FATE AND EFFECTS OF HYDROCARBON-DEGRADING BACTERIA USED

TO INOCULATE SOIL FOR ON-SITE BIOREMEDIATION IN THE ARCTIC

EFFETS ET SURVIE DE SOUCHES MICROBIENNES UTILISÉES POUR LA

BIORESTAURATION DE SOLS CONTAMINÉS AUX HYDROCARBURES

DANS L'ARCTIQUE

A Thesis Submitted

to the Faculty of the Royal Military College of Canada

by

Eric J. M. Thornassin-Lacroix, BSc.

Captain

In Partial Fulfillment o f the Requirements for the Degree o f

Master o f Science

June, 2000

@Copyright by J.M.E. Thornassin-Lacroix 2000 This thesis may be used within the Department of National Defence but copyright for open publications rernains the property of the author.

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ACKNOWLEDGEMENTS

1 would like to thank first Dr. William Mohn. Associate Professor at the

Department of Microbiology and Immunology, University of British Coiumbia. and Dr.

Kenneth Reimer. Director of the Environmental Sciences Group. Royal Military College

of Canada. who provided me guidance throughout this Master's Degree. Their help.

support. and supervision were essential to the completion of this thesis.

1 would like to thank Matt Colden and the ESG field tram for their help in

building the biopiles and sampling them at multiple time points. The analytical work

could not have been done without the help of Gordon Stewart and Mikael Eriksson for

analyzing TPH in soi1 sarnples and the Biotechnology Lab Fermentation Pilot Plant

(UBC) for the preparation of the inoculum that was used in the field expenment.

1 am gratefül to Dr. Mohn's laboratory group for their amazing support and

incredible patience with regard to my many questions. My regards go especially to Dr.

Zhongtang Yu and Emma Master who accompanied me through the joy and pain of

molecular biology work and research. Without their experience and advice. this work

could not have been completed.

1 finally want to thank my fiancé Marie-Chantal who supported me al1 through

this time spent in British Columbia coping with my extended periods spent in the lab. Her

understanding, patience and encouragement inside and outside the lab encouraged me not

to give up.

ABSTRACT

Thomassin-Lacroix Eric J.M. M.Sc. (Env. Sciences). Royal Military College of Canada. June 2000. Fate and Effects of Hydrocarbon-Degrading Bacteria Used to Inoculate Soi1 for On-Site Bioremediation in the Arctic. Supervisors: Dr. William Mohn and Dr. Kenneth Reimer.

Numerous Arctic and sub-Arctic sites have been contaminated with a variety of

petroleurn hydrocarbons such as diesel and jet fuel. The low arnbient temperature and

short treatment season in the Arctic harnpers effective biodegradation of hydrocarbon-

contarninated soil. The main goal of this project was to study the effect of

bioaugmentation for on-site bioremediation of hydrocarbon-contarninated soi1 at

Canadian Forces Station (CFS) Alert. Ellesmere Island, Nunavut. The inoculum used for

this project was enriched from soil at CFS AIert for its capability to degrade jet fuel at

low temperature. The three most abundant organisms in the enrichment culture were

identified through 16s nbosomal DNA (rDNA) analysis. These organisms showed high

16s rDNA similarity to Rhodococcirs erythmpolis. Sphingornonus sp. UN 1 FI. and

Pserrdornonu.s symnrha. Three specific polymerase chain reaction (PCR) primer sets

were designed for these strains. and a PCR-most probable number (PCR-MPN) assay was

developed to monitor their fate. growth. and possible spread to nearby locations during a

field experiment. Results showed that both inoculated and uninoculated treatments

presented an average total petroleum hydrocarbon (TPH) removal of 75% over 65 days.

This result suggests that the density of the inoculum that was used (approximately log

cells per g dry soil) was not large enough to stimulate hydrocarbon removal and that the

indigenous population is aIready weli adapted to biodegrade these petroleum

hydrocarbons. Two of the three phylotypes were present in greater numbers in the

inoculated biopiles at O days than in the uninoculated ones. After 65 days of treatment.

populations of phylotypes were similar in both treatments. except for one phylotype (Ale-

1.14) which was less abundant in the uninoculated biopiles. A laboratory microcosm

experiment tested the effect of different inoculum densities and the fate of the three

strains and showed simitar results to the field experiment. The PCR assays were also used

to measure the dynamics of the three strains in the enrichment culture through time. The

results of this investigation showed that bioaugmentation did not stimulate hydrocarbon

biodegradat ion at C FS Alert and also that the indigenous hydrocarbon-degrading

microflora is abundant and already adapted to fulfill this task at this location. The

conclusions of this work will be directly applied to further on-site applications in the

remediation of hydrocarbon-contarninated soi1 in the Arctic.

Thornassin-Lacroix Eric J.M. M.Sc. (Sciences Env.). Collège Militaire Royal du Canada. Juin 2000. Effets et Survie de Souches Microbiennes Utilisées pour la Biorestauration de Sols Contaminés aux Hydrocarbures dans l'Arctique. Superviseurs: Dr. William Mohn et Dr. Kenneth Reimer.

Plusieurs sites localisés dans 1' Arctique canadien ont été contaminés avec diverses

sources d'hydrocarbures comme le diésel et le carburant à aviation. Les basses

températures qui prédominent ainsi que les étés très courts sont responsables d'une

biodégradation des hydrocarbures plus lente que dans les régions climatiques situées plus

au sud. J'ai étudié les effets de la bioaugmentation sur la biorestauration de sols

contaminés aux hydrocarbures à la Station des Forces Canadiennes (SFC) Alert qui est

située sur la pointe nord de l'Île Ellesmere dans le Temtoire du Nunavut. L'inoculum

utilisé pour cette expérience a été enrichi à partir d'un échantillon de sol de la SFC Alert

et a été cultivé à basse température avec du carburant à aviation comme seule source de

carbone. Les microorganismes les plus abondants dans la culture ont été identifiés à partir

de leur gène ribosomal 16s (16s rDNA). Les trois organismes les plus abondants ont

présenté une grande similarité à Rhodococc~cs erythropolis. Sphingomonas sp. UN 1 F 1 et

Psezidornonos synmthu. Trois paires d'amorces qui sont spécifiques à chacune des

souches ont été construites et une technique de réaction de polymérase en chaîne-nombre

le plus probable (PCR-MPN) a été developée afin de suivre leur croissance, leur survie et

aussi de mesurer si ils ont la capacité de se déplacer de l'endroit ou ils ont été introduits.

Les résultats obtenus ont démontré que les traitements inoculés et non-inoculés ont tout

vii

deux présenté une baisse des hydrocarbures d'environ 75% sur une période de 65 jours.

Ce résultat suggère que la densité de l'inoculum utilisée (approximativement 10' cellules

par gramme de sol sec) n'était pas assez grande pour stimuler la biodegradation des

hydrocarbures et aussi que la population microbienne indigène est déjà élevée et très bien

adaptée à dégrader ces composés organiques. Deux des trois souches les plus abondantes

de l'inoculum ont été détectées dans les biopiles inoculées et en moins grand nombre

dans les biopiles non-inoculées au début de l'expérience. Après 65 jours de traitement.

les souches étaient en nombres égaux dans les deux traitements excepté pour Ale- 1.14 qui

etait en moins grand nombre dans les biopiles non-inoculées. Une expérience impliquant

des microcosmes a testé les effets de différentes densités d'inoculum ainsi que la survie

des souches microbiennes et a présenté des résultats similaires à ceux de l'expérience a la

SFC Alert. Les résultats de ce projet ont démontré que l'utilisation d'un inoculum pour la

biorestauration de sols contaminés à la SFC AIert n'a pas stimulé la biodégradation des

hydrocarbures. De plus. la microflore indigène responsable de la biodégradation des

hydrocarbures est déjà nombreuse et très efficace à effectuer cette biotransformation dans

les sols contaminés à la SFC Alert.

viii

TABLE OF CONTENTS

Page

ABSTRACT ........................ .... .................................................................................. iv

... TABLE OF CONTENTS ................................................................................................. vrii

LIST OF FIGURES .........................................................................................................xi

... LIST OF TABLES ........................................................................................................... x111

ABBREVIATIONS AND SYMBOLS ........................................................................... .xiv

1 . INTRODUCTION ............. ................. ....................................................................... 1 1.1 Fuel spills in the Arctic ....................................................................................... . . . I

7 1.3 Review of bacterial metabolism of hydrocarbons ...................................................... 1 .2.1 Aero bic degradation ............................................................................................... -3 1 2.2 Anaerobic degradation ........................................................................................... -7 1.3 Physical. chernical . and environmental factors affecting the biodegradation of

.................................................................................................................... hydrocarbons 11 ............................................................................................................ 1 .3.1 Temperature 1 1

1.3 -2 Nutrients .................................................................................................................. 13 1 .3.3 Chemical composition of petroleum hydrocarbons ................................................ 15 1.3.4 Bioavailability ............................. .... ................................................................. 16 1.3.5 Geophysiochemical properties of the soi1 .......................................................... 19

.................................................................................................................... 1 2.6 Oxygen 20 1.3.7 Water activity .......................................................................................................... 21

37 1.3.8 pH ............................................................................................................................. - 73 1.4 Biological factors affecting the biodegradation of hydrocarbons ............................... - 77 1.4.1 Acciimation period .................................................................................................. --

1.4.2 Adaptation and effect of prior exposure ................................................................ -23 ...... 1.43 Adaptation by alteration of genetic composition of the microbial community 24

1.4.4 Role of plasmids in adaptation ................................................................................ 25 ......................................................................................... 1.4.5 Synergism and predation 26

.............................................................................................................. 1.4.6 Inoculation 27 1.5 Technologies available for hydrocarbon biodegradation ........................................... 30

......................................................................................... 1 .5 . I Intrinsic Bioremediation 30 1-52 Landfarming ............................................................................................................ 31

...................................... 1 S.3 Composting biotreatment .. ................................................ 32

TABLE OF CONTENTS . CONTWUED

1 -5 -4 Engineered biopiles ................................................................................................. 32 1 S.5 Bioventing and biosparging .................................................................................... 35 1 S .6 Phytoremediation .................................................................................................... 36 1.6 Phylogenetic identification and species-specific detection of hydrocarbon

.......................................................................................................................... degraders 37 1 -7 Canadian Environmental Protection Act (CEPA) reguiations ................................... 43

..... 2 . THESIS OBJECTIVES ......... ............ ...........,,,.............. ....46 2.1 Nature of the problem ................................................................................................ 46

.................................................................................................................... 2.2 Rationale 47 .................................................................................................................. 2.3 Objectives 48

3 . MATERIALS AND METHODS ................... .. ................................................... 49 . . Site description and soi1 source ....................... .. ...................................................... 49 Site ctimate ................................................................................................................. 50 Alert- 1 enrichment culture ......................................................................................... 51 Field experiment at CFS Alert ................................................................................... 54

............................................................................................... Laboratory experiment 56 DNA extraction from Iiquid culture ........................................................................... 57 DNA extraction from soi1 and DNA purification .................................................... 3 8 16s rDNA PCR and DNA sequencing ...................................................................... 59

................................................................................................ Phylogenetic analysis 60 . .

3.1 0 Restriction Fragment Length Polymorphism (RFLP) analysis .............................. A 0 3.1 1 Phylotype-specific oligonucleotide primers ............................................................ 61

................................................................................................... 3.12 Primers specificity 64 ..................................................................................................... 3.1 3 PCR-MPN assay -64

3.14 Enumeration of total viable bacteria and hydrocarbon-degraders ........................... 67 3.1 5 Soi1 sarnpling . soi1 physical and chemical properties . and TPH analysis ................ 68 3.16 Statistics ................................................................................................................ 70

4 . RESULTS ......................... ........................ .....71 4.1 Alert- 1 enrichment culture ........................ ... .............................................................. 71 4.2 Field experiment ........................................................................................................ 82 4.3 Laboratory experiments ............................................................................................. 89

5 . DISCUSSION ........................................................................................................... ..97 5.1 Alert- 1 enrichment culture ......................................................................................... 97 5.2 Field experiment ........................................................................................................ 104 5.3 Laboratory experiment ............................................................................................... 109 5.4 Statistical evaluation of the field and the microcosm experiments ............................ 114 5.5 CEPA notification of new substances ................................................................... 1 1 7

TABLE OF CONTENTS. CONTINUED

6 . CONCLUSIONS ........................................................................................................ 120

........................................................................................................... 7 . RE FERENCES 121

8, APPENDICES ........................................................................................................... 139 Appendix A GenBank submission data for Ale- 1 .6 . Ale- 1 .1 4. and Ale- 1 -46 ................ -139

................... Appendix B TPH concentration and soi1 water content in field experiment 142 Appendix C Analysis of variance CANOVA) tables ..................... .. ..................... 145

LIST OF FIGURES

Figure Page

I . 1 : Aerobic degradation of aliphatic hydrocarbons and metabolic pathways ................ 6

1-3: Postulated pathways of anaerobic toluene degradation based on results from several laboratories ................................................ ... ................................................. 9

1 -3 : Schematic representation of a hydrocarbon-contaminated soi1 particle ................... 21

1-4: Side view of a biopile with passive aeration ........................................................ 34

1-5: Phylogenetic relationships arnong life f o m s based upon rRNA sequences ............ 41

3-1 : CFS Alert (marked by an anow) . Ellesmere Island . Nunavut ................................. 50

3-2: 0.8% agarose gels showing PCR amplified 16s rDNA gene fragments in a serial dilution method .................................................................................................... 67

4- 1 : DNA extraction from Alert-1 enrichment culture ........................................... 72

4-2: The 973 bp fragment from the 16s rDNA gene amplified from the genomic ................................................................................. DNA of Alert- 1 enrichment culture 72

4-3: 0.8% agarose gel showing Alert- 1 clones containing the 973-bp 16s rDNA inserts afier digestion with EcoRl ............................................................................... 73

4-4: Phylogenetic distribution of the 29 clones partiaIly sequenced in the Alert- 1 165 rDNA library ............................................................................................................. 76

4-5: Unrooted tree showing phylogenetic relationship of Alert-1 enrichment culture clones (in bold) and representative members ................................................... 77

4-6: Restriction patterns of the 16s rDNA genes from the 5 1 clones in the Alert- 1 . 16s rDNA Iibrary ............................................................................................................. 78

4-7: Distribution in OTUs among 54 bacterial 1 6 s rDNA clones from the Alert-l enrichment culture after digestion with Msp 1 ................................................................. 79

4-8: Estimation of diversity in the Alert-1 enrichment culture afler digestion with ................................................................................................................................. Mspl 79

xii

LIST OF FIGURES (CONTNUED)

4-9: Abundance of the three most abundant phylotypes and the total bacterial population in the Alert- 1 enrichment culture versus time ............................................... 8 1

4-1 0: Outside temperature at CFS Alert during the field experiment (provided by Environment Canada) ...................................................................................................... 83

4-1 1 : Final biodegradation of TPH in the field experiment showing the progress between the control and inoculated biopiles after 65 days of treatment .......................... 84

4-1 2: Population of phylotypes in the control and inoculated biopiles at CFS Alert afler O and 65 days of treatment ............................ ... ........................................................ 86

4-13: Spatial sarnpling locations around the experimental site in order to measure if the inoculated strains can spread to nearby locations ............................................ 88

4-14: TPH removal in the microcosm experiment ........................................................... 92

4-1 5: Chromatogram of the TPH at the start and the end (92 days) o f the microcosm experiment showing the removal o f straight aliphatic compounds. ................................ 93

4-16: Populations of phylotypes in the microcosm experiment at 4 and 29 days ............ 94

4-1 7: Enumeration of total viable heterotrophs in the microcosm experiment at 4 and 29 days in TSB ( 10% strength) medium ............................................................... 96

4- 18: Enumeration of hydrocarbon degraders in the microcosm experiment at 4 and 29 days in the hydrocarbon medium .................................................................... 96

LIST OF TABLES

Table Page

1 . 1 : Factors enhancing aerobic biodegradation of petroleum hydrocarbons ................... 4

1-2: Compounds degraded under anaerobic conditions .............................................. 10

1-3: Chemical composition of Jet Fuel A compared to diesel fuel ............................... 16

1-4: Effects of Ryegrass on hydrocarbon degradation in soi1 ................... .. ................ 37

.............................................................................. 1-5: Ribosomal RNAs in Prokaryotes 38

1-6: 16s rRNA sequences cornparison between different organisms .............................. 39

1-7: Group-specific 16s rDNA sequencing primers .................... .. ........................ 43

3- 1 : Universal and phylotype-specific PCR primer sequences ................................... 63

3-2: Theoretical alignrnent of sequences of the phylotype-specific primers designed for Ale- 1.6. Ale-1.14, and Ale- 1.46 with database sequences of 165 rDNA genes from species tested and not tested by PCR ............................................................................... 65

3-3: Phylotype-specific primers: annealing temperature and product size ...................... 66

3-4: CFS Alert soi1 physical and chemical characteristics ............................................... 70

........ 4- 1 : Phylogenetic association of 29 clones based on partial 1 6s rDNA sequences 74

4-2: Soi1 samples collected from the experimental site before the start of the experiment (lune 1 5'h . 1999) and afier 65 days (September 1 9th . 1999) ......................... 90

4-3: Analysis of CFS Alert pristine sarnples for TPH and phylotype detection .............. 91

xiv

ABBREVIATIONS AND SYMBOLS

bp %TEX OC CEPA CFS D AP DIS0 DND DNA dNTP ESG GC GC-FID kb MPN OTU PCR PCR-MPN POL PPm rDNA RDP RFLP RMC Sab TPH U vol/wt

base pair Benzene. Toluene. Xylene. Ethylbenzene degrees Celsius Canadian Environrnental Protection Act Canadian Forces Station diammonium phosphate Defence Information Services Organization Departrnent of National Defence deoxyribonucleic acid deox yc ytidine 5' -triphosphate Environmental Sciences Group gas chromatograph gas chromatograph - flarne ionization detector kilobase most probable number operational taxonomic unit polymerase chain reation polymerase chain reation - most probable number petroleum. oil. lubricant parts per million or mgkg ribosomal DNA ribosomal database project restriction fragment length polymorphism Royal Military College similarity rank total petroleum hydrocarbons unit volume per weight

1. INTRODUCTION

1.1 Fuel spills in the Arctic

Numerous Arctic and sub-Arctic sites have been contaminated with a variety of

petroleum hydrocarbons such as diesel and jet fùel (1 -4). These spills occurred in regions

where petroleurn hydrocarbons were extensively used for day-to-day operations. Many of

these sites are former and active military stations where the spills happened in accordance

with practices and operations that were normal at that time. With increasing attention

towards the preservation of the environment and also decommissioning of former

military sites. the clean up of hydrocarbon-contaminated environments has gained

increasing interest. Most investigations on the biodegradation of organic pollutants

concern petroleum hydrocarbons. because oil and petroleum spills represent a widespread

problem in these northern locations. There are three main potential sources of

environmental pollution with petroleum hydrocarbons: (i) continuous low-level inputs

from road surfaces and domestic waste. (ii) major spillage from tankers. pipelines and

storage tanks. and (iii) slow, natural seepage from natural oil reservoirs (5 ) . Accidental

contamination of soi1 with hydrocarbons occurs primarily through production,

transportation and storage accidents such as rupture of pipelines or storage tanks. road

accidents or during refueling activity (6) .

It is estimated that the annual global input of petroleurn to the environment is

between 1.7 and 8.8 million metric tons, the majority of which is derived from

anthropogenic sources (7). Biodegradation of hydrocarbons by natural populations of

microorganisms represents one of the primary rnechanisms by which petroleum and other

hydrocarbon pollutants are eliminated from the environrnent. The effects of

environrnental parameters on the microbial degradation of hydrocarbons. the elucidation

of metabolic pathways and genetic basis for hydrocarbon dissimilation by

microorganisms. and the effects of hydrocarbon contamination on microorganisms and

microbial communities have been areas of intense interest and the subjects of several

reviews (8- 10).

1.2 Review of bacterial metabolism of hydrocarbons

Hydrocarbons are a ubiquitous class of natural compounds. Not only are they

found in petroleum-polluted areas, but small concentrations are present in most soils and

sediments ( 1 1 - 1 2). It is therefore not surprising that hydrocarbon-oxidizing bacteria are

located in virtually al1 natural areas. although with large variations in numbers and

species diversity (13). The reason why petroleum hydrocarbons are a major ecological

problem is that hydrocarbon-degrading microorganisms must have available sources of

oxygen, nitrogen and phosphate. elements which are not present in sufficient quantities in

cmde oit and petroleum products. Thus. effectiveness of a bioremediation program

depends on defining the environrnental limitations and overcoming them in a practical

way.

Several conditions must be satisfied for biodegradation to take place in an

environment (14). (Table 1-1). These include the following: (a) An organism that has the

necessary enzymes to bring about the biodegradation must exist. The mere existence of

an organism with the appropriate catabolic potential is necessary but not suficient for

biodegradation to occur. (b) That organism must be present in the environrnent

containing the chemical. Although some microorganisms are present in essentially every

environment near the earth's surface. particular environments may not contain an

organism with the appropriate enzymes. ( c ) The chemical must be accessible to the

organism having the requisite enzymes. Many chemicals persist even in environments

containing the biodegrading species simply because the organism does not have access to

the cornpound that it would othenvise degrade. Inaccessibility may result from the

substrate being in a different microenvironment from the organism, in a solvent not

miscible with water. or sorbed to solid surfaces. (d) If the initial enzyme bringing about

the degradation is extracellular. the bonds acted upon by that enzyme must be exposed

for the catalyst to function. This is not always the case because of sorption of many

molecules. (e) Should the enzymes catalyzing the initial degradation be intracellular. the

target molecule must penetrate the surface of the ce11 to the intemal sites where the

enzyme acts. Altematively. the products of an extracellular reaction must penetrate the

ce11 for the transformation to proceed further. (f) Because the population or biomass of

bacteria or fungi acting on many synthetic compounds is initially small. conditions in the

environment must be conducive to allow for proliferation of the potentially active

microorganisms.

1.2.1 Aerobic degradation

In general. aerobic metabolism of hydrocarbons requires oxygenase enzymes,

which incorporate molecular oxygen into the reduced substrate. Typicaily with aliphatic

hydrocarbons, alcohols are initially produced; these are oxidized sequentially, via

dehydrogenases, to carboxylic acids, which then undergo P-oxidation. In the case of

aromatic substrates. as well as polyaromatic hydrocarbons (PAH). hydroxylation of a ring

occurs via mono- o r dioxygenase e n q m e s in eukaryotes and prokaryotes (15). Afier di01

formation, the ring is cleaved. then further degraded. Of course, many variations to these

rnetabolic schemes exist depending of the environmental conditions. the pollutants. and

the microorganisms involved.

Table 1 - 1 : Factors enhancing aerobic biodegradation of petroleum hydrocarbons

A. Microorganisms with: 1. Hydrocarbon-oxidizing enzymes 2. Ability to adhere to hydrocarbons 3. Emulsifier-producing potential 4. Mechanisms for desorption from hydrocarbons

B. Water C. Oxygen D. Phosphorus E. Utilizable nitrogen source Adapted from ( 1 6).

Aerobic microbial degradation of hydrocarbons is a multiphase reaction,

involving oxygen gas. water-insoluble hydrocarbons, water. dissolved salts and

microorganisms. The fact that the first step in aerobic oxidation of hydrocarbons often

involves a membrane-bound oxygenase makes it essential for microorganisms to corne

into direct contact with the hydrocarbon substrate. Growth then often proceeds on the

hydrocarbodwater interface. Bactena have developed two general strategies for

enhancing contact with water-insoluble hydrocarbons: specific adhesion mechanisms and

production of extracellular emulsifying agents. Many hydrocarbon-degrading

microorganisms produce extracellular emulsifiing agents. In some cases. ernulsifier

production is induced by growth on hydrocarbons ( 1 7).

Several reviews have been published on the microbial metabolism of straight-

chain and branched alkanes (1 8), cyciic alkanes (1 9) and aromatic hydrocarbons (1 5). It

has been established that the tirst step in the aerobic degradation of hydrocarbons by

bacteria is usually the introduction o f molecular oxygen into the hydrocarbon. In the case

of aromatic hydrocarbons. ring fission usually involves a dihydroxylation reaction and

the subsequent formation of a ch-dihydrodiol (20) and is carried out by a membrane-

bound enzyme system (2 1 ). Further oxidation leads to the formation of catechols (Fig. 1 -

1 ) that are substrates for another deoxygenase that catalyzes ring tission (22).

In general. alkanes are terminally oxidized to the corresponding alcohol. aldehyde

and fany acid (23). Fatty acids derived from alkanes are then further oxidized to acetate

and proprionate (odd-chain al kanes) by inducible oxidation systems. Di fferent

microorganisms exhibit different group specificities. For example. some grow on alkanes

of six to ten carbons in chain length. whereas others grow on long- chain alkanes. Some

of the oxygenases are encoded on plasmids and others on chromosomal genes.

Subterminal oxidation apparently occurs in some bacterial species (24).

- - - - - - -

Aero bic Degradation of the BT EX C hemicals

Ethylbenzene

Toluene: R = CH3

Ethylbenzene: R = CHzCH3

Fig. 1 - 1 : Aerobic degradation of aliphatic hydrocarbons and metabolic pathways.

1.2.2 Anaerobic degradation

Metabolic steps in the biodegradation of hydrocarbons follow two major strategies:

oxidation and/or reduction. Because hydrocarbons are already chemically reduced and

stable compounds (a practical demonstration of this is the longevity o f petroleum

reservoirs). further reduction. while thermodynamically possible. is not a primary mode

for biodegradation. even under strict anaerobic conditions. A number o f reports (25-28)

have demonstrated that tohene. benzene. and a variety of alkanes can be biodegraded

under the strictest o f anaerobic conditions by sulfidogenic and methanogenic cultures. In

these well-docurnented cases. anaerobic metabolism still follows an oxidation strategy. In

the absence of molecular oxygen. water-derived oxygen serves as a reactant, while

carbon dioxide or sulfate serve as the electron acceptors for anaerobic oxidation of the

substrates to hydroxylated aromatic compounds or fatty acids. respectively; further

metabolism can then follow one of several established routes. such as ring cleavage and

P-oxidation. Table 1-2 lists several compounds that can be degraded under anaerobic

conditions.

Hydrocarbon biodegradation under anaerobic. denitrifying conditions also follows an

oxidative strategy. In the presence of nitrate. hydrocarbon substrates, e.g.. toluene. are

metabolized to oxidized intermediates pnor to further biodegradation (29-3 1). In a series

of well-documented laboratory and field studies on the degradation of BTEX

contaminants in a nitrate-amended, subsurface aquifer soil, Hutchins and coworkers (32)

and Barbaro et al. (33) reported that the substituted aromatics, toluene, ethylbenzene, and

xylenes were biologically removed from the soil under denitrifying conditions. In the

same studies. benzene levels dropped only after small amounts of molecular oxygen were

provided. presumably to aid the initial ring oxidation of the molecule by oxygenases. For

unsubstituted aromatics. oxygenation may help to "prime" the molecule for further attack

by destabilizing the aromatic ring via delocalization of its rr: electrons. This "priming"

phenornenon has practical implications in the field. Reduced substrates will. at best.

undergo only very slow biodegradation in anaerobic or oxygen-limited subsoils.

However, oxidized metabolites produced near the surface may migrate down in the lower

depths and be more readily degraded in the oxygen-limited subsurface. where altemate

electron acceptors such as sulfate or nitrate predominate. In addition. partially oxidized

metabolites are generally more water-soluble and may partition more readily into the

aqueous phase. Fig. 1-2 lists some postulated pathways of anaerobic toluene degradation

based on results from several laboratories.

Anaerobic degradation of petroleum hydrocarbons in natural environments by

microorganisrns has been shown in some other studies to occur only at negligible rates

(25. 34. 35), and its ecoiogical significance has been generally considered to be minor (8.

36-38). However. the microbial degradation of oxidized aromatic compounds such as

benzoate (39) and of halogenated aromatic compounds such as the halobenzoates (40).

chlorophenols ( I I ) . and polychlorinated biphenyls (42) has been shown to occur under

anaerobic conditions (Table 1 -2). Recent evidence also indicates that microbial consortia

from soi1 and sludge are capable o f metabolizing unsubstituted and substituted aromatic

compounds, including benzene, toluene, xylene, 1,3-dimethytbenzene, acenaphtene, and

naphthalene. in the absence of molecular oxygen (26,43,44).

Fig. 1-2: Postulated pathways of anaerobic totuene degradation based on results from several laboratories. Initial steps in the pathway shown are (i) oxidation of the methyl group; (ii) carboxylation of the aromatic ring: (iii) hydroxylation of the methyl group; (ivj para-hydroxylation of the ring. 1, Toluene; 2. benzoate; 3. toluate;. 4. benzyI alcohol; 5. benzaldehyde; 6. benzoate; 7. p-cresol; 8, p-hydroxybenzylalcohol; 9. p- hydroxybenzaldehyde: 10. p-hydroxybenzoate. Adapted from (45).

Hydroxylation of the aromatic ring of toluene and benzene is believed to depend on water

as a source of oxygen (26). Nitrate can act as the final electron acceptor under

denitrifying conditions (44). The amount of substrate removed by anaerobic

biodegradation can be significant; at least 50% of benzene and toluene were mineralized

in 60 days under methanogenic conditions (26), and naphthalene and acenaphthene were

degraded to nondetectable levels in 45 and 40 days, respectively, under denitriQing

conditions (44).

Table 1-2: Compounds degraded under anaerobic conditions

Chloroalkanes and alkenes Carbon tetrachloride C hloroform Vinyi chloride 1 -2-Dic hloroethane 1.1.1 -Trichloroethylene Trichloroethylene 1.1.3.2-Tetrachloroethane TetrachloroethyIene

Phenols Phenol 2- and 3-Chlorophenol 2,4- and 2.5-Dichlorophenol Trichlorophenols Tetrachlorophenols Pentachlorophenols 2-, 3-, and 4-Nitrophenol

-

Benzoates Benzoate 2-. 3-. and 4-Chlorobenzoate 3.4- and 3,5-Dichlorobenzoate

Aromatic hydrocarbons Toluene Ethy lbenzene O- and m-Xylene

Others Highly chlorinated PCBs DimethyI phthalate P yridine Quinoline m- and p-Cresol 2.4-D 2.4.5-T Diuron Linuron

Adapted from (46).

The importance of anaerobic biodegradation of aromatic hydrocarbons in the

environment is unknown. and further studies are required to elucidate anaerobic

pathways, as well as determine whether other hydrocarbons. such as alkanes, and

hydrocarbon mixtures. such as crude oil. can be fully degraded under denitrifying or

methanogenic conditions. Although there is a growing arnount of evidence that reduced

substrates such as hydrocarbons c m indeed be biodegraded in the absence of molecular

oxygen, biodegradation proceeds more rapidly and eficiently under nontimiting, aerobic

conditions. where oxygen is available to serve both as reactant and electron acceptor in

metabolism. The higher biodegradation rates observed in aerobic environments often are

indicative of faster aerobic growth rates and may reflect a greater net production of

energy during oxidative phosphorylation and electron transport. Biodegradation under

aerobic conditions is usually more --complete", resulting in greater rates of mineralization

of the hydrocarbon contaminant to its ultirnate endproducts. carbon dioxide and water.

This apparent effect of the extent o f biodegradation also has important implications for

the field. To minimize future liabilities from a contarninated site. it is essential that a

bioremediation process be conducted to minimize the formation of undesirable

interrnediary metabolites. which may be mobile and/or toxic while maximizing

biodegradation of the contarninants to their ultimate and harmless endproducts.

1.3 Physical, chernical, and environmental factors affecting the biodegradation of hydrocarbons

1.3.1 Temperature

Temperature influences petroleum biodegradation by its effects on the physical

nature and chemical composition of the hydrocarbons, rate of hydrocarbon degradation

and composition of the microbial community (8). At low ternperatures. the viscosity of

oil increases. the volatilization of toxic short-chain alkanes is reduced, and their water

solubiIity is increased. delaying the onset of biodegradation (47). Rates of degradation are

generally observed to decrease with decreasing temperature; this is believed to be a result

primarily of decreased rates of enzyme activity (47,48). Climate and season are expected

to select for different populations of hydrocarbon-utilizing bacteria that are adapted to

ambient temperatures. Colwell et al. (49) reported extensive degradation of Metula crude

oil by mixed cultures of marine bacteria at 3°C. and Huddleston and Cresswell (50)

observed petroleum biodegradation in soi1 at -l.l°C.

Most laboratory studies on the biodegradation of hydrocarbons have involved

microorganisms that can grow at temperatures of 25-35°C. Mesophilic microorganisms

are usually metabolicaIly inactive at temperatures 58-10°C. In many regions,

environmental conditions select populations with a low optimal temperature for

biodegradation. Cold-adapted microorganisms are able to grow and multiply even at O°C

and below. Their minimum. optimum and maximum temperature for growth are

respectively 04°C. >15 and >20°C for psychrotolerants, and 50. 115 and 9 0 ° C

respectively for psychrophiles (51). Cold-adapted strategies include the molecular

adaptation of membrane lipid composition, protein synthesis and enzyme activity (1. 52).

Cold-adapted microorganisms can be very sensitive to increased temperatures. Many

hydrocarbon-degrading bactena isolated at 1 O°C grow well at 15°C but not at al1 at 25°C;

similarly a bacterium isolated at 8°C failed to grow at 18°C and was killed within 10 min

at 25°C (53).

Since %O% of the biosphere has temperatures <5"C. cold-adapted

microorganisms are widely distributed in nature. with Gram-negative bacteria being

dominant (54). Hydrocarbon degraders are ubiquitous in most ecosystems. They

comprise less than O. 1% of the microbial community in unpolluted environments but can

constitute up to 100% of the culturable microorganisms in hydrocarbon-polluted

ecosystems (8). In most environments, enrichment of hydrocarbon-degrading microbial

populations occurs soon after hydrocarbon contamination.

1.3.2 Nutrients

The nutrient status of a soil directly impacts rnicrobial activity and

biodegradation. To grow. heterotrophic bacteria require. in addition to an organic

compound that serves as a source of carbon and electron donor, a group of other nutrient

elements and an electron acceptor. The electron acceptor for aerobes is oxygen. but it

may be nitrate. sulfate. CO,. ferric iron. or organic compounds for specific bacteria able

to utilize these substances to accept the electrons released in the oxidation of the electron

donor. Many bacteria and fungi also require low concentrations of one or more arnino

acids. B vitarnins. fat-soluble vitarnins. or other organic molecules; these trace organic

nutrients are termed growth factors. These growth factors are generally present in most

soils in concentrations acceptable for cellular metabolic activities. Nitrogen. and to a

lesser extent phosphorus, are necessary for cellular metabolism and can be found in low

concentrations in many soils, including Arctic soils (55-58) . It should be noted, however.

that excessively high nitrogen loadings. e-g.. C/N ratios less than 20. may resuIt in an

inhibition of soil microbial activity. possibly due to nitrite toxicity. These values are used

as guidelines and a treatability study always should be conducted before undertaking any

bioremediation of contaminated soits. Many studies have been conducted on the effects

of biostimulation in Arctic soils and they al1 reported positive effects o f nutrient addition

(55-57). The input of large quantities o f carbon sources (i.e. petroleum hydrocarbons)

tends to result in a rapid depletion of available pools of the major inorganic nutrients such

as nitrogen and phosphorus.

One of the major limitations in the biodegradation of hydrocarbons on land and

water is then an available source of nitrogen and phosphorus. In theory, approximatety

150 mg of nitrogen and 30 mg of phosphorus are consumed in the conversion of 1 g of

hydrocarbon to cet1 material. Numerous field and Iaboratory studies report a wide

application range for nitrogen andor phosphorus supplementation to soil. On a CM

molar basis. reports for optimal fertilizer applications range from approximately 2 to 200

for nitrogen (5. 59). Another way to calculate the ratio of N and P to be added is to

estimate the amount of C in the material to be degraded. For example. if it is assurned

that 30% of the C is assimilated into the biomass of cells carrying out the bioremediation

and that the resulting biomass has a C: N: P ratio of 50: 5: 1. the arnount of N and P to be

added would be equivalent to 3 and 0.6% (dg) of the C: Le.. for IO0 units of substrate-C.

30 units of biomass-C would be formed. and 3 units of N and 0.6 units of P would be

needed by that biomass. Such calcuIations often considerably overestimate the need for N

and P because (a) the biomass is itself decomposed, which renders the N and P available

once again to further enhance the bioremediation. and (b) the soil witl contain some

available N and P for microbial use. Overuse of fertilizer N and P results in an unwanted

expense and may also result in nitrate pollution of ground or surface waters. Hence. an

initial laboratory study is often performed to determine the appropriate amount of

fertilizers to add. That assessrnent may include determination of the amount of available

N (typically ammonium and nitrate) and available (but not total) P in the soil.

The nitrogen and phosphorus requirements for maximum growth of hydrocarbon

oxidizers can generally be satisfied by ammonium phosphate. Altematively, these

requirements can be met with a mixture of other salts, such as ammonium sulfate,

ammonium nitrate, ammonium chloride, potassium phosphate, sodium phosphate and

calcium phosphate. When ammonium salts of strong acids are used, the pH o f the

medium generaIly decreases with growth. This problern can be overcome by using urea

as the nitrogen source. Al1 of these compounds have a high water solubility that reduces

their effectiveness in open systems because of rapid dilution. In principle. the problem

c m be solved by using oleophilic nitrogen and phosphorus compounds with low C:N and

C:P ratios. For example. it was found that a combination of paraffinized urea and octyl

phosphate was able to replace nitrate and inorganic phosphate. respectively (60). Urea

and diarnmonium phosphate (DAP) were both used as fertilizers in both the field and

microcosm experiments described in this project at a C:N:P ratio of 100:3.25:0.75 as it

was recommended by past experiments dealing with CFS AIert hydrocarbon-

contaminated soi1 ( 6 1 ).

1.3.3 Chernical composition of petroleum hydrocarbons

Petroleum hydrocarbons can be divided into four classes: the saturates. the aromatics.

the asphaltenes (phenols. fatty acids, ketones, esters. and porphyrins). and the resins

(pyridines. quinolines. carbazoles. sulfoxides, and amides). (1 0). Hydrocarbons differ in

their susceptibility to rnicrobial attack and. in the past. have generaliy been ranked in the

following order of decreasing susceptibility: n-alkanes > branc hed alkanes > low-

molecular weight aromatics > cyclic alkanes (1 9). Biodegradation rates have been shown

to be highest for the saturates. followed by the light aromatics. with high-molecular-

weight aromatics and polar compounds exhibiting extremely Iow rates of degradation

(62-64).

The type and size of chemical structure may indirectly affect biodegradability by

altering the bioavailability of the contaminant to the degrading microorganisms. Because

hydrocarbons are hydrophobic. water-insoluble compounds, bioavailability is perhaps

key to determining a contaminant's biodegradation potential. Biodegradability of

hydrocarbons in soils has been demonstrated to correlate to their water solubilities. which

are generally inversely proportional to their respective molecular weights (65. 66). Other

structural attributes. such as degree of unsaturation. can affect water solubility and

ultimately uptake and availability to the degrading microorganisms. Given the same. or

similar molecular weight unsaturated and aromatic compounds exhibit greater water

solubility. Table 1-3 lists the chemical composition o f Jet Fuel and diesel fuel and shows

that Jet Fuel has a greater monocyclic arornatic hydrocarbons content (mainly BTEX

compounds) than diesel fuel.

Table 1-3: Chemical composition of Jet Fuel A compared to diesel fueln

Constituents Jet Fuel A Diesel fuel (vol. %) (W. %)

Methyl alkanes 3.26 - 3.32 0.45 Methyl alkenes O MonocycIic aromatic hydrocarbons 29.85 - 3 1.85 Polycyclic aromatic hydrocarbons 0.63 Simple alkanes 53.7 10.92 - 73.3 ' ~ d a p t e d from (67).

1.3.4 Bioavailability

The bioavailability of substrate to the degrading microbial community is also a

critical factor in determining the fate of a contaminant. A recent review (68) points out

the difficulties in establishing unifying principles on how bioavailability affects

biodegradation. especially in soils. Studies performed on highly variable systems, such as

soils. can provide results that are mixed and ofien dificult to compare. In fact. they can

even be contradictory. owing to differences in matnx (soi1 type). contaminant,

equilibration time. and, in cases where surfactants are used to solubilize the contaminant.

surfactant type andor sorption and concentration (69).

In a comprehensive review on surfactants and soliibilization. Miller (70) reports that

the uptake and utilization of gaseous and liquid hydrocarbons may occur either in the

dissolved state. or directly by surface (interfacial) contact. The microbial utilization of

solid. hydrophobic substrates require solubilization, or emulsification. prior to uptake and

metabolism (7 1 ). Others (72) have deterrnined that growth on crystalline substrates, e-g..

naphthalene. results in linear growth rates. indicating that partitioning. Le.. solubilization.

of the substrate is rate limiting to biodegradation. According to a review by Britten (73)-

uptake of hydrocarbons most likeiy occurs by a t tachent , then incorporation into the

cytoplasmic membrane. Altemately, transport occurs by passive or facilitated diffusion in

the presence of solubilizing agents; intracellular transport is probably coordinated with

enzymatic oxidation.

Sorne researchers have shown enhanced metabolism of polycyclic aromatics in the

presence of a nonionic surfactant (74, 75). whereas others have demonstrated that

surfactants may actually inhibit metabolism dunng micellization (76). The latter

hypothesize that the micelles undergo a form of reversible, physiological interaction with

the ce11 membranes. thereby temporarily inhibiting biodegradation. The use o f surfactants

for overcoming bioavailability limitations has received much recent attention. even

though their potential to improve biodegradation had been recognized earlier (60).

Because hydrocarbons are hydrophobic compounds, and microorganisms require an

aqueous environment for optimal growth and activity. biodegradation occurs in (at least)

a biphasic system. comprised of immiscibie components. Surface-active agents,

containing both hydrophobic and hydrophilic moieties. provide a means for decreasing

interfacial tensions and enhancing the rniscibility of two or more phases. Commercially

available surfactants, both ionic and nonionic in nature (76-78), as well as biosurfactants

and biosurfactant-producing bacteria. have been investigated for their ability to increase

bioavailability (69. 70. 72). Although results regarding their efficacy are mixed. it

appears that one of the more effective applications is their use in soils where

contarninants are sorbed to the matrix (72).

Other methods for increasing bioavailability rnay also enhance the biodegradation o f

contaminants in a soil. For example. physical dismption of soil aggregates using

sonication has been reported to increase biodegradation rates effectively in a l a n d f m

experirnent (79). Others have demonstrated that soil constituents may signi ficantl y

impact the bioavailability of contaminants (80). In the latter study. two contaminated

soils with similar contamination histories demonstrated very different biodegradation

profiles. Under the same conditions. one presented high PAH-degradation rates. relying

on its native microbial populations. whereas the other demonstrated no PAH

biodegradation. even a fe r inocdation with known PAH degraders. After ruling out

toxicity effects. the lack of activity in the latter was attributed to differences in

bioavailability within the two soil matrices. This soil had a higher soil organic matter

content, which more tightly bound to contaminants. Similar results have been reported by

others (8 1 ), where mineralization rates of a contaminant. e.g.. phenanthrene, are lower in

soils with a high organic matter content, which readily sorbs hydrophobic compounds.

Soluble humic substances. in particular humic and fùlvic acids. appear to be major

binding sites: their binding potential can be attenuated by mineral soil components. as

well as pH and salt concentrations (82). Weathering, or the age o f contamination, may

also affect bioavailability by physicalIy trapping. hindering. andor slowing desorption of

contarninants fiom the soi1 (83).

1.3.5 Geophysiochemical properties of the soil

Soils Vary widely with regard to geology. hydrology. climate. fertility. and other

physicaf attributes. The geophysiochemical properties of a soil are instrumental in

determining the fate of a contaminant. By virtue of complex matrix interactions. soils

ofien mitigate the potentially toxic effects of a contaminant. through binding and sorption

phenomena. while also providing a solid. physical support to help protect and stabilize

microorganisms and their cellular components. In addition. soils O fien define the

physiological constraints in a particular environment. These. in turn. impact microbial

activity. Le.. biodegradation. and can be critical for achieving optimal rates of

hydrocarbon removal.

Most soils are multiphasic systerns. containing an ionic solid matrix and some

associated organic matter, which is surrounded by a water film. as is schematically shown

in Fig. 1-3. In unsaturated soils. generally referred to as the vudose zone, a gas phase

permeates the pore spaces; in saturated soiIs. pores spaces are part o f the aqueous phase.

When hydrocarbons are introduced ont0 the surface of a soil. a number of physical

phenomena impact their removal o r fate in the environment (36, 84). For fresh spills of

light hydrocarbons, volatilization may play an important role in removing the material

from the soil surface. particularly on less permeable surfaces. For heavier hydrocarbons,

auto-. thermal-. and photo-oxidation mechanisms. in addition to biological degradation.

may partially oxidize the contarninants on the soil surface. making them more water

soluble and perhaps more bioavailable. Polar intermediates also exhibit greater

movement than non-polar compounds through the underlying unsaturated soil. or vadose

zone. eventually to the water table. This may not always be the case; Iaboratory studies

conducted by Miller and coworkers (85) have demonstrated that photoproducts of

benzo[a] pyrene photolysis are rapidl y detoxi fied. most likel y through mineral ization or

binding to the soil organic matter. Water-immiscible hydrocarbons can also move down

through the soil. albeit more slowly, thereby introducing an additional oil phase to a

multiphasic matrix. which may change the water holding capacity of a soil.

1.3.6 Oxygen

The initial steps in the catabolism of aliphatic (18). cyclic (19). and aromatic (15)

hydrocarbons by aerobic bacteria and fungi involve the oxidation of the substrate by

oxygenases. for which molecular oxygen is required. Aerobic conditions are therefore

necessary for this route of microbial oxidation of hydrocarbons in the environment. The

availability of oxygen in soils is dependent on rates of microbial oxygen consumption.

the type of soil. whether the soil is saturated, and the presence of utilizable substrates that

can Iead to oxygen depletion (36). The concentration of oxygen has been identified as the

rate-limiting variable in the biodegradation of petroleum in some soils (86).

Air space

hydrocarbons

Fig. 1-3: Schematic representation of a hydrocarbon-contaminated soil particle.

1.3.7 Water activity

The water activity ( u , ~ ) of soils c m range from 0.0 to 0.99, in contrast to aquatic

environments. in which water activity is stable at a value near 0.98 (36). Hydrocarbon

biodegradation in terrestrial ecosystems rnay therefore be limited by the availôble water

for microbial growth and metabolism. Dibble and Bartha (87). in a study of oil sludge

degradation in soil. reported optimal rates of biodegradation at 30 to 90% water

saturation. The failure to observe inhibition of degradation at the lower values was

ascribed to a hydrocarbon-mediated reduction in the water-holding capacity of the soil.

1-3.8 pH

In contrat to most aquatic ecosystems. soil pH can be highly variable, ranging from

2.5 in mine spoils to 1 1 .O in alkaline deserts (36). Most heterotrophic bactena and fungi

favor a pH near neutrality. with fungi being more tolerant of acidic conditions (88).

Extremes in pH. as can be observed in some soils, would therefore be expected to have a

negative influence on the ability of microbial populations to degrade hydrocarbons.

Verstraete el al. (89) reported a near doubling of rates of biodegradation of gasoline in an

acidic (pH 4.5) soil by adjusting the pH to 7.4. Rates dropped significantly. however.

when the pH was further raised to 8.5. Similarly, Dibble and Bartha (87) observed an

optimal pH of 7.8. in the range 5.0 to 7.8. for the mineralization of oily sfudge in soil.

1.4 BiologicaI factors affecting the biodegradation of hydrocarbons

1.4.1 Acclimation period

Prior to the degradation of many organic compounds. a penod is noted in which no

destruction of the chemical is evident. This time interval is designated an acclimation

period or. sometirnes. an adaptation or lag petiod. It may be defined as the length of time

between the addition or entry of the chemical into an environment and evidence of its

detectable loss. During this interval, no change in concentration is noted. but then the

disappearance becomes evident and the rate of degradation ofien becomes rapid.

The duration of the acclimation period may Vary enormously. It rnay be less than one

hour or can take many months (90). The duration varies among chernicals and

environments and it also depends on the concentration of the compound and a number of

environmental conditions. These environmental conditions include the temperature, the

pH. the aeration. and the nutrient concentrations. The acclimation phase is considered to

end at the onset of the period of detectable biodegradation. The concentration of the

compound also greatly affects the length o f time before noticing a decline in its

concentration. Afier the acclimation. the rate of metabolism of the chemical may be slow

or rapid. but if a second addition or accidental spi11 of the chemical is made during this

time of active metabolism. the loss of the second increment characteristically occurs with

little or no acclimation. This greater rate on subsequent additions probabty results from

increases in number of degrading organisms following repeated encounter with the

chemicat.

1.4.2 Adaptation and effect of prior exposure

Prior exposure of a microbial community to hydrocarbons. either from anthropogenic

sources such as accidentat oil spills. petroleurn exploration and transportation activities.

and waste oil disposal. or from natural sources such as seeps and plant-derived

hydrocarbons (7. 36). is important in determining how rapidly subsequent hydrocarbon

inputs can be biodegraded. This phenornenon. which results from increases in the

hydrocarbon-utilizing potential of the community, is known as adaptation (91 ). The three

interrelated mechanisms by which adaptation can occur are (i) induction and/or

repression of specific enzymes, (ii) genetic changes which result in new metabolic

capabilities. and (iii) selective enrichment of organisms able to transform the compound

or compounds of interest (91, 92). Selective ennchment has been widely observed in

studies of hydrocarbon and petroleum degradation in the environment. A large number of

reports. reviewed by Colwell and WaIker (10). Atlas (8). Bossert and Bartha (36),

Cooney (37). and Floodgate (38) have shown that the numbers of hydrocarbon-utilizing

microorganisms and their proportion in the heterotrophic community increase upon

exposure to petroleum or other hydrocarbon pollutants and that the levels o f

hydrocarbon-utilizing microorganisms generally reflect the degree of contamination o f

the ecosystem.

1.4.3 Adaptation by alteration of genetic composition of the microbial community

Of the three above mechanisms for adaptation of microbial communities to chemical

contaminants. only selective enrichment has been examined in detail. as discussed in the

previous section. This has been primarily a result of limitation imposed by available

methods. which have. until recently. restricted the study of adaptation of microbial

communities to the phenornenon of selective enrichment. in which the numbers or

proportion of microorganisms that can utilize the compound of interest increase within

the community and can be enumerated by their ability to grow on a medium containing

the compound as sole carbon source.

The primary gne t ic mechanism for the adaptation of the microbial community is

the amplification. by means of selective enrichment and gene transfer and mutation. o f

genes which are involved in the metabolism of the chemical contaminant (92, 93). Direct

monitoring of this process with respect to adaptation to hydrocarbons has recently been

made possible by the development of DNA probes specific for the genes encoding

hydrocarbon-catabolic pathways (94). Sayler et al. (95), for example, using the colony

hybridization technique, showed a correlation between the enhanced rates of PAH

mineralization in oil-contaminated sediments and an increase in the number of colonies

containing DNA sequences which hybridized to TOL (toluate oxidation) and NAH

(naphthalene oxidation) plasmid probes. The colony hybridization procedure. however.

has the disadvantage of requiring the growth of organisms on laboratory media. which

limits sensitivity and does not allow detection of DNA sequences in viable but

nonculturable microorganisms (96). Dot blot hybridization. in which DNA is extracted

from environmental samples and then probed (97. 98), can be used to detect specific

sequences in the environment without the need for isolation and culture of

microorganisms. The polymerase chain reaction (PCR) technique can improve the

sensitivity of the dot blot method by 3 orders of magnitude. permitting the detection of 1

ceIl per g of sediment sarnples (99).

The use of these methods in conjunction with nucleic acid probes for genes

involved in hydrocarbon metabolism will allow rneasurement of the frequency of these

genes within the microbial community (94). This will also permit assessrnent of the

relative degree of adaptation of the community as well as a more detailed analysis of the

dynarnics of gene amplification associated with adaptation.

1.4.4 Role of plasmids in adaptation

Plasmid DNA may play a particularly important role in genetic adaptation in that it

represents a highly mobile form of DNA which c m be transferred via conjugaison or

transformation and can impart novel phenotypes, including hydrocarbon-oxidizing

ability. to recipient organisms. The pathways for the metabolism of naphthalene,

salicylate, camphor, octane, xylene, and toluene have been shown to be encoded on

plasrnids in Psertdomonas spp. (100). Exposure of natural microbial populations to oil or

other hydrocarbons may impose a selective advantage to strains possessing plasmids

encoding enzymes for hydrocarbon catabolism, resulting in an overall increase in the

plasmid frequency in the community.

1.45 Synergism and Predation

Many biodegradation processes require the cooperation of more than a single species.

These interactions may be necessary for the initial step in the conversion. a later phase of

transformation. or the mineraiization of the compounds. These various interactions

represent several types of synergism. in which two or more species carry out a

transformation that one alone cannot perfonn or in which the process carried out by the

multispecies mixture is more rapid than the sums of the rates of reactions effected by

each of the separate species. Thus, some reactions take place in mixtures of species but

not in pure culture or take place more readily in multispecies associations (90).

A number of mechanisms for synergistic relationships have been described, but

undoubtedly other mechanisms have yet to be discovered. (a) One or more species

provide B vitamins. amino acids. or other growth factors to one or more of the other

organisms. (b) One species grows on the test compound and carries out an incomptete

degradation to yield one or several organic products. and the second species commonly

grows on the intermediate in the sequence. (c) The initial species cometabolizes the target

compound to yield a product that it can no longer metabolize, and the second species

destroys that product. (d) The first species converts the substrate to a toxic metabolite that

then slows the transformation. but the reaction proceeds rapidly if the second member of

the association destroys the inhibitor.

An environrnent with a high density of bacteria or a large fùngal biomass usually will

also contain microorganisms that act as predators or parasites and some that wi11 cause

lysis. These predatory. parasitic. or lytic inhabitants rnay affect the biodegradation carried

out by bacteria and fungi. The impact is o fen deleterious. but it rnay be beneficial.

Among the predators and parasites found in soils and sediments are protozoa,

bacteriophages. viruses affecting fungi. l3dellovibrio. mycobacteria. Acrasiales. and

organisms that excrete enzymes that destroy ce11 walls of fungi or bacteria and thereby

cause their Iysis. Of these several groups. only the protozoa are known to affect

biodegradation. This does not mean that the other groups are not important, only that

evidence for their roIe has not been obtained (90).

Protozoa typically multiply by feeding on bacteria. In environments in which these

microscopie animals are abundant, their grazing rnay markedly reduce the number of

bacteria since 10' to IO" bacteria rnay be consumed to permit the division of a single

protozoan (90). However. not only rnay protozoa affect bacterial activity by grazing but

they rnay facilitate the cycling of limiting inorganic nutrients (especially N and P) and

excrete essential growth factors. In some environments. protozoa are sparse and not

particularly active. so that their role is highly dependent on prevailing conditions.

1 A 6 Inoculation

Microorganisms with a phenomenal array of catabolic activities are widespread.

Soils. sediments, fresh and marine waters, and industrial and municipal waste-treatment

systems possess large and often highly diverse rnicrobial communities that potentially

can exhibit many degradative capacities. and when these capacities are expressed fully

and rapidly. organic chernicals are readily destroyed. Nevertheless. many synthetic

compounds persist for some time in these sarne environments. even though these

molecules are biodegradable. and the question has been asked whether inoculation might

appreciably enhance the decomposition of these compounds. Such inoculation is ais0

referred as bioaugmentation. The method for bioaugmentation is to set up an enrichment

culture by isolating a bacterium or a consortium able to use the target compound as a C

source. The next step is to grow the organism or consortium in culture to get a large ce11

biomass. and then add the organism or consortium to the natural environment containing

the target compound to degrade.

There may be many beneficial advantages to bioaugmentation of a contarninated

environment. Inoculation rnay markedly reduce the acclimation penod of the degrading

microflora. If the time for the community to reach full activity is but a day o r two.

attempts to establish an organism probably would be pointless. However. if the

acclimation period is weeks or months. as it can be for some pollutants. and the risk of

human. animal. or plant exposure increases as the persistence of the toxicant increases,

some fom of intervention to enhance decomposition is called for. Also. inoculation may

be necessary because conditions at the site preclude members of the resident community

from functioning rapidly. Thus. when the unwanted chemical is present at a concentration

high enough to suppress the native biodegrading species, when the temperature is too

high, or the circumstances are otherwise stressful, the addition of a species able to destroy

the chemical and also tolerate the stress may be highly beneficial. It is also clear that

microorganisms acting on certain pollutants may be absent from particular environments.

A compound that is metabolized by many species wili Iikely encounter one or several

species in al1 microbial communities that can transform it. However. certain synthetic

compounds are apparently transfomed by very few species. and it is thus likely that not a

single one of the very few species with the requisite enzymes may be present in a

particular site. This view is in line with the frequent observation that some organic

compounds are mineralized or otherwise metabolized in samples from one but not

another environment and that active microorganisms can only be isolated from some

environrnents.

The approach to inoculation must be calculated and prudent. If there is an indigenous

microflora capable of carrying out the degradative reaction. conditions that favor its

multiplication. and rapid destruction of the pollutant are not essential and additions of

inocula are not needed. If these conditions do not pertain. intervention is called for. The

lack of need for bioaugrnentation is we1I illustrated in waters and soils contaminated with

oil. Such environments contain bacteria able to grow on and destroy a variety of

hydrocarbons. and the penistence of components of oil is not a consequence of the

absence of organisms but rather the absence of full set of conditions necessary for the

indigenous species to function rapidly (8, 9. 54).

There are several reasons that can explain failures when bioaugmentation is used for

experimental studies. Among them. (a) limiting nutrients, (b) suppression by predaton

and parasites, ( c ) inability of bacteria to move appreciably through soil, (d) use of other

carbon sources, (e) competition with the indigenous microflora, and (f) unsuccessful

colonization of the organisms resulting in death before biodegradation occurs. These case

studies apply to field sites and experiments. In contrast. inoculation is very frequently

successful in bioreactors (90). The conditions in these bioreactors are quite different from

those in nature. and frequently few and sometimes no microorganisms having the needed

biodegradative activity are present. Hence. the addition of such organisms is often

beneficial and sometimes essential. Furthemore, bioreactors are engineered systems

whose conditions are readily altered or optimized for particular processes. They can be

designed to promote the multiplication and activity of the inoculated species - in contrast

with field sites.

1.5 Technologies available for hydrocarbon biodegradation

1.5.1 Intrinsic Bioremediation

It is widely accepted that petroleum contamination will nati y attenuate. that is,

be degraded over time in even the coldest climate. Natural attenuation (or intrinsic

bioremediation) is becoming the accepted remedial option for low-risk petroieum-

contaminated sites as a cost-effective remedial alternative. Natural attenuation is not

strictly a biodegradation process by indigenous microorganisms that transfonn

contaminants to intermediate products or innocuous end products. or imrnobilize them.

Physical and chernical phenomena such as dispersion, sorption and abiotic

transformations are often important. However, biodegradation is most ofien the primary

mechanism for contaminant destruction. To date, the most common application has been

to petroleurn contaminants (101). When oil is accidentally discharged into the

environment, carefùl case studies and risk assessrnent are required to document

ecological darnage and to evaluate the rates and mechanisms of environmental self-

purification (1 02). Intrinsic bioremediation may require that the source of contamination

is first removed to prevent additional entry and spread into the surroundings. A long-tem

monitoring program is often required to confirm that biodegradation is. in fact. taking

place and that further movement of the pollutants is not occurring.

1.5.2 Landfarming

Landfarming is an above-ground process where contaminated soils are provided

with required nutrients and spread out in thin layers that can be tilled by vanous

mechanical means. Tilling provides oxygen and ensures the thorough dispersal of added

moisture and nutrients. Landfarms were originally operated with contaminated soils and

wastes added directly ont0 the ground. with no provisions for leachate control or vapor

emissions. Present day operations require containment of soils with leachate collection

systems and above ground enclosures for vapor control. Petroleum wastes were

historically treated by landfarming techniques (103). At one time it was estimated that

nearly half of petroleum oily wastes were treated at landfarm operations (1 04).

Landfarming c m be used to treat oily or hydrocarbon-rich materials that are

inadvertently spilled on soil. The considerable amount of carbon added in these wastes

has the potential to support a large biomass, but the soil has too Iittle N and P-and

possibly other inorganic nutrïents-to support such large biomasses, so N and P are added

to the soil. ofien in the form of commercial fertilizers.

1.5.3 Composting biotreatment

Composting is the biological decomposition and stabilization of organic

substrates (Le. petroleum hydrocarbons), under conditions that allow development of

high temperatures as a result o f biologically produced heat. to produce a final product

that is stable, free o f plant seeds. and can be beneficially applied to land. The process

relies on thermophilic microorganisms to biodegrade the hydrocarbon contarninants. This

technology is best used for highly contarninated soils (such as refinery sludges) and in

areas where temperature is critical to the sustained treatment process. The contaminants

are mixed with a solid organic substance that is itself readily degraded. such as fresh

straw. wood chips, wood bark. o r straw that had been used for livestock bedding. These

bulking agents improve soi1 texture for aeration and drainage. The system is optimized

for pH, moisture, and nutrients via imgation techniques; it is then placed in a simple heap

o r formed into long rows known as windrows. It can further be enclosed to contain

volatile emissions. For a successful application. it is important that the bulking agents do

not compete with the biodegradation o f the contaminants. The higher temperatures (45-

60°C) also are beneficial for high rates o f microbial activity and reduction of pathogens in

the treated wastes.

1.5.4 Engineered biopiles

Biopiles, also known as biocells. bioheaps, and biomounds, are used to reduce

concentrations of petroleum constituents in excavated soils through the use o f microbial

degradation. This technology involves heaping contarninated soils into piles (or "cells")

and stimuIating aerobic microbial activity within the soils through the aeration ancilor

addition of minerals. nutrients, and moisture. The enhanced microbial activity results in

degradation of adsorbed petroleum-product constituents through microbial respiration.

Biopiles are similar to landfarms in that they are both above-ground. engineered systems

that use oxygen. generally frorn air. to stimulate the growth and reproduction of aerobic

bacteria which. in turn. degrade the petroleum constituents adsorbed to soil. While

landfarms are aerated by tilling or plowing. biopiles are aerated most often by forcing air

to move by injection or extraction through slotted or perforated piping placed throughout

the pile.

The typical height of biopiles varies between 1 and 3 meters. Additional land area

around the biopile(s) will be required for sIoping the sides of the pile, for containment

berms. and for access. The length and width of biopiles is generally not restricted unless

aeration is to occur by manually turning the soils. In general, biopiles that will be turned

should not exceed 2 to 3 meters in width. Biopiles are typically constructed in "lifis".

Blended soil is mounded up to a depth of no more than a few feet and then aeration and

moisturizing piping is laid prior to the addition of the next lifi (Fig. 1-4). This process is

repeated until the pile is at the desired height. Blending the soil may involve the addition

of (a) rnicrobial inoculum or manure. to both augment the microbial population and/or

provide additional nutrients. and (b) soil amendments (e.g.. gypsum) and bulking

materials (cg.. sawdust. or straw), to ensure that the biopile medium has a loose or

divided texture.

Perforated PVC pipes Hydrocarbon-

Polyethy Iene contaminated

soif

Fig. 1-4: Side view of a biopile with passive aeration. Similar to the ones built for the field experiment at CFS Alert.

Volatile constituents tend to evaporate from the biopile into the air because of the

aeration system chosen rather than being biodegraded by bacteria. In these cases. vapors

must be captured or contained for further treatment and biodegradation. This can be

accomplished by covering the biopile and installation of collection piping beneath the

cover. If air is added to the pile by applying a vacuum to the aeration piping. volatile

constituent vapors will pass into the extracted air Stream that can be treated. if necessary.

In some cases (where allowed). it may be acceptable to reinject the extracted vapors back

into the soil pile for additional degradation. In some cases the vapors may need to be

treated (typically through carbon adsorption). Another detail to take into consideration is

the leaching of contaminants into the environment. To prevent possible leaching of

contaminants from the biopile into the underlying groundwater. biopiles may be required

to be constructed on top o f an impermeable liner. Leachate that drains from the biopile is

then collected for treatment and disposal.

Biopiles are designed to optimize the conditions for aerobic bacteria to biodegrade

organic contaminants. The effectiveness of a biopile system depends on many parameters

that can be grouped into three categories: (1) soil characteristics, (2) presence of

hydrocarbon-degrading rnicroorganisms, and (3) proper climatic conditions. Soi1 texture

affects the permeability. moisture content. and bulk density o f the soil. Fine-grained soils

are less permeable than coarse-grained soils. Soils with lower permeability are more

difficult to aerate. but tend to retain moisture better than soil with higher permeability.

However. lower permeability is usually associated with soils that clump together making

it difficult to evenly distribute moisture. air. and nutrients. At certain times during the

operational life of the biopile the soil may need to be turned (or tilled) to promote

continued aeration and biodegradation.

1 S.5 Bioventing and biosparging

Bioventing is an approach to solid-phase treatment of contaminants that relies on

methods of introducing air into soil above the water tabIe (the vadose zone or the

unsaturated portion of soil). which thereby provides Oz needed as the terminal electron

acceptor to aerobic microorganisms. The air is introduced either by a vacuum extraction

method or by forcing air into the soil under positive pressure. Appropriate withdrawal or

air-injection wells are the ways by which the vacuum or positive pressure is applird to

the soil. The procedure is attractive because it operates in situ and because of the Iittle

equipment required. Bioventing is not recornmended for compounds with high vapor

pressures that may volatilized too quickly before being biodegraded. It is also not suitable

for soils of low permeability because the air may not move through the soil suflïciently

rapidly to provide enough Oz to sustain active metabolism by aerobes. Care must also

being exercised when air injection is used to prevent the introduced air from spreading

volatile compounds into portions o f soil not already contaminated.

Biosparging takes a similar approach to bioventing but the air is introduced into

the saturated zone. Le. below the water table. The purpose is not only to provide Oz but

also to transfer volatile compounds into the overlaying unsaturated (vadose) zone, which

usually contains a population of microorganisms capable o f degrading the target

compounds. In addition, some biodegradation will occur in the aquifer in response to the

O2 added. As with bioventing, the air flow rate should not be too high that volatile

compounds pass through the vadose zone without being degraded.

1 S.6 Phytoremediation

Phytoremediation is a fairly new technology that involves the use of plants that,

directly or indirectly. result in the removal or degradation of organic pollutants. It

involves processes that may involve uptake of the contaminant by the plant or

biodegradation by the microflora cotonizing the root or the soil immediately next to the

root system also called the rhizosphere (105). Rhizosphere is defined as that part of the

soil adhering to a plant root system afier shaking to remove loose soil. Rhizosphere size

is determined by the size and cornplexity of a plant root system and may represent a

significant contact area (106). Microbial density is high in rhizosphere soil. typically

ranging from 5 to 20 times greater than soil without roots. Higher microbial metabolic

activities result from plant root exudates, including organic acids. sugars, and other

organic materials. Plants benefit frorn increased solubilization of minerals. synthesis of

vitarnins, and other growth-stimulating materiak mediated by microorganisms (1 07). The

chief factor that distinguishes the rhizosphere is the continuous low-molecular weight

organic compounds excreted by the roots. These compounds serve as a source of readily

available carbon and energy that sustains a large community of microorganisms.

In contrast. some carbon sources in nonrhizosphere soil are high-rnolecular

weight. poorly available substances that are only slowly utilized and support a

community of bacteria and hngi that are not as metabolically active (107). In one

investigation. for example. a defined mixture of alkanes and PAHs was added to pots

containing 400 g of soil. which were then planted with ryegrass (Lolitrrn perenne). The

rate and extent of loss of total hydrocarbons were enhanced by ryegrass (Table 1-4).

although no marked beneficial effect on PAH degradation was evident (108).

Table 1-4: Effect of Ryegrass on hydrocarbon degradation in soil"

Weeks Total hydr~carbons (mgkg) Unplanted Planted

O 4330 4330 5 3690 2140 12 2150 605 17 1270 223 22 792 I l 2

" Adapted from ( 108).

1.6 Phylogenetic identification and species-specific detection of hydrocarbon degraders

The study of microbial diversity and community dynamics is increasing in

microbial ecology. Recent advancements in molecular biology provided tools to analyze

communities that were almost impossible to characterize in the ps t . It is now possible to

define the causes of time-dependent changes in the health of a stressed ecosystem on the

basis of the structural composition of the ecosystem population (109).

The analyses of microbial communities that are invo lved in hydrocarbon

degradation are still a challenge to microbiologists and microbial ecologists. It is

estimated that =90-99% of the species making up heterotrophic communities d o not form

colonies when current laboratory techniques are applied ( 1 10. I l 1 ). Soi1 communities

remain some of the most difficult communities to characterize due to their extreme

phenotypic and genotypic diversity. and spatial variability. Estimates of the genotypic

diversity in these communities based on DNA renaturation experiments suggests that

there are 4 x 1 o3 to 7 x 1 O' different genome equivalents per g of soil ( 1 12). which. if

extrapolated to species diversity. suggests that there are perhaps 103 or even more species

pet- g of soil.

Molecular phylogeny is the phylogeny o f a portion o f a gene. An example o f

genes consewed through the billions of years o f evolutionary divergence are those that

define the ribosomal RNAs (rRNAs). Most prokaryotes have three rRNAs. called the 5s.

16s and 23s rRNA that are present in several copies within each ce11 (Table1 -5).

Table 1-5: Ribosomal RNAs in Prokaryotes

Namea S ize (nucleotides) Location 5s 120 Large subunit of ribosomes

16s 1500 Small subunit of ribosomes

2 3 s 2900 Large subunit of ribosomes " The name is based on the rate that the molecule sediments (sinks) in water. Bigger molecuies sediment faster than small ones.

The 5s has been extensively studied, but its size is usually too small for reliable

phylogenetic inference and specificity. The 16s and 23s rRNAs are sufficiently large to

be quite usehl and reliable for phylogenetic identification. The extraordinary

conservation of rRNA genes can be seen in Table 1-6, where fragments of the smaIl

subunit ( 16s) rRNA gene sequences from organisms spanning the known diversity o f life

are shown.

Table 1-6: 16s rRNA sequences comparison between different organismsa

16s rRNA seauences

Yeast

Corn

Escherichiu coli

Therrrlococ.cizis celer --GTGGCAGCCGCCGCCGTAATACCGGCGGCCCGACTGGGrGGCCGC

.Jir/f0/obz~s ~ z ~ ~ o l u r i c z ~ s --GTGTCAGCCGCCGCCGTAATACCAGCTCCGCGAGTGG~~CGGGGT

" Adapted from ( 1 1 3).

Woese el al. (1 14) recognized the full potential of rRNA sequences as a measure

of phylogenetic relatedness. They initially used an RNA sequencing method that

deterrnined about 1/4 of the nucieotides in the 16s rRNA (the best technology available

at the time). This amount of data greatly exceeded anything else then available. Using

newer methods. it is now routine to determine the sequence of the entire 165 rRNA

molecule. Today, the accumulated 16s rRNA sequences (about 10,000) constitute the

largest body of data available for infemng relationships among organisms. These

sequences also allowed researchers to build phylogenetic trees showing the evolutionary

distance arnong the three (identified) Domains of life: Bacteria. Archaea and Eucarya

(Fig. 1-5).

The ability to identify and quantify specific microbial species within

environmental settings would be valuable to numerous fields of research. Changes in

microbial community structure induced by natural or anthropogenic factors could be

monitored. Trends in microbial community composition during bioremediation of

hydrocarbons. whether of indigenous or introduced species. could be determined. The

need for species-specific detection of indigenous bacteria involved in bioremediation

processes is needed to rnonitor introduced organisrns. However, the techniques avaiiable

for identifying and quantifying specific microbial species have been of limited usefulness

for in sirif real world settings due to the necessity of prior culturing of bacteria. inability

to quantify microorganisms. or lack of sensitivity (1 16). More accurate and sensitive

methods that could offer both species-specific detection and quantification directly in the

real world sarnple are needed. since prior culturing of samples may significantly alter the

microbial comrnunity structure ( 1 17).

7 --YI--

KU-

Fig. 1-5: Phylogenetic relationships among life forms based upon rRNA sequences. The Iengths of the lines are proportional to the evolutionary differences. The position of the root in the tree is approximate. Adapted from (1 15).

A number of molecular approaches have recently reported for bacterial species-

specific identification. Phospholipid fany acid profiles have been found to be specific for

microbial genera, but vaiy with growth conditions and serve as indicators of changes in

comrnunity structure rathrr than identification or quantification of individual species

( 1 18-120). Sequencing of genes. such as the rRNA genes, has proven to be valuable in

species identification ( 1 21 ). Reverse sarnple genome probing has been reported to enable

the identification of different species involved in the degradation of hydrocarbons ( 122).

Fluorescent and radiolabelled oligonucleotide probes specific for gene sequences in the

species of interest have also been usehl (123). Several polymerase chain reaction (PCR)

based procedures have been reported for the identification of bacterial species. A number

of PCR prïmers have been developed for particular bacterial genes including the 16s

rRNA gene (124, 125). The majority of reported 16s rRNA sequence PCR primers

(Table 1-7) are designed to arnplify a wide range o f bacterial sequences. which can be

subsequently sequenced o r subjected to denaturing gradient gel electrophoresis (DGGE)

for species identification (125. 126). In other cases PCR primers have been designed to

be species-specific. such as those reported for in situ PCR and single-ce11 microscopic

identification of Escherichia coli and other species ( 1 27).

Some other methods rely specifically on fingerprinting communities like random

arnplified polymorphic DNA (RAPD-PCR). arbitrarily primed-PCR (AP-PCR). repetitive

extragenic palindromic-PCR (REP-PCR). and enterobacterial intragenic consensus

sequence-PCR (ERIC-PCR) provide complex banding pattern fingerprints of individual

species ( 128- 130). These species-specific fingerprints are generally not arnenable to in

situ environmental analysis without prier culturing of samples. Al1 of these approaches

either require prior culturing of the bacterial species o r provide minimal quantification

capabilities.

In the present study. phylotype-specific PCR primer sets based on the 16s rRNA

gene sequences of the most abundant organisms in the Alert-1 enrichment culture were

designed and used in a PCR-MPN assay (cf. Materials and Methods, Section 13). The

16s rDNA gene is present throughout the prokaryotes. containing both highly conserved

sequence regions and highly variable sequence regions ( 1 3 1 ).

Table 1-7: Group-specific 16s rDNA sequencing primers.

Name Sequencea Comments 27f 5' AGAGTTTGATCMTGGCTAG> PCR and sequencing, most eubacteria 109rI 5' ACGYGTTACKCACCCGT> Broad speciticity 109r2 5' AKRCATTACTCACCCGT> Most gamma and some beta proteobacteria 3 4 3 5' CTGCTGCSYCCCGTAG> Most eubacteria 357r 5' CTCCTACGGGAGGCAGCAG> Most eubacteria 5 19r 5' GWATTACCGCGGCKGCTG> Most eubacteria. eukaryotes. archaebacteria 53Of 5' GTGCCAGCMGCCGCGG> Most eubacteria. eukaryotes. archaebacteria 685r l 5' TCTACGRATTTCACCYCTAC> Alpha and delta proteo bacteria, fusobacteria 685r2 5' TCTACGCATTTCACYGCTAC> Ail beta and gamma proteobacteria 6851-3 5' TCTRCGCATTYCACCGCTAC> Most Gram +. cyanobacteria. 907r 5' CCGTCAATTCMTTTRAGTTT, Most eubacteria. eukaryotes. archaebacteria 926f 5' AAACTYAAAKG AATTGACGG> Most eubacteria. eukaryotes, archaebacteria 1 100r 5' GGGTTGCGCTCGTTG> Most eubacteria 1 1 I4r 5' GCAACGAGCGCAACCC> Most eubacteria l 392r 5' ACGGGCGGTGTGTRC> Most eubacteria. eukaryotes. archaebacteria I 406r 5' TGYACACACCTCCCGT> Most eubacteria, eukaryotes. archaebacteria I492r 5' TACGGYTACCTTGTTACGACTT> PCR and sequencing, most eubacteria. archaebacteria 1525r 5' AAGGAGGTG WTCCARCC> PCR and sequencing. most eubacteria, archaebacteria " M =C:A. Y =C:T. K=G:T. R=A:G.S =G:C. W=A:T:all I:l. Adapted fiom ( 132).

1.7 Canadian Environmental Protection Act (CEPA) regulations

The Cuncidiun Environmental Protection Act (CEPA) was promulgated on June 30,

1988. Its purpose is to give the federal govemment authority to address pollution

problems on land. in water. and through al1 layers of the atmosphere. The Act takes a

preventative approach to these pollution problems by requiring that substances be

identified and assessed to determine whether they are "toxic." As defined in CEPA.

"toxic" refers to risk to the environment and human health. CEPA gives the federal

government authot-ity to address pollution problems caused by a wide variety of

substances, both inanimate and animate matter. As a result, the Act addresses substances

ranging frorn chernicals to organisms.

The New Substances Notification Regulations were first published in the Canudu

Gazette in three parts. The first two parts prescribed the process for notification of new

substances that are chernicals and polymers. and the third one prescribed general

administrative and testing requirements. These Regulations came into force on July 1.

1994. The second part of the Regulations was arnended to include Part 11.1. which

prescribes the process for notification of new substances that are organisms. including

microorganisms. This Part of the Regulations came into force September 1. 1997. Thus.

Environment Canada must approve every field experiment involving the use of either

indigenous or non-indigenous microorganisms. To do so, Part II. 1 must be filed at least 3

months prior to starting the experiment and Environment Canada must approve the

experimental design.

The New Substances Notification Regulations that was completed for this project

included 2 parts: Part A and Part B. The first part requires identification and

administrative information about the manufacturer and the second one refers to the

characterization of the organisms or consortium used in the experiment. In this project. a

consortium was used in an experimental field study where the microorganisms used are

indigenous to the ecozone where they were added.

The information requested included the strain history and a description of any

modifications that were made to the rnicroorganisms. A description of the biological and

ecological characteristics of the microorganisms is also needed including: (a) the

infectivity. pathogenicity to non-human species, toxicity and toxigenicity, (b) the

conditions required for, and conditions that Iimit, survival, growth and replication, (c) the

life cycle. (d) the resistance to antibiotics and tolerance to metals and pesticides, (e) the

involvement in biogeochemical cycling. and (f) the mechanisms of dispersal of the

microorganisms. The objectives of the field study also need to be detailed including the

procedures for transporting the microorganisms to the site and a description of any

procedures for monitoring the microorganisms and its ecotogical effects at the site of the

experimental study. Finally. the microorganisms must go through an antibiotic

susceptibility testing in order to detect any resistance to known antibiotics. This form was

completed prior to the field experiment conducted at CFS Alert dunng the summer of

1999.

2. THESIS OBJECTIVES

2.1 Nature of the problem

A microbial consortium is proposed for use as an inoculum for bioremediating

hydrocarbon-contaminated soi1 at CFS Alert using engineered biopiles. The most

effective hydrocarbon-degrading consortium is expected to be complex. undefined

microbial communities composed of indigenous organisms and selected for their

biodegradation capabi l i ties. There are two major di fficulties in working with such

cultures: (a) the identification of the component organisms. and (b) monitoring the

consortium to determine whether it survives and is active in the soil. The vast majority of

soi1 rnicroorganisms (90-99%) cannot be isolated and maintained in pure culture; thus.

classical methods are thought to be ineffective to identify and enumerate such organisms.

Furthemore. consortia degrading complex substrates. particularly hydrocarbon mixtures

in fuels. will likely be composed of rnany species. making isolation- and cultivation-

based methods di fficult.

The regulations under the Canadian Environmental Protection Act (CEPA) of the

use of microorganisms for such bioremediation applications include requirements for

extensive information about the cultures. These requirernents refer to the identification

and monitoring methods of the inoculated strains. Methods that would assist in answering

these requirements would be of great benefit in assessing bioremediation in field

experiments especially on a large scale. Essentially, these would allow one to determine

if the inoculum is present and active in the experimental treatments.

2.2 Rationale

Molecular methods based on DNA analysis developed in the past 10 years c m

overcome several of the difficulties described above. Essentially. one c m analyze a

complex microbial community by analyzing that community's DNA. This c m allow

phylogenetic identification of organisms and determination o f the abundance of

individual organisms in the community. Phylogenetic identification is of limited value. as

it does not provide information about the metabolic capabilities of an organism.

However, phylogenetic identification does address information requirements under

CEPA regulations. and it does provide a b a i s for monitoring the organisms in soii or

other environments. The DNA sequence information used to identify an organism can

also be used to design specific probe (oligonucleotides) for that organism.

The 16s ribosomal DNA (rDNA) is the gene encoding the 1 6 s ribosomal RNA

(rRNA) that is present in al1 bacteria. It was possible to isolate this gene using the

polymerase chain reaction (PCR). Random cloning o f 16s rDNAs from a hydrocarbon-

degrading consortium was done. This consortium was enriched from CFS Alert

hydrocarbon-contaminated soi1 at 7OC with Jet-A1 Fuel as the sole organic substrate. An

initial screening indicated how many of the cloned genes were identical and the

frequency distribution of each unique sequence. This showed the phylogenetic rkhness

and diversity of the consortium. In this study. twenty-nine 16s rDNAs were partially

sequenced, and cornparison of those sequences to ones in the Ribosomal Database Project

(RDP) allowed phylogenetic identification of the most abundant phylotypes in the

consortium.

PCR primers were then designed for the three most abundant phylotypes in the

hydrocarbon-degrading consortium based upon hypervariable regions of each 16s rDNA

sequence. DNA extracted frorn soi1 and cultures were tested with the primers to quantifi

the selected organisms. This method, a PCR-MPN assay. was used in the laboratory to

monitor stability of populations in the consortium through serial cultures. The stability of

such consortium is a fundamental question of relevance to bioremediation and regulations

of bioremediation which has by no means been answered. The PCR-MPN assay was also

used to measure populations of phylotypes in the field experiment at CFS Alert and

monitor the fate of inoculated consortium, survival. growth. and possible spread to

nearby locations. Engineered biopiles were used for on-site bioremediation of

hydrocarbon-contarninated soi1 at CFS Alert. This cost-effective technology showed good

results in past field experiments (4. 133) and does not require high maintenance.

2.3 Objectives

The objectives of this project are: (a) characterize a hydrocarbon-degrading

consortium using molecular tools. (b) detennine the effect of bioaugmentation on TPH

biodegradation during a field experiment at CFS Alert. ( c ) rnonitor the fate. growth. and

spread of the inoculated consortium. (d) measure population dynarnics of the three most

abundant phylotypes in the Alert-1 consortium, and ( e ) confirrn the results of the field

experiment by a laboratory experiment looking at different densities of inocuIum.

3. MATERIALS AND METHODS

3.1 Site description and soil source

Canadian Forces Station Alert is located on the northeastem tip of Ellesmere

Island, Nunavut. at 82"30'06" N, 62"19'47" W (Fig. 3-1). CFS Alert is the most northerly,

permanently inhabited location in the world. Alert is part of the Defense Information

Systems Organization (DISO) and the Canadian Forces Supplementary Radio System

(CFSRS). The closest Canadian Inuit community to Alert is Grise Fiord (population 148)

located almost 800 km away on the southeastern tip of EIlesmere Island. Alert is also

Iocated roughly 800 km from the North Pole and 40 km south of northernmost point in

Canada. The Ellesmere Island National Park Reserve (EINPR) is located 40 km to the

south and West of Alert. The Alert area was not included in the EINPR at the request of

DND as it was considered "necessary for military operations relating to the operation of

CFS Alert".

The soil used for this project was collected from two locations at CFS Alert. Soi1

collected at the upper POL (ESG #12228) site was used for the preparation and growth

of an enrichment culture (below). The second soil source came from the new airstrip spi11

area (4) and was used for the field experiments and also for the microcosm experiments.

Both soils had an initial average contamination level of 3,000 ppm (mgkg) of TPH (4).

Fig. 3-1 : CFS Alert (marked by an arrow), Ellesmere Island. Nunavut.

3.2 Site climate

Because Alert is located in an Arctic desert, the Station experiences low

precipitation. high sublimation and high runoff (because of permafrost and lack of soil)

that leads to little rnoisture in the land. The Station experiences low temperatures year

round and receives 24 hours of daylight for 6 months from the beginning of April to the

beginning of September and 24 hours of darkness between mid October and the

beginning of March. The prevailing winds of the ocean influence the local temperatures

at Alert. The mean daily temperature for January, February and March is -30°C with a

record low of -50°C. In July. the mean daily maximum temperature is 64°C with the

record high being 20°C. Alert has only 20 to 30 frost-free days per year. The greatest

frequency of blizzards occurs in February. Most of the annual precipitation is received

during the months of July. August and September with the least arnounts received during

November to A p d period. The mean annual precipitation received by Alert is 155 mm.

Ice is present on nearby Upper Dumbell Lake from August to June and reaches a

maximum thickness of 200 cm during the winter. The sea starts to freeze in late August

with freeze-over completed by early September and does not start the three-month break

up period until June.

3.3 Alert-1 enrichment culture

The enrichment culture was prepared from 0.1 g of soi1 collected from the upper

POL site at CFS Alert (ESG Sarnple #12228). (4) and suspended in 10 mL of cold PAS

minera1 medium (134). 200 ppm of filter sterilized (0.2-pm filter) Jet-Al fuel was also

added and was used as the sole organic substrate. The enrichrnent culture was incubated

on a shaker at 7OC for 2 weeks. 200 ppm more fuel was added and incubation continued

for 3 more weeks. The enrichrnent culture was in duplicate, and two tubes were set up as

uninoculated controIs. These controls showed no signs of growth during the entire length

of the experiment. 100 pL of the above cultures was added to dupiicate tubes with 10 mL

of new PAS medium containing 400 pprn of filter-sterilized Jet-A1 fuel and incubated for

2 weeks. This procedure was repeated two other times and 18 mL of the last duplicate

cultures were pooled and centrifuged (1 5 min at 16,000 x g). The pellet was suspended in

20 mL cotd PAS. This was centrifuged again and the peIIet was suspended in 4 mL cold

PAS with 10% (vol/wt) dry honey and 20% (vol/wt) skim milk powder as

cryoprotectants. to optimize the cells viability. Eight 0.5-mL aliquots of the Alert-1

enrichment culture were flash frozen in a dry ice and ethanol bath and vacuum dried.

These aliquots were then stored in a 4°C refrigerator.

Two 0.5-mL lyophilized aliquots were rehydrated in separate tubes with 1-mL

cold PAS for 15 min. They were then added to two tubes with 9-mL PAS before Jet Fuel

was added (200 ppm). the tube were incubated at 7°C. An uninoculateci tube was also

prepared as a negative growth control. Growth in the form of heavy flakes was apparent

afier 5 days in the two inoculated tubes and there was no growth in the uninocuiated one.

Jet Fuel was added (300 ppm) and the tubes were incubated for another week at 7OC. One

mL of each culture was then added to 100-mL PAS flasks and 500 ppm of Jet Fuel was

added. Two other additions of Jet Fuel (500 ppm) were made afier 6 and 8 days,

respectively. The two cultures were then brought to the Biotechnology Lab Fermentation

Pilot Plant at UBC and loyphilized the sarne way than descnbed above. A total of 18 g of

lyophilized wet cells was prepared and will serve for the field and microcosm

experirnents as the Alert- 1 inoculum.

The Alert-1 inoculum was brought to CFS Alert, and 6.0 g wet cells were used to

inoculate the three inoculated biopiles by adding the lyophilized ceIls to thirty litres of

water that came from the Upper Dumbell Lake which is the source for drinkable water

for the station. Tap water was not be used because it is osmotically hypotonic to al1

bacterial cells (except dormant spores). The inoculum was allowed to stand for 45 min,

and then 10 litres were added to each inoculated pile. The control biopiles did not receive

any blank water. Each pile had an estimated soil volume of 0.5 rn3 and the original plan

was to inoculate each pile with lo6 cells per g of dry soil. Cells were enumerated (direct

count) by using a Petroff-Hausser counter (Hausser scientific). (135). This method was

done using 1 g of lyophilized cells (from the Alert-1 inoculum) after resuspension in 9.0

mL of saline buffer solution containing 0.1 % sodium pyrophosphate ( 1 g/L) and 2% NaCl

(8g/L) (pH 7.5). This method estimated the number of cells at 1.0 x IO'" cells per g of

lyophilized wet cells. This was used to calculate the densities of 1 o6 and 1 o9 cells per

gram of dry soil.

The 6.0 g wet cells that were brought to CFS Alert for the field experiment

represents approximately 6.0 x 10'" cells for 1.5 m3 (3 inoculated biopiles at 0.5 m3 each)

of hydrocarbon contarninated soil. 1.5 m3 of soil had a weight of 2 700 kg wet and

calculations on water content on CFS Alert soil showed a water percentage of 15.5%. so

1.5 rn3 weighed around 2 280 kg. This means that the density of the inoculum added in

the field experiment was approximately 1 x 10' cells per g of dry soil. The biopiles where

then inoculated with a greater density of inoculum than originally planned. For the

microcosm experiments 1.9 x 105 g of the Alert-1 lyophilized cells were used.

representing approximately 5.0 x 10" cells. The cells were suspended in 4 mL of saline

buffer solution containing 0.1% sodium pyrophosphate (1 g/L) and 2% NaCl (8gIL) (pH

7.5). 1 mL of this solution was used to inoculate each experiment requiring a ce11 density

of approximately 1 x 1 O' cells per g of dry soil. The last mL was diluted by adding 3 pl of

resuspended cells in 3 mL of the same saline buffer solution. Then one mL was used to

inoculate each experirnent requiring a ce11 density of approximately 1 x 1 o6 tells per g of

dry soil. Each microcosm experiment had a final volume of 80 g of hydrocarbon-

contarninated soil.

3.4 Field experiment at CFS AIert

Small-scale biopiles were built at CFS Alert to evaluate the effect of

bioaugmentation on TPH biodegradation. The experiment consisted of 6 small-scale

biopiles: 3 being inocutated with the Alert-1 consortium and 3 control uninoculated

biopiles. The pile size was approximately 1 rn x 1 m x 0.5 rn (1 x w x h) with a volume of

soil of approximately 0.5 m3. The biopiles were constructed in a single line. from East to

West. to minimize differences in the effects of the Sun and the wind on the petrolewn

degradation in each pile.

Soi1 chosen for this field experirnent was contarninated with petroleum

hydrocarbons in 1997 and came from the new spi11 area at CFS AIert (4). Average TPH

concentrations were determined by gas chromatograph (GC) analysis at the Analytical

Services Group (ASG) at the Royal Military College of Canada and showed a

concentration of total petroleum hydrocarbons of 3,000 pprn (4). The site chosen for this

experiment is located near the C-Span building at CFS Alert and was initially leveled by

a front-end loader. A volume of approximately 0.5 m3 of hydrocarbon-contarninated soil

was placed on a tarp by measuring approximately 2m x 2m x 0.125m. Nutrients and soil

amendments were then added to the biopiles. The commercial fertilizers used were urea

(46% N - granular) and diammonium phosphate (1 8% N, 46% PzOs) and were obtained

from Agrico Fertilizer Co. Canada. Urea and diarnmonium phosphate were used at

concentrations of 1.04 kg and O. 14 kg, respectively. per cubic meter of hydrocarbon-

contaminated soil. Al1 biopiles were also amended with a commercial surfactant called

BiosolveTM. supplied by The Westford Chemical Corporation, Westford, MA. BiosolveTM

is a rnitigating and encapsulating agent for fuel spills. It is advertized to be effective in

remediating soil contarninated with hydrocarbons and it has the property to increase the

bioavaiIability of hydrocarbons to the indigenous hydrocarbon-degrading microflora in

soil. BiosolveTM was used at a concentration of 3% of the original solution supplied by

the manufacturer and applied at a volume of 1.25 L per cubic meter in each biopile or

microcosm. Gro BrixTM (Gr0 Brix Dist. Co., Mississauga. ON) is a cocoa fiber bulking

agent and was used in al1 biopiles to increase airflow and porosity of the high clay

content encountered in Alert soil. Gro Brix was used at a ratio of 10% (vol/weight) in al1

biopiles and microcosms.

The Alert-1 consortium was added last in the three inoculated biopiles at a ce11

density of approxirnately log cells/g of dry soil. Care was taken not to accidentally

inocdate control treatments during the pile construction. To ensure maximum

hornogeneity of the amendments in soil. a mobile concrete mixer was used and allowed

soil mixing for a period of 20 min per pile. The amended soil was then used to build the

biopiles by placing half of the soil on a polyethylene sheet that was used to prevent TPH

leachate. Passive aeration in the biopiles was implemented by using two PVC pipes per

pile that were perforated with two rows of holes that were about 6 inches apart. These

pipes were placed at the center of each pile. The second half of the contaminated soil was

then placed on top of the pipes and the pile was finally covered with another thin sheet of

polyethylene to prevent drying of the pile.

3.5 Laboratory experiment

The biodegradation of the soil from CFS Alert was monitored in soil microcosm

experiments to determine the effectiveness of bioaugmentation on TPH biodegradation

using CFS Alert hydrocarbon-contaminated soil. The soil used for this experiment was

brought back from CFS Alert during the summer of 1999 and stored at -20°C. This soi1 is

the sarne hydrocarbon-contaminated soil that was used in the field experiment and had

approximately the sarne initial TPH concentration (3.000 ppm). The soil was thawed and

seived in a 2-mm seive. Three sets of experiments were made in triplicate having: ( i ) an

uninoculated control treatment. (ii) a treatment being inoculated with 106 cells per g of

dry soil. and (iii) another inoculated treatment with lo9 cells per g of dry soil. Another

soil microcosm was set as a sterile control after adding sodium azide (3 g/L) in order to

kill any microorganisms present in soil. Each soil microcosms contained 80 g of

hydrocarbon-contaminated soil of and were amended with the same concentration of

GroBrixïM. diarnmonium phosphate, urea. and BiosolveTM (per volume of hydrocarbon-

contaminated soil) than in the field experirnent. The soil was placed in 125-mL bottles

with screw caps and mixed well for five min before being incubated at 4°C. Sarnpling

was done every week taking 3 g of soil for TPH measurements and 1 g for DNA

extraction. The sarnples were frozen at -20°C awaiting nucleic acids extraction. The

experiment length was set to 92 days to measure TPH removal and also quantify

inoculated hydrocarbon-degrading strains.

3.6 DNA extraction from liquid culture

Sufficient quantities of DNA suitable for use in PCR amplification experiments

were readily obtained from the Alert-I enrichment culture using a bead beating lysis

method folIowed by isopropano1 precipitation (shown below). (1 36).

Sludge biomass in a 2mL screw-capped microtube and spin at 16.000 x g for 5 min at J°C; decant.

To the pellet. add 2.0 g of zirconiakilica beads mm in diameter). I .O mL TsoE5 containing 3% SDS.

Bead beat for 2.5 min at 5,000 rpm; cool on ice for 1 min: beat for another 2.5 min. I f

Spin for 3 min and collect the supernatant 3 1" extract I f

Add 0.9 mL TSOE5 with 3% SDS; bead beat and spin + 2"d extract

(Optimal) Repeat the zid extraction + 3rd extrart

Add 10M NHjOAc to a final conc. of 2 M; mix well. Place on ice for 5 min.

Centrifuge for 10 min at k: collect the supernatant.

Precipitate the nucleic acids from the supernatant with 1/10 Volume of 3 M NaOAc and with I Volume of Isopropanol. Leave on ice for 30 mi spin for 15 min. Remove supernatant. I

Rinse the pellet with 70% ethanol. spin for 5 min, remove supematant and vacuum dry for 2 min. I *

Dissolve the nucleic acids in 100 pL of TE. Pool together. I f

Add RNAse (5pL) and put in water bath for 15 min at 37°C. I +

Add 1 /IO Volume o f 3 M NaOAc and 2 Volume of EtOH to precipitate again. Place on ice for 15 min, spin or 15 min, remove supernatant. i

Dry the pellet for 2 min. Dissolve the nucleic acids in 50 pL of TE buffer.

3.7 DNA extraction from soil and DNA purification

PCR-ready DNA was readily obtained from 0.5 g of soil by using the FastDNAB

SPiN Kit for Soi1 (Bio 101. Vista Calif.). A 978-pL volume of 200 mM sodium

phosphate buffer (pH 8.0). 122 pL of MT buffer. and 500 mg of soil were added to a 2.0

mL conical screw cap micro centrifuge tube (Fisher Scientific Ltd.) containing a matrix

designed to lyse most ce11 types. The mixture was shaken in a Mini Beadbeater (Biopsec

Products, OK) at 2.500 rpm for 2.5 min, cooled on ice and shaken for another 2.5 min.

and then centri fuged at 16.000 x g for 30 S. One millilitre of supernatant was removed

and mixed with 250 pL of protein-precipitating solution. This mixture was centrifuged at

16,000 x g for 5 min at room temperature. The supernatant was then collected and stored

at -20°C.

A volume of 250 pL of the soil supernatant was added to a Spinfilter with 500 PL

of binding matrix. This tube was gently inverted five times, incubated for 5 min at room

temperature. and then centnfuged for 30 s at 16,000 x g. For this step. and al1 other

purification steps. the eluate in the catch tube was discarded aftrr centrifugation. The

pellet in the Spinfilter was washed by adding 500 pL of salt ethanol wash solution and

then centrifuged for 30 s at 16.000 x g. The Spinfilter was then centrifuged for 1 min at

16,000 x g to dry the pellet. The DNA was eluted by transfemng the Spinfilter to a new

catch tube. adding 50 pL of TE buffer. gently flicking the tube five times, and then

centrifuged for 1 min at 16,000 x g. To minimize DNA shearing, vortex mixing was

avoided. The DNA was then PCR-ready to use and was free of PCR inhibitors.

3.8 16s rDNA PCR and DNA sequencing

DNA obtained from the Alert-1 enrichment culture was used for 16s rDNA PCR

amplification. The 16s ribosomal DNA (rDNA) was amplified using the reagents and

procedures of Gibco BRL Life Technologies, Inc. (Gaithersburg. MD.) in a 0.5-mL tube

in a total volume of 50 pL. One microlitre of template DNA was added to a mixture of 5

PL of 10X PCR amplification buffer (10X buffer contains 200 m M Tris-HC1 [pH 8.41

and 500 mM KCI). 1.5 pL of magnesium chloride (50 mM). 0.4 pL of deoxynuc~eoside

triphosphate (10 mM). 0.25 PL of each 519f and 1492r primers (0.5 pM each), (137).

0.25 PL ( 1 -25 U) of Taq DNA polymerase. and 40.35 pL of sterile deionized water. The

Oligonucleotide Synthesis Laboratory. at the University of British Columbia. synthesized

the universal primers used. Thermal cycling was performed in a Powerblock II System

(ERICOMP) according to the following prograrn: initial denaturation at 95OC for 2 min;

20 cycles of 95°C for 30 S. 50°C for 45 S. and 72°C for 90 s: and a final extension at

73OC for 5 min.

PCR products were cloned with the TOPO TA cloning kit according to the

manufacturer~s instructions (Invitrogen. Cartsbad, Calif.). Resulting transformants were

screened by alkaline lysis (1 38). fo11owed by digestion of recovered plasmids with EcoRl

and checking for 973 bp fragments on a 0.8% agarose gel stained with ethidium bromide

(5 pdmL). and detected by UV excitation. Nearly 400 bp of the ribosornal sub-unit were

sequenced by using (FS) Taq terminator chemistry and primer 519f. Sequencing was

performed by the DNA Sequencing Laboratory, University of British Columbia. with a

mode1 373 DNA Automatic Sequencer (Applied Biosystems). The 16s rDNA partial

sequences determined for Ale-1 -6. Ale-1.14, and Ale-1.46 have been deposited in the

EMBL Nucleotide Database and have the following accession numbers : AF230874.

AF230875. and AF230876. respectively.

3.9 Phy logenetic analysis

Each 16s rDNA sequence that was determined was compared to other prokaryotic

1 6 s rDNA sequences using the Similarity - Rank analysis service o f the Ribosomal

Database Project (RDP) (139). The 16s rDNA sequences of the closest relatives to the

Arct ic soi1 isolates Variovorrrr paradoxtts. Pseltdomonus symnthu. Psezrdomonus

crerziginosu. Microcystis rlubens. Thermotogu thermurttm. Rhodococcus wythropolis.

Rhodococczrs glo berrtlus. Chloro bizcm limicola. Sphingomonas str. BN6. und

Sphingornonas str. UN 1 FI were retrieved from the RDP and aligned with the 16s rDNA

sequences of the Arctic soi1 isolates using Clustal X (available from the Department of

Genetics. University of Washington). One hundred bootstrapped data sets of the aligned

sequences were obtained using SEQBOOT. Phylogeny estimates for each of these data

sets were obtained by using the default parameters of DNADIST. A phylogenetic tree

was constmcted by analyzing the resulting distance matrices with the default parameten

o f NEIGHBOR and CONSENSE X (also available from the Department of Genetics,

University of Washington).

3.10 Restriction Fragment Length Polymorphism (RFLP) analysis

A different approach than sequencing the ribosomal sub-unit gene was used in

order to understand the community structure of the Alert-1 enrichment culture. This

approach used recently-developed techniques in molecular biology and provided a

culture-independent analysis of comrnunity structure ( 140. 14 1 ). RFLP analysis

examined variations in 16s rDNA sequences within the Alert-1 enrichment culture by

using a tetrameric enzyme to cut the 16s rDNA gene fragments of each clone in order to

identify different band patterns indicative of phylotypes in the enrichment culture.

Ptasrnid DNA was obtained frorn the 51 clones in the Alert-1 Iibrary using the

QIAprep Spin Miniprep kit (Calif.). Insert 16s rDNA gene fragments were restricted

from the plasmid vector using Mspl that recognizes the tetrarneric sequence CCGG. The

genomic DNA of each clone was incubated in a water bath at 37°C for 3 hours with 2.5 U

of a restriction enzyme in the appropriate buffer. and RFLP fragments were separated by

gel electrophoresis in 2.5% agarose stained with ethidium bromide (5 pg/rnL) and

detected by UV excitation. The RFLP patterns were compared by eye.

3.1 1 Phylotype-specific oligonucleotide primers

Phylotype-specific primers were designed for the 3 most abundant phylotypes in

the Alert- 1 consortium as identified through 16s rDNA sequencing and phylogenetic

association (Table 3-1). The oligonucleotides used for PCR priming were designed by

comparing the 1 -kb 16s rDNA sequences of Ale- 1 -6. Ale- 1.14. and Ale- 1.46 with the

closest relatives for each clones in GenBank (142). The sequences were aligned using

ClustalX and hypervariable regions in the three clones were retrieved. Specific sequences

(1 6 to 21 bp long) were then selected to design phylotype-specific PCR primers that were

at least specific at the 3' end to ensure specificity during PCR amplification.

The fonvard primer for Ale-1.6 was selected at position 648 of the 16s rDNA

gene of the reference organism Pseudomonas synranfha and has the following sequence :

5'-GAACTGCATTCAAAACTGTCG-3'. The reverse primer selected was at position

1065 and has the following sequence : 5'-TGTTCCCGAAGGCACCC-3'. The 1 -kb 16s

rDNA sequence from Ale-1 -6 (95.9% similar to Pseudornonas synxantha on RDP) was

compared and manually aligned with the 61 closest strains on GenBank after alignment

with BlastX (143). The alignment showed that the forward primer has a complementary

sequence to two other strains of Pseridumonas br~.rssicwceurrim and Pseridomonns

thivenalensis. The reverse primer had no complementary sequence to any other strain.

The PCR amplified product obtained with this phylotype-specific primer set is expected

to have a length of 4 17 bp.

The fonvard primer designed for Ale-1.14 was selected at position 61 1 of th

reference organism Sphingomonas sp. UNIFI and has the following sequence: 5 ' -

TGCTAGAATCTTGGAGAGGC-3'. The reverse primer was selected at position 1425

and has the following sequence: 5'-CCTTCGGGTGAATCCAAA-3'. The 1 -kb sequence

of Ale- 1.14 was compared and rnanually aligned with the 59 closest strains on GenBank

afier alignment with Blast. The primer set is complementary to four other strains of

Sphingomonus sp. str. MBIC 3020, Sphingornonus sp. str. BN6, Aerobic bacillus, and

Sphingornunus sp. str. UNI F2. The fonvard primer is also cornplementary to two strains

of Sphingomonas sp. str. DhA-3 3 and Sphingomonas sp. str. UN 1 F 1. These alignrnent

results predict that the primer set is specific to five Sphingomonas strains having high

similarity in their 16s rDNA sequence. The PCR amplified product obtained with this

primer set is expected to have a length of 8 14 bp.

The forward primer selected for Ale-1 -46 is situated at position 541 of the

reference organism Rhodococctls eryrhropolis and has the following sequence: 5 ' -

ATTACTGGGCGTAAAGAGT-3'. The reverse primer is located at position 1242 and

has the following sequence: 5 '-CGCAGCCCTCTGTACT-3'. The 1-kb 16s rDNA

sequence for Ale-I -46 was compared and manually aligned with the 44 ciosest strains on

GenBank afier alignment with Blast. The primer set has complementary sequences to one

other strain of Rhodococcrrs rrythropolis. The primer set designed for Ale-1.46 is

predicted to be species-specific to Rhodococc~ts erythropoiis. The PCR amplified product

has a length of 70 1 bp.

Table 3- 1 : Universal and phylotype-specific PCR primer sequences

Primer Length Nucleoside Sequenceh (bases) positionsu (5' > 3')

Ut1 iversal primers

Ale- 1.6 648f 2 1 648-668 GAACTGCATTCAAAACTGTCG> 1065r 17 1065- 1049 TGTTCCCGAAGGCACCC>

Ale- 1.46 541f 19 54 1-559 ATTACTGGGCGTAAAGAGP 1242r 16 1242- 1 227 CGCAGCCCTCTGTACP

" Nucleotide position for the universal primers are based on the reported 16s rDNA gene sequence for E. coli, GenBank Accession number EO5 133 (47). Nucleotide positions for al1 other prirners are based on the reported 16s rDNA sequences for the closest phytogenetic strain after alignment on RDP. ' K = G:T, and W= A:T; al1 1 : 1 .

3.12 Primer specificity

The three phylotype-specific PCR primer sets were tested against different

Psezrdomonus. Rhodococcus. and Sphingomonas strains to test their specificity. This

work was done by testing the primers by PCR amplification and/or by alignrnent o f the

oligonucleotide sequences to corresponding regions in the 16s rDNA of closest relatives

in the sarne genus (Table 3-2). The primer set designed for Ale-1.6 did not show

similarity to any of its closest relatives. The primers designed for Ale-1.14 showed

complete similarity to four reference strains and Ale-1.46 to three reference strains.

3.13 PCR-MPN Assay

DNA was extracted from each soi1 sarnple, as described above. using the B I 0 101

extraction kit. Tm-fold serial dilutions of DNA were made to IO" by adding 5 yL o f

DNA solution to 45 PL of TE solution (1 38). The diluted DNA was then PCR amplified

using the three phylotype-specific primer sets with the specific annealing temperatures

and conditions required for each set (Table 3-3). PCR amplification was done using the

reagents and procedures of Gibco BRL Life Technologies. Inc. (Gaithersburg, MD.) in a

0.2-mL tube using a total volume o f 25 PL- 0.25 microlitre of each dilution in triplicate

was added in a mixture of 2.5 pL of 10X PCR amplification buffer (IOX buffer contains

100 mM Tris-HCl [pH 8-41 and 500 mM KCl), 0.2 PL of deoxynucleoside triphosphate

(10 mM). 0.125 pL of both phylotype-specific primers (0.5 pM each), and 0.5 U of Tuq

polymerase. The Oligonucleotide Synthesis Laboratory. University of British Columbia,

synthesized the three phylotype-specific primer sets used. The annealing temperatures

were obtained after trials using different concentrations of magnesium chlonde and

annealing ternperatures. The optima1 annealing temperature for both Ale4 -6 and Ale-

1.46 was 62°C and 57°C for Ale- 1.14.

Table 3-2: Theoretical alignment of sequences of the phylotype-specific prirners designed for Ale- 1.6. Ale-1.14, and Ale- 1.46 with database sequences of 16s rDNA genes from species tested and not tested by PCR.

Secluence vs*: PCR Strain ~roduct

Ale- 1.6

P. syunrhu P. hrussicuc.c.urztm P. rhivervalensis P. umygdaii ATCC 3 36 I 4 P. agurici ATCC 2594 1 P. pzrridu P. syringae ATCC 1 93 1 0 P. srttlzrri ATCC 1 7589 P. ahietuniphilu BK M E-9

Sphingomonus sp. UN I F2 Sphingomonas sp. MICB 320 Sphingomonus sp. BN6 Aerobic bacillus Sphingomonus sp. UN 1 F I Sphingonlonus sp. D HA-33 Sphingomonus sp. DHA-95 Sphingomonus sp. R W I

A le- I .46

Rhod~~coccrts enrhropolis Nocurclioides ~runsvalensis Rhodococcus eqzti Rhodoc.occ.us globenrlus Rhodoc.occzcs koreensis TsztkamtireIIa wrurislaviensis

61 If TGCTAGAATCTTGGAGAGGC

TGCîAGAATCnGGAGAGGC TGCTAGAATCTTGGAGAGGC .TGCîAGMTCTTGG/\Gr\GGC TGCThGAATCmGG:\GAGGC TGC'TAGAATCTTGGtIGt\GGC TGCTAGAATCTTGGAGAGGC TGCTAGAATCTTGGAGAGGC CGCT~J~AACCTGCIAGAGGI

54 1 f AITACTGGGCGTAAAGAGT

A'ITACTGGGCGTAAAGAGT

ATTACTGGGCGTAAAGAGC ATTACTGGGCGTAAAGAGC AITACTGGGCGTAAAGAGT ATTACTGGGCGTAAAGAGC ATTACTGGGCGTAAAGAGC

TGGTGCCTCGGGAACA - TGGTGCC'TTCGGG AAC A - TGGTGCCTTCGGGAACA - ~ G T G C C ~ C G G G A A C A GAGTGCCTICGGGAACA TGGTGCCTTCGGGAAC - TGGTGCCTTCGGGAGCA - TGGTGCCITCGGGAACT - TGGTGCCTTCGGGAACA -

142% TITGGATTCACCCGAAGG

TITGGATTCACCCGAAGG

rnGGATTC.4CCCGAAGG TITGGA~nCACCCGAAGG

TTTGG ATîC ACCCGhAGG GTTGG ATTCACCCGAAGG - GTTGGATTCA-CGAAGG - GïTGGATTCAICGAAGG - CTTGGATTCtKCCGAAGG -

1243 AGTACAGAGGGCTGCG

AGTACAGAGGGCTGCG CGTACAGAGGGCTGCG

CGTACAGAGGGCTGCG - AGTACAGAGGGCTGCG AGTACAGAGGGCTGCG GGTACAGAGGGCTGCG -

+

NIT N r r

N r r

+

N n - N /T

N r r N m

NIT

+

N r r Nil- Nn- N r r Nil- N r r

" Nucleotides underlined and bolded differ fiom comesponding nucleotides in the oligonucleotide sequence. N/T = not tested.

Thermal cycling was performed in a MiniCycler fiom MJ Research (Calif.)

according to the following program: initial denaturation at 95OC for 2 min: 35 cycles of

95°C for 30 S. 57°C for 30 s for Ale-1.14 and 62°C for 30 s for Ale-1.6 and Ale-1.46. and

72°C for 90 s: and a final extension at 72OC for 5 min. Detection was based on the

presence of a PCR product after loading on a 0.8% agarose gel stained with ethidium

bromide (5 mg/mL). detected by UV excitation. The MPN numbers were obtained by

using the Web-based software QualityTM (AppIet) (144-147).

Table 3-3: Phylotype-specific primers: annealing temperature and product size.

PCR primer set Annealing temp. (OC) Product size (bp) Ale- 1.6 63°C 417

Ale-1.14

Ale- 1 -46

The plasmid DNA of the three most abundant organisms was used to calibrate the

PCR-MPN assay and to estimate the PCR detection limit for each phylotype (Fig. 3-2).

This plasmid DNA has the 165 rDNA fragment (973 bp) used to determine the

phylot ype-speci fic primers for eac h clone and was collected after alkaline lysis. The

number of DNA copies per pL was estimated by measuring the absorbance at 260 nrn.

Ale-1.6 (Pserrdomonas isynyarz(ha) was estimated at 7.59 x 10" copies per microlitre,

Ale-1.14 (Sphingomonas str. UN1 F I ) was estimated to have 7.59 x 10" copies per

microlitre, and Ale- 1.46 (Rhodococcus eryéhropolis) to have 7.23 x 1 01° copies/pL.

67

The plasmid DNA of each clone was diluted up to a dilution factor of IO"> (around

50 copies per PL) and used for PCR-MPN amplification using each primer optimal

conditions. Dilutions were made by using 5 pl of DNA in 45 PL o f TE buffer. Results

showed that the PCR amplification could detect up to 70 copies o f DNA per microlitre of

Ale-1.6 (Psercdomonas synrantha). 500 copies of DNA per micro

(Sphingomonas str. BN6). and 700 copies of DNA per micro1

( Rhodococctcs eryrhropolis).

litre of Ale- 1.14

itre of Ale-1.46

Spliingornonas sp. U N I F 1 Pseudomonas symntha Rhodococcus erytfiropolis

10-1- IO-^ 10-1 - 10-1 -

Fig. 3-2: 0.8% agarose gels showing PCR amplified 16s rDNA gene fragments in a serial dilution method. The left gel shows the MPN-PCR for Ale-1.14, the middle one shows the assay for Ale- 1.6. and the right one for Ale4 -46.

3.14 Enurneration of total viable heterotrophs and hydrocarbon degraders

Total viable heterotrophs (Le. culturable organisms) and hydrocarbon degraders in

the microcosm experiments were enumerated using a most probable number (MPN)

method modified from that of Wrenn and Venosa (148). This method involved the use of

microtiter plates with 96 wells. One gram of soi1 was mixed by vortexing several times in

9.0 mL of saline buffer solution containing 0.1% sodium pyrophosphate ( 1 g/L) and 2%

NaCl (8g/L). (pH 7.5). 180 pL of either TSB (10% strength) (BBL) used for total viable

heterothrophs or Bushnell-Haas (Difco) for hydrocarbon degraders was added to the

microtube weIls using a multichannel pipette. For hydrocarbon degraders enurneration,

1 -0 pL of filter (0.2-pm filter) sterilized Jet-A 1 fuel (5.000 ppm) was also added to each

well. Serial dilutions up to IO-" were done in 10-mL metal-capped glass tubes. and 20 PL

of each dilution was added to each corresponding well. The plates were incubated at 4°C

for 29 days before measunng growth. Growth for total viable heterotrophs was based on

turbidity and positive wells were scored visually. Jet Fuel oxidation was detected by

adding 50 pL of iodonitrotetrazoliurn violet (NT) (3g/L). In positive wells. iNT is

reduced to an insoluble formazan that deposits intracellularly as a red precipitate allowing

visual detection and scoring.

3.15 Soi1 sampling, soi1 physical and chemical properties, and TPH analysis

Biopiles were sampled at different tirnepoints using a composite sampling

method. Three sarnpIes per pile were taken at each timepoint. The control biopiles were

always sarnpled before the inoculated ones. The composite sampling means that small

amount of soil was taken from 8 different locations inside the pile and the soil collected

was mixed thoroughly before filling a 125-mL sterile TPH bottle. Triplicate sarnples

from each biopile were sampled this way. For the last timepoint (65 days), only one

composite sample was collected from each pile by taking soil from 5 different locations

inside the pile. Only one composite sample was taken instead of three because the

biopiles were frozen at that time (September 19. 1999) and also because of time and

resource constraints. Soil samples were also taken from the e~perimental site before the

start of the experiment and also at the end of the treatment period. These samples were

used to measure if the inoculum was spreading to nearby locations. They were taken

dong four transects (North. South. East. and West) starting at the location where the

biopiles were built and extending 100 meters away from the experimental site. Pristine

soil sarnples were also taken from remote locations outside inhabited area of the station

(up to 20 km away) to measure basetine TPH levels and also quantify the three strains in

non-contarninated locations, The location of these pristine sarnples is listed in Table 4-3.

The samples were frozen immediately in a -20°C freezer after sampling and

Pacific Soil Analysis Inc. (Vancouver. BC) conducted the soil physical and chemical

characterization to determine soil particle size and total carbon on the hydrocarbon-

contarninated soil used in both the field and microcosm experiments (Table 3-4). Total

petroleum hydrocarbons (TPH) were extracted from the soil samples and quantified by

gas chromatograph-flarne ionization detection (GC-FID) as described by Mohn and

Stewart (58). The soil water content was measured by placing known volumes of soil in a

110°C oven overnight and by weighing it the day after to determine water percentage in

al1 samples where TPH was analyzed to give a concentration per g of dry soil (see

Appendix B).

Table 3-4: CFS Alert soi1 physical and chernical characteristics.

Soi1 analysis Soi1 # l u Soi1 #zb Particle-size analysis %(sand/silt/clay ) 36.6 49.3 14.1 nd Soi1 water(%) 13 13 Soi1 pH 7.2 7.2 Total C (%) 3.77 3.92 " Soil from CFS Alert kept at 4'C for 5 months: "ame soi1 but kept frozen at -20°C for 5 months: nd: not deterrnined.

3.16 Statistics

An analysis of variance (ANOVA) was done for the field and the laboratory

experiments to test significant differences between triplicate set-ups and also between

treatments. The ANOVA was done for TPH values and also MPN numbers for both

experiments where the number of replication was greater than one. The test confirmed no

significant differences if P < 0.05. The confidence interval used was 0.05 (a = 0.05) and

the results for both experiments are presented in Appendix C.

4. RESULTS

4.1 Alert-1 enrichment culture

DNA extraction and cloning. The genomic DNA extracted is representative of

the total microbial community present in the Alert-1 enrichment culture. Fig. 4-1 shows

that the extraction method yielded a large arnount of nucleic acids from the enrichment

culture. The genomic DNA was PCR arnplified using the universal primer 519f and

I JWr and the PCR products were loaded on a 0.8% agarose gel to verify that they had

the expected 973-bp 16s rDNA gene fragment. Fig. 4-2 shows the 0.8% agarose gel with

products of the expected size.

The PCR products were cloned. and a total of 54 colonies were randomly picked

after they tested positive for a-complementation of P-galactosidase. A total of 51 of these

clones contained inserts of approximately the size of the expected 973-bp 16s rDNA

fragment afier digestion with EcoR1. Clones Ale-1 3. Ale4 20. and Ale-1.3 1 had no

insert or inserts of the wrong size and were rejected from the Alert-1-16s rDNA library.

Fig. 4-3 shows 25 clones of the Alert-1 16s rDNA library (Ale-1 -30 to Ale-1 -54) after

digestion with EcoR1. This screening step is essential to determine and select the clones

with 16s rDNA inserts.

16s rDNA analysis and phylogenetic identification. 29 clones from the 51 in

the Alert-1 16s rDNA library were randomly selected and were partially sequenced

(approximately 500 bp) using the 926f primer. The 16s rDNA sequences were then

compared with the ones present in the RDP (4) for phylogenetic association.

Fig. 4-1: DNA extraction from Alert-1 enrichment culture. 4 pL of a 1-kb ladder (100 ng/pI) (lane 1 and 5) was used to quantify the DNA extracted from the culture. In lane 2. 5 pL of DNA was loaded and in lane 3.2 pL of DNA was loaded. Lane 4 was empty.

Fig. 4-2: The 973 bp fragment from the 16s rDNA gene amplified frorn the genomic DNA of Alert-1 enrichment culture. Lane 1 and 6 were loaded with 2 pL o f 1 -kb ladder, lane 2 was the negative control, lane 3 is the desired PCR product using a DNA template with a ten-fold dilution. Lane 4 and 5 show the desired PCR product using the DNA template with two and three ten-fold dilution respectively.

The Sab values listed in Table 4-1 are similarity rank (Sab) numbers given afier

random alignment of al1 seven-base oligomers present within each sequence submitted

with the sequences present in the RDP. The value is a percentage similarity (ranging from

O to 1.0) between the seven-base oligomers aligned from the target sequence with al1

sequences listed in the RDP. This value can be considered as an estimate of the

phylogenetic relatedness of the organism having the submitted sequence and the

organisms represented in the RDP. There are about 10.000 sequences in the RDP. most of

them are from to the small subunit rihosomal DNA of Prokaryotes.

TabIe 4-1 lists the 29 clones sequenced in the Alert- 1-1 6 s rDNA library and the

Sab values for each clone along with its closest relative in the RDP. For example. the

clone Ale-1. l sequence is 100% similar (Sob = 1 .O) to the 16s rDNA sequence of

Rhodococcrts etythropoIis listed in the database.

Fig. 4-3: 0.8% agarose gel showing 25 Alert-l clones containing the 973-bp 16s rDNA inserts afier digestion with EcoR1. Clones are numbered fiom Ale-1.30 (left) to Ale-1.54 (right). 2 pL of I-kb ladder was loaded on the first and last lane of the gel to quantify the fragments.

74

Table 4-1 : Phylogenetic association of 29 clones based on partial 16s rDNA sequences.

Clonea S a b Phylogenetic Association

Ale-1.1 Ale- 1.5 Ate- 1 -6 Ale- 1.8 Ale-1-10 Ale-1.1 1 Ale-1.13 Ale-1.14 Ale-1.16 Ale- 1 . 1 8 Ale- 1.2 1 Ale- 1.23 Ale- 1 25 Ale- 1.27 Ale- 1.28 Ale- 1.32 Ale- 1.34 Ale- 1.35 Ale- 1.37 Ale- 1.38 Ale- 1.39 Ale-1.41 Ale- 1 -43 A le- 1.45 A le- 1.46 Ale- 1.48 Ale- 1.49 Ale- 1.52 Ale- 1.53

1 .00oP Rhodococcus erythropolis Pseudomonm s-w-wnth [AM 1 2356 Pseudomonus s-vn-ranthu I A M 1 23 5 6 Sphingornonas sp. str. UN 1 F 1 Variovorax paradoxzrs [AM 1 23 73 Rhodococcus globertrlzn DS M 4954 (T) Rhodococcz~s etythropolis Sphingornonus sp. str. UN 1 F 1 Sphingomonas sp. str. BN6 Pseudomonus sjmxanthu IAM 1 23 56 Rhodococcus etythropolis Variovorm purado-ms 1 A M 1 23 73 Rhoùococctcs erythropolis Rhodococcus eryrhropolis Rhociococcus erythropolis Rhodococcz~s evthropolis Sphingonroricls sp. str. B N 6 Psc.udomonas aeruginosa Rhodococcus erythr0poli.s Rhodococcrrs erythropolis Sphingornonas sp. str. UN 1 F2 Rhodococcus erythropo lis Rhodococctn eryrhropolis Rhodococczrs eryrhropolis Rhodococcus etythropolis Psezrdoniorius svn.ranthu 1 A M 1 23 56 Rhodococczr.s eryrhropolis Rhodococcu.~ erythropolis

0.969 Spliir~gonronas sp. str. U N 1 F I "Clones sequenced in the Alert- 1- 16s rDNA library.

The sequences were 400-500 bp long and represent almost one third of the total

16s rDNA gene. The region of the small subunit ribosomal gene sequenced contains

several hypervariable regions allowing this phylogenetic association. Close relatives of

Rhodococcus eryrhropolis were the most abundant phylotype in the Alert-1 enrichrnent

culture. Of the 29 clones sequenced, 55% were of this phylotype (Fig. 4-4). This suggests

that 55% of the community consists of members of Rhodococcus erythropolis or close

relatives. The second most abundant phylotype (21%) was rnost closely related to strains

in the genus Sphingomonas followed by a group related to Pseudomonas synxantha

(14%) and a group related to Variovorux pnradoxus (7%). A single clone was rnost

similar to the 16s rDNA of Pseudomonas aeruginosa. The Sphingomonas sp. phylotypes

were substantially variable between members. The sequences of the six clones were rnost

similar to three different strains of this genus. The three most abundant phylotypes

present in the Alert-1 enrichrnent culture were selected as targets for phylotype-specific

PCR primer design.

A phylogenetic tree was built using unique sequences amongst the 29 clones

sequenced m d represents the Alert-1 enrichment culture's major phylogenetic groups and

also the evolutionary distance between each of them and the reference strains (Fig. 4-5).

The clones were affiliated with the a-, B-, and y-Proteobacreria. and High G + C Gram

positive bacteria which are very distantly related groups. This tree indicates the

phylogenetic richness in the e ~ c h r n e n t culture which is one component of the diversity

of the community.

RFLP analysis was also done on the Alert-1 clones using a tetrarneric enzyme and

showed similar trends of diversity in the community. Fig. 4-5 shows the restriction

patterns of each of 5 1 clones in the Alert-1 library after digestion with Mspl . The enzyme

used recognizes and cuts the ribosomal subunit gene at every occurrence o f -CCGG-7

cutting with a high frequency dependent on the probability of occurrence of the four-base

recognition sequence. A restriction enzyme with a longer recognition sequence would cut

less frequently and would yield in fewer and larger DNA fragments.

Rhodococcus 8rythropolis A

2% 15 a E O - O % ' O

Sphingomonas sp. e Pseudomonas

B 5 F

s Pseudornonas aeruginosa

O lBzBBz4 1 2 3 4 5

P hylotypes

Fig. 4-4: Distribution of phylotypes of the 29 clones in the Alert-1-16s rDNA library. Analysis is on the b a i s of 400 to 500 bp sequences. The closest relative o f each phylotype is indicated.

Each similar pattern is indicative o f organisms likely belonging to a related phylogenetic

group (approximately equivalent to a species). A total of 8 different restriction patterns

were found in Fig. 4-5. being indicative of phylogenetic richness in the Alert-1

enrichment culture. Each different pattern is called an operational taxonomie unit (OTU)

and is assumed to represent a unique phylogenetic group in the community analyzed. The

number o f OTUs is an indicator of phylogenetic richness, and the relative abundance o f

OTUs is indicative of community structure.

Fig. 4-7 shows the distribution of OTUs in the group of 5 I bacterial 16s rDNA

clones from the Alert-1 enrichment culture distinguished by Mspl digestion. Abundance,

as determined by the number of 16s rDNA clones found in each OTU. was used to define

the community structure.

Sphingomonas sp. BN6 sp. UN 1 F I

P.seuriornorrus ueruginusu

P Chlorobizm limicola Ale-1.10

I ilr-iororar paradartrs Green Sulfu r Bacteria

.\ /içrocysris riabrns

Cyanobactena Rhodococctrs globenrhrs Ale-1.11

Tlrerrnomga rhermanrrn High G + C O. 1

Thermotogales Gram positives

Fig. 4-5: Unrooted tree showing phylogenetic relationship of Alert-1 enrichment culture clones (in bold) and reference strains. The phylogenetic tree was generated with nearly one third of the 16s rDNA gene. The scale bar represents 0.1 estimated change per nucleotide and the numbers indicate bootstrap values and represent percent confidence of 100 replicate analysis.

Fig. 4-6: Restriction patterns of the 16s rDNA genes from the 5 1 clones in the Alert-l- 16s rDNA library. 1 O pL of each reaction mixture was loaded on a 2.5% agarose gel. the first and the 1 s t lane contain 2 pL of 100-bp ladder to indicate DNA size.

The sequential determination of cumulative OTUs following RFLP analysis of a 5 1 -clone

bacterial 16s rDNA clone library is represented in Fig. 4-8. For exarnple. after 21 clones

were exarnined, 6 OTUs were detected. The 16s rDNA clone numbers reflect the order of

initial detection. which was assumed to be stochastic relative to the distribution of clones

generated in the library. To determine whether in situ bacterial diversity was well

described by the 165 rDNA clones examined and sequenced. the cumulative number of

OTUs was plotted in Fig. 4-8 as a function of clone number. This figure shows that the

detection of new OTUs afier analyzing 22 clones was not as frequent as the number of

OTUs detected in the first 2 1 clones analyzed. The fact that only 3 new OTUs were found

in the last 3 1 clones analyzed indicates that the microbial diversity was well characterized

in the Alert- 1 16s rDNA library by the RFLP analysis.

1 2 3 4 5 6 7 8

Operational Taxonornic Uni& (OTU)

Fig. 4-7: Distribution in OTUs arnong 54 bacterial 16s rDNA clones from the Alert-I enrichment culture afier digestion with Msp 1 .

16s rDNA Clone (s)

Fig. 4-8: Estimation of diversity in the Alert-1 enrichment cdture after digestion with Mspl. This graph shows the sequential detection of cumulative OTUs following RFLP analysis of 5 1 -clone bacterial in the Alert- 1 16s rDNA clone Iibrary.

The main goals o f the above work were the characterization and the phylogenetic

identification of the organisms present in the Alert-1 enrichment culture. The next step

was the quantification of the three most abundant phylotypes in the Atert-1 enrichment

culture. Phylotype-specific PCR primers were designed for Ale- 1.6. Ale- 1.14. and Ale-

1.46 and were used in a PCR-MPN assay. This assay c m quanti@ the rDNA copy

number for organisms putatively belonging to each phylotype within the total community

and was done on the enrichment culture. The total bacteria. as well as members of the

Ale- 1 -6. Ale-1.14. and Ale- 1.46 phylotypes. were quantified in the Alert- 1 culture at four

different timepoints: 1 1. 2 1. 89. and 162 days. This culture was grown at 4OC in PAS

medium with Jet-Al Fuel as the only organic substrate. Fil. 4-9 shows the abundance of

each phylotype at the different timepoints along with each addition of 60 ppm of Jet-Al

Fuel. The numbers listed are most probable numbers (MPN) and were obtained by

extracting the DNA from 6 mL of the enrichment culture at each timepoint and by using

the phylotype-specific primers and the universal primer pair 5 I9f/l4Wr in the PCR-MPN

assay.

The total bacteria quantification did not show any variations in numbers between

each timepoint. The assay indicated approximately 4.0 x 10' cells per mL of the

enrichment culture for the total bacterial community at each of the four timepoints

analyzed. With respect to the three most abundant clones, Ale-1.14 is by far the most

abundant of the three phylotypes at I l and 21 days with around 4 x IO" copies per mL of

culture. The MPN of this phylotype decreased €rom 89 to 162 days to a final MPN of 400

copies per mL of culture. Al1 three phylotypes were present in approximately the same

number of copies per mL after 162 days of growth. The total bacterial density in this

experiment was expected to increase with time in the enrichment culture. The turbidity of

the culture. visually observed. increased from the start to the end of the experiment

indicating an increase in the culture biomass.

I.OE+OI x m > i e ~ x x x w W f i m

O 20 40 60 80 100 120 140 160 180

Time (days)

Fig. 4-9: Abundance of the three most abundant phylotypes and the total bacterial population in the Alert-1 enrichment culture versus time. A Ale-1.14. m Ale-1.46. + Ale- 1.6. and x - total bacterial population. The syrnbol (*) on the x-axis shows time when 60 ppm of Jet-Al fuel were added.

A sample of the enrichment culture was also streaked on PAS plates to try

culturing organisms present in the Alert- 1 enrichment culture. The plates were incubated

at 7°C with Jet-Al Fuel vapors as the sole organic substrate. Seventeen colonies were

randornly picked and were used as template for PCR amplification using the three

phylotype-specific primer sets to determine if the three most abundant phylotypes were

culturable. A total of 6 colonies were positively identified as members o f the Ale.l-44

phylotype (Rhodococczrs erythropolis) and 3 other colonies as members of the Ale-1 -6

phylotype (Psezrdomonas syn~antha). The success in isolating organisrns belonging to

two of the major phylotypes was surprising because most soil microorganisms (90-99%)

are not culturable with conventional methods.

4.2 The field experiment

The goal of the field experiment was CO deterrnine the effect o f inoculation on

TPH biodegradation for on-site bioremediation of hydrocarbon-contarninated soi1 at CFS

Alert and also to monitor the growth and fate of the inoculum. Six 0.5 m' biopiles were

built, three control uninoculated and three inoculated with the Alert-1 consortium at a

density of 106 cells per g of dry soil. The experiment length was 65 days and TPH

measurement and strain quantification were done at four tirnepoints. The outside

temperature at CFS Alert was recorded during the experiment and is presented in Fig. 4-

IO. A total of 24 days in the experiment had an outside temperature above 0°C. the

remaining of the experiment was done with a temperature below 0°C. The biopiles were

frozen at the last sampling time (65 days). The temperature inside the biopiles was not

recorded.

TPH biodegradation. Fig. 4-1 1 shows the TPH degradation profile in the field

experiment during the 65-day experiment. The data shown in this figure presents the

overall TPH removal in the control uninoculated biopiles versus the inoculated biopiles.

The only difference between the two treatments was the addition of the inoculum in the

inoculated biopiles. The data presented are the means calculated from the triplicate

treatments and include the standard deviation of the mean.

Bioaugmentation was not effective in stimulating TPH removal in the field

experiment. The control uninoculated biopiles showed final TPH levels of around 500

ppm (mgkg of dry soil) after 65 days of treatment and the inoculated biopiles had an

average final TPH concentration of 700 ppm (mgkg of dry soil). The most active

biodegradation rates (90 mg of TPH per kg of dry soil per day) were in the first 14 days

o f the experiment where almost 50% removal occurred.

Expenment length (days)

O 10 20 30 40 50 60 70

Fig. 4-10: Outside temperature at CFS AIert during the field experiment (provided by Environment Canada). The field experiment started on June 16 and the last tirnepoint was on September 19, 1999.

Analysis of variance (ANOVA). (a = 0.05). confirms that there were no

significant differences between the TPH concentrations in the control biopiles versus the

inoculated biopiles at any tirne. The ANOVA was also applied to test variability in

triplicate set-ups and confirmed that there were significant differences in TPH

concentration between replicate treatments in the control uninoculated treatment at al1

times. For the inoculated treatment. the ANOVA showed significant differences in TPH

concentration between replicate treatments in only one timepoint (O days) but no

variability in the two later timepoint tested (14 and 28 days). For details of the ANOVA

tests. see Appendix 3.

30 40

Time (days)

Fig. 4-1 1: Final biodegradation o f TPH in the field experiment showing the progress between the control and inocülated biopiles after 65 days of treatment. O Uninoculated biopiles, and o inoculated biopiles. Error bars indicate standard deviation; n = 3.

Populations of phylotypes. The three most abundant phylotypes were also

quantified in the field experiment using the PCR-MPN assay and the phylotype-specific

primers. The goal was to monitor the inoculated strains and test their fate in the

inoculated biopiles. The Ale-1.14 and Ale- 1.46 phylotypes were more abundant in the

inoculated biopiies than the uninoculated ones at the start o f the experiment (Fig. 4-12)

and were each approximately ten times higher in the inoculated treatments compared to

the uninoculated ones. The Ale-1.6 phylotype population was not significantly different

on day O between the two treatments, so the inoculation of this phylotype could not be

detected at the start of the experiment. The phylotypes were also quantified after 65 days

of treatment. and the MPN of the three phylotypes in each treatment were similar.

approximately 106 cells per g of dry soil. The only significant difference in the three

phylotypes at that timepoint was for Ale-1.14 having a MPN ten tirnes greater in the

inoculated biopiles than in the control uninoculated ones. Al1 phylotypes increased

significantly in both treatrnents. Thus. the effect of inoculation was more apparent at the

start of the experiment than after 65 days of treatment. Analysis of variance (a = 0.05)

was done to test if there was significant differences with respect to phylotype

enumeration within tri pl icate set-ups and also between treatments. Results showed that

there were significant differences in the MPN numbers of the three phylotypes in the

inoculated treatment at time O days. This result may suggest that the inoculum was not

weIi mixed in the biopiles. On the other hand. no statistical variability was shown for the

three phylotypes in the control uninoculated treatment at the sarne time. With respect to

ANOVA analysis between treatments. there were significant differences in MPN

numbers for the Ale- 1.14 and Ale- 1.46 at O and 65 days. Ale- 1.6 phylotype did not have

any variability between treatment at the same tirnepoints (Appendix 3).

Testing the spreading capability of the inoculum. Soil samples were also taken

at the experimental site before the biopiles were constructed and at the end of the

treatment period (65 days). This was done to determine if any of the three strains could

be detected prior to starting the experiment and if the inoculated strains were spreading

from the experimenta1 site during the bioremediation experiment. Soil sarnples were

taken along four transects at 25 m. 50 m. and 200 m away from the location where the

biopiles were built (Fig. 4- 13).

Control Aies hoculated Ales Control Files inocuhted Ries O B y s O days 65 Days 65 ûays

Fig. 4-1 2: Populations o f phylotypes in the control and inoculated biopiles at CFS Alert afier O and 65 days of treatment. Error bars indicate standard deviation; n = 3.

Twelve soil samples were collected before the start of the experiment ( 3 sarnples

per transect) and another twelve after 65 days o f treatment. Al1 sarnples were screened

with the three phylotype-specific PCR assays to see if any of the three strains could be

detected and enumerated at these locations (Table 4-2). Detection levels for al1 three

phylotypes were calculated and Ale-1 -6 was undetectable at < 70 copies per g of dry soil.

Ale-1.14 was undetectable at < 500 copies per g of dry soil. and Ale-1.46 was

undetectable at < 700 copies per g o f dry soi1 (Fig. 3-2). Only the Ale-1.14 phylotype

could be detected in the sarnples taken. This phylotype was detected at 20 m East and 20

m South at the start of the experiment and also afier 65 days of treatment. The goal was

to test if Ale- 1 - 1 4 could spread during the 65 days of treatment by enumerating this strain

at both timepoints. At the 20 m East location. Ale-1.14 phylotype was estimated at 190

copies per g of dry soil before starting the experiment and at 370 copies per g of dry soil

after 65 days of treatment. At the 20 m South location. Ale-1 -14 was present in the sarne

density at both timepoints. These results do not suggest that Ale-1.14 phylotype spread

from the experimental site to nearby locations.

Pristine and other hydrocarbon-contaminated soils. The Ale-1 -14 phylotype

was also the only phylotype present in most pristine soils collected at CFS Alert. Al1

three phylotypes could be detected in two other hydrocarbon-contaminated soils

(different locations than the field experiment) at the station. Ten pristine soil samples

were analyzed for TPH and for the three most abundant phylotypes in the Alert-1

enrichment culture in order to see if these phylotypes were indigenous to non-

hydrocarbon-contaminated soils at CFS Alert (Table 4-3).

Fig. 4-13: Spatial sampling locations around the experimental site in order to measure if the inoculated strains c m spread to nearby locations. "O" at the center of the Figure indicates the location at CFS Alert where the biopiles were built.

Three samples were tested for TPH and al1 ten samples were screened for the

three phylotypes. The three pristine sarnples tested for total petroleum hydrocarbons

showed no residual TPH. proving their uncontaminated state. OnIy Ale- 1.14 could be

detected by PCR amplification in the sarnples. Neither Ale-1 -6 nor Ale-1 -46 phylotypes

were detected in these samples. A PCR-MPN assay was then done to enumerate Ale- 1.14

in two positive pristine sarnples and this phylotype was estimated at approximately 190

copies per g of dry soi1 in each sarnple.

The three phy lotypes were detected in both hydrocarbon-contarninated soils tested

but no enumeration was done. These two contarninated soils were sampled from on-site

bioremediation experiments where nutrients and biosurfactant were supplemented. The

diesel day tank sample was taken frorn engineered biopiles and the other sample was

collected from a l and fming experiment. The detection limits for the three most

abundant phylotypes were calculated from plasmid DNA and by using the PCR-MPN

assay (Fig. 3-2). AIe-1.6 was detected above 70 copieslpl of DNA. Ale-1 -14 was

detected above 500 copies/pL o f DNA. and Ale-1.46 could be detected above 700

copies/pL of DNA.

4.3 Laboratory experiment

TPH removai in microcosms. CFS Alert hydrocarbon-contarninated soil in

laboratory rnicrocosms incubated at 7OC behaved sirnilady to the soil treated in the field

experirnent with respect to hydrocarbon disappearance. Fig. 1-14 shows no difference

between the controI uninoculated rnicrocosms, the microcosms inoculated with 1 o6 cells

per g of dry soil. and the microcosms inoculated with 109 cells per g of dry soil with

respect to TPH biodegradation. ANOVA (a = 0.05) indicated no significant differences

between the three treatments in ten out of eleven tirnepoints tested. The only exception

was at 32 days where significant differences in TPH concentrations were detected

between treatments (Appendix 3).

Table 4-2: Soil sarnples collected from the experimental site before the start of the experiment (June 1 5Ih. 1999) and afier 65 days (September 1 9'h. 1999). The detection and enumeration of the three most abundant phylotypes (Ale-1.6, Ale-1.14. and Ale-1.46) in the inoculurn is also shown.

Soi1 sarnple Locat iona S trains detectedb Enumerationc (MPN/g of dry soil)

ln if iu l sunlples UBC-99- 1 0 I I 0 0 m N Ale-1-14 nt U BC-99- 1 0 2 50 m N nd nt UBC-99- 103 20 m N Ale-1.14 nt UBC-99- I 0 4 1 0 0 m E nd nt U BC-99- 1 0 5 50 m E Ale-1.14 nt U BC-99- 1 06 20 rn E Ale-1.14 1.9 x IO? UBC-99- 1 0 7 1 0 0 m S nd nt U BC-99- 1 0 8 50 m S Ale-1.14 nt U BC-99- 1 09 20 rn S Ale- 1.14 1.9 x IO'

nt nt nt

Final sumplcis UBC-99- 17 1 UBC-99- I 72 U BC-99- 1 73 U BC-99- 1 74 UBC-99- 1 75 UBC-99- I 76 UBC-99- 1 77 U BC-99- I 78 U BC-99- 1 79

nd nd nd nd nd

Ale- 1. Ale- I . Ale-1. Ale- 1.

U BC-99- I 80 1 0 0 m S Ale-]. 14 nt UBC-99- 18 I 50 m S nd nt UBC-99- 1 82 20 m S Ale-1-14 1.9 x IO' " Locations are relative to the point where the biopiies were built, nd = none detected. ' nt = not tested.

Table 4-3: Analysis of CFS Alert pristine and hydrocarbon-contaminated sarnples for TPH and phylotype detection.

Sample Location at T P H ~ Phylotypes MPN number CFS ~ l e r t ' > (mg/g o f dry soil) detectedC (per g of dry soil) UBC-99- 183 021 573 nt Ale-1.14 nt

UBC-99- 185 Hilgard Bay Area nt Ale-1 -14 nt

UBC-99- i 86 023 547 nt Ale-1.14 nt

UBC-99- 1 87 023 547 nt AIe-1 -14 nt

Diesel day tankd CFS AIert = 5.000 Ale-1.6.-1.14, nt

and - 1.46

Lanfarming plots'' CFS Alert = 5.000 Ale-1.6. -1.14. nt

and - 1 -46 "Grid coordinates at CFS Alert. nt = not tested. ' nd = none detected, '' = Treated soi1 (4).

The sterile control showed little TPH disappearance which rnay be due to TPH

volatilization during sampling periods. The initial TPH concentration in al1 three

experiments was around 2.400 ppm ( m g k g of dry soil) and the final TPH concentration

left after 92 days of treatment was around 650 ppm.

Most TPH removal in the microcosms was due to biodegradation. The difference

in TPH removaI between the sterile control and the active set-ups is indicative of

microbial degradation of the petroleum hydrocarbons in soil. Fig. 4-15 shows the actual

profile of the total petroleurn hydrocarbons in the soil at the start and the end of the

experiment. In this chromatogram, six major peaks being representative of aliphatic non-

branched compounds are shown and are reduced afier 92 days o f treatrnent in the

rnicrocosms.

Fig. 4- 14: TPH removal in the microcosm experiment. X-Sterile control. O Uninoculated. mhoculated 1 06. and A Inoculated 1 09. Error bars indicate standard deviation: n = 3.

TPH Start TPH remaining after 92 days. FID signal

2300 mg/kg of dry soi1 FID signai 7.0d 700 mgkg of dry soi1

7 .0~5

Fig. 4-1 5: Chromatograrn of the TPH at the start and the end (92 days) of the microcosm experiment showing the removal of straight aliphatic compounds. C 1 1 : undecane, C 12: dodecane. C 13: tridecane. C 14: tetradecane. and C 15: pentadecane. A GC-FID was used for this analysis and an intemal standard (is) is shown on the chromatograrn. The intemal standard used is phenanthrene.

Populations of phylotypes. The microcosm experiment showed sirnilar results with

respect to phylotype enumeration than did the field experiment (Fig. 4-16). The total

bacterial community was additionally enumerated in the laboratory experiment. The total

bacterial MPN did not change during the experiment (at 4 and 29 days) in both treatments

and was the sarne in both treatments. The inoculum could be detected for two phylotypes

after 4 days of treatment in the inoculated microcosm. Both Ale-1.14 and Ale- 1.46

phylotypes were present in greater numbers (one-fold higher for Ale-1.46 and two-fold

higher for Ale-1.14) in the inoculated microcosm after 4 days compared to the control

uninoculated one. Ale-1.6 phylotype was one-fold (ten times) more abundant in the

inoculated treatment after 4 days of incubation than in the uninoculated treatment. The

populations of phylotypes at 29 days presented the exact same pattern for al1 three

phylotypes in the uninoculated and the inoculated microcosms. The populations of Ale-

1.14 and Ale- 1 -46 increased in the uninoculated treatment but were unchanged in the

inoculated treatment. Fig. 4-16 does not include error bars because the three phylotypes

were quantified from only one sample per treatment at the two timepoints tested instead

of three samples per treatment (like in the field experiment). Each sample analyzed by the

PCR-MPN assays for the laboratory experiment had 5 pL of DNA extracted from each

triplicate microcosm pooled together. This method was used to reduce the number of

PCR reactions and is still taking in account the populations in each triplicate set-up for

each treatment (uninoculated control and inoculated with 109 cells per g of dry soil).

aTotal bacteria

Control 4 Days

Control 29 Days

lnoculated 4 Days

lnoculated 29 Days

Fig. 4-1 6: Populations of phylotypes in the microcosm experiment at 4 and 29 days. Only the control uninoculated experiment (C) and the inoculated experiment with lo9 cells per g of dry soil ( 1 0A9) were tested.

The total culturable heterotrophs and total hydrocarbon degraders were also

enumerated in the laboratory experirnents. Both groups showed an increase from 4 days

of treatment to 29 days (Fig. 4-17). The number o f total culturable heterotrophs was

similar in al1 three treatments afier 4 days of incubation with a MPN of approximately 6.0

x 10' cells per g of dry soil. Afier 29 days of treatrnent. the total culturable heterotrophs

in the control experiment increased by more than four-fold. Both the inoculated

microcosms with 1 o6 and 1 o9 cells per g of dry soil showed an increase of approximately

ten times.

The culturable hydrocarbon degraders in the laboratory experiment also showed a

great increase between 4 and 29 days of incubation (Fiy. 4-18). The number of

hydrocarbon degraders were approximately the sarne in the three treatments after 4 days

of incubation. Thus. the inocula were not detectable as increases in culturable

hydrocarbon degraders. Hydrocarbon degraders increased by more than 100 times in al1

treatments. Culturable hydrocarbon-degraders. as a fraction of total culturable

heterotrophs, increased from approximately 0.22 to 9.0% in the microcosm inoculated

with 106 cells per g of dry soil. and from approximately O. 13 to 22.9% in the microcosm

inoculated with lo9 cells per g of dry soil during the incubation period. The culturable

hydrocarbon degraders. again as a fraction of total culturable heterotrophs. did not

increase in the control microcosm during the sarne period.

Control 1 1 0A6 RI 1 0A9 1 .OE+l3 r

4 days 29 days

Fig. 4- 17: Enumeration o f total culturable heterotrophs in the microcosm experiment at 4 and 29 days in TSB (10% strength) medium. Error bars indicate standard deviation; n = 3.

iZ4 Control W 1 0A6 BI 0A9 1.00E+11 [

4 days 29 days

Fig. 4-18: Enumeration of hydrocarbon degraders in the microcosm experiment at 4 and 29 days in the hydrocarbon medium. Error bars indicate standard deviation; n = 3.

5. DISCUSSION

5.1 Alert-1 enrichment culture

The Alert-1 enrichrnent culture is a cold-adapted hydrocarbon-degrading

consortium that was grown to serve as the inoculum in a field experiment at CFS Alert.

The field experiment's main goal was to test the effect of inoculation for on-site

bioremediation of hydrocarbon-contaminated soil in engineered biopiles. The Alert-1

enrichment culture was inoculated with hydrocarbon-contarninated soil that originated

from the upper POL site at CFS Alert. This location was contaminated with diesel fuel,

and T'PH levels remained at high concentrations before the soil was remediated during

the surnmer of 1998 (4). The Alert-1 enrichrnent culture is indigenous to CFS Alert as it

was enriched from the station's hydrocarbon-contaminated soil. It was grown at 4OC in

minera1 medium with Jet Fuel as the only organic substrate. This consortium is assumed

to contain psychrotolerant organisms that c m degrade petroleum hydrocarbons occumng

in Jet Fuel which is similar to Arctic diesel fuel.

The Alert-1 enrichrnent culture was characterized by extracting the culture's

genomic DNA and by PCR arnplifying the 16s rDNA genes of the microbial community.

This molecular method to identiG the composition of a microbial community is

extremely powerful. This method relies on information encoded in highly conserved

ribosornal genes. Most soil microorganisms (90-99%) cannot be cultured or screened

using conventional microbiological methods and thus require molecular biology tools.

The choice to do the analysis on ribosomal DNA (rDNA) instead of ribosomal RNA

@RNA) was based on the fact that DNA more closely represents the composition of the

microbial cornmunity. Analysis at the RNA level is influenced by physiological activity

of the population because the copy n m b e r of rRNA per ce11 c m Vary greatly (149).

Direct analysis of 16s rRNA can potentially bias diversity estimations in favor of rapidly

growing populations of cells or in favor of the best adapted groups in the consortium.

This can underestimate the genetic diversity present in a given habitat compared to 16s

rDNA that is more representative of the absolute genetic diversity and community

structure. including slow growing or dormant organisms. Analysis of rDNA involves the

use of universal primers that are cornplementary to highly conserved regions of the 16s

rDNA of the entire bacteria domain. Therefore. I assurned that the Alert-1-16s rDNA

clone library approximated the relative distribution of phylotypes in the Alert-l

enrichment culture.

Phylogenetic association of randomly selected organisms within the microbial

cornmunity was successfd in identifying the most abundant members of the Alert-1

enrichment culture. Species diversity and species richness were also assessed using the

same rnethod. allowing the identification of phylogenetic groups that may be highly

active in the biodegradation of hydrocarbons at CFS Alert and maybe eIsewhere in the

Arctic. Phylogenetic identification is accurate if 16s rDNA sequences that are submitted

to RDP are highly similar to the ones recorded in the database (Sab values > 0.98).

Another potential way to identify unknown organisms is by DNADNA hybridization of

the entire genomic DNA of a pure bacterium. If the DNA hybridization of the unknown

organism to that of the DNA of the reference organism indicates 70% or greater identity,

the organisms are considered to belong to the same species (150). The 29 clones in the

Alert-1-16s rDNA library that were sequenced showed high similarity rank values to

reference strains in general. suggesting a correct phylogenetic association (Table 4- 1).

This is tme especially with the clones having 100% similarity to Rhodococcus

erythropolis (Sab = 1.0). which are likely members o f that species. The Alert-l

enrichrnent culture was expected to contain several organisms competing for the sole

energy source. Fig. 4-4. 4-7. and 4-8 al1 show a community structure on the basis of the

phylogenetic groups (or OTUs) identified or estimated in the Alert- 1 - 16s rDNA library.

In these three figures. groups with larger populations are dominant and are expected to be

better adapted to the environmental conditions and to grow and reproduce more

efficiently. Based on the 16s rDNA analyses. organisms cIosely related to R. eryrhropolis

are presumed to be the most cornpetitive group in the AIert-1 enrichment culture. The

RFLP analyses showed conclusive results with respect to the most abundant phylogenetic

groups (Fig. 4-7). Presumably OTU 1, that accounts for 55% of the 16s rDNA clones,

corresponds to R. erythropolis phylogenetic group. Similady. OTU 2 (20% of the clones

analyzed) likely corresponds to the Sphingomonas sp. group and OTU 3 (5%) is most

likely to be related to Pseudornonas synranthu group. These results are consistent with

the phylogenetic identification of 29 clones in the Alert-1 library after sequencing the

16s rDNA gene (Fig. 4-4). In this figure. 55% of the clones sequenced showed high

similarity to R. erythropolis. 2 1% to Sphingomonas sp., and 14% to P. symantha. The

latter phylogenetic group showed a difference in percentage of the clones analyzed in

both figures with the two methods (5% versus 14%) but Iikely corresponds to P.

symntha phylogenetic group.

The three most abundant phylotypes in the Alert-1 enrichrnent culture are

assumed to be psychrotolerant hydrocarbon-degrading organisms. Many researchers have

isolated strains related to these most abundant phylotypes having capabilities to degrade

hydrocarbons at low temperature. Rhodococcus sp. str. Ql5 was shown to degrade

variable chain-length alkanes at low temperatures and to possess an aliphatic aldehyde

dehydrogense gene highly homologous to the Rhodococcz~s e~hropo l i s thcA gene

( 15 1 ). R. eryfhropolis BD2 has the ability to utilize isopropylbenzene as the sole organic

substrate ( 1 52). An aromatic-compound-degrading Sphingornonas sp. was isoiated from

Antarctica and shown to possess the GST gene which was successfully used as a genetic

marker for PAH-degrading bacteria (1 53). Three Psetldomonas strains were isolated from

petroleum-contaminated Arctic soils and characterized. Two of these strains have

degradative capabilities for C5 to C l 2 n-alkanes. toluene. and naphthalene at low

temperatures ( 1 54).

The use of the 16s rDNA analysis to estimate community structure is an efficient

tool but also has limitations and potential biases. Among them. the possibility of selecting

specific groups during the extraction process is possible. and attention should be taken to

mavimize the extraction efficiency and also DNA yield to avoid selection before PCR

amplification of the cloned 16s rDNA. There is also potential for bias during the PCR

amplification using universal primers (155) and also PCR-mediated chirneric gene

amplification (1 56). However. this nucleic-acid-based approach for population detection

and quantification is certainly less biased than culture-based methods which can only

detect a small fraction of soi1 organisms.

The RFLP analysis of the Alert-1 clones was another molecular method to study

community structure by estimating unique band patterns after digestion with a tetrarneric

enzyme. The number of OTUs in Fig. 4-7 and also their relative abundance is consistent

with the community structure determined after sequencing the 165 rDNA genes (Fig. 4-

4). The RFLP method allows estimation of community structure but is less reliable and

precise than sequencing the small subunit ribosomal gene. One way to increase resolution

of RFLP analysis is the use of tandem tetrarneric restriction enzymes to establish OTUs

based on more recognition sites in the 16s rDNA ( 1 57).

The three most abundant phylotypes in the consortium were identified by

sequencing nearly two-thirds of the 16s rDNA of each clone. Phylotype-specific PCR

primers were then designed for the Ale- 1.6 (Pseudornonns sp. ). Ale- 1.14 (Sphingornonas

sp. ). and Ale- 2 -46 (Rhodococcr~~ eryrhropolis) phylotypes by comparing their 1 6s rDNA

sequences to the closest matches on GenBank (142). Nearly fifty sequences from

reference organisms that are closely related to each clone were retrieved and manually

aligned with the sequences obtained from Ale- 1 -6. Ale- 1 - 14, and Ale- 1.46. Hypervariable

regions in the 1 . 1 Kb sequence of each clone were determined and were then used to

design oligonucleotides that were presumably specific to only the three most abundant

phylotypes in the Alert- 1 enrichment culture. Table 3-4 summarizes the alignments of the

oligonucleotide primers designed for the three clones with the corresponding database

sequences of 16s rDNA genes from closely related species. Other organisms within the

same genera were tested to see if they would yield a product after PCR amplification

using the phylotype-specific PCR primers of Ale- 1.6 and Ale- 1.14. The nine reference

strains tested for PCR amplification using these two primer sets did not yield in any

amplification of their 16s rDNA genes. The theoretical alignment did show four

organisms having sequences with 100% sirnilarity to Ale- 1.14 primer's sequences. The

Ale-1.6 primer set did not have complete identity with nine reference strains (afier

theoretical alignrnent) and the primer set designed is likely specific to this clone only.

The Ale-1.46 sequence is identical to that of Rhodococcus crythropolis. Thus. primers

could not be designed to discriminate between the two.

These phylotype-specific primers were used in the PCR-MPN assays to estimate

the populations o f the three phylotypes in the enrichment culture. along with the use o f

universal primers to estimate the total bacterial population size. The genomic DNA was

extracted from six mL of the enrichment culture at 1 1. 21. 89. and 162 days. It was quite

surprising thôt the estimation of the total bacterial community did not Vary during the

length o f the experiment (Fig. 4-9). This number was expected to increase because the

turbidity of the culture did increase over time. This visual observation suggested that the

biomass was increasing, and the total bacterial community was expected to do the sarne.

Two possible reasons that could explain this result are related to the culture composition

and the sampling technique. The Alert-l enrichment culture was mainly composed o f

cells aggregated together and also contained a high extracellular polysaccharide content.

The sarnpling of the culture was done using a Pasteur pipette that could have been

clogged with the ce11 biomass. So from one timepoint to another. there is a possibility that

the sarne amount of biomass was collected. not representative of the culture ce11 density.

and this would yield the sarne arnount of DNA.

The population dynarnics o f the three clones, relative to one another, did Vary

during the experiment and accounted for approximately 10% of the total bacteria afier 14

days of incubation (Fig. 4-9). This fraction decreased to approximately 1% at 92 days,

and less than 0.1% afier 165 days o f incubation. This result is not consistent with the

community structure in Figs. 4-4 and 4-7 where the Rhodococclrs eryrhropolis phylotype

is the most abundant (approximately 55%) in the Alert-1 enrichment culture after

sequencing the 165 rDNA gene and also after RFLP analysis. One possible explmation is

that two different e ~ c h m m t cultures were used to conduct the moIecular work and the

population dynamics of the three rnost abundant phylotypes. The DNA extraction

followed by the RFLP analysis and the 16s rDNA sequencing were done on an initial

enrichment culture after incubation for 2 1 days. The enumeration of the three phylotypes

was done later on another Alert-1 enrichment culture that was started from the same

Iyophilized cells and also with the same conditions as the first culture. It is then possible

that the lyophilized cells used to start the first enrichment culture couId have differed in

phylotype population densities from the second culture. Both cultures were grown at 7°C

with the same addition of Jet-Al Fuel as the sole organic substrate. This suggests that

even when incubated under constant conditions, the composition of a mixed ennchrnent

culture may Vary substantially. Another area of concern is the efficiency of the sampling

method and the accuracy of getting a representative sample of the microbial community.

The problem of having aggregated cells in the Alert-1 enrichment culture could be

responsible for non-representative sampling of the community.

Several authors have anal yzed the microbial diversity in different soils using

molecular methods including 16s rDNA sequencing and RFLP analysis (1 57- 160). Other

researchers (122) identified bacteria from soi1 using partial 16s rDNA sequencing and

showed the enrichment of several Pseudarnonas spp. which were found to be capable of

toluene mineralization. Degrange and Bardin ( 16 1 ) showed a novel method for detecting

and counting Nitrobacter populations in situ with the PCR afier designing 16s rDNA

specific primers. Counts were made using MPN and fluorescent antibody methods. A

PCR-MPN assay was ais0 designed and the counting rate reached 65 to 72% of

inoculated Nirrohacrer cells in soil. Finally. Wilson et al. ( 1 1 7) also designed 1 6s rDNA

species-specific PCR primers for the detection of hydrocarbon-utilizing bacteria in

environmental samples that were successful in detecting Pseudomonas aeruginosu.

Stentrophomonus (Xanrhomonas) rnaZtophilia. and Serratia marsescens.

5.2 Field experiment

The field experiment reported here was the first experiment designed to test the

efficiency of bioaugmentation for on-site bioremediation at CFS Alert. The treatment

system was planned to be as simple as possible with no aeration or heating systems. It

was expected that the treatment penod would be the summer (approximately 2 months) at

CFS Alert. It turned out that the station experienced low temperatures and a short

treatment season during the summer of 1999 (Fig. 4-10). Out of a total of 65 days of

treatment. 42 days were at temperatures below 0°C. This short treatment season did not

prevent biodegradation or growth of hydrocarbon-degrading populations (Fig. 4-1 1 and

Fig. 4-1 3). The design of the biopiles minimized necessary maintenance or monitoring.

Four timepoints were chosen to measure TPH concentrations and two timepoints for the

enurneration of the three most abundant phylotypes in the inoculum. The concentration of

the fertilizer added (N and P) was based on previous work done both in the field and also

in the laboratory, where a C:N:P ratio of 100:3.25:0.75 was shown to be optimal in

microcosm experiments with CFS Alert hydrocarbon-contaminated soil (61). The soil

water content was estirnated at 15.5% after testing 60 soil sarnples, and the use of the

bulking agent allowed increased porosity in the hydrocarbon-contarninated soil. It is

evident that the hydrocarbon-contaminated soi1 from CFS Alert used in this experiment

could permit extensive TPH removal and had proper physical characteristics to support

microbial degradation (Table 3-4). Effective on-site bioremediation of this soi1 matrix

with the proper concentrations of amendments is possible (Fig. 4-1 1 ).

Bioaugmentation of three biopiles using the Alert- 1 consortium did not

significantly stimulate TPH removal in the field experiment at CFS Alert. Both

inoculated and control biopiles had similar TPH removal patterns. This result raises

several hypotheses to explain why a cold-adapted hydrocarbon-degrading consortium that

was indigenous to the treatment site did not stimulate T'PH biodegradation. The most

obvious one would be that the inoculum did not survive in the biopiles afler its addition.

The Alert-1 consortium was enriched from Jet-Al FueI that has a different chemical

composition than diesel fuel (Table 1-3). Jet Fuel has a higher monocyclic aromatic

hydrocarbons composition and it is assumed that the inoculum was selected to degrade

such compounds. It may be possible that the Alert-l consortium may not be fully adapted

for biodegradation of contarninated soi1 with arctic diesel or other hydrocarbon mixtures.

It was shown with the PCR-MPN assays that the three most abundant phylotypes could

survive in these contarninated areas at CFS AIert and that their concentration was large

and was stimulated by the presence of hydrocarbons (Fig. 4-12, 4-1 6. and TabIe 4-3).

These phylotypes are assumed to be key players in TPH biodegradation at CFS Alert and

are the proof that the indigenous microflora is already adapted to biodegrade such

compounds. The TPH removal obtained after 65 days of treatment showed that the

inoculation did not stimulate TPH biodegradation, but also showed that inoculation may

not be required to achieve great extent o f hydrocarbon bioremediation at this location

(Fig. 4- 1 1 ).

The PCR-MPN assay was designed to quantify the inoculated organisms in the

inoculated biopiles versus the control uninoculated ones to test their fate and survival

(Fig. 4-12). The inoculum could be detected at the start of the experirnent as an increase

in population sizes of two phytotypes from the control to the inoculated biopiles. These

two phylotypes. Ale- 1.14 (Sphingornonas sp. ) and Ale- 1 -46 (R. eryihropolis). were

present in greater numbers in the inoculated biopiles than the control ones at the start of

the experiment. One major limitation of the DNA extraction from soil is that the required

volume of soil is only 0.5 g. and it is believed that rnicroorganisms are very

heterogenous. present in different niches in soil where both the carbon source and other

growth elements are present and bioavailable. This would mean that 0.5 g of soil may not

be representative of the entire biopile bacterial community. It is mainty for this reason

that composite. triplicate sampling was done in each pile at each tirnepoint to minimize

variability. The PCR-MPN assay was also done in triplicate for each phylotype in each

sample analyzed. Many explanations have been listed in the Introduction. section 1.4.6.

with respect to inoculation and possible reasons explaining failures to stimulate

biodegradation. Among them. the inability o f bacteria to move appreciably through soil,

the competition with the indigenous microflora, and the unsuccessful colonization of the

organisms resulting in death before biodegradation occurs seem to be the most probable

reasons. Many researchers have studied the effect o f inoculation for hydrocarbon

biodegradation in different environments. In one study, the addition of a mixture of

hydrocarbon-degrading bacteria to a marine-water microcosm did not enhance the

degradation of crude oil polluting the seawater. and the indigenous microflora degraded

the oil (162). Similarly. the addition of soil with a large population o f hydrocarbon

degraders to soil freshl y contarninated wi th hydrocarbons reduced the acc 1 imation period.

but the indigenous population soon multiplied and canied out the desired biodegradation

( 163). Another field experiment using biopiles for hydrocarbon biodegradation in the

Arctic showed stimulation of hydrocarbon biodegradation after the addition of an

indigenous inoculum (1 33). Mohn and Stewart (58) also showed stimulation of dodecane

rnineralization after inoculating Arctic soil rnicrocosrns with indigenous or non-

indigenous hydrocarbon-degrading microorganisms. Various authors reported that

inoculation had no positive. or only marginal. effects on hydrocarbon biodegradation

rates in temperate climates (1 64, 165). Also studies on experimentally ( 1 66. 167) and

chronically (1 68) hydrocarbon-contaminated cold alpine soils demonstrated that

bioaugmentation with cold-adapted biodegraders is not successful even after addition of

N and P. Inoculation resulted only in a small increase (57%) of the hydrocarbon loss in

five unfertilized aIpine subsoils. whereas bioaugmentation of fertilized soils was without

any effect in al1 investigated soils (167). Al1 investigated soils harboured enough

hydrocarbon-degrading indigenous soil microorganisms that are able to metabolize diesel

oil at low temperature more effectively than introduced cold-adapted hydrocarbon-

degrading rnicroorganisms. The authors assumed that the inocula might have been

replaced by the indigenous biodegraders with tirne.

It was s h o w in this study through the use of the PCR-MPN assay that the three

most abundant phylotypes present in the Alert-1 inoculurn are also present in high

numbers in CFS Alert hydrocarbon-contaminated soil (Fig. 4- 12, 4- 16, and Table 4-3).

This suggests that the indigenous microflora is already capable of hydrocarbon

biodegradation and that the inoculum might have been redundant to the indigenous

hydrocarbon biodegraders. This could explain results presented in Fig. 4-1 3 where there

are no major differences in strain numbers in both control and inoculated treatments afier

65 days of treatment.

The inoculum used for biopiles dunng the field experiment oiiginated from the

Alert-1 enrichment culture that was itself incubated with hydrocarbon-contarninated soil

collected at the upper POL site at CFS Alert. The soil used in the field experiment came

from the new spiII area also at CFS Alert. It seems that both sites contained similar

hydrocarbon-degrading cornmunities because the most abundant organisms in the

enrichment culture were also present in high numbers in both hydrocarbon-contaminated

soils at CFS Alert. Other hydrocarbon-contaminated areas at CFS Alert treated by

biostimulation (i.e. not inoculated) were tested to see if they contained the three most

abundant phylotypes in the Alert-1 enrichment culture (TabIe 4-3). In two samples tested

(from the diesel day tank and the l a n d f m i n g treatment plots). (4). Ale-1.6. Ale-1.14.

and Ale-1.46 phylotypes were detected by the PCR assays. This result sustains the

evidence that the three clones are indigenous to hydrocarbon-contarninated areas at CFS

Alert that they may be involved in hydrocarbon catabolism. Ten pristine sarnples remote

fi-om the station and surrounding roads were also sampled to measure TPH levels and

phylotype populations in non-contaminated areas. Three sarnples were tested for TPH

and they al1 had no detectable TPH. With respect to the three phylotypes. only Ale-1.14

(Sphingomonas sp.) was detected at low density in seven samples and was enumerated at

approximately 190 copies per g of dry soi1 in two samples (Table 4-2). This number is a

small fraction of Ale- 1.14 populations in CFS Alert hydrocarbon-contaminated soil, even

without inoculation with the Alert-1 enrichment culture. This result means that Ale-1.14

is present at detectable levels in non-hydrocarbon-contaminated soi1 but is enriched in the

presence of petroleurn hydrocarbons. The detection of Ale- 1.14 in nearby pnstine

locations was consistent with similar levels of Aie-1.14 found in the sarnples taken to test

the spreading capability of the inoculum (Table 4-2 and 4-3). In sarnples UBC-99-106

(20 m East. before the experiment) and UBC-99-176 (20 m East. after 65 days). Ale-1.14

showed an increase from approximately 190 copies to 370 copies per g of dry soil.

Nevertheless. this result does not indicate spreading of the inoculum. because Ale- 1.14

was present in low numbers in many of sarnples tested. The increase in the latter example

is small and most likely due to random variation.

TPH removal in the field experiment is likely to be due to microbial catabolism

rather than the combined effects of abiotic factors. This is based on the growth of the

three most abundant phylotypes during the field experiment. These phylotypes showed

increases by almost two orders of magnitude between O and 65 days of treatment (Fig. 4-

12). This result suggests that the hydrocarbon-degrading bacteria present in soil were

enriched during the experiment and supports the assumption that TPH removal was the

effect of microbial activity.

5.3 Laboratory experiment

The microcosm experiment was planned and implemented to verify results from

the field experiment at CFS Alert during the summer of 1999. Questions related to

bioaugmentation were still unsolved and more experiments were needed in order to

explain fully what could have happened in the field expcnment. One of the hypotheses

explaining the failure of the inoculation process to stimulate TPH biodegradation was that

the density of the inoculum used in the field experiment was too low. This hypothesis

was tested in the microcosrn experiment by using two different densities of inoculum: 106

and lo9 cells per g of dry soil.

Conditions in the microcosm experiment were designed to mimic those in the

field experiment. The incubation temperature of the microcosms was 7°C which was in

sarne range of temperature as the field experiment at CFS Alert. The same amendments

were added at the same concentrations in the rnicrocosm and field experiments and the

inoculum came from the same enrichment culture (lyophilized cells). The soi1 used for

the microcosm experiment was also the same hydrocarbon-contaminated soil used in the

field experiment but with a slightly lower TPH concentration. The major difference

between both experiments was the physical environment where the experiments were

conducted. The field experiment was built and the treatment took place in an open

environment where the wind. Sun. and meteorological conditions could have had effects

on the results reported. The microcosm experiment was done in capped-bottles in an

incubator where no volatilization or photo-oxidation could have taken place. The abiotic

factors in the field experiment should be considered as more important than the

laboratory experiment. Another difference between both experiments is based on soil

preparation before building the biopiles. In the field experiment. the soil was brought

from different locations in the new spi11 area and was mixed in a mobile concrete mixer

for at least 20 minutes per pile allowing good homogeneity between the soi1 and the

amendments. The microcosm soi1 came from the same location and was manually seived

with a ?-mm seive to remove rocks and large soil particles. With respect to sarnpling. in

the microcosm experiment only one sample was taken at each timepoint per replicate

treatment. and there were eleven timepoints. compared to four in the field experiment.

Phylotype populations in the field experiment were assessed at two timepoints. The total

treatment Iength of the field experiment was 65 days compared to 93 days in the

Iaboratory experiment.

The overall result of the microcosrn experiment did correspond to the one from

the field experiment at CFS Alert. Basically. the two different densities of inoculurn did

not stimulate TPH biodegradation in the hydrocarbon-contaminated soil. There was no

statistical difference in hydrocarbon removal in the three treatrnents: control

uninoculated. inoculated with 106 cells per g of dry mil. and inoculated with 109 cells per

g of dry soil (Fig. 4-14). The sterile control did show a slight decrease in TPH. which

may have been due to volatilization during microcosm sarnpling. Even the population

dynamics of the inoculated strains in microcosms did follow the same trend as in the field

experiment. The inoculum could be detected at the first timepoint by the PCR-MPN

assay. 4 days in the microcosm experiment, O days in the field experiment, in the

inoculated biopiles versus the control uninoculated ones (as the Ale- 1.14 and Ale- 1 -46

phylotypes). At the second timepoint. 29 days in the microcosm expenment, 65 days in

the field experiment. the populations of phylotypes in both treatments were similar with

no significant diffierences between populations in inoculated and uninoculated treatments.

There was a difference in phylotypes enurneration between the field and the

laboratory experiments. The initial populations (for the three phylotypes) were ten times

higher in the laboratory experiments than in the field experiments in the timepoints tested

by the PCR-MPN assays (Fig. 4-12 and 4-16). This result was expected because the

microcosrns were inoculated with a density of 1 o9 cells per g of dry soi1 compared to 10'

cells per g of dry soil in the biopiles. This difference in the inoculum densities that was

used in both experiments was detected by the PCR-MPN assays.

Some inconsistencies in the results from the PCR-MPN assay must be explained

to fully understand the limitations o f this method. The PCR-MPN standardization assay

was done by using the phylotype-specific primers designed for the three most abundant

phylotypes in the Alert-1 enrichment culture. An experiment was designed to test the

sensitivity of the assay by measuring the amount o f DNA copies required to yield a

positive signal (PCR product) for each clone studied (Ale-1.6. Aie-1.14. and Ale-1.46)

but not for the total bacteria1 community. The results showed that Ale-1.6 could be

detected with 60 copies of DNA per pl. Ale-1.14 could be detected with 500 copies per

pl. and Ale-1.46 with 700 copies per pl (Fig. 3-2). The PCR method should in theory

yield a product with a single copy of DNA (or a single positive cell in an environmental

sarnple). These results are indicative of a high detection limit by the assay especially for

Ale- 1.14 and Ale-1.46. This would mean that the MPN numbers in Fig. 4-9.4- 12. and 4-

16 could be lower than the actual populations of phylotypes in the samples tested for Ale-

1.14 and Ale- 1.46. The DNA quantification method (of pIasmid DNA), that was done

prior to the standardization assay, could also contribute to a high detection limit by not

accurately measuring the concentration of nucleic acids before doing the assay. An

overestimation of copy numbers for the three clones (Ale-1.6. Ale-1.14. and Ale-1.46)

would increase the detection limit calculated by the assay for each phylotype. The DN.4

extracted from soil may present a different detection limit for the three most abundant

phylotypes than the plasmid DNA of each clone because o f the presence of organic

matter and PCR inhibitors in soii.

The total culturable heterotrophs and hydrocarbon degraders also had a significant

increase in population numbers in the MPN-growth assay done for the laboratory

experiment at two different timepoints (4 and 29 days of incubation at 7°C). The increase

in the microcosms of hydrocarbon degraders was greater than that of total culturable

heterotrophs (Fig. 4-17 and Fig. 4-18). In these figures. the control uninoculated

microcosm had a very large increase of total culturable heteretrophs and also

hydrocarbon degraders compared to the other two treatments. This result was also higher

than the bacterial popuIations measured by the PCR-MPN assay. The most obvious

hypothesis to explain this result is found by looking at the serial dilution method. It is

possible that a mass of cells aggregated together could have been transferred in the ten-

foId dilution process and would yield in higher MPNs. The MPN numbers as seen in Fig.

4-1 7 and 4-1 8 for the control microcosms appear too high to be accurate. The sarne

dilution tubes were used in both MPN-growth assays. this explains the very high values

for total culturabte heterotrophs and hydrocarbon degraders in both MPNs. The increase

in culturable heterotrophs (x 10'). (Fig. 4-1 7). is also not consistent with the unchanged

bacterial MPN seen in Fig. 4-16. The PCR-MPN assays should be more reliable than

growth-based methods because they rely on the presence of target DNA instead of

culturing soi[ organisms. One reason to explain the above result may be related to the

extraction yield of the method used to extract DNA from soi1 samples. The Bio-1 O1 kit

uses a DNA binding matrix to bind the DNA afier ce11 lysis. This may become a limiting

factor if the matnx gets saturated and if remaining nucleic acids are being flushed (see

section 3.7 in Materials and Methods) and not recovered. This could explain why the

bacterial MPN remain unchanged in both enurneration done on the enrichment culture

and also the laboratory experiment (Fig. 4-9. 4- 16). The culturable hydrocarbon-

degraders population showed an increase. as a fraction of total culturable heterotrophs. in

the inoculated treatments between 4 and 29 days of incubation (Fig. 4-1 7 and 4- 1 8). This

result may represent the inoculated organisms that were added to these microcosms at

different densities (1 o6 and 1 o9 cellslg of dry soil). This trend was not present in the

control uninoculated treatment and reinforced the hypothesis that the increase was due to

the inoculated organisms. This enrichment of hydrocarbon degraders is also correlated to

TPH removal in the microcosms during this period reinforcing the fact that the removal is

due to microbial degradation.

The MPN method has also disadvantages that are relevant to mention here to

explain the above results. The MPN is a single estimated number while the true number

(95% confidence lirnit) may show extreme variation from the MPN (169). The cell

extraction method used (by vortexing the soil samples in the saline buffer solution) may

not extract the entire bacterial population and thus not be entirely representative of the

microbial community in the soil sarnples analyzed.

5.4 Statistical evaluation of the field and the microcosrn experiments

Both the field and the microcosm experiments were set up to determine the effects

of inoculation on TPH biodegradation. In the field experiment, only two treatments were

tested having a triplicate set-up of control uninoculated biopiles and a triplicate set-up of

inoculated biopiles. Each biopile was sampled four times during the treatment period by

taking triplicate composite samples per pile per timepoint. This sarnpling method was

done in order to reduce the statistical variability among samples with respect to TPH

concentration in soil. In the microcosm experiment. only one sarnple was taken at each

timepoint from the triplicate treatments. This was decided because of the smaller volume

of soil treated in the microcosms. In order to measure the statistical confidence between

triplicate samples and also between different treatments. an analysis of variance

(ANOVA) has been done for both the field and the microcosm experiments.

The main conclusions that emerged from this statistical analysis are that the field

experiment showed greater variations among treatments than the microcosm experiment.

Appendix 3 shows the results of the ANOVA for both experiments. With respect to the

field experiment. the first analysis compared the triplicate biopiles together at each of the

four tirnepoints to see if there was any statistical variations within each of three replicate

biopiles of either the control uninoculated or inoculated treatment. The two hypotheses

tested were ( i ) Ho: TPH concentration does not differ among triplicate biopiles and

treatrnents. and (ii) H.,: TPH concentration does differ among triplicate biopiles and

treatments. If the F ratio obtained is at least as large as the F critical value. than Ho is

rejected and there is statistical difference between triplicate biopiles or treatments. This

was the case for al1 the triplicate biopiles except two: inoculated biopiles at 14 and 28

days. All the other triplicate set-ups showed statistical differences among triplicate

biopiles in the field experiment. The second analysis done was to compare the treatments

together to see if there was variance between the control uninoculated and the inoculated

treatrnents at each specific timepoint. Results showed that there was not variance in TPH

concentration between the two groups confirming the field results on TPH biodegradation

between the two treatments (Fig- 4- 1 1 ).

The ANOVA was also done for the microcosm experiment. In this case. no

analysis of variance was done to compare triplicate set-ups because only one sample per

set-up per tirnepoint was taken. Thus. only treatments were compared together in order to

detect any variance in TPH concentration between the control uninoculated treatment, the

inoculated treatment with 1 o6 cells per g of dry soil. and the inoculated treatment with 109

cells per g of dry soil. During the experiment. eleven sarnpIing times were set and among

them. only the one done at 22 days showed variance in TPH concentration between al1

three treatments. The other 10 timepoints resulted in no variance between the three

treatments confirming again the overall TPH biodegradation profile in the microcosrn

experiment (Fig. 4- 1 3).

Many reasons and hypotheses c m be responsible for such results in the field

experiment. The major ones being the abiotic factors coupled to variable TPH gradients

in the hydrocarbon-contaminated soil used to build the field experiment biopiles. Each

pile showed almost no variance when triplicate sampling was done and TPH

concentration measured but variance between the triplicate biopiles. This can be caused

by digging soil frorn the contaminated area where variations in TPH concentrations can

be spatially and geographically different depending of the depth and specific location of

sampling. A front-end loader was used to dig the soil from the contarninated area and this

soil was then used to build biopiles one per one with soil coming fiom different locations

in this contaminated area. When the desired volume of soil to build one pile was

acquired, the amendments were added and the soil was mixed thoroughly in a mobile

concrete mixer for at least 20 minutes. This is the most plausible cause of variations

between triplicate set-up and no variation within the same biopile.

The microcosm experiment did not show any variation between treatrnents except

one tirnepoint (22 days). The main reason to explain this result is related to the soil used

to build the microcosms. The same hydrocarbon-contaminated soi1 that was used for the

field experiment was shipped to UBC and was kept Frozen before unthawing it and

seiving through a 2-mm seive. The soil used in al1 treatments originated from the sarne

contaminated soil that was mixed thoroughly together before adding 80 g per

microcosms. This is the reason why the analysis of variance did not show any statistical

variations arnongst treatments.

Another reason to consider in order to explain the ANOVA results in both the

field and the microcosm experiments is the efficiency of the inoculum added in different

densities to the inoculated treatments. There are no evidence that bioaugmentation made

any statistical difference on TPH biodegradation as shown in Fig. 4-1 1 and 4-13. The

analysis of variance on the two experiments was helpful in confinning the results of both

the field and the microcosm experiments.

5.5 CEPA notification of new substances

A goal of this project was to provide a tool facilitating the writing of the CEPA

notification of new substances f o m that is required for any field experiment involving

the use of microorganisms. Many of these requirements are listed in the Introduction,

Section 1.8, and are related to the composition and the properties of the consortium used

in the field experiment. The majority of the information requested by CEPA was

impossible to answer originally because the consortium used in the field experiment was

not characterized and its composition was still unknown. Most information required in

the CEPA form with respect to the utilization of an inoculum in a field experiment

requires the use of new technologies in rnolecular biology that were not available in the

past.

This project was successtùl in identifying the most abundant strains in the

consortium through 16s rDNA phylogenetic association. This identification is essential

for answering questions about strain history and description of the biological and

ecological characteristics of the microorganisms introduced in the field experiment. Some

of these questions were related to the infectivity. pathogenecity to non-human species.

toxicity. and toxigenicity of the inoculated rnicroorganisms. The 16s rDNA identification

of the most abundant phylotypes in the Alert-1 enrichment culture showed no pathogens

present in the inoculum used at CFS Alert for the field experiment. The design of the

strain-specific PCR primers for the three most abundant strains was also successful in

describing a method requested by CEPA that could be used to distinguish and the detect

the microorganisms inoculated. The inoculated organimsm could be detected in early

tirnepoints in both the field and the laboratory experiments. The PCR-MPN assay

designed for strain enumeration was also helpful in answering many questions in the

notification with respect to mechanism o f dispersal of the inoculum and aiso the survival

and growth of the introduced consortium- The three phylotypes monitored did not spread

from the experimentai site as determined by the assay. The PCR-MPN assay was also

helpfûl in answering details in Section 5, Part B, of the CEPA form about the

environmental fate of the inoculum such as the estimated quantities of the

microorganisms in soi1 and methods determining the fate of the introduced organisms in

the experiment. It was shown that the inoculated organisms were gradually replaced by

the indigenous microflora and that they were not disrupting the microbial communities

already present in CFS Alert soil.

6. CONCLUSIONS

This thesis studied the effect of inoculation on TPH biodegradation for on-site

bioremediation at CFS Alert. Both a field and a laboratory experiment showed that

inoculation did not stimulate TPH biodegradation in hydrocarbon-contaminated soils

from CFS Alert. Population dynarnics of hydrocarbon-degrading strains present in the

inoculum was also investigated to test the growth, fate. and sumival or inoculated

organisms. Both experiments presented similar results by measuring an increase in

populations of two phylotypes in early timepoints and showing no difference in

population numbers in control uninoculated treatments versus inoculated treatments at

later timepoints. The three most abundant strains in the inoculum were already present in

large numbers in hydrocarbon-contaminated soils at CFS Alert and onIy one strain was

detectabte at low density in pristine sarnples. This strâin. Ale-1 -14. did not spread to

nearby locations in the field experiment after 65 days o f treatment.

This project was successful in answering information required by CEPA for the

use of microorganisms in a field experiment and also by characterizing a hydrocarbon-

degrading consortium with the use of molecular tools. Species-specific detection o f three

hydrocarbon-degrading strains present in the inoculum allowed the monitoring of

inoculated strains during the experiment. The findings of this thesis improved Our

understanding of microbial biodegradation in the Arctic and will be helpful for future

design of large-scale applications for the remediation of hydrocarbon-contarninated soil.

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8. APPENDICES

APPENDIX A

1. GenBank submission data for Ale-1.6

LOCUS AF230874 1 0 0 9 bp DNA BCT 27-APR-2000 DEFINITION Psrudomonas synxantha 16s ribosomal RNA gene, partial sequence. ACCESSION AF230874 VERSION A F 2 3 0 8 7 4 . 1 G I : 7 6 5 0 3 8 4 KEYWORDS SOURCE Pseudomonas synxantha. ORGANISM Pseudornonas synxantha

Bacteria; Proteobacteria; gamma subaivision; Pseudomonâs group; Pseudomonas. REFERENCZ 1 (bases I to 1 0 0 9 ) AUTHORS Thornassin-Lacroix, E . J. M. and Mohn, W.W. TITLE 16s r R N A partial sequence of environmental clone isolated from hydrocarbon-contarninated Arc~ic soil JOURNAL Unpublished REFERUNCE 2 (bases 1 to 1 0 0 9 ) AUTHORS Thornassin-Lacroix,Z.J.M. and Mohn,W.W. TITLE Direct Subrnission JOURNAL Submitted (03-FEB-2000) Microbiology and Immunology, University of British Columbia, No. 300-6174 University Boulvard, Vancouver, BC V6T 123, Canada FEATURES Locat Fon/QualiG' L l e r ~ Source 1.. 1009

/organism="Pseudomonas synxantha" /db-xref="taxon: 4 7 8 8 3 " /note="isolated from Arctic soil"

r RNA <1. . > I O 0 9 /product="16S ribosomal RNA"

BASE CC)UNT 2 5 2 a 2 3 1 c 318 g 208 t ORIGIN

jcccttcaqc agccgcggtà gagcgcgcgt aggtggttcg gcactcaaaa ctgtcgagct qaaatgcgta gatataqqaa acactqaggt gcgaaaqcgt taaacqatgt caactagccg aqttgaccqc ctgggqagta gcacaaqcgg tggagcatgt gacatccaat gaactttcca gcatqqctgt cgtcagctcg ccttgtcctt agttaccaqc ccggaggaag gtgggqatqa tgctacaatg gtcggtacag cgatcgtagt ccqgatcgca

ztacagaqgg ttaagttqga aqagtatggt ggaacaccag gggqaqcaaa ttggqagcct cggccgcaag ggtttaattc gagatggatg tgtcgtgaga acgtaatggt cgtcaagtca aqggttgcca gtctgcaact

tgcaaqcqtt aatcggaatt tgtgaaatcc ccgggctcaa agaggqtgqt ggaattccct tggcqaaggc gaccacctgg caggattaga taccctggta tgagctctta gtggcgcaqc gttaaaactc aaatgaattg gaagcaacgc gaagaacctt ggtgccttcg ggaacattqa tgttgqgtta agtcccgtaa qggcactcta aggagactgc tcatggccct tacggcctgg aqccgcgaqg tggagctaat cgactgcgtg aagtcqgaat

actqggcgta cctgggaact gtgtaqcwt actgatactg gt ccacgccg taacgcatta acgqgggccc accaggcctt gacaggtgct cgagcgcaac cqgtgacaaa gctacacacg cccagaaaac cgctagtaat

841 cgcgaatcaq aatgtcgcgq tgaatacgtt cccgggcctt gtacacaccq cccgtcacac 901 catgggâgtg ggttgcacca gaaqtagcta gtctaacctt cgggaggacq gttaccacgg 961 tgtgattcat gactggggtg aaqtcqtaac aaggtagccg taaaqggcg / /

2. GenBank submission data for Ale-1.14

LOCUS AF230875 1011 bp DNA BCT 27-APR-2000 DEFINITION Sphingomonas sp. BN6 1 6 s ribosomal RNA gene, partis1 sequence . ACCESSION AF230875 VERSION AF230875.1 GI: 7 6 5 0 3 0 5 KEYWORDS SOURCE Sphinqomonas sp. BN6. ORGANISM Sphingornonas sp. BN6; Bacteria; Proteobâcteria; alpha subdivision; Sphingomonas group; Sphingomonas. REFERENCE 1 [bases 1 to 1011) AUTHORS Thomassin-Lacroix, E. J.M. and Mohn, W. W. TITLE 16s rRNA partial sequence of environmental clone isolated £rom hydrocarbon-contaminated Arctic soi1 JOURNAL Unpublished REFERENCE 2 (bases 1 to 1011) AUTHORS Thomassin-Lacroix, E. J . N . and Mohn, W. W. TITLE Direct Submission JOURNAL Submitted (03-FEB-2000) Microbioloqy and Imrnunology, University of British Columbia, No. 300-6174 University Boulvard, Vancouver, BC V6T 123, Canada FEATURES Location/Quaiifiers Source 1.. 1011

/organism="Spningomonas sp. BN6" /strain="BNGW /db-xref="taxon:l21428" /note="isolated from Arctic soii"

r RNA <1.. >IO11 /pr~duct="16S ribosomal RNA"

BASE COUNT 244 a 235 c 319 g 213 t ORIGIN 1 gcccttcaqc agccgcggta atacggaggg agctagcgtt gttcggaatt actgggcgta 61 aagcgcacgt aggcggcqat ttaagtcaga gqtgaaagcc cgqggctcaa ccccggaact 121 gcctttjaga ctgqattgcE âgaatcttgg agagqcgagr ggaattccqâ gtgîagaqgt 181 gaaattcgta gatattcgga agaacaccag tggcgaaqgc ggctcqctgq acaagtattg 241 acqctgaqgt gcgaaagcgt ggggagcaaa caggattaga taccctggta gtccacgccg 301 taaacgatgd taactagctg ctggggcaca tqgtqtttcg gtggcgcagc taacqcatta 361 aqttatccgc ctggggagta cgqtcgcaag attaaaactc aaagqaattg acgggggcct 421 gcacaagcgq tqgaqcatgt qqtttaattc gaagcaacgc gcaqaacctt accagcgttt 4 8 1 gacatcctca tcgcggattt cagaqatgat trccttcagt tcggctggat gagtqacagq 541 tgctgcatqg ctqtcgtcag ctcgtgtcgt gagatgttgg gttaagtccc gcaacgagcg 601 caaccctcgc ctttagttgc cagcattaag ttgggtactc taaaggaacc gccqgtgata 6 6 1 agccgqagqa aggtggggat gacgtcaagt cctcatggcc cttacgcgct gqgctacaca 721 cqtgctacaa tqgcgactac agtgqgctqc aaccgtgcqa qcggtagcta atctccaaaa 781 gtcqtctcaq ttcggattgt tctctgcaac tcqagaqcat gaaggcggaa cgctagtaa 8 4 1 tcgcgqatca gcatqccgcg gtgaatacgt tcccaggcct tgtacacacc gcccgtcaca 901 ccatgqgatt tggattcacc cgaaggcact gcgctaaccc gcaagggagg cagqtqacca 961 cqgtgqgttt agagactggq gtgaagtcgt aacaaggtag ccgtaaaggg c / /

3. GenBank submission data for Ale-1.46

LOCUS AF230876 1 0 1 1 bp CNA BCT 27-APR-2000 D E F I N I T I O N Rhodococcus erythropolis 16s ribosomal RNA gene, pzrtial sequence. ACCESSION AF230876 VERS I O N AF230876.1 GI :7650386 KCYWORDS SOURCE Rhodococcus erythropolis . ORGANISM Rhodococcus erythropolis; Bacteria; Firmicutes; Actinobacteria; Actinobacteridae; Actinomycetales; Corynebscterineae; Nocardiaceae; Rhodococcus. REFERENCE 1 (bases 1 to 1011) AUTHORS Thomassiri-Lacroix, E. J.M. and Mohn, W.W. T I T L E 16s :RNA partial sequence of environmental clone isolated f rom nydrocarbon-contaminated Arctic s ~ i l JOURNAL Unpublished REFERENCE 2 (bâses 1 c o 1011) >.UTHORS Thornassin-Lacroix, E . J.M. and Mohn, W. W. TITLE Direct Submission JOURNAL S~tbmitted (03-FE9-2000) Microbiology and Immunology, University of British Columbia, No- 300-6174 University Boulvard, Vancouver, BC V6T 123, Canada FEATURES source

r RNA

BASE COUNT ORIGIN

gcccttcaqc àaqagt tcgt qcaggcgata qaââtgcgca acgctgagga taaacqqtgq aaqcgccccg cgcacaaqcg tgacatatac catggctgtc cctatcttat

gqtctcaqtt gcagatcagc catgaaagtc

Location/Quaiifiers 1 . . 1011 /orqanism="Rhodococcus erythropolis" /db-xref=lltaxon: 1 8 3 3 " /note="isolatea from Arctic soil" cl.. > i 0 1 1 /product="lGS ribosomzl RNA"

a 245 c 334 g 202 t

agccgcgqta aggcgqtttg cgggcagact gatatcagga acqaaagcqt gcgctaggtg cctqggoaqt qcggagcatg cggaaagct g gtcagctcgt gttgccaqcâ tgqggacgac ccagtacaqa cggatcgggg aacgctgcgg ggtaacaccc

atacgtaqqg tcgcgtcgtt tgaqtactqc ggaacaccqg 99qtagcgaa tgggttcctt acqgccgcaa tqqattaatt cagagatgtq qtcgtgagat cgttatggtg gtcaaqtcat qqgctgcgao tctgcaactc tgaatacgtt gaagccggtq acgaagtcgt

tgcaagcgtt tgtgaâaacc aggggaqact cggc5Taaggc caggattaga ccacggaa tc gqctaaaact cga tgcaacg gccccccttg gttgggttaa gqgactcgta catqcccctt accgtgaggt qaccccgtga cccgggcctt gcttaacccc aacaagqtaq

gtccggaatt agcagctcaa ggaattcctg

ggg=ctctgg taccctggta cqtgccqtag caaaggaatt cqaagaacct tggtcggtat gtcccgcaac aqagactgcc atgtccaggq ggagcgaatc agtcggaqtc qtacacaccg ttgtggga99 ccgt aaaqgg

actqqgcgta ctgctggctt gtgtaqcggt gcaqtsactg qtccacqccg ctaacgcatt qacqqgggcc tacctqggtt acaqqtggtg gagcqcaacc ggqqtcaact cttcacacat ccttaaagct gctagtaatc cccgtcacgt gagccgtcga C

C C C m m a ? ? ? W C O W F Y Y . - L A &

P W W O ( D 0 3

C C C c c clc c c

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PPP

I P P 3 3 3 E 0 0 (O iD (D

P P P 0 0 0 0 0 - N o 0 ) o o c o

P P P O O O O 0 0 P N N ! A 0

C C C C m m a I n ? O?? w w w c D * FF'?

- - - - - - 3 2 1 3 3 3 3 0 0 0 0 0 0 0 0 0 0 0 0

G L S G E E % O % % % % m ( D m ( D ( D ( D a a a a a a T

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096 528 105 558 219 494 181 582 Control#l Control#2 lnoculated #1 lnoculated #2 Control#3 Inoculated #3

Pristine samples Pristine samples Pristine sarnples Pristine samples

Sept 19 - 65 days 65 days 65 days 65 days 65 days 65 days

1. Anova: Single factor analysis for the field experiment with respect to TPH values (a = 0.05)

1 . Control biopiles at O davs

SUMMARY

Groirps Count Su m Average Variance

ANOVA

Source of C.'uria[ion SS 4 MS F P-vulue f cri[ Between Groups 1 7 13669 - 3 856334.3 6.875028 0.028038 5.143249 Within Groups 747343.3 6 124557.2

Total 24600 12 8

2. Control biopiles at 14 days

SUMMARY

Gro trps Cozrnt Strm Average Vuriance I # I 3 79 18 2639.333 49477.33

Source of Variation SS 4 hfS F P-vulire F cri[ Between Groups 322350.9 - 3 16 1 175.4 5.457654 0.044629 5.143249 Within Groups 177192 6 29532

Total 499542.9 8

3. Control bio~iies at 28 davs

SUMMARY

ANOVA

Source O/ Furiarion SS 4f- hIS F P-value F crir Between Groups 607544 - 3 303772 10.75578 0-0 10373 5.143249 Within Groups 169456 6 28242.67

Total 777000 8

4. Inoculated bio~iles at O davs

SUMMARY

Grozips Cozinr S~rm Average Fariance I # 1 3 38 15 127 1.667 1 1 105.33 1#2 3 3420 I 140 8029 I#3 3 332 l 1 107 31861

ANOVA

Sorrrce of l~ariarion SS 4 I LlS F P-valire F crif

Between Groups 45540.22 2 22770.1 1 1.33954 I 0.330394 5.143249 Within Groups I O 1990.7 6 16998.44

5. inocula ted biopiles at 14 davs

SUMMARY Cru tips Cotrnr Strm A verage Variance Ct l 3 2988 996 282 1

ANOVA Sorrrce of Variarion SS df MS F P-vulire F crit Between Groups 1723 147 2 86 1573.4 8.664274 0.0 1 70 13 5.143249 Within Groups 59663 8.7 6 99439.78

Total 23 19786 8

6. lnoculated biopiles at 28 davs

SUMMARY Groups Counr Sum Average Variance I # 1 3 4805 160 1.667 7074.333

ANOVA Sotrrce of Furia f ion SS d f MS F P-val tre F crit

Between Groups 62332.67 - 3 3 l 166.33 1.044207 0.408 19 1 5.143249 Within Groups 17908 1 -3 6 29846.89

Total 241414 8

7. ControVInoculated b i o ~ i l e s at O davs

SUMMARY - - . -- - -

Gto zrps Cotrnf Sttm Average Variance

control 9 27309 3034.333 30750 1 -5 inoculated 9 25397 282 1.889 62442.86

ANOVA Source of Variation SS df MS F P-value F crir Between Groups 303096.9 I 203096.9 1 .O97986 0.3 1 028 4.493998 Within Groups 2959555 16 184972.2

Total 3 162652 17

8. ControVI noculated b i o ~ i l e s at 14 davs

SUMMARY Gr0 trps Count Sum .4 veruge Variance

control 9 14533 16 14.778 289973.2 inoculated 9 14370 1596.667 301 76.75

ANOVA Sorrrce of b ariarion SS d f ICfS F P-valtre F crit

Between Groups 1476.056 I 1476.056 0.00922 1 0.924692 4,493998 Within Groups 256 1200 16 160075

Total 2562676 17

9. ControYInoculated biopiles at 28 davs

SUMMARY

control 9 97 17 1079.667 97 125 inoculated 9 1 0556 1 172.889 1844 1.36

ANOVA Sotrrce of t .uriar ion SS (if hfS F P-value F cri[ Between Groups 39 106.72 I 39 106.72 0.676784 0.422788 4.493998 Within Groups 924530.9 16 57783.1 O

Total 963637.6 17

1 O. - ControVlnoculated biopiles at 65 davs

SUMMARY Grozips Corrnt Surir A verugr C.irriunce Control 3 1478 492.6667 20505.33 lnoculated 3 2206 735.3333 10080.33

ANOVA Sorrrce of kriat ion SS df MS F P-value F cri[ Between Groups 88330.67 I 88330.67 5.775952 0.074089 7.70865 Within Groups 61 171.33 4 1 5292.83

Total 149502 5

2. Anova: Single factor analysis for the laboratory experiment with respect to TPH values (a = 0.05)

1 . M icrocosms at O days

SUMMARY

Grozrps Corinf Sztm Average Variance Control 3 72 10.9 17 2403.639 98 I .9254 1 0A6 3 7056.278 2352.093 17933.96 1 0A9 3 7000.565 2333.522 24 10.724

ANOVA

Source of kriation SS dS MS F P-value F crit Between Groups 79 18.347 2 3959. 1 74 0.556934 0.599979 5.143249 Within Groups 42653.23 6 7 108.87 1

Total 5057 1.57 8

2. Microcosms at 4 davs

SUMMARY

Groups Corrnt Srtm .-1 verage Variance Control 3 7 170.5 13 2390.1 7 1 10065.8 1

ANOVA

Sorrrce of b'ariation SS df MS F P-valne F cri! -

Between Croups 6869.742 - 7 3434.87 1 0.7 18978 0.52492 5.143249 Within Groups 28664.6 1 6 4777.435

Total 35534.35 8

3. Microcosms at 8 davs

SUMMARY

Grorrps Corrnt Sztm ,-î verage Variance Control 1 0A6 1 0A9

ANOVA

Source of C.arintion SS df MS F P-value F cri! Setween Groups 169 12.06 2 8456.032 2.00 144 1 0.2 158 13 5.143249 Within Croups 25349.83 6 4224,972

Total 4236 1 -9 8

4. Microcosms at 1 1 davs

SUMMARY

Grorrps Coztnt Swn Average tariance Control 3 6 149.038 2048.346 8 133.478 1 0A6 3 5833.6 12 1944.537 12354.82 1 0A9 3 59 10.894 1970.298 6669.663

ANOVA

Source of Variation SS @ MS F P-valire F crit Between Croups 1753 1.3 2 8765.652 0.968296 0.432067 5.143249 Within Groups 543 15.93 6 9052.655

5. Microcosms at 15 davs

SUMMARY

Total 7 1847.23 8

Groups Cortnf Srrm .-î verage hriance Control 3 5290.101 1763.367 5577.757

ANOVA

Source of l~uriution SS dî hfS F P-value F crit Between Groups 34 106.73 - 3 17053.36 2.162349 O. 196255 5.143249 Within Groups 473 18.99 6 7886.498

Total 8 1425.72 8

6. Microcosms at 22 davs

SUMMARY

Groltps Coirnt Sum Average Variance Control 3 45 16-64 1 1505.547 639.9 17

ANOVA Soitrce of f. uriution SS df hfS F P-value F cri! Between Groups 20786.3 1 - 9 10393.1 1 10.40598 0.0 1 1206 5.143249 Within Groups 5992.58 6 998.7633

Total 36778.79 8

7. Microcosms at 29 davs

SUMMARY

Grortps Count Sum A verage Variance Control 3 3895.676 1 398.559 2352.237

ANOVA

Source of Variation SS d f MS F P-value F cri[ Between Groups 14247.3 3 2 71 23.666 1.126032 0.384385 5.143249 Within Groups 37958.07 6 6326.345

8. Microcosms at 36 davs

Total 52205.4 8

SUMMARY

Croups Colin[ Szim .4 wrage Variance

Control 3 3545.223 1 18 1.74 1 17786.9 1 1 0A6 3 3895.7 1.1 1298.57 1 160 12.82 1 0A9 3 3787.708 1262.569 5487.045

ANOVA

So~trce O)/' Varia lion SS df M S F P-value F cric

Between Groups 2 1378.6 1 - 3 10739.3 1 0.82007 0.484339 5.143249 Within Groups 78573.56 6 1 3095.59

Total 1 00052.3 8

9. Microcosrns at 50 davs

SUMMARY

Croups Corrnt Sum Average Variance

Control 3 2849.825 949.94 18 1030 1.38 1 0A6 3 2953.853 984.6 176 40362.3 1 1 O"9 3 3976.085 992.0283 44837.82

ANOVA

Source of Curiurion SS df hfS F P-value F cri1

Between Groups 3028.603 - 3 1 5 14.302 0.047569 0.95390 1 5.143249 Within Groups 191003 6 3 1833.84

Total 19403 1 -6 8

10. Microcosrns at 65 davs

SUMMARY

Croups Cortnt Sitm Average Variance

Control 3 2288.779 762.9262 10680.25 1 0A6 3 2434.498 8 I 1.4993 44 1 1 1 1 0A9 3 2490.732 830.244 1 86 1 1.126

ANOVA

Source of Variation SS 4- MS F P- value F cri!

Between Groups 7242.4 13 2 362 1 207 O. 17 1344 0.8465 13 5.143249 Within Groups 126804.7 6 21 134.12

Total 134047.2 8

1 1. Microcosms at 92 davs

SUMMARY

Grozips Cozrnf Sum cl veruge Variance Control 3 2067.828 689.276 12802.76 10A6 3 22 15-20? 738.4008 35777.86 1 0A9 3 2066.508 688.836 13287.87

ANOVA

Sorrrce of 2.ariufion SS d f IMS F P-vulue F crit Between Groups 4870.103 2 2435.05 1 0. 1 18076 0.890643 5.143249 Within Groups 123737 6 20622.83

Total 128607.1 8

Anova: Single factor analysis for PCR-MPN in the field experiment (a = 0.05).

1. Time O davs, Control biopiles, Pseudomonas

SUMMARY Groups Count Sum Average Variance C#l P 3 56566.94 18855.65 301 530.3 C#2 P 3 5551 9.41 18506.47 142237.5 C#3 P 3 55473.19 18491.06 57041.13

ANOVA Source of Variation SS df MS F P-value F crit Between Groups 255086.1 2 127543 0.764022 0.506299 5.143249 Within Groups 1001618 6 166936.3

Total 1256704 8

2. Time O davs. lnoculated biopiles, Pseudomonas

SUMMARY Groups Count Sum Average Variance I n M l P 3 106328.2 35442.72 357031.6

ANOVA

Source of Variation SS df MS F P-value F crit Between Groups 6.03E+08 2 3.02€+08 2145.255 2.72E-09 5.143249 Within Groups 843550.6 6 140591 -8

Total 6.04E+08 8

3. Time O days, Control biopiles, Rhodococcus

SUMMARY Groups Count Sum Average Variance C#l R 3 581.202 193.734 31.83169

ANOVA Source of Variation SS df MS F P-value F crit Between Groups 4313.388 2 21 56.694 0.947948 0.438783 5.143249 Within Groups 13650.71 6 2275.1 19

Total 17964.1 8

4. Time O davs, lnoculated biopiles. Rhodococcus

SUMMARY Groups Count Sum Average Variance Ino#l R 3 10632.82 3544.272 3570.31 6 lnoü2 R 3 6945.989 231 5.33 85661 7.6 lnM3 R 3 5480.066 1 826.689 492.9743

ANOVA Source of Variation SS df MS F P-value F cnt Between Groups 4699 162 2 2349581 8.1 89729 0.01 927 1 5.143249 Within Groups 1721 362 6 286893.6

Total 6420523 8

5. Time O davs, Control biopiles. Sphinaomonas

SUMMARY Groups Count Sum Average Variance C#l S 3 2789.262 929.754 733.1 352

ANOVA Source of Variation SS d f MS F P-value F crit Between Groups 884881 -3 2 442440.7 1 -46841 2 0.302625 5.143249 Within Groups 1807834 6 301 305.6

Total 269271 5 8

6. Time O davs. lnoculated biopiles, S~hinciomonas

SUMMARY Groups Count Sum Average Variance I n d l S 3 53847.81 17949.27 91 568.49

ANOVA Source of Variation SS df MS F P-value F crit Between Groups 1.73€+08 2 86508328 1805.036 4.57E-09 5.143249 Within Groups 287556.5 6 47926.09

Total 1.73E+08 8

7. Time O davs, Control vs lnoculated biopiles, Pseudomonas

SUMMARY Groups Count Sum Average Variance inoculated 9 214803.9 23867.1 75506753 control 9 167559.5 1861 7.73 157088

ANOVA Source of Variation SS df MS F P-value F crit Between Groups 1.24€+08 1 1.24E+08 3.277693 0.089047 4.493998 Within Groups 6.05€+08 16 37831921

Total 7.29E+08 17

8. Time O davs. Control vs lnoculated biopiles, Rhodococcus

SUMMARY Groups Count Sum Average Variance inoculated 9 23058.87 2562.097 802565.4 control 9 1866.47 207.3856 2245.51 2

ANOVA Source of Variation SS df MS F P-value F crit

Between Groups Within Groups

Total

9. Time O davs. Control vs lnoculated biopiles, Sphinctornonas

SUMMARY Groups Count Sum Average Variance inoculated 9 135124.4 15013.82 21663027 control 9 5577.682 61 9.7424 336589.4

ANOVA Source of Variation SS df MS F P-value F crit Between Groups 9.32E+08 1 9.32€+08 84.76084 8.57508 4.493998 Within Groups 1.76€+08 16 10999808

Total 1.1 1 E+09 17

10. Time 65 davs, Control vs lnoculated biopiles, Pseudomonas

SUMMARY Groups Count Sum Average Variance - control 3 463971 6 1546572 9.82€+11 inoculated 3 621 8492 2072831 4.97€+08

ANOVA Source of Variation SS df MS F P-value F crit Between Groups 4.15€+11 1 4.15€+11 0.84561 9 0.409831 7.70865 Within Groups 1.97E+12 4 4.91 E+11

Total 2.38€+12 5

II. Time 65 davs, Control vs lnoculated biopiles, Rhodococcus

SUMMARY Groups Count Sum Averaqe Variance - control 3 62853570 20951 190 5.96E+11 inoculated 3 8216962 2738987 1.29E+12

ANOVA Source of Variation SS df MS F P-value F crit Between Groups 4.98E+14 1 4.98E+14 528.3334 2.12E-05 7.70865

Within Groups 3.77€+12 4 9.42€+ 1 1

Total 5.01 E+14 5

12. Time 65 davs, Conttol vs lnoculated biopiles, Sphinqomonas

SUMMARY Groups Count Sum Average Variance control 3 453239.2 151 079.7 8.74E+09 inoculated 3 6218492 2072831 4.97€+08

ANOVA Source of Variation SS df MS F P-value F cnt Between Groups 5.54€+12 1 5.54€+12 1 199.52 4.15E-06 7.70865 Within Groups 1.85E+1 O 4 4.62€+09

Total 5.56E+12 5