exploration of optimum operating conditions for enhanced laccase … · 2017. 3. 6. · aslam et...

Aslam et al., J. Anim. Plant Sci. 26(3):2016

794

EXPLORATION OF OPTIMUM OPERATING CONDITIONS FOR ENHANCEDLACCASE ENZYME PRODUCTION BY PLEUROTUS NEBRODENSIS WC 850

THROUGH RESPONSE SURFACE METHODOLOGY

S. Aslam1, M. Asgher2, F. Hussain2 and N. A. Khan3

1Industrial Biotechnology Laboratory, Department of Biochemistry, University of Agriculture, Faisalabad, Pakistan2Department of Biochemistry, University of Agriculture, Faisalabad, Pakistan

3Department of Plant Pathology, University of Agriculture, Faisalabad, Pakistan*Corresponding author’s Email address: [email protected]

ABSTRACT

Laccase is a blue copper containing enzyme which is capable of catalyzing the oxidation of phenolic compounds tophenoxyl radicals. The purpose of recent study was to find optimum conditions for maximum laccase enzyme productionby Pleurotus nebrodensis WC 850 by applying an important statistical technique response surface methodology (RSM)through solid state fermentation of lignocellulosic biomass. Firstly, screening experiments were conducted in order toselect the best substrate for maximum laccase enzyme production among six different lignocellulosic substrates. Wheatstraw was selected as best substrate with enzyme activity 145.10 U/mL after 6th day of fermentation. Different physicalparameters including pH, temperature, inoculum size, incubation time and moisture were then optimized by responsesurface methodology under central composite design (CCD). RSM is an effective strategy which explores the optimumoperating conditions for multivariable system as well as it also examines the simultaneous, systematic and effectivevariation of crucial components and determines the possible interaction among higher order effects which results inenhanced enzyme yield. The increase in laccase enzyme activity (171.63 U/mL) was observed at pH 5, temperature30°C, inoculum size 4mL, incubation time 144mL and moisture 50% after optimization of different factors at differentlevels. This study reveal that optimization of different factors have significant effect on laccase enzyme production.Moreover, optimization of different parameters through RSM is time saving and good technique in biotechnology.

Key words: Laccase, Pleurotus nebrodensis, Response Surface Methodology

INTRODUCTION

Enzymes are multitalented catalysts that haveability to catalyze reactions in short time including thosereactions which are difficult to perform using chemicalmethods. Enzymes have been preferred because of theirunique catalytic nature and their specialty to work undercomplex and moderate conditions (Sarrouh et al., 2012).Enzymes can be produced through fermentationbiotechnology by utilization of many agro- industrialwaste materials which are mostly supplied by paper-pulpindustries and agro industries including forestry. Theselignocellulosic waste materials cause environmentalpollution when left untreated despite of the fact that theycan be transformed into useful products like differentorganic chemicals, enzymes and biofuels. So it isessential to explore new industrial science which canefficiently utilize this waste material and convert it intobeneficial products (Isroi et al., 2011).

Fermentation biotechnology includes a series ofsteps which leads to conversion of complex substratesinto simpler compounds by application of differentmicroorganisms like fungi and bacteria (Robinson et al.,2001). Fermentation technology is vast immensely usedindustrial science that deals with the formulation of

variety of substances like antibiotics, single cell proteinand enzymes. Fermentation technology has gainedimportance due to its economic and environmentalbenefits (Howard et al., 2003). There are many types offermentation but solid state fermentation (SSF) isconsidered reliable and useful than submergedfermentation (SmF) because of its greater productyielding ability, shortened energy prerequisites and easilyperformable downstream processing (Gupte et al., 2007;Bhatnagar et al., 2008).

Most of the white rot fungi produce laccase(Wong, 2009). Among different white rot fungi Pleurotusspecies have been described as best laccase enzymeproducers because of its capability to secrete oxidativeand hydrolytic enzymes which are responsible forlignocellulose degradation (Penninckx et al., 2006;Kachlishvili et al., 2008). There are many applications ofPleurotus species in environmental and biotechnologyfields because of their ability to utilize lignocellulosicsubstrates via secreting hydrolytic and oxidative enzymes(Cohen, 2002; Mikiashvili et al., 2004).

Laccases are multicopper (MCO) phenoloxidases responsible for oxidation of phenoliccompounds to phenoxyl radicals. Laccase was firstexplored in Rhus Vernicifera and also found in insects,

The Journal of Animal & Plant Sciences, 26(3): 2016, Page: 794-804ISSN: 1018-7081


795

bacteria and plants (Dittmer et al., 2004; Giardina et al.,2010; Maciel et al., 2010). Fungal laccases are differentas compared to bacterial and plant laccases due to its highredox potential (Brijwani et al., 2010). Laccase are hemecontaining glycoproteins having molecular weight 60- 80KDa (Hatakka, 2001).

There are many applications of laccase enzymein paper and pulp industry, food industry and textileindustry (Maciel et al., 2010). High redox potential offungal laccases makes them applicable in biotechnologyas well as food industry (Mohammadian et al., 2010).Laccases are being used for food processing, thestabilization of fruit juices and bioremediation of wastewater (Morozova et al., 2007; Ribeiro et al., 2010;Ramachandran et al., 2013) including production ofhormone derivatives and delignification of wood pulps(Widsten and Kandelbauer, 2008; Koschorreck et al.,2009; Brijwani et al., 2010, Asad et al., 2012).Due to many applications of laccase enzyme in industry itis important to search new methods for laccase enzymeproduction by fermentation biotechnology. Extensiveknowledge and understanding regarding recenttechnologies and scientific matters is essential in order toestablish an industry including identification of exoticbiological sources and their genetic manipulation throughmutation for over-production, partial purification andstabilization for production of versatile enzymes(Azevedo et al., 2012).Response surface methodology (RSM) is a set ofstatistical and mathematical techniques which is mostlyused to develop a model and analysis of problems inwhich a response of interest is affected by many variablesand the main objective is to optimize this response(Montgomery, 2005). RSM has been applied foroptimization purpose as a powerful statistical techniquein biotechnology (Palvannan and Satishkumar 2010;Diwaniyan et al., 2012). RSM is also used to study theinteractions among different factors at changing levels(Vivekanadan et al., 2014).The objective of this study was to check the potential ofnew indigenous strain of Pleurotus nebrodensis WC 850for laccase enzyme production through solid statefermentation of lignocellulosic materials. Moreover, thisstudy involves the optimization of different physicalparameters like pH, temperature, inoculum size,incubation time and moisture level of substrate forenhanced laccase enzyme production by a uniquestatistical technique response surface methodology undercentral composite design.

MATERIALS AND METHODS

Fungal Strain: Pure culture of Pleurotus nebrodensisWC 850 was obtained from Mushroom Laboratory,Department of Plant Pathology, University of AgricultureFaisalabad, Pakistan. Pure culture was maintained on

Potato dextrose agar (PDA) slants at pH 4.4 and 28°Ctemperature. It was multiplied periodically for further useand preserved at 4°C.

Substrate Collection and Preparation: Six differentsubstrates were used for laccase enzyme production.These include sugarcane baggase, wheat straw, ricestraw, banana stalk, corn stover and corn cobs. Thesesubstrates were obtained from Industrial BiotechnologyLaboratory and CPC Rafhan Mill Faisalabad. All thesesubstrates were dried in oven at 80°C and then ground inan electric grinder to powder form of 40mm mesh size.These were stored in air tight plastic jars to keep themmoisture free.

Inoculum Development: Homogeneous sporesuspension of P. nebrodensis WC 850 was prepared bygrowing the fungus in inoculum medium for 5-8 days.The inoculum medium was of Kirk (Tien and Kirk, 1988)supplemented with 1% (w/v) glucose. The medium pHwas adjusted to 4.5 and it was sterilized at 121°Ctemperature in laboratory scale autoclave (Sanyo, Japan)for 15 minutes. A loopful of P. nebrodensis WC 850spores was then transferred to moderate cool sterilizedinoculum medium under sterile conditions in laminarhood (Dalton, Japan). Inoculated flask was incubated at31°C for 9 days in shaker (Sanyo- Gallemkemp, UK)with continuous shaking (120 rpm) to obtain the sporenumber of 1×106 to 1×108 spores/mL (Kay-Shoemakeand Watwood, 1996).

Screening experiments for best substrate selection: P.nebrodensis was grown on all six substrates. Experimentswere conducted in triplicate using 250 mL Erlenmeyerflasks in a temperature controlled incubator (EYLA SLI-600ND, Japan). The flasks contained 5g of respectivesubstrates were moistened with 10mL of the basalmedium without glucose. Each flask was sterilized at121°C in an autoclave for 15 minutes and inoculated with5mL of freshly prepared inoculum medium. Theinoculated flasks were kept at 30°C for 1-10 days intemperature controlled incubator to determine the suitablesubstrate with high enzymatic activity. After the end ofstipulated fermentation time period, the experimental andcontrol flasks were harvested by adding 100 mL ofdistilled water and kept in shaker for 30 minutes. Filtrateswere then centrifuged at 10,000 rpm for 10 minutes atroom temperature. The supernatants were collectedcarefully and stored in sterilized glass bottles for enzymeactivity determinations.

Laccase enzyme assay: Enzyme activity of supernatantcollected at the end of screening experiments andoptimization steps was determined using aspectrophotometer (T 60, PG, Instruments, UK). Laccaseenzyme was assayed by monitoring 2, 2 azinobis 3-ethyl-benzthiazoline 6 sulphonate (ABTS) oxidation in50mM sodium malonate buffer at 420 nm (Wolfendon


796

and Wilson, 1982). The enzyme activity was expressed asU/mL.

Optimization of culture conditions for enhancedlaccase enzyme production by RSM under centralcomposite Design: Five different parameters includingpH, temperature, inoculum size, incubation time andmoisture level were optimized by advance optimizationmethod, response surface methodology RSM by usingstatistical software DOE, 9.0 (Design of Experts, 9.0).Central composite design was used for the optimizationand improvement of laccase enzyme production by P.nebrodensis with six center points α= 0.5 and sixreplicates for each center point. The full experimentalplan with regard to their values in actual form is providedin (Table 1). The data obtained from RSM on laccaseproduction were subjected to analysis of variance. Asecond degree of quadratic polynomial equation wasselected to estimate the response of dependent variablesand then it was fitted to data by multiple linear regressionY= β0+ β1X1 + β2X2+ β3X3+ β4X4+ β5X5+ β11X12+ β22X2

2

+β33X32+ β44X4

2+ β55X52+ β12X1X2+ β13X1X3+ β14X1X4+

β15X1X5 +β23X2X3 + β24X2X4+ β25X2X5+ β34X3X4+β35X3X5+ β45X4X5

Where Y is predicted response, X1,X2, X3, X4,X5 are independent variables β0 is intercept, β1, β2, β3,β4,β5 are linear coefficients β11, β22, β33, β44, β55 squaredcoefficients and β12, β13, β14, β15, β23, β24, β25, β34, β35, β45

are interaction coefficients

Table 1. Experimental Units of independent variablesin actual and coded form.

IndependentVariables

Coded Levels(-1) (+1)

pH 2 6Temperature (°C) 20 40Inoculum Size (mL) 2 6Incubation Time (h) 48 240Moisture 40 60

RESULTS

Selection of best substrate for Laccase enzymeproduction: P. nebrodensis WC 850 was grown on sixdifferent substrates including sugarcane baggase, cornstover, banana stalk, wheat straw, rice straw, wheat strawand corn cobs for ten days for production of laccaseenzyme. After every 48 hours, triplicate flasks wereharvested and examined for laccase enzyme activity.Increased laccase enzyme activity of 145.10 U/ mL notedon wheat straw after six days of incubation. Second bestsubstrate for laccase enzyme production was banana stalkwith enzyme activity 136.16 U/mL after eight days offermentation (Table 2). Laccase is produced duringsecondary metabolism by white rot fungi. Wheat strawwas taken as most excellent substrate for laccase enzymeproduction by P. nebrodensis WC 850 after screeningexperiments.

Table 2. Screening experiment for best substrate selection for laccase enzyme production by Pleurotus nebrodensis

Substrates Enzyme activities U/mLIncubation Days

2 4 6 8 10Corn Cobs 113.34±1.12 117.76±2.81 120.56±3.03 116.22±1.63 117.10±4.01Corn Stover 112.68±2.63 113.88±3.01 116.24±3.21 113.32±2.13 114.44±3.34Sugarcane Baggase 118.32±4.80 118.90±1.19 127.78±4.70 116.10±6.51 120.56±5.32Banana Stalk 91.40±1.16 104.06±1.10 136.16±5.11 128.16±2.33 123.21±1.11Wheat Straw 105.01±2.18 125.10±2.30 145.10±3.20 122.12±2.10 130.68±1.02Rice Straw 105.48±2.03 100.34±4.80 101.04±2.63 104.02±1.02 108.40±6.10

Process optimization for maximum production ofLaccase enzyme by Response surface methodologyunder central composite design: Wheat straw was usedfurther for the optimization of solid state fermentationproduction process. Physical parameters including pH,temperature, inoculum size, incubation time and moisturewere optimized through response surface methodology(RSM) under central composite design (CCD). Theoptimum laccase enzyme production was obtained on pH5, temperature 30°C, inoculum size 5 mL (1×106 to1×108) spores/mL, incubation time (144 h) and (50%)moisture level (Table 3). The enhanced laccase enzymeactivity was 171 U/ mL after optimization.

ANOVA to check adequacy of the Model: Dataobtained from response surface methodology wassubjected to analysis of variance. Analysis of variance(ANOVA) results of the quadratic models are presentedin Table 4. The results of RSM were then used to fitsecond order polynomial equation i.e.Y= (150.28) + (2.40 A) + (-2.85B) + (-3.85 C) + (2.03D) + (3.94 E) + (-0.64 AB) + ( 0.068 AB) + (6.23 AD) +(-3.55 AE) + ( 0.34 BC) + ( 0.17 BD) + (2.28 BE) + (-1.87 CD) + (0.94 CE) + (-0.87 DE) + (82.16 A2) + ( -73.66B2) + ( -34.18 C2) + (36.88 D2) + (-29.08 E2)

The effect of interactions among differentfactors on laccase enzyme production was also studied by


797

using design of experts 9.0 (DOE 9.0). The large F- valueof model 171.62 indicates that the model is significant(Table 4). The t and P values are mostly used to evaluatethe significance of each coefficient. Greater t-value andlowered p-value indicate that the correspondingcoefficients are highly significant. Linear terms including(A, B, C, D, E) interaction terms (AD, AE, BE, CD, CE,DE) and quadratic terms A2, B2, C2, D2, E2 weresignificant with p-values<0.0001. Non significant valueof lack of fit 0.8842 for laccase proved the model’s

uniformity. Coefficient of variation R2 is used todetermine the variability in examined response by testedfactors and their mutual interaction. The concluded R2

value of 0.9597 is in correspondence with actual R2 valueof 0.9968. The adjusted R2 value is close to actual R2

value. Moreover, the low value of coefficient of variationis 0.95% confirms the preciseness and variability ofexperiments. The regular signal to noise ratio marked theadequate precision. Standard deviation value is used toindicate the model compatibility with predicted response.

Table 3. Process optimization for enhanced Laccase enzyme production by Pleurotus nebrodensis WC 850through response surface methodology under central composite design.

Runs pH Temperature(°C)

Inoculum size(mL)

Incubation Time(h)

Moisture(%)

Laccase activity(U/mL)

1234567891011121314151617181920212223242526272829303132

45662462262644442264443464644422

3530204040302040202040203030303020204030303030304030402530304020

44666466622244442624444325644422

14414448

24048

14424024048

2404848

14414496

14424024024019214414414414448

14448

14414414424048

5050606060504040406040405045505540604050505050506050405050506060

130.06171.63127.88137.12141.69154.28142.24108.51127.23148.66123.89134.49150.85140.14157.85144.96130.61126.96144.22160.23149.8150.1

169.09143.03127.07139.52116.86132.75150.1

150.88137.17144.15


798

Table 4. Analysis of variance table for quadratic polynomial model for laccase enzyme production by Pleurotusnebrodensis.

Source Sum of Squares df MeanSquare

F- value P ValueProb> F

ModelpHTemperatureInoculum sizeIncubation TimeMoistureABACADAEBCBDBECDCEDEA2B2C2D2E2ResidualLack of FitPure ErrorCor Total

6130.7695.04134.08244.5767.69256.536.64

0.074620.63201.711.840.49

83.2255.8414.0112.23

1053.91847.03182.37212.37132.0019.655.79

13.866150.41

2011111111111111111111

1165

31

306.5495.04

134.08244.5767.69

256.536.64

0.074620.63201.71

1.840.49

83.2255.8414.0112.23

1053.91847.03182.37212.37132.00

1.790.972.77

171.6253.2175.07136.9337.90143.633.72

0.042347.48112.931.030.27

46.5931.267.846.85

590.06474.23102.10118.9073.91

0.35

<0.0001<0.0001<0.0001<0.0001<0.0001<0.00010.08000.8422

<0.0001<0.00010.33160.6121

<0.00010.00020.01730.0240

<0.0001<0.0001<0.0001<0.0001<0.0001

0.8842

Significant

not significant

Regression Coefficient for laccase production byPleurotus nebrodensis WC 850: A coefficient ismeasure of any specified process. The regressioncoefficient table indicated that the positive t value in caseof pH, incubation time and moisture has a significanteffect on enzyme production while temperature andinoculum size has not significant influence on enzymeproduction with negative t value. The regressioncoefficient for interaction among pH and incubation time,temperature and moisture and inoculum size andmoisture were significant having p-value 0.000 while

other interaction terms were not significant having p-value greater than 0.05 (Table 5). While the positivevalue of regression coefficient for quadratic terms likepH*pH and Incubation time*Incubation time indicatesthe existence of a minimum for these activities. Thenegative value of regression coefficients for quadraticterms like temperature*Temperaure, Moisture*Moistureand Inoculum size*Inoculum size indicated the existenceof maximum of laccase enzyme activity as a function of acertain levels of these factors. Beyond this point, thesefactors have inhibitory influences.

Table 5. Estimated regression coefficients for laccase enzyme production by Pleurotus nebrodensis WC 850 in SSFof Wheat straw.

Term Coefficient SE Coefficient T PConstantpHTemperatureInoculum SizeIncubation TimeMoisturepH*TemperaturepH*Inoculum sizepH*Incubation Time

150.282.40-2.85-3.852.033.94-0.640.0686.23

0.340.330.330.330.330.330.330.330.33

4427.27-8.64-11.666.1511.94-1.940.2118.87

0.0000.0000.0010.0800.0000.0000.0800.8410.000


799

pH*MoistureTemperature*Inoculum SizeTemperature*Incubation TimeTemperature*MoistureInoculum size*Incubation TimeInoculum size*MoistureIncubation Time* MoisturepH* pHTemperature*TemperatureInoculum size*Inoculum sizeIncubation Time*Incubation TimeMoisture* Moisture

-3.550.340.172.28-1.870.94-0.8782.16-73.66-34.1836.88-29.08

0.330.330.330.330.330.330.333.383.383.383.383.38

-10.761.030.526.91-5.662.85-2.6424.31-21.79-10.1210.91-8.60

0.0600.3330.6110.0000.0500.0000.0100.0210.0810.0230.0000.009

Interaction among variables: Effect of varying physicalparameters and their interaction was investigated onlaccase enzyme production through RSM and resultshave been described under the following subheadings.Comparable effects regarding two variables wereelucidated by response surface plots. Three dimensionalresponse surface plots were used to determine theinteractive effect of experimental parameters on laccaseenzyme secretion.

pH v/s Temperature: The 3D response surface curveshows how laccase enzyme production is influenced bypH and temperature (Fig 1 A). The optimum pH forlaccase enzyme is 5 and optimum temperature for laccaseenzyme production is 30°C. pH and temperature play animportant role in enzyme production. Both these factorshave antagonistic effect which means that with theincrease in pH there is an increase in enzyme yield butthe increase in temperature had an inhibitory effect onlaccase enzyme production.

pH v/s Inoculum Size: The response surface curveshowed maximum laccase activity at medium level ofboth factors (Fig 1 B). Response surface plot revealedthat the pH range 4- 5 increased laccase enzyme activity

but further increase in inoculum size caused an inhibitoryeffect. The optimum inoculum size was 4mL for laccaseenzyme production.

pH v/s Moisture: The 3 D surface graphs shows that theoptimum yield of laccase obtained at pH 5 and 50 %moisture content (Fig 1 C). Both these factors havesignificant effect on laccase enzyme production whichmeans that with the initial increase in pH and moisturelevel laccase enzyme yield increased.

pH v/s Incubation Time: The interactive effect of pHand incubation time (IT) indicated increase in enzymeproduction with the increase in pH and Incubation time(IT). The 3D response surface plot showed that atbeginning level of pH (2-4) and high incubation time(192-240 h) the laccase activity was low. (Fig 1 D).

Temperature v/s inoculum size: Response surface plotrevealed high yield of laccase at 30°C temperature and4ml inoculum size but lower yield was observed atincreased levels of these factors. Response surface graphshowed that the temperature range (35-40°C) decreasedsynthesis of laccase enzyme (Fig 1 E).

20 25

30 35

4023

45

6

50

100

150

200

250

Lacc

ase

(U/m

L)

pH Temperature (0C) 2

3 4

5 62

34

56

50

100

150

200

250

Lacc

ase

(U/m

L)

pH Inoculum Size (mL)

(A) (B)


800

40 45

50 55

6023

45

6

50

100

150

200

250

300La

ccas

e (U/

mL)

pH Moisture (%) 48

96 144

192 2402

34

56

50

100

150

200

250

300

Lacc

ase (

U/mL

)

pH Incubation Time (h)

(B) (D)

2 3

4 5

62025

3035

40

0

50

100

150

200

250

300

Lacc

ase (

U/mL

)

Temperature (0C) Inoculum Size (mL) 48

96 144

192 24020

2530

3540

0

50

100

150

200

250

300

Lacc

ase (

U/mL

)Temperature (0C) Incubation Time (h)

(E) (F)

40 45

50 55

602025

3035

40

0

50

100

150

200

250

300

Lacc

ase (

U/mL

)

Temperature (0C) Moisture (%) 40 45

50 55

6023

45

6

0

50

100

150

200

250

300

Lacc

ase (

U/mL

)

Inoculum Size (mL) Moisture (%)

(G) (H)

48 96

144 192

2402

34

56

0

50

100

150

200

250

300

Lacc

ase

(U/m

L)

Inoculum Size (mL) Incubation Time (h) 40

45 50

55 60

48

96

144192

240

100

120

140

160

180

200

Lacc

ase

(U/m

L)

Incubation Time (h)Moisture (%)

(I) (J)Fig 1. Three dimensional response surface graphs (Created by using DOE 9.0) for laccase enzyme production by

Pleurotus nebrodensis showing the interactive effects (A) pH v/s Temperature (B) pH v/s Inoculum size(C) pH v/s moisture (D) pH v/s incubation time (E) Temperature v/s Inoculum size (F) Temperature v/sIncubation time (G) Temperature v/s Moisture (H) Inoculum size v/s Moisture (I) Inoculum size v/sIncubation Time (J) Incubation Time v/s Moisture


801

Temperature v/s incubation time: The saddle shapeplot for laccase enzyme production showed thedifferential production of laccase at varied temperatureand incubation time. Temperature and incubation timehad antagonistic as well as synergistic effect onmaximum enzyme production. The optimizedtemperature and incubation time (IT) for laccasesecretion were 30°C and 144 h (Fig 1 F).

Temperature v/s Moisture: The production of laccaseenzyme was affected by both factors. Combined effect ofinoculum size and temperature play an important role inenhanced production of laccase enzyme. Temperatureand moisture have strong interactive effect on laccaseenzyme production. While higher levels of these factorshave inhibitory effects on laccase enzyme production(Fig 1 G).

Inoculum size v/s Moisture: P. nebrodensis WC 850revealed optimized laccase enzyme yield at balancedlevel of moisture i.e 50% and inoculum size 4mL.Additional rise in both levels results in lowered fungalgrowth and enzyme yield. The 3D surface plot showedthat interaction among inoculum size and moisture hadsignificant influence on laccase enzyme yield (Fig 1 H).

Inoculum size v/s Incubation time: 3 D surface plotshowed that with the increase in inoculum size andincubation time laccase enzyme production increased butfurther increase in both factors had inhibitory effect (Fig1 I). The interaction effect of inoculum size (IS) andincubation time (IT) was positive for laccase enzymeproduction. The three dimensional response surface plotis showing that the incubation time (IT) of 144 h is mosteffective in enhancing the yield of laccase enzyme.

Incubation Time v/s Moisture: The optimum yield oflaccase can be obtained at incubation time 144 h andmoisture level 50 %. (Fig 1 J). The graph shows that bothfactors play an important role on the secretion of laccaseenzyme by P. nebrodensis WC 850. The graph alsoshowed that at initial moisture level 45-55% growth of P.nebrodensis was high resulting in higher production oflaccase enzyme in the solid state fermentation mediumcontaining wheat straw.

DISCUSSION

In the present study the potential of anindigenous strain of P. nebrodensis for laccase enzymeproduction through solid state fermentation oflignocellulosic material was investigated. For thispurpose, screening experiments were performed in orderto select the best substrate suitable for laccase enzymeproduction. The maximum activity (145.10 U/mL) oflaccase enzyme was observed when grown on wheatstraw after six days of fermentation. Other findings of our

research also revealed that varying culture processes playan important role in increased enzyme yield. The increasein enzyme activity (171.63 U/mL) was observed afteroptimization of different factors through RSM responsesurface methodology.

Varying levels of pH, temperature, inoculumsize, incubation time and moisture were optimized byresponse surface methodology under central compositedesign to check their effect on laccase enzymeproduction. It was predicted by our results that the effectof pH is obvious and the amount of laccase increasedwith the initial increase in pH upto 5 but further increasein pH lowered the enzyme activity. High pH may affectthe activity of enzyme due to conformational changes inenzyme structure (Tavares et al., 2006; Kiran et al., 2012;Vivekanadan et al., 2014)). Response surface analysisshowed that pH in range of 3.0- 5.0 has significant effecton increased laccase enzyme production by Trametesversicolor (Singh et al., 2008). The optimized pH forlaccase enzyme falls in the range 4.5-6.0 (Sivakumar etal., 2010). The growth pattern of white rot fungus istolerant to wide range of pH indicated that white rotfungus has flexibility to adapt according to differentecological conditions (Pandey et al., 2001; Rinu et al.,2012).

Temperature is also an important factor whichplay vital role in enhancement of enzyme activity. Whiterot fungi is capable of secreting the laccase enzyme underoptimum conditions (Yasmeen et al., 2013). Dhakar andPandey, 2013 investigated that suboptimal temperatures15- 35°C are suitable for enhanced laccase enzymeproduction. Our results are in close agreement withfindings of Snajdar and Baldrain 2007 who reportedmaximum laccase enzyme activity by Trametesversicolor between 25 and 30°C. Yasmeen et al. (2013)reported that optimum temperature range of 25°C to37°Cis best optimum range for the production of laccaseenzyme. Optimum pH and temperature are crucial factorsfor the appropriate growth and metabolic action ofmicroorganism (Couto et al., 2006; Fatma et al., 2010;Yasmeen et al., 2013).

The growth of microorganism in solid substratefermentation medium is also influenced by inoculum size.Low inoculum size is not suitable for growth ofmicroorganism while large quantity of microorganismcause competitive inhibition (Sabu et al., 2005). Largequantity of inoculum results in lowered metabolicactivities of microorganism due to lack of nutrients (Patelet al., 2009). Muhammad et al. (2012) found the loweredenzyme yield at higher and lower inoculum levels. In ourcase medium level of inoculum 4mL showed best laccaseenzyme production by P. nebrodensis WC 850 whengrown on wheat straw.

Moisture content is also an important factor tobe considered for the growth of microorganism.According to our results moderate moisture level 50%


802

proved best for increased laccase enzyme production.High level of moisture content affects the substrateporosity and results in ceased oxygen transport leading tolow enzyme yield (Chhaya and Modi, 2013). While lowmoisture content caused inhibition of microbial growthby limiting the access of white rot fungi to essentialnutrients (Shaheen et al., 2008; Chhaya and Modi, 2013).

Incubation time is also an important factorwhich affects the biosynthesis of fungus. Our results arein line with Nadeem et al. (2014) reported that maximumlaccase activity in Pleurotus ostreatus after 6th days ofincubation. Asgher et al. (2012) reported that the timetaken by microorganism in order to produce laccaseenzyme is due to long lag phase and primary metabolism.Wang et al. (2011) also reported the maximum activity oflaccase enzyme after six days of incubation. Our currentresults suggest that response surface methodology is aunique and advance technique that not only considers oneor more factors at one time but it also determines theinteraction among different factors and their significanteffect on increased laccase enzyme production in lesstime.

Conclusion: The production of laccase enzyme can beimproved by optimization of different factors by responsesurface methodology using central composite design. Allfive parameters including pH, temperature, inoculumsize, incubation time and moisture had significant effecton laccase enzyme production. It was observed thatstatistical optimization approach had helped to find outthe most significant operating factors and optimum levelsfor laccase enzyme production by P. nebrodensis.

REFERENCES

Asad, M. J., M. Imran, S. H. Hadri, and S. Mehmood(2012). Production and industrial applications oflaccase enzyme. J. Cell and Mol. Biol. 10: 1-11.

Asgher, M., H. M. N. Iqbal, and M. J. Asad (2012).Kinetic characterization of purified laccaseproduced from Trametes versicolor IBL- 04 insolid state bioprocessing of corn cobs.Bioresources. 7: 1171- 1188.

Azevedo, V., T. M. Santos, and R. Dias (2012). Up-to-date insight on industrial enzymes applicationsand global market. J Bioprocess Biotechniq S4.

Bhatnagar, A., S. Kumar, and J. Gomes (2008).Operating conditions of 2001 staged verticalreactor for bioconversion of wheat straw byPhanerochaete chrysosporium. BioresourceTechnology. 99: 6917-6927.

Brijwani, K., A. Rigdon, and P.V. Vadlani (2010).Fungal laccases: Production, Function andApplications in food processing. EnzymeResearch. 2010:1-10.

Chhaya, R. and H. A. Modi (2013). Comparative study oflaccase production by Streptomyces chartreusisin solid state and submerged fermentation. Int. J.Fund. and Appl. Life Sci. 3: 73- 84.

Cohen, L.P.Y.H.R (2002). Biotechnological applicationsand potential of wood degrading mushroom ofthe genus Pleurotus. Appl. Microbiol. andBiotechnol. 58: 582-594.

Couto, R., S. E. Lopez, and M. A. Sanroman (2006).Utilization of grape seeds for laccase productionin solid state fermentors. J. Food Engi.. 74: 263-267.

Dhakar, K.., and A. Pandey (2013). Laccase productionfrom a temperature and pH tolerant fungal strainof Trametes hirusta (MTCC 11397). EnzymeResearch. 2013:1-9.

Dittmer, N. T., R. J. Suderman, H. Jiang, Y. C. Zhu, M.J. Gorman, K. J. Kramer, and M. R. Kanost(2004). Characterization of cDNAs encodingputative laccase-like multicopper oxidases anddevelopmental expression in the tobaccohornworm, Manduca sexta, and the malariamosquito, Anopheles gambiae. Insect Biochem.and Molecul. Biol. 34: 29-41.

Diwaniyan, S., K. K. Sharma, and R. C. Kuhad (2012).Laccase from an alkaline tolerantbasidiomycetes Crinipellis sp. RCK- 1:production optimization by response surfacemethodology. J. Basic Microbiol. 52: 397- 407.

Fatma, H., A. E. Zaher, and M. Fadel (2010). Productionof bioethanol via enzymatic saccharification ofrice straw by cellulose produced byTrichoderma reesi, under solid statefermentation. New York Science J. 3: 72- 78.

Giardina, P., V. Faraco, and G. Sannia (2010). Laccases:a never ending story. Cell Molecul. Life Sci. 67:369- 385.

Gupte, A., S. Gupte, and H. Patel (2007). Ligninolyticenzyme production under solid statefermentation by white rot fungi. J. Sci. andIndust. Research. 66: 611- 614.

Hatakka, A (2001). Bidegradation of lignin.Biotechnology. 1: 129-180.

Howard, R. L., S. Howard, and E. Abotsi (2003).Lignocellulose biotechnology: issue ofbioconversion and enzyme production. Afri. J.Biotechnol. 2: 602- 619.

Isroi., R. Millati, K. Lundquist, and C. Niklasson (2011).Biological pretreatment of lignocellulose withwhite rot fungi and its applications: A review.Bioresources. 6: 5224-5259.

Kachlishvili, E., E. Metreveli, and T. Kharziani (2008).Lentinus edodes and Pleurotus specieslignocellulolytic enzymes activity in submergedand solid state fermentation of lignocellulosic


803

waste of different composition. BioresourceTechnology. 99:457- 462.

Kay-Shoemake, J. L. and M. E. Watwood (1996).Limitations of the lignin peroxidases system ofthe white rot fungus, Phanerochaetechrysosporium. Appl. Microbiol. andBiotechnol. 46:43 -442.

Kiran, A., S. Ali, M. Asgher, and M. F. Anwar (2012).Comparative study on decolorization of reactivedye 222 by white rot fungi Pleurotus ostreatusIBL- 02 and Phanerochaete chrysosporium IBL-03. Afr. J. Microbiol. Research. 6: 3639- 3650.

Koschorreck, K., R. D. Schmid, and V.B. Urlacher(2009). Improving the functional expression of aBacillus licheniformis laccase by random andsite-directed mutagenesis. J. Biotechnol. 9: 1-10.

Maciel, M. J. M., A. C. E. Silva, and H. C. T. Ribeiro(2010). Industrial and biotechnologicalapplications of ligninolytic enzymes ofbasidiomycota: A Review. Elect. J. Biotechnol.13: 1- 13.

Mikiashvili, N., S. Wasser, and E. Nevo (2004).Lignocellulolytic enzyme activities ofmedicinally important basidiomycete fromdifferent ecological niches. Inter. J. Medi.Mushroom. 6: 63- 71.

Mohammadian, M., M. F. Roudsari, N. Mollania, A. B.Dalfard, and K. Khajeh (2010). Enhancedexpression of a recombinant bacterial laccase atlow temperature and microacrobic conditions:purification and biochemical characterization. J.Indust. Microbiol. Biotechnol. 5: 41-45.

Montgomery, D. C (2005). Design and Analysis ofExperiments: Response surface method anddesigns. New Jersey: John Wiley and Sons, Inc.

Morozova, O. V., G. P. Shumakovich, M. A.Gorbacheva, S. V. Shleev, and A. I. Yaropolov(2007). “Blue” Laccases. J. Biochem. 72: 1136-1150.

Muhammad, I., N. Muhammad, and S. Quratulain(2012). Media optimization for amylaseproduction in solid state fermentation of wheatbran by fungal strains. J. Cell and Molecul. Biol.10: 55- 64.

Nadeem, A., S. Baig, and N. Sheikh (2014).Mycotechnological production of laccase byPleurotus ostreatus P1 and its inhibition study.J. Animal and Plant Sci. 24: 492- 502.

Palvannan, T., and P. Satishkumar (2010). Production oflaccase from Pleurotus florida NCIM 1243using Plackett- Burman design and responsesurface methodology. J. Basic Microbiol. 50:325- 335.

Pandey, A., L. M. S. Paloni, and D. Bisht (2001).Dominant fungi in the rhisosphere of established

tea bushes and their interaction with thedominant bacteria under in situ conditions.Microbiol. Research. 156: 377- 382.

Patel, H., A. Gupte, and S. Gupte (2009). Effect ofdifferent culture conditions and inducers onproduction of laccase by basidiomycete fungalisolate Pleurotus ostreatus HP- 1 under solidstate fermentation. Biresources. 4: 268- 284.

Penninckx, M., E. Kachlishvili, V. Elisashvili, and M.Kevesitadze (2006). Use of Pleurotus dryins forlignocellulolytic enzymes production insubmerged fermentation of mandarin peels andtree leaves. Enz. Microb. Technol. 38: 998-1004.

Ramachandran, P., R. Sundharam, J. Palaniyappan, andA.P. Munusamy (2013). Potential processimplicated in bioremediation of textile effluents:A Review. Adv. Appl. Sci. Research. 4: 131-145.

Ribeiro, D.S., S.M.B. Henrique, L.S. Oliveira, G.A.Macedo, and L.F. Fleuri (2010). Enzymes injuice processing a review. Int. J. Food Sci. andTechnol. 45: 635-641.

Rinu, K., A. Pandey, and L. M. S. Paloni (2012).Utilization of psychrotolerant phosphatesolubilizing fungi under low temperatureconditions of mountain ecosystem, “inmicroorganisms in sustainable agriculture andbiotechnology, T. Satyanarayna, B. N. Johri andParkash. Eds. Springer Science Media. 77- 90.

Robinson, T., D. Sing, and P. Nigam (2001). Solid statefermentation: a promising microbial technologyfor secondary metabolite production. Appl.Microbiol. and Biotechnol. 55: 284- 289.

Sabu, A., A. Pandey, M. J. Dand, and G. Szakais (2005).Tamarind seed powder and palm kernel cake:two novel agro residues for production oftannase under solid state fermentation byAspergillus niger ATCC 16620. Biores.Technol. 96: 1223- 1228.

Sarrouh, B., T. M. Santos, and R. Dias (2012). Up-to-date insight on industrial enzymes applicationsand global market. J Bioprocess. andBiotechniq. S4.

Shaheen, I., H. N. Bhatti, and T. Ashraf (2008).Production, purification and thermalcharacterization and thermal characterization ofinvertase from a newly isolated Fusariumspecies under solid state fermentation. Int. J.Food Sci. Technol. 43: 1152- 1158.

Singh, G., N. Ahuja, P. Sharma and N. Capalash (2008).Response surface methodology for theoptimized production of an alkalophilic laccasefrom ϒ- proteobacterium JB. Bioresources. 4:544- 553.


804

Sivakumar, P., R. Rajendran, C. Balakumar, and M.Tamilvendan (2010). Isolation, screening andoptimization of production medium forthermostable laccase production fromGanoderma sp. Int. J. Engi. Sci. and Technol. 2:7133- 7141.

Snajdar, J. and P. Baldrain (2007). Temperature affectsthe production activity and stability ofligninolytic enzyme in Pleurotus ostreatus andTrametes versicolor. Fol. Microbiol. 52: 498-502.

Tavares , A. P. M., M. A. Z. Coelho, and M. S. M.Agapito (2006). Optimization and modeling oflaccase production by Trametes versicolor in abioreactor using statistical experimental design.Appl. Biochem. Biotechnol. 41: 794- 799.

Tien, M. and T. K, Kirk (1988). Lignin peroxidase ofPhanerochaete chrysosporium. Methods inEnzymol. 33:569-575.

Vivekanadan, K. E., S. Kumaresan, R. S. Kumar, and T.Balasubramian (2014). Optimization of mediumcomposition of laccase production byAspergillus nidulans KF974331 through

response surface methodology- A statisticalapproach. Int. J. Research in Pure and Appl.Microbiol. 4 (2): 32- 38.

Wang, C., M. Zhao, L. Lu, X. Wei, and T. Li (2011).Characterization of laccase from Bacillussubtilis WD 23 and its use in decolorization.Afr. J. Biotechnol. 10: 2186- 2192.

Widsten, P. and A. Kandelbauer (2008). Laccaseapplications in the forest products industry: AReview. Enz. and Microb. Technol. 42: 293-307.

Wolfenden, B. S., and R. I. Wilson (1982). Radicalcations as reference chromogens in kineticstudies of one electron transfer reactions. J.Chem. Society Perkin Transac. 11: 805-812.

Wong, D (2009). Structure and action mechanism ofligninolytic enzymes. Appl. Biochem. andBiotechnol. 157: 174- 209.

Yasmeen, Q., M. Asgher, M. A. Sheikh, and H. Nawaz(2013). Optimization of ligninolytic enzymesproduction through response surfacemethodology. Bioresources. 8: 944-968.

exploration of optimum operating conditions for enhanced laccase … · 2017. 3. 6. · aslam et...

Documents