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

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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.