This article was downloaded by: [Pennsylvania State University]On: 30 August 2013, At: 18:00Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

Separation Science and TechnologyPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/lsst20

Application of Response Surface Methodology toOptimize Three Phase Partitioning for Purification ofLaccase from Pleurotus ostreatusVaidyanathan Vinoth Kumar a , Vasanthakumar Sathyaselvabala a , Selvaraj Dinesh Kirupha a ,Arukkani Murugesan a , Thangaraj Vidyadevi a & Subramanian Sivanesan aa Department of Chemical Engineering, Environmental Management Laboratory, A.C. Collegeof Technology, Anna University-Chennai, Chennai, Tamil Nadu, IndiaAccepted author version posted online: 05 Jul 2011.Published online: 03 Oct 2011.

To cite this article: Vaidyanathan Vinoth Kumar , Vasanthakumar Sathyaselvabala , Selvaraj Dinesh Kirupha , ArukkaniMurugesan , Thangaraj Vidyadevi & Subramanian Sivanesan (2011) Application of Response Surface Methodology to OptimizeThree Phase Partitioning for Purification of Laccase from Pleurotus ostreatus , Separation Science and Technology, 46:12,1922-1930, DOI: 10.1080/01496395.2011.583306

To link to this article: http://dx.doi.org/10.1080/01496395.2011.583306

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) containedin the publications on our platform. However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.

This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Application of Response Surface Methodology to OptimizeThree Phase Partitioning for Purification of Laccase fromPleurotus ostreatus

Vaidyanathan Vinoth Kumar, Vasanthakumar Sathyaselvabala, Selvaraj DineshKirupha, Arukkani Murugesan, Thangaraj Vidyadevi, and Subramanian SivanesanDepartment of Chemical Engineering, Environmental Management Laboratory, A.C. College ofTechnology, Anna University-Chennai, Chennai, Tamil Nadu, India

We used a novel approach to purify Pleurotus ostreatus laccaseusing the three phase partitioning (TPP) methodology. The aim ofour research was to study the effect of TPP parameters on laccasepurity and yield. The response surface methodology (RSM) hasbeen applied to design the experiments to evaluate the interactiveeffects of the three most important operating variables: ammoniumsulphate saturation (w/v) (20–80%), ratio of crude extract tot-butanol (v/v) (1:1 to 1:3), and temperature (20–60�C). Using thismethodology, the optimum values for the critical components wereobtained as follows: ammonium sulphate saturation (w/v),50–60%; ratio of crude extract to t-butanol (v/v) 1.0:1.8; tempera-ture 42–45�C, respectively. Under optimal conditions, the experi-mental laccase yield and purity was 184% and 7.22-fold,respectively. SDS-PAGE and RP-HPLC revealed that the laccasewas purified by TPP. The determination coefficients (R2) were0.9891 and 0.9728 for laccase purity and yield, respectively, indicat-ing an adequate degree of reliability in the model. To our knowl-edge, the present work demonstrates for the first time thesuccessful application of RSM to TPP.

Keywords laccase; response surface methodology; three phasepartitioning

INTRODUCTION

Downstream processing costs are an extremely impor-tant factor as these constitute up to 80% of the overallproduction costs of proteins=enzymes. Purification of pro-tein is usually an important post-production step; it is gen-erally difficult to do, despite the development of a range oftechniques. Purification difficulties led to the developmentof interfacial protein enrichment method, called three-phase partitioning (TPP), which was first used by Tanand Lovrein in 1972 (1). The TPP system is able to precipi-tate and collect proteins as a separate layer formed between

aqueous and organic phases with the aid of a dissolvedinorganic salt (generally ammonium sulphate) and tert-butanol. This method has been successfully employed forthe purification of various proteins mainly due to itssimplicity, easy of handling, being feasible at room tempera-ture, inexpensive, and environmental friendly (2–15). TPPhas been successfully used in the purification of proteins likecellulase (2,3), amylase (2), pectinase (3), glucoamylase (3),pullulanase (3), a-galactosidases (2,15), alkaline phospha-tase (2,12), peroxidase (8,11), protease (2,14), phospholipase(6), aryl alcohol oxidase (5), carbonic anhydrase, catalaseand superoxide dismutase (2), invertase (2), amylase, andprotease inhibitor (4). It has been used both for upstreamand downstream protein purification processes and hasat the same time been used as a one-step purificationprotocol (6).

The ultimate objective of protein is to achieve both highyield and purity. Like other techniques, the efficiency ofTPP purification can be affected by factors including thenatural properties of the target protein (pH, isoelectricpoint, hydrophobicity, concentration, solubility, and dena-turation of the protein) and purification conditions(ammonium sulphate saturation, ratio of crude extract tot-butanol and temperature) (8,11,13,14). To obtain bothhigh yield and purity, it is important to understand therelationship between these two goals and the purificationfactors and to optimize purification conditions accordingly.The partitioning of proteins in TPP purification is influ-enced by factors such as ammonium sulphate saturation,ratio of crude extract to t-butanol, and temperature(2–4,11–14).

In general, process optimization by the traditional tech-nique of varying one variable at a time to achieve optimaloutput is used (16). The classical approach for optimizationinvolves the change of one variable at a time, which is tedi-ous, extremely time consuming, and expensive if a largenumber of variables are involved. This method does notbring about interaction between various parameters and

Received 15 December 2010; accepted 19 April 2011.Address correspondence to Subramanian Sivanesan, Chemical

Engineering, A.C. College of Technology, Chennai-25, Chennai-600025, Tamil Nadu, India. Tel.: 91-044-22359166; Fax:91-044-22359166. E-mail: sivanesh@yahoo.com

Separation Science and Technology, 46: 1922–1930, 2011

Copyright # Taylor & Francis Group, LLC

ISSN: 0149-6395 print=1520-5754 online

DOI: 10.1080/01496395.2011.583306

1922

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

often leads to an incomplete understanding of system beha-vior, resulting in unclear results and a lack of accuracy (17).To overcome these difficulties, a statistical approach suchas response surface methodology (RSM) can be used asan alternative optimization tool. The RSM approach tooptimization requires first an experimental design and thenfitting experimental data into an empirical model equationto determine the optimum conditions (17,18,19). RSM isan efficient mathematical approach widely applied in theoptimization of purification processes, including immobi-lized metal affinity chromatography (IMAC) (20), dyeligand affinity membrane chromatography (21), reversemiceller extraction (22), and aqueous two phase extraction(ATPE) (23–25). It can give information about the interac-tion between variables, provide the information necessaryfor design, and process optimization, simultaneously.

Response surface procedures are not only primarily usedfor the purpose of allowing the researchers to understandthe mechanism of the system or process, but also to deter-mine the optimum conditions or to determine a region forthe factors at a certain operating specifications are met(19). The application of statistical experimental designtechniques in purification processes could result inimproved product yields and purity, reduced process varia-bility, closer confirmation of the output response to nom-inal and targeted requirements, as well as reduceddevelopment time and overall costs (18).

In the present work, we performed small-scale batchtype TPP in 50mL centrifuge tubes in order to easilymanipulate a variety of purification conditions. The objec-tive of this work is to optimize TPP purification conditionsusing RSM. This was achieved by examining the effect ofoperating parameters such as ammonium sulphate satu-ration, ratio of crude extract to t-butanol, and temperatureon the TPP purification. To our knowledge, the presentwork demonstrates for the first time the successful appli-cation of RSM optimization to TPP.

MATERIALS AND METHODS

Microorganism, Chemicals, Substrates, and Inoculum

Pleurotus ostreatus was obtained from Tamilnadu Agri-culture University (TNAU), Coimbatore, India and main-tained on malt extract agar slants and stored at 4�C inrefrigerator (5). In our previous report, we found thatPleurotus ostreatus has ability to produce laccase (5). Mol-ecular weight markers, 2,20-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and veratryl alcohol were obtainedfrom Sigma Chemical Co., St Louis, Missouri. All the che-micals and reagents used were of analytical grade. In ourlab, we found that Sago hampas (SH) was the best substratefor the maximum production of laccase. SH was choppedinto small pieces and dried in an oven at 60�C to 5%(w=w) moisture content. It was ground to powder form

(40mm particle size) prior to its use in SSF. Inoculum wasprepared by harvesting spores from 6-d old culturegrown on wheat bran in sufficient sterile distilled water con-taining 0.1% of tween 80 in order to give the desired sporeconcentration.

Fermentation Media

Pilot scale solid state fermentation was carried out inenamel coated metallic trays (45� 30� 4 cm) containing300 g of SH moistened with 300mL mineral salt solution(1.0:1.0w=v) composed of malt extract 1%; yeast extract0.4%; glucose 0.4%; 0.1% veratryl alcohol; 5mM l-tyrosineand the initial pH of the cultures were 6.3, autoclaved andinoculated with 10% (w=v). The contents of the trays weremixed before and after inoculation. The trays were coveredwith aluminum foil and incubated in a temperature controlchamber at 30�C. At selected times duplicate trays weretaken out of the chamber, buffer was added to the fermen-ted mass, the suspensions were stirred and centrifuged at10000 g for 30min and the supernatant was filtered throughWhatman No. 1 filter paper and the enzyme activities weredetermined in the filtrate.

Laccase Assay

The laccase activity was determined using 2,20-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) as the sub-strate (26). The laccase reaction mixture contained0.5mL of 0.45mM ABTS, 1.2mL of 0.1M phosphate buf-fer (pH 6.0) and 0.5mL of filtrate to give a final reactionvolume of 2.2mL. The oxidation of the substrate (ABTS)was monitored by the increase in the absorbance at 420 nm,over 90 s at 30�C (�2�C), using e¼ 3.6� 104 cm�1M�1.Enzymatic activity was expressed as 1U¼ 1 mmol of ABTSoxidized per min at 25�C (�1).

Three-Phase Partitioning (TPP)

Purification of the laccase enzyme was performed byTPP for a one-step purification step based on a modifiedprocedure reported by Dhananjay and Mullimani (15). Inorder to adopt the mentioned procedure to our study, thecrude enzyme solution (5.26U=ml at pH 4.2) was broughtto 20, 30, 40, 50, 60, 70, and 80% (w=v) saturations usingammonium sulphate (Table 1). To this solution, tert-buta-nol was added in order to obtain 1:0.5, 1:1, 1:1.5, 1:2, 1:2.5,1:3 (v=v) ratio of crude enzyme to tert-butanol at the speci-fied temperature (Table 1). After incubation for 1 h at 20,30, 40, 50, and 60�C, the mixture was centrifuged(2000� g for 5min) to facilitate the separation of phases.The lower aqueous layer and the interfacial precipitatewere collected; the latter was dissolved in 0.1M sodiumphosphate buffer, pH 4.0. Protein concentration wasdetermined by Lowry’s method using bovine serumalbumin as the standard (27).

PURIFYING PLEUROTUS OSTREATUS USING TPP METHODOLOGY 1923

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

Response Surface Methodology Design

In the present study, the effects of operating parametersof TPP were optimized using RSM (28,29). Based onexperience and economic feasibility, a (Box-BehnkenDesign) BBD was employed (30,31). The experimental fac-tors were ammonium sulphate saturation; 20–80% (w=v),ratio of crude extract to t-butanol; 1.0:1.0–1.0:3.0 (v=v)and temperature; 20–60�C as shown in Table 2. The morethe experimental factors selected for RSM, the more accu-rate the empirical model equation. However, too many fac-tors can create a more complicated model equation,resulting in an increase in the number of experiments tobe performed. In some cases, experimental error increasesas both the number of experiments and the time requiredincrease. Therefore, it is important to select an appropriatenumber of critical purification factors in an experimental

design. The total number of experimental runs was 17 withreplications and the yield and purity of laccase was takenas the dependent variable or response as shown in Table 3.

Statistical analysis of the model was performed to evalu-ate the analysis of variance (ANOVA). This analysisincluded Fisher’s F-test (overall model significance), itsassociated probability P (F), and determination coefficientR2 which measures the goodness of fit at regression models.For each variable, the quadratic model was represented ascontour plates (3D) and the response surface curves weregenerated using Design expert 8.0 trial version.

SDS-PAGE Analysis

For calculation of the protein molecular mass,SDS-PAGE was carried out with a 10% gel, as describedby Laemmli (32). Molecular weight markers were usedaccording to the instructions provided by the manufacturer(High Molecular Weight Markers Kit, Cat no. SDS-6H).After running the gel, the proteins were stained by Coo-massie brilliant blue R-250.

RP-HPLC Analysis of TPP Purified Laccase

Purity of the enzyme was confirmed by RP-HPLC(Reverse Phase – High Performance Liquid Chromato-graphy) analysis using Agilent 1100 HPLC system.RP-HPLC was carried out according to the method ofDivakar et al., 2010 (33). The purified laccase was appliedon to C-18 column (Zorbax C-18, 4.6mm� 250mm i.d.,5 mm particle size, Agilent technologies).

TABLE 1Classical optimization of process conditions used for TPP of the laccase

Ammoniumsulphate (w=v)

Crude extractto t-butanol (v=v) Temperature (�C) Yield (%) Purity (fold)

20 1.0:1.0 40 68� 2.4 1.3� 0.1630 1.0:1.0 40 86� 3.3 1.4� 0.1140 1.0:1.0 40 103� 3.1 1.9� 0.2050 1.0:1.0 40 111� 3.8 1.9� 0.2360 1.0:1.0 40 97� 3.1 1.6� 0.2070 1.0:1.0 40 65� 1.5 1.3� 0.0680 1.0:1.0 40 40� 2.4 0.8� 0.0650 1.0:0.5 40 86� 2.1 1.3� 0.1250 1.0:1.5 40 116� 7.8 2.1� 0.1650 1.0:2.0 40 110� 4.9 1.8� 0.1150 1.0:2.5 40 72� 3.6 1.1� 0.2350 1.0:3.0 40 48� 2.0 0.8� 0.2050 1.0:1.5 20 81� 0.8 1.6� 0.1550 1.0: 1.5 30 96� 1.5 1.9� 0.3350 1.0: 1.5 50 70� 1.3 1.5� 0.1550 1.0: 1.5 60 52� 1.8 1.1� 0.09

Note: Each experiment was carried out in duplicate and the difference in the reading was less than �5%.

TABLE 2Experimental factors and coded levels in the three factorthree-level response surface design used for optimizing

the purity and yield of laccase

Coded units

Experimental factors Symbol � 0 þ

(NH4)2SO4 saturation (%) A 20 50 80Ratio of crude extractto t-butanol (v=v)

B 1:1 1:2 1:3

Temperature (�C) C 20 40 60

1924 V. V. KUMAR ET AL.

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

RESULTS AND DISCUSSION

Preliminary TPP of Laccase

To employ a statistical approach for optimization of lac-case TPP purification, it was necessary to first gain infor-mation about purification factors and the nature of theexperiments. TPP purification was optimized by the tra-ditional technique of varying one variable at a time toachieve optimal yield and purity. Therefore, preliminaryTPP purification was performed with the 2.11mg=ml pro-tein concentration (containing 5.26U=ml of laccase). Vari-ous experiments at different saturations of ammoniumsulphate (%), different crude extract to tert-butanol ratio(v=v), and different temperatures (�C) as given in Table 1were performed. As it is seen, all these three parametershave a major influence on the purification of the laccase.For example, an increase of the saturation level ofammonium sulphate from 30 to 50%, at 1:1 crude extractto tert-butanol (v=v) ratio and 40�C, increased the yieldby 111% and purification by 1.9-fold; however, furtherincrease to 60% saturation decreased the same responsesby 97% and 1.6-fold, respectively.

The effect of the crude extract to tert-butanol (v=v) ratiowas also very considerable where the change from 1:1 to1:1.5, increased the yield and purity by 116% and 2.1-fold,respectively. Similarly, an increase of the temperature from40 to 50�C reduced the yield and purity by 70 and 1.5-fold,respectively. Based on these observations the best resultswere obtained at 50% saturation with ammonium sulphate,

1:1.5 (v=v) ratio of crude extract to tert-butanol andtemperature 40�C. The results of the preliminary TPP areshown in Table 1. Results showed that 116% yield and2.16 fold purification were obtained in the precipitate.The preliminary TPP purification (Fig. 1) provided impor-tant information regarding each purification factor and thisinformation was used in RSM experiments. At this stage,proteins were not completely separated for satisfactorypurity and yield and further fine tuning of optimizationof accurate TPP conditions was needed.

Development of Regression Model

The experimental results of the BBD were fitted with asecond order polynomial equation. The values ofregression coefficient were calculated, and the fitted equa-tions (in terms of coded value) for predicting laccase yieldand purity were given succeedingly regardless of the signifi-cance of the coefficients:

Yield ¼ 169þ 2:38A� 21:88Bþ 16:50C þ 1:25AB

þ 9:0AC � 18BC � 52:63A2

� 44:13B2 � 33:88C2

ð1Þ

Purity ¼ 6:94þ 0:95A� 0:75Bþ 0:60C � 1:05AB

þ 0:12AC þ 0:38BC � 2:14A2

� 2:37B2 � 2:44C2

ð2Þ

TABLE 3Box Behnken design matrix for the experimental design and predicted results for laccase purity and yield

Factors Actual Predicted

OrderAmmonium

sulphate (w=v)t-butanol to

crude extract (v=v) Temperature (�C) Purity (fold) Yield (%) Purity (fold) Yield (%)

1 80 1:1 40 5.6 85 5.19 95.252 80 1:2 60 3.66 114 4.03 110.33 50 1:3 20 1.19 64 1.15 70.624 20 1:3 40 1.37 57 1.78 46.755 80 1:3 40 1.79 59 1.58 546 80 1:2 20 2.35 61 2.59 59.377 20 1:1 40 0.98 88 1.19 838 20 1:2 20 1.31 69 0.93 729 50 1:2 40 7.22 184 6.94 169

10 50 1:2 40 6.66 176 6.94 17011 50 1:2 40 6.85 161 6.94 16912 50 1:2 40 7 165 6.94 16913 50 1:1 60 3.84 154 3.84 15414 20 1:2 60 2.14 86 1.89 87.6215 50 1:2 40 6.97 159 6.94 16916 50 1:1 20 1.73 87 1.89 78.317 50 1:3 60 1.76 59 1.59 67.6

PURIFYING PLEUROTUS OSTREATUS USING TPP METHODOLOGY 1925

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

where A, B, C are ammonium sulphate saturation, ratio ofcrude extract to t-butanol and temperature, respectively.The statistical significance of Eqs. (1) and (2) was checkedby ANOVA for response surface quadratic model and issummarized in Tables 4 and 5. The regression analysis indi-cates that all the three parameters had significant influenceon the laccase purity and yield, which was confirmed by theP-values of the analysis (Table 4). The ANOVA indicatedthat the model F value for the overall regression model issignificant at 5% and the lack of fit is insignificant, indicat-ing that the first-order model with interaction is adequate.

The regression model provided accurate description of theexperimental data indicating successful correlation amongthe three TPP purification parameters that affect the yieldand purity of laccase. This was further supported by thevalue of the correlation coefficient, R

2. The mathematical

adjustment of those values generated R2¼ 0.9728

(97.28%) for laccase yield and R2¼ 0.9891 (98.91%) forpurity, revealing that the model was unable to explain only2.72% and 1.09% of the overall effects, demonstrating it tobe a robust statistical model. Adjusted R

2value of 0.9751

(97.51%) for purification and 0.9371 (93.71%) suggestedthat the model was significant. A very low value of coef-ficient of variation (CV %) for laccase yield (11.02) andpurity (10.57) clearly indicate precision and a good dealof reliability of experimental values.

Effects of Process Parameters and Optimization

Figure 2 represents the relationship between the actualand predicted laccase purity and yield. The cluster of mea-surements near the diagonal line in the parity plot indicatesa good fit of the model and demonstrates a satisfactorycorrelation between the actual and predicted values. Theminimum laccase yield of 57% was obtained with the mini-mum purity of 1.37 fold at ammonium sulphate (%) 20,ratio of crude extract to t-butanol (v=v) 1:3, and tempera-ture 40�C. However, a maximum yield of 184% wasobtained with a purity of 7.22 fold, which occurs withammonium sulphate (%) 50, ratio of crude extract tot-butanol (v=v) 1:2, and temperature of 40�C (Table 3).

The three dimensional (3D) response surface graphs forlaccase yield and purity based on the final model are

FIG. 1. SDS- PAGE analysis of purified laccase using TPP from

Pleurotus ostreatus.

TABLE 4Regression coefficients and their significance in the quadratic model of laccase purity and yield

Purity Yield

SourceSum ofsquares Df

Meansquare

P valueProb>F

Sum ofsquares Df

Meansquare

P valueProb>F

Model 95.61 9 10.62 <0.0001 35147.99 9 3905.33 0.0001A 7.22 1 7.22 0.0002 45.13 1 45.13 0.5884B 4.56 1 4.56 0.0009 3828.13 1 3828.13 0.0012C 2.90 1 2.90 0.0032 2178 1 2178 0.0056AB 4.41 1 4.41 0.0010 6.25 1 6.25 0.8389AC 0.058 1 0.058 0.5559 324 1 324 0.1724BC 0.59 1 0.59 0.0877 1296 1 1296 0.0189A2 19.19 1 19.19 <0.0001 11660.59 1 11660.59 <0.0001B2 23.65 1 23.65 <0.0001 8197.96 1 8197.96 0.0001C2 25.07 1 25.07 <0.0001 4831.64 1 4831.64 0.0006Residual 1.05 7 0.15 982.25 7 140.32Lack of Fit 0.89 3 0.30 0.0457 528.25 3 176.08 0.3322Pure error 0.17 4 0.042 454 4 113.50Cor Total 96.66 16 36310.24 16

1926 V. V. KUMAR ET AL.

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

depicted in Fig. 3. The response at the central point corre-sponds to a maximum degree of achievable laccase yieldand purity for that set of variables. The experimentalresults clearly showed that laccase purification by TPPheavily depends on ammonium sulphate saturation, ratioof crude extract to t-butanol, and temperature. Almostall interactions in the designed experiments yielded a‘‘spherical’’ or ‘‘nearly spherical’’ variance function. Thisindicated that the effects of variables are both individualas well as interrelated, allowing for the prediction ofoptimum concentration levels for maximized laccase yieldand purity.

One of the important parameters in TPP is the concen-tration of ammonium sulphate used for precipitating theprotein in the interfacial phase. As the result obtained,the system consisted of 50% ammonium sulphate, whichseemed to be the optimum condition for laccase partition-ing due to its highest laccase yield at the interphase (Fig. 3).However, this fraction gave low enzyme purity. While thehighest purity was found in the interfacial phase of the sys-tem contained 60% ammonium sulphate (Table 3). Theeffect of ammonium sulphate on the TPP is significant withincreasing ammonium sulphate concentration up to

50–60%. Further increase in ammonium sulphate concen-tration decreases the laccase yield and purity. This is alsovalidated by theoretical study. The increase in ammoniumsulfate saturation does not influence the protein content inthe interfacial precipitate because at the higher saturations,most of the ammonium sulfate remained insoluble (in pres-ence of t-butanol) indicating that its solubility limit hasbeen crossed (visual observations) (11).

The protein purification process was carried out at lowtemperatures. Although the requirement of low tempera-tures in TPP has not been clearly reported, it has been sug-gested in new systems (2). This present study, demonstratesthat temperature was a critical parameter for laccase separ-ation in TPP. The laccase yield was increased with theincrease in temperature up to the optimum level(42–45�C), after which the yield declined and the purityalso dropped (Fig. 3). Lowering the temperature led todecrease in the activity yield but no significant change inspecific activity. Laccase yield and purity were decreasedat the higher temperature as in comparison to 42–45�C.This may be due to the combined effect of ammonium sul-phate and t-butanol along with temperature coming intoplay, which leads to denaturation of enzyme. Because ofthe differences in yield and purity at different temperatures,42–45�C was considered to be convenient and economicalfor further studies.

The ratio of crude extract to t-butanol is also ratherimportant in TPP. t-butanol has been found to consistentlyperform better than all other organic solvents (2,7,15,34),because of its size and branched structure, and it doesnot easily permeate inside the folded protein moleculesand hence does not cause denaturation (2,7,34). From the3D plots, maximum laccase yield and purity was observedat an optimum ratio of t-butanol to crude extract was 1.8

TABLE 5Model fitting for laccase purity and yield

Values

Model terms Purity Yield

Coefficient of variance 10.57 11.02R2 0.9891 0.9728Adjusted R2 0.9751 0.9371

FIG. 2. Relationship between the actual and predicted laccase yield and purity.

PURIFYING PLEUROTUS OSTREATUS USING TPP METHODOLOGY 1927

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

TABLE 6TPP of Laccase from Pleurotus ostreatus

StepsEnzyme activity

(U)Protein concent

(mg)Specific activity

(U=mg)Purity(fold)

Yield(%)

Crude 5.26 2.11 2.5 1� 0.0 100� 0.0Preliminary TPP – Precipitate� 6.10 1.13 5.4 2.16� 0.14 116� 8.3Preliminary TPP – Aqueous phase� 2.84 1.06 2.67 1.06� 0.22 54� 3.9RSM optimized TPP – Precipitateþ 9.67 0.72 18.0 7.22� 0.36 184� 7.2RSM optimized TPP – Aqueousphaseþ

3.39 0.98 3.45 1.38� 0.15 64� 3

�Preliminary TPP conditions – Temperature 40� 2�C; ammonium sulphate saturation 50% (w=v); ratio of crude extract to t-butanol1.0: 1.5 (v=v); pH 4.0.

þRSM Optimized TPP conditions – Temperature 43� 2�C; ammonium sulphate saturation 60% (w=v); ratio of crude extract tot-butanol 1.0: 1.8 (v=v); pH 4.0.

FIG. 3. a–f Response surfaces showing the effect of ammonium sulphate, ratio of crude extract to t-butanol, and temperature on laccase yield and

purity.

1928 V. V. KUMAR ET AL.

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

(v=v) (Fig. 3). Decreasing the t-butanol volume in the com-bined effect of ammonium sulfate results in decreasedpurity and yield was observed in the interfacial precipitate.Increasing the t-butanol volume leads to decrease inenzyme yield and purity; this may be due to high viscosityin the top phase and enzyme inactivation (6,34). UsingRSM, optimum conditions for laccase yield and purity byTPP, respectively, were found to be ammonium sulphatesaturation 50–60% (w=v), ratio of crude extract to t–buta-nol 1.0:1.8 (v=v), and temperature (42–45�C).

Overall Purification

Using RSM, optimum conditions for laccase yield andpurity by TPP, respectively, were found to be ammoniumsulphate saturation 50–60% (w=v), ratio of crude extractto t–butanol 1.0:1.8 (v=v), and temperature (42–45�C).We compared the purification based on the RSM opti-mized TPP conditions with those from the preliminaryTPP (Table 6 and Fig 1). This comparison showed thatconditions derived from the RSM optimized TPP purifi-cation strategy resulted in the best combination of laccaseyield (184%) and purity (7.22) (Table 6). The fractions ofthe interfacial precipitate arising from the preliminaryand RSM optimized TPP were analyzed by SDS-PAGE.In preliminary TPP, the direct precipitation of crudeextracts, laccase became part of the interfacial precipitatewith other proteins and revealed four protein bands, oneof which possessed laccase activity. RSM optimized TPPwhich having the specific activity of the purified P. ostrea-tus laccase was 18U=mg of protein and the molecular massof laccase was estimated to be 72 kDa (Fig. 1). The molecu-lar mass of the enzyme reported here is similar to that of thelaccase fromTramates sp (36). Also, values of 72.7 kDa havebeen described for laccase fromMyrioconium sp (37). Purity

of the enzyme was confirmed by RP-HPLC analysis. It waseluted as a single peak with retention time of 15.09min in areverse phase C-18 column as shown in Fig. 4.

TPP is an efficient purification technique, where remark-able increase in the yield of various enzymes were reportedpreviously like inveratse (1000%) (2), Ipomea peroxidase(976%) (11), and Calotropis procera latex protease (165%)(14). Singh et al., 2001 attributed the increase in enzymeactivity due to a higher concentration of B-factor asobserved by X-ray diffraction studies (35). They alsoreported that enzyme activation frequently observed dur-ing TPP may be a result of increased flexibility in theenzyme molecule. These unusual percentage yields werebelieved to be due to adopting a number of amino acidresidues on the enzyme molecule (14).

CONCLUSIONS

RSM was performed to optimize the TPP parametersfor laccase purification from P. ostreatus. RSM appliedin this work proved to be efficient for optimizing enzymeyield and purity by TPP providing suitable designs andmodels for the experiments. The optimum conditionsdeveloped in this experimental setup achieved laccase yieldof 184% and 7.22 fold purity. From this it is clear thatfurther investigations on laccase purification by TPP at apilot scale could be highly beneficial.

REFERENCES

1. Tan, K.H.; Lovrein, R. (1972) Enzymology in aqueous-organic

cosolvent binary mixtures. J. Biol. Chem., 247 (10): 3278–3285.

2. Dennison, C.; Lovrein, R. (1997) Three phase partitioning: Concen-

tration and purification of proteins. Protein Expr Purif., 11: 149–161.

3. Mondal, K.; Jain, S.; Teotia, S.; Gupta, M.N. (2006) Emerging oper-

ation in protein bioseparation. Biotechnol Ann Rev., 12: 1–29.

4. Saxena, L.; Iyer, B.K.; Ananthanarayan, L. (2007) Three phase par-

titioning as a novel method for purification of ragi (Eleusine coracana)

bifunctional amylase=protease inhibitor. Process. Biochem., 42: 491–

495.

5. Vinothkumar, V.; Rapheal, V.S. (2010) Induction and purification by

three-phase partitioning of aryl alcohol oxidase (AAO) from Pleurotus

ostreatus. Appl. Biochem. Biotechnol., 163: 423–432.

6. Sharma, S.; Gupta, M.N. (2001) Purification of phospholipase D from

Dacus carota by three-phase partitioning and its characterization.

Protein Expres Purif., 21: 310–316.

7. Pike, R.N.; Dennison, C. (1989) Protein fractionation by three-phase

partitioning in aqueousif-butanol mixtures. Biotechnol Bioeng., 33:

221–228.

8. Szamos, J.; Hoschke, A. (1992) Purification of horseradish peroxidase

by three-phase partitioning. Acta Aliment., 21: 253–260.

9. Szamos, J.; Kiss, E. (1995) Three-phase partitioning of crude protein

extracts. J. Colloid Interface Sci., 170: 290–292.

10. Szamos, J.; Janosi, A.; Tamas, B.; Kiss, E. (1998) A novel partitioning

method as a possible tool for investigating meat. I. Z Lebensm Unters

Forsch A., 206: 208–212.

11. Narayan, A.V.; Madhusudhan, M.C.; Raghavarao, K.S.M.S. (2008)

Extraction and purification of Ipomoea peroxidase employing

three-phase partitioning. Appl. Biochem. Biotechnol., 151: 263–272.

FIG. 4. RP-HPLC analysis of TPP purified Pleurotus laccase.

PURIFYING PLEUROTUS OSTREATUS USING TPP METHODOLOGY 1929

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3

12. Sharma, A.; Sharma, S.; Gupta, M.N. (2000) Purification of alkaline

phosphatase from chicken intestine by three-phase partitioning and

use of phenyl-sepharose 6B in the batch mode. Biosepar., 9: 155–161.

13. Dogan, N.; Tari, C. (2008) Characterization of three-phase parti-

tioned exo polygalacturonase from aspergillus sojae with unique

properties. Biochem. Eng. J., 39: 43–50.

14. Rawdkuena, S.; Chaiwut, P.; Pintathong, P.; Benjakulc, S. (2010)

Three-phase partitioning of protease from calotropis procera latex.

Biochem. Eng. J., 50: 145–149.

15. Dhananjay, S.K.; Mulimani, V.H. (2009) Three-phase partitioning of

a-galactosidase from fermented media of Aspergillus oryzae and com-

parison with conventional purification techniques. J. Ind. Microbiol.

Biotechnol., 36: 123–128.

16. Gokhale, D.V.; Patil, S.G.; Bastawde, K.B. (1991) Optimization of

cellulase production by Aspergillus niger NCIM 1207. Appl. Biochem.

Biotechnol., 30: 99–109.

17. Cochran, W.G.; Cox, G.M. (1992) In Experimental Designs, 2nd Ed.;

Wiley Classics Library: New York.

18. Box, G.; Hunter, W.; Hunter, J. (1978) Statistics for Experimenters:

An Introduction to Design, Data Analysis, and Model Building. Wiley

and Sons: New york.

19. Haaland, P.D. (1989) Experimental Design in Biotechnology. Marcel

Dekker.

20. Shin, H.S.; Cha, H.J. (2003) Statistical optimization for immobilized

metal affinity purification of secreted human erythropoietin from dro-

sophila S2 cells. Protein Expr. Puri., 28: 331–339.

21. Su, S.N.; Nie, H.L.; Zhu, L.M.; Chen, X.T. (2009) Optimization of

adsorption conditions of papain on dye affinity membrane using

response surface methodology. Biores. Technol., 100: 2336–2340.

22. Bera, M.B.; Panesar, P.S.; Panesar, R.; Singh, B. (2008) Application

of reverse micelle extraction process for amylase recovery using

response surface methodology. Bioprocess Biosyst. Eng., 31: 379–384.

23. Saisubramanian, N.; Sivasubramanian, S.; Nandakumar, N.;

Indirakumar, B.; Chaudhary, N.A.; Puvanakrishnan, R. (2008) Two

step purification of Acinetobacter sp. lipase and its evaluation as a

detergent additive at low temperatures. Appl. Biochem Biotechnol.,

150: 139–156.

24. Li, C.; Bai, J.; Li, W.; Cai, Z.; Ouyang, F. (2001) Optimization of

conditions for bacteriocin extraction in PEG=salt aqueous two-phase

systems using statistical experimental designs. Biotechnol. Prog., 17

(2): 366–368.

25. Ling, Y.Q.; Nie, H.L.; Su, S.N.; White, C.B.; Zhu, L.M. (2010)

Optimization of affinity partitioning conditions of papain in aqueous

two-phase system using response surface methodology. Sep. Purif.

Technol., 73 (3): 343–348.

26. Ang, T.N.; Ngoh, G.C.; Chua, A.S.M. (2010) A quantitative method for

fungal ligninolytic enzyme screening studies. Asia-Pac. J. Chem. Eng,

27. Lowry, O.H.; Rosebrough, N.J.; Farr, A.L.; Randall, J.R. (1951)

Protein measurement with the folin phenol reagent. J. Biol. Chem.,

193: 265–275.

28. Myers, R.H.; Montgomery, D.C. (2002) Response Surface Method-

ology: Process and Product Optimization Using Designed Experiments;

Wiley: New York.

29. Kalil, S.J.; Maugeri, F.; Rodrigues, M.I. (2000) Response surface

analysis and simulation as a tool for bioprocess design and optimiza-

tion. Process Biochem., 35: 539–550.

30. Ferreira, S.L.C.; Bruns, R.E.; Ferreira, H.S.; Matos, G.D.; David,

J.M.; Brand, G.C.; Da Silva, E.G.P.; Portugal, L.A.; dos Reis, P.S.;

Souza, A.S.; dos Santos, W.N.L. (2007) Box Behnken design: An

alternative for the optimization of analytical methods. Anal. Chim.

Acta, 597: 179–186.

31. Box, G.E.P.; Behnken, D.W. (1960) Some new three level design for

the study of quantitative variables. Technometrics, 2: 455–475.

32. Laemmli, U.K. (1970) Cleavage of structural proteins during the

assembly of the head of bacteriophage T4. Nature (London), 227: 680.

33. Divakar, K.; Deepa Arul Priya, J.; Gautam, P. (2010) Purification

and characterization of thermostable organic solvent-stable protease

from Aeromonas veronii PG01. J. Mol. Cat. B: Enzymatic, 66:

311–318.

34. Dennison, C., Moolman, L., Pillay, C.S.; Meinesz, R.E. (2000)

t-Butanol: Nature gift for protein isolation. S. Afr. J. Sci., 96:

159–160.

35. Singh, R.K.; Gourinath, S.; Sharma, S.; Roy, I.; Gupta, M.N.; Betzel,

C.; Srinivasan, A.; Singh, T.P. (2001) Enhancement of enzyme activity

through three phase partitioning: Crystal structure of a modified

serine protease at 1.5 A resolution. Protein Eng., 14: 307–313.

36. Xiao, Y.Z.; Chen, Q.; Hang, J.; Shi, Y.Y.; Wu, J.; Hong, Y.Z.; Wang,

Y.P. (2004) Selective induction, purification and characterization of a

laccase isozyme from the basidiomycete Trametes sp. AH28-2.

Mycologia., 96: 26–35.

37. Martin, C.; Pecyna, M.; Kellner, H.; Jehmlich, N.; Junghanns, C.;

Benndorf, D.; von Bergen, M.; Schlosser, D. (2007) Purification and

biochemical characterization of a laccase from the aquatic fungus

Myrioconium sp. UHH 1-13-18-4 and molecular analysis of the

laccase-encoding gene. Appl. Microbiol. Biotechnol., 77: 613–624.

1930 V. V. KUMAR ET AL.

DOI:10.1002=apj.451 (article in press).

Dow

nloa

ded

by [

Penn

sylv

ania

Sta

te U

nive

rsity

] at

18:

00 3

0 A

ugus

t 201

3