg at site A which increased up

to 119 and 106 %, 300 and 303 % and 198 and 187 % at site B, C and D during low and

high flow seasons, respectively (Fig. 4.44).

4.6.2.4 Iron:

Iron concentrations fluctuated from 91.85 to 384.15 mg/kg of the river bed

sediment. Its concentration varied between 108.39 and 91.85 mg/kg at site A, between

189.86 and 164.27 mg/kg at site B, between 384.15 and 354.48 mg/kg at site C and

between 273.65 and 237.33 mg/kg at site D during low and high flow seasons,

respectively. Iron contents increased 75, 254 and 153 % and 79, 286 and 158 % at sites B,

C and D in comparison with respective values for the upstream site A during low and

high flow respectively (table 4.29, Fig. 4.44).

4.6.2.5 Lead:

The lead concentrations were lowest at the site A both during low and high flow

seasons with respective values of 1.03 mg/kg and 0.75 mg/kg (table 4.29). The metal

concentrations increased up to 77.67 and 89.33 % at site B. 178.64 and 230.67 % at site C

Chapter 4 Results

232

and 463.11 and 548.00 % at site D during low and high flow seasons, respectively

compared with corresponding values at site A (Fig. 4.44).

4.6.2.6 Zinc:

Zinc concentrations ranged between 134.66 and 402.30 mg/kg of the river bed

dried sediments. Its concentrations varied between 148.82 and 134.66, 186.00 and 166.33,

402.30 and 300.78 and 243.44 and 223.42 mg/kg at downstream sites A, B, C and D

during low and high flow correspondingly. Zinc contents increased 25, 170 and 64 % and

24, 123 and 66 % at sites B, C and D in comparison with respective values for the

upstream site A during low and high flow respectively (table 4.29, Fig. 4.44).

4.6.2.7 Manganese:

Manganese concentration fluctuated between 13.93 to 137.23 mg/kg of the river

bed sediments. The metal concentrations increased up to 100 and 62 % at site B, 723 and

431 % at site C and 297 and 320 % at site D during low and high flow seasons,

respectively as the corresponding values of 16.67 mg/kg and 13.93 mg/kg at site A (Fig.

4.44).

4.6.2.8 Nickel:

Nickel concentrations were 3.27 and 2.65 mg/kg at site A during low and high

flow season, respectively. The metal contents increased up to 80, 853 and 609 % during

low flow and 98, 874 and 531 % during high flow at sites B, C and D respectively (Fig.

4.44).

4.6.2.9 Mercury:

The mercury concentrations of sediment sampled from the site A were 1.12 and

1.02 mg/Kg during low and high flow seasons, respectively. Highest increase in the metal

concentration was observed at site C. Mercury concentrations increased up to 137 and 38

% at site B, 1699 and 1442 % at site C and 1298.21 and 1047.06 % at site D during low

and high flow seasons, respectively when compared with the corresponding values for the

site A mentioned above (Fig. 4.44).

Chapter 4 Results

233

Table 4.29 Mean concentration (mg/kg of dried bed sediment) of heavy metals in sediment with their standard error of means (SEM)

and significance for alongstream locations and flow seasons of the river Ravi.

Trace metals in sediment Cd Cr Cu Fe Pb Zn Mn Ni Hg

Sampling sites

Site A: Siphon (Control) 0.20d 10.91d 17.16d 100.12d 0.89d 141.74d 15.30d 2.96d 1.07d

Site B: Shahdera 0.57c 28.73c 36.54c 177.07c 1.63c 176.17c 27.99c 5.56c 2.03c

Site C: Sunder 2.00a 54.28a 68.85a 369.32a 5.33a 351.54a 105.59a 28.50a 17.94a

Site D: Head Balloki 1.16b 43.37b 50.27b 255.49b 2.68b 233.43b 62.32b 19.95b 13.68b


Seasons

High 0.84b 29.29b 39.71b 211.98b 2.38b 206.30b 42.26b 12.61b 7.47b

Low 1.13a 39.35a 46.70a 239.01a 2.88a 245.14a 63.35a 15.88a 9.89a

SEM and Significance 0.020*** 0.318*** 0.174*** 2.787*** 0.030*** 6.848** 1.715*** 0.254*** 0.164***



Chapter 4 Results

234

Table 4.30 Mean concentration (mg/kg of dried bed sediment) of heavy metals in sediment with their standard error of means (SEM)

and significance sampled from different alongstream locations (Siphon (upstream) =A; Shahdera =B; Sunder =C; and balloki =D)


Sites

Seasons

A B C D

Low High Low High Low High Low High SEM With Significance

Heavy metals in Sediments

Cd 0.23f 0.17f 0.67e 0.48e 2.34a 1.66b 1.28c 1.04d 0.040***

Cr 12.12f 9.70f 32.15d 25.30e 67.94a 40.61c 45.19b 41.56c 0.637***

Cu 18.37g 15.95h 40.22e 32.86f 73.47a 64.24b 54.73c 45.81d 0.348***

Fe 108.39f 91.85f 189.86e 164.27e 384.15a 354.48b 273.65c 237.33d 5.574

Pb 1.03f 0.75f 1.83e 1.42e 5.80a 4.86b 2.87c 2.48d 0.059***

Zn 148.82g 134.66g 186.00e 166.33f 402.30a 300.78b 243.44c 223.42d 13.696*

Mn 16.67e 13.93e 33.40cde 22.59de 137.23a 73.96b 66.10bc 58.55cd 3.429***

Ni 3.27fg 2.65g 5.88e 5.25ef 31.17a 25.82b 23.19c 16.71d 0.507***

Hg 1.12de 1.02e 2.65d 1.41de 20.15a 15.73b 15.66b 11.70c 0.328***



Chapter 4 Results

235

0%

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Cad

miu

m

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Ch

rom

ium

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Copper

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B C DSampling Sites

Iro

n

Low Flow High Flow

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B C DSampling Sites

Lead

Low Flow High Flow

Ti

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300%

B C DSampling Sites

Zin

c

Low Flow High Flow


Chapter 4 Results

236

0%

150%

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450%

600%

750%

900%

B C DSampling Sites

Mag

nese

Low Flow High Flow

0%

200%

400%

600%

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1000%

B C DSampling Sites

Nic

kel

Low Flow High Flow

0%

450%

900%

1350%

1800%

B C DSampling Sites

Merc

ury

Low Flow High Flow

Fig. 4.44 Percent increase of heave metal contents of river bed sediments sampled

from downstream sites (Shahdera =B; Sunder =C; and balloki =D) from the

corresponding values of sediment sampled from upstream site A (Siphon = control)


Chapter 4 Results

237

4.6.3 Bioaccumulation of metals in different organs of the fishes:

Concentrations of Cd, Cr, Cu, Fe, Pb, Zn, Mn, Ni and Hg in dried samples of eyes,

gills, heart, intestine, kidney, liver, scale and skin of the three fish species (Cirrhinus

mrigala, Labeo rohita and Catla catla) sampled from the described sites during low and

high flow seasons of river Ravi were determined with the help of atomic absorption

spectrophotometers while the metal content of muscle tissue of the fishes were measured

by employing Inductively coupled plasma optical emission spectroscopy (ICP-OES). All

the metals’ bioacuumulation differed significantly (P<0.001) When comparison were

made between tissues, fish species, sampling sites and flow seasons (table 4.31). When

the data of all the three fish species were pooled and viewed for the along stream sites, it

appeared that, in general, highest and lowest concentrations of the metals were found for

the site C and A, respectively. While for site B and D had obviously higher metal contents

than the site A. However, different metals depicted differing increasing and decreasing

trends of accumulation for the site B and D (table 4.31). Following is the metal wise

account describing bioaccumulation potential of the different organs/tissues of the

different fish species.

4.6.3.1 Cadmium:

Highest mean cadmium bioaccumulation up to 0.28 mg/kg was found at site C.

Next to the rank appeared the site D, B and A with means Cd contents upto 0.20 mg/Kg,

0.12 mg/kg, 0.07 mg/kg respectively. The Cd contents was found upto 0.19 mg/kg and

0.14 mg/kg during low and high flows (table 4.31). The highest cadmium

bioaccumulation was recorded in L. rohita (0.17 mg/kg) than C. catla (0.15 mg/kg) and

C. mrigala (0.15 mg/kg).Mean accumulation pattern in fishes tissue was in order of:

kidney (0.23 mg/kg) > liver (0.20 mg/kg) > intestine (0.19 mg/kg) > scale (0.17 mg/kg) >

heart (0.16 mg/kg) > eyes (0.15 mg/kg) > skin (0.15 mg/kg) > gills (0.13 mg/kg) (table

4.31).

Chapter 4 Results

238

Mean Cd bioaccumulation in different organs of C. mrigala ranged from 0.06 to

0.13 mg/Kg and 0.03 to 0.08 mg/Kg at site A while accumulation ranged from 0.13 to

0.23 mg/Kg and 0.05 to 0.14 mg/Kg for site B, 0.29 to 0.49 mg/Kg and 0.18 to 0.34

mg/Kg for site C and 0.17 to 0.36 mg/Kg and 0.13 to 0.25 mg/Kg for site D during low

and high flow season respectively (tables 4.32-4.38, Fig. 4.45).

The mean Cd accumulation in different organs ranged from 0.06 to 0.12 mg/kg

and 0.03 to 0.07 mg/kg in L. rohita at site A during low and high flow season

respectively. While the accumulation in L. rohtia ranged from 0.10 to 0.15. mg/kg and

0.08 to 0.13. mg/kg for site B, 0.21 to 0.39 mg/kg and 0.17 to 0.30 mg/kg for site C and

0.15 to 0.27 mg/kg and 0.09 to 0.21 mg/kg for site D during low and high flow season

respectively (tables 4.32-4.38, Fig. 4.54).

The mean bioacummulation ranged from 0.05 to 0.15 mg/kg and 0.03 to 0.11

mg/kg in different organs of C. catla at site A during low and high flow season

respectively (Fig. 4.63). While the Cd accumulation in C. catla corresponding to low and

high flow ranged from 0.09 to 0.21 mg/kg and 0.07 to 0.15 mg/kg for site B, 0.25 to 0.55

mg/kg and 0.16 to 0.32 mg/kg for site C and 0.13 to 0.34 mg/kg and 0.10 to 0.26 mg/kg

for site D (tables 4.32-4.38, Fig. 4.63).

4.6.3.2 Chromium:

Highest mean chromium bioaccumulation up to 5.39 mg/kg was recorded at site

C than site D (3.49 mg/Kg), B (2.83 mg/kg) and A (1.43 mg/kg). Effects of seasons

appeared in the metal contents upto 3.94 mg/kg and 2.63 mg/kg during low and high flow

respectively (table 4.31). The highest chromium accumulation was recorded in C. mrigala

(3.59 mg/kg) than C. catla (3.28 mg/kg) and L. rohita (2.99 mg/Kg). The accumulation

pattern in fish organs/tissues was in order of: kidney (4.16 mg/kg) >Liver (3.87 mg/kg) >

intestine (3.64 mg/kg) > heart (3.52 mg/kg) > scale (3.05 mg/kg) > eyes (3.04 mg/kg) >

skin (2.96 mg/kg) > gills (2.91 mg/kg) (table 4.31).

Chapter 4 Results

239

Mean Cr bioaccumulation in different organs of C. mrigala ranged from 1.23 to

1.98 mg/Kg and 0.98 to 1.58 mg/Kg at site A while, the metal accumulation ranged

between 2.43 -4.17 mg/Kg and 2.03 -3.29 mg/Kg at site B, 6.86 – 10.38 mg/Kg and 3.09 -

5.88 mg/Kg at site C and 4.05-6.77 mg/Kg and 2.48-4.38 mg/Kg at site D during low and

high flow season respectively (tables 4.32-4.38, Fig. 4.46).

The metal accumulation in the organ/tissues of L. rohita showed ranged between

1.33-1.99 mg/Kg and 0.89 - 1.69 mg/Kg at site A while 2.65 - 4.55 mg/Kg and 1.79 - 3.22

mg/Kg for site B, 4.13 -6.63 mg/Kg and 2.99-5.10 mg/Kg for site C and 3.03-5.43 mg/Kg

and 2.31-3.46 mg/Kg for site D during low and high flow season respectively tables 4.32-

4.38, Fig. 4.55).

The mean Cr accumulation in different organs ranged from 1.25 to 2.01 mg/kg

and 1.02 to 1.58 mg/kg in C. catla at site A during low and high flow season respectively.

While the accumulation in C. catla was recorded ranged from 2.57 to 4.41. mg/kg and

2.07 to 3.73. mg/kg for site B, 5.91 to 8.82 mg/kg and 3.26 to 5.56 mg/kg for site C and



4.6.3.3 Copper:

Highest mean copper bioacuumulation up to 8.51 mg/kg was measured at site C.

Then sites B, D and C showed the Cu accumulation in descending order with

corresponding values of 6.85 mg/kg, 6.80 mg/kg and 5.01 mg/kg. The mean low and

high flow season values differ significantly (P<0.001) with corresponding values of 7.18

mg/kg and 6.40 mg/kg (table.4.31). The highest copper bioaccumulation in C. mrigala

(6.84 mg/kg) than C. catla (6.79 mg/kg) and L. rohita (6.74 mg/kg). The accumulation

pattern in fish organs/tissues was in order of kidney (9.06 mg/kg) > liver (8.65 mg/kg) >

intestine (8.30 mg/kg) > heart (6.90 mg/kg) > scale (6.53 mg/kg) > skin (6.20 mg/kg) >

gills (5.70 mg/kg) > eyes (5.68 mg/kg) (table 4.31).

Chapter 4 Results

240

Mean copper bioaccumulation in different organs/tissues of C. mrigala were

ranged between 4.38 -6.93 mg/Kg and 3.76-6.21 mg/Kg at site A while site B, C and D

specimen showed ranged from 6.31-11.16 mg/Kg and 5.15 -9.08 mg/Kg, 7.42-12.79

mg/Kg and 5.82-11.03 mg/Kg, 5.56-9.98 mg/Kg and 4.95-8.66 mg/Kg during low and

high flow season respectively (tables 4.32-4.38, Fig. 4.47).

The mean accumulation ranged from 4.25-6.74 and 3.55-6.04 in organs/tissues of

L. rohita netted from site A while other sampling site B showed ranged from 5.62 to9.58

mg/Kg and from 4.82 to 9.24 mg/Kg, site C from 6.93 to 12.13 mg/Kg and from 5.87 to

11.13 mg/Kg and site D from 5.87 to 10.53 mg/Kg and 5.33 to 9.64 mg/Kg during low

and high flow seasons, respectively (tables 4.32-4.38, Fig. 4.56).

Mean copper contents in fish tissues/organs of C. catla showed value up to 4.53 –

7.18 mg/Kg and 3.73 – 6.35 mg/Kg at site A during low and high flow seasons,

respectively. While the corresponding values in sampled from site B ranged from 5.72 to

9.58 mg/Kg and 4.85 to 9.28 mg/Kg, site C ranged from 6.78 to 13.69 mg/Kg and 5.72 to

11.40 mg/Kg and site D ranged from 6.13 to 9.03 mg/Kg and 5.06 to 8.72 mg/Kg during

low and high flow season, respectively (tables 4.32-4.38, Fig. 4.65).

4.6.3.4 Iron:

Mean iron bioaccumulation along stream sampling localities up to 68.12 mg/kg

was recorded at site C. While the corresponding value 58.83 mg/kg for site D, 50.57

mg/kg for site B and 41.35 mg/kg for site A were noted (table 4.31). When the data was

pooled for investigating the effect of flow seasons, the metal concentration was higher

during low (58.66 mg/kg) flow than high (51.13 mg/kg) flow. Among fish species,

highest iron bioaccumulation in C. catla (58.66 mg/kg) than C. mrigala (54.14 mg/kg)

and L. rohita (51.89 mg/kg) were recorded. Iron bioaccumulation pattern in fish

organs/tissue was in order of: kidney (72.22 mg/kg)> liver (68.29 mg/kg) > intestine

(64.12 mg/kg) > heart (56.27 mg/kg) > scale (53.11 mg/kg) > eyes (50.11 mg/kg) > skin

(49.73 mg/kg) > gills (45.57 mg/kg) (table 4.31).

Chapter 4 Results

241

Mean Fe bioaccumulation in different organs/tissues of C. mrigala ranged from

29.79 to 56.99 mg/Kg and 24.35 to 48.45 mg/Kg at site A while accumulation ranged

from 42.78 to 75.77 mg/Kg and 33.21 to 69.82 mg/Kg for site B, 66.24 to 97.43 mg/Kg

and 54.80 to 84.33 mg/Kg for site C and 56.75 to 83.41 mg/Kg and 40.55 to 76.02 mg/Kg

for site D during low and high flow season respectively (tables 4.32-4.38, Fig. 4.48).

The mean Fe accumulation in different organs/tissues ranged from 30.55 to 58.24

mg/Kg and 26.98 to 53.68 mg/kg in L. rohita at site A during low and high flow season

respectively. While the accumulation in L. rohtia ranged from 41.11 to 68.28 mg/kg and

38.11 to 58.19 mg/kg for site B, 56.12 to 83.54 mg/kg and 47.60 to 77.48 mg/kg for site

C and 43.35 to 84.72 mg/kg and 39.07 to 80.24 mg/kg for site D during low and high

flow season respectively (tables 4.32-4.38, Fig. 4.57).

The mean bioacummulation ranged from 31.17 to 69.21 mg/kg and 28.21 to 56.14

mg/kg in different organs/tissues of C. catla at site A during low and high flow season

respectively (tables 4.31). While the Fe accumulation in C. catla corresponding to low

and high flow seasons ranged from 38.21 to 75.65 mg/kg and 35.79 to 63.25 mg/kg for

site B, 71.27 to 97.81 mg/kg and 51.94 to 91.66 mg/kg for site C and 56.94 to 84.50

mg/kg and 48.88 to 78.55 mg/kg for site D (Fig. 4.66).

4.6.3.5 Lead:

The mean lead bioaccumulation up to 4.61 mg/kg was measured at site C. Next to

rank appeared the sites D, B and A with mean Pb concentrations up to 2.94 mg/kg, 1.81

mg/kg and 0.32 mg/kg. When the data were visualized for the effect of seasons, lead

bioaccumulation appeared up to 2.68 mg/kg and 2.16 mg/kg during low and high flows

(table 4.31). The lead bioacuumulation pattern in fish tissue was in order of kidney (3.06

mg/kg)> liver (2.93 mg/kg)> intestine (2.80 mg/kg) > heart (2.63 mg/kg) > scale (2.58

mg/kg) > eyes (2.29 mg/kg) > gills (2.07 mg/kg) > skin (1.93 mg/kg). The highest lead

accumulation was recorded in C. catla (2.49 mg/kg) than L. rohita (2.39 mg/kg) and C.

mrigala (2.37 mg/kg).

Chapter 4 Results

242

The higher Pb accumulation in organs/tissues of C. mrigala were measured at site

C up to 3.92-6.28 mg/Kg and 3.30 – 5.94 mg/Kg during low and high flow season,

respectively. While the Pb accumulation in C. mrigala corresponding to low and high

flow seasons ranged from 0.23 to 0.47 mg/kg and 0.18 to 0.37 mg/kg for site A, 1.70 to

2.88 mg/kg and 1.22 to 2.05 mg/kg for site B and 2.48 to 4.46 mg/kg and 1.68 to 3.02

mg/kg for site D (tables 4.32-4.38, Fig.4.49).

The mean accumulation ranged from 0.27 to 0.53 and 0.19 to 0.40 mg/Kg in

organs/tissues of L. rohita netted from site A while other sampling showed ranged from

1.77 to 3.00 mg/Kg and from 1.28 to 2.14 mg/Kg for site B during low and high flow

seasons, respectively. The metal accumulation corresponding value ranged from 3.85 to

6.30 mg/Kg and from 2.80 to 5.04 mg/Kg for site C and for site D measured from 2.47 to

4.44 mg/Kg and 2.12 to 3.82 mg/Kg during low and high flow seasons, respectively

(tables 4.32-4.38, Fig. 4.58).

Mean lead contents in fish tissues/organs of C. catla showed value up to 0.26 to

0.50 mg/Kg and 0.23 to 0.47 mg/Kg at site A during low and high flow seasons,

respectively. While the corresponding values in fish sampled from site B ranged from

1.77 to 3.01 mg/Kg and 1.21 to 2.14 mg/Kg, site C ranged from 4.07 to 6.66 mg/Kg and

3.52 to 6.33 mg/Kg and site D ranged from 2.55 to 4.58 mg/Kg and 1.86 to 3.35 mg/Kg

during low and high flow season, respectively (Fig. 4.67).

4.6.3.6 Zinc:

Highest mean zinc bioaccumulation occur at site C. While the metal mg/Kg of

organs/tissues of the fishes appeared up to 31.93, 45.96, 71.12 and 56.05 mg/Kg for the

sites A, B, C and D, respectively. The mean low and high flow season values differ

significantly (P<0.001) with corresponding values of 55.80 and 46.72 mg/Kg (table 4.31).

The highest zinc accumulation was recorded in C. mrigala (52.94 mg/kg) than L.

rohita (51.24 mg/kg) and C. catla (49.61 mg/kg). The zinc accumulation pattern in fish

tissue was in order of kidney (68.16 mg/kg) > liver (63.32 mg/kg) >heart (58.27 mg/kg) >

Chapter 4 Results

243

intestine (57.11 mg/kg) > scale (51.82 mg/kg) > eyes (46.40 mg/kg) > gills (42.41 mg/kg)

> skin (39.69 mg/kg) (table 4.31).

Mean Zn bioaccumulation in different organs of C. mrigala ranged from 30.07 to

51.70 mg/Kg and 25.66 to 44.12 mg/Kg at site A while, the metal accumulation ranged

between 37.37 to 77.54 mg/Kg and 33.73 to 57.99 mg/Kg at site B, 70.32 to 120.89

mg/Kg and 46.51 to 79.96 mg/Kg at site C and 41.61 to 71.53 mg/Kg and 37.18 to 63.92

mg/Kg at site D during low and high flow season respectively (tables 4.33-4.39, Fig.

4.50).

The metal accumulation in the organ/tissues of L. rohita showed ranged between

25.27-43.44 mg/Kg and 23.76-40.86 mg/Kg at site A while 36.19-75.28 mg/Kg and

32.86-56.50 mg/Kg for site B, 53.67-92.27 mg/Kg and 49.37-84.88 mg/Kg for site C and

49.98-85.94 mg/Kg and 40.07-68.89 mg/Kg for site D during low and high flow season

respectively (Fig. 4.59).

The mean Zn accumulation in different organs ranged from 24.33 to 41.82 mg/kg

and 19.57 to 33.65 mg/kg in C. catla at site A during low and high flow season

respectively. While the accumulation in C. catla was recorded ranged from 37.64 to 72.31

mg/kg and 30.83 to 53.00 mg/kg for site B, 56.20 to 96.62 mg/kg and 50.96 to 87.62

mg/kg for site C and 42.26 to 72.66 mg/kg and 40.22 to 69.14 mg/kg for site D during

low and high flow season respectively (tables 4.33-4.39, Fig. 4.68).

4.6.3.7 Maganese:

Mean maganese accumulation 15.61 mg/kg was measured at site C. While

sampling sites D, B and A showed metal bioaccumulation in descending order up to 7.33,

5.49 and 3.31 mg/kg. The mean metal contents differed significantly (P<0.001) in

corresponding values of low flow (8.95 mg/kg) to high flow (6.93 mg/kg). Among the

three fish species, the C. mrigala had highest maganese accumulation up to 8.36 mg/kg.

While L. rohita and C. catla showed the metal levels up to 8.15 and 7.30 mg/kg

respectively (table 4.31). The metal bioaccumulation pattern in fish organs/tisssue was in

Chapter 4 Results

244

order of: kidney (10.55 mg/kg) > liver (9.31 mg/kg) > intestine (9.17 mg/kg) > heart (9.05

mg/kg) > scale (7.81 mg/kg) > eyes (7.25 mg/kg) > gills (42.41 mg/kg) > skin (39.69

mg/kg).

Higher Mn bioaccumulation were recorded in organs/tissues ranged from 16.52 to

28.49 mg/Kg in C. mrigala at site C during low flow seasons. While L. rohita and C.

catla showed the higher metals accumulation ranged from 13.49 to 23.27 mg/Kg and

from 56.20 to 96.62 mg/Kg at site C during low flow seasons, respectively (tables 4.33-

4.39).

4.6.3.8 Nickel:

Among sampling sites, higher mean 3.20 mg/kg nickel bioaccumulation in

occurred at site C. while the metals contents/Kg of the fishes organs/tissues appeared in

descending order up to 2.54, 0.34 and 0.14 from sampling sites D, B and A respectively.

Effect of seasons appeared in the metal contents up to1.57 and 1.28 mg/kg during low and

high flow seasons, respectively (table 4.31). Among fish species, the C. mrgiala had

highest accumulation up to 1.59 mg/kg. While the L. rohita and C. catla showed the

metal levels up to 1.37 and 1.32 mg/Kg. The nickel bioaccumulation pattern in fish tissue

was in decending order: kidney (1.88 mg/kg) > liver (1.76 mg/kg) > intestine (1.65

mg/kg) > heart (1.57 mg/kg) > scale (1.40 mg/kg) >eyes (1.28 mg/kg) >gills (1.24 mg/kg)

> skin (1.15 mg/kg) (table 4.31).

Mean Ni bioaccumulation in different organs/tissues of C. mrigala ranged from

0.38 to 0.69 mg/Kg and 0.36 to 0.62 mg/Kg at site A while accumulation ranged from

0.54 to 0.92 mg/Kg and 0.57 to 0.95 mg/Kg for site B, 3.41 to 5.88 mg/Kg and 2.56 to

4.29 mg/Kg for site C and 1.16 to 1.74 mg/Kg and 0.97 to 1.68 mg/Kg for site D during

low and high flow seasons, respectively (tables 4.33-4.39, Fig. 4.52).

The mean Ni accumulation in different organs/tissues ranged from 0.40 to 0.73

mg/kg and 0.40 to 0.70 mg/kg in L. rohita at site A during low and high flow season

respectively. While the accumulation in L. rohtia ranged from 0.58 to 0.98 mg/Kg and

Chapter 4 Results

245

0.57 to 0.94 mg/kg for site B, 2.87 to 4.95 mg/kg and 1.89 to 3.17 mg/kg for site C and


respectively (Fig. 4.61).

The mean bioacummulation of the metal ranged from 3.00 to 4.89 mg/kg and 1.65

to 2.84 mg/kg in different organs/tissues of C. catla at site A during low and high flow

seasons, respectively. While the Ni accumulation in C. catla corresponding to low and

high flows ranged from 3.85 to 6.62 mg/kg and 3.48 to 5.98 mg/kg for site B, 12.56 to

21.66 mg/kg and 10.05 to 17.28 mg/kg for site C and 5.94 to 10.21 mg/kg and 4.69 to

8.07 mg/kg for site D (tables 4.33-4.39, Fig. 4.70).

4.6.3.9 Mercury:

Mean mercury bioaccumulation 3.05 mg/kg was measured at site C than D (2.54

mg/kg), B (0.34 mg/kg) and A (0.14 mg/kg) during low flow (1.77 mg/kg) and high flow

(1.33 mg/kg). The mercury bioaccumulation pattern in fish tissue was in order of: liver

(2.24 mg/kg) > kidney (2.09 mg/kg) > intestine (1.92 mg/kg) > heart (1.73 mg/kg) > scale

(1.47 mg/kg) > eyes (1.34 mg/kg) >skin (1.23 mg/kg) >gills (0.79 mg/kg). The highest

mercury accumulation was recorded in C. mrigala (1.54 mg/kg) than C. catla (1.52

mg/kg) and L. rohita (1.50 mg/kg) (table 4.31).

Mean Hg bioaccumulation in different tissues of C. mrigala ranged from

0.13±0.039 to 0.24 mg/Kg and 0.07 to 0.22 mg/Kg at site A while, the metal

accumulation ranged between 0.14 -0.68 mg/Kg and 0.15-0.47 mg/Kg at site B, 1.83-5.70

mg/Kg and 1.28-4.14 mg/Kg at site C and 1.39-4.49 mg/Kg and 1.11-3.57 mg/Kg at site

D during low and high flow season respectively (tables 4.33-4.39, Fig. 4.53).

The metal accumulation in the organ/tissues of L. rohita showed ranged from 0.05

to 0.18 mg/Kg and 0.07 to 0.22 mg/Kg at site A while 0.13 to 0.62 mg/Kg and 0.14 to

0.43 mg/Kg for site B, 1.73 to 5.39 mg/Kg and 1.26 to 4.06 mg/Kg for site C and 1.41 to

4.54 mg/Kg and 1.09 to 3.51 mg/Kg for site D during low and high flow season


Chapter 4 Results

246

The mean Hg accumulation in different organs/tissues ranged from 0.06 to 0.20

mg/kg and 0.07 to 0.22 mg/kg in C. catla at site A during low and high flow seasons,

respectively. While the accumulation in C. catla was recorded ranged from 0.12 to 0.60

mg/kg and 0.16 to 0.50 mg/kg for site B, 1.79 to 5.55 mg/kg and 1.30 to 4.18 mg/kg for

site C and 1.35 to 4.34 mg/kg and 1.12 to 3.60 mg/kg for site D during low and high flow

seasons, respectively (tables 4.33-4.39, Fig. 4.71).

Chapter 4 Results

247

Table 4.31 Means of metals’ concentrations for sampling sites, flow seasons, fish species and fishes organs with standard error of

means (SEM) and significance (P).

Metals Cd Cr Cu Fe Pb Zn Mn Ni Hg

Sampling sites

Site A: Siphon (Control) 0.07d 1.43

d 5.01

c 41.35

d 0.32

d 31.93

d 3.31

d 0.52

d 0.14

d


2.83c

6.85b 50.57

c 1.81

c 45.96

c 5.49

c 0.76

c 0.34

c


5.39a

8.51a

68.84a

4.61a 71.12

a 15.61

a 3.20

a 3.05

a


3.49b

6.80b

58.83b 2.94

b 56.05

b 7.33

b 1.21

b 2.54

b


Seasons

High 0.14b 2.63

b 6.40

b 51.13

b 2.16

b 46.72

b 6.93

b 1.28

b 1.33

b

Low 0.19a

3.94a 7.18

a 58.66

a 2.68

a 55.80

a 8.95

a 1.57

a 1.71

a


Fish Species

Cirrhinus mrigala 0.17a 3.59

a 6.84

a 54.14

b 2.37

c 52.94

a 8.36

a 1.59

a 1.54

a

Labeo rohita 0.15b 2.99

c 6.74

c 51.89

c 2.39

b 51.24

b 8.15

b 1.37

b 1.50

c


b 6.79

b 58.66

a 2.49

a 49.61

c 7.30

c 1.32

c 1.52

b


Fishes Organs

Skin 0.15f

2.96f 6.20f 49.73

e 1.93

g 39.69

h 6.36

f 1.15

h 1.23

g

Gills 0.13g 2.91

f 5.70g 45.57

f 2.07

f 42.41

g 6.48

f 1.24

g 0.79

i

Eyes 0.15f

3.04e 5.68g 50.10

f 2.29

e 46.40

f 7.25

e 1.28

f 1.34

f

Scales 0.17d 3.05

e 6.53e 53.11

f 2.58

d 51.82

e 7.81

d 1.40

e 1.47

e

Heart 0.16e 3.52

d 6.90d 56.27

d 2.63

d 58.27

c 9.05

c 1.57

d 1.73

d

Intestine 0.19c 3.64

c 8.30c 64.12

c 2.80

c 57.11

d 9.17

bc 1.65

c 1.92

c

Liver 0.20b

3.87b 8.65b 68.29

b 2.93

b 63.32

b 9.31

b 1.76

b 2.24

a

Kidney 0.23a

4.16a

9.06a 72.22a 3.06

a 68.16

a 10.55

a 1.88

a 2.09

b




Chapter 4 Results

248

Table 4.32 Means±SD of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish organs of the fish species sampled during two flow

seasons from the selected upstream sampling site A (siphon).

Site A

Fish

Species

Tissues Eyes Gills Heart Intestine Kidney Liver Scale Skin

Season Low High Low High Low high Low high Low high Low High Low high Low high

Metals

Cir

rhin

us

mri

gala

Cd 0.09

±0.012

0.03

±0.003

0.06

±0.003

0.04

±0.003

0.07

±0.004

0.05

±0.004

0.08

±0.004

0.04

±0.004

0.13

±0.043

0.08

±0.025

0.09

±0.017

0.06

±0.015

0.10

±0.008

0.08

±0.019

0.07

±0.021

0.04

±0.011

Cr 1.4

±0.012

1.12

±0.038

1.74

±0.040

0.98

±0.013

1.58

±0.044

1.39

±0.060

1.82

±0.016

1.46

±0.065

1.98

±0.018

1.58

±0.053

1.88

±0.017

1.3

±0.044

1.32

±0.012

1.18

±0.040

1.23

±0.011

1.02

±0.034

Cu 5.24

±0.097

4.42

±0.059

4.38

±0.081

3.76

±0.050

6.13

±0.114

5.69

±0.076

5.86

±0.109

6.09

±0.081

6.93

±0.129

6.21

±0.129

6.47

±0.120

5.23

±0.069

5.29

±0.396

4.74

±0.063

4.47

±0.083

4.05

±0.054

Fe 36.55

±1.360

32.04

±1.792

29.76

±1.108

24.35

±1.362

35.24

±1.312

39.51

±2.211

51.95

±2.289

45.92

±2.569

56.99

±2.556

48.45

±2.711

48.3

±1.797

43.34

±2.425

42.29

±1.574

37.95

±2.123

38.2

±5.752

30.12

±1.685

Pb 0.31

±0.025

0.24

±0.051

0.26

±0.022

0.18

±0.037

0.44

±0.048

0.37

±0.077

0.47

±0.053

0.27

±0.057

0.41

±0.034

0.28

±0.058

0.37

±0.035

0.31

±0.064

0.32

±0.026

0.23

±0.049

0.23

±0.020

0.20

±0.041

Labeo

roh

ita

Cd 0.07

±0.014

0.04

±0.010

0.09

±0.012

0.05

±0.015

0.06

±0.003

0.04

±0.004

0.07

±0.003

0.03

±0.010

0.08

±0.004

0.05

±0.005

0.07

±0.003

0.03

±0.011

0.12

±0.022

0.07

±0.028

0.09

±0.034

0.06

±0.030

Cr 1.83

±0.109

1.69

±0.121

1.33

±0.120

1.29

±0.167

1.79

±0.057

1.2

±0.067

1.83

±0.059

1.15

±0.064

1.99

±0.064

1.27

±0.071

1.89

±0.061

1.05

±0.059

1.99

±0.395

0.89

±0.136

1.55

±0.319

1.4

±0.257

Cu 5.09

±0.074

4.17

±0.100

4.25

±0.062

3.55

±0.085

5.96

±0.087

5.36

±0.129

5.99

±0.347

5.74

±0.138

6.74

±0.098

6.04

±0.145

6.29

±0.092

4.93

±0.119

4.85

±0.071

4.47

±0.107

4.34

±0.063

3.82

±0.092

Fe 37.52

±0.997

35.5

±1.493

30.55

±0.812

26.98

±1.134

46.18

±0.961

41.78

±0.834

53.33

±1.417

50.88

±2.139

58.24

±4.319

53.68

±2.257

49.58

±1.311

42.02

±5.300

43.41

±1.154

42.04

±1.768

38.94

±3.971

33.37

±1.403

Pb 0.35

±0.072

0.27

±0.055

0.30

±0.061

0.19

±0.040

0.50

±0.106

0.40

±0.083

0.53

±0.114

0.30

±0.061

0.46

±0.095

0.31

±0.063

0.42

±0.088

0.34

±0.069

0.36

±0.076

0.26

±0.053

0.27

±0.055

0.22

±0.045

Catl

a c

atl

a

Cd 0.05

±0.006

0.03±

0.003

0.08

±0.019

0.06

±0.016

0.09

±0.021

0.05

±0.012

0.12

±0.020

0.09

±0.025

0.15

±0.039

0.11

±0.036

0.07

±0.008

0.05

±0.005

0.09

±0.025

0.06

±0.012

0.07

±0.019

0.04

±0.011

Cr 1.52

±0.061

1.23±

0.065

1.57

±0.053

1.12

±0.045

1.81

±0.061

1.5

±0.502

1.85

±0.063

1.43

±0.481

2.01

±0.068

1.58

±0.530

1.92

±0.065

1.31

±0.438

1.35

±0.045

1.19

±0.398

1.25

±0.042

1.02

±0.343

Cu 5.42

±0.170

4.38±

0.047

4.53

±0.142

3.73

±0.040

6.35

±0.199

5.64

±0.061

6.06

±0.190

6.03

±0.065

7.18

±0.225

6.35

±0.069

6.7

±0.210

5.18

±0.056

5.17

±0.162

4.7

±0.051

4.63

±0.145

4.01

±0.043

Fe 38.28

±2.178

37.12±

1.729

31.17

±1.773

28.21

±1.314

56.91

±2.366

45.78

±2.133

54.41

±3.096

53.2

±2.479

69.21

±3.048

56.14

±2.615

60.58

±2.671

50.21

±2.339

48.29

±1.221

43.96

±2.048

49.53

±1.988

34.89

±1.625

Pb 0.33

±0.074

0.32

±0.063

0.28

±0.064

0.23

±0.046

0.48

±0.095

0.47

±0.117

0.50

±0.126

0.35

±0.070

0.44

±0.098

0.36

±0.072

0.40

±0.094

0.40

±0.079

0.35

±0.077

0.30

±0.061

0.26

±0.051

0.25

±0.057

Chapter 4 Results

249

Table 4.33 Means of metals (Zn, Mn, Ni, Hg) concentrations in fish organs of the fish species sampled during two flow seasons from

the selected upstream sampling site A (siphon) with standard deviation (SD)

Site A

Fish

Species


Season Low High Low high Low high Low high Low high Low High Low high Low high

irrh

inu

s m

rigala

Metals

Zn 35.08

±2.228

29.94

±3.542

31.92

±2.027

25.66

±3.036

41.41

±2.630

35.34

±4.181

44.84

±2.848

38.27

±4.527

51.70

±3.284

41.65

±4.926

48.80

±3.099

44.12

±5.219

38.51

±2.446

32.87

±3.888

30.07

±1.910

27.24

±3.222

Mn 3.39

±0.033

3.31

±0.034

3.08

±0.030

3.01

±0.031

4.00

±0.039

3.90

±0.041

4.33

±0.042

4.23

±0.044

4.99

±0.049

4.87

±0.051

4.71

±0.046

4.60

±0.048

3.80

±0.037

3.71

±0.039

2.90

±0.028

2.84

±0.030

Ni 0.53

±0.029

0.42

±0.027

0.48

±0.026

0.36

±0.023

0.61

±0.033

0.46

±0.029

0.65

±0.035

0.54

±0.034

0.69

±0.038

0.62

±0.039

0.65

±0.036

0.58

±0.037

0.50

±0.027

0.51

±0.032

0.37

±0.019

0.38

±0.024

Hg 0.15

±0.047

0.10

±0.015

0.13

±0.039

0.14

±0.020

0.17

±0.051

0.14

±0.020

0.22

±0.067

0.22

±0.032

0.19

±0.058

0.16

±0.023

0.24

±0.073

0.17

±0.025

0.20

±0.060

0.16

±0.024

0.07

±0.020

0.07

±0.011

Metals

Labeo

roh

ita

Zn 29.48

±1.028

27.73

±1.336

26.82

±0.935

23.76

±1.145

34.80

±1.213

32.73

±1.577

37.68

±1.314

35.44

±1.708

43.44

±1.515

38.57

±1.859

41.00

±1.430

40.86

±1.969

32.36

±1.128

30.44

±1.467

25.27

±0.881

25.22

±1.216

Mn 3.38

±0.040

2.50

±0.114

3.08

±0.037

2.27

±0.104

3.99

±0.047

2.95

±0.135

4.32

±0.051

3.19

±0.146

4.98

±0.059

3.68

±0.168

4.70

±0.056

3.48

±0.159

3.79

±0.045

2.80

±0.128

2.90

±0.034

2.14

±0.098

Ni 0.56

±0.047

0.48

±0.043

0.51

±0.042

0.41

±0.036

0.64

±0.054

0.53

±0.047

0.69

±0.057

0.62

±0.055

0.73

±0.061

0.70

±0.062

0.70

±0.058

0.66

±0.058

0.53

±0.044

0.58

±0.051

0.40

±0.033

0.43

±0.038

Hg 0.12

±0.006

0.11

±0.005

0.10

±0.005

0.14

±0.006

0.13

±0.006

0.14

±0.007

0.16

±0.008

0.22

±0.011

0.14

±0.007

0.16

±0.007

0.18

±0.009

0.18

±0.008

0.15

±0.007

0.16

±0.008

0.05

±0.002

0.07

±0.003

Metals

Catl

a c

atl

a

Zn 28.38

±1.874

22.83

±1.569

25.82

±1.704

19.57

±1.345

33.50

±2.212

26.95

±1.853

36.28

±2.395

29.18

±2.006

41.82

±2.761

31.76

±2.183

39.48

±2.606

33.65

±2.313

31.16

±2.057

25.06

±1.723

24.33

±1.606

20.77

±1.428

Mn 3.50

±0.145

1.92

±0.114

3.18

±0.132

1.75

±0.104

4.13

±0.171

2.27

±0.135

4.47

±0.185

2.46

±0.146

4.89

±0.203

2.84

±0.169

4.73

±0.196

2.68

±0.159

3.92

±0.162

2.16

±0.128

3.00

±0.124

1.65

±0.098

Ni 0.57

±0.020

0.42

±0.023

0.51

±0.018

0.35

±0.019

0.65

±0.022

0.46

±0.025

0.69

±0.024

0.54

±0.029

0.74

±0.025

0.61

±0.033

0.70

±0.024

0.57

±0.031

0.53

±0.018

0.50

±0.027

0.40

±0.012

0.38

±0.020

Hg 0.13

±0.008

0.10

±0.005

0.11

±0.007

0.13

±0.007

0.14

±0.009

0.14

±0.007

0.18

±0.012

0.22

±0.011

0.16

±0.010

0.15

±0.008

0.20

±0.013

0.17

±0.008

0.17

±0.011

0.16

±0.008

0.06

±0.004

0.07

±0.004

Chapter 4 Results

250

Table 4.34 Means±SD of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish organs of the fish species sampled during two flow

seasons from the selected downstream sampling site B (shahdera).

Site B

Fish

Species



Metals

Cir

rhin

us

mri

gala

Cd 0.18

±0.022

0.05

±0.018

0.14

±0.017

0.1

±0.007

0.15

±0.007

0.12

±0.009

0.14

±0.006

0.11

±0.008

0.19

±0.008

0.14

±0.010

0.23

±0.040

0.13

±0.010

0.11

±0.020

0.07

±0.005

0.15

±0.021

0.12

±0.018

Cr 2.43

±0.050

2.03

±0.053

2.99

±0.085

2.4

±0.061

3.26

±0.074

2.89

±0.069

3.34

±0.068

2.1

±0.136

4.18

±0.085

3.29

±0.122

3.67

±0.075

2.24

±0.078

2.4

±0.118

1.75

±0.171

3.08

±0.063

2.21

±0.167

Cu 6.48

±0.130

5.15

±0.354

6.31

±0.462

5.3

±0.326

7.83

±0.157

6.22

±0.319

8.51

±0.170

7.69

±0.078

10.26

±0.205

9.08

±0.386

11.16

±0.628

8.15

±0.396

4.5

±0.090

4.11

±0.042

7.28

±0.731

6.9

±0.449

Fe 42.78

±3.330

36.7

±2.068

49.37

±3.797

41.07

±2.314

57.87

±3.919

51.26

±3.651

64.26

±3.135

57.96

±3.266

75.77

±2.559

69.82

±3.935

69.83

±3.365

64.37

±3.628

32.88

±1.846

29.13

±1.641

51.43

±6.274

43.21

±1.871

Pb 2.19

±0.16

1.75

±0.09

1.83

±0.13

1.36

±0.07

2.88

±0.21

1.86

±0.09

2.02

±0.14

1.79

±0.09

2.16

±0.11

2.05

±0.15

1.92

±0.10

1.75

±0.12

1.90

±0.14

1.22

±0.06

1.70

±0.12

1.51

±0.08

Labeo

roh

ita

Cd 0.12

±0.015

0.08

±0.006

0.1

±0.003

0.09

±0.006

0.12

±0.003

0.11

±0.007

0.11

±0.003

0.1

±0.007

0.15

±0.004

0.13

±0.008

0.13

±0.003

0.12

±0.008

0.07

±0.002

0.06

±0.004

0.15

±0.029

0.1

±0.024

Cr 2.65

±0.047

1.89

±0.026

3.04

±0.053

2.13

±0.035

3.34

±0.059

2.46

±0.033

3.64

±0.062

2.64

±0.036

4.55

±0.080

3.22

±0.044

4.00

±0.070

2.76

±0.037

2.29

±0.040

1.66

±0.023

3.36

±0.059

2.81

±0.182

Cu 6.05

±0.057

4.82

±0.102

5.62

±0.209

5.51

±0.117

7.31

±0.069

5.83

±0.124

7.94

±0.075

7.58

±0.156

9.58

±0.091

9.24

±0.196

9.2

±0.087

8.99

±0.191

4.2

±0.040

4.05

±0.086

5.67

±0.054

5.17

±0.382

Fe 46.13

±2.141

39.84

±2.732

41.09

±1.822

38.11

±3.226

51.28

±2.274

47.07

±4.142

68.08

±4.068

56.61

±1.928

68.28

±4.732

59.19

±2.322

63.91

±3.993

52.87

±3.513

29.14

±1.292

28.45

±0.969

56.71

±4.494

52.43

±4.823

Pb 2.28

±0.133

1.84

±0.169

1.91

±0.111

1.43

±0.131

3.00

±0.175

1.96

±0.179

2.11

±0.123

1.89

±0.173

2.28

±0.209

2.14

±0.125

2.02

±0.191

1.82

±0.106

1.98

±0.115

1.28

±0.118

1.77

±0.103

1.59

±0.146

Catl

a c

atl

a

Cd 0.09

±0.010

0.07

±0.007

0.12

±0.013

0.08

±0.008

0.13

±0.015

0.09

±0.010

0.16

±0.018

0.12

±0.026

0.21

±0.028

0.15

±0.029

0.13

±0.015

0.1

±0.010

0.08

±0.015

0.05

±0.005

0.11

±0.024

0.08

±0.025

Cr 2.57

±0.046

2.19

±0.069

2.95

±0.053

2.46

±0.078

3.24

±0.058

2.84

±0.090

3.53

±0.063

3.05

±0.096

4.41

±0.079

3.73

±0.118

3.88

±0.069

3.19

±0.101

2.22

±0.040

1.92

±0.061

3.26

±0.058

2.67

±0.084

Cu 6.05

±0.053

4.85

±0.050

5.72

±0.197

5.54

±0.057

7.31

±0.508

5.86

±0.497

7.94

±0.509

7.62

±0.468

9.58

±0.460

9.28

±0.552

8.8

±0.162

8.51

±0.547

4.2

±0.037

4.07

±0.042

6.67

±0.680

5.21

±0.712

Fe 47.6

±3.760

39.56

±1.731

52.76

±1.586

44.27

±1.937

58.37

±2.210

53.25

±2.706

62.03

±4.593

50.47

±4.411

75.65

±4.331

63.25

±5.883

69.1

±5.496

58.38

±3.960

36.32

±4.689

31.39

±1.374

38.21

±1.417

35.79

±1.566

Pb 2.28

±0.201

1.73

±0.219

1.91

±0.168

1.35

±0.170

3.01

±0.265

1.84

±0.233

2.11

±0.186

1.78

±0.224

2.14

±0.189

2.14

±0.271

1.90

±0.239

1.82

±0.161

1.98

±0.175

1.21

±0.152

1.77

±0.156

1.50

±0.189

Chapter 4 Results

251

Table 4.35 Means±SD of metals (Zn, Mn, Ni, Hg) concentrations in fish organs of the fish species sampled during two flow seasons

from the selected downstream sampling site B (shahdera).

Site B

Fish

Species



Cir

rhin

us

mri

gala

Metals

Zn 43.49

±2.072

39.35

±2.271

37.27

±1.776

33.73

±1.946

57.76

±2.753

50.29

±2.903

55.58

±2.649

43.19

±2.493

77.54

±3.696

57.99±

3.347

60.49

±2.883

54.73

±3.159

51.33

±2.446

46.45

±2.681

39.56

±1.885

35.80

±2.066

Mn 4.87

±0.025

4.31

±0.079

5.17

±0.027

3.92

±0.072

6.37

±0.033

5.09

±0.093

7.91

±0.041

6.00

±0.110

8.38

±0.043

6.36

±0.116

7.27

±0.038

5.51

±0.101

6.71

±0.035

4.83

±0.088

5.68

±0.029

3.70

±0.068

Ni 0.61

±0.027

0.65

±0.027

0.65

±0.029

0.60

±0.025

0.80

±0.035

0.83

±0.035

0.85

±0.038

0.78

±0.032

0.92

±0.041

0.95

±0.039

0.86

±0.038

0.88

±0.037

0.72

±0.032

0.71

±0.030

0.55

±0.024

0.57

±0.024

Hg 0.34

±0.059

0.28

±0.076

0.32

±0.056

0.19

±0.052

0.50

±0.088

0.34

±0.091

0.69

±0.119

0.33

±0.088

0.54

±0.093

0.42

±0.114

0.45

±0.078

0.47

±0.127

0.43

±0.074

0.31

±0.084

0.14

±0.024

0.15

±0.041

Metals

Labeo

roh

ita

Zn 42.22

±1.059

38.34

±1.160

36.19

±0.908

32.86

±0.994

56.08

±1.407

49.00

±1.482

53.97

±1.354

42.08

±1.273

75.28

±1.889

56.50

±1.709

58.73

±1.474

53.33

±1.613

49.84

±1.251

45.26

±1.369

38.41

±0.964

34.88

±1.055

Mn 4.88

±0.042

5.53

±0.103

5.18

±0.044

5.03

±0.093

6.38

±0.055

6.53

±0.121

7.93

±0.068

7.69

±0.143

8.40

±0.072

8.15

±0.151

7.28

±0.062

7.07

±0.131

6.73

±0.058

6.19

±0.115

5.70

±0.049

4.74

±0.088

Ni 0.65

±0.068

0.64

±0.071

0.70

±0.073

0.60

±0.067

0.85

±0.089

0.83

±0.091

0.91

±0.095

0.78

±0.086

0.98

±0.103

0.94

±0.104

0.92

±0.096

0.88

±0.097

0.77

±0.081

0.71

±0.078

0.58

±0.061

0.57

±0.063

Hg 0.31

±0.018

0.26

±0.028

0.29

±0.017

0.18

±0.019

0.46

±0.027

0.31

±0.034

0.62

±0.037

0.30

±0.033

0.49

±0.029

0.39

±0.042

0.41

±0.024

0.43

±0.047

0.39

±0.023

0.29

±0.031

0.13

±0.008

0.14

±0.015

Metals

Catl

a c

atl

a

Zn 43.91

±1.599

35.97

±1.447

37.64

±1.370

30.83

±1.240

58.33

±2.124

45.97

±1.850

56.13

±2.043

39.48

±1.589

72.31

±2.633

53.00

±2.133

61.08

±2.224

50.03

±2.013

51.84

±1.887

42.46

±1.708

39.95

±1.454

32.72

±1.317

Mn 3.85

±0.042

4.06

±0.089

4.09

±0.045

3.69

±0.081

5.03

±0.055

4.79

±0.104

6.25

±0.068

5.65

±0.123

6.62

±0.072

5.98

±0.130

5.74

±0.063

5.19

±0.113

5.30

±0.058

4.55

±0.099

4.49

±0.049

3.48

±0.076

Ni 0.79

±0.019

0.68

±0.022

0.85

±0.020

0.64

±0.021

1.03

±0.025

0.88

±0.028

1.10

±0.026

0.82

±0.027

1.19

±0.029

1.00

±0.032

1.12

±0.027

0.93

±0.030

0.93

±0.022

0.75

±0.024

0.71

±0.017

0.60

±0.019

Hg 0.30

±0.025

0.30

±0.027

0.28

±0.024

0.20

±0.019

0.44

±0.037

0.35

±0.032

0.60

±0.051

0.34

±0.031

0.47

±0.040

0.44

±0.040

0.39

±0.033

0.50

±0.045

0.37

±0.032

0.33

±0.030

0.12

±0.010

0.16

±0.015

Chapter 4 Results

252

Table 4.36 Means of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish organs of the fish species sampled during two flow seasons

from the selected downstream sampling site C (sunder) with standard deviation (SD)

Site C

Fish

Species



Cir

rhin

us

mri

gala

Metals

Cd 0.36

±0.034

0.2

±0.018

0.29

±0.027

0.18

±0.016

0.38

±0.036

0.25

±0.023

0.4

±0.038

0.28

±0.026

0.49

±0.046

0.34

±0.031

0.46

±0.043

0.31

±0.028

0.35

±0.038

0.26

±0.037

0.29

±0.040

0.18

±0.026

Cr 7.67

±0.159

3.28

±0.155

6.86

±0.142

3.91

±0.465

8.62

±0.179

5.64

±0.172

10

±0.208

4.27

±0.202

10.38

±0.216

4.95

±0.234

9.25

±0.192

5.88

±0.184

7.36

±0.153

3.09

±0.146

8.11

±0.169

3.41

±0.161

Cu 7.46

±0.045

5.82

±0.094

7.99

±0.629

6.67

±0.107

8.41

±0.487

7.7

±0.124

12.79

±0.077

11.03

±0.177

11.85

±0.072

9.64

±0.895

11.72

±0.779

10.52

±0.169

8.98

±0.054

8.24

±0.376

7.42

±0.996

6.54

±1.249

Fe 73.13

±2.157

61.44

±2.055

66.24

±1.954

54.8

±2.717

70.22

±2.972

64.25

±2.149

85.6

±2.525

77.5

±2.593

97.43

±5.060

80.32

±2.687

89.73

±5.073

84.33

±2.821

75.71

±2.233

57.79

±7.262

66.37

±3.289

57.83

±1.934

Pb 4.08

±0.066

3.97

±0.209

4.71

±0.076

3.59

±0.189

4.92

±0.259

4.43

±0.071

6.23

±0.100

5.11

±0.269

6.28

±0.401

5.94

±0.313

5.42

±0.103

5.40

±0.285

5.85

±0.094

4.53

±0.238

3.92

±0.063

3.30

±0.174

Labeo

roh

ita

Cd 0.26

±0.004

0.19

±0.009

0.21

±0.003

0.17

±0.007

0.27

±0.004

0.24

±0.011

0.29

±0.004

0.2

±0.058

0.38

±0.042

0.29

±0.045

0.39

±0.055

0.3

±0.013

0.26

±0.035

0.22

±0.010

0.32

±0.064

0.24

±0.056

Cr 6.63

±0.649

3.37

±0.194

4.13

±0.141

2.99

±0.172

5.19

±0.178

3.75

±0.216

6.03

±0.206

4.4

±0.253

6.26

±0.214

5.1

±0.293

5.57

±0.191

3.99

±0.230

4.44

±0.152

3.18

±0.183

4.89

±0.167

3.51

±0.202

Cu 7.08

±0.041

5.87

±0.118

6.93

±0.459

6.72

±0.135

8.03

±0.876

7.77

±0.156

12.13

±0.070

11.13

±0.224

11.24

±0.065

8.71

±0.175

10.54

±0.061

10.61

±0.214

8.81

±0.427

8.62

±0.174

7.99

±0.277

7.59

±0.593

Fe 65.8

±2.417

56.45

±0.882

59.61

±2.189

47.6

±0.744

64.19

±6.075

59.03

±0.922

77.03

±2.829

71.21

±1.112

79.67

±4.544

73.79

±1.153

83.54

±3.906

77.48

±1.210

68.12

±2.502

53.91

±3.619

56.12

±2.061

53.13

±0.830

Pb 4.00

±0.230

3.37

±0.213

4.62

±0.265

3.05

±0.193

4.34

±0.249

4.18

±0.264

6.11

±0.351

4.34

±0.274

5.92

±0.397

5.04

±0.318

6.30

±0.361

4.59

±0.290

5.74

±0.329

3.84

±0.243

3.85

±0.221

2.80

±0.177

Catl

a c

atl

a

Cd 0.33

±0.030

0.23±

0.036

0.29

±0.023

0.18

±0.020

0.35

±0.032

0.25

±0.034

0.37

±0.034

0.27

±0.033

0.55

±0.039

0.39

±0.040

0.42

±0.039

0.28

±0.030

0.39

±0.048

0.26

±0.048

0.25

±0.029

0.16

±0.023

Cr 6.54

±0.074

3.68

±0.140

5.92

±0.067

3.26

±0.124

7.22

±0.082

4.09

±0.155

8.47

±0.822

4.79

±0.182

8.82

±0.100

5.56

±0.211

7.79

±0.524

4.35

±0.166

6.31

±0.072

3.47

±0.132

6.77

±0.077

3.82

±0.145

Cu 7.99

±0.500

6.01

±0.233

7.49

±0.537

6.89

±0.267

8.13

±0.422

7.96

±0.308

13.69

±0.998

11.4

±0.636

12.68

±0.997

10.93

±1.343

11.9

±1.019

10.87

±0.674

9.61

±0.469

8.83

±0.342

6.76

±0.533

5.72

±0.222

Fe 83.56

±2.211

66.78

±2.719

75.69

±2.002

56.31

±2.293

78.81

±1.820

69.84

±2.844

97.81

±2.588

84.24

±3.430

88.47

±2.341

87.3

±3.554

93.39

±2.471

91.66

±3.732

86.51

±2.289

51.94

±2.115

71.27

±1.885

62.86

±2.559

Pb 4.36

±0.229

4.23

±0.425

4.89

±0.226

3.83

±0.385

5.25

±0.528

4.59

±0.212

5.46

±0.298

5.45

±0.548

6.43

±0.310

6.33

±0.636

6.66

±0.307

5.76

±0.579

6.07

±0.280

4.82

±0.485

4.07

±0.188

3.52

±0.354

Chapter 4 Results

253


the selected downstream sampling site C (sunder) with standard deviation (SD)

Site C

Fish

Species



Cir

rhin

us

mri

gala

Metals

Zn 82.04

±8.048

56.27

±2.653

74.63

±7.322

54.26

±2.558

96.84

±9.501

67.90

±3.201

104.86

±10.287

69.35

±3.270

120.89

±11.861

79.96

±3.770

114.11

±11.195

75.47

±3.558

90.05

±8.835

64.05

±3.020

70.32

±6.899

46.51

±2.193

Mn 21.67

±1.321

10.96

±1.733

17.58

±1.071

9.97

±1.577

26.98

±1.644

12.93

±2.046

22.73

±1.386

15.24

±2.411

28.49

±1.737

16.15

±2.554

24.55

±1.496

14.01

±2.216

19.25

±1.173

12.28

±1.942

16.52

±1.007

9.39

±1.486

Ni 3.78

±0.025

2.89

±0.141

4.09

±0.027

2.65

±0.130

5.11

±0.034

3.28

±0.161

5.36

±0.036

3.51

±0.172

5.88

±0.039

4.29

±0.210

5.64

±0.038

3.90

±0.191

4.55

±0.030

3.04

±0.149

3.41

±0.023

2.56

±0.125

Hg 3.77

±0.143

2.78

±0.110

1.83

±0.069

1.28

±0.051

4.07

±0.154

3.00

±0.118

3.95

±0.150

3.00

±0.118

5.70

±0.216

4.14

±0.163

5.09

±0.193

3.71

±0.147

3.40

±0.129

2.53

±0.100

2.34

±0.089

1.78

±0.070

Metals

Labeo

roh

ita

Zn 62.61

±1.454

59.74

±1.207

56.96

±1.323

57.60

±1.163

73.91

±1.716

72.08

±1.456

80.03

±1.858

73.62

±1.487

92.27

±2.143

84.88

±1.715

87.09

±2.022

80.12

±1.618

68.73

±1.596

67.99

±1.373

53.67

±1.246

49.37

±0.997

Mn 17.70

±1.146

12.03

±1.348

14.36

±0.930

10.95

±1.227

22.03

±1.427

14.20

±1.592

18.56

±1.202

16.73

±1.876

23.27

±1.507

17.73

±1.987

20.05

±1.298

15.38

±1.724

15.72

±1.018

13.48

±1.511

13.49

±0.874

10.31

±1.156

Ni 3.18

±0.098

2.13

±0.143

3.44

±0.106

1.96

±0.132

4.30

±0.132

2.42

±0.162

4.51

±0.139

2.59

±0.174

4.95

±0.152

3.17

±0.213

4.74

±0.146

2.88

±0.193

3.83

±0.118

2.25

±0.151

2.87

±0.088

1.89

±0.127

Hg 3.56

±0.095

2.73

±0.113

1.73

±0.046

1.26

±0.052

3.85

±0.102

2.94

±0.122

3.74

±0.099

2.94

±0.122

5.39

±0.143

4.06

±0.143

4.82

±0.128

3.64

±0.151

3.22

±0.085

2.48

±0.103

2.22

±0.059

1.75

±0.072

Metals

Catl

a c

atl

a

Zn 65.56

±1.605

61.67

±1.529

59.65

±1.460

59.46

±1.474

77.39

±1.895

74.41

±1.845

83.80

±2.052

76.00

±1.885

96.62

±2.365

87.62

±2.173

91.20

±2.233

82.71

±2.051

71.97

±1.762

70.19

±1.740

56.20

±1.376

50.97

±1.264

Mn 16.48

±1.368

11.73

±0.933

13.37

±1.110

10.67

±0.849

20.51

±1.703

13.84

±1.102

17.28

±1.435

16.31

±1.298

21.66

±1.798

17.28

±1.376

18.67

±1.550

14.99

±1.193

14.63

±1.215

13.14

±1.046

12.56

±1.043

10.05

±0.800

Ni 2.19

±0.042

2.62

±0.068

2.37

±0.045

2.46

±0.064

2.96

±0.057

3.13

±0.081

3.10

±0.059

3.26

±0.085

3.41

±0.065

3.97

±0.103

3.26

±0.062

3.58

±0.093

2.64

±0.050

2.78

±0.072

1.97

±0.038

2.45

±0.064

Hg 3.67

±0.111

2.81

±0.059

1.79

±0.054

1.30

±0.027

3.97

±0.120

3.03

±0.063

3.85

±0.116

3.03

±0.063

5.55

±0.168

4.18

±0.087

4.96

±0.150

3.75

±0.078

3.31

±0.100

2.55

±0.053

2.28

±0.069

1.80

±0.038

Chapter 4 Results

254

Table 4.38 Means of metals (Cd, Cr, Cu, Fe, Pb) concentrations in fish organs of the fish species sampled durign two flow seasons

from the selected downstream sampling site D (head Balloki) with standard deviation (SD).

Site D

Fish

Species



Metals

Cir

rhin

us

mri

gala

Cd 0.24

±0.032

0.13

±0.031

0.17

±0.026

0.13

±0.031

0.24

±0.033

0.16

±0.023

0.31

±0.029

0.2

±0.034

0.36

±0.045

0.25

±0.035

0.32

±0.041

0.23

±0.041

0.19

±0.025

0.16

±0.024

0.22

±0.043

0.15

±0.025

Cr 4.05

±0.612

2.75

±0.094

4.36

±0.167

2.85

±0.336

5.3

±0.350

3.16

±0.475

6.46

±0.262

3.03

±3.03

5.95

±0.555

3.43

±0.131

6.77

±0.295

4.38

±0.129

4.67

±0.196

2.75

±0.382

4.83

±0.130

2.48

±0.080

Cu 5.57

±0.68

4.95

±0.87

6.51

±0.74

5.74

±0.69

8.02

±0.47

6.49

±0.14

6.93

±0.70

6.32

±0.73

9.32

±0.74

8.66

±1.08

9.98

±0.76

8.39

±0.99

7.38

±0.90

6.66

±0.88

6.24

±0.43

6.1

±0.49

Fe 59.46

±3.23

40.55

±3.14

56.75

±4.58

44.4

±5.32

67.9

±3.69

51.48

±5.82

70.6

±4.67

52.13

±3.02

83.41

±5.15

76.02

±4.42

72.7

±4.86

60.07

±4.78

61.84

±2.27

48.51

±3.35

57.25

±3.23

49.64

±1.53

Pb 3.40

±0.18

2.02

±0.09

2.70

±0.15

1.68

±0.08

2.86

±0.13

2.80

±0.15

3.84

±0.21

2.60

±0.12

4.06

±0.22

3.02

±0.14

4.46

±0.24

2.75

±0.13

3.70

±0.20

2.51

±0.12

2.48

±0.13

1.83

±0.09

Labeo

roh

ita

Cd 0.19

±0.08

0.12

±0.04

0.15

±0.03

0.09

±0.02

0.18

±0.03

0.12

±0.02

0.23

±0.05

0.16

±0.03

0.27

±0.07

0.21

±0.05

0.25

±0.05

0.18

±0.04

0.22

±0.03

0.17

±0.04

0.26

±0.05

0.21

±0.05

Cr 3.69

±0.484

2.55

±0.665

3.34

±0.520

2.47

±0.468

3.89

±0.397

2.65

±0.204

3.03

±0.145

2.99

±0.389

5.43

±0.491

3.46

±0.430

4.28

±0.496

3.12

±0.382

3.2

±0.413

2.91

±0.296

3.51

±0.422

2.31

±0.241

Cu 6.73

±0.542

5.33

±0.402

5.87

±0.303

5.72

±0.396

7.85

±0.360

6.47

±0.256

8.43

±0.424

7.8

±0.437

10.53

±0.345

9.64

±0.495

9.61

±0.654

9.36

±0.660

6.57

±0.301

5.64

±0.223

7.37

±0.229

6.78

±0.157

Fe 51.42

±3.730

47.25

±3.483

43.35

±4.027

39.07

±4.126

55.88

±5.866

51.79

±4.966

64.14

±6.226

60.46

±4.829

78.79

±4.644

70.27

±4.859

84.72

±6.939

80.24

±3.440

52.11

±3.853

48.52

±4.459

44.44

±3.976

41.95

±4.471

Pb 3.39

±0.187

2.55

±0.178

2.69

±0.149

2.12

±0.148

3.61

±0.252

2.79

±0.154

3.83

±0.212

3.29

±0.229

4.05

±0.224

3.82

±0.266

4.44

±0.246

3.48

±0.242

3.69

±0.204

3.17

±0.221

2.47

±0.137

2.31

±0.161

Catl

a c

atl

a

Cd 0.28

±0.040

0.19

±0.030

0.13

±0.025

0.1

±0.015

0.22

±0.028

0.17

±0.029

0.34

±0.036

0.26

±0.033

0.29

±0.028

0.24

±0.028

0.21

±0.038

0.16

±0.031

0.24

±0.029

0.18

±0.027

0.24

±0.028

0.2

±0.026

Cr 3.77

±0.357

2.53

±0.339

3.04

±0.517

2.75

±0.439

3.98

±0.586

3.63

±0.519

3.13

±0.442

2.96

±0.090

3.55

±0.386

3.13

±0.350

4.39

±0.291

4.09

±0.198

3.6

±0.322

2.89

±0.321

3.58

±0.204

2.29

±0.260

Cu 6.35

±0.451

5.06

±0.547

6.2

±0.676

5.81

±0.341

7.33

±0.132

6.06

±0.102

7.66

±0.446

6.89

±0.492

9.03

±0.862

8.72

±0.530

7.67

±0.138

6.89

±0.116

6.14

±0.110

5.28

±0.537

7.08

±0.626

6.88

±0.581

Fe 66.35

±2.919

60.69

±2.879

58.53

±5.296

53.61

±2.543

76.12

±3.625

70.8

±3.358

65.56

±3.938

63.38

±0.007

84.5

±3.008

78.55

±3.726

76.68

±3.568

71.81

±3.406

77.47

±5.142

65.74

±3.118

56.94

±3.658

48.89

±2.319

Pb 3.49

±0.237

2.24

±0.562

2.77

±0.189

1.86

±0.468

3.17

±0.795

2.87

±0.196

3.94

±0.268

2.88

±0.724

4.17

±0.283

3.35

±0.841

4.58

±0.311

3.05

±0.766

3.80

±0.258

2.78

±0.698

2.55

±0.173

2.03

±0.509

Chapter 4 Results

255


the selected downstream sampling site D (head Balloki) with standard deviation (SD)

Site D

Fish

Species



Metals

Cir

rhin

us

mri

gala

Zn 57.30

±2.321

39.46

±2.410

48.54

±1.966

43.38

±2.649

69.33

±2.808

60.34

±3.684

67.52

±2.734

48.60

±2.967

71.53

±2.897

63.92

±3.903

70.73

±2.865

55.44

±3.385

53.29

±2.158

51.20

±3.127

41.61

±1.685

37.18

±2.270

Mn 6.42

±1.142

6.32

±0.959

6.05

±1.076

5.75

±0.873

9.82

±1.745

7.46

±1.133

8.33

±1.481

8.07

±1.226

10.40

±1.849

9.31

±1.414

9.02

±1.604

8.79

±1.335

7.91

±1.406

7.08

±1.075

7.06

±1.255

5.41

±0.822

Ni 1.39

±0.046

1.14

±0.041

1.28

±0.043

0.97

±0.035

1.41

±0.047

1.43

±0.052

1.52

±0.050

1.47

±0.053

1.74

±0.058

1.68

±0.061

1.64

±0.054

1.57

±0.057

1.23

±0.041

1.26

±0.045

1.16

±0.038

1.19

±0.043

Hg 1.94

±0.072

1.54

±0.077

1.39

±0.052

1.11

±0.056

3.25

±0.121

2.58

±0.130

4.03

±0.150

3.20

±0.160

3.25

±0.121

2.58

±0.130

4.49

±0.168

3.57

±0.179

2.74

±0.102

2.18

±0.109

3.02

±0.113

2.40

±0.120

Metals

Labeo

roh

ita

Zn 68.84

±1.765

42.53

±1.679

58.31

±1.496

46.75

±1.846

83.29

±2.136

65.02

±2.568

81.11

±2.080

52.37

±2.068

85.94

±2.204

68.89

±2.720

84.97

±2.179

59.75

±2.359

64.01

±1.642

55.18

±2.179

49.98

±1.282

40.07

±1.582

Mn 6.41

±0.119

6.94

±0.115

6.03

±0.112

6.31

±0.104

9.79

±0.181

8.19

±0.136

8.31

±0.154

8.87

±0.147

10.38

±0.192

10.23

±0.169

9.00

±0.167

9.65

±0.160

7.89

±0.146

7.77

±0.129

7.04

±0.130

5.95

±0.098

Ni 1.27

±0.077

0.92

±0.408

1.17

±0.071

0.78

±0.344

1.28

±0.078

1.15

±0.508

1.39

±0.084

1.19

±0.524

1.58

±0.096

1.35

±0.598

1.49

±0.090

1.26

±0.559

1.13

±0.068

1.01

±0.447

1.06

±0.064

0.96

±0.424

Hg 1.96

±0.030

1.51

±0.035

1.41

±0.022

1.09

±0.026

3.29

±0.051

2.54

±0.060

4.07

±0.063

3.15

±0.074

3.29

±0.051

2.54

±0.060

4.54

±0.071

3.51

±0.082

2.77

±0.043

2.14

±0.050

3.05

±0.047

2.36

±0.055

Metals

Catl

a c

atl

a

Zn 58.21

±1.991

42.68

±1.137

49.31

±1.687

46.92

±1.249

70.43

±2.409

65.26

±1.738

68.59

±2.346

52.56

±1.400

72.66

±2.486

69.14

±1.841

71.85

±2.458

59.97

±1.597

54.13

±1.852

55.38

±1.475

42.26

±1.446

40.22

±1.071

Mn 6.30

±0.029

5.47

±0.740

5.94

±0.027

4.98

±0.673

9.64

±0.044

6.46

±0.873

8.18

±0.038

7.00

±0.945

10.21

±0.047

8.07

±1.090

8.86

±0.041

7.61

±1.029

7.76

±0.036

6.13

±0.828

6.93

±0.032

4.69

±0.634

Ni 1.15

±0.030

1.11

±0.025

1.06

±0.028

0.94

±0.021

1.16

±0.031

1.38

±0.032

1.26

±0.033

1.43

±0.033

1.43

±0.038

1.63

±0.037

1.35

±0.036

1.52

±0.035

1.02

±0.027

1.22

±0.028

0.96

±0.025

1.15

±0.026

Hg 1.87

±0.023

1.55

±0.039

1.35

±0.017

1.12

±0.028

3.14

±0.039

2.61

±0.065

3.89

±0.049

3.23

±0.081

3.14

±0.039

2.61

±0.065

4.34

±0.054

3.60

±0.090

2.65

±0.033

2.20

±0.055

2.92

±0.037

2.42

±0.061

Chapter 4 Results

256

Table 4.40 Means of metals concentrations standard error of means (SEM) and significance) in fish organs of sampled fish species

during two flow seasons from the selected sampling sites

Metals

SEM and Significance

S Se Sp T S x Se S x Sp S x T Se x Sp Se x T Sp x T S x Se

x Sp

S x Se

x T

S x Sp

x T

Se x Sp

x T

S x Se

x Sp x

T

Cd 0.001*** 0.001*** 0.001*** 0.002*** 0.002*** 0.002*** 0.004*** 0.002*** 0.003*** 0.003*** 0.003*** 0.005*** 0.006*** 0.005*** 0.009***

Cr 0.010*** 0.007*** 0.009*** 0.016*** 0.015*** 0.018*** 0.031*** 0.013*** 0.022*** 0.027*** 0.025*** 0.044*** 0.054*** 0.038*** 0.076***

Cu 0.017*** 0.012*** 0.014*** 0.025*** 0.024*** 0.029*** 0.050*** 0.020*** 0.035*** 0.043*** 0.041*** 0.071*** 0.087*** 0.061*** 0.123***

Fe 0.144*** 0.102*** 0.125*** 0.216*** 0.204*** 0.249*** 0.432*** 0.176*** 0.305*** 0.374*** 0.353*** 0.611*** 0.748*** 0.529*** 1.058***

Pb 0.011*** 0.007*** 0.009*** 0.016*** 0.015*** 0.018*** 0.032*** 0.013* 0.022*** 0.027* 0.026*** 0.045*** 0.055*** 0.039* 0.077***

Zn 0.126*** 0.089*** 0.109*** 0.190*** 0.179*** 0.219*** 0.379*** 0.155*** 0.268*** 0.328* 0.310*** 0.536*** 0.657** 0.464* 0.929***

Mn 0.037*** 0.026*** 0.032*** 0.056*** 0.053*** 0.065*** 0.112*** 0.046*** 0.079*** 0.097 0.092*** 0.159*** 0.195 0.138 0.275

Ni 0.005*** 0.004*** 0.005*** 0.008*** 0.007*** 0.009*** 0.016*** 0.006*** 0.011*** 0.014*** 0.013*** 0.022*** 0.027*** 0.019*** 0.039***

Hg 0.003*** 0.002*** 0.003*** 0.005*** 0.005*** 0.006*** 0.010*** 0.004*** 0.007*** 0.009 0.008*** 0.014*** 0.017 0.012 0.024


Abrevations:

Site = S; Season=Se; Species=Sp; Fish tissues=T

Chapter 4 Results

257

0

0.1

0.2

0.3

0.4

0.5

0.6

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Siphon Shahdera Sunder Balloki

Sampling Sites

Co

ncen

trati

on

(m

g/K

g)

Skin gills eyes Scales Heart Intestine Liver Kidney

Fig. 4.45 Means of Cd concentrations in different organs of the Cirrhinus mrigala

sampled during the low and high flow seasons from alongstream sites of river Ravi

with their standard deviations (SD)

0

2

4

6

8

10

12

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.46 Means of Cr concentrations in different organs of the Cirrhinus mrigala



Chapter 4 Results

258

0

2

4

6

8

10

12

14

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.47 Means of Cu concentrations in different organs of the Cirrhinus mrigala



0

20

40

60

80

100

120

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.48 Means of Fe concentrations in different organs of the Cirrhinus mrigala



Chapter 4 Results

259

0

1

2

3

4

5

6

7

8

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.49 Means of Pb concentrations in different organs of the Cirrhinus mrigala



0

20

40

60

80

100

120

140

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trait

on

(m

g/k

g)


Fig. 4.50 Means of Zn concentrations in different organs of the Cirrhinus mrigala



Chapter 4 Results

260

0

5

10

15

20

25

30

35

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(mg

/Kg

)


Fig. 4.51 Means of Mn concentrations in different organs of the Cirrhinus mrigala



0

1

2

3

4

5

6

7

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.52 Means of Ni concentrations in different organs of the Cirrhinus mrigala



Chapter 4 Results

261

0

1

2

3

4

5

6

7

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.53 Means of Hg concentrations in different organs of the Cirrhinus mrigala



Chapter 4 Results

262

0.0

0.1

0.2

0.3

0.4

0.5

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Meta

ls c

on

cen

trati

on

s (

mg

/kg

)


Fig. 4.54 Means of Cd concentrations in different organs of the Labeo rohita sampled

during the low and high flow seasons from alongstream sites of river Ravi with their

standard deviations (SD).

0

1

2

3

4

5

6

7

8

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Meta

ls c

on

cen

trati

on

s (

mg

/kg

)


Fig. 4.55 Means of Cr concentrations in different organs of the Labeo rohita sampled


standard deviations (SD)

Chapter 4 Results

263

2

4

6

8

10

12

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

meta

l co

ncen

trati

on

(m

g/k

g)


Fig. 4.56 Means of Cu concentrations in different organs of the Labeo rohita sampled



10

30

50

70

90

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Meta

l co

ncen

trati

on

(m

g/k

g)


Fig. 4.57 Means of Fe concentrations in different organs of the Labeo rohita sampled



Chapter 4 Results

264

0

1

2

3

4

5

6

7

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Meta

l co

ncen

trati

on

(m

g/k

g)


Fig. 4.58 Means of Pb concentrations in different organs of the Labeo rohita sampled



10

25

40

55

70

85

100

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Meta

l co

ncen

trati

on

(m

g/k

g)


Fig. 4.59 Means of Zn concentrations in different organs of the Labeo rohita sampled



Chapter 4 Results

265

0

1

2

3

4

5

6

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Meta

l co

ncen

trati

on

(m

g/k

g)


Fig. 4.60 Means of Mn concentrations in different organs of the Labeo rohita



0

1

2

3

4

5

6

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

meta

ls c

on

cen

trati

on

s (

mg

/kg

)


Fig. 4.61 Means of Ni concentrations in different organs of the Labeo rohita sampled



Chapter 4 Results

266

0

1

2

3

4

5

6

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

meta

ls c

on

cen

trati

on

s (

mg

/kg

)


Fig. 4.62 Means of Hg concentrations in different organs of the Labeo rohita sampled



Chapter 4 Results

267

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.63 Means of Cd concentrations in different organs of the Catla catla sampled



0

2

4

6

8

10

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.64 Means of Cr concentrations in different organs of the Catla catla sampled



Chapter 4 Results

268

0

2

4

6

8

10

12

14

16

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling sites

Co

ncen

trati

on

(m

g/k

g)


Fig. 4.65 Means of Cu concentrations in different organs of the Catla catla sampled



0

20

40

60

80

100

120

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.66 Means of Fe concentrations in different organs of the Catla catla sampled



Chapter 4 Results

269

0

1

2

3

4

5

6

7

8

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.67 Means of Pb concentrations in different organs of the Catla catla sampled



0

20

40

60

80

100

120

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.68 Means of Zn concentrations in different organs of the Catla catla sampled



Chapter 4 Results

270

0

5

10

15

20

25

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.69 Means of Mn concentrations in different organs of the Catla catla sampled



0.0

1.0

2.0

3.0

4.0

5.0

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling Sites

Co

ncen

trati

on

(m

g/K

g)


Fig. 4.70 Means of Ni concentrations in different organs of the Catla catla sampled



Chapter 4 Results

271

0

1

2

3

4

5

6

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow

Low

flow

High

flow


Sampling sites

co

ncen

trati

on

(m

g/K

g)


Fig. 4.71 Means of Hg concentrations in different organs of the Catla catla sampled



Chapter 4 Results

272

4.6.4 Metals accumulaion in muscle of the fishes:

Table 4.41 shows macro elements mean concentration in mg/Kg of freeze dried

muscle of C. mrigala, L. rohita and C. catla collected from four different sites during two

flow seasons of the river Ravi. All macro elements (Ca, Mg, K, Na, P) showed significant

differences among sites, seasons and the fish species (table 4.41).

The mean highest concentrations of Ca (14032 mg/kg), K (3953 mg/kg), Na (5190

mg/kg), Mg (667 mg/kg), P (10079 mg/kg) were measured at site C. The values of 10042,

6736 and 3793 mg/kg for Ca; 3682, 3314 and 2796 mg/kg for K; 4446, 3873 and 3171

mg/kg for Na; 601, 624 and 573 mg/kg for Mg; and 8319, 6768 and 5323 mg/kg for P

were recorded at sites B, D and A, respectively. Mean concentration of Ca (10663

mg/kg), K (3607 mg/kg), Na (4515 mg/kg), Mg (659 mg/kg) and P (8513 mg/kg) during

low flow season were higher than their respective values i.e., 6638, 3266, 3825, 573 and

6732 mg/kg for Ca, K, Na, Mg and P during high flow season. The accumulation pattern

among the sites was site C > site B>site D> site A, excepting the Mg. The order of mean

concentration of these element was Ca>P>Na>K>Mg (table 4.41).

The highest mean concentrations up to 9887 mg/kg for Ca, 3485 mg/kg for K,

4372 mg/kg for Na and 8179 mg/kg for P, while lowest 576 mg/kg for Mg were measured

in C. catla among the three fish species. The highest mean concentration 639 mg/kg for

Mg but lowest 3394 mg/kg for K appeared in muscles of L. rohita. The muscle of C.

mrigala had lowest mean concentrations of Ca (7917 mg/kg), Na (4008 mg/kg) and P

(7271 mg/kg) (table 4.41).

Mean lowest Ca concentrations were measured at site A in C. mrigala (4438 and

3494 mg/kg), L. rohita (4593 and 2785 mg/kg) and C. catla (4562 and 2886 mg/kg)

which increased 2.96, 4.11, 2.20 and 4.11, 2.20, 1.57 folds in C. mrigala, 4.28, 5.38, 2.58

and 2.92, 3.15, 2.46 folds in L. rohita and, 4.78, 9.28, 2.56 and 2.72, 3.47, 2.03 folds in

C. catla at site B, C and D during low and high flow seasons, respectively. Mean Mg

concentration ranged from 572 to 656 mg/kg and 459 to 612 mg/kg, K ranged from 3066

Chapter 4 Results

273

to 4500 mg/kg and 2560 to 3782 mg/kg, Na varied between 3405 to 7502 mg/kg and

2903 to 4555 mg/kg, P ranged between 6005 to 15613 mg/kg and 4724 to 8348 mg/kg of

the fishes’ muscles during low and high flow seasons, respectively (table 4.42).

Heavy metals’ (Cd, Cr, Cu, Pb, Mn, Ni, Zn, Fe) concentrations in the muscles of

C. mrigala, L. rohita and C. catla representing from different sites of the river Ravi are

presented in table 4.43 All the metals showed significant difference among the sites and

seasons. Cadmium, lead and iron showed non significant difference (P>0.05) among fish

species (table 4.45). The mean highest concentrations of Cd (0.13 mg/kg), Cr (3.65

mg/kg), Cu (5.03 mg/kg), Fe (44.59 mg/kg), Pb (2.85 mg/kg), Zn (48.96 mg/kg), Mn

(9.75 mg/kg) and Ni (1.85 mg/kg) were measured at site C. Then 0.03, 0.07 and 0.04

mg/kg of Cd, 0.95, 4.18 and 3.63 mg/kg of Cr, 2.96, 4.18 and 3.63 mg/kg of Cu, 25.64,

30.92 and 37.84 mg/kg of Fe, 0.17, 1.00 and 1.77 mg/kg of Pb, 22.73, 31.89 and 37.54

mg/kg of Zn, 2.25, 3.73 and 5.26 mg/kg ofr Mn and 0.33, 0.47 and 0.80 mg/kg of Ni were

recorded for the sites A, B and D respectively (table 4.44). The metal accumulation

pattern among the sites C > site D > site B > site A, except cadmium, chromium and

copper. The order of mean concentration of these element was Zn > Fe> Mn >Cu > Cr >

Pb > Ni > Cd.

Mean concentrations of Cd (0.07 mg/kg), Cr (2.35 mg/kg), Cu (4.14 mg/kg), Fe

(36.02 mg/kg), Pb (1.61 mg/kg), Zn (37.67 mg/kg), Mn (5.87 mg/kg) and Ni (0.99

mg/kg) appeared higher during low flow than the respective values of Cd (0.06 mg/kg),

Cr (1.64 mg/kg), Cu ( 3.76 mg/kg), Fe (33.47 mg/kg), Pb (1.29 mg/kg), Zn (32.90

mg/kg), Mn (4.62 mg/kg) and Ni (0.74 mg/kg) during the high flow season (table 4.44).

The highest mean concentrations of 0.07 mg/kg for Cd, 4.00 mg/kg for Cu, 37.05

mg/kg for Zn, 0.87 mg/kg for Ni while lowest values of 34.35 mg/kg for Fe, 5.11 mg/kg

for Mn were determined in C. mrigala. The highest mean concentrations up to 2.19

mg/kg for Cr, 35.38 mg/kg for Fe, 1.50 mg/kg for Pb whereas lowest contents of 34.16

mg/kg for Zn and 0.83 mg/kg for Ni were measured in C. catla. The lowest accumulation

Chapter 4 Results

274

of1.81 mg/kg of Cr, 3.86 mg/kg of Cu, 1.41 mg/kg of Pb while highest concentrations of

5.39 mg/kg for Mn and 0.89 mg/kg for Ni appeared in the muscles of L. rohita among

three fish species (table 4.44).

However, site x season x fish species interactions gave, in general, non significant

(P>0.05) differences, except for the Cr, Mn, Zn and Fe (table 4.46). Among the analyzed

metals, the fishes’ muscles showed highest concentrations of Zn (71.12 mg/Kg) while

lowest of Cd (0.07 mg/Kg). The order of metal bioaccumulation in fishes’ muscle was

zinc > iron > manganese > chromium > copper > lead > nickel > cadmium. Muscles of

the C. mrigala, L. rohita, C. catla sampled from site C accumulated Cd up to 434, 300

and 467 %, Cr (323, 282 and 438 %), Cu (72, 65 and 77 %), Pb (1656, 1450 and 1626

%), Mn (299, 336 and 374 %), Ni (473, 620 and 386 %), Zn (116, 121 and 122 %) and Fe

(58, 75 and 78 %) as compared with the corresponding metals’ levels found for the

respective fish species collected from the upstream site (A) during low flow season (table

4.44). Lowest Pb concentrations were measured at site A in C. mrigala (0.18 and 0.14

mg/kg), L. rohita (0.20 and 0.15 mg/kg) and C. catla (0.19 and 0.18 mg/kg) which

increased up to 7.36, 22.57 and 14.29 folds and 6.71, 18.86 and 9.71 folds in C. mrigala,

7.13, 20.67 and 13.20 folds and 6.60, 13.93 and 11.40 folds in L. rohita, 5.94, 18.22 and

11.39 folds and 5.17, 15.78 and 8.33 folds in C. catla at the sites B, C and D during low

and high flow seasons, respectively (table 4.45).

Chapter 4 Results

275

Table 4.41 Mean macro elements concentration in muscles for sampling sites, flow

seasons and fish species with their standard error of means (SEM) and significance

(P)

Ca K Na Mg P

Sampling sites

Site A: Siphon (Control) 3793d 2796

d 3171

d 573

d 5323

d

Site B: Shahdera 10042b

3682b

4446b 601

c 8319

b

Site C: Sunder 14032a

3953a

5190a

667a

10079a

Site D: Head Balloki 6736c

3314c

3873c

624b 6768

c


Seasons

High 6638b 3266

b 3825

b 573

b 6732

b

Low 10663a

3607a 4515

a 659

a 8513

a


Species

Cirrhinus mrigala 7917b 3430a 4008b 633a 7271b

Labeo rohita 8149b 3394a 4131ab 639a 7417b

Catla catla 9887a 3485a 4372a 576b 8179a

SEM and Significance 96.24*** 41.18 76.41** 4.89*** 91.52***

Values within the same column earmarked with same superscripit did not differ

significantly from each other (P>0.05)

Here *,** and *** represent significance at P<0.05, P<0.01 and P<0.001 respectively

(Minitab 16 General linear model)

Chapter 4 Results

276

Table 4.42 Mean macro elements’ bioaccumulation (mg/Kg dried weight) in muscles of three fish species sampled from different

alongstream locations (siphon (upstream) = A; Shahdera= B; Sunder=C; and head balloki =D) during low and high flow seasons.

Fish

species Elements A B C D SEM with Significance

Low High Low High Low High Low High Site x Season

Cirrhinus

mrigala

Ca 4438ef 3494

f 10331

b 8260

cd 14356

a 9311

bc 7670

d 5472

e 221.02***

Mg 666a 580

b 671

a 567

b 696

a 603

b 678

a 607

b 8.68

K 2968cd

2802d 3798

ab 3653

abc 3912

a 3770

ab 3381

abcd 3160

bcd 133.31

Na 3207de

2904e 4613

ab 4306

abc 4877

a 4344

abc 4005

bc 3803

cd 126.34

P 5535ef 4775

f 8602

ab 7621

bcd 9830

a 8348

bc 7104

cd 6356

de 233.54

Labeo

rohita

Ca 4593f 2785

g 11910

b 8126

cd 14991

a 8759

c 7176

de 6852

e 219.50***

Mg 649b 511

c 644

b 637

b 793

a 671

b 659

b 548

c 13.73 **

K 3128c 2253

d 3894

a 3450

bc 4017

a 3740

ab 3354

bc 3316

bc 78.13**

Na 3790c 2820

d 4638

b 4249

bc 5526

a 4338

bc 3846

c 3841

c 129.53**

P 6194cd

4707d 9118

b 7588

c 10703

a 7631

bc 6698

c 6696

c 270.87**

Catla

catla

Ca 4562ef 2886

f 13782

b 7843

d 26769

a 10006

c 7382

d 5866

de 353.92***

Mg 571.7ab

458.7c 600.7

a 485.5

bc 626.8

a 612.3

a 656.3

a 594.9

a 17.58

K 3066cd

2560d 3900

ab 3398

bc 4500

a 3782

abc 3365

bc 3309

bc 129.74

Na 3405bc

2903c 4841

b 4029

bc 7502

a 4555

bc 3934

bc 3811

bc 327.70*

P 6005de

4724e 9686

b 7300

cd 15613

a 8348

bc 7064

cd 6690

d 270.36***



Chapter 4 Results

277

Table 4.43 Mean Standard error of means (SEM) with significance P indicated by *, ** and *** represent significance at P<0.05,

P<0.01 and P<0.001 respectively for minerals concentration in muscles of selected fish species from four river sampling sites with

two flow seasons.

Macro

element

SEM and Significance

S Se Sp S x Se S x Sp Se x Sp S x Se x Sp

Ca 111.128*** 78.580*** 96.240*** 157.159*** 192.480*** 136.104*** 272.208***

Mg 5.642*** 3.989*** 4.886*** 7.978 9.771*** 6.909 13.819***

K 47.555*** 33.627*** 41.184 67.254* 82.368 58.243 116.486

Na 88.231*** 62.389*** 76.410** 124.777*** 152.821** 108.060** 216.121**

P 105.674*** 74.723*** 91.516*** 149.445*** 183.033*** 129.424*** 258.847***

Chapter 4 Results

278

Table 4.44 Mean heavy metals concentration in muscles concentration in muscles for sampling sites, flow seasons and fish species

with their standard error of means (SEM) and significance (P).

Cd Cr Cu Fe Pb Zn Mn Ni

Sampling sites

Site A: Siphon (Control) 0.03c 0.95

d 2.96

d 25.64

d 0.17

d 22.73

d 2.25

d 0.33

c

Site B: Shahdera 0.07b

2.04b

4.18c 30.92

c 1.00

c 31.89

c 3.73

c 0.47

c


3.65a

5.03a

44.59a

2.85a

48.96a

9.75a 1.85

a

Site D: Head Balloki 0.04c

1.35c

3.63b

37.84b 1.77

b 37.54

b 5.26

b 0.80

b


Seasons

High 0.06b 1.64

b 3.76

b 33.47

b 1.29

b 32.90

b 4.62

b 0.74

b

Low 0.07a

2.35a 4.14

a 36.02

a 1.61

a 37.67

a 5.87

a 0.99

a


Species

Cirrhinus mrigala 0.07a 1.99

b 4.00

a 34.35

a 1.43

a 37.05

a 5.11

b 0.87

a

Labeo rohita 0.06a 1.81

c 3.86

c 34.51

a 1.41

a 34.63

ab 5.39

a 0.89

a


a 3.98

ab 35.38

a 1.50

a 34.16

b 5.24

ab 0.83

a

SEM and Significance 0.003 0.028*** 0.039* 0.341 0.056 0.699* 0.055** 0.040



Chapter 4 Results

279

Table 4.45 Mean heavy metals (mg/Kg dried weight) bioaccumulation in muscles of three fish species sampled from different

alongstream locations (siphon (upstream) = A; Shahdera= B; Sunder=C; and head balloki =D) during low and high flow seasons.

Fish species Element A B C D SEM with Significance

Low High Low High Low High Low High Site x Season

Cirrhinus

mrigala

Cd 0.03bc

0.03c 0.08abc

0.07bc

0.16a 0.11

ab 0.04

bc 0.04

bc 0.014

Cr 1.06fg

0.88g 2.13bc

1.96cd

4.48a 2.54

b 1.54

de 1.33

ef 0.075***

Cu 3.04f 2.99f 4.41

bc 4.09

cd 5.24

a 4.79

b 3.90

de 3.55

e 0.068

Pb 0.18e 0.14e 1.03de 0.94

cde 3.16

a 2.64

ab 2.00

bc 1.36

cd 0.189

Mn 2.56e 2.50

e 4.29

cd 3.23

de 10.22

a 6.70

b 6.40

b 4.99

c 0.223***

Ni 0.37d 0.29

d 0.46

d 0.44

d 2.12

a 1.52

b 1.00

c 0.78

c 0.056**

Zn 27.94 24.57 34.78 31.96 60.38 43.52 38.28 34.97 3.341

Fe 27.31d 21.83

e 31.44

c 30.63

c 43.24

a 42.11

ab 39.36

b 38.87

b 0.591**

Labeo rohita Cd 0.03de

0.03e 0.07

c 0.06

c 0.12

a 0.10

b 0.04

d 0.04

de 0.002*

Cr 1.02de

0.71e 2.30

b 1.68

c 3.90

a 2.34

b 1.36

cd 1.16

de 0.089***

Cu 3.02c 2.62

c 4.22

b 4.10

b 4.98

a 4.71

ab 4.00

b 3.27

c 0.128

Pb 0.20e 0.15

e 1.07

cd 0.99

d 3.10

a 2.09

b 1.98

b 1.71

bc 0.118*

Mn 2.55e 1.80

f 4.33

d 4.09

d 11.11

a 8.73

b 5.31

c 5.23

c 0.071***

Ni 0.36c 0.30

c 0.51

bc 0.39

c 2.59

a 1.47

b 0.90

bc 0.60

bc 0.187

Zn 22.02g 21.34

g 32.17

e 29.28

f 48.65

a 45.39

b 42.72

c 35.52

d 0.373***

Fe 27.28d 23.53

e 29.88

d 29.61

d 47.83

a 42.02

b 38.81

bc 37.12

c 0.619*

Catla catla Cd 0.03e 0.03

e 0.07

c 0.06

cd 0.17

a 0.11

b 0.04

de 0.04

de 0.005***

Cr 1.06e 0.96

e 2.22

c 1.93

c 5.70

a 2.93

b 1.49

d 1.21

de 0.075***

Cu 3.20de

2.87e 4.21

bc 4.07

c 5.65

a 4.79

b 3.79

cd 3.27

de 0.123

Pb 0.19ef 0.18

f 1.07

de 0.93

def 3.28

a 2.84

ab 2.05

bc 1.50

cd 0.157

Mn 2.62f 1.44

g 3.40

e 3.06

ef 12.42

a 9.34

b 5.23

c 4.38

d 0.130***

Ni 0.37ef 0.28

f 0.58

d 0.45

de 1.80

a 1.61

b 0.79

c 0.73

c 0.025

Zn 22.68e 17.85

f 34.65

c 28.52

d 50.41

a 45.45

b 37.35

c 36.40

c 0.640*

Fe 27.95de

25.93e 31.12

cde 32.81

cde 49.85

a 42.50

ab 38.17

bc 34.73

bcd 1.434

Chapter 4 Results

280

Table 4.46 Mean Standard error of means (SEM) with significance P indicated by *, ** and *** represent significance at P<0.05,

P<0.01 and P<0.001 respectively for metals concentration in muscles of selected fish species from four river sampling sites with two

flow seasons.

Metals SEM and Significance


Cd 0.004*** 0.002*** 0.003 0.005** 0.006 0.004 0.009

Cr 0.033*** 0.023*** 0.028*** 0.046*** 0.056*** 0.040* 0.080***

Cu 0.045*** 0.032*** 0.039* 0.063* 0.077 0.055 0.110

Pb 0.064*** 0.045*** 0.056 0.091** 0.111 0.079 0.158

Mn 0.063*** 0.045*** 0.055** 0.089*** 0.109*** 0.077** 0.154**

Ni 0.046*** 0.033*** 0.040 0.066** 0.081 0.057 0.114

Zn 0.807*** 0.570*** 0.699* 1.141 1.397 0.988 1.976*

Fe 0.394*** 0.278*** 0.341 0.557** 0.077** 0.055 0.110*

Abbrevations: Sampling Sites=S; FlowSeasons=Se; Fish Species=Sp;

Chapter 4 Results

281

4.7 Fatty acid profiles of the fishes muscles:

Means of fatty acid composition in muscles of the carp species and effects of sampling

sites, flow seasons and the sampled fish species in this regard are presented in tables 4.47 to

4.60. The analysis showed significant differences (P<0.001) among the sites, seasons and

fish species in terms of fatty acid composition viz., total saturated fatty acid (Total SFA),

total monounsaturated fatty acids (total MUFA), total polyunsaturated fatty acids (total

PUFA), total omerga (ω)3, total ω6, and ω3/ω6 ratio of fatty acids (table 4.57).

For the fishes muscles, total SFA were higher than total MUFA and total PUFA. The

highest total SFA (57.09 %) were found at site C than B (54.75 %), D (53.52 %) and A

(50.85 %) whereas reverse order was found for total PUFA at site C (5.98 %) followed by D

(7.36 %), B (8.90 %) and A (11.87 %). The total MUFA were 37.29 % higher at site A than

36.93 % (site C), 36.35 % (site B) and 39.19 % (site D). The total ω3 (4.57 %, 3.48 %, 2.01

% and 2.46 %) long chain PUFA were found lesser than total ω6 long chain PUFA (7.15 %,

5.25 %, 3.87 % and 4.58 %) at the sites A, B, C, D respectively (table 4.47).

The total SFA were higher (54.18 %) during low flow than high flow (53. 18 %) season

of the river while total PUFA, ω3, ω 6 and ω3/ω6 appeared in lesser amounts during low

flows compared to the high flow season (table 4.47). The total MUFA remained unaffected to

the effects of seasons.

Among fish species, C. catla showed lowest total PUFA (7.37 %), ω6 (4.09 %) and

highest total SFA (57.79 %), ω3/ω6 ratio (0.70) whereas C. mrigala showed highest total

MUFA (42.76 %) and lowest total SFA (48.76 %), ω3 (2.65 %) and ω3/ ω6 ratio (0.47 %). L.

rohita showed highest total PUFA (9.72 %), ω3 (3.63 %), ω6 (5.85 %) and lowest total

MUFA (34.67 %) among the three fish species (table 4.47).

Chapter 4 Results

282

Table 4.57 presents the site x season x fish species interactions for the total SFA, total

MUFA, total PUFA, total ω3, total ω6, and ω3/ω6 fatty acids. All parameters showed

significant (P<0.001) interactions.

In the present investigation, 12 SFA, 15 MUFA and 11 PUFA were detected in muscles

of the fish species. The mean highest total SFA were found in the muscle of C. catla (68.58

and 53.06 %) at site C (table 4.55, Fig. 4.74) as compared to the values for L. rohita (53.03

and 60.81 %) and C. mrigala (51.69 and 55.37 %) during high and low flow seasons,

respectively. Among the SFAs the most abundant were palmitic, stearic and myristic acids.

Palmitic acid was predominant fatty acid in the carps muscles and comprised upto 66.84 %,

62.92 % and 61.79 % of total SFA in C. mrigala, L. rohita and C. Catla, respectively (tables

4.47 to 4.55). Total MUFA contents showed non-significant difference (P>0.05) among the

river Ravi flow seasons. Oleic and palmitoleic acids dominated among MUFA in all the fish

species. Oleic acid was highest MUFA and comprised upto 50.37 %, 46.93 %, 50.72 % of

total MUFA in C. mrigala, C. catla and L. rohita, respectively. The mean range of total

MUFA in muscles of the C. mrigala, L. rohita and C. catla appeared from 38.21-49.60 %,

33.75-37.68 %, and 28.81-43.88 %, respectively of the total fatty acids (tables 4.47 to 4.56).

Total and all PUFA showed significant differences for the sampling sites, flow seasons,

fish species and site x season x fish species interaction. C. catla showed highest (15.29 and

15.29 %) total PUFA at site A in comparison with L. rohita (12.18 % and 10.91 % and C.

mrigala (10.91 and 10.22 %) during high and low flow seasons, respectively. Decreasing

trend of total PUFA appeared responsive to the downstream locations up to the site C. Total

PUFA decreased downstream up to 10.76 and 9.85 % for L. rohita, 9.64 and 8.12 % for C.

mrigala and 7.71 and 7.30 % for C. catla at site B. While at site C reductions up to 9.28 and

5.46 % for L. rohita, 7.51 and 6.14 % for C. mrigala and 4.43 and 3.05 % for C. catla were

recorded respectively for high and low flow seasons (tables 4.47 to 4.56). These reductions in

Chapter 4 Results

283

the total PUFA, more or less, stabilized at site D as total PUFA measured for this site in

muscles of L. rohita (10.21 and 9.14 %), C. mrigala (8.56 and 6.70 %) and C. catla (6.15 and

3.39 %) showed a recovery trend as compared to the value obtained for the site C during high

and low flow seasons, respectively. Linleic and α-linolenic acids were higher among PUFA

(Fig. 4.72 to 4.74). The mean percentage of ω3 PUFA tended to be higher in L. rohita (4.12

and 3.15 %) than in C. catla (3.69 and 2.52 %) and C. mrigala (2.82 and 2.39 %) during high

and low flow seasons, respectively. Whereas ω6 PUFA content was highest in L. rohita (5.85

%) and lowest in C. catla (4.09 %). Higher ω3/ ω6 ratio (0.70) was observed in C. catla than

L. rohita (0.61) and C. mrigala (0.47).

Chapter 4 Results

284

Table 4.47 Means of total fatty acid composition of muscles with standard error of means (SEM) and significance for

sampling sites, flow seasons and fish species.

SFA MUFA PUFA ω3 ω6 ω3/ ω6

Sampling sites

Site A: Siphon (Control) 50.85d

37.29b

11.87a

4.57a

7.15a

0.64b

Site B: Shahdera 54.75b

36.35c

8.90b

3.48b

5.25b

0.68a


36.93b

5.98d

2.01d

3.87d

0.53c

Site D: Head Balloki 53.52c

39.19a

7.36c

2.46c

4.58c

0.53c


Seasons

High 53.18b

37.44a

9.39a

3.58a 5.65

a 0.63

a

Low 54.93a

37.44a

7.66b

2.69b

4.77b

0.56b

SEM and Significance 0.077*** 0.067 0.061*** 0.041*** 0.036*** 0.007***

Fish Species

Cirrhinus mrigala 48.76c

42.76a

8.48b

2.65c

5.68b

0.47c

Labeo rohita 55.60b

34.67b

9.72a

3.63a

5.85a

0.61b


b 7.37

c 3.11

b 4.09

c 0.70

a




Abbrevations:

SFA=saturated fatty acid; MUFA=Monounsaturated fatty acid; PUFA=polyunsaturated fatty acid; ω = omega

Chapter 4 Results

285

Table 4.48 Mean fatty acid profiles of Cirrhinus mrigala (Mori) for four

downstream river flow sites (Siphon = A; Shahdera = B; Sunder = C and Balloki =

D) with standard error of means (SEM) and significance (P)

Fatty acid Sampling Sites

SEM P A B C D

Saturated fatty acids (SFA)

C:12:0 Lauric 0.04c 0.26

a 0.25

a 0.23

b 0.004 0.000

C:13:0 Tridecanoate 0.06d 0.34

b 0.39

a 0.26

c 0.007 0.000

C:14:0 Myristic 2.76d 6.79

a 5.10

b 3.91

c 0.085 0.000

C:15:0 Pentadecanoic 0.78d 3.91

a 2.96

b 2.13

c 0.044 0.000

C:16:0 Palmitic 30.11b 31.09

b 34.65

a 34.52

a 0.286 0.000

C:17:0 Heptadecanoic 1.45c 2.08

b 2.49

a 1.95

b 0.028 0.000

C:18:0 Stearic 4.06d 4.50

c 6.02

a 4.90

b 0.072 0.000

C:19:0 0.30c 0.46

a 0.44

a 0.34

b 0.008 0.000

C:20:0 Arachidic 0.25d 0.43

c 0.53

a 0.47

b 0.006 0.000

C:22:0 Behenic 0.11d 0.34

a 0.19

b 0.17

c 0.004 0.000

C:23:0 Tricosanoic 0.71b 1.11

a 0.43

c 0.21

d 0.010 0.000

C:24:0 Lignoceric 0.15b 0.31

a 0.09

c 0.07

d 0.003 0.000

Monounsaturated fatty acid (MUFA)

C:14:1 Myristoleic 0.39d 1.16

b 1.32

a 1.06

c 0.013 0.000

C:15:1 Cis-10 pentadecanoic 0.45c 0.89

a 0.89

a 0.56

b 0.006 0.000

C:16:1t9 0.25c 0.27

c 0.44

a 0.40

b 0.005 0.000

C:16:1 Palmitoleic 12.52a 10.86

b 8.63

c 7.75

d 0.162 0.000

C:17:1 Cis-10 Heptadecanoic 0.98d 2.10

a 1.22

c 1.30

b 0.013 0.000

C:18:1t9 Elaidic 0.33c 0.53

b 0.76

a 0.35

c 0.016 0.000

C:18:1t11Vaccinic 0.000 0.12a 0.10

ab 0.06

b 0.004 0.000

C:18:1 Oleic 26.68a 16.47

c 18.44

d 24.95

b 0.220 0.000

C:18:1c11 4.45d 5.12

b 5.51

a 4.83

c 0.058 0.000

C:19:1 0.29a 0.05

b 0.000 0.06

b 0.004 0.000

C:20:1 5 Eicosonoic 0.06d 0.16

c 0.30

a 0.18

b 0.003 0.000

C:20:1 8 Eicosonoic 0.46b 0.27

c 0.53

a 0.28

c 0.010 0.000

C:20:1 11Eicosonoic 1.50a 1.23

b 1.30

b 1.13

c 0.018 0.000

C:22:1 Erucic 0.25ab

0.27a 0.21

c 0.24

b 0.004 0.000

C:24:1 Nervoniv 0.06a 0.04

b 0.01

c 0.05

a 0.002 0.000

Polyunsaturated fattyacids (PUFA) C:18:2 Linolelaidic 0.20

a 0.13

b 0.11

c 0.14

b 0.003 0.000

C:18:2 Linoleic ((LA) ω6 4.79a 3.23

c 3.06

d 3.98

b 0.026 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.26b 0.28

a 0.14

c 0.14

c 0.003 0.000

C:18:3 alpha-linolenic ω3 1.37ab

1.31b 1.22

c 1.45

a 0.020 0.000

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.35c 0.38

b 0.44

a 0.37

d 0.004 0.000

C:20:3 Cis-8, 11, 14 Eicosatrienoic (hGLA) ω 6 0.48a 0.29

b 0.15

d 0.20

c 0.002 0.000


a 0.710

b 0.52

c 0.012 0.000

C:20:4 Arachidonic ω 6 0.17b 0.22

a 0.15

c 0.08

d 0.004 0.000

C:20:5 Eicosapentaenoic (EPA) ω 3 0.04ab

0.04a 0.03

b 0.02

c 0.001 0.000

C:22:5 Docosapentanoic (DOA) ω 3 0.48a 0.43

b 0.24

c 0.16

d 0.004 0.000

C:22:6 Docosahexaenoic (DHA) ω 6 1.17b 1.24

a 0.58

d 0.65

c 0.006 0.000

Values within the same row earmarked with same superscript did not differ significantly


Chapter 4 Results

286

Table 4.49 Fatty acid profiles of Cirrhinus mrigala (Mori) for two flow season of

river Ravi with standard error of means (SEM) and significance (P)

Fatty acids Flow Season

SEM P Low High


C:12:0 Lauric 0.21 0.19 0.003 0.000

C:13:0 Tridecanoate 0.30 0.19 0.005 0.000

C:14:0 Myristic 4.83 4.56 0.060 0.002

C:15:0 Pentadecanoic 2.58 2.25 0.031 0.000

C:16:0 Palmitic 33.53 32.88 0.202 0.000

C:17:0 Heptadecanoic 2.00 1.88 0.020 0.436

C:18:0 Stearic 5.05 4.69 0.051 0.001

C:19:0 0.43 0.39 0.005 0.000

C:20:0 Arachidic 0.41 0.36 0.004 0.082

C:22:0 Behenic 0.25 0.14 0.003 0.000

C:23:0 Tricosanoic 0.43 0.78 0.007 0.000

C:24:0 Lignoceric 0.14 0.18 0.002 0.000

Monounsaturated fatty acids (MUFA)

C:14:1 Myristoleic 0.85 0.90 0.009 0.000

C:15:1 Cis-10 pentadecanoic 0.71 0.72 0.004 0.032

C:16:1t9 0.25 0.25 0.003 0.000

C:16:1 Palmitoleic 9.99 10.56 0.114 0.564

C:17:1 Cis-10 Heptadecanoic 1.26 1.33 0.009 0.000

C:18:1t9 Elaidic 0.52 0.53 0.011 0.006

C:18:1t11Vaccinic 0.08 0.06 0.003 0.575

C:18:1 Oleic 21.17 21.75 0.156 0.003

C:18:1c11 5.27 5.00 0.041 0.000

C:19:1 0.08 0.09 0.003 0.000

C:20:1 5 Eicosonoic 0.11 0.06 0.002 0.000

C:20:1 8 Eicosonoic 0.39 0.38 0.007 0.072

C:20:1 11Eicosonoic 1.16 1.28 0.013 0.000

C:22:1 Erucic 0.17 0.21 0.003 0.000

C:24:1 Nervoniv 0.03 0.04 0.001 0.000

Polyunsaturated fattyacids (PUFA)

C:18:2 Linolelaidic 0.16 0.15 0.002 0.000

C:18:2 Linoleic ((LA) ω6 3.54 3.50 0.019 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.18 0.20 0.002 0.000

C:18:3 alpha-linolenic ω3 1.37 1.34 0.014 0.013

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.32 0.27 0.003 0.000

C:20:3 Cis-8, 11, 14 Eicosatrienoic (hGLA) ω 6 0.23 0.28 0.001 0.000

C:20:3 Cis-11, 14, 17 Eicosatrienoic (hGLA) ω 3 0.73 1.09 0.008 0.000

C:20:4 Arachidonic ω 6 0.14 0.14 0.003 0.000

C:20:5 Eicosapentaenoic (EPA) ω 3 0.03 0.04 0.001 0.001

C:22:5 Docosapentanoic (DOA) ω 3 0.26 0.35 0.003 0.000

C:22:6 Docosahexaenoic (DHA) ω 6 0.84 0.99 0.004 0.000

Values within the same row earmarked with same superscript did not differ significantly


Chapter 4 Results

287

Table 4.50 Mean fatty acid profile of Cirrhinus mrigala (Mori) with standard error

of means (SEM) and significance (P) for four alongstream sites (Siphon = A;

Shahdera = B; Sunder =C and Balloki=D) with two flow season.

Fatty acid Site A Site B Site C Site D SEM P

Low High Low High Low High Low High

Saturated fatty acids (SFA) C:12:0 Lauric 0.04d 0.05d 0.30a 0.21e 0.27b 0.23c 0.25b 0.21c 0.005 0.000

C:13:0 Tridecanoate 0.07e 0.05e 0.54a 0.14d 0.44b 0.34c 0.13d 0.38c 0.010 0.000

C:14:0 Myristic 2.84e 2.68e 7.24a 6.33b 5.41c 4.80c 3.84d 3.99d 0.120 0.010

C:15:0 Pentadecanoic 0.81f 0.74f 4.55a 3.28b 3.07bc 2.85c 1.90e 2.37d 0.062 0.000

C:16:0 Palmitic 30.23de 29.99e 32.27cd 29.92e 35.61ab 33.68bc 36.01a 33.03bc 0.404 0.047

C:17:0 Heptadecanoic 1.74e 1.17f 2.04d 2.11cd 2.62a 2.37bc 1.62e 2.28b 0.040 0.000

C:18:0 Stearic 4.61c 3.51d 4.68c 4.31c 6.14a 5.89b 4.78c 5.02c 0.101 0.001

C:19:0 0.32cd 0.27d 0.50a 0.42b 0.54a 0.34c 0.34c 0.34c 0.011 0.000

C:20:0 Arachidic 0.28d 0.21e 0.49b 0.36c 0.50b 0.57a 0.39c 0.56a 0.008 0.000

C:22:0 Behenic 0.12c 0.11c 0.57a 0.12c 0.19b 0.18b 0.14c 0.20b 0.006 0.000

C:23:0 Tricosanoic 0.73b 0.69b 0.39d 1.83a 0.48c 0.38d 0.14f 0.28e 0.014 0.000

C:24:0 Lignoceric 0.27b 0.04e 0.10c 0.51a 0.12c 0.07d 0.06d 0.08d 0.004 0.000

Monounsaturated fatty acids (MUFA) C:14:1 Myristoleic 0.38e 0.40e 1.08c 1.23b 1.11c 1.53a 0.85d 1.26b 0.018 0.000

C:15:1 Cis-10 pentadecanoic 0.46f 0.43f 0.85c 0.93b 1.03a 0.76d 0.49f 0.64e 0.008 0.000

C:16:1t9 0.25d 0.26cd 0.29c 0.25d 0.23d 0.65a 0.26cd 0.55b 0.007 0.000

C:16:1 Palmitoleic 11.47b 13.57a 10.76b 10.95b 9.27c 7.99c 8.45c 7.04d 0.229 0.000

C:17:1 Cis-10 Heptadecanoic 0.98f 0.99f 1.96b 2.25a 0.85g 1.60c 1.24e 1.35d 0.018 0.000

C:18:1t9 Elaidic 0.30d 0.36d 0.53c 0.52c 0.88a 0.64b 0.37d 0.33d 0.022 0.001

C:18:1t11Vaccinic 0.00 0.00 0.14b 0.10c 0.16ab 0.04d 0.00 0.17a 0.006 0.000

C:18:1 Oleic 26.70a 26.66a 15.29e 17.65d 16.82d 20.07c 25.89a 24.02b 0.311 0.000

C:18:1c11 4.53cd 4.36d 5.58b 4.66cd 6.25a 4.77cd 4.74cd 4.92c 0.082 0.000

C:19:1 0.29a 0.29a 0.04c 0.06c 0.00 0.00 0.00 0.12b 0.005 0.000

C:20:1 5 Eicosonoic 0.07d 0.06de 0.23c 0.08d 0.07d 0.52a 0.04e 0.32b 0.004 0.000

C:20:1 8 Eicosonoic 0.48b 0.45b 0.29c 0.26cd 0.60a 0.45b 0.21d 0.34c 0.013 0.000

C:20:1 11Eicosonoic 1.51a 1.49a 0.99d 1.47ab 1.09cd 1.51a 1.06d 1.20bc 0.026 0.000

C:22:1 Erucic 0.27b 0.24c 0.17d 0.36a 0.15e 0.26bc 0.10f 0.38a 0.005 0.000

C:24:1 Nervoniv 0.05ab 0.06a 0.04c 0.04bc 0.00 0.02d 0.05b 0.06ab 0.002 0.405

Polyunsaturated fattyacids (PUFA) C:18:2 Linolelaidic 0.23a 0.18b 0.13c 0.13c 0.14c 0.08d 0.15c 0.12c 0.004 0.001

C:18:2 Linoleic ((LA) ω6 4.83a 4.76a 3.27d 3.18d 2.56e 3.55c 3.49c 4.47b 0.037 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.27b 0.25b 0.23c 0.34a 0.11f 0.17e 0.09f 0.19d 0.004 0.000

C:18:3 alpha-linolenic ω3 1.27b 1.47a 1.48a 1.15b 1.29b 1.15b 1.44a 1.46a 0.028 0.000

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.33e 0.37d 0.50b 0.26f 0.27f 0.61a 0.19g 0.42c 0.006 0.000 C:20:3 Cis-8, 11, 14 Eicosatrienoic

(hGLA) ω 6 0.49a 0.46b 0.18f 0.41c 0.11h 0.20e 0.16g 0.24d 0.003 0.000

C:20:3 Cis-11, 14, 17 Eicosatrienoic

(hGLA) ω 3 1.14c 1.40b 0.72d 1.92a 0.70d 0.72d 0.35e 0.68d 0.016 0.000

C:20:4 Arachidonic ω 6 0.14de 0.19bc 0.24a 0.21b 0.12e 0.18cd 0.04f 0.12e 0.005 0.000

C:20:5 Eicosapentaenoic (EPA) ω 3 0.02cd 0.05a 0.04ab 0.04a 0.04bc 0.03cd 0.02d 0.03cd 0.002 0.001

C:22:5 Docosapentanoic (DOA) ω 3 0.49b 0.47b 0.24c 0.62a 0.22c 0.26c 0.10d 0.23c 0.005 0.000

C:22:6 Docosahexaenoic (DHA) ω 6 1.02d 1.32b 1.09c 1.39a 0.58e 0.59e 0.68d 0.61e 0.008 0.000

Values within the same row earmarked with same superscripit did not differ significantly


Chapter 4 Results

288

Table 4.51 Mean fatty acid profiles of Labeo rohita (Rohu) for four downstream

river flow sites (Siphon = A; Shahdera = B; Sunder = C and Balloki = D) with

standard error of means (SEM) and significance (P)


SEM P A B C D


C:12:0 Lauric 0.07a

0.09a 0.00 0.09

a 0.007 0.000

C:13:0 Tridecanoate 0.17d

0.20c

0.29b

0.47a

0.003 0.000

C:14:0 Myristic 4.21c

4.08c 5.45

b 8.67

a 0.060 0.000

C:15:0 Pentadecanoic 1.92c

2.19b

2.29b

3.00a

0.027 0.000

C:16:0 Palmitic 35.12b

34.52b 36.84

a 33.49

c 0.152 0.000

C:17:0 Heptadecanoic 2.45b

2.65a

2.59a

2.65a

0.022 0.001

C:18:0 Stearic 8.05b

8.83a

7.76b

5.87c

0.103 0.000

C:19:0 0.47c

0.53a

0.50b

0.51ab

0.006 0.000

C:20:0 Arachidic 0.56b

0.63a 0.56

b 0.51

b 0.012 0.001

C:22:0 Behenic 0.36a

0.24b

0.26b

0.19c

0.006 0.000

C:23:0 Tricosanoic 0.73c 0.79

b 0.27

d 0.86

a 0.010 0.000

C:24:0 Lignoceric 0.12a

0.09c

0.11b

0.08d

0.002 0.000

Monounsaturated fatty acid (MUFA)

C:14:1 Myristoleic 1.35c

1.48ab

1.56a

1.39 0.027 0.002

C:15:1 Cis-10 pentadecanoic 0.55b 0.38

c 0.64

a 0.51 0.009 0.000

C:16:1t9 0.23c

0.31b

0.37a

0.31 0.006 0.000

C:16:1 Palmitoleic 6.78d 8.10

c 9.44

b 9.85 0.064 0.000

C:17:1 Cis-10 Heptadecanoic 1.01b

1.10b

1.01b

1.05 0.098 0.893

C:18:1t9 Elaidic 0.53a

0.42b

0.35c

0.28 0.007 0.000

C:18:1t11Vaccinic 0.14c

0.19a

0.20a

0.17 0.004 0.000

C:18:1 Oleic 16.54a

16.62a

16.13a

15.81 0.169 0.031

C:18:1c11 4.32ab

4.51a

4.14b

3.16 0.058 0.000

C:19:1 0.10a

0.05b

0.05b

0.03 0.002 0.000

C:20:1 5 Eicosonoic 0.04c

0.05c 0.13

b 0.28 0.002 0.000

C:20:1 8 Eicosonoic 0.32a 0.22

b 0.18

c 0.05 0.009 0.000

C:20:1 11Eicosonoic 1.67a

1.06b

1.25b

0.74 0.059 0.000

C:22:1 Erucic 0.55a

0.32b

0.22c

0.29 0.014 0.000

C:24:1 Nervoniv 0.10a

0.02c

0.04b

0.02 0.002 0.000


c 0.21

b 0.09

c 0.53

a 0.005 0.000

C:18:2 Linoleic ((LA) ω6 4.98a 4.44

b 3.57

c 2.72

d 0.057 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.17b

0.16b

0.17b

0.37a

0.004 0.000 C:18:3 alpha-linolenic ω3 2.73

a 2.30

a 1.59

b 1.65

b 0.110 0.000

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.25b

0.22c 0.25

b 0.33

a 0.005 0.000

C:20:3 Cis-8, 11, 14 Eicosatrienoic (hGLA) ω 6 0.22b 0.20

c 0.19

c 0.27

a 0.004 0.000

C:20:3 Cis-11, 14, 17 Eicosatrienoic (hGLA) ω 3 1.16b

1.14b

0.68c

1.46a

0.041 0.000 C:20:4 Arachidonic ω 6 0.18

a 0.14

b 0.11

c 0.12

c 0.004 0.000

C:20:5 Eicosapentaenoic (EPA) ω 3 0.02a

0.01b

0.02a

0.02a

0.001 0.001

C:22:5 Docosapentanoic (DOA) ω 3 0.50b

0.49b

0.21c

0.55a

0.008 0.000 C:22:6 Docosahexaenoic (DHA) ω 6 1.23

b 1.00

c 0.49

d 1.65

a 0.021 0.000



Chapter 4 Results

289

Table 4.52 Fatty acid profiles of Labeo rohita (Rohu) for two flow season of river

Ravi with standard error of means (SEM) and significance (P)

Fatty acid Flow Season

SEM P Low High

Saturated fatty acids (SFA) C:12:0 Lauric 0.09

a 0.03

b 0.005 0.000

C:13:0 Tridecanoate 0.31a

0.26b

0.002 0.000 C:14:0 Myristic 6.38

a 4.83

b 0.043 0.000

C:15:0 Pentadecanoic 2.65a

2.05b

0.019 0.000 C:16:0 Palmitic 33.97

b 36.02

a 0.108 0.000

C:17:0 Heptadecanoic 2.54a

2.63b

0.015 0.004

C:18:0 Stearic 7.79a

7.47b 0.073 0.015

C:19:0 0.53a

0.48b

0.004 0.000 C:20:0 Arachidic 0.61

a 0.52

b 0.008 0.000


0.24b

0.004 0.000 C:23:0 Tricosanoic 0.70

a 0.63

b 0.007 0.000

C:24:0 Lignoceric 0.10a 0.10

a 0.002 0.063

Monounsaturated fatty acids (MUFA)

C:14:1 Myristoleic 1.57 1.32 0.019 0.000

C:15:1 Cis-10 pentadecanoic 0.61 0.43 0.006 0.000

C:16:1t9 0.26 0.35 0.004 0.000

C:16:1 Palmitoleic 9.16 7.92 0.045 0.000

C:17:1 Cis-10 Heptadecanoic 1.08 1.01 0.069 0.462

C:18:1t9 Elaidic 0.43 0.36 0.005 0.000

C:18:1t11Vaccinic 0.17 0.18 0.003 0.015

C:18:1 Oleic 16.25 16.29 0.120 0.816

C:18:1c11 3.86 4.20 0.041 0.000 C:19:1 0.03 0.08 0.002 0.000 C:20:1 5 Eicosonoic 0.14 0.11 0.002 0.000

C:20:1 8 Eicosonoic 0.22 0.16 0.006 0.000

C:20:1 11Eicosonoic 1.03 1.33 0.042 0.001

C:22:1 Erucic 0.32 0.37 0.010 0.003

C:24:1 Nervoniv 0.06 0.03 0.001 0.000


a 0.21

b 0.004 0.000

C:18:2 Linoleic ((LA) ω6 3.66b

4.19a 0.040 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.22a

0.22a

0.003 0.603

C:18:3 alpha-linolenic ω3 1.66b

2.48a 0.077 0.000

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.23b

0.30a 0.004 0.000


0.25a 0.003 0.000


1.20a

0.029 0.003

C:20:4 Arachidonic ω 6 0.10b

0.17b 0.003 0.000


0.02a 0.001 0.007

C:22:5 Docosapentanoic (DOA) ω 3 0.45a

0.43b 0.006 0.023

C:22:6 Docosahexaenoic (DHA) ω 6 1.04b 1.14

a 0.015 0.001



Chapter 4 Results

290

Table 4.53 Mean fatty acid profile of Labeo rohita (Rohu) with two flow season from

four downstream river flow sites (Siphon: site A; Shahdera: site B; Sunder: site C;

head bolloki: site D) with standard error of means (SEM) and significance (P)

Fatty acid Site A Site B Site C Site D

SEM P Low High Low High Low High Low High

Saturated fatty acids (SFA) C:12:0 Lauric 0.00 0.14a 0.19a 0.00 0.00 0.00 0.19a 0.00 0.010 0.000

C:13:0 Tridecanoate 0.09f 0.24c 0.22c 0.17d 0.44b 0.14e 0.48a 0.47a 0.004 0.000

C:14:0 Myristic 4.88d 3.55ef 4.47d 3.69e 7.74c 3.16f 8.43b 8.92a 0.085 0.000

C:15:0 Pentadecanoic 2.05c 1.78d 2.59b 1.79d 3.06a 1.53e 2.90a 3.09a 0.038 0.000

C:16:0 Palmitic 33.77c 36.47ab 32.39d 36.66ab 37.46a 36.21b 32.26d 34.72c 0.216 0.000

C:17:0 Heptadecanoic 1.99d 2.92a 2.77a 2.52b 2.87a 2.30c 2.53b 2.77a 0.031 0.000

C:18:0 Stearic 8.79ab 7.32d 9.44a 8.22b 7.35cd 8.17bc 5.58e 6.17e 0.146 0.000

C:19:0 0.48d 0.46de 0.56ab 0.50cd 0.58a 0.43e 0.49d 0.54bc 0.008 0.000

C:20:0 Arachidic 0.51cd 0.60bc 0.77a 0.48d 0.65b 0.47d 0.49d 0.53cd 0.017 0.000

C:22:0 Behenic 0.40a 0.31b 0.24c 0.24c 0.30b 0.21cd 0.17d 0.21cd 0.008 0.000

C:23:0 Tricosanoic 0.84ab 0.62c 0.90a 0.68c 0.24d 0.31d 0.82b 0.91a 0.014 0.000

C:24:0 Lignoceric 0.15a 0.10bc 0.08cd 0.10b 0.11e 0.11e 0.07d 0.08cd 0.003 0.000

Monounsaturated fatty acids (MUFA) C:14:1 Myristoleic 1.20c 1.50b 1.77a 1.19c 1.96a 1.16c 1.34 1.44 0.038 0.000

C:15:1 Cis-10 pentadecanoic 0.53c 0.56c 0.67b 0.09d 0.74a 0.54c 0.50 0.52 0.012 0.000

C:16:1t9 0.16e 0.29c 0.22d 0.40a 0.36ab 0.38ab 0.28 0.34 0.009 0.000

C:16:1 Palmitoleic 7.67e 5.89f 7.37e 8.83d 11.56c 7.32e 10.04 9.66 0.090 0.000

C:17:1 Cis-10 Heptadecanoic 0.81cd 1.21b 1.17b 1.03bc 0.95bcd 1.06bc 1.39 0.72 0.138 0.025

C:18:1t9 Elaidic 0.66a 0.41b 0.40b 0.44b 0.41b 0.30c 0.27 0.28 0.010 0.000

C:18:1t11Vaccinic 0.09d 0.19b 0.16bc 0.23a 0.26a 0.14c 0.17 0.17 0.006 0.000

C:18:1 Oleic 17.51b 15.56d 17.02bc 16.21cd 12.34e 19.91a 18.13 13.48 0.240 0.000

C:18:1c11 3.49cd 5.15a 5.10a 3.93c 3.84c 4.43b 3.03 3.29 0.082 0.000

C:19:1 0.07c 0.13a 0.00 0.10b 0.00 0.10b 0.05 0.00 0.003 0.000

C:20:1 5 Eicosonoic 0.00 0.09d 0.09d 0.00 0.20c 0.06e 0.26 0.29 0.003 0.000

C:20:1 8 Eicosonoic 0.46a 0.18cd 0.29b 0.16d 0.12de 0.24bc 0.03 0.07 0.012 0.000

C:20:1 11Eicosonoic 1.66a 1.68a 0.97b 1.14b 0.81b 1.70a 0.70 0.79 0.084 0.003

C:22:1 Erucic 0.63a 0.48b 0.22cd 0.42b 0.14d 0.29c 0.27 0.30 0.019 0.003

C:24:1 Nervoniv 0.17a 0.03c 0.03bc 0.00 0.05b 0.04bc 0.00 0.04 0.003 0.000

Polyunsaturated fatty acids (PUFA) C:18:2 Linolelaidic 0.11c 0.11c 0.31b 0.11c 0.09c 0.10c 0.52a 0.53a 0.007 0.000

C:18:2 Linoleic ((LA) ω6 5.13a 4.84ab 4.29c 4.58bc 2.67d 4.47bc 2.57d 2.87d 0.080 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.20c 0.14d 0.12d 0.19c 0.19c 0.15d 0.36b 0.39a 0.006 0.000

C:18:3 alpha-linolenic ω3 1.98bc 3.48a 2.10bc 2.51b 0.97d 2.21bc 1.57cd 1.73bcd 0.155 0.007

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.22d 0.29b 0.16e 0.27bc 0.23cd 0.27bc 0.30b 0.36a 0.007 0.007

C:20:3 Cis-8, 11, 14 Eicosatrienoic (hGLA) ω 6 0.23c 0.20d 0.12e 0.27ab 0.13e 0.25bc 0.26bc 0.29a 0.005 0.000

C:20:3 Cis-11, 14, 17 Eicosatrienoic (hGLA) ω 3 1.04bc 1.28ab 1.21b 1.07bc 0.51d 0.86c 1.35ab 1.57a 0.058 0.015

C:20:4 Arachidonic ω 6 0.11c 0.24a 0.11c 0.17b 0.06d 0.16b 0.12c 0.12c 0.006 0.000

C:20:5 Eicosapentaenoic (EPA) ω 3 0.02bc 0.02ab 0.03a 0.00 0.01c 0.02ab 0.02abc 0.02abc 0.001 0.000

C:22:5 Docosapentanoic (DOA) ω 3 0.60a 0.40c 0.52b 0.47b 0.16e 0.25d 0.52b 0.59a 0.012 0.000

C:22:6 Docosahexaenoic (DHA) ω 6 1.27c 1.18c 0.89d 1.11c 0.44e 0.55e 1.55b 1.74a 0.029 0.004



Chapter 4 Results

291

Table 4.54 Mean fatty acid profiles of Catla catla (thaila) for four downstream river

flow sites (Siphon = A; Shahdera = B; Sunder = C and Balloki = D) with standard

error of means (SEM) and significance (P)


SEM P A B C D


C:12:0 Lauric 0.06c 0.29

a 0.00 0.13

b 0.003 0.000

C:13:0 Tridecanoate 0.11c

0.10c

0.20a 0.15

b 0.004 0.000

C:14:0 Myristic 4.77c

5.29a 5.12

b 3.51

d 0.037 0.000

C:15:0 Pentadecanoic 1.75b

2.50a

1.77b 1.54

c 0.031 0.000

C:16:0 Palmitic 35.91b

33.41c

38.24a 35.28

b 0.144 0.000


2.52d

2.79b 2.65

c 0.015 0.000

C:18:0 Stearic 8.41d

10.97a

10.70b 9.76

c 0.044 0.000

C:19:0 0.41c

0.55a

0.39d 0.50

b 0.003 0.000

C:20:0 Arachidic 0.67b

0.79a

0.54c 0.47

d 0.007 0.000


0.65b 0.53

c 0.35

d 0.010 0.000

C:23:0 Tricosanoic 1.27a 0.55

b 0.24

d 0.39

c 0.014 0.000

C:24:0 Lignoceric 0.38a

0.17b

0.30b 0.26

b 0.010 0.000

Monounsaturated fatty acid (MUFA) C:14:1 Myristoleic 0.94

d 1.85

a 1.30

b 1.53 0.007 0.000

C:15:1 Cis-10 pentadecanoic 0.60b

0.62b 0.60

b 0.64 0.014 0.284

C:16:1t9 0.28a

0.17b 0.17

b 0.29 0.003 0.000

C:16:1 Palmitoleic 6.54d 6.82

c 8.97

b 5.36 0.035 0.000

C:17:1 Cis-10 Heptadecanoic 0.99a

0.78b

0.77b 1.49 0.015 0.000

C:18:1t9 Elaidic 0.45c

0.71a 0.54

b 0.75 0.011 0.000

C:18:1t11Vaccinic 0.03b

0.00 0.00 0.15 0.000 0.000

C:18:1 Oleic 13.58d

16.27c

16.88b 24.04 0.048 0.000

C:18:1c11 3.51d

3.98c 4.52

a 3.62 0.018 0.000

C:19:1 0.04b

0.02d

0.03c 0.08 0.001 0.000

C:20:1 5 Eicosonoic 0.03c

0.02d

0.08a 0.06 0.001 0.000

C:20:1 8 Eicosonoic 0.13d

0.58b 0.26

c 0.85 0.006 0.000

C:20:1 11Eicosonoic 1.23c

2.08a 1.03

c 1.34 0.020 0.000

C:22:1 Erucic 0.47b

0.64a 0.14

d 0.20 0.009 0.000

C:24:1 Nervoniv 0.13b 0.15

a 0.12

ab 0.03 0.003 0.000


b 0.14

b 0.11

c 0.30

a 0.002 0.000

C:18:2 Linoleic ((LA) ω6 4.02a 2.98

b 1.44

d 1.82

c 0.074 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.22a 0.10

b 0.11

b 0.10

b 0.005 0.000

C:18:3 alpha-linolenic ω3 4.11a 2.55

b 0.77

c 0.72

c 0.054 0.000

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.30a

0.15b 0.11

c 0.30

a 0.005 0.000

C:20:3 Cis-8, 11, 14 Eicosatrienoic (hGLA) ω 6 0.21a

0.13c 0.07

d 0.17

b 0.005 0.000


b 0.37

c 0.58

b 0.026 0.000

C:20:4 Arachidonic ω 6 0.11a 0.11

a 0.04

b 0.00 0.003 0.000

C:20:5 Eicosapentaenoic (EPA) ω 3 0.01a 0.01

a 0.00 0.00 0.000 0.000

C:22:5 Docosapentanoic (DOA) ω 3 0.73d 0.33

a 0.19

c 0.25

b 0.016 0.000

C:22:6 Docosahexaenoic (DHA) ω 6 2.33a

0.49c 0.53

b 0.52

b 0.042 0.000



Chapter 4 Results

292

Table 4.55 Fatty acid profiles of Catla catla (Thaila) for two flow season of river Ravi

with standard error of means (SEM) and significance (P)

Thaila Fatty acid Flow Season

SEM P Low High

Saturated fatty acids (SFA) C:12:0 Lauric 0.18

a 0.06

b 0.002 0.000

C:13:0 Tridecanoate 0.14a

0.14a

0.002 0.200 C:14:0 Myristic 4.93

a 4.42

b 0.026 0.000

C:15:0 Pentadecanoic 2.17a

1.61b

0.022 0.000 C:16:0 Palmitic 35.89

a 35.52

b 0.101 0.034


2.61b 0.011 0.000

C:18:0 Stearic 9.83b

10.09a

0.031 0.000 C:19:0 0.53

a 0.39

b 0.002 0.000

C:20:0 Arachidic 0.69a

0.54b

0.005 0.000 C:22:0 Behenic 0.67

a 0.48

b 0.007 0.000

C:23:0 Tricosanoic 0.47b

0.75a

0.010 0.000 C:24:0 Lignoceric 0.27

b 0.29

a 0.007 0.000

Monounsaturated fatty acids (MUFA) C:14:1 Myristoleic 1.52 1.29 0.005 0.000 C:15:1 Cis-10 pentadecanoic 0.68 0.55 0.010 0.000 C:16:1t9 0.22 0.24 0.003 0.000 C:16:1 Palmitoleic 7.47 6.38 0.025 0.000 C:17:1 Cis-10 Heptadecanoic 0.99 1.03 0.010 0.037 C:18:1t9 Elaidic 0.65 0.58 0.008 0.000 C:18:1t11Vaccinic 0.02 0.07 0.001 0.000 C:18:1 Oleic 17.22 18.17 0.034 0.000 C:18:1c11 4.01 3.80 0.013 0.000 C:19:1 0.03 0.05 0.001 0.000 C:20:1 5 Eicosonoic 0.05 0.05 0.000 0.191 C:20:1 8 Eicosonoic 0.42 0.49 0.005 0.000 C:20:1 11Eicosonoic 1.35 1.49 0.014 0.000 C:22:1 Erucic 0.33 0.40 0.006 0.000 C:24:1 Nervoniv 0.11 0.11 0.002 0.006


a 0.14

b 0.002 0.000

C:18:2 Linoleic ((LA) ω6 2.40b

2.73a

0.052 0.002 C:18:3 gamma-linolenic (GLA) ω6 0.09

b 0.17

a 0.003 0.000

C:18:3 alpha-linolenic ω3 1.63b

2.44a

0.038 0.000 C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.17

b 0.26

a 0.003 0.000


0.18a 0.004 0.000


0.79a 0.018 0.000

C:20:4 Arachidonic ω 6 0.07a

0.06b 0.002 0.004


0.00 0.000 0.000 C:22:5 Docosapentanoic (DOA) ω 3 0.30

b 0.46

b 0.011 0.000

C:22:6 Docosahexaenoic (DHA) ω 6 0.79b

1.15a

0.029 0.001

Values within the same row earmarked with same superscripit did not differ

significantly from each other (P>0.05)

Chapter 4 Results

293

Table 4.56 Mean fatty acid profile of Catla catla (Thaila) with two flow season from four

downstream river flow sites (Siphon: site A; Shahdera: site B; Sunder: site C; head

bolloki: site D) with standard error of means (SEM) and significance (P)

Fatty acid Site A Site B Site C Site D

SEM P Low High Low High Low High Low High

Saturated fatty acids (SFA) C:12:0 Lauric 0.00 0.11c 0.47a 0.12c 0.00 0.00 0.25b 0.00 0.005 0.000

C:13:0 Tridecanoate 0.11c 0.11c 0.10c 0.09c 0.09c 0.32a 0.26b 0.05d 0.005 0.000

C:14:0 Myristic 4.79c 4.75c 6.47a 4.12d 4.10d 6.15b 4.37d 2.65e 0.052 0.000

C:15:0 Pentadecanoic 1.75c 1.75c 3.67a 1.33d 1.36d 2.19b 1.91c 1.17d 0.044 0.000

C:16:0 Palmitic 37.36c 34.45e 31.57de 35.24de 36.08d 40.40a 38.55b 32.01f 0.203 0.000

C:17:0 Heptadecanoic 3.09d 2.98d 3.46b 1.58g 1.73f 3.85a 3.28c 2.02e 0.021 0.000

C:18:0 Stearic 9.01e 7.81g 12.12b 9.82cd 8.23f 13.17a 9.96c 9.57d 0.062 0.000

C:19:0 0.43d 0.38f 0.79a 0.31g 0.29g 0.48c 0.59b 0.41e 0.004 0.000

C:20:0 Arachidic 0.66b 0.68b 1.02a 0.57c 0.43d 0.64b 0.66b 0.28e 0.009 0.000

C:22:0 Behenic 0.77a 0.78a 0.78a 0.52b 0.52b 0.54b 0.60b 0.10c 0.015 0.000

C:23:0 Tricosanoic 1.13b 1.42a 0.47d 0.63c 0.14f 0.34e 0.16f 0.62c 0.020 0.000

C:24:0 Lignoceric 0.39b 0.37b 0.19c 0.15b 0.10d 0.50a 0.38b 0.14cd 0.014 0.000

Monounsaturated fatty acids (MUFA) C:14:1 Myristoleic 0.94e 0.94e 2.43a 1.27c 1.40b 1.21d 1.32 1.74 0.010 0.000

C:15:1 Cis-10 pentadecanoic 0.60c 0.60c 0.79b 0.45e 0.77b 0.43e 0.55 0.72 0.019 0.000

C:16:1t9 0.29b 0.27b 0.21c 0.14f 0.16ef 0.18de 0.21 0.37 0.005 0.000

C:16:1 Palmitoleic 6.37f 6.71d 7.82c 5.83g 11.16b 6.79d 4.54 6.18 0.050 0.000

C:17:1 Cis-10 Heptadecanoic 0.98b 1.00b 0.94b 0.63d 0.82c 0.73cd 1.23 1.75 0.021 0.000

C:18:1t9 Elaidic 0.44d 0.46cd 0.89a 0.54c 0.65b 0.44d 0.64 0.86 0.016 0.000

C:18:1t11Vaccinic 0.07b 0.00 0.00 0.00 0.00 0.00 0.00 0.29 0.001 0.000

C:18:1 Oleic 13.75e 13.41f 10.59h 21.95b 21.58c 12.19g 22.97 25.12 0.068 0.000

C:18:1c11 3.53d 3.49de 4.58c 3.37e 5.53b 3.51de 2.41 4.84 0.026 0.000

C:19:1 0.05b 0.03d 0.04c 0.00 0.03d 0.03d 0.00 0.17 0.001 0.000

C:20:1 5 Eicosonoic 0.00 0.05d 0.00 0.04e 0.09b 0.08c 0.10 0.02 0.001 0.000

C:20:1 8 Eicosonoic 0.15ef 0.11f 0.74b 0.43c 0.33d 0.20e 0.47 1.22 0.009 0.000

C:20:1 11Eicosonoic 1.10e 1.37cd 1.76b 2.39a 1.12e 0.94de 1.42 1.26 0.029 0.000

C:22:1 Erucic 0.41c 0.52b 0.62a 0.66a 0.14e 0.14c 0.14 0.26 0.013 0.000

C:24:1 Nervoniv 0.11c 0.15b 0.19a 0.12c 0.11c 0.13a 0.03 0.04 0.005 0.000

Polyunsaturated fatty acids (PUFA) C:18:2 Linolelaidic 0.14d 0.14d 0.18c 0.10e 0.09e 0.13d 0.41a 0.20b 0.003 0.000

C:18:2 Linoleic ((LA) ω6 3.58b 4.46a 3.24bc 2.73cd 1.51e 1.37e 1.29e 2.35d 0.105 0.000

C:18:3 gamma-linolenic (GLA) ω6 0.15bc 0.29a 0.09ef 0.11de 0.05g 0.17b 0.07fg 0.13cd 0.007 0.000

C:18:3 alpha-linolenic ω3 2.98b 5.25a 2.33c 2.78b 0.66d 0.88d 0.57d 0.87d 0.076 0.000

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.26c 0.34b 0.19d 0.12ef 0.09f 0.13e 0.14e 0.47a 0.007 0.000 C:20:3 Cis-8, 11, 14 Eicosatrienoic (hGLA)

ω 6 0.18b 0.25a 0.11cd 0.14c 0.06e 0.08de 0.08de 0.26a 0.008 0.000


(hGLA) ω 3 1.28a 1.30a 0.46cd 0.53c 0.27d 0.47cd 0.29d 0.87b 0.036 0.000

C:20:4 Arachidonic ω 6 0.20a 0.03d 0.10c 0.13b 0.00 0.08c 0.00 0.00 0.005 0.000

C:20:5 Eicosapentaenoic (EPA) ω 3 0.03a 0.00 0.01b 0.01b 0.00 0.00 0.00 0.00 0.000 0.000

C:22:5 Docosapentanoic (DOA) ω 3 0.63b 0.83a 0.27cde 0.39c 0.13f 0.25def 0.15ef 0.35cd 0.023 0.231

C:22:6 Docosahexaenoic (DHA) ω 6 2.25a 2.41a 0.31d 0.67bc 0.20d 0.87b 0.39cd 0.65bc 0.059 0.001



Chapter 4 Results

294

Table 4.57 Means of total fatty acid composition of muscles with standard error of

means (SEM and significance for sampled fish species from selected four sites with two

flow seasons of river Ravi

Sites

Seasons

A B C D

Low High Low high Low High Low High

Cirrhinus mrigala

Fatty acid

SFA 42.04 39.49 53.67 49.55 55.37 51.68 49.58 48.73

MUFA 47.74 49.60 38.21 40.81 38.50 40.80 43.74 42.71

PUFA 10.22 10.91 8.12 9.64 6.14 7.51 6.70 8.56

ω3 2.93 3.38 2.48 3.73 2.25 2.15 1.90 2.39

ω6 7.07 7.35 5.50 5.79 3.75 5.28 4.65 6.05

ω3/ ω6 0.41 0.46 0.45 0.64 0.60 0.41 0.41 0.40

Labeo rohita

Fatty acid

SFA 53.96 54.51 54.62 55.07 60.81 53.03 54.41 58.41

MUFA 35.10 33.35 35.48 34.17 33.73 37.68 36.45 31.39

PUFA 10.91 12.18 9.85 10.76 5.46 9.28 9.14 10.21

ω3 3.64 5.18 3.85 4.05 1.65 3.34 3.46 3.90

ω6 7.16 6.90 5.70 6.60 3.71 5.85 5.16 5.77

ω3/ ω6 0.51 0.75 0.68 0.61 0.45 0.57 0.67 0.68

Catla catla

Fatty acid SFA 59.51 55.59 61.10 54.48 53.06 68.58 60.97 49.01

MUFA 28.81 29.12 31.61 37.81 43.88 26.99 36.02 44.83

PUFA 11.68 15.29 7.30 7.71 3.05 4.43 3.39 6.15

ω3 4.91 7.38 3.08 3.72 1.06 1.60 1.01 2.09

ω6 6.63 7.77 4.03 3.89 1.90 2.70 1.97 3.86

ω3/ ω6 0.74 0.95 0.76 0.96 0.56 0.59 0.51 0.54

Values within the same row earmarked with same superscripit did not

differ significantly from each other (P>0.05)

Here *,** and *** represent significance at P<0.05, P<0.01 and P<0.001

respectively (Minitab 16 General linear model)

Abbreviations SEM and

Significace

SFA Saturated Fatty acid 0.266***

MUFA Mono Unsaturated Fatty acid 0.233***

PUFA Poly Unsaturated Fatty acid 0.212***

ω3 Omega-3 0.144***

ω6 Omega-6 0.124***

ω3/ ω6 Omega-3/Omega-6 ratio 0.023***

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295

Table 4.58 Mean of Standard error of means (SEM) with significance *, ** and *** indicated by *, ** and *** represent

significance at P<0.05, P<0.01 and P<0.001 respectively for Saturated fatty acids in muscles of selected fish species from

four river sampling sites with two flow seasons.

Fatty acid SEM with Significance

S Se Sp S x Se S x Sp Se x Sp S x Se x Sp Saturated fatty acids

C:12:0 Lauric 0.003*** 0.002*** 0.003*** 0.004*** 0.005*** 0.004*** 0.007***

C:13:0 Tridecanoate 0.003*** 0.002*** 0.002*** 0.004*** 0.005*** 0.003*** 0.007***

C:14:0 Myristic 0.037*** 0.026*** 0.032*** 0.052*** 0.064*** 0.045*** 0.090***

C:15:0 Pentadecanoic 0.020*** 0.014*** 0.017*** 0.028*** 0.035*** 0.025*** 0.049***

C:16:0 Palmitic 0.118*** 0.083 0.102*** 0.167*** 0.205*** 0.145*** 0.289***

C:17:0 Heptadecanoic 0.013*** 0.009*** 0.011*** 0.018*** 0.022*** 0.016*** 0.031***

C:18:0 Stearic 0.044*** 0.031** 0.038*** 0.063*** 0.077*** 0.054*** 0.109***

C:19:0 0.003*** 0.002*** 0.003*** 0.005*** 0.006*** 0.004*** 0.008***

C:20:0 Arachidic 0.005*** 0.004*** 0.004*** 0.007*** 0.009*** 0.006*** 0.012***

C:22:0 Behenic 0.004*** 0.003*** 0.004*** 0.006*** 0.007*** 0.005*** 0.010***

C:23:0 Tricosanoic 0.007*** 0.005*** 0.006*** 0.009*** 0.012*** 0.008*** 0.016***

C:24:0 Lignoceric 0.004*** 0.003*** 0.003*** 0.005*** 0.006*** 0.004*** 0.009***

Total SFA 0.109*** 0.077*** 0.094*** 0.154*** 0.188*** 0.133*** 0.266***

Abbrevations: Sampling Sites=S; FlowSeasons=Se; Fish Species=Sp

Chapter 4 Results

296


significance at P<0.05, P<0.01 and P<0.001 respectively for Monounsaturated fatty acid in muscles of selected fish species

from four river sampling sites with two flow seasons.



C:14:1 Myristoleic 0.010*** 0.007*** 0.009*** 0.014*** 0.018*** 0.012*** 0.025***

C:15:1 Cis-10 pentadecanoic 0.006*** 0.004*** 0.005*** 0.008*** 0.010*** 0.007*** 0.014***

C:16:1t9 0.003*** 0.002*** 0.002*** 0.004*** 0.005*** 0.003*** 0.007***

C:16:1 Palmitoleic 0.059*** 0.042*** 0.051*** 0.084*** 0.102*** 0.072*** 0.145***

C:17:1 Cis-10 Heptadecanoic 0.033*** 0.024* 0.029*** 0.047** 0.058*** 0.041*** 0.081***

C:18:1t9 Elaidic 0.007*** 0.005*** 0.006*** 0.010*** 0.012*** 0.008 0.017***

C:18:1t11Vaccinic 0.002*** 0.001*** 0.002*** 0.003*** 0.003*** 0.002*** 0.005***

C:18:1 Oleic 0.094*** 0.066*** 0.081*** 0.133*** 0.163*** 0.115** 0.230***

C:18:1c11 0.028*** 0.020*** 0.024*** 0.040*** 0.048*** 0.034*** 0.069***

C:19:1 0.001*** 0.001*** 0.001*** 0.002*** 0.002*** 0.002*** 0.003***

C:20:1 5 Eicosonoic 0.001*** 0.001*** 0.001*** 0.002*** 0.002*** 0.002*** 0.003***

C:20:1 8 Eicosonoic 0.005*** 0.003 0.004*** 0.007*** 0.008*** 0.006*** 0.012***

C:20:1 11Eicosonoic 0.022*** 0.015*** 0.019*** 0.031*** 0.038*** 0.027 0.053***

C:22:1 Erucic 0.006*** 0.004*** 0.005*** 0.008*** 0.010*** 0.007*** 0.014***

C:24:1 Nervoniv 0.001*** 0.001** 0.001*** 0.002*** 0.002*** 0.002*** 0.004***

Total MUFA 0.095*** 0.067 0.083*** 0.135*** 0.165*** 0.117*** 0.233***


Chapter 4 Results

297


significance at P<0.05, P<0.01 and P<0.001 respectively for polyunsaturated fatty acid in muscles of selected fish species

from four river sampling sites with two flow seasons.



C:18:2 Linolelaidic 0.002*** 0.001*** 0.002*** 0.003*** 0.004*** 0.003*** 0.005***

C:18:2 Linoleic ((LA) ω6 0.032*** 0.023*** 0.028*** 0.046*** 0.056*** 0.040* 0.079***

C:18:3 gamma-linolenic (GLA) ω6 0.002*** 0.002*** 0.002*** 0.003*** 0.004*** 0.003*** 0.006***

C:18:3 alpha-linolenic ω3 0.041*** 0.029*** 0.036*** 0.058*** 0.071*** 0.050*** 0.101***

C:20:2 Cis-11, 14 Eicosadienoic ω 6 0.003*** 0.002*** 0.002*** 0.004*** 0.005*** 0.003*** 0.007***


(hGLA) ω 6 0.002*** 0.002*** 0.002*** 0.003*** 0.004*** 0.003*** 0.006***


(hGLA) ω 3 0.017*** 0.012*** 0.014*** 0.023*** 0.029*** 0.020*** 0.040***

C:20:4 Arachidonic ω 6 0.002*** 0.002*** 0.002*** 0.003*** 0.004*** 0.003*** 0.005***

C:20:5 Eicosapentaenoic (EPA) ω 3 0.001*** 0.000* 0.001*** 0.001*** 0.001*** 0.001*** 0.001***

C:22:5 Docosapentanoic (DOA) ω 3 0.006*** 0.004*** 0.005*** 0.009*** 0.011*** 0.008*** 0.015***

C:22:6 Docosahexaenoic (DHA) ω 6 0.016*** 0.011*** 0.014*** 0.022** 0.027*** 0.019* 0.038***

Total PUFA 0.087*** 0.061*** 0.075*** 0.122*** 0.150*** 0.106* 0.212***

ω 3 0.059*** 0.041*** 0.051*** 0.083*** 0.102*** 0.072*** 0.144***

ω 6 0.051*** 0.036*** 0.044*** 0.071*** 0.087*** 0.062 0.124***

Ω 3/ ω 6 0.009*** 0.007*** 0.008*** 0.013*** 0.016*** 0.011*** 0.023***


Chapter 4 Results

298

0

10

20

30

40

50

60



Sampling Sites

Fatt

y a

cid

(%

)

SFA MUFA PUFA

Fig. 4.72 Means of total fatty acid composition of muscles in C. mrigala from selected

four sites with two flow seasons of river Ravi

0

10

20

30

40

50

60

70



Sampling Sites

Fatt

y a

cid

(%

)

SFA MUFA PUFA

Fig. 4.73 Means of total fatty acid composition of muscles in Labeo rohita from selected


Chapter 4 Results

299

0

10

20

30

40

50

60

70



Sampling Sites

Fatt

y a

cid

(%

)

SFA MUFA PUFA

Fig. 4.74 Means of total fatty acid composition of muscles in Catla catla from selected


Chapter 5 Discussion

300

DISCUSSION

The present study reports effects of untreated domestic and industrial sewages on

some physicochemical parameters of the river Ravi water, its bed sediment and fish fauna, in

terms of growth, gut contents’ bacterial heavy metals resistance and metals bioaccumulation

in different organs of the animals. The study area spanned over a river segment of about 90

Km by passing Lahore, the second largest city of Pakistan. This investigation was based on

four sampling sites viz., an upstream locality Siphon (A) and three downstream localities i.e.,

Shahdera (B), Sunder (C) and Balloki (D). The densely populated and industrial city, empties

its untreated domestic as well industrial effluents in to the Ravi mainly between the sites A

and B and B and C. The upstream site A is relatively less polluted while the site D respires a

little bit better due in part to the river’s pollutants’ masking/detoxifying potential over a run

of about 90 Km and in part due to dilution effect of Q.B. canal which joins the river before

the site D. As the sampling was done both during high and low flow seasons of the river, less

drastic effects were found during the high flow season. It will be interesting to note in the

forthcoming description that, in general, all the parameters analyzed showed healthier

profiles at site A (upstream) and highly and at most highly stressed looks for the sites B and

C, respectively. Whereas at site D pollutions’ stressed did not further increase, rather showed

some levels of recovery due to above mentioned reasons. This investigation can be

considered a case study for cosmopolitan cities of developing countries which are polluting

their river with heavy urban effluents’ loads. The information, consequent of the present


301

investigation, on the fishes health acquisition of metals’ resistant bacteria in their gut and

metals’ pollutants accumulation levels in different organs of the different species sampled

from different alongstream locations with reference to the urban effluents discharging points

are valuable for authorities concerned with town planning, environmental rehabilitation,

public health and riverine fauna. Due to multifaceted nature of the study, its outcomes are

discussed according to the following subheadings.

5.1 Physico-chemical parameters of the sampling localities:

5.2 Biometeric data of sampled fish species:

5.3 Proximate analysis of the fishes’ muscles:

5.4 Biochemical analyses of the fishes’ muscles

5.5 Heavy metals’ resistant bacteria from gut contents of the fishes:

5.6 Heavy metal Concentration in water, sediment and fishes’ organ:

5.7 Fatty acid analysis:

5.8 Conclusion

5.1 Physico-chemical parameters of the sampling localities:

Freshwater environments are subjected to variations in ecological parameters which

in turn determine the distribution pattern of organisms according to availabilities of particular

habitats. Physical, chemical and biological characteristics of fresh waters do respond to

seasonal fluctuations. In the present study, water temperature gradually increased for

downstream locations as compared to the upstream site A (22.87 and 24.10 ºC), up to the site

C (23.53 and 24.93 ºC) and then it reduced at site D (22.83 and 24.43 ºC) during low and

high flow seasons, respectively. It is well known that temperature variation of a freshwater

habitat is one of the most important external factors that influence fish production (Huet,

1986). While flowing water, in general, lack wide fluctuations in temperature (Leonard,

1971). Downstream changes of water temperature for Lahore stretch of the river Ravi may


302

be attributed to the addition of domestic and industrial effluents, whose microbial oxidations

might had produced heat sufficient to raise temperature of the water. Whereas reduction in

temperature at site D may be considered reflective of recovery of quality of river water which

improved gradually between the sampling sites C and site D due partly to the merging of

Q.B. link canal into the river. Higher value of temperature of the river water recorded during

high flow than low flow was associated with gradual decrease of the parameter from post

monsoon (high flow) to winter (low flow). Kumar et al. (2011) reported gradual increase in

temperature of surface water in the month of March till the onset of monsoon season in July

and then gradual decrease from the rainy to the post monsoon season. Obviously, longer

photoperiod of summer raises river water temperature (Nirmal et al., 2008).

Dissolved oxygen (DO) content of any aquatic system is considered as an index of

functioning of biological and physicochemical processes. DO has an inverse relation with

water temperature (Ali, 1999). Lower DO of the Ravi water during low flow might be a

function of microbial decomposition of concentrated organic loads of the untreated domestic

and industrial effluents discharged adjacent to the Hudiara drain and Deg Nullah. The

biodegradable components of the inloads, require a large amount of oxygen to be oxidized by

microorganisms and ultimately result into depletion of DO. In the present study, trend of DO

level showed alarming situation for the inhabitant fish species, especially at site C during low

flow having a value of 3.80 mg/l. Safe recommended concentration of DO is 4.0 mg/l for

fishes, however, most species are distressed when it falls between 2.0 - 4.0 mg/l. Low level

of DO (less than 2.0 mg/l) can cause fish mortality (McNeil and Closs, 2007). DO showed a

significant negative correlation with levels of total dissolve solids, nitrate, chloride and

sulphate for the study sampling sites. Thus DO can serve as a single useful and important

parameter of water quality as with the increase in the value of most of other physico-

chemical parameters, the concentration of DO decreases. Different fish species have different


303

oxygen consumption rates corresponding at a given water temperature. For instance, Catla

catla is least tolerant, while Labeo rohita seems to be more tolerant to low oxygen contents

of water (Tabinda et al., 2003). Lower value of DO obtained in this study clearly

demonstrates the Lahore urban organic loads inputs to the river Ravi, while passing the city.

Suspended and dissolve solids are common tests of polluted waters. Waters with high

dissolved and/or suspended solids are of inferior quality. Waters with less than 2.5 mg/l of

total solids cause 5.5 times more production of fish than the waters with total solids

exceeding 100 mg/l. Light penetration has inverse relationship with turbidity. Waters with

less than 2.5 mg/litre solids are less turbid and allow more light penetration, 12.8 folds more

planktonic yield and 5.5 times more fish production. While waters with turbidity exceeding

100 mg/l have low light penetration as well as fish production (Boyd and Tucker, 1998; Ali

et al., 2000). Significant high value of total dissolved solids (TDS) ranging from 64.7 to 948

mg/l might have resulted due to effluents’ higher concentration of soluble salts and other

components. Subramaninan (2004) reported TDS up to 272 mg/l for Cauvery, 241 mg/l for

Ganges, 224 mg/l for Mahandi and 173 mg/l for river Indus. Total suspended solids at all the

sampling sites of the river varying from 213 to 908.7 mg/l exceeded the recommended

National Environmental Quality Standards (NEQs) value. Due to high dissolve and

suspended solids, the colour of the river water was grayish black. It appears that the

communal effluents from the urban and industrial areas mixed heavy quantity of dissolved

and suspended solids to the river water. Comparable results have been reported by Yausafzai

et al. (2010b) for river Kabul, Pakistan. Total alkalinity and hardness of water depend upon

the nature and amount of dissolved salts. Alkalinity is mainly imparted by calcium and

magnesium ions, which apart from sulphate, chloride, nitrite and nitrate are found in

combination with carbonates and bicarbonates (Mohan et al., 2007, Prasad and Patil, 2008).

Carbonates and bicarbonates have positive correlation with alkalinity. Downstream high


304

values of this parameter could also be attributed to discharge of industrial effluents which

contained dissolved cations and anions. Magnesium hardness exhibited strong positive

correlation with chloride which advocated that magnesium mainly remain present as

magnesium chloride as reported by Bhandari and Nayal (2008). Magnesium also showed

positive correlation with phosphate, sulphate, nitrite and nitrate. Downstream elevated values

of nitrate, nitrite and phosphate could be associated with agricultural fertilizers’ run off. This

trend is expected one for rivers bound to some commercial farms and agro-allied industries.

The increased usage of nitrogen based fertilizers as well as the poultry and other agricultural

wastes from such farms significantly contribute for elevated nitrate levels in rivers’ waters.

(Yang et al., 2004, Nnaji et al., 2010; Osibanjo et al., 2011). The spatial and temporal

variations in nitrates represent the final product of the biochemical oxidation of ammonia

(Mahananda et al., 2010). Nitrite, nitrate and phosphate contents of the Ravi water showed

negative correlation with DO. The higher nutrient contents (indicated by nitrate and

phosphate) of the sampling area waters may be responsible for lower DO value due to higher

consumption of DO. Lesser values of DO downstream might have been exerting respiratory

stress for the aquatic fauna. While, comparatively lower values of phosphate recorded during

high flow season might be due to utilization of phosphate as nutrients by algae and other

plants. Significant higher levels of these variables resulted into eutrophication which was

observable in patches near the bank of the river, especially during low flow season. Higher

concentration of chloride is considered to be the indicator of pollution due to organic wastes

of animals and humans’ origin. Chloride also gets added to rivers’ waters from the discharge

of industrial effluents containing hydrochloric acid, common salt and chloride containing

compounds used as industrial raw materials, particularly in food industries (Kumar et al.,

2006; Suthar et al., 2008). Development of residential colonies in the catchment areas of

river Ravi is also causing this type of pollution. These results are in conformity with the


305

finding of other workers (Ghumman, 2011; Steinman et al., 2011). Subramaninan (2004)

reported values of the parameter as 11 mg/l for Brahamputra, 17 for Godavari and 10 for

Ganges. All these south Asian rivers show chloride values less than the study area of the

river Ravi. Yausafzai et al. (2010b) reported comparable results for the river Kabul. Higher

ammonia content up to 1.22 mg/l at site C during low flow season showed deterioration of

water quality owing to the inputs of untreated industrial effluents. Ammonia is extremely

toxic to fish and should be present below 0.2 mg/l for better fish growth (Chapman, 1992).

Muhammad et al. (1998) reported 0.002 mg/l of ammonia for river Swat, Pakistan. Sulphate

contents of the river water, like other variables, showed significant elevation up to 2.49 folds

at site C as compared to the situation at the site A during low flow season. The sulphate

contents of present study area are much higher than those reported for the Kabul (Yausafzai

et al., 2010b), Cauvery, Gomti and Mahandi rivers (Subramaninan, 2004). Sulphate contents

exhibit positive correlation with nitrate, nitrite, chloride, hardness and phosphate which

suggests that they all represent common sources (Bhandari and Nayal, 2008).

For the above referred of the river’s water, parameters ranges of physico-chemical, it

is concluded that urban domestic and industrial effluents’ loads have been deteriorating the

river’s natural habitat in general. While at present, the situation recovers to some extent at the

last study location downstream. If no prompt and strong pollution control measures will be

taken, more zone of the river will become polluted and less inhabitable for the fish species.

5.2 Biometric data of sampled fish species:

Total length and weight data did not differ significantly (P>0.05) at different sites and

flow seasons. However, significance differences (P<0.001) were observed for total lengths

among the fish species. Growth coefficient (b) ranged from 3.08 to 3.19 and from 3.07 to

3.16 in C. mrigala, from 3.08 to 3.21 and from 3.06 to 3.17 in L. rohita and from 3.03 to 3.16

and from 3.01 to 3.11 in C. catla during high and low flow seasons, respectively. Value of


306

‘b’ for the studied fish species indicated positive allometric growth as described by Wootton

(1998). Accordingly, a value of ‘b’ significantly larger or smaller than 3.0 represents

allometric growth and a value greater than 3 indicates that the fish have become heavier

(positive allometric) for its length. Apart from present study, many researchers have reported

comparable allometric growths for different fish species (Salam and Janjua, 1991; Zafar et

al., 2003; Shakir et al., 2008). In the present study, ‘b’ measured highest up to 3.19 and 3.16

in C. mrigala, 3.21 and 3.17 in L. rohita and 3.16 and 3.11 in C. catla at site A, while lowest

values appeared for C. mrigala as 3.08 and 3.07, L. rohita as 3.08 and 3.06, and C. catla as

3.03 and 3.01 at site C during high and low flow seasons, respectively. The trend of ‘b’ is

noticeable in this study for the sampled fish species, as the parameter reduced up to site C

and then, more or less stabilized at site D with a little bit recovery as compared to respective

values for the third study point during low as well as high flow seasons. Fluctuations in the

values of ‘b’ at the different polluted sites indicated negative urban effects of the discharges

on growth of the riverine fishes. These results are in line with the findings of Rao et al.

(2005) who reported the variation in ‘b’ of Liza parsia (Hamilton-Buchanan) from the

polluted sampling station (b=2.50) in comparison with unpolluted sampling station (b=2.52).

Rauf et al. (2009b) while describing heavy metal contamination in the sediment of river Ravi

(Lahore Siphon to Balloki headworks) reported highest concentration of copper in Taj

Company nulla, while minimum concentration of cadmium at Lahore Siphon. Jabeen et al.

(2012) reported that toxicity of metals fluctuated significantly in sampling fish species at

three sampling stations viz. Shahdara bridge, Balloki headworks and Sidhnai barrage with

season. These workers have also documented alarming health status of river Ravi at the three

main public fishing sites, characterized higher levels than the recommended permissible

standards of Al, As, Ba, Cr, Ni and Zn in fishes. .Significant decreases in the values of ‘b’ of

fishes sampled from site B, C and D. In the present investigation as compared to the


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respective values of the parameters at site A, during both low and high flow seasons

represented reductions in weight gain of the respective fishes. Giguere et al. (2004) described

that control fish species gained significantly more weight than the stressed Perca flavescens.

Reduction in weight gain has been associated with metal toxicity stress by Hussain et al.

(2010) in C. mrigala following metal mixture exposure. In the present investigation, value of

‘b’ appeared lower during low flow than high flow season in all the fish species. Seasonal

variations reinforce pollutants’ effects on fish species as suggested by Imam et al. (2010) that

Tilapia zilli, Oreochromis niloticus, Hemichromis bimaculatus and Clarias gariepinus

showed low ‘b’ value in dry season than wet season in Wasai reservoir, Nigeria.

Condition factor (K) is an indicator of fish plumpness and favorable environmental

conditions. Values of ‘K’ significantly differed at different sites, seasons and fish species.

Mean ‘K’ in C. mrigala was 1.00 while in L. rohita and in C. catla the parameter appeared

up to 1.16 and 1.24, respectively. Even the ‘K’ range was found to be greater than 1 for L.

rohita (1.03-1.18) and C. Catla (1.14-1.27) but ‘K’ while the parameter fluctuated between

0.97 to 1.05 with mean ‘K’ values of 0.98, 1.0, 1.04 and 0.98 in C. mrigala at sites A, B, C

and D, respective. Nikos (2004) reported that adequately fed fish had ‘K’ greater than 1,

while undernourished one had a ‘K’ less than 1. The present results for C. catla (1.16) and C.

mrigala (1.08) fell within the range reported by Memon et al. (2011) for these species raised

under control conditions. Fish with a high K value are heavy, while fish with a low ‘K’ value

are lighter for their respective length (Wootton, 1998). It is well known that ‘K’ fluctuates

within fish species due to differences in feeding, climate and environmental conditions,

(Lizama et al., 2002). In the present study, increase in ‘K’ at downstream sites might be an

indication of availability of better food due to increase in primary and secondary productions

which in turn can be associated with presence of cattle farms along the river Ravi and

fertilizers’ run off as indicated by downstream elevated values of nitrate, nitrite and


308

phosphate. Abid and Ahmed (2009) have described association of growth performance of

Labeo rohita with diet. The higher K values of the fishes sampled from the highly polluted

sites in comparison with their respective values of the parameters for the upstream site, A

might have also resulted due to disturbance in fish physiology and biochemistry.

Biochemical responses of fishes are influenced by environmental factors, such as physico-

chemical profiles of aquatic medium, seasons, fish nutrition status, age, health and presence

of toxic substances (Lohner et al., 2001; Hedayati and Safahieh, 2011). Metal’ stressed C.

mrigala, L. rohita and C. catla showed higher feed intake than control (Hussain et al., 2010,

2011). Higher feed intake refers to disturbance in metabolism. Variations in the energy

reserves (carbohydrates, protein and lipids) are indicative of long term exposure of toxicant

stressor (Mayer et al., 1992). This aspect for the present study is discussed in the forthcoming

sections 5.3 and 5.4.

The present study revealed adverse effects of river Ravi pollutants, especially at site

C on growth and health status of the inhabitant fish species. The growth coefficient results

warrant for immediate measures to save the river’s ecological role by keeping it free from the

untreated effluents’ pollution.

5.3 Proximate analysis of the fishes’ muscles:

Over all moisture contents in the fishes’ muscles fluctuated from 71.42 to 75.86 %

and fell within the ranges observed by other researchers (Sharma et al., 2010; Memon et al.,

2011). Fats are generally regarded as the most important constituents, which determine the

quality of fish meat (Love, 1988). Based on fat content and crude protein, all the fish species

of this study were ranked as lean and high protein fish, because fat contents of their muscles

were lower than 5% (Rahman et al., 1995) and protein contents greater than 15 % (Stansby,

1976). Mehboob et al. (2003) reported comparable results for fat contents (1.30 -2.94 %) of

wild Labeo rohita. Increasing trend of crude protein and decreasing levels of carbohydrate,


309

fat and ash contents of muscles of the fishes from downstream sites might be another

outcome of the river water pollutants’ stresses. Several laboratory load investigations support

this notion. For example, Susan et al. (2010) noticed an increase in protein content in the

muscle of Cirrhinus mrigala under lethal concentrations of fenvalerate (synthetic

pyrethroids). While Sindhe et al. (2002) revealed decrease in lipids contents in Notopterus

notopterus exposed to sub-lethal concentrations of heavy metal. Similarly, reductions in

lipids profile have been reported by Kaur and Saxena (2001) in fish flesh sampled from

polluted waters of river Sutluj. In the present study, fishes showed progressive reduction in

fat reserves of muscles. It is known that after reaching a critical low level of fat for a given

fish species; Proteins began to be utilized for energetic purposes (Hassan, 1996).

Carbohydrates are considered to be degraded at first under stress condition of animals.

Chemical stress causes depletion of stored carbohydrates (Vijayavel and Balasubramanian,

2006). Pollutants’ stresses might have induced increases in metabolism resulting in increased

utility of carbohydrates as energy source. The present results are in accordance with the

finding of Garg et al. (2009) who reported significant reduction in carbohydrates contents in

muscle of Labeo rohita, Cirrhinus mrigala and Catla catla after an exposure to heavy metals.

5.4 Biochemical analyses of the fishes’ muscles:

Fish muscle’s biochemical profiles can be used as organism’s stress indicator. Vivid

differences in the muscles’ biochemical parameters appeared for the fishes collected from

downstream locations characterized with heavy insults of domestic and industrial sewages as

compared to biochemical profiles of the fish sampled from the upstream location of the river

Ravi, before its entrance to the city Lahore. Evaluation of three energy reserves;

carbohydrates, total and soluble proteins and lipids are generally considered as indicators of

fish health. Variations in these reserves have been described as indicative of long term

exposure of stressor(s) (Mayer et al., 1992). Biochemical responses can be affected by


310

environmental factors, such as physico-chemical profiles of aquatic medium, season, fish

nutrition status, age and health (Lohner et al., 2001).

Carbohydrates decreased retrogressively from the site B to C. The decreases as

compared to the carbohydrate content of muscles of fishes from site A during low and high

flow periods were recorded as 77 % and 74 %, respectively for the site C. It appears that

during high flow season, dilution of the urban pollutants mitigated their effects to some

extent. Carbohydrates are considered to be the first degraded under stress condition of

animals. It has previously (section 5.3) been discussed that chemical stress causes depletion

of stored carbohydrates. Toxicants’ stress may induce glycogenolysis possibly by increasing

the activity of glycogen phosphorylase to meet the energy demand or may affect

glycogenesis by inhibiting the activity of carbohydrate metabolism (Valarmathi and Azariah,

2002). Radhakrishnaiah et al. (1992) have noted stimulation of glycogenolysis in L. rohita

after an exposure to a sub lethal concentration of copper. Dhavale and Masurekar (1986)

suggested that reduction in tissues carbohydrate content may be due to prevalence of hypoxic

condition as in oxygen limitation, carbohydrate consumption is enhanced. It might be

concluded that decreases in the carbohydrates of muscles of the fishes being reported in this

study are reflective of less availability of dissolved oxygen and direct effects of heavy metals

and other pollutants on the animals. James et al. (1991) endorsed significant reduction in

carbohydrate contents of Oreochromis mossambicus to increase in catabolic process due to

heavy metals’ toxicity. Pollutants toxicants caused reduction in carbohydrate content in other

freshwater fishes has also been reported (Vijayram et al., 1989; Jebakumar et al., 1990;

Somnath, 1991). Bhattacharya et al. (1987) studied blood glucose and hepatic glycogen

profiles in C. punctatus following exposure to sub lethal concentrations of single and mixture

of toxicants. These workers noticed hyperglycemia with depletion in hepatic glycogen for

short term exposure, while in long term test, hyperglycemia was recorded with continual


311

lessening of hepatic glycogen content. Glycogen exhaustion may be a demonstration of an

initial regulatory action which increases intermediary metabolism consequential in protection

of the hepatocytes under xenobiotics insults. Khanna and Gill (1975) reported damage of

pancrease in Channa punctatus, following administration of cobalt chloride and cobalt nitrate

which lead to hyperglycemia along with degranulation and vacuolization of pancreatic tissue

in the initial stages and damage of β-cells in later stages.

Total and soluble protein contents of the fishes’ muscles significantly increased for

the downstream locations. Pollutants’ stresses, probably, accelerated synthesis of protein.

Tissue protein content has been suggested as an indicator of xenobiotic-induced stress in

aquatic organisms (Srivastava and Srivastava, 2008). The present results are in agreement

with the findings of Lohner et al. (2001) who attributed increases in protein contents of

metals’ exposed animals to synthesis of proteins required for sequestering the metals.

Similarly, Susan et al. (2010) noticed an increase in protein content in the muscle of

Cirrhinus mrigala exposed to fenvalerate (synthetic pyrethroids) and suggested that the

toxicant stress might had stimulated protein synthesis for detoxification enzymes at the

expense of glycogen to meet additional requirement in the synthetic activity of tissue. Several

workers reported that altered in the activity of several enzymes like alanine transferase and

aspartate amino transferase after toxicant exposure. Alanine amino transferase has been

strongly implicated in the production of energy in tissue and is considered as a stress

indicator whereas aspirate amino transferase is the main transaminase that interferes with

tricaboxylic acid cycle. (Lohner et al., 2001; Susan et al., 2010). The present results are also

in line with those reported by Yousafzai and Shakoori, (2009b) for endangered fish species,

Tor putitora netted from polluted part of Indus river, Pakistan.

Total lipid contents of the fishes’ muscles decreased downstream, resembling the

pattern of carbohydrate decline. The results are in line of Srivastava and Srivastava (2008)


312

who showed reduction in total lipids content in freshwater fish, Channa punctatus after

chronic exposure to zinc. Lipid is an imperative fuel reserve of the fish during stress

condition. Thus proteolysis, glycogenolysis and hydrolysis of lipids have been reported to

generate more energy through glucogenesis in order to cope with the increased energy

demands in fish exposed to metal toxicity (Gunstone, 1960). Liver dysfunction or inhibition

of oxidative phosphorylation or metabolization of glycerol for energy demand under

pollution associated stress condition might have been the possible causes of reduced lipid

contents in muscles of the fishes. Vincent et al. (1996) reported decline of lipids contents in

Catla catla after an exposure of 20, 25, 30 and 35 mg/l of chromium. Similarly, reductions in

lipids profile have been reported by Kaur and Saxena (2001) in fish flesh sampled from

polluted waters of river Sutluj in Pakistan. Shukla et al. (2002) observed decrease in lipid

content of Channa punctatus after 60 days exposure of cadmium and with other metals.

Giridhar and Indira (1997) suggested that to overcome the stress, animal tends to mobilize

lipids by stimulating its lipases which act on lipids and breakdown them into free fatty acids.

Which then may undergo β-oxidation leading to the formation of Acety-CoA) which enters

into tricarboxylic acid cycle to make the energy available.

Cholesterol is a vital structural component of cell membrane as well as the outer

layer of plasma lipoproteins. It is the precursor of all steroid hormones (Yang and Chen,

2003). In the present study, cholesterol content also showed pattern similar to the fate of

lipids pollutants’ responsive decreases for downstream locations indicated

hypocholesteremia. Agrahari et al. (2007) reported that hypocholesteremia after exposure to

monocrotophos. The hypocholesteremia observed in the present study might had been a

consequent of inhibitory effects of metals on cholesterol synthesis. It might be referred to

heavy metals inhibit cholesterol synthesis in fish. Inhibition of cholesterol biosynthesis in the

liver might had occurred due to lack of cholesterol starting material (acetyl-coenzyme A) as


313

suggested by Ali (1989). Reduced absorption of dietary cholesterol as reported by Kanagaraj

et al. (1993) and/or utilization of fatty deposits instead of glucose for energy purpose as

reported by Remia et al. (2008) might have also contributed for the observed deficits of

cholesterol content. Decreases in cholesterol level can also be correlated with the inhibition

of protein metabolism and switching on the energy production source to some other

metabolites as suggested by Ali (1989). Results of the present study are in accordance with

the observation of Al-Kahtani (2011) who reported decline in cholesterol content of muscle

of Oreochromis niloticus (tilapia) following exposure to insecticides.

DNA content of the fishes’ muscles did not significantly differ among the

downstream sites and seasons. However, elevations at downstream sites, especially during

low flow season were apparent as compared to the value obtained for respective fish sampled

from the site A. RNA content differed significantly in different seasons and decreased for

downstream sites. Das and Mukherjee (2003) reported elevated DNA and decreased RNA

contents in muscle of Labeo rohita after an exposure of sub-lethal concentration of

cypermethrin. Similar, findings have been reported by Yousafzai and Shakoori (2009b) who

suggested that DNA seemed to be resistant to the ambient toxicants.

The results indicated significant increases in soluble and total protein, and DNA

contents of the fishes muscles exposed to the domestic and industrial effluents’ origin

pollutants as compared to the respective values obtained for the fish tissue sampled from the

upstream location. Whereas significant decreases in carbohydrates, total lipids, cholesterol

and RNA contents of the pollution exposed fish meat as compared to the respective values of

a given fish muscle from the upstream location were evident. The biochemical profiles

indicated that the fish health is under strong negative effects of pollutants loads and warrants

for quick measures to control the pollutants on one hand. While on the other hand these


314

trends of meat compositional biochemical changes might be considered indicative of long

term pollution of water resources.

5.5 Heavy metals’ resistant bacteria from gut contents of the fishes:

The present study revealed presence of heavy metal-resistant bacteria in gut contents

of the fish species sampled from the contaminated segment of the river. High number of

bacteria of diverse kinds are present in gut contents of fishes (Cahill, 1990; Mondal et al.,

2008). However, scarce of data exist in the published literature about heavy metal resistant

bacterial profiles from gut contents of fishes inhabiting the contaminated waters. This is the

first report on presence of heavy metal resistant bacteria in the gut contents of three fish

species inhabiting a polluted segment of the river Ravi in Pakistan. In the present study, one

hundred twenty three heavy metals resistant bacteria were isolated from the gut contents of

the reported fishes. These bacterial isolates grew in the presence of 250 to1000 µg, 350 to

1400 µg, 10 to 70 µg, 350 to 1650 µg of Cu2+

, Pb2+

, Hg2+

and Cr6+

ions per ml of nutrient

agar, respectively. Thus these bacteria were thriving in the presence of heavy metals

contaminated food and water within the gut of the fishes and might had been playing

important roles in the process of food digestion as well as mitigating the effects of the heavy

metals present in the polluted river’s water. Fishes are suitable indicators for monitoring

different aspects of environmental pollution as they may concentrate over a period of time

recalcitrant pollutants in their tissues/organs whereas their gut contents are influenced

directly from physicochemical and biological characteristics of the water which they inhabit.

While characteristics of running water are subject to rapid changes due to continuous flow in

the streams and river. Thus spreading sampling of such waters and their subsequent

physicochemical and biological analyses would indicate a very transient picture of the

environment. Analysis of the gut contents of fishes sampled from a particular location on the

other hand may indicate presence and frequency of particular matter and food items available


315

to the fish within that environment over a relatively longer time stretch. Inasmuch as

isolation of particular pollutant resistant bacteria concerned, it is well known that they are

easily obtained from toxicants’ contaminated soils and stagnant and very slow flowing waters

(Faryal, 2003; Qazilbash, 2004). In case of river water with a rapid and big flow isolation of

pollutant resistant bacteria might be a difficult task especially base on a few samples. In the

present study urban effluents’ pollution of the river Ravi within the Lahore region was

investigated mainly focusing at heavy metals’ contamination. As the river water receives

heavy insults of both domestic and industrial effleuents in the study region. The industrial

effluents do contaminate the river with heavy metals in addition to other kinds of pollutants.

Owing to relatively stable nature of gut contents of the riverine fishes, but continuously

exposed to the surrounding influences as compared to the river water presence of heavy

metal resistant bacteria was hypothesized in the highly heavy metal contaminated part of the

Ravi. Metal resistance is nothing new for bacteria. In order to survive in the presence of high

concentrations of metals in the aquatic medium, different bacteria showed different resistance

mechanisms since 3 to 4 billion years ago (Silver et al., 1989). Development of metals

resistance among the members of microbiota of anthropogenically created microhabitats

necessitating such mechanisms have been well documented from different environments and

diverse parts of the world (Faryal, 2003; Qazilbash, 2004). The microenvironment of bacteria

associated with the gastrointestinal tract of an animal influences the host in many ways.

Considering the importance in the digestion process and health promoting effects for the

hosts, composition, diversity and morphological characteristics of the gut microflora in many

species of marine and freshwater fish species have been researched extensively (Ringo et al.,

2006; Izvekova et al., 2007; Mondal et al., 2008; Tanu et al., 2012). However, apart from the

nutritional and health promoting impacts of gut microflora of fishes, very little is known

about the enteric existence of pollutant resistant/bioremeditionally important bacterial


316

profiles. The present study was thus aimed at isolation and characterization of the heavy

metals resistant bacteria from the gut contents of the fishes sampled from the polluted river.

In fact enteric environment of aquatic animals such as fishes inhabiting polluted waters

should be considered very promising pockets for selection/or development of bacterial strains

resistant to the pollutants loads they are continuously facing. This notion derived from the

well established phenomenon of bacterial strains selection/development resistant to particular

pollutant(s) continuous stimuli while facing selective pressures in anthropogenically made

select environments such as industrial including mine drainage and exposing microbes’

continuous culturing to a pollutant at laboratory level. Microflora flim the gut environments

of fishes inhabiting contaminated above described environments; set of above conditions

favouring selection/development of pollutant resistant bacteria are met successfully. Results

of the present study in the forth coming pages, brought vivid support to this notion.

Highest mean colony forming units (C.F.U.) appeared from gut contents of Catla

catla (30.2 x 105 /g). While next to the rank were Labeo rohita (27.6 x 10

5/g) and Cirrhinus

mrigala (24.9 x 105/g) netted from site A during high flow season. Whereas mean lowest

C.F.U. were for Catla catla (0.56 x 105 /g). and for Labeo rohita (1.21 x 10

5 /g) at site C

during low flow season. Results of present study are within the range reported by different

authors that the number of bacteria ranges from 103 to 10

8/g (Lesel, 1981), 10

5 to 10

9/g

(Sugita et al., 1991), 103 to 10

4/g (Zmyslowska et al., 2000) of fish gut contents. Here few

comments are highly relevant. That is difference between the above referred reports and the

present result should be kept in mind in terms of nature of bacterial isolates. The above cited

authors have reported C.F.U. from gut contents of the fishes while employing general

purpose media, whereas in the present study only heavy metals tolerant microbes are being

reported. Besides this difference, comparable levels of bacterial C.F.U. amongst the referred

work and the present study indicate that due to long exposure of the given river segment,


317

prevalence of the pollutants’ tolerant bacteria could achieve a high profile. While lowest

C.F.U. values obtained during low flow seasons of the river, indicate high concentrations of

the toxicants which might had exerted bactericidal effects on some of the microbes. These

results dictates for proper dilutions of pollutants to be introduced in to natural water systems,

for the natural bioremediational process to be continued.

Despite the highly polluted nature of the urban influenced river segment, all the

sampled fish species showed adequate feeding level at all sampling sites as it indicated by

‘K’ values which were greater or equal to one (section 4.2.1). It is known that nutrient levels

in fish intestine enhance growth and persistence of autochthonous (indigenous) bacteria that

are able to adhere and colonize in the host’s gut epithelial surface, whereas allochthonous

(transient) bacteria, that are incidental visitors in the digestive tract, are rejected after some

time without colonizing (Grimes, 1986; Ringo et al., 2007). However, Olsen et al. (2001)

reported that the allochthonous microbiota might be able to colonize under special conditions

such as stress. The microorganism is able to colonize the digestive tract when it can persist

there for a long time, by possessing a multiplication rate higher than expulsion rate. In fact

nutrient status with the fishes’ gut, levels of fish growth and health promoting bacteria in the

intestine and the fishes growths all appear supportive to each other. Role of beneficial

bacteria in gut of fishes for growth and health of the animal is well established (Hatha, 2000;

Tanu et al., 2012). Food digestive enzymatic profiles of the 45 select bacterial isolates in the

present study indicated that 67, 71 and 71 % of them expressed amylolytic, cellulolytic and

proteolytic activities, respectively. While 49 % of the isolates were found positive for the

three categories of the exoenzymes. 9, 4.5 and 9 % bacterial isolates amylase and cellulose,

amylase and protease and cellulose and protease activities concomitantly. Nutrition digestive

role of intestinal bacteria is well documented. For example Ray et al. (2010) detected a huge

population of amylase, cellulase and protease producing bacteria (Bacillus subtilis) from


318

intestinal tract of three Indian carps, C. catla, C. mrigala and L. rohita. Bacillus

thuringiensis, Bacillus megaterium, Citrobacter freundii played important role in different

enzymes production in intestine of carps. Bacillus megaterium produced penicillin amidase

used for making penicillin. It produces enzymes for modifying corticosteroids as well as

several amino acid dehydrogenases (Saha and Ray, 2011; Askarian et al., 2012). Ghosh et al.

(2010) by employing culture base analysis and electron microscopy evaluation have

confirmed adherent bacterial strains express enzymatic activity in the digestive tract of Labeo

rohita and identified sequencing as Bacilli, Aeromonas, Enterobacter and Pseudomonas

species following 16S rRNA genes. Autochthonous and/or allochthonous nature of the

bacterial isolated was not worked out in the present study. However, it can be speculated that

some of authochthonous bacteria might had developed metals resistances following

continuous exposure to the polluted environment and culturing within the gut habitat. This

notion got support from the identification of the bacterial isolates, as many of the species

recovered have been reported autochthonous to several fish species (discussed in

forthcoming pages). Whilst possibility of thriving of allochthonous bacteria secondarily

populating the gut environment can not be ruled out. Possibly some metals resistant bacteria

characterized with food digestive enzymes might had entered along with food and water in

the fishes gut and then ‘mutualism’ developed under the stressed condition (Olsen et al.,

2001). Differences in the number of metals resistant bacteria in gut contents of fishes

sampled from different localities might refer to ecological and contaminated habitats of the

microorganisms (Ringo et al., 2007). Decreasing trend of C.F.U of metal resistant bacteria

for the downstream sampling sites in the present study might be associated with increasing

concentration of metals in waters, sediment and fishes organs/tissues. Lowest C.F.U. were

found in the gut contents of fishes sampled from site C (sunder) wherein highest metals’

concentrations were recorded in water, sediment and the fishes’ tissues. Rajbanshi (2008)


319

reported toxic effects of the heavy metals on the growth of microorganisms and reported

decreases in metal resistant bacteria with increases in heavy metals’ concentrations.

Similarly, significantly reduced number of bacteria in intestinal tract of rainbow trout

(Oncorhynchus mykiss) following exposure to 0.5, 2 and 8 mg/l of Zn has been reported

(Mickeniene and Syvokie, 2008). In another investigations these workers demonstrated that

three months’ metal exposure influenced the abundance of bacteria in digestive tract of trout

(Oncorhynchus mykiss) and the number of bacteria after exposure to 0.1 mg/l of copper

decreased two folds as compared to control (Mickeniene and Syvokiene, 1998). The diversity

and abundance of bacteria in the digestive tract of rainbow trout also decreased following

exposure to a mixture of five (Zn, Cu, Ni, Cr, Fe) metals (Mickeniene and Syvokiene, 2001).

Heavy metal resistant microorganisms do not arise by chance but represent consequences of

selection factors like environmental concentrations of heavy metals. Due to prolonged

exposure to heavy metals, bacteria can acquire highly specific resistance mechanisms to

inhibit the impact of heavy metals (Barkay, 1987; Rasmussen and Sorensen, 2001). In this

study, the select bacterial strains showed varying levels of resistances against different

metals. The isolated bacteria showed metals resistances ranging from 250 to 1000 µg/ml for

Cu2+

, 350 to 1400 µg/ml for Pb2+

, 10 to 70 µg/ml for Hg2+

and 350 to 1650 µg/ml for Cr6+

.

Multiple metal resistances in bacteria occur only against those heavy metals that have similar

mechanisms underlying their toxicity. And the heavy metals being reported (Cu, Pb, Cr and

Hg) have similar toxic mechanisms. Recently, Saha and Ray (2011) isolated Bacillus

magaterium and Bacillus subtilis from the gut of Ctenopharyngodon idella and Cyprinus

carpio respectively.

Aeromonas are autochthonous to aquatic environments worldwide and have been

strongly implicated in the etiology of a variety of fish and human diseases. Several

Aeromonas spp. are potential pathogens. Out of forty five select strains, eight showed


320

similarlities with Aeromonas spp. The Strain BHR7-2 showed 98 % similarly with

Aeromonas (A) salmonicida. The A. Salmonicida has been classically considered a fish

pathogen able to develop furunculosis (Figueras et al., 2000; Garduno et al., 2000; Martinez-

Murcia et al., 2005). Aeromonas veronii is a well known fish pathogenic bacteria (Orozova et

al., 2009). In present study, Aeromonas veronii was from gut contents of Labeo rohita.

Similar finding have been reported by Ghosh et al. (2010) about the isolation of Aeromonas

veronii from the gut of Labeo rohita. In the present study, values of C.F.U. revealed that

Aeromonas spp. were abundant in the gut contents of the sampled fish species. The presence

of a higher number of Aeromonas in the digestive tract may play an important role in the

process of digestion as Aeromonas species secrete several enzymes like porteases and

chitinases (Pemberton et al., 1997; Sugita et al., 1999). Aeromonas spp. have been detected

in the normal intestinal mucosa from several fishes, such as Atlantic cod (Gadus morhua L.)

and Grass carp (Ctenopharyngodon idellus) [Ringo et al., 2006; Wu et al., 2012]. Bacteria in

the mucosa may be regarded as indigenous species, and are involved in host nutrition,

mucosal defense, and host immunity (Salzman et al., 2002; Ringo et al., 2003). Several

authors have documented that Aeromonas may play more important roles in fish biology,

other than as pathogenic microbes (Gibson et al., 1998;, Gibson, 1999; Irianto and Austin,

2002) However, the presence of Aeromonas in the intestine may agree with the findings of

Hiney et al. (1994) and Lodemel et al. (2001) that the intestine might be the primary location

for Aeromonas colonization under stress-induced infections. The isolate DHR5-1 showed 96

% similarity with the strain, Obesumbacterium proteus after sequence blast. Priest et al.

(1973) showed that Obesumbacterium proteus is a close relative of many enteric bacteria. In

the present study, the isolated genera Klebsiella, Serratia and Citrobacter are disease causing

bacteria but are a normal part of gut flora of animals (Orozova et al., 2009; William et al.,

2010). Potential pathogens have been considered important members of the intestinal


321

microbiota (Wu et al., 2012).Detailed information about these genera in the literature are

scanty, however, there appears a consensus by several workers that the digestive tract is

somehow, affected by these genera (Jutfelt et al., 2006; Ringo et al., 2007, Sugita et al.,

2008; Ringo et al., 2010). Isolates of the present study were obtained from apparently healthy

freshwater fish species. Several bacterial species have been isolated from other varieties of

healthy fish species (Wiklund and Dalsgaard, 1998; Ray et al., 2012). Most abundantly

reported bacterial communities are related to feed digestion. Bacillus spp. has been shown to

possess adhesion abilities, provide immunostimulation and produce bacteriocins (Cherif et

al., 2001; Cladera-Olivera et al. 2004; Duc et al. 2004; Barbosa et al., 2005). Therefore, one

can hypothesize that beneficial bacteria colonizing the digestive tract by producing, for

example, bacterocins may offer protection against invading fish pathogens (Ringo et al.,

2005; Desriac et al., 2010). It is difficult to generalize contribution of the gastrointestinal

microbiota, because of the complexity and variable ecology of the digestive tract of different

fish and the microbial species. However, the bacterial isolates being reported in this study are

well adapted to unfavorable conditions by their resistances to various heavy metals and these

microbes could be good candidates for remediation of heavy metals in heavily polluted sites.

Further, these findings may help not only in developing bioremediation processes of

contaminated water bodies but they can be administered to the gut of fishes for protecting

alleviating them from expected heavy metals intoxification. After natively the bacteria can

recruited to alleviate toxic effects to the fishes which had been accidentally or otherwise

exposed to heavy metals pollution. Prevalence of the 250 to 1000, 350 to 1400, 10 to 70 and

350 to 1650 µg/ ml of Cu2+

, Pb2+

, Hg2+

and Cr6+

respectively resistant bacteria with multiple

metal resistance in the gut of the Cirrhinus mrigala, Labeo rohita and Catla catla fishes

inhabiting the contaminated segment of the river Ravi indicate possible roles of these

microbes for the metals’ remediation of detoxification and thus benefiting their host by


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alleviating the toxicities of the contaminants. Obviously this aspect of the isolated bacteria is

to be verified experimentally. Further research may demonstrated their beneficial roles in

rehabilitating metals contaminated water habitats or application of such bacteria may protect

diminishing fish fauna within heavy metals polluted waters. While food hydrolyzing

enzymatic potential of the heavy metal resistant bacterial isolates dictates for the possibility

that these bacteria were normal inhabitant of the gut environment benefiting their host within

their exoamylases, cellulases and proteases. And the continuous heavy metals exposure made

them metal resistant just to survive in the presence of varying levels of the metals, with little

or not direct role for the process of bioremediation. If this possibility emerges as factual,

even then beneficial roles of these microbes in for the fish growth and prevalence in the

contaminated environment cannot be ruled out. In short, the bacterial diversity preserved

during the course of this study is of interest to the researchers study mechanisms of heavy

metals tolerance by the aquatic vertebrate models.

5.6 Heavy metal Concentration in water, sediment and fishes’ organ:

Heavy metals may have special disturbing effects on the ecological balance of the

recipient environment (Vosyliene and Jankaite, 2006; Farombi et al., 2007; Ayandiran et al.,

2009). These contaminants can decline water and sediments quality and may badly affect

inhabitant fish health and other biological attributes like trophic structure and taxonomic

richness etc. (Fernandes et al., 2007; Batzias and Siontorou, 2008) and also form a major

hazard because of their bioaccumulation, toxicity and persistence in the food chains (Feng Li

et al., 2008; Murugesan et al., 2008; Taghinia et al., 2010; Sekhavatjou et al., 2010, 2011). In

present study, contamination of river Ravi was investigated by determining heavy metals’

content in water, sediments and three inhabitant fish species. Main sources of pollution for

the river Ravi in the select stretch of present study, from upstream less polluted site (siphon)

to downstream sampling site (Balloki), are municipal sewage of Lahore city (second largest


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city of Pakistan), industrial effluents and agriculture runoff. The present study revealed

significant variations of metals’ (cadmium, chromium, copper, iron, lead, zinc, maganese,

nickel and mercury) toxicity in water, sediment and fishes’ organs. All studied metals

showed higher contaminations at the downstream sampling sites B and C as compared to the

upstream site A. Whereas quality of the river water seemed to improve at the last

downstream sampling site D (Balloki). This improvement might be associated with

mixing/joining of Q. B link canal water between site C and D. Javed (2004b) and Yayintas et

al. (2007) reported that metal concentration in the river Ravi is a potential hazard to aquatic

life and exceeds the permissible limits for sustainable conservation of aquatic habitat. Results

of this study, revealed that mean metal concentration in the river water was in order of: Fe

>Zn >Mn> Cr> Cu >Ni > Hg > Pb > Cd. Whereas in sediment sampled from the select sites,

the metals appeared in the order of Fe > Zn > Mn > Cu > Cr > Ni > Hg > Pb > Cd. Similar

trends were found by Rauf (2009) while studying the river segment from Lahore siphon to

Balloki headworks, he reported order of the metals’ concentration as Cu > Cr > Cd > Co for

water samples and Cu > Cr > Co > Cd in sediment samples. Javed and Hayat (1995)

suggested that significant variations in metal concentrations were resultant of untreated urban

sewage and industrial effluents that increased the heavy metals contents in river Ravi bed

sediments. Therefore, higher concentration of heavy metals in sediment samples indicated

heavy pollutants’ load insults to the river Ravi. River sediments are important sinks for

various toxicants like heavy metals and pesticides etc. Transfer of pollutants in water,

sediment and fish species depends upon the physico-chemical profiles of aquatic system

(Morgan and Stumm, 1991; Javed, 2003). Different researchers concluded that determination

of metal concentrations in bed sediment is sensitive, because heavy metal enrichment in bed

sediment is dependent upon biological, chemical and environmental factors (Luoma, 1990;

Javed, 2003; Ubaidullah et al., 2004b). In the present study, dissolved oxygen and metals


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concentrations had negative correlation at downstream sampling sites. In the present

investigation, total alkalinity and total hardness showed direct relationship with metal

concentrations in downstream waters, sediments and fishes samples. Van Aardt and Erdmann

(2004) and Erdogrul and Ates (2006) reported that the availability of metals in water depend

upon temperature and hardness of water. The metals contents appeared higher in sediment

than water samples in the present study. This might be due to the increased trend of total

alkalinity at downstream sampling sites both during high as well as low flow seasons. Jeanne

(1977) suggested that under alkaline conditions, metals can be hydrolyzed and form insoluble

hydroxides, which settled down into the river bed sediments. Higher metals’ concentrations

in the sediments in the present investigation could also be correlated to the higher metals

concentrations in different tissues of the fish species investigated. Coetzee et al. (2002)

described that metals from sediment can be reintroduced into water, with changing physico-

chemical parameters, in to bio-available forms to fish by means of gills or skin.

Freshwater fish are often at the top of food chain. Elevated level of metals in different

fish tissues mainly originates from abiotic and biotic components of aquatic resources

polluted by municipal sewage and industrial effluents (Novelli et al., 1998; Mansour and

Sidky, 2002; Van Aadt and Erdmann, 2004; Altindag and Yigit, 2005; Javed, 2006).

Therefore, metals’ bioaccumulation in different fish species of different trophic levels can be

considered as an index of metal pollution in the aquatic bodies (Tawari-Fufeyin and Ekaye,

2007; Karadede-Akin and Unlu, 2007). In the present study, fishes’ organs showed

significant variations in metals bioaccumulation. Such variations have been correlated by

various workers to difference in uptake, absorption, storage, regulation, age, geographical

location, season and excretion abilities of given fish species (Al-Yousuf et al., 2000; Scerbo

et al., 2005; Solhaug Jenssen et al., 2010). In the present study, all metals’ (Cd, Cr, Cu, Fe,

Pb, Zn, Mn, Ni and Hg) bioaccumulation in different organs appeared significantly (P<0.001)


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different among selected fish species. The highest level of Fe, while lowest of Cd were

recorded in the fishes’ organs. Bioaccumulation of heavy metals in an organism is a result of

difference in uptake and excretion and this is much important factor in metal accumulation in

fish. On the other hand, the gender is an important factor that may influence the metals

bioaccumulation in biota (Burger, 2007; Vahter et al., 2007). Al-Yousaf et al. (2000)

reported that copper, manganese and zinc bioaccumulation in tissues of fish was affected by

the sex. They found that the mean metal concentrations in different tissues of female fish

species were higher than those in male fish species and suggested that it may be due to the

difference in metabolic activities of two sexes. Similarly, Alhashemi et al. (2011) reported

higher accumulation of metals in female than male fish species, Barbus grypus and Barbus

sharpeyi. Metals’ bioaccumulation levels in relation to difference in sex of the fishes,

however, was not investigated in the present study. The metals’ contents of different organs

of the three fish species investigated appeared several folds higher than their corresponding

values in the water as well as the level of water quality guidelines and standards by NEQs.

Metals’ bioaccumulation in fish tissues provides evidences of exposure to contaminated

aquatic environment as the fish can absorb and bioacuumulate the available metals directly

from their surrounding environment via skin and gills or through the ingestion of

contaminated water and food (Ademoroti, 1996; Kotze, et al., 1999). The metals also varied

amongst different tissues of the same fish. Metals uptake from blood at tissue levels is a

biphasic process, which involves rapid adsorption or binding to the surface, followed by a

slower transport into cell interior (Crist et al., 1988). Transport of different metals ions in to

intracellular compartment may be facilitated by either diffusion of the metals ions across the

cell membrane or by active transport of metals ions through binding with different specific

carrier proteins. Presence of different metal binding proteins is an indication of toxic metal

pollution in an aquatic environment (Hennig, 2008). Fish regulate metal ions through


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excretion via kidney and gills. Ability of each tissue or organ to either regulate or accumulate

metals can be directly related to the total amount of metal accumulation in that specific tissue

or organ. However, Fish’s ability to synthesise metal binding proteins is limited (Brown and

Parsons, 1978). When metabolic cababilities for excrection and binding the pollutants are

exceeded from threshold limit, toxic effects will results, unless the fish has an alternate way

of detoxification. In scaly fish species, the alternate detoxification process may be

calcification as suggested by Simkiss (1977). For the present study, it is worth mentioning

that higher values of metals in the scales might had made survival of the fish species possible

through detoxification of the pollutants by calcification. However, different organs showed

significant variations in metals bioaccumulations, which may be attributed to differences in

species, position of tissues in aquatic environment, uptake, absorption, storage, regulation

and excretion abilities of the fishes (Kotze, 1997; Kotze et al., 1999).

Physico-chemical and ecological factors do influence the intensity of heavy metals

uptake in animals. Temperature and dissolved oxygen have negative correlation. Higher

temperature results in decreasing dissolved oxygen contents, which leads to increase in

metabolic rate. Because of this, the fish take up greater amounts of metals as a result of

increased diffusion or active transport associated with higher rates of water movement across

the gills (Prosi, 1979). Ionized forms of metals exert greater toxicity for fish and are

produced at elevated temperature. Avenant-Oldewage and Marx (2000) reported that

physico-chemical parameters such as temperature, pH and total dissolved solids influence the

availability of heavy metals. Higher values of anions, choride and phosphate have an

important role in regulating concentration of metals in an aquatic ecosystem. (Kotze et al.,

1999).

In the present study, metal concentrations significantly varied at the different

sampling sites and seasons in water, sediment and fish samples. Javed (2003) also found site


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specific metal accumulations in fish species of the river Ravi corresponding with metallic

toxicity in water, sediment and plankton. Tekin-Ozan and Kir (2007) suggested that

bioavailability of different metals may be influenced by physiological activities of fish during

different seasons while Seasonal variation in metal accumulation may be influenced by

stream conditions, toxicants load, water chemistry and other environmental factors which

affect the availability of metal (Heiny and Tate, 1997) while Farkas et al. (2000) described

that seasonal variations in metal bioaccumulation is related to changing to feeding behaviour

of fish species.. Significant variations in macro elements among the muscles of the sampled

fish species were found in this study. Sodium and potassium are the most common non toxic

metals, as these are abundant in the earth’s crust. Due to their water solubility, both Na and K

are leached out from soil and rocks into the neighboring water. Excessive Na and K can

impart a bitter taste to drinking water and could be hazardous for people with cardiac, hepatic

and renal ailments. There is no specific recommended value of these elements for fishes’

muscles so it is difficult to comment on this aspect of the study Calcium and magnesium

occur naturally in the sediment and represent most common ions causing freshwater hardness

(USEPA, 1999). In this study, mean Mg contents were highest (667 mg/kg) at site C than D

(624 mg/kg), B (601 mg/kg) and A (573 mg/kg). Swann (2000) reported that it is unclear that

elevated levels of macro elements in fish tissues are harmful for fish itself, other wildlife

species and human consuming such fish. Elevated level of Ca with mean values in C.

mrigala up to 7917 mg/kg, L. rohita up to 8149 mg/kg and C. catla up to 9887 mg/kg may

not be a major concern for the consumers as the element is not harmful. However, their

elevated levels confirmed their value in providing strength to fish, particularly in fins and

scales as reported by Jabeen and Chaudhry (2010b).

Metals bioaccumulation in fish muscle is of major concern for the consumer health as

this tissue is served as meat. Further transportation of metal from muscle to liver/kidney is


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required for any level of detoxification. Kidneys and Liver are the major organs of metabolic

activities including elimination/excretion and detoxification of contaminants present in the

blood stream (Klavercamp et al., 1984; Kent, 1998). High metals’ concentrations may alter

levels of various biochemical parameters in liver and cause severe liver damage (Mayers and

Hendricks, 1984; Ferguson, 1989). In the present study, considerable levels of heavy metals

in the kidneys of the fish species. This may be due to the transport of metals ions from other

tissues for elimination. Higher metals concentrations in gills may be due to highly branched

structure with increased surface area of gills allowing maximum absorption/adsorption of the

toxicants from water, as has been described by Mayers et al. (1985). In the present study,

overall bioaccumulation pattern of metals in different organs (muscle, skin, gills, eyes,

scales, heart, intestine, liver and kidney) was in the order of: Fe > Zn > Mn > Cu > Cr > Pb >

Hg > Ni >Cd. Similar accumulation pattern (Fe > Zn >Cr > Pb >Ni > Cu) was found by

Qadir and Malik (2011) for eight edible fish species from two polluted tributaries of river

Chenab, Pakistan. The present results are in line with those reported by Zyadah and Chouikhi

(1999) and Javed and Mehmood (2000a) for fishes collected from Aegean Sea, Turkey and

river Ravi, Pakistan respectively.

Zn bioaccumulation ranged from 24.57 to 60.38 mg/kg for C. mrigala, 21.34 to 48.65

mg/kg for L. rohita and 17.85 to 50.41 mg/Kg for C. catla. These ranges represented highest

concentrations among the studied metals in muscles at different sites and seasons in the

present study. The results are in good agreement with those of Jabeen and Chaudhry (2010a).

Zn contents were studies in kidney of C. mrigala (120.89±11.861) than C. catla

(96.62±2.143 mg/kg) and L. rohita (92.27±2.143 mg/kg). All the above values of the Zn in

the fishes’ tissues are higher than the recommended limits of 50 mg/kg in fish (FAO, 1983;

WHO, 1985). Consequently, the consumption of riverine fish from the reported segment of

the Ravi may pose Zn induced health hazards. Lower mean value of Zn in gills (42.61


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mg/kg) is suggestive for rapidly excretion of the metal from the tissue. These results are

comparable with Zn accumulation pattern of freshwater fish Channa punctatus, characterized

with lower bioaccumulation in gills than in the kidney and liver (Murugan et al., 2008). Fish

have a tendency to push zinc burden from muscles to other tissues like kidney during

metallic stress and this deloading is beneficial to consumers who are using fish muscle for

food (Murugan et al., 2008). Zn bioaccumulation in fish organs of the three fish species

significantly (P<0.001) differed among the sampling sites and flow seasons. Several workers

have reported non significant variations of Zn accumulation in fishes, regarding the effect of

season (Velcheva, 2006; Tekin-Özan and Kir, 2007; Qadir and Malik, 2011). In fact the

varying results indicate difference in river flows, geographical distribution and many other

differences of different rivers’ habitats. Besides season, effects of differences in localities

along the river may influence the metal uptake process in fishes. For example Schmitt et al.

(2002; 2007) described significant spatial variation in Zn accumulation in freshwater fishes.

Iron is a micronutrient and essential for animals’ health. Fe bioaccumulation ranged

between 21.83-43.24 mg/kg, 23.53-47.83 mg/kg and 25.93-49.85 mg/kg were measured in

muscles corresponding of C. mrigala, L. rohita and C. catla. Bury et al. (2003) found that

excessive amount of iron can be harmful for fish health including gills clogging and

respiratory perturbations. Mn is an essential micronutrient (Dallas and Day, 1993). It does

not occur naturally as a metal in aquatic ecosystems but it is found in various salts such as

MnCaCO3 (rhodocrosite), Mn SiO3 (rhodonite) and MnO2 (pyrolusite). Mn ranged from 2.50

to10.22 mg/kg, 1.80 to11.11 mg/kg, and 1.44 to 12.42 mg/Kg, in muscles of C mrigala,

L.rohita and C. catla, respectively. At site C the Mn contents of muscles of C. catla, L.

rohita and C. mrigala increased up to 374, 336 and 299 %, respectively in comparison with

the site A during low flow season. The permissible limits of 0.01 mg/kg (WHO, 1985) and

0.05 mg/kg (FEPA, 2003) rendered the present levels of the metal toxic for the fish as well as


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for human consumption. Livers of C. mrigala, L. rohita and C. catla expressed mean higher

concentrations of the metal up to 24.55±1.496 mg/kg, 20.05±1.298 mg/kg and 18.67±1.550

mg/kg, respectively. Mn concentration was considerably higher in liver than muscles,

presumably due to its function as a cofactor for the activation of many enzymes (Sures et al.,

1999). The Mn has been reported to be taken up directly through gills or indirectly from food

and ingested sediments via gut (Bendell-Young and Harvey, 1986). High Mn values in gills

of the sampled fish species indicated the metal accumulation tendency of the respiratory

organs reported by Jabeen and Chaudhry (2010a) for tilapia. High Mn content interferes with

metabolic pathways such as the disruption of Na regulation in central nervous system by

inhibiting dopamine formation which may ultimately cause fish deaths (Jabeen and

Chaudhry, 2010a). In the Present study, elevated levels of Mn in different organs are of

concern, as such fish can cause Mn-related disorders in the consumers.

Muscles of C. mrigala, L. rohita and C. catla showed 2.99 to 5.24 mg/kg, 2.62-4.98

mg/kg and 2.87 to 5.65 mg/ kg of Cu. All these ranges are higher than that these reported by

Malik et al. (2010) for Ctenopharyngodon idella and Labeo rohita. Avenant-Oldewage and

Marx (2000) referred that fish muscles accumulate less amount of Cu even if fish is exposed

to higher levels of the metal. Allen-Gills and Martynov (1995) refered least bioaccumulation

of copper in muscle to low levels of binding proteins in fish muscles. Copper is an essential

part of several enzymes and is necessary for the synthesis of haemoglobin, fish growth and

reproduction (Sivaperumal et al., 2007) while its higher intake can cause adverse health

problems. Fish affected by toxic exposure of copper become darker, lethargic and indifferent

to external stimuli. Fish may become extremely colourful just before death since copper

caused the melanophores to relax. Sensitive fish species may restrict themselves to area of

stream where copper concentrations are lowest. In the present study the fishes, however, did

not show any apparent signs of abnormality. Cu concentration in liver of C. mrigala


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(11.72±0.779 mg/kg), L. rohita (10.54±0.061 mg/kg) and C. catla (11.90±1.019 mg/kg), for

example, were lower than permissible level of 30 mg/Kg Cu of fish (WHO, 1985; FEPA,

2003) Concentration of copper in water, sediment and fish organs could be linked with the

effluents of pharmaceutical and agricultural applications. Pharmaceutical factories in the

vicinity of river Ravi, especially near the site C (sunder) could be considered one point

source of the pollution. Copper salts are used as pesticides and fungicides. Agriculture runoff

could bring copper into river Ravi. Higher Cu accumulation in liver was followed by

intestine, heart, scale, eyes, gills, skin and muscle in the present investigation. Comparable

results of Cu bioaccumulation have been reported others. (Avenant-Oldewage and Marx,

2000; Campenhout et al., 2004; Chatterjee et al., 2006; Qadir and Malik, 2011).) In the

present study, Cu bioaccumulation significantly (P>0.001) differed among sampling sites and

flow seasons. Kotze et al. (1999) and Beldi et al. (2006) also found significant spatial

differences in Cu accumulation in fishes. Whereas Avenant-Oldewage and Marx (2000) and

Tekin-Ozan and Kir (2007) described significant seasonal discrepancies in Cu

bioaccumulation in different fish species.

Nickel is essential for normal growth and reproduction but becomes carcinogenic

when present in higher amount. Mean concentrations ranged from 0.29 to 2.12 mg/kg, 0.30

to 2.59 mg/kg and 0.28 to 1.61 mg /kg in muscles of C. mrigala, L. rohita and C. catla,

respectively in the present study. These values are below the permissible level of Ni (10

mg/kg) in fish for human consumption (Eisler, 1998). Ni accumulations in kidneys of C.

mrigala, L. rohita and C. catla sampled from site C increased up to 848 %, 607 % and 387

%, respectively as compared to the corresponding values at site A. Ni bioaccumulation in the

three fish species showed significant variations among sampling sites and flow seasons of

river Ravi. Higher concentrations of Ni in river Ravi water, sediment and fish sampled from

low stream locations could be linked with effluents from ghee, oil and food industries


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situated in Kala shah Kaku industrial areas as well as Multan road industrial area which

discharge their effluent directly/indirectly into rive Ravi. Nussey et al. (2000) reported

significant seasonal variations in Ni bioaccumulation. Nickel is considered less toxic in

comparison to Pb, Hg , Cr and Cd (Clark, 2001). The symptoms of Ni toxicity in fishes are

fast mouth opening, opercula (Beraldo et al., 1995) convulsive movements and loss of

equilibrium before death (Khangarot and Ray, 1990; Eisler, 1998). Higher concentration of

Ni reduces respiration rate and causes death due to blood hypoxia (Ellgaard et al., 1995;

Eisler, 1998).

Highest Cd increases up to 433, 300 and 467 % were appeared in muscles of C.

mrigala, L. rohita and C. catla, respectively sampled from site C when compared with

corresponding values for site A during low flow season. However the Cd concentrations

detected in the investigated organs of the fishes were lower as compare to levels of the other

metals. Cadmium (Cd) is highly toxic as it can cause anomalies such as reduction in the

development and growth rates as well as skeletal ossification even at lowest concentrations

(Wright and Welbourn, 2002). The cadmium levels in fish muscles reflect its bioavailability

in aquatic environment and it could have carcinogenic effect on aquatic biota and humans.

Cd toxicity in fish varies from species to species, developmental stages, interference of

toxicants and water hardness (USEPA, 1999). In the present study, Mean Cd

bioaccumulations showed significant variations among upstream and downstream sampling

sites and for the two flow seasons. Tekin-Özan and Kir (2007) found seasonal variations in

Cd bioaccumulation between fishes of Beyşehir Lake, Turkey. Higher concentration of Cd in

fish is an indicator of the environmental contamination of surrounding medium (Kojadinovic

et al., 2007). In the present study order of accumulation of Cd was kidney > liver > intestine

> scale > heart > eyes > skin > gills. Yilmaz et al. (2007) reported higher accumulation of

cadmium in liver and gills of Leuciscus cephalus and Lepornis gibbosus. Similarly, mean Cd


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bioaccumulation has been reforted higher in liver and gills of B. grypus (Alhashemi et al.,

2011).

Lead (Pb) belongs to the group of toxic and non essential metals which implies that it

has no known function in biochemical processes (Adeyeye et al., 1996). Pb is known to

induce reduction in cognitive development and intellectual performance in children and

increased blood pressure and cardiovascular diseases in adults (EC, 2001). It is well known

fact that anthropogenic activities had influenced the lead content of aquatic life including

fish. Pb enters in aquatic medium through erosion and leaching from soil, lead dust fallout,

municipal and industrial water discharges, steel runoffs and precipitation (DWAF, 1996). Pb

bioaccumulation ranged from 0.14 to 3.16 mg/kg, 0.15 to 3.10 mg/kg and 0.18 to 3.28 mg/kg

in C. mrigala, L. rohita and C. catla, respectively. These levels indicated the Pb content

much higher than the permissible limits of 2 mg/kg (WHO, 1985) in fish for human

consumption. Fall out deposit, welding and painting units, automobile exhaust and batteries

manufacturing plants situated within the city Lahore are major sources of Pb contamination

to the river Ravi. Similar results were reported by Qadir and Malik (2011) for fishes of river

Chenab, Pakistan. Pb profile in the sampled fish species varied among different tissues at the

four sampling sites in two flow seasons. In the present investigation, higher value of Pb in

scales of C. catla (6.07±0.280 mg/kg), C. mrigala (5.85±0.094 mg/kg) and L. rohita

(5.74±0.329 mg/kg) are in agreement with Pb content of scales of Oreochromis mossambicus

(5.49-5.8 mg/kg) reported Jabeen and Chaudhry (2010a) who referred further that Pb

possessed a major affinity to reside in hard tissues like fins and scales of the fish. Results of

the present study indicated lower mean Pb accumulation in muscles than other fish organs. It

is known that Pb poorly accumulates in fish muscles (Bradley and Morris 1986; Wagner and

Boman, 2003). In the present study, significant seasonal variations in Pb accumulation were

recorded. Likewise, Mansour and Sidky (2002) and Mwashote (2003) and reported


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significant seasonal variations in Pb accumulation in fishes from African waters. Toxic effect

of Pb decreases with an increase in water hardness. High level of water hardness reduces

bioavailability of heavy metal (Wright and Welbourn, 2002). Factors such as age, sex and

food and interference of Pb with other chemical present in mixture of effluents affect the

adsorption process of Pb in fishes (Eisler, 1988; USEPA, 1999). Sub-lethal and acute lead

toxicity in fish causes renal disorders which interfere with glucose metabolism. Pb disrupts

haemoglobin synthesis and also interferes with uptake of potassium and calcium through the

gills. Fish affected by lead poisoning become disoriented and skin may peel off after long

term exposure to contaminated water (USEPA, 1999). Conclusively it could be interfered

that heavy load of lead in fish organs especially the muscles, could induce health hazards in

fish as well as in fish consuming communities.

Cr accumulation varied between 0.88 to 4.48 mg/kg, 0.71 to 3.90 mg/kg and 0.96 to

5.70 mg/kg in muscles of C. mrigala, L. rohita and C. catla, respectively. These levels were

higher than the standard permissible limits of 0.05 – 0.15 mg/kg in food fish (WHO 1985;

FEPA 2003). More bioaccumulation of Cr occurred during the low flow season. The results

are in agreement with those reported by Malik et al. (2010) for the muscles of Labeo rohita.

The highest Cr accumulation appeared in Kidneys of C. mrigala (10.38±0.216), L. rohita

(6.26±0.214) and C. catla (8.82±0.100). In view of the higher levels of Cr, than the WHO

limits, it could be inferred that consumption of these fish could lead to health hazards in

humans. All the sampled fish species showed higher bioaccumulation of Cr at downstream

sampling sites especially at site C than upstream sampling site A. Furthermore the metal

concentration were higher during low flow season than high flow season. Cr accumulations

differed significantly among sampling sites and season. Comparable results have been

reported by Qadir and Malik (2011) for inhabitant fish species of river Chenab, Pakistan.

Jabeen and Chaudhry (2010b) reported similar results for Cyrinus carpio from Indus river,


335

Pakistan. Chromium (Cr) is widely used in industries but it is considered as a serious

environmental toxicants. Unregulated disposal of chromium containing effluent has led to

contamination of soil, sediment and water. Exposure of Cr occurs by intake of contaminated

food and water and breathing contaminated air. It leads to various disorders including allergic

disease, liver damage, lung irritation and cancer. The toxic effect and bioaccumulation of Cr

in fish is highly influenced by water hardness, organic matter and development stage of fish

(USEPA, 1999). Higher concentration of Cr causes abnormal development of fish embryos,

over production of mucous and blood serum, malfunction of liver and chromosomal

aberration. High Cr bioaccumulation in fish tissues could be due to chromite deposits in the

close vicinity of the study area, and presence of tanning, and corrosion control plating and

pigment manufacturing units situated along the Hudiara drain both in Indian and Pakistani

sides of the river Ravi (Saeed and Bahzad, 2006).

Mercury (Hg) accumulation significantly differed among the sampling sites, seasons,

fish species and fishes’ organs. Mean Hg accumulation in the fishes’ organs were in the order

of liver > kidney > intestine > heart > scale > eyes > skin > gills. The lowest Hg

accumulation was recorded for the 0.14 mg/kg in fishes netted from site A. the mean values

ranged up to 0.34 mg/kg, 3.05 mg/kg and 2.54 mg/kg at the sites B, C and D, respectively.

Values at the two downstream sites exceeded the permissible concentration (0.5 mg/kg) for

edible fish (Forstner and Wittmann, 1981). Higher Hg concentration in kidney and liver are

related to detoxification and excretion processes of these organs. Furthermore, metals are

bound in liver to specific polypeptides (metallothioneins) as described by Jezierska and

Witeska (2001). The fishes’ gills contained significantly higher metal concentrations than

muscles in the present study. Mercury (Hg) is a highly toxic and most closely monitored

toxicant in fish. With the exception of occupational exposure, fish are recognized as the

single largest source of Hg toxicity for human being. Anthropogenic sources of mercury in


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the environment include municipal waste (incinerators) and certain industrial processes. The

most worrying form of mercury is Hg2+

because it dissolves quickly in water and is

consequently the most commonly found in the aquatic ecosystems. Mercury bioaccumulates

in fish mainly as methylmercury. In freshwater bodies, small organisms convert naturally

occurring inorganic mercury into organic methylmercury. Methylmercury binds with

particles and sediments which later on may be eaten by fish. As fish eliminate Hg at a much

slower rate, it accumulates in fish tissues and organs from wherein it can not be removed by

filleting or cooking. Hg inhibits enzyme activity and increases the abnormal cell division,

thus it is very important to investigate mercury contamination in fishes The fish species

which are at lower trophic level accumulate low metal concentration in comparison to those

occupy higher trophic level (Burger et al., 2001; Peakall and Burger, 2003). Heavy metals in

the fishes’ organs showed high bioaccumulation of metals especially mercury, nickel,

cadmium in the present study which indicated that these fishes are capable of accumulating

metals up to more than 3000 times the corresponding metals concentration in water.

Comparable finding has been reported by Onwumere and Oladimeji (1990) who described

that the fish, Oreochromis niloticus accumulated thousand times higher metals’ (Cd, Cr, Cu,

Fe, Pb, Zn and Mn) concentrations than their levels in the exposure medium. The present

study suggests that the sampled carp fish species were able to bioaccumulate different metals

in its different tissues with variable intensity. Impact of consumption of such metals

harbouring meat on the fish consumers of the study area, is to be determined.

5.7 Fatty acid analysis:

Variations in fatty acid composition of the fish muscles appeared for the different

sampling sites. Percentage of total SFA and PUFA were significantly (P<0.001) different,

whereas no significant (P>0.05) difference was detected in the percentage of total MUFA in

two flow seasons. The three carp fish species had, in general, SFA>MUFA>PUFA for all the


337

sampling sites. Highest total SFA in C. catla (60.82 %), L. rohita (56.92 %) and C. mrigala

(53.4 %) were found at site C. While lower contents of SFA in C. mrigala (40.8 %), L. rohita

(54.23 %) and C. catla (57.55 %) appeared at site A. The higher SFA in all fish species in the

present results are in line with the research of Jabeen and Chaudhry (2011) who have also

reported higher SFA in all fish species collected from Indus river, Pakistan. While by

Kalyoncu et al. (2011) reported contrary results that SFA were lower than MUFA at different

seasons. The literature also supports the finding of Kalyoncu et al. (2011) for other fish

species (Celik et al., 2005; Gulner et al., 2008).

In the present study, variations in fatty acid compositions in carp species may be

attributed to the seasons and pollutants’ loads. Increased levels of SFA have been reported by

Konar et al. (2010) in skin and muscle of Oncorhynchus mykiss exposed to Cd in comparison

with control. The higher SFA maintain the fish health and give them an advantage in curing

illness (Ugoala et al., 2009b). Sea water fish species have different fatty acid composition

when compared with freshwater fish species as they contain higher PUFA (27.4 – 49.2 %)

than SFA (21.1-39.6 %) (Visentainer et al. 2007). The difference may be due to the fact that

freshwater fish feed mainly on plant material, while marine fish feed on zooplankton which

are rich in PUFA (Osman et al., 2007). Palmitic acid among SFA, oleic acid among MUFA

was dominant in all the three fish species. Several researchers reported the same for oleic

acid among MUFA (Oliveira et al. 2003; Celik et al., 2005; Gonza’lez et al., 2006; Gular et

al., 2008; Akpinar et al., 2009; Osibona et al., 2009). These fatty acids often indicate kind of

diet and have exogenous origin (Ackman, 1989). Sharma et al. (2010) attributed higher

palmitic acid content of Labeo rohita to use of supplementary feed containing high amount

of palmitic acid, Memon et al. (2011) confirmed the origin of these fatty acids from diet for

C. mrigala, L. rohita and C. catla. Kalyoncu et al. (2011) showed highest level of oleic acid

among MUFA for Vimba vimba tenella in winter season. Similarly, Gular et al. (2008)


338

reported that oleic acid was the predominant MUFA in muscle of zander, Sander lucioperca

living in freshwater in Turkey. According to Akpinar et al. (2009), among MUFA, the major

fatty acid is oleic acid in muscle (22.4 -22.1 %) of male and female of Salmo trutta

macrostigma. The size, age, reproductive status of fish, geographical locations, degree of

pollution, nutrional condition, fish origin and water temperature influence the fatty acid

composition of fish muscle to certain extents (Ackman, 1989, Bandara et al., 2001, Kitts et

al., 2004). Fish muscle is essential source of PUFA with therapeutic effects on consumers’

health and play a vital role in the management of diabetes and autoimmune disorders

(Hooper et al., 2004). All the fish species showed higher content of omega-6 fatty acids than

omega-3. These finding are in line with the findings of Ugoala et al. (2009a) and reverse to

the report of Memon et al. (2011) in which farm carp fish is described rich in omega-3.

PUFA are characterized by high level of linoleic acid which is essential in human nutrition

being not synthesized in the body but required for tissue development (Ugoala et al., 2009b).

Docosahexaenoic acids (DHA) ranged from 0.49 to 1.17 % of the total fatty acids of the three

fish species from river Ravi. Thus meat of these fishes is characterized by healing effect for

alleviating muscle pain and inflammation as suggested by Jabeen and Chaudhry (2011).

Total PUFA decreased for C. mrigala 6.8 %, L. rohita 7.37 % and C. catla 3.74 % at

downstream sampling site C in comparison with site A and reflected pollutants’ stresses on

the inhabitant fishes. The levels of linoleic (ω 6) acid (1.29-5.13 %) and γ-linolenic (ω 3)

acid (0.07-0.36 %) were found to be different at the two seasons. Similar, seasonal variations

have been reported by Kalyoncu et al., 2011. Konar et al. (2010) documented significant

decrease in PUFA after exposure of cadmium in rainbow trout (Oncorhynchus mykiss).

While Choi et al. (2002) associated earlier reduction in PUFA with pollutant induction of

prostaglandin biosynthesis pathway. Likewise decrease in PUFA after chromium exposure


339

compared to control group has also been reported by Coban and Yilmaz (2011) in Cyprinus

carpio (common carp).

5.8 Conclusion:

Effect of urban effluents of domestic, industrial and agricultural origins increased for

the rive Ravi water in a diagrammatic way from their baseline values at the upstream site A

(Siphon) up to the site C (Sunder). While values of almost all the physiochemical parameters

of the river water and bed sediment fell within intermediate levels compared to the respective

differences recorded at the sites A and C. In fact at the last sampling site D (Balloki) the

physiochemical parameters did not further increase, rather many of them did express

decreasing trends as compared to the respective levels recovered for the site C, however, the

water quality in general did not recover to the level found at the upstream site A. Biphasic

nature of the physical and chemical parameters indicative of pollutants’ loads in terms of

increasing trend up to site C and a leveling off/decreasing look at the site D remained

consistent both for low and high flow seasons. However, for the later flow season due to

higher dilution rate’s effect for the river water the pollutants’ level followed the biphasic

graphic pattern for the four sampling sites but with, in general, lesser magnitudes of all the

parameters. For example, DO values ranged from 5.23 to 5.37 , 4.30 to 4.63, 3.80 to 4.17 and

4.13 to 4.40 mg/L at the site A, B, C and D during low to high flow seasons, respectively.

Likewise, total dissolved solid per liter of the sampled waters ranged from 580 to 164.7,

674.7 to 266.7, 948 to 436.7 and 741 to 360.3 for the site A, B, C and D, during low to high

flow seasons, respectively. In short all the analyzed parameters for assessing the river

pollution status qualified a three stepped changes followed by a plateau for the last sampling

locality. Negative allometric growth appeared for the fish species at the sites B and C.

Obviously for all the three fish species the growth coefficient was normal at site A. While at

site D it recovered and became better than the situation found at site C but could not


340

approach to the levels observed at the upstream locality. For C. mrigala the ‘b’ values at site

A through D during the low and high flow season were 3.16 and 3.19, 3.13 and 3.17, 3.07

and 3.08 and 3.14 and 3.15 respectively. More or less the same pattern was depicted by the

remaining two species. The growth coefficient also strengthened the biphasic pattern for

upstream and the downstream localities.

The trend of changes in proximate analyses appeared responsive to the downstream

locations; crude protein contents of the muscles showed increases while moisture,

carbohydrate, fat and ash contents decreases up to site C during both low and high flow

seasons. While the parameters more or less, stabilized at site D corresponding to the values

of the site C. Similar trend of changes in biochemical parameters like total and soluble

proteins and DNA contents of the muscles showed increases, while carbohydrate, total lipids,

cholesterol and RNA contents decreases up to site C with more or less recovery trend at site

D during both low and high flow seasons.

One of the major objectives of the present study was isolation of heavy metals

resistant bacteria from gut contents of the fish species inhabiting upstream as well as the

polluted segment of the river Ravi. The hypothesis was derived from the idea that the flowing

water microbial communities are highly dynamic in terms of their diversity as well as

population densities. While the fish gut environment represents a relatively stable

environment with continuous growth and expulsion of the resident and/or visiting bacteria.

Continuously growing bacteria exposed to pollutants’ loads are very prone for developing

resistance mechanisms. Presence of such pollutants’ resistance bacteria in gut of the fishes

may render the animals to survive in the otherwise toxic environment. In the present study

one hundred and twenty three heavy metals’ resistant bacteria were isolated from gut

contents of the three fish species. The bacteria could tolerate Cu, Hg, Cr and Pb ions up to

950, 1350, 65 and 1600 µg/ml in vitro. Inasmuch as the maximum heavy metals’ resistance


341

levels of bacteria isolated from the sampled fishes’ gut contents is concerned, they too

strengthened the diagrammatic pattern for the upstream and three downstream locations of

the river Ravi. It was interesting to note that all the reported isolates showed multiple metals’

resistances. Both allochthonous as well as autochthonous species were recovered.

Colonization of allochthonous microbes to the gut of animals has been reported a consequent

of environmental stress on the animals. Perhaps the carp fishes would not had shown normal

feeding levels as assessed by the ‘K’ values for all the three species at the three downstream

sites if they had not harboured the metals’ resistant bacteria in the guts. The bacterial species

recovered from the fishes may in future be required for recovering health status of heavy

metals exposed fishes. However, heavy metals detoxification status and resistances

mechanisms of these bacterial isolates is yet to be worked out.

Concentrations levels of heavy metals in the river’s waters and bed sediments as well

as their bioaccumulation in the fishes organs including muscles also followed the sitewise

pattern. Values of almost all the metals at sites B and D fell within intermediate levels

compared to the respective values for the site A and C. All metals’ levels in waters samples

were higher than the permissible limit recommended by NEQs. It was worth important to

note that Cr, Pb, Mn and Hg were much higher in muscles compared to the WHO

recommended values. It could be inferred that consumption of these fishes from study area

especially site C could lead to health hazards in humans.

In the present investigation, 12 saturated fatty acid (SFA), 15 monounsaturated fatty

acid (MUFA) and 11 Polyunsaturated fatty acid (PUFA) were observed to be present in

fishes muscles.. All three carp fish species had, in general, SFA>MUFA>PUFA for all the

sampling sites. Basically fish muscle is source of essential PUFA that may have therapeutic

effects on consumers’ health and play a vital role in the management of diabetes and

autoimmune disorders. Total PUFA levels decreased in the sampled fish species at


342

downstream sampling site C in comparison with the site A reflecting pollutants’ stresses on

the inhabitant fish. This study signifies a change in the fatty acid composition of the fish

species in response to the pollution loads within a relatively small segment of the river. This

change in fatty acid composition of fish may imply that the river water pollution can affect

nutritional quality of fish and subsequently the health of fish consuming communities.

Findings of the present study formulate a model for insults untreated industrial and

domestic origins’ effluent from a city characterized with a population load over 10 million to

the river in terms of the metals contaminations of its abiotic and biotic components. Length

of a river segment and its flow level in conjunction with prevalence of metals’ resistant

bacteria in the intestinal contents of fishes are important factors for identifying locations

where a river system starts recovering and could approach after traveling a more distinct

location to the physico-chemical and biochemical attributes of upstream sites. However,

many other factors such as water temperature, river bed biogeochemistry and geographical

locations are to be considered for pridicting river pollution loads and their detoxification and

recovry of the normal biota. Detailed information based model may guide for granting

permits to new industries and town planners. Obviously application of a such model would

be a transient stragy for saving the biodiversity before suitable legislation and its strict

compiling is made for proper treatment for both domestic as well as industrial effluents in

developing countries.

343

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