View
5
Download
0
Category
Preview:
Citation preview
Results and Discussion
103
CHAPTER 4
RESULTS AND DISCUSSION
4.1 Fungal growth studies
The fungal hyphae presented extensive expansion, with the
observation of different stages of growth including primary and secondary
branches and giving origin to vegetative mycelium. Figure 4.1 shows the
luxuriant growth of Fusarium oxysporum on solid media in petri plates. A
white mat of fungus covered almost the entire plate.
4.1.1 Dry weight of the fungus/ biomass production
The change in biomass of the fungus over a period of time has been
presented in Figure 4.2. The fungal biomass increased at a slow rate till
about 48 hours but thereafter increased exponentially as earlier described
by Granjo et al. (2007) for Fusarium verticillioides. However, after about
8 days this rapid growth stabilized and the trend became more towards
stationary phase (Figure 4.2). The lag phase up to 24 h of culture is
Results and Discussion
104
usually observed when fresh medium is inoculated with cells derived
from an old culture. In such a scenario, the cells are deprived of enzymes
and the total growth rate can only be reached when the optimum
concentrations of these substances for synthesis are restored (Granjo et
al., 2007).
Results and Discussion
105
Figure 4.1. Growth of Fusarium oxysporum on solid media.
Results and Discussion
106
Several workers have also reported an initial lag period, followed by rapid
growth in diverse fungal genus like Piromyces (Teunissen et al., 1991).
Figure 4.2. Change in fungal biomass over time (bars represent standard error values at 5% significance).
4.1.2 Glucose utilization
The usage and availability of growth substrate viz. glucose is of
immense importance to predict the growth rate and multiplication of fungi
in laboratory cultures. This assumes more significance for a good and
luxuriant growth of fungi for industrial purposes. Figure 4.3 depicts the
utilization of glucose over a period of time. The concentration of glucose
in the liquid media containing F. oxysporum decreased rapidly upto the
initial 4 days and became static thereafter (Figure 4.3). Such a trend of
high glucose usage in the initial growth period has also been observed
Fun
gal b
iom
ass
(mg)
Time (hours)
Results and Discussion
107
earlier in other microbes (Wetter et al., 2003; Xu et al., 2003; Thiet et al.,
2006). The high residual glucose concentration at the initial growth phase
was attributed to increasing activity of starch hydrolyzing enzymes such
as amylases, pectinase which convert the substrate to simple sugar which
was utilized by the fungus. However, once the carbohydrates were
utilized, growth utilization declined and the fungus afterwards utilized its
metabolic end products for growth (Figure 4.3).
Figure 4.3. Glucose utilization by the fungus over a period of time (bars represent standard error values at 5% significance)
Glu
cose
(gm
/150
ml)
Time (hours)
Results and Discussion
108
4.1.3 MTT assay
Various methods are available for the determination of cell
densities of fungal cells. The commonly used method include
hemocytometer counting, determination of protein content, wet or dry
weight measurement, and determination of the optical density (OD).
While hemocytometer counting and protein determination have the
disadvantage of being time-consuming and tedious, the measurement of
wet or even dry weight is not practically possible for very small culture
volumes (Freimoser et al., 1999). The measurement of the optical density
works well if cell shapes are regular, as for example in yeasts, but in our
case it is problematic because of the irregular cell shapes and dimensions
of F. oxysporum and moreover, the unequal growth, clumping, and
adherence of filamentous fungi in assay tubes indicate towards the use of
MTT as the most suitable assay for viability (Meletiadis et al., 2000). The
MTT test is preferred because of its accuracy and reliability (Mosman,
1983).
The results of MTT assay indicating variation in optical density
against time are presented in Figure 4.4. A gradual increase in the number
of living cells over a period of time with a concomitant increase in optical
density values was observed (Figure 4.4). The pattern depicted is similar
to the growth curve of fungal biomass.
Results and Discussion
109
Figure 4.4. MTT assay showing OD vs. time (bars represent standard error values at 5% significance)
4.1.4 pH variation over time
Figure 4.5 presents the changes in pH of the growth medium as
fungal growth continues over a period of time. The results show that the
pH of the medium gradually decreases as the fungal growth progresses.
However, the reduction is more in the initial 48 hours; thereafter the
reduction in pH slows down. Such a reduction in the pH of the media has
also been observed in other fungus like Glomus intraradices (Bago et al.,
Time (hours)
OD
Results and Discussion
110
1996) wherein a decrease in the pH of the medium was observed on
extensive mycelium development.
Figure 4.5. Graph depicting pH of culture filtrate at
different time intervals (bars represent standard
error values at 5% significance)
This reduction in pH may be because of the end products of
metabolism that are secreted in the medium by the fungus, especially
carbon dioxide (CO2). The pH variation seems to be inversely
proportional to the fungal growth since a lowering in pH resulted in
higher fungal growth. Our result patterns are matching with the previous
studies performed in the fungus Rhizopus (Odeniyi et al., 2009) wherein
the growth of the fungus reduced as the pH increased until none was
Time (hours)
pH
Results and Discussion
111
recorded beyond pH 6.0. A consistent high mycelia length was recorded
at low pH and the fungal growth rate reduced as the pH increased towards
a neutral range until growth was not supported at pH 7.0 and beyond
(Odeniyi et al., 2009).
4.1.5 Protein estimation
In estimating the true protein content of biological material it is
important that the method of protein determination is chosen which is
accurate, as well as convenient enough to be used for routine testing.
Changes in soluble protein content have been detected by various
techniques in a wide range of organisms, including the fungi
Blastocladielln emersorzii (Cantino and Goldstein, 1962) and Neurospora
crassa (Williams and Tatum, 1966). For protein estimation of fungal
cells, Solomons (1973) suggested that the Folin method was not reliable
for protein determination. However, successive studies have shown that
the Folin method applied to hot alkali extracts of fungal biomass is in
good agreement with protein estimation based on amino acid analysis
(Christias et al., 1975). Thus, the Folin method of protein determination is
a reliable and convenient for routine determinations of the true protein
content in fungal cells (Christias et al., 1975).
Results and Discussion
112
Figure 4.6. Variation in protein content in the pellet over time (bars represent standard error values at 5% significance)
Figure 4.7. Variation in protein content in the supernatant over time (bars represent standard error values at 5% significance)
Time (hours)
mg/g
Time (hours)
mg/ml
Results and Discussion
113
The variation in protein content in pellet and supernatant over a
period of time have been shown in Figures 4.6 and 4.7 respectively. The
protein content in the pellet was about 246 mg/g after the initial 24 hours
of growth which is quite comparable to that reported for other fungi
(Czajkowska and Ilnicka-Olejniczak, 1988). During the subsequent period
of nitrogen depletion, there was a marked and persistent decrease in the
overall amount of protein. The protein content of the fungus dropped to
183 mg/g after 3 days of culture and further to 112 mg/g after about 6
days of culture. Thus, there was a drop of more than 50% after about 6
days of fungal growth (Figure 4.6). The same trend was observed in the
protein content of the supernatant. The protein content of the supernatant
was considerably low (138 mg/ml) as compared to the pellet (Figure 4.7).
The protein content dropped to 96 mg/ml after 48 hours, 82 mg/ml after
72 hours and finally to 47 mg/ml after 144 hours of growth (Figure 4.7).
This drop in protein content in the supernatant was remarkable since a
drop of 66% was observed after 6 days of culture (Figure 4.7). Thus,
under conditions of nitrogen starvation, there was a rapid and specific loss
of proteins, a fact observed in other fungi like Penicillium griseofulvum
(Bent 1967).
Rapidly increasing world population has resulted in a rising
demand of protein for both human and animal consumption. The situation
has intensified more due to the escalating prices of traditional protein
ingredients (Yabaya and Ado, 2008). There is an urgent requirement for
new sources of protein that will not require agricultural land, cost and
tedious means of production. Microbial proteins are microbial cells grown
and harvested for use as a protein source for human and animal
Results and Discussion
114
consumption (Senez, 1987; Frazier and Westhoff, 1988). This microbial
protein is referred to as a whole microbial biomass which can be derived
from a variety of microorganisms both unicellular and multicellular
namely bacteria, yeast, fungi and microscopic algae. According to
literature F. oxysporum, along with 2 other species viz. F. graminearum
and F. solani are considered edible strains of Fusarium (Ward 1998;
Moore and Chiu, 2001; Wiebe, 2002). The value for protein content
obtained in the present study agreed with the protein content value
obtained in the study on F. oxysporum by Christias et al. (1975).
However, the protein values of the present study were slightly less than
the values obtained in F. oxysporum in a previous study (Ahangi et al.,
2008) where the fungus was explored for production of mycoprotein. The
lower protein content obtained in the present study was probably due to
the use of different growth media in both the experiments. The amino acid
composition of F. oxysporum mycoprotein is also comparable with that of
the soybean meal and FAO reference protein (Ahangi et al., 2008). Thus,
Fusarium seems to be a good organism for microbial protein production.
Preliminary experiments have shown that Fusarium spp. grows well and
produce satisfactory yield in liquid cultures. F. oxysporum is also reported
to contain high amounts of all essential amino acids and gives satisfactory
yields of biomass in liquid cultures utilizing inexpensive agricultural
waste products (Christias et al., 1975). Therefore, Fusarium is a much
better organism for microbial protein production than other fungi like
Aspergillus and Penicillum. More efforts are needed to explore the
possibilities of Fusarium as a protein source.
Results and Discussion
115
4.2 Production and characterization of silver nanoparticles
4.2.1 Standardization of AgNO3 concentration for nanoparticle
production
It is well known that silver ions and silver-based compounds are
highly toxic to microorganisms (Cho et al., 2005) showing strong biocidal
effects on a wide range of microbes including fungi (Keuk-Jun et al.,
2008; Petica et al., 2008; Min et al., 2009). Therefore, the first step
involved the standardization of silver nitrate concentration for
nanoparticle production since higher concentrations of AgNO3 would be
detrimental to F. oxysporum. Any unreasonable increase in AgNO3
concentration would lead to a decrease in the fungal concentration and a
concomitant decrease in the production of silver nanoparticle. In the
present experiment, the growth of F. oxysporum was determined at
varying concentrations of AgNO3 ranging from 1mM to 20 mM (Table
4.1). The results showed only marginal decrease (5.91 %) in fungal
biomass at 1mM AgNO3. Further increase of AgNO3 concentration led to
a rapid decrease in fungal biomass that was of the order of 22% for 5mM
AgNO3, 36 % for 10 mM AgNO3 and 78 % for 20 mM AgNO3 (Table
4.1). Therefore, 1 mM AgNO3 concentration was determined as the ideal
concentration for production of silver nanoparticles.
Results and Discussion
116
Concentration
of AgNO3
Fungal biomass
(mg/ml)
% decrease
Control 3.89 mg -
1mM 3.66 mg 5.91
5mM 3.02mg 22.36
10mM 2.49 mg 35.99
15mM 1.58 mg 59.38
20mM 0.86 mg 77.89
Table 4.1. Effect of different concentrations of AgNO3 on F. oxysporum biomass.
4.2.2 Visual observation
The reduction of silver ions was visibly evident from the colour
changes associated with it. Figure 4.8 shows the colour changes before
and after the process of biological reduction. The colour of the media
turned light brown in 48 h and attained maximum intensity after 72 h
indicative of the formation of Ag nanoparticles. The change in colour of
the reaction mixture has been proved to be an indication of the formation
of silver nanoparticles using Fusarium spp. by Ahmad et al. (2003a),
Duran et al. (2005) and Ingle et al. (2009). This phenomenon has also
been observed during the formation of silver nanoparticles using other
microbes like Klebsiella (Shahverdi et al. 2007), Pleurotus (Nithya and
Raghunathan, 2009), Coriolus (Sanghi and Verma, 2009), Aspergillus
(Navazi et al., 2010), Trichoderma (Vahabi et al., 2011). The exact
reaction mechanism leading to the formation of silver nanoparticles by
microbes is yet to be elucidated.
Results and Discussion
117
Figure 4.8 Fungal cell filtrate before and after treatment with solution of
1mM silver nitrate.
Results and Discussion
118
However, Ahmad et al. (2002) have reported that certain NADH
dependent reductases were involved in the reduction of silver ions in case
of F. oxysporum, a fact corroborated by Duran et al. (2005) and
Anilkumar et al. (2007).
4.2.3 Scanning electron microscope (SEM) analysis
The second step of confirmation of nano-sized particles is its
characterization for which scanning electron microscope (SEM) is used in
the current study. This technique images the sample surface by detecting
scattered or secondary electrons which are emitted from the surface of a
sample due to excitation by the primary electron beam (Borisenko and
Ossicini, 2008). The electrons interact with the atoms that make up the
sample producing signals that contain information about the sample's
surface topography, composition and other properties such as electrical
conductivity.
SEM has been used as an efficient technique for silver nanoparticle
characterization (Chen et al., 2003; Zhang et al., 2007; Salunkhe et al.,
2011). Figure 4.9 and 4.10 shows the scanning electron micrograph of the
fungal mycelium treated as positive control (incubated with deionized
water) at low and high magnifications. Figure 4.11 and 4.12 show fungal
mycelium treated with silver nitrate solution at the same magnifications.
The surface deposited silver nanoparticles are seen clearly at a higher
magnification in the silver nitrate treated fungal mycelium.
Results and Discussion
119
Figure 4.9. Scanning electron micrograph of the fungal mycelium incubated with deionized water.
Figure 4.10. Scanning electron micrograph of the fungal mycelium incubated with 1.0 mM silver nitrate solution.
20 µm
20 µm
Results and Discussion
120
Figure 4.11. Scanning electron micrograph of the fungal mycelium incubated with deionized water (Magnified view).
Figure 4.12. Scanning electron micrograph of the fungal mycelium incubated with 1.0 mM silver nitrate solution (Magnified view).
100 nm
100 nm
Results and Discussion
121
4.2.4 Transmission electron microscope (TEM) analysis
Transmission electron microscopy (TEM) has provided further
insight into the morphology and size details of the silver nanoparticles. A
representative TEM image recorded from the silver nanoparticles solution
is shown in Figure 4.13. The figure shows individual silver particles as
well as a number of aggregates. The morphology of the nanoparticles is
variable, with majority of them spherical. In this micrograph, spherical
nanoparticles in the size range 1-50 nm were observed. Majority of the
nanoparticles were of 10-15 nm diameter (Table 4.2). About 78% of the
nanoparticles were below 25 nm. The size of silver nanoparticles in our
experiment corroborate with other studies done with Fusarium spp. viz.
Duran et al. (2005), Mohammadian et al. (2007), Basavaraja et al. (2008),
Ingle et al. (2009) and Khosravi and Shojaosadati (2009).
The nanoparticles were not in direct contact even within the
aggregates, indicating stabilization of the nanoparticles by a capping
agent. This corroborates with the previous observation by Ahmad et al.
(2003a) in their study on Fusarium oxysporum and by Saifuddin et al.
(2009) while working on silver nanoparticle production mediated by
Bacillus subtilis. There are various mechanisms of biological synthesis
evident in the literature that are related to NADH-dependent reductases,
nitrate reductase (Vaidyanathan et al., 2009) oligopeptide catalysis,
precipitating the particles with several forms (hexagonal, spherical, and
triangular) (Naik et al., 2002). However, the fungal reduction of silver
ions (Ag+) in aqueous solution generally yields colloidal silver with
particle diameter in the range of nanometers.
Results and Discussion
122
Figure 4.13. TEM image of silver nanoparticles produced by F. oxysporum.
Size of nanoparticles (nm) % nanoparticles
0-5 12
5-10 19
10-15 22
15-20 14
20-25 11
25-30 9
30-35 6
35-40 3
40-45 3
45-50 1
Table 4.2. Particle size of silver nanoparticles and their percentage distribution.
100 nm
Results and Discussion
123
4.2.5 Zetasizer analysis
The results of the control and treated samples are provided in
Figures 4.14 and 4.15. The hydrodynamic diameter of the aqueous
solution of AgNO3 without the fungus in water was ranging from 100-
800nm with a mean diameter of 221.4 nm. However, in the presence of
the fungal filtrate the range of the particle reduces up to 8-220 nm with
mean diameter to 45.84 nm. This shows the increased formation of silver
nanoparticles in the presence of fungal filtrate. The size of silver
nanoparticles obtained by Zetasizer is greater than that obtained through
transmission electron microscopy (TEM). This might be due to the fact
that the particle size in dynamic light scattering is augmented
substantially by the hydrated capping agents (probably protein) or from
solvation effects. In such cases the hydrodynamic diameter could be as
high as 1.3 times the original diameter of the capped particles (Mukherjee
et al., 2008). Similar results where particle size of silver nanoparticles
obtained through Zetasizer are comparatively lower than those obtained
through TEM have also been reported by Maliszewska et al. (2009).
Results and Discussion
124
Figure 4.14. Particle size distribution of control sample (Aqueous
solution of AgNO3 without the fungus).
Figure 4.15 Particle size distribution of treated sample (Fungal
filtrate and AgNO3).
Results and Discussion
125
4.3 In silico studies
In silico is an expression meant for predictive studies in relation to
every scientific approaches where docking is no exception. Docking
procedures aim to identify correct poses of ligands in the binding pocket
of a protein and to predict the affinity between the ligand and the protein.
The setup for a ligand docking approach requires the following
components: A target protein structure with or without a bound ligand,
the molecules of interest or a database containing existing or virtual
compounds for the docking process, and a computational framework that
allows the implementation of the desired docking and scoring procedures
(Krovat et al., 2005). Docking consists of two parts, namely, the accurate
prediction of the orientation (pose) of the bioactive conformation into the
binding pocket, and the estimation of the tightness of target-ligand
interactions (scoring) (Kontoyianni et al., 2004; Ballester and Mitchell,
2010).
Figures 4.16 and 4.17 shows the interaction of silver (ligand) with
outer membrane proteins of E. coli. The binding energy calculation of
SYBYL results regarding protein ligand (metal) interaction for two E. coli
outer membrane proteins have been shown in Table 4.3. The outer
membrane proteins (Omp) from E. coli belong to a family of highly
conserved bacterial proteins that promote bacterial adhesion to and entry
into mammalian cells (Vogt and Schulz, 1999). Moreover, these proteins
have a role in the resistance against attack by the human complement
system. Hence, it is an important target for docking studies in relation
with silver particles.
Results and Discussion
126
Figure 4.16 Docking result of silver (ligand) with outer membrane protein (trans membrane domain) (1QJ8) of E. coli.
Results and Discussion
127
Figure 4.17 Docking result of silver (ligand) with outer membrane protein (trans membrane domain) (1QJP) of E. coli.
Results and Discussion
128
Protein name (PDB/Protein Model Portal)
Source Organism
Ligand Binding Residues
FlexX docking Score
Outer membrane protein (trans membrane domain) (1QJ8)
E. coli Ag GLN 17 MET 18 ASN 19
-7.9476
Outer membrane protein (trans membrane domain) (1QJP)
E. coli Ag GLN 14 TRP 15
-1.5745
Table 4.3 Result of protein-ligand interaction in E. coli.
The figures show that the ligand docked deeply into the binding
pockets of the outer membrane proteins (OMPs) of E. coli.
Comparatively, the ligand exhibited lower free energy with the binding
site of OMP (trans membrane domain) (1QJ8) (-7.9476) as compared to
the outer membrane protein (trans membrane domain) (1QJP) (-1.5745).
The more negative value for outer membrane protein (trans membrane
domain) (1QJ8) indicates a better interaction of the ligand with the target
protein. An analysis of the results showed the following putative
functional site residues of the target proteins viz: for outer membrane
protein (trans membrane domain) (1QJ8) it was GLN17, MET18 and
ASN19, while for outer membrane protein (trans membrane domain)
(1QJP) it was GLN14 and TRP15 (Table 4.3).
Figures 4.18, 4.19 and 4.20 show the interaction results of silver
(ligand) with OMPs of P. aeruginosa. The binding energy calculation
which is one of the most important and authentic criteria for analyzing
interaction results of protein-ligand for P. aeruginosa proteins have been
provided in Table 4.4.
Results and Discussion
129
Figure 4.18 Docking result of silver (ligand) with drug discharge outer membrane protein (1WP1) of Pseudomonas aeruginosa using SYBYL X 1.1.1.
Results and Discussion
130
Figure 4.19 Docking result of silver (ligand) with drug discharge outer membrane protein (3D5K) of Pseudomonas aeruginosa using SYBYL X 1.1.1.
Results and Discussion
131
Figure 4.20 Docking result of silver (ligand) with drug discharge outer membrane protein (Modelled) (OPR 86) of Pseudomonas aeruginosa using SYBYL X 1.1.1.
Results and Discussion
132
The figures show that Ag as a ligand docked deeply into the
binding pockets of the outer membrane protein (modelled) (Opr 86) of the
bacterium. The Flexidock score for proteins-ligand docking in P.
aeruginosa ranged from -6.1948 to -36.6728. Among the 3 proteins under
study, the outer membrane protein (modelled) (Opr 86) exhibited the
lowest free energy having a Flexidock score of -36.67 kcal/mole. In
contrast, drug discharge outer membrane protein (1WP1) had a Flexidock
score of -6.1948. Thus, the outer membrane protein (modelled) (Opr 86)
has a better interaction with Ag ligand as compared to other proteins of P.
aeruginosa. An analysis of the results showed the following putative
functional site residues of the target proteins viz: LEU119, GLY120,
ALA304 and ASN305 for drug discharge outer membrane protein
(1WP1); TRP39, ASN450 and GLN451 for outer membrane protein
(3D5K); and HIS158, ILE159 and ASN160 for outer membrane protein
(modelled) (Opr 86) (Table 4.4).
A good docking interaction implies the prediction of ligand
conformation and orientation within the binding site and their lower
interaction energies (Srinivasan et al., 2004; Camacho and Vajda, 2011).
The reasonable low binding energy values indicates that silver as a ligand
is in most favourable region of the protein and that the protein has good
affinity with the ligand. Our results show that silver may prove to be a
strong antibacterial agent against E. coli and P. aeruginosa, especially if
used at nanoscale. However, the antibacterial action of silver seems to be
more in case of P. aeruginosa as compared to E. coli as shown by the
lower Flexidock score. One needs to verify the results obtained by in-
silico analysis through a comprehensive in-vitro procedure. Thus, the in
Results and Discussion
133
vitro validation of antimicrobial activity of silver nanoparticles on in
silico screened microbes was carried out to confirm the results obtained
by in silico analysis as validation is the final and the most important part
after predictive studies.
Protein name (PDB/Protein Model Portal)
Source Organism
Ligand Binding Residues
FlexX docking Score
Drug discharge outer membrane protein (1WP1)
P. aeruginosa Ag LEU 119 GLY 120 ALA 304 ASN 305
-6.1948
Outer membrane protein (3D5K)
P. aeruginosa Ag TRP 39 ASN 450 GLN 451
-16.0532
Outer membrane protein (Modelled) (Opr 86)
P. aeruginosa Ag HIS 158 ILE 159 ASN 160
-36.6728
Table 4.4 Result of protein-ligand interaction in P. aeruginosa.
Results and Discussion
134
4.4 Antibacterial activity of silver nanoparticles
In-vitro validation of antimicrobial activity of silver nanoparticles
on in silico screened microbes was carried out on both solid and liquid
media.The antibacterial activity of different concentrations of silver
nanoparticles was tested against 2 bacteria viz. E. coli and P. aeruginosa.
Each of the bacteria was tested with different concentrations of silver
nanoparticles in order to observe the effect on bacterial growth. The
results demonstrated that the concentration of silver nanoparticles that
prevents bacteria growth is different for each type.
4.4.1 E. coli
4.4.1.1 Liquid media
The antibacterial activity of silver nanoparticles on E. coli in liquid
media are depicted in Figure 4.21. In the presence of silver nanoparticles,
the growth curves of E. coli included three phases: lag phase, exponential
phase, and stabilized phase. Decline phases in each growth curve could
not be revealed because the total numbers of bacteria, including live and
dead ones were assayed, based on the value of OD 600. It has been
observed that optical density of the growth medium decreased as
comparison to the control with increasing concentration of silver
nanoparticles. In the absence of silver nanoparticles, E. coli reached the
exponential phase rapidly. Exposure to various concentrations of silver
nanoparticles retarded the growth of bacterial cells. With increasing
concentration of silver nanoparticles, the rate of growth rate slowed down
Results and Discussion
135
significantly. No growth of bacterial cells was seen in the first 5 hours at
20, 50 and 100 µg/ml of Ag nanoparticles. When the concentration of
silver nanoparticles was 20 µg/ml, no growth of E. coli could be detected
at 50 hours, indicating that the minimum inhibitory concentration (MIC)
of AgNPs to E. coli was 20 µg/ml. Silver nanoparticles above 20 µg/ml
and higher have been found to be effective bactericide.
4.4.1.2 Solid media
Generally, microbial growth in liquid is planktonic, whereas the
structure of a microbial colony grown on a surface is considerably
complex (Fujikawa, 1994; Mattilla and Frost, 1988). The surface of solids
is susceptible to attachment by and subsequent growth of microorganisms
where they might exist as a biofilm, a unique microbial community
(Madigan et al., 2000). Studies on microbial surface growth, therefore, are
thought to be considerably important in many microbiological fields
(Fujikawa and Morozumi, 2005).
Figure 4.22 shows the number of bacterial colonies grown on
nutrient agar plates as a function of concentration of silver nanoparticles,
while Figure 4.23 shows the images of petri plates incubated under
conditions in Figure 4.22. The bacterial cell colonies on agar-plates were
detected by viable cell counts, a technique of counting the number of
colonies that are developed after a sample has been diluted and spread
over the surface of a nutrient medium solidified with agar and contained
in a petri dish (Raffi et al., 2008).The number of bacterial colonies
Results and Discussion
136
reduced significantly with increased concentrations of silver
nanoparticles. About 55% inhibition in bacterial growth was observed in
plates supplemented with 5 µg/ml silver nanoparticles; and 90% in plates
supplemented with 10 µg/ml silver nanoparticles. Very less colony
forming units (CFU) were observed in the samples containing 20 µg/ml
silver nanoparticles. No CFU were observed in samples containing silver
nanoparticle greater than 20 µg/ml. Thus the bacterial growth inhibition
trend found in CFU data is quite similar to the results of OD.
Figure 4.21 Growth pattern of E.coli in different concentrations of silver nanoparticles.
Control
5 µg/ml 10 µg/ml 20 µg/ml 50 µg/ml 100 µg/ml
0 5 10 15 20 Concentration of AgNP (µg/ml)
OD
(600
nm
)
Results and Discussion
137
Figure 4.22 Antibacterial characterization by CFU as a function of silver nanoparticle concentration on nutrient agar plates on E. coli.
Figure 4.23 The images of petri dishes incubated in conditions of Figure 4.20.
Control 5 µg/ml
10 µg/ml
20 µg/ml
50 µg/ml
C 5 10 20 50 100 Concentration of AgNP (µg/ml)
CF
U a
fter
48
hour
s of
incu
bati
on (1
08 cel
ls/m
l)
Results and Discussion
138
4.4.2 Pseudomonas aeruginosa
4.4.2.1 Liquid media
The antibacterial activity of silver nanoparticles on the bacterium
P. aeruginosa in liquid media are depicted in Figure 4.24. The same trend
was observed in P. aeruginosa as was seen in E. coli. The control plates
clearly showed the three phases of bacterial growth viz. the lag phase, the
exponential or log phase, and the stabilization phase. In the presence of
silver nanoparticles, although the growth curves were observed but the
decline phases in each growth curve could not be revealed. This was due
to the fact that the total numbers of bacteria, including live and dead ones
were assayed. Exposure to different concentrations of silver nanoparticles
retarded the growth of bacterial cells to a considerable extent. No growth
of bacterial cells was seen in the initial 5 hours at 5, 10 and 20 µg/ml of
silver nanoparticles. When the concentration of silver nanoparticles was
10 µg/ml, no growth of E. coli was detected even at 50 hours, indicating
that the minimum inhibitory concentration (MIC) of silver nanoparticles
to E. coli was around 10 µg/ml. Thus, silver nanoparticles of 10 µg/ml
concentration and higher could be effective bactericide against P.
aeruginosa.
Results and Discussion
139
Figure 4.24 Growth pattern of P. aeruginosa in different concentrations of silver nanoparticles.
4.4.2.2 Solid media
Figure 4.25 shows the number of bacterial colonies grown on
nutrient agar plates as a function of concentration of silver nanoparticles,
while Figure 4.26 shows the images of petri plates incubated under
conditions in Figure 4.25. The number of P. aeruginosa reduced
significantly with increased concentrations of silver nanoparticles. About
50 % inhibition in bacterial growth was observed in plates supplemented
with 1 µg/ml silver nanoparticles; and 75 % in plates supplemented with 5
µg/ml silver nanoparticles. No CFU were observed in samples containing
silver nanoparticles greater than 10 µg/ml. Thus the bacterial growth
inhibition trend found in CFU data was quite similar to the results of OD.
Control
1 µg/ml
2 µg/ml 5 µg/ml 10 µg/ml 20 µg/ml
0 5 10 15 20 Concentration of AgNP (µg/ml)
OD
(600
nm
)
Results and Discussion
140
Figure 4.25 Antibacterial characterization by CFU as a function of silver nanoparticle concentration on nutrient agar plates against P. aeruginosa.
Figure 4.26 Petri dishes incubated in conditions of Figure 4.24.
CF
U a
fter
48
hour
s of
incu
bati
on (1
08 cel
ls/m
l)
C 1 5 10 20 Concentration of AgNP (µg/ml)
Control 1 µg/ml
5 µg/ml 10 µg/ml
Results and Discussion
141
The results on both the microorganisms showed that silver nanoparticles
have potent antibacterial activity.
Studies on the mechanism of inhibitory action of silver ions on
microorganism have showed that upon Ag+ treatment, DNA loses its
replication ability and expression of ribosomal subunit proteins, as well as
other cellular proteins and enzymes essential to ATP production, becomes
inactivated (Yamanaka et al., 2005; Muhling and Bradford, 2009). It has
also been hypothesized that Ag+ primarily affects the function of
membrane bound enzymes, in the respiratory chain (Furr et al., 1994).
However, the mechanism of bactericidal actions of silver nanoparticles is
still not well understood. The positive charge on Ag+ is an important
factor for its antibacterial nature, through electrostatic interaction between
the negatively charged cell membrane of the microorganisms and
positively charged nanoparticles. It has been proposed that the
electrostatic force might be an additional cause for the interaction of the
nanoparticles with the bacteria (Tiwari et al., 2008). In several reports on
the bactericidal activity of silver nanoparticles (McDonnell and Russell,
1999; Pal et al., 2007), it was shown that the interaction between silver
nanoparticles and constituents of the bacterial membrane caused
structural changes and damage to membranes, finally leading to cell
death. Nanosilver, a particle of Ag element, is a new class of material
with remarkably different physiochemical characteristics such as
increased optical, electromagnetic and catalytic properties from the bulk
materials (Wenseleers et al., 2002; Kelly et al., 2003). Nanoparticles with
at least one dimension of 100nm or less have unique physicochemical
Results and Discussion
142
properties, such as high catalytic capabilities and ability to generate
reactive oxygen species (ROS) (Nel et al., 2006; Limbach et al., 2007).
Silver in the form of nanoparticles could be therefore more reactive with
its increased catalytic properties and become more toxic than the bulk
counterpart. The minute size of silver nanoparticles ensures that a
significantly large surface area of the particles is in contact with the
bacterial cells (Parameswari et al., 2010). Such a large contact surface is
expected to enhance the extent of bacterial elimination. Growth on agar
plates is considered to be a more ready means of distinguishing
antimicrobial properties of silver nanoparticles. A previous study (Sondi
and Salopek-Sondi, 2004) pointed out a distinct difference between these
two methods. However, in our study liquid growth experiments showed
similar results, a fact also noted by Parameswari et al. (2010) while
working on silver nanoparticles synthesized by the chemical method. The
extent of inhibition of E. coli and P. aeruginosa depended on the
concentration of the silver nanoparticles as well as on the initial bacterial
population. The number of both microorganisms decreased with an
increase in the concentration of silver nanoparticles. The duration of
treatment markedly affected the microbial population.
Recommended