Studies on L-Asparaginase Production by Using Staphylococcus ...

November 2012- January 2013, Vol. 3, No. 1, 201-209. e- ISSN: 2249 –1929
Journal of Chemical, Biological and Physical Sciences
An International Peer Review E-3 Journal of Sciences
Available online at www.jcbsc.org
Section B: Biological Science
CODEN (USA): JCBPAT
Research Article
<strong>Studies</strong> on L-Asparaginase Production by Using
Staphylococcus Capitis
Udaya Paglla 1 , C.S.V.R.Rao and Satish Babu Rajulapati 2*
1 DVR & Dr.HS MIC College of Technology, Kanchkacherla, (A.P) INDIA
2
National Institute of Technology Warangal (A.P) INDIA
Received: 23 September 2012; Revised: 1 November; Accepted: 4 November 2012
Abstract: L-Asparaginase is a therapeutic enzyme which is used in treatment of
different types of cancers. Many bacteria are able to produce this enzyme but it has
some side effects. If this enzyme is produced from microbe which is isolated from
medicinal plants, side effects can be reduced. This paper presents the study on
L-Asparaginase production by endophytic bacteria from Mentha Spicata. Four microbes
were isolated and tested for enzyme production. One of these microbes shown positive
results for L-Asparaginase production and it was identified as Staphylococcus capitis.
Medium composition was optimized for the improvement of L-asparaginase activity by
RSM (Response Surface Methodology). Effect of five process variables such as time,
temperature, pH, inoculum size and substrate concentration were studied on enzyme
activity. The optimized process variables were found to be pH 6.2, temperature 25°C,
substrate concentration 0.5 g, time 6 days and inoculum size was 3 ml. It was observed
that L-asparaginase activity was improved from 83 to 224 U/ml after optimization.
Keywords: L-Asparaginase, Entophytic bacteria, staphylococcus capitis, Mentha
spicata, response surface methodology, optimization
INTRODUCTION
L-Asparaginase (L-Asparaginase amino hydrolase, EC 3.5.1.1) is an amidase group of enzyme involved in
the catabolism of amino acid asparagine i.e. hydrolysis of the asparagines into aspartic acid and ammonia.
This therapeutic enzyme is mainly used in treatment different forms of cancer (acute lymphoblastic
leukemia). Asparagines are an essential amino acid which is essential for cell growth but it is not
synthesized inside the body by any metabolic pathway. Leukemic cells undergo cell division at high rate,
so they require more asparagine but leukemic cells are unable to synthesize adequate levels of asparagines.
They depend upon extracellular sources or de novo synthesis in the liver or dietary sources, for asparagines
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to synthesis different proteins. When Asparaginase was taken as the therapeutic agent, it depletes the levels
of serum asparagine. Because of that the extracellular source for Leukemic cells is not available. Normal
cells produce protein through their intrinsic metabolic pathways. But cells Leukemic cells cannot produce
protein, so undergo death. The production of L-asparaginase has been studied in various microorganisms
like E. coli 1,2 , Erwinia aroideae 3 , streptomyces griseus 4 , zymomonas mobilis 5 , Bacillus licheniformis 6 ,
Enterobacter aerogenes 7 ,Pseudomonas aeruginosa 8 , Staphylococcus sp 9 ,Thermus thermophilus 10 ,
Aspergillus tamari and Aspergillus terreus 11 , Aspergillus niger 12 .
Endophytic organisms present inside the plant tissues. Various endophytic fungi have the potential to
produce L-asparaginase. The man objective of study was characterization and screening of endophytic
bacteria isolated from mentha spicata for L-asparaginase and Response surface methodology was used to
optimize response of interest (L-asparaginase activity), which was influenced by five independent
variables i.e. time, temperature, pH, Inoculum size, substrate concentration.
MATERIALS AND METHOD
Sample collection: Mentha spicata (mint) plant leaves were used to isolate endophytic bacteria.
Sample pretreatment and isolation of endophytic bacyteria: Pretreatment was done by using three step
surface sterilization process 13 . Fresh leaves were exercised from Mentha spicata plant and washed under
running tap water to remove dust. Then leaves were washed with 70% ethanol for 2 minutes and these
leaves were placed in 2% Sodium hypo chlorite (HOCL) solution which contain Tween 20 for 10 sec
followed by washing with sterile distilled water. By using sterile mortar and pestle, pretreated leaves were
crushed. One ml of crushed sample was taken and serially diluted using potassium phosphate buffer
(12.5mM). 0.1 ml of aliquot from 10 -2 to10 -5 dilutions was taken and spread on to the nutrient agar
medium. These plates were incubated at 25°c for 5 days. Pure cultures were prepared and tested for L-
Asparaginase production.
Characterization of endophytic bacteria: Entophytic bacteria were characterized by biochemical tests.
All biochemical tests were done and the results were analyzed by Berger’s manual.
Assay for L-Asparaginase: Rapid plate assay 14 was used to screen L-Asparaginase producing bacteria
Qualitative assay: Modified M-9 agar medium was used for qualitative analysis of endophytic bacteria.
Which contain(per 1000 ml of distilled water) Na2HPO4.2H2O, 6.0g; KH2PO4, 3.0 g; NaCl, 0.5 g; L-
Asparagine, 5.0 g; MgSO4.7H2O,2.0 ml; CaCl2 .2H2O,0.1 ml; 20% glucose stock,10.0 ml; agar,20g;
2.5% dye (phenol red) stock solution was prepared in ethanol and pH was adjusted to 7.0. From this, 0.3
ml of dye (stock solution) was added to 100ml of modified M-9 medium. All endophytic bacteria were
placed on the Modified M-9 agar medium and NaNO3 (nitrogen source) was added as control to M-9
medium instead of L-Asparagine. All plates were incubated at 37°C for an 18 h. Formation of pink zone
around the bacterial colonies indicate the L-Asparaginase production by bacteria because at alkaline pH
(due to accumulation of ammonia in medium) phenol red indicator was converted to pink.
Asparaginase activiyt assay: Modified M-9 liquid medium was used to determine Asparaginase activity.
50 ml of medium was taken in 250 ml Erlenmeyer flask and inoculated with endophytic bacteria which
shown positive result in qualitative assay. This flask was incubated at 37°C at 250 rev min -1 for 48 h.
modified method of Mashburn and Wriston was used to assay L-Asparaginase activity in which 0.1 ml of
cell suspension was taken to which 0.9 ml of 0.1 M sodium borate buffer and 1 ml of 0.04 M L-
Asparaginase were added. This mixture was incubated for 10 minutes at 37°C. After 10 min 0.5 ml of 15%
trichloro acetic acid was added and centrifuged at 8000 rpm for 10 min. supernatant was collected. 0.2 ml
of supernatant was diluted to 8 ml with distilled water. This mixture was treated with Nessler’s reagent and
1 ml of 2M NaOH. This mixture was incubated at 37°C for 15 min and absorbance determined at 500 nm
was compared with Standard curve which was prepared from ammonium sulfate solution in different
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concentrations. 1 I.U (International Unit) of L-Asparaginase is equal to amount of ammonia liberated from
L-Asparagine per minute.
Protein assay: The amount of Asparaginase produced from selected endophytic bacteria was determined
by using lowery’s method 15 and absorbance was compared with standard curve which was prepared from
bovine serum albumin.
EXPERIMENTAL DESIGN AND OPTIMIZATION
Response surface methodology is a statistical technique useful for developing, improving and optimizing
the response variables to increase the response of interest. Five independent variables time, temperature,
pH, Inoculum size, substrate concentration were used, which has significant influence on L-Asparaginase
activity. RSM was used to explore true relationship between independent variables and relative responses.
The response of interest was Asparaginase activity.
Central composite design (CCD) is one of the methodology in RSM, which was used to find of optimal
concentrations of five variables.CCD has three groups of designed points i.e. two- level factorial, axial and
central points. In these regard a 2 3 factorial CCD with six Center points, ten axial points, (alpha-1) leading
to total number of 32 experiments was employed for optimization of variables. Each variable in CCD was
studied at three different levels (-1, 0, +1).where 0 is the center point between minimum and maximum
variables, -1 and+ 1 are minimum and maximum variables. Coded levels for five independent variables
were presented in Table-1
Variables
Table- 1: Codes for five variables and their experimental range
Codes
Experimental range
Minimum
(-1)
Center point
Time A 1 3.5 6
pH B 3 5 7
Temperature C 25 35 45
Inoculum size D 0.5 1.75 3
Substrate concentration E 0.5 2.25 4
(0)
Maximum
The system behavior was explained by second degree polynomial model (Eq.1) which includes all the
interaction terms of variables. Second degree polynomial model was used to calculate predicted response.
Y = b 0 +b 1 A+b 2 B+b 3 C+b 4 D+b 5 E+b 11 A 2 +b 22 B 2 +b 33 C 2 +b 44 D 2 +b 55 E 2 +b 12 AB+b 13 AC+b 14
AD+b 15 AE+b 23 BC+b 24 BD+b 25 BE+b 34 CD+b 35 CE+b 45 DE.
(Eq.1)
Where y is predicted response, b 0 mean/ intercept, b 1 b 2 b 3 b 4 b 5 were linear coefficients, b 12 b 13 b 14 b 15 b 23
b 24 b 25 b 34 b 35 b 45 were interaction coefficients, b 11 b 22 b 33 b 44 b 55 were squared coefficients.
The experiments were analyzed by using design of experiment software (MINITAB 15), Response surface
plots were generated, by taking response function on Z-axis, two independent variables on X and Y-axis
and other variables were kept constant at their center points.
RESULTS AND DISCUSSION
Isolation and charectarization of endophytic bacteria: From Mentha spicata five endophytic bacterial
colonies were isolated. Out of these, only one colony was able to produce desired enzyme and this microbe
(+1)
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was characterized as staphylococcus capitis. Enzyme activity from Staphylococcus capitis was shown in
the Fig 1.
Control
Fig.1: Proof for the production of L-Asperginase from staphylococcus capitis
Qualitative and quantitative assay for l- asparaginase: Pink zone was observed around Staphylococcus
capitis colony. The activity of L-asparaginase was observed as 83 U/ml.
Protein assay: The amount of protein produced from Staphylococcus capitis was observed as 9.6 mg/ml
from BSA standards.
Optimization using response surface methodology: CCD (Central composite design) was used to
determine the suitable concentrations of five variables and their interaction on L-asparaginase production
by Staphylococcus capitis. Experimental design and observed and predicted values of experiments carried
out by the CCD design were presented in Table- 2. After observation of data it was depicted that the
activity of L-asparaginase dependent on the combination of time, temperature, pH, Inoculum size,
substrate concentration.The data obtained from CCD was analyzed by fitted it into the second degree
polynomial model. The second degree polynomial equation (Eq. 2) for L-asparaginase production was
expressed as follows
Y= -958.804+23.807A+45.192B+1272.867C -106.887D -133.387E +2.475A 2 +23.702B 2 +65.568C 2
+148.763D 2 +10.596E 2 +19.125AB -3.575AC -3.000AD -5.857AE -5.219BC -3.750BD-14.464BE-
3.550CD-0.893CE-43.714DE. (Eq. 2)
Where A, B, C, D and E are Time, pH, Temperature, Inoculum size, substrate concentration respectively.
According to the data fitted in the equation, highest interaction was identified between time and pH i.e.
19.125.
Analysis of variance (ANOVA) of the quadratic regression equation indicated that the multiple correlation
coefficient of R 2 (R-sq) is 0.9784 i.e. the model gives 97.84% variation in the response. The goodness of
fit of the values in regression equation was explained by observing the adjusted determination coefficient,
adjusted R 2 (R 2 adj) and the value R 2 adj is 0.96.It indicated that there is a small variation between observed
and predicted values for the L-asparaginase activity, so that the proposed model provide satisfactory and
accurate results. The predicted R 2 (R 2 pred) value is 0.94.
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Table -2: Experimental and predicted values for all the trial runs carried out in the experiment
Time pH Tem. Inoculum
Substrate
Observed
Predicted
Run
size
concentration
enzyme
enzyme
Order
activity
activity
(U/ml)
(U/ml)
1. 3.5 5 35 0.5 2.25 82 72.7
2 3.5 5 35 1.75 2.25 52 62.5
3 6 5 35 1.75 2.25 184 164
4 6 7 45 3 4 124 126
5 1 3 25 3 0.5 10 8.3
6 6 7 25 3 0.5 224 224.3
7 6 7 25 0.5 4 200 205.3
8 3.5 5 35 1.75 2.25 44 62.7
9 3.5 5 45 1.75 2.25 80 80.4
10 6 7 45 0.5 0.5 160 159
11 3.5 3 35 1.75 2.25 22 10.1
12 1 5 35 1.75 2.25 12 17.9
13 3.5 5 35 1.75 4 90 65.2
14 3.5 5 35 1.75 2.25 54 62.7
15 1 7 45 0.5 4 14 14.2
16 6 3 45 3 0.5 140 139.6
17 1 3 45 3 4 18 18.8
18 3.5 5 35 3 2.25 78 73.1
19 1 7 25 0.5 0.5 12 9.6
20 3.5 7 35 1.75 2.25 32 29.7
21 1 7 45 3 0.5 20 15.2
22 6 3 25 3 4 138 297
23 6 3 25 0.5 0.5 126 15.2
24 1 7 25 3 4 14 143.9
25 3.5 5 25 1.75 2.25 109 128
26 3.5 5 35 1.75 0.5 56 15.5
27 3.5 5 35 1.75 2.25 60 94.4
28 6 3 45 0.5 4 144 148.6
29 3.5 5 35 1.75 2.25 48 62.7
30 1 3 45 0.5 0.5 16 12.9
31 1 3 25 0.5 4 9 12.2
32 3.5 5 35 1.75 2.25 62 62.7
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Table- 3: Analysis of variance (ANOVA) for all the terms
Source
Sum of
squares
Degree
of freedom
Mean
squares
F-value Probe >F
Regression 20 11555914 577796 24.96
Linear 5 9870044 1974009 85.26
Square 5 1001407 200281 8.65 0.002
Interaction 10 684462 68446 2.96 0.045
Residual Error 11 254673 23152
Lack-of-Fit 6 230940 38490 8.11 0.018
Pure Error 5 23733 4747
Total 31 11810588
RESULTS AND DISCUSSION
CCD (Central composite design) was used to determine the suitable concentrations of five variables and
their interaction on L-asparaginase production by Staphylococcus capitis. Experimental and predicted
values of experiments carried out by the CCD design were presented in Table 2. After observation of data
it was depicted that the activity of L-asparaginase dependent on the combination of time, temperature, pH,
Inoculum size, substrate concentration. The data obtained from CCD was analyzed by fitted it into the
second degree polynomial model. The second degree polynomial equation (Eq. 2) for L-asparaginase
production was expressed as follows
Y= -958.804+23.807A+45.192B+1272.867C -106.887D -133.387E +2.475A 2 +23.702B 2 +65.568C 2
+148.763D 2 +10.596E 2 +19.125AB -3.575AC -3.000AD -5.857AE -5.219BC -3.750BD-14.464BE-
3.550CD-0.893CE-43.714DE. (Eq. 2)
Where A, B, C, D and E are Time, pH, Temperature, Inoculum size, substrate concentration respectively.
According to the data fitted in the equation, highest interaction was identified between time and pH i.e.
19.125.
Analysis of variance (ANOVA) of the quadratic regression equation indicated that the multiple correlation
coefficient of R 2 (R-sq) is 0. i.e. the model gives 97.84% variation in the response. The goodness of fit of
the values in regression equation was explained by observing the adjusted determination coefficient,
adjusted R 2 (R 2 adj) and the value R 2 adj is 0.96. It indicated that there is a small variation between
observed and predicted values for the L-asparaginase activity, so that the proposed model provides
satisfactory and accurate results. The predicted R 2 (R 2 pred) value is 0.94.
Residual plots showing the distribution between experimental and predicted values was presented in
Fig. 2. Three dimensional surface graphs showing interaction between variables were presented in Fig. 3.
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Percent
9 9
9 0
5 0
1 0
R e s i d u a l P l o t s f o r e n z y m e a c t i v i t y ( u / m l )
N o r m a l P r o b a b i li t y P l o t
Residual
V e r s u s F it s
2 0 0
1 0 0
0
- 1 0 0
1
- 2 0 0
- 1 0 0
0
R e s i d u a l
1 0 0
2 0 0
- 2 0 0
0
5 0 0
1 0 0 0 1 5 0 0
F i t t e d V a l u e
2 0 0 0
H is t o g r a m
V e r s u s O r d e r
Frequency
1 2
9
6
3
Residual
2 0 0
1 0 0
0
- 1 0 0
0
- 2 0 0
- 1 0 0
0
R e s i d u a l
1 0 0
2 0 0
- 2 0 0
2
4
6
8
1 0 1 2 1 4 1 6 1 8 2 0 2 2 2 4
O b s e r v a t i o n O r d e r
2 6
2 8
3 0
3 2
Fig. 2: Residual plots showing the distribution between experimental and predicted values
A
B
C
D
Fig. 3(a): shows the response for the interactive factors; pH and time when inoculum size, substrate
concentration, temperature were kept constant, Fig. 3(b): shows the response for the interactive ;
factors; temperature and pH, when time, substrate concentration, inoculum size were kept constant.
Fig. 3(c): shows the response for the interactive factors; inoculum size and pH when temperature,
time, substrate concentration. Fig. 3(d): shows the response for the interactive factors; substrate
concentration and pH when Temperature, time, Inoculum size were kept constant
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DISCUSSION
The optimum conditions for L-Asparaginase activity were pH 6.2, temperature 25°C, substrate
concentration 0.5 g, time 6 days and inoculum size 3 ml. From the response surface regression coefficients
the variable showing higher influence on the production of L-asparaginase is pH followed by inoculum
size, substrate concentration, temperature and time. The analysis was performed by un coded units. The
experimental values were in close agreement with statistically predicted values i.e. Predicted value is 224.3
and the observed value is 224 shows the authenticity of the model. The maximum activity of L-
asparaginase under optimized conditions is 224 U/ml.
CONCLUSION
The application of RSM for optimization of L-asparaginase activity allows quick identification of the
important variables and interactions between them. The essential step in the use of RSM experimental
design methods is to select the suitable ranges of the selected variables in the initial experiments. The
eventual objective of RSM is to determine the optimum operating conditions for the system or to determine
a region of the factor space in which operating specifications are satisfied. Since RSM is used to study the
influence of several variables on response by varying them simultaneously in a limited number of
experiments, it was thought to fit the scope of this study. The CCD methods allowed to study and explore
conditions in just 32 experimental runs with an overall 96% increase in L-asparaginase production in
optimized conditions. This work has demonstrated the use of a central composite design by determining
conditions leading to maximum L-asparaginase activity. Central composite experimental design maximizes
the amount of information that can be obtained, while limiting the numbers of individual experiments
required. The enzyme specific activity predicted by the model at optimal conditions agreed fittingly with
experimental data, thus confirming the model validity.
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*Correspondence Author: Satish Babu Rajulapati; National Institute of Technology
Warangal,A.P, INDIA
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