26 Nanoscience and Nanotechnology: An International Journal 2013; 3(2): 26-32

ISSN: 2278-1374

Original Article

Bacterial synthesis of silver nanoparticles by using optimized biomass growth of

Bacillus sp.

Malarkodi C, Rajeshkumar S, Paulkumar K, Gnanajobitha G, Vanaja M, Annadurai G *

Environmental Nanotechnology Division

Sri Paramakalyani Centre for Environmental Sciences

Manonmaniam Sundaranar University, Alwarkurichi – 627412, Tamilnadu, India.

Tel/Fax: 04634 – 283406

Email: annananoteam@gmail.com, gannadurai@hotmail.com

Received 27 March 2013; accepted 08 April 2013

Abstract

Biosynthesis of nanoparticles is the major division in the field of applicable Nanoscience and nanotechnology. Silver

nanoparticles are playing an important role in biomedical and various applications. In this investigation Bacillus sp.

bacterium was used for the synthesis of silver nanoparticles. For the optimized production of silver nanoparticles Response

Surface methodology was applied. In this various growth factors like nitrogen source, pH and temperature was changed

and culture production was increased. The synthesis of silver nanoparticles was rapid and stable analyzed by UV-vis

spectrophotometer. Most of the particles are spherical in shape and size ranges from 65-70 nm analyzed using Scanning

Electron Microscope (SEM). Finally the nature of the nanoparticles was identified by Elemental analysis (EDX).

© 2013 Universal Research Publications. All rights reserved

Keywords: Bacillus sp., Response surface methodology, SEM, EDX.

1. Introduction

Nanoparticles are creature viewed as essential building

blocks of nanotechnology. A vital aspect of

nanotechnology concerns the growth of experimental

processes for the synthesis of nanoparticles of different

sizes, shape and proscribed dispersity. With the expansion

of new chemical and physical methods, the concern for

environmental contaminations are also sharp as the

chemical methods concerned in the synthesis of

nanoparticles make a large amount of hazardous by

products. Thus, there is a need for microbe mediated

synthesis that includes a clean, nontoxic and ecofriently

method of nanoparticle synthesis [1]. As a report,

researchers in the field of nanoparticles synthesis and

congregation have twisted to biological system of

inspiration [2]. Nanoparticles demonstrate completely

novel or improved properties compared with larger

particles of the size and these new properties are derivative

due to the variation in specific exact characteristics such as

size, distribution and morphology of the particles [3]. It is

well well-known to facilitate silver is an effective

antibacterial agent and possesses a strong antibacterial

activity against bacteria, viruses and fungi, even though the

mechanism and the way of action are still not well known

[4, 5]. Response surface methodology (RSM) is a collection

of statistical techniques for designing experiments, building

models, evaluating the effective factors and most

importantly, searching for the optimum conditions of the

factors for a desirable response [6,7]. The Box-Behnken

design was investigating linear, quadratic, and cross

product effects of three factors, each varied at three levels

and also includes three centre points for replication [6-9].

This could be done by involving three major steps i.e.

performing statistically designed experiments, estimating

the coefficient in mathematical model, predicting the

response and checking adequacy of the model [10]. This

study demonstrated the intracellular synthesis of stable

silver nanoparticles using the bacteria S.nematodiphila.

2. Materials and methods

2.1. Bacterial strain and growth conditions

Collection of samples, isolation and identification

The sample was collected from most contaminated area

common toilet in MS university campus. The isolated

organism was maintained for nutrient agar medium. the

organism were cultivated in 1 liter of medium containing

1.0 gm of Beef extract, 2.0 gm of yeast extract, 5gm of

peptone, 5gm of sodium chloride, 15gm of agar. The

organism was incubated at 35°C. The isolates were

morphologically and microbiologically characterized as

Bacillus sp..

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27 Nanoscience and Nanotechnology: An International Journal 2013; 3(2): 26-32

2.2. Optimization

2.2.1. Experimental design and optimized by Response

Surface Methodology (RSM)

RSM is an empirical statistical modeling technique

employed for multiple regression analysis using

quantitative data obtained from properly designed

experiments to solve multivariable equations

simultaneously. A factorial central composite rotary design

(CCRD) for three factors with replicates at the centre point

and star points was used. The different five variables used

were yeast extract, peptone, sodium chloride, pH and

Temperature. The CCRD contains total number of

experiments with five variables was 46 experiments. Forty

experiments were augmented with ten replications at the

center points to evaluate the pure error. In order to ascribe

the effect of factors on response surface in the region of

investigation, a Box-Behnken design with five levels was

performed. The Box-Behnken design was applied using

Design-Expert (version 7.0.1); in the optimization process

the response can be related to chosen factors by linear or

quadratic models. The average of the maximum biomass

activity of the duplicate values obtained was taken as

dependent variable or response Yi (U). Duplicates are

necessary to estimate the variability of experimental

measurements, i.e. the repeatability of the phenomenon.

Replicates at the centre of the domain in three blocks

permit the checking of the absence of bias between several

sets of experiments. The experimental results of RSM were

fitted via the response surface regression procedure, using

the following second–order polynomial equation:

)..........,,,,( 54321 kXXXXXXfY (1)

The true relationship between Y and Xk may be complicated

and, in most cases, it is unknown; however, a second-

degree quadratic polynomial can be used to represent the

function in the range of interest:

ji

k

j

ij

k

jii

i

k

i

iii

k

i

io XXRXRXRRY2

1

,1

2

11

(2)

where X1, X2, X3, X4, X5, …, Xk are the input variables

which affect the response Y, R0, Ri, Rii and Rij (i = 1–k,

j = 1–k) are the known parameters, ε is the random error. A

second-order model is designed such that variance of Y is

constant for all points equidistant from the center of the

design. Coding of the variables was done according to the

following equation

i

oii

X

XXX

(3)

Where Xi is the coded value and Xo is the actual value of

the independent variable, Xo is the actual value at the center

point and Xi is the step change value. The following

equation was used for coding the actual experimental

values of the factors in the range of (1- to +1). In system

involving five significant independent variables X1, X2, X3,

X4 and X5 the mathematical relationship of the response of

these variables can be approximated by quadratic (second

degree) polynomial equation;

54455335

43345225422432235115411431132112

2

555

2

444

3

333

2

222

2

11155443322110

XXbXXb

XXbXXbXXbXXbXXbXXbXXbXXb

XbXbXbXbXbXbXbXbXbXbbY

(4)

Where Y is the predicted value, bo is the constant: Yeast

Extract (g/L) (0.4, 8, 1.0) (X1); Peptone (g/L) (0.4, 0.5 0.6)

(X2), NaCl (g/L) (0.4, 0.5, 0.6) (X3), Temperature (25, 30,

35 0C) (X4) and pH (6.4, 7.4, 8.4.) (X5), b1, b2, b3, b4 and b5

are linear coefficients, b12, b13, b14, b15, b23, b24 b25, b34, b35

and b45 are cross product coefficients and b11, b22, b33 b44

and b55 are quadratic coefficients. The design of

experiments was carried out for analysis using the design

expert by Stat Ease lnc, Statistics Made Easy, Minneapolis,

MN Version .7)

The experimental design that involves factors like Yeast

extract, NaCl, Peptone, pH and Temperature. For the

selection of significant variables for optimization of

Maximum Biomass Activity by bacterial strain Bacillus sp.

a variety of phsico-chemical factors such as Temperature

(25º, 30º, 35º) and pH (6.4, 7.4 and 8.4) at different

concentrations of above nutrient agar designed. The design

experiments were carried out in conical flasks containing

minimal medium and inoculated with bacterial strain

Bacillus sp. kept at 180 rpm in shaker for different

incubation period (hrs). After incubation period, the

amount of maximum biomass Activity was calculated the

UV-Vis spectrophotometer at 600 nm.

2.3. Intracellular synthesis of silver nanoparticles

The optimized biomass and without optimized Bacillus sp.

strain was used for the synthesis of silver nanoparticles.

100 ml of nutrient broth and growth factors changed

nutrients were prepared after one loopful culture of Bacillus

sp. was inoculated in this broth. Then the broth was placed

in the orbital shaker for 24 hours to the growth of culture.

Then 1mM of Silver Nitrate crystals were weighed and

added with 24 hrs incubated 100ml of culture and kept it in

a shaker at 200 rpm per minute. The changing of color was

noted and a photograph was taken.

2.4. Characterization of nanoparticle

The UV- visible spectrum of this solution was recorded in

Perkin – Elmer spectrophotometer. The particles

wavelength ranges from 300 to 700nm. Bacillus sp. treated

with silver nanoparticle was air dried and used for analysis.

The morphology and particle sizes were determined by

Scanning electron microscope (SEM) was performed on a

HITACHI Model S-3000H by focusing on nanoparticles.

The EDX spectra also measured by the same instrument.

3. Result and Discussion

3.1. Isolation and Identification of microorganism

The microorganisms in the most contaminated toilet Sink

were isolated by dilution technique. The dominant bacterial

strains are identified as Bacillus sp., on the morphological

and biochemical characteristics (Fig.1). Gram’s staining as a preliminary test; the test gives a gram positive, rod shape.

They were serially diluted and spread on nutrient agar

plates. The starch has been hydrolyzed and a clear zone by

the addition of iodine solution. The character is described

the organism is found to be a Bacillus sp. The character is

described the organism is found to be a Bacillus sp. was

determined using Bergey’s manual of determinative

bacteriology [11].

3.2. Response surface methodology

RSM is an experimental modeling performance used to

estimate the relationship between a set of convenient

28 Nanoscience and Nanotechnology: An International Journal 2013; 3(2): 26-32

Figure 1: Bacillus sp. in (a) in Nutrient agar containing Plate and (b) Nutrient broth containing bacterial culture.

Table 1: Box–Behnken design based on the five independent experimental variables which was used for predicting

theoretical values to find out the production of maximum biomass

Run No Yeast Extract Peptone NaCl pH Temperature Actual Value Predicted Value

1 0.1 0.3 0.5 7.4 30 1.2500 1.2396

2 1.5 0.3 0.5 7.4 30 1.7688 1.7584

3 0.1 0.7 0.5 7.4 30 1.4796 1.4817

4 1.5 0.7 0.5 7.4 30 1.4254 1.4275

5 0.8 0.5 0.3 6.4 30 1.4424 1.4320

6 0.8 0.5 0.7 6.4 30 1.4947 1.4842

7 0.8 0.5 0.3 8.4 30 1.5244 1.5265

8 0.8 0.5 0.7 8.4 30 1.4967 1.4988

9 0.8 0.3 0.5 7.4 25 1.6026 1.5922

10 0.8 0.7 0.5 7.4 25 1.4668 1.4688

11 0.8 0.3 0.5 7.4 35 1.4680 1.4576

12 0.8 0.7 0.5 7.4 35 1.4901 1.4922

13 0.1 0.5 0.3 7.4 30 1.5280 1.5321

14 1.5 0.5 0.3 7.4 30 1.7272 1.7314

15 0.1 0.5 0.7 7.4 30 1.5072 1.5114

16 1.5 0.5 0.7 7.4 30 1.7725 1.7766

17 0.8 0.5 0.5 6.4 25 1.5844 1.5739

18 0.8 0.5 0.5 8.4 25 1.5469 1.5489

19 0.8 0.5 0.5 6.4 35 1.4492 1.4388

20 0.8 0.5 0.5 8.4 35 1.5707 1.5728

21 0.8 0.3 0.3 7.4 30 1.6444 1.6340

22 0.8 0.7 0.3 7.4 30 1.2606 1.2626

23 0.8 0.3 0.7 7.4 30 1.3297 1.3193

24 0.8 0.7 0.7 7.4 30 1.5998 1.6019

25 0.1 0.5 0.5 6.4 30 1.4110 1.4006

26 1.5 0.5 0.5 6.4 30 1.5708 1.5603

27 0.1 0.5 0.5 8.4 30 1.3805 1.3826

28 1.5 0.5 0.5 8.4 30 1.6853 1.6873

29 0.8 0.5 0.3 7.4 25 1.3633 1.3675

30 0.8 0.5 0.7 7.4 25 2.0116 2.0157

31 0.8 0.5 0.3 7.4 35 1.9437 1.9479

32 0.8 0.5 0.7 7.4 35 1.3199 1.3241

33 0.1 0.5 0.5 7.4 25 1.8296 1.8338

34 1.5 0.5 0.5 7.4 25 1.5899 1.5941

35 0.1 0.5 0.5 7.4 35 1.3020 1.3062

36 1.5 0.5 0.5 7.4 35 2.0063 2.0104

37 0.8 0.3 0.5 6.4 30 0.7622 0.8122

38 0.8 0.7 0.5 6.4 30 1.7694 1.7819

39 0.8 0.3 0.5 8.4 30 1.8682 1.8807

40 0.8 0.7 0.5 8.4 30 0.8474 0.8224

41 0.8 0.5 0.5 7.4 30 0.9780 0.9780

42 0.8 0.5 0.5 7.4 30 0.9780 0.9780

43 0.8 0.5 0.5 7.4 30 0.9780 0.9780

44 0.8 0.5 0.5 7.4 30 0.9780 0.9780

45 0.8 0.5 0.5 7.4 30 0.9780 0.9780

46 0.8 0.5 0.5 7.4 30 0.9780 0.9780

29 Nanoscience and Nanotechnology: An International Journal 2013; 3(2): 26-32

empirical factors and observed consequences. Basically this

optimization process involves three major steps,

performing the statistically designed experiments,

estimating the coefficients in a mathematical model and

predicting the response and checking the adequacy of the

model. The experimental conducted in the present study

were targeted toward the construction of a quadratic model

consisting of forty six trials. After performing a screening

of factors and their interactions, the response surface

analysis was carried out, in order to find the optimal

conditions for the maximum biomass activity. The

maximum level of biomass from these experiments along

with the mean actual and predicted values responses by

showing the Table1. The result of ANOVA indicates that

the quadratic model of regression is represented in Table2.

The following variables can be approximated by quadratic

polynomial equation. 2 2 2

0.978 0.116 0.022 0.006 0.027 0.027 0.341 0.157 0.3181 2 3 4 5 1 2 3

2 20.188 0.367 0.143 0.0161 0.036 0.236 0.1634 5 1 2 1 3 1 4 1 5 2 3

0.507 0.039 0.02 0.318 0.0392 4 2 5 3 4 3 5 4 5

Y X X X X X X X X

X X X X X X X X X X X X

X X X X X X X X X X

The coefficient of R2 value was always between 0 and 1. R

2

for response was 0.9987 values greater than 0.1000 indicate

the model terms are not significant. The values of predicted

R2

of 0.9952 are in reasonable agreement with the Adjusted

R-Squared of 0.9978. The results of maximum production

of biomass indicated that the “F – value” of the model was

Figure 2: (a) Maximum biomass activity on 3-D graphics

for response surface optimization versus Yeast Extract and

Peptone.

Figure 2: (b) Maximum biomass activity on 3-D graphics

for response surface optimization versus Peptone and NaCl.

Figure 2: (c) Maximum biomass activity on 3-D graphics

for response surface optimization versus NaCl and pH.

Figure 2: (d) Maximum biomass activity on 3-D graphics

for response surface optimization versus pH and

Temperature.

Figure 2: (e) Maximum biomass activity on 3-D graphics

for response surface optimization versus Temperature and

Yeast Extract.

Figure 2: (f) Factor plot representing the individual

variables effect Maximum biomass activity by bacterial

strain Bacillus sp.

30 Nanoscience and Nanotechnology: An International Journal 2013; 3(2): 26-32

Table 2: ANOVA for Response Surface Quadratic Model Analysis of variance

Source Coefficient Estimate Mean Square F Value p-value Prob > F

Model 0.978 0.206 1030 < 0.0001*

A-Yeas 0.116 0.216 1079 < 0.0001*

Extract

B-Peptone - 0.02 0.008 39 < 0.0001*

C-Nacl 0.006 0.001 3 0.0955*

D-pH 0.027 0.01 59 < 0.0001*

E- Temp - 0.02 0.012 62 < 0.0001*

AB - 0.14 0.082 410 < 0.0001*

AC 0.016 0.001 5 0.0280*

AD 0.036 0.005 26 < 0.0001*

AE 0.236 0.223 1114 < 0.0001*

BC 0.163 0.107 535 < 0.0001*

BD - 0.50 1.028 5141 < 0.0001*

BE 0.039 0.006 31 < 0.0001*

CD - 0.02 0.002 8 0.0091*

CE - 0.31 0.404 2022 < 0.0001*

DE 0.039 0.003 2 < 0.0001*

A2 0.341 1.015 5077 < 0.0001*

B2 0.157 0.217 1085 < 0.0001*

C 2 0.318 0.887 4434 < 0.0001*

D 2 0.188 0.310 1552 < 0.0001*

E 2 0.367 1.176 5878 <0.0001*

Residual 0.005 0.000 R2 0.9987

Lack of Fit 0.005 0.000 Adj R2 0.9978

Pure Error 0 0.000 Pred R2 0.995

Cor Total 4.124343 - Adeq Precision 125.9504 *Values of "Prob > F" less than 0.0500 indicate model terms

1029.83 implies the model is significant. There is only a

0.01% chance that a “Model F- value” this large could

occur due to noise. Values of "Prob > F" less than 0.0500

indicate model terms are significant. Also, the Values of

"Prob > F" less than 0.0500 indicate model terms are

significant. The R2 values indicating that the model could

be explain 95% of the variability. Adeq Precision"

measures the signal to noise ratio. A ratio greater than 4 is

desirable. The ratio of 125.950 indicates an adequate

signal. This model can be used to navigate the design

space. [12] Showed the Maximum amount of enzyme

lipase production from Geotrichum candidum can be

increased because of the role of carbon source and nitrogen

source. [7] Reported the maximum percentage of keratinase

activity (100%) is done because of the calcium chloride

concentration. The salt concentration in the optimization

studies for the increased production of the keratinase

activity from the Scopulariopsis brevicaulis giving a best

result and improved that role. Yeast extract, peptone and

salt concentration were involves the production of the

maximized nanoparticles synthesis, here the effect of yeast

extract explained in the Fig. 2(a) the maximum yield is

produced in the range 1.510 absorbance and it is in the

range of 0.90 g/l, the peptone (Fig. 2(b)) is the one of the

carbon source it is in the absorption range of 1.301 and

maximum activity was obtained from the 0.80 g/dl. Based

on that the concentration of the salt sodium chloride

concentration were changed and the maximum yield was

obtained at the range of absorption at 1.55 and in the

amount of the salt for that is 0.56 g/l it represented in

(Fig. 2(c)). Fig. 2(d) and Fig. 2(e) showed the 3-D-plot

representing maximum biomass activity against pH (7.5 to

7.8) and Temperature (250 to 35

0C). Optimization level of

pH (7.4) and Temperature (270C) were determined at

maximum biomass activity. The internal environment of all

living cells is believed to be approximately neutral. The

permeated substances can upset the internal. The pH

balance since the bacterial activity decreases as the pH

deviates from neutral conditions. The factor effect function

of certain factor is a function that describes how the

response moves as the level of those factor changes, when

the other factors are fixed at their optimum levels. From the

trace plot Fig. 2(f) it can be observed that each of nutrients

used in the present study has its individual effect on

maximum biomass activity by bacterial strain Bacillus sp.,.

The different nutrients were used in the study of phenol

degradation by mixed liquors of Pseudomonas putida and

activated sludge and the factor plot can be explain the

optimum levels of the nutrients [13].

3.3. Synthesis of silver nanoparticles

3.3.1. Visual identification

In this study bacterial biomass was mixed with silver

nitrate solution (pH 7.5) and incubated at 37° C for

24hours. The fig shows no change in color of the mixture

31 Nanoscience and Nanotechnology: An International Journal 2013; 3(2): 26-32

was culture biomass without addition of silver nitrate

during incubated in same condition. The appearance of

milkfish white color is a clear indication of the formation of

silver nanoparticle in the reaction mixture after 12 hrs

incubation (Fig.3 (a)). The production of nanoparticle

whitish brown in color (Fig.3(b)). The appearance of brown

color was due to the excitation of surface Plasmon

vibrations. Similar observation was made by [14] in the

Extracellular synthesis of silver nanoparticle by Aspergillus

fumigatus strain by extracellular process. The brown color

of medium could be due to excitation of surface plasmon

vibrations of silver nanoparticle. In this the optimized

culture was having dark brown in color denotes that the

good nanoparticles synthesis when compare to normal one.

Figure 3: Biosynthesis of silver nanoparticle using Bacillus

sp. (awith addition of cadmium sulphate 12 hrs incubation)

(b) 24 hrs incubation

3.3.2. UV –Vis spectrophotometer

The synthesized silver nanoparticle was primarily

characterized by UV spectrophotometer. The UV-visible

spectra recorded at different time intervals showed

increased absorbance with increasing time of incubation.

Fig. 4 illustrates the absorbance spectra of reaction mixture

containing aqueous solution of 1mM silver nitrate and the

culture supernatant of Bacillus sp. after incubation. The

intensity of the colour from the cells harvested at the

stationary phase was the maximum and also stable. The

band corresponding to the surface plasmon resonance at

410 to 430 nm. The strong peak at 420 nm. Similar time

equilibrium has been reported for Aspergillus flavus [15].

The exact mechanism for the synthesis of nanoparticles has

not been clearly established but an enzyme NADH-

dependent nitrate reductase is known to be involved in the

process [16].

Figure 4: UV-vis spectrum of bio synthesis of silver

nanoparticle by using Bacillus sp.

3.4. SEM with EDS

The morphology of the silver nanoparticles was analyzed

by using the Scanning Electron Microscope. Fig. 5(a) & (b)

shows SEM images of the optimized bacterial culture

mediated silver nano powder having spherical, pseudo

spherical and some undefined morphology with traces of

agglomeration because of the biological molecules bind

with the nanoparticles present in the bacteria [17]. The

obtained size distribution is mostly closely related sizes.

The range of particle size of the nanoparticle was found to

be in between 65 to 70 nm. In the EDX spectrum of the

bacterial mediated silver nanoparticles, the strongest peak

detected was from silver with weaker peaks from carbon

and oxygen (Fig. 6). This indicates that the biological

synthesis of silver nanoparticles is relatively unadulterated

in chemical composition. This result was closely related

with the SEM results.

Figure: 5 SEM images of the silver nanoparticles formed

by the reaction of 1 mM AgNo3 and Bacillus sp. broth

Figure 6: EDX spectrum of silver nanoparticles

4. Conclusion

Silver nanoparticles are having a lot of applications

in various fields like antimicrobials, preservatives, paints,

biosensors and cosmetics. So improving of nanoparticles

synthesis is the major object in the field of synthesis of

silver nanoparticles. The usage of bacteria is the good

approach to the production of Eco-friendly and costs

effectual silver nanoparticles. The rapid and high

production of silver nanoparticles was produced by the

optimized culture of Bacillus sp. and spherical shaped

nanoparticle was fabricated using the same. Optimization

of nanoparticles synthesis by improved production of

culture growth will giving a good prospect for the

maximum fabrication and it is very useful for the many

silver based applications.

5. Acknowledgement Author, CM UGC, India for the financial support

under Rajiv Gandhi National Fellowship (Sanction

32 Nanoscience and Nanotechnology: An International Journal 2013; 3(2): 26-32

Letter No. F.14-2(SC)/2009(SA-III)-09/2010). and authors

acknowledge DST for FIST grant (Ref no S/FST/ESI-

101/2010), Cochin University for SEM analyses.

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Source of support: UGC, India [Rajiv Gandhi National Fellowship (Sanction Letter No.F. 14-2(SC)/2009 (SA-III) -09/2010)] and

DST for FIST grant (Ref no S/FST/ESI-101/2010); Conflict of interest: None declared