Enzyme and Microbial Technology 33 (2003) 92–96

Statistical optimization of medium components for theproduction of chitinase byAlcaligenes xylosoxydans

Rajiv Vaidya, Pranav Vyas, H.S. Chhatpar∗Department of Microbiology and Biotechnology Centre, Faculty of Science, M.S. University of Baroda, Vadodara 390 002, Gujarat, India

Received 5 September 2002; received in revised form 2 April 2003; accepted 4 April 2003

Abstract

The nutritional medium requirement for chitinase production byAlcaligenes xylosoxydansIMI no. 385022 was optimized. The importantmedium components, identified by initial screening method of Plackett–Burman were Tween 20, yeast extract and chitin. Box–Behnkenresponse surface methodology was applied to further optimize chitinase production. The optimal concentration for higher production ofchitinase were (g/l): (NH4)2SO4, 1.0; KH2PO4, 1.36; MgSO4·7H2O, 0.3; Tween 20, 0.12; yeast extract, 0.3 and chitin, 15. Using thisstatistical optimization method, the chitinase production was found to increase from 12 to 29 U/ml.© 2003 Elsevier Science Inc. All rights reserved.

Keywords: Alcaligenes xylosoxydans; Box–Behnken; Chitinase; Medium optimization; Plackett–Burman

1. Introduction

Chitinases are the enzymes that degrade chitin, whichis a polymer ofN-acetylglucosamine linked by�-1,4 gly-cosidic bond. Endochitinase andN-acetylhexosaminidaseare two major enzymes of the chitinase system[1].Chitinolytic enzymes have broad range of applications:(i) cytochemical localization of chitin/chitosan usingchitinase–chitosanase–gold complex[2], (ii) fungal proto-plast technology[3], (iii) preparation of chitooligosaccha-rides[4,5], (iv) as biocontrol agents[6,7] and (v) conversionof waste chitin produced by shellfish processing industry tosingle cell protein[8,9].

Alcaligenes xylosoxydans, a novel and high chitinase pro-ducing isolate is reported to be active against fungal phy-topathogens likeFusariumsp. andRhizoctonia bataticola[10]. There are large number of reports on optimization ofcarbon and nitrogen source on classical method of mediumoptimization by changing one independent variable whilefixing all the others at a certain level. This can be extremelytime consuming and expensive for a large number of vari-ables. Conventional practice of single factor optimizationby maintaining other factors at an unspecified constant leveldoes not depict the combined effect of all the factors in-volved. The method requires a large number of experimentsto determine optimum levels, which are unreliable. Opti-

∗ Corresponding author. Tel.:+91-265-2794396; fax:+91-265-2792508.E-mail address:chhatparhs@yahoo.co.in (H.S. Chhatpar).

mizing all the effecting parameters can eliminate these lim-itations of a single factor optimization process collectivelyby statistical experimental design using Plackett–Burmanand response surface methodology (RSM)[11]. There aremany other techniques available for screening and opti-mization of process parameters[12] including non-statisticalself-optimization technique[13]. Plackett–Burman design isa well-established and widely used statistical design tech-nique for the screening of the medium components in shakeflask[14]. The design screens the important variables effect-ing the chitinase production as well as their significance lev-els but does not consider the interaction effects among thevariables. The variables screened by Plackett–Burman de-sign were further optimized in a 23 factorial Box–Behnkendesign methodology[15]. There are very few reports onthe statistical optimization for the production of chitinase.This report is an attempt to formulate a suitable productionmedium using statistical optimization that can substantiallyincrease the chitinase production byA. xylosoxydans.

2. Materials and methods

2.1. Organism, culture conditions and medium used

The cultureA. xylosoxydansIMI no. 385022, has been iso-lated in our laboratory from seafood industrial waste, iden-tified by CAB International, Surrrey, UK and was used inthe present studies. The culture conditions for the growth,

0141-0229/03/$ – see front matter © 2003 Elsevier Science Inc. All rights reserved.doi:10.1016/S0141-0229(03)00100-5

R. Vaidya et al. / Enzyme and Microbial Technology 33 (2003) 92–96 93

Table 1Plackett–Burman experimental design matrix with chitinase production

Trial no. Variablesa/levelsb Chitinase production(U/ml)

X1 X2 X3 X4 X5 X6 D1 D2 D3 D4 D5

1 + + − + + + − − − + − 16.802 − + + − + + + − − − + 15.703 + − + + − + + + − − − 25.034 − + − + + − + + + − − 9.765 − − + − + + − + + + − 13.156 − − − + − + + − + + + 20.117 + − − − + − + + − + + 3.568 + + − − − + − + + − + 16.559 + + + − − − + − + + − 12.05

10 − + + + − − − + − + + 11.2011 + − + + + − − − + − + 5.6012 − − − − − − − − − − − 4.25

a X1, (NH4)2SO4 at a high concentration of 2 g/l and a low concentarion of 0.5 g/l;X2, KH2PO4 at a high concentration of 2.72 g/l and a lowconcentarion of 0.68 g/l;X3, MgSO4·7H2O at a high concentration of 0.6 g/l and a low concentarion of 0.15 g/l;X4, Tween 20 at a high concentrationof 0.25 g/l and a low concentarion of 0.05 g/l;X5, yeast extract at a high concentration of 2 g/l and a low concentarion of 0.25 g/l;X6, chitin at a highconcentration of 15 g/l and a low concentarion of 2.5 g/l;D1, D2, D3, D4 and D5 are dummy variables.

b +, the high concentration of variable;−, the low concentration of variable.

preparation of acid swollen chitin and chitinase assay meth-ods were same as described earlier[10].

2.2. Medium for chitinase production (g/l)

Chitin, 5.0; yeast extract, 0.5; (NH4)2SO4, 1.0; MgSO4·7H2O, 0.3 and KH2PO4, 1.36. The pH of the medium wasadjusted to 8.5 and the medium was sterilized by autoclavingat 121◦C for 15 min[16].

2.3. Optimization procedure

The optimization of medium constituents for chitinaseproduction by A. xylosoxydanswas carried out in twostages.

2.3.1. Identification of important nutrient componentsTo find out the important medium components Plackett–

Burman design was followed[14] as shown inTable 1.Total number of trials to be carried out according toPlackett–Burman isk + 1 wherek is number of variables(medium components). Each variable is represented at twolevels, high and low which are denoted by (+) and (−),respectively. The number of positive signs and negativesigns per trial are (k + 1)/2 and (k − 1)/2, respectively.Each column should contain equal number of positive andnegative signs. Here six variables and five dummy variableswere screened in 12 trials, each variable being a mediumconstituent.Table 1shows design for conducting 12 trials.Each row represents a trial and each column represents anindependent or dummy variable. The effect of each variablewas determined by following equation:

E(Xi) = 2(∑

Mi+ − Mi−)

N(1)

whereE(Xi) is the concentration effect of the tested vari-able. Mi+ and Mi− are the chitinase activities from thetrials where the variable (Xi) measured was present at highand low concentrations, respectively andN is the number oftrials (12). Experimental error was estimated by calculatingthe variance among the dummy variables as follows:

Veff =∑

(Ed)2

n(2)

whereVeff is the variance of the concentration effect,Edis the concentration effect for the dummy variable andn isthe number of dummy variables.

The standard error (S.E.) of the concentration effect wasthe square root of the variance of an effect and the signif-icance level (P-value) of each concentration effect was de-termined using Student’st-test:

t(xi) = E(Xi)

S.E.(3)

whereE(Xi) is the effect of variableXi.

2.3.2. Optimization of screened componentsResponse surface methodology was used to optimize the

screened components for enhanced chitinase production us-ing Box–Behnken design[15]. The behavior of the systemwas explained by the following quadratic equation:

Y = β0 +∑

βixi +∑

βijxixj +∑

βiix2i (4)

whereY is predicted response,β0 is offset term,βi is linearoffset,βii is squared offset,βij is interaction effect, andxi

is dimensionless coded value ofXi

Statistical software package Design-Expert (Version6.0.2, State-Ease, Minneapolis, MN, USA) was used todesign and analyze experiment. A 23 factorial design, with

94 R. Vaidya et al. / Enzyme and Microbial Technology 33 (2003) 92–96

Table 2Effect estimates for chitinase production from the result of Plackett–Burman design

Factors Medium components Effect S.E. t(5) P-value Confidence level (%)

X1 (NH4)2SO4 0.903 1.3275 0.6802 0.5266 47.34X2 KH2PO4 1.727 1.3275 1.3009 0.2500 75.00X3 MgSO4·7H2O 1.950 1.3275 1.4689 0.2018 79.82X4 Tween 20 3.873 1.3275 2.9175 0.0331 96.69X5 Yeast extract −4.103 1.3275 3.0908 0.0271 97.29X6 Chitin 10.153 1.3275 7.6482 0.0006 99.94

five replicates at the centre point with total number of 17trials was employed. The coded and uncoded values of thevariables at various levels are given inTable 2.

3. Results and discussion

3.1. Screening of important media components forchitinase production by A. xylosoxydans

A. xylosoxydansproduces 12 U/ml chitinase at flask levelwith basal medium. To enhance the production of chitinase,statistical method of medium optimization was tried.Table 1represents the Plackett–Burman experimental design for 12trials with two levels of concentrations for each variable andcorresponding chitinase activity. The variableX1 to X6 rep-resents the medium constituents andX7 to X11 representsthe dummy variables/unassigned variables.Table 2 repre-sents the effect, standard error,t(5), P and confidence level.The effect of variablesX1 ((NH4)2SO4), X2 (KH2PO4), X3(MgSO4), X4 (Tween 20),X5 (yeast extract) andX6 (chitin),were found to be 0.903, 1.727, 1.950, 3.873,−4.103 and10.153, respectively. The confidence level of variablesX1((NH4)2SO4), X2 (KH2PO4) and X3 (MgSO4) are below95% and hence considered insignificant. The rest of the vari-ablesX4 (Tween 20),X5 (yeast extract) andX6 (chitin) hadconfidence level above 95% and were considered to be sig-nificant.

The above results indicated that the Plackett–Burmandesign is powerful tool for identifying factors, which hadsignificant influence on chitinase production. The exactoptimal values of the individual factors are still unknownbut can be determined by the subsequent Box–Behnkenexperiment.

3.2. Optimization of screened medium components forchitinase production by A. xylosoxydans

The variables showing confidence level above 95% inthe Plackett–Burman design were selected and further opti-mized using Box–Behnken design. Contour plots were ob-tained when the data (of chitinase production) were fed intothe design expert software, and analyzed by it. The softwarehas the function by which we can predict the production of

chitinase within studied range of all three medium compo-nents. Here each contour plot represents the effect of twomedium components at their studied concentration rangeand at fixed concentration of the third medium component.The value of third medium component was varied for thatsituation with the software and the optimum value wasfound out. Based on the results of Plackett–Burman de-sign, whereX1 ((NH4)2SO4), X2 (KH2PO4), X3 (MgSO4),were found to be non-significant, so their concentra-tion were set at their middle level in Box–Behnkendesign.

Table 3represents the experimental design and the resultsobtained for chitinase production. The variables used for thefactorial analysis were Tween 20, yeast extract and chitinfor chitinase production. The centre point in the design wasrepeated for five times for estimation of error. The actual andcoded factor levels are represented inTable 3for chitinaseproduction. Data were analyzed by linear multiple regressionusing the Design-Expert (Version 6.0.2; Stat-Ease, Inc.) andthe following equation was obtained.

Y = +20.84− 1.07x1 − 0.81x2 + 9.70x3−2.56x21−0.92x2

2

− 1.50x23 + 1.04x1x2 + 0.13x1x3 − 0.19x2x3 (5)

whereY is the predicted response andx1, x2 andx3 are thecoded values of Tween 20, yeast extract and chitin, respec-tively.

Isoresponse contour plots showing the effect of Tween 20and yeast extract, Tween 20 and chitin and yeast extract andchitin are shown inFigs. 1–3, respectively. The statisticaloptimal values of variables are obtained when moving alongthe major and minor axis of the contour and the responseat the centre point yields maximum chitinase production.From the study of the contour plots, the optimal value forconcentration ofx1, x2 andx3 (Tween 20, yeast extract andchitin, respectively) were found to be 0.12, 0.3 and 15 g/l,respectively.

To validate the regression coefficient, analysis of variance(ANOVA) for chitinase production was performed (Table 4).The values of correlation coefficient, ModelF and ModelP > F were found to be 0.9429, 6.23 and 0.0124, respec-tively which implies that the model is significant. Value oflack of fit F and lack of fitP > F were found to be 2.93and 0.1630, respectively which implies that the lack of fit is

R. Vaidya et al. / Enzyme and Microbial Technology 33 (2003) 92–96 95

Table 3Box–Behnken experimental design matrix with experimental and predicted values of chitinase production

Trial number Variables/levels Chitinase production (U/ml)

Tween 20 Yeast extract Chitin Experimental Predicted

Codedvalue

Actualvalue (g/l)

Codedvalue

Actualvalue (g/l)

Codedvalue

Actualvalue (g/l)

1 −1 0.05 −1 0.25 0 8.75 20.15 20.282 +1 0.25 −1 0.25 0 8.75 14.88 16.053 −1 0.05 +1 2.00 0 8.75 17.77 16.594 +1 0.25 +1 2.00 0 8.75 16.66 16.525 −1 0.05 0 1.13 −1 2.50 4.93 8.296 +1 0.25 0 1.13 −1 2.50 3.57 5.897 −1 0.05 0 1.13 +1 15 29.75 27.438 +1 0.25 0 1.13 +1 15 28.90 25.549 0 0.15 −1 0.25 −1 2.50 12.84 9.39

10 0 0.15 +1 2.00 −1 2.50 10.29 8.1111 0 0.15 −1 0.25 +1 15 26.95 29.1212 0 0.15 +1 2.00 +1 15 23.63 27.1313 0 0.15 0 1.13 0 8.75 15.98 20.8414 0 0.15 0 1.13 0 8.75 22.44 20.8415 0 0.15 0 1.13 0 8.75 21.34 20.8416 0 0.15 0 1.13 0 8.75 21.34 20.8417 0 0.15 0 1.13 0 8.75 23.12 20.84

non-significant. Non-significant lack of fit made the modelfit. Here the value of correlation coefficient (R) is 0.9429indicates a good agreement between experimental and pre-dicted values of chitinase production.

A. xylosoxydanswas found to produce 29 U/ml chitinasewith the statistically optimized medium, which is 141%higher than the basal medium. With the use of statisticaloptimization method, 35% increase in riboflavin production

Fig. 1. Contour plot showing the effect of Tween 20 and yeast extract onchitinase production at 15 g/l chitin.

was reported in u.v. mutant ofErmothecium ashbyii[17]and 35% higher recombinant hirudin production inSaccha-romyces cerevisiae[18].

Methodology of Plackett–Burman was found to be veryuseful for the determination of relevant variables for furtheroptimization. This made it possible to consider a large num-ber of variables and avoid the loss of information, whichmight be essential in the optimization of the process. The

Fig. 2. Contour plot showing the effect of Tween 20 and chitin on chitinaseproduction at 0.3 g/l yeast extract.

96 R. Vaidya et al. / Enzyme and Microbial Technology 33 (2003) 92–96

Table 4Analysis of variance and regression analysis for the chitinase production byA. xylosoxydansa

Source Sum of squares Degree of freedom Mean square F-value P > F

Model 816.16 9 90.68 6.23 0.0124Residual 101.89 7 14.56Lack of fit 70.02 3 23.34 2.93 0.1630Pure error 31.87 4 7.97

Corrected total 918.05 16

a Coefficient of determination(R2) = 0.8890; correlation coefficient(R) = 0.9429.

Fig. 3. Contour plot showing the effect of yeast extract and chitin onchitinase production at 0.12 g/l Tween 20.

use of these techniques has helped in finding out the im-portant medium components, which have significant effecton chitinase production. As a whole the methodology ofPlackett–Burman and Box–Behnken designs have proved tobe very effective.

Acknowledgments

We sincerely acknowledge the GSFC Science Foundation,Vadodara, India for their financial support to carry out thisresearch work. We would also like to thank Mark Anderson,Principal, Stat-Ease, Inc. Minneapolis, USA for permittingus to use his Design-Expert (Version 6.0.2) software.

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