BIOTECHNOLOGICAL PRODUCTS AND PROCESS ENGINEERING

Improvement of α-L-arabinofuranosidase productionby Talaromyces thermophilus and agro-industrial residuessaccharification

Mohamed Guerfali & Moncef Chaabouni &Ali Gargouri & Hafedh Belghith

Received: 15 June 2009 /Revised: 30 July 2009 /Accepted: 31 July 2009 /Published online: 21 August 2009# Springer-Verlag 2009

Abstract This study is an application of an experimentaldesign methodology for the optimization of the cultureconditions of α-L-arabinofuranosidase production by Talar-omyces thermophilus. Wheat bran and yeast extract werefirst selected as the best carbon and nitrogen sources,respectively, for enzyme production. A Plackett–Burmandesign was then used to evaluate the effects of eightvariables. Statistical analyses showed that while pH had anegative effect on α-L-arabinofuranosidase production,wheat bran and MgSO4 had a significantly positive effect.The values of the latter three parameters were furtheroptimised using a central composite design and a responsesurface methodology. The experimental results were fittedto a second-order polynomial model that yielded adetermination coefficient of R2=0.91. The statistical outputshowed that the linear and quadric terms of the threevariables had significant effects. Using optimal conditions,the experimental value of α-L-arabinofuranosidase activityproduced was very close to the model-predicted value. Theoptimal temperature and pH of enzyme activity were 55 °Cand 7.0, respectively. This enzyme was very stable over aconsiderable pH range from 4 to 9. The crude enzyme of T.thermophilus rich in α-L-arabinofuranosidase was also usedfor saccharification of lignocellulosic materials and arabi-nose production.

Keywords Response surface methodology .

Optimization .α-L-arabinofuranosidase . Arabinose .

Talaromyces thermophilus

Introduction

Hemicelluloses are the second most abundant polysacchar-ides in nature; they represent about 20–35% of lignocellulosicbiomass (Wyman 1994). Hetero-1,4-β-D-xylan, the majorconstituent of hemicellulose, consists of a backbone ofβ-1,4-linked xylopyranose and side chains of α-L-arabinofuranoside, acetyl groups, and/or 4-o-methylglucur-onic acid at the C-2 and C-3 positions of the xylose units(Whistler and Richards 1970). The xylan-degrading enzymesystems of microorganisms include endo-β-1,4-xylanase(EC 3.2.1.8), β-D-xylosidase (EC 3.2.1.37), and the side-chain-debranching enzymes, as α-L-arabinofuranosidase (EC3.2.1.55), α-glucuronidase (EC 3.2.1.139) and acetylxylanesterase (EC 3.1.1.72) (Sunna and Antrankian 1997).

In fact, α-L-arabinofuranosidases (Abfs; EC 3.2.1.55) areexo-type enzymes that generally catalyse the cleavage ofthe terminal α-L-arabinofuranosyl residues of arabinoxylan,arabinan and arabinogalactan (Kaji 1984). They haverecently been identified as further parts in the xylanolyticsystem (Biley 1985), removing arabinose from the sidechains. In general, these enzymes are produced by bacteria(Gomes et al. 2000), actinomycetes (Zimmermann et al.1988), and several fungi namely those of Aspergillusterreus (Le Clinche et al. 1997), Aspergillus awamori(Kaneko et al. 1998) and Penicillium purpurogenum (DeIoannes et al. 2000).

Researchers have recently realised that effective Abfproduction is important for a wide range of applications. Itis, for instance, of particular importance for the effective

M. Guerfali :A. Gargouri :H. Belghith (*)Laboratoire de Génétique Moléculaire des Eucaryotes,Centre de Biotechnologie de Sfax,BP “1177”, 3038 Sfax, Tunisiae-mail: hafeth.belghith@cbs.rnrt.tn

M. ChaabouniLaboratoire de Chimie Industrielle,Ecole Nationale d’Ingénieurs de Sfax,BP W, 3038 Sfax, Tunisia

Appl Microbiol Biotechnol (2010) 85:1361–1372DOI 10.1007/s00253-009-2178-2

conversion of hemicellulosic biomass into fuels andchemicals, the efficient delignification of pulp, the properutilisation of plant materials for animal feed (Numan andBhosle 2006) and the improved hydrolysis of grapemonoterpenyl glycosides during wine fermentation (Gunataet al. 1990).

In the context of this increasing interest in Abf produc-tion, particularly in environmental and agro-industrialprocesses, we have recently isolated and identified anew Talaromyces thermophilus strain that proved efficien-cy in the production of large amounts of thermostablexylanolytic enzymes, including an endo-xylanase (Maalejet al. 2009), a β-xylosidase (Guerfali et al. 2009) and α-L-arabinofuranosidase. This enzymatic complex can be easilyemployed in the processes of the bioconversion ofagricultural wastes into simple fermentable products.

A particular concern in this context is the cost-effectiveness of the composition of the culture medium. Ithas recently been estimated that around 30–40% of theproduction cost was allocated to the growth medium (Kirket al. 2002). The optimization of fermentation conditions bymedia formulation is, therefore, essential for the develop-ment of adequate and productive fermentation processes.

The conventional techniques that are currently usedoften involve a process wherein one independent variable ischanged while the other factors are kept constant (onefactor at a time). This technique is not only laborious andtime-consuming but is also hazy, particularly in terms ofpredictive accuracy with regards to the determination of thetrue optimum of each parameter involved in the system(Haaland 1989). Fortunately, recent research suggests thatthese limitations can be overcome through the use ofexperimental design methodology. Prominent among theseare the Plackett–Burman (PB) factorial designs. The lattercan identify factors which have the most important effectsand that are, therefore, quite useful in preliminary studieswhose main objective is to select variables that can be fixedor eliminated in further optimization processes. Responsesurface methodology (RSM) is a powerful experimentaldesign that has also been used to achieve similar goals.RSM is a collection of statistical techniques used fordesigning experiments, building models, evaluating theeffects of factors, and searching optimum conditions fordesirable responses (De Coninck et al. 2000). Overall,statistical experimental designs have been extensivelyapplied in the optimization of the composition of growthmedia, the conditions of enzymatic hydrolysis, and themonitoring of the fermentation and food manufacturingprocesses (Hajji et al. 2008; Li et al. 2008).

In view of this, a statistical experimental design wasemployed to optimise culture conditions for higher Abfproduction by T. thermophilus under submerged fermenta-tion. A Plackett–Burman design was used to identify the

most significant variables influencing Abf production. Aresponse surface methodology combined with a centralcomposite design (CCD) was then used to further optimisethose variables, including wheat bran percentage, MgSO4

concentration and pH. The properties of the crude α-L-arabinofuranosidase were also studied to identify its idealconditions of applications for lignocellulosic materialssaccharification and arabinose production.

Materials and methods

Microorganism and culture conditions

The present study reports on a newly isolated thermo-tolerant fungal strain from a soil sample collected in thethermal station of El Hamma in the south of Tunisia. Thefungal isolate was identified as T. thermophilus Stolk byCBS (Centraalbureau voor schimmelculturen, Holland),Code reference: detail 274-2003. The deposit number ofT. thermophilus in the national strain bank of Tunisia(Tunisian Collection of Microorganisms CTM10.103). TheT. thermophilus was cultivated in a modified liquidMandels medium (Mandels and Weber 1969) KH2PO4,1 g; K2HPO4, 2.5 g; 1.4 g; MgSO4·7 H2O, 0.3 g; CaCl2,0.3 g; Tween 80, 1 ml and 1 l of water. The pH of themedium, which was 7.0, was supplemented with 1 ml of anoligo-elements solution with MnSO4, 1,6 g/l; ZnSO4, 1,4 g/l;FeSO4, 5 g/l and CoCl2, 2 g/l. The nitrogen and carbonsources were supplemented to the grown medium andautoclaved at 120 °C for 20 min. The enzyme productionwas carried out in 500-ml flasks, each of which contained100 ml of the culture medium that was incubated at 50 °Cand at an agitation rate of 160 rpm for 5 days. At differenttime intervals, the samples were withdrawn and centrifugedat 5,000 rpm for 15 min, and the clear supernatant was usedas a crude enzyme in the assay procedure.

Different carbon sources (commercial sources such asxylans, and local sources such as wheat bran, barley bran,wheat straw and rabbit food) at 2% were tested for theireffects on the kinetics of α-L-arabinofuranosidase produc-tion. Under this condition, the nitrogen source (peptone 1 g/l)was maintained fixed. A wide range of mineral and organicnitrogen sources were also tested for their ability to produceα-L-arabinofuranosidase.

Enzyme assays

A spectrophotometric method was used to measure α-L-arabinofuranosidase activity with p-nitrophenyl β-D-arabinofuranoside (pNPA) as a substrate (Yanai and Sato2000). The assay mixture contained 200 μl of pNPA in50 mM potassium phosphate buffer (pH 7.0), and 200 μl of

1362 Appl Microbiol Biotechnol (2010) 85:1361–1372

enzyme solution. After incubation for 10 min at 50 °C, thereaction was stopped by the addition of 1.6 ml of Na2CO3

(1 M). The absorbance (nanometer) due to the release ofp-nitrophenol was measured at 405 nm.

Optimization of α-L-arabinofuranosidase production

The optimization of α-L-arabinofuranosidase productionwas carried out using a statistical experimental design thatconsisted of two major steps. The first step involved thescreening of the significant variables that affected enzymeproduction; the second involved the further optimization ofthe relatively important variables.

Selection of significant variables by Plackett–Burmandesign

Plackett–Burman design, an efficient technique formedium component optimization, was used to screen‘k’ variables in just ‘k+1’ number of experiments (Plackettand Burman 1946). The (PB) design was then used toevaluate the relative importance of eight parameters for α-L-arabinofuranosidase production in submerged culture. Infact, this design does not consider the interaction effectsamong the variables and was used only to screen theimportant variables affecting α-L-arabinofuranosidaseproduction. The variables that were chosen for the presentstudy were (A) initial pH, (B) inoculum size, (C) wheatbran percentage, (D) yeast extract concentration, (E)agitation rate, (F) aeration, (G) CaCl2 concentration and(H) MgSO4 concentration. The experimental design withthe names, symbol codes, and actual levels of the variablesis presented in Tables 1 and 2.

The Plackett–Burman experimental design was based onthe following first order model equation:

y ¼ b0 þX

b ixi ð1Þ

Where y is the response (α-L-arabinofuranosidase activityU/ml), β0 is the model intercepts, bi is the linear coefficient,and xi is the level of the independent variable. The effectsof each variable on α-L-arabinofuranosidase activity wereestimated as the difference between both averages ofmeasurements made at the higher level and at the lowerlevel. The significance of each variable was determined viaa Student’s t test.

Optimization by response surface methodology

The next step in the formulation of the medium was todetermine the optimum levels of the significant variablesfor α-L-arabinofuranosidase production. For this purpose, aRSM was adopted to maximise enzyme production using aCCD. The significant variables that were selected were (X1)wheat bran percentage, (X2) initial pH and (X3) MgSO4

concentration. Each variable was assessed at five codedlevels (−1.682, −1, 0, +1 and +1.682). A total of 19experiments were conducted including five replicates at thecentre point. The response values y

� �used in each trial

were the average of the duplicates.

Statistical analysis and modelling

The data obtained from RSM with regards to α-L-arabinofuranosidase production were subjected to analysisof variance (ANOVA) to check for errors and thesignificance of each parameter. α-L-arabinofuranosidaseproduction was taken as response y

� �. The data were then

subjected to a multiple regression analysis to obtain anempirical model that could relate the response measured tothe independent variables. The behaviour of the system wasexplained by the following quadratic equation:

y ¼ b0 þ b1X1 þ b2X2 þ b3X3 þ b11X21 þ b22X

22

þ b33X23 þ b12X1X2 þ b23X2X3 þ b13X1X3

ð2Þ

Where y refers to the predicted response, X1, X2, X3 to theindependent coded variables, β0 to the offset term, β1, β2,β3 to the linear effects, β11, β22, β33 to the squared effectsand β12, β23, β13 to the interaction terms.

The statistical software package, (Nemrod-W by LPRAIMarseilles, France; Mathieu et al. 2000) was used toconduct a regression analysis on the experimental dataand to plot the response surface graphs. The statisticalsignificance of the model was determined by the applica-tion of Fisher’s F test. The two-dimensional graphical

Table 1 Experimental variables at different levels used for theproduction of α-L-arabinofuranosidase by T. thermophilus usingPlackett–Burman design

Symbolcode

Variables Units Experimental levels

Low(−1)

Higher(+1)

A Initial pH – 5.5 8.5

B Inoculums size Spore/ml 105 108

C Wheat bran % 1.5 4

D Yeast extract g/l 1 5

E Agitation rate rpm 100 200

F Aeration % 17 40

G CaCl2 g/l 0.1 1

H MgSO4 g/l 0.1 1

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representation of the system behaviour, called the iso-response contour plot, was used to describe the individualand cumulative effects of the variables as well as thepossible correlations that existed between them.

Validation of the model

The statistical model was validated with respect to all of thethree variables within the design space. Further experimentswere conducted in which the spot tests that were notinvolved in the model design and that were located in theinterior area of study (run 20, 21, 22 and 23) were takeninto account. Those four experimental combinations wereused to study the α-L-arabinofuranosidase production underthe experimental conditions described above.

Enzyme characteristics

The optimum temperature of the crude α-L-arabinofurano-sidase was determined by incubating the supernatant of theculture with pNPA (2 mM) at different temperaturesranging from 30 to 75 °C. The enzyme thermostabilitywas determined by measuring the residual activity afterincubation of the enzyme for 10 h at different temperaturesat pH 7.0 in the absence of substrate. The optimum pH forα-L-arabinofuranosidase activity was determined by incu-bating the supernatant with pNPA for 10 min at 55 °C indifferent buffers: 50 mM citrate, pH 3, 4 and 5; 50 mMphosphate, pH 6, 7 and 8; 50 mM AMPSO buffer, pH 9;and 50 mM glycine, pH 10 and 11. The stability at 4 °C invarious pH conditions was assessed by incubating the

enzyme at different pH and by measuring the residualactivity after 24 h using the standard protocol.

Hydrothermal pre-treatment and enzymatic hydrolysis

Five types of agro-industrial residues (wheat bran, barleybran, wheat straw, sorghum straw, wheat straw and wheatsesame) were used for sugar production by enzymatichydrolysis. Lignocellulosic materials were crashed to obtaina particle size less than 1 mm diameter and hemicellulosefractions were extracted according to the method of Dien etal. 2006. This method consists of incubated 1 g of eachresidue 30 min at 180 °C in 10 ml phosphate buffer pH7.0. After the hydrothermal pre-treatment, 1 ml of crudeenzyme of T. thermophilus (containing 11.5 U/ml of endo-xylanase, 0.8 U/ml of β-xylosidase, 0.72 U/ml of α-L-arabinofuranosidase, 0.45 U/ml of β-D-mannosidase and atotal protein of 445 mg/l) was added to each preparationand the samples were incubated at 55 °C for 3 h at agitationrate of 160 rpm. After suitable time intervals, aliquots werewithdrawn, centrifuged and analysed by HPLC; and thereducing sugars were estimated by dinitrosalicylic acid(Miller 1959).

High-performance liquid chromatography

The hydrolysis products were monitored by high-performance liquid chromatography (HPLC; Bio-RadAminex 87-C, column 7.8×300 mm). A solution ofsimple sugar (glucose, xylose and arabinose), at 1 g/l each,was used as a standard.

Table 2 The experimental design using the Plackett–Burman method for screening of variables

Run Aa B C D E F G H Abf activity U/ml

Yb (1) Y (2)

1 1 1 −1 1 1 1 −1 −1 0.016 0.019

2 −1 1 1 −1 1 1 1 −1 0.26 0.29

3 1 −1 1 1 −1 1 1 1 0.23 0.27

4 −1 1 −1 1 1 −1 1 1 0.34 0.36

5 −1 −1 1 −1 1 1 −1 1 0.44 0.49

6 −1 −1 −1 1 −1 1 1 −1 0.01 0.17

7 1 −1 −1 −1 1 −1 1 1 0.20 0.18

8 1 1 −1 −1 −1 1 −1 1 0.012 0.017

9 1 1 1 −1 −1 −1 1 −1 0.27 0.321

10 −1 1 1 1 −1 −1 −1 1 0.37 0.43

11 1 −1 1 1 1 −1 −1 −1 0.27 0.26

12 −1 −1 −1 −1 −1 −1 −1 −1 0.01 0.013

a The symbol were the same as those in Table 1b Y (1) and Y (2) were the observed values of α-L-arabinofuranosidase activity realised in duplicate

1364 Appl Microbiol Biotechnol (2010) 85:1361–1372

Results

Selection of carbon and nitrogen sources

A series of experiments were first carried out to study theeffects of various complex carbon and nitrogen sources on α-L-arabinofuranosidase production by T. thermophilus. Abasal medium supplemented with 1 g/l peptone as a nitrogensource was used to evaluate the effect of carbon sources at2.0 % (w/v) on enzyme production (Fig. 1a). The initial pHwas adjusted to 7.0. The level of α-L-arabinofuranosidaseproduced by T. thermophilus was largely dependent on thecarbon source used in the medium. The highest levels ofactivity were observed at 5 days of growth for the most ofthe substrates studied. Wheat bran appeared to be the bestcarbon source with regard to α-L-arabinofuranosidaseactivity (0.25 U/ml) and was, therefore, selected forfurther investigation. However, with xylan as a carbonsource, Oat-spelt xylan, which contains α-L-arabinofur-anosyl residue at O-3 position of xylose backbone at everyeight to ten xylose molecules (Schwarz et al. 1995), hasoften been considered to be a better inducer of enzymeactivity than beechwood or birchwood xylan. Othercarbon sources used, namely, barley bran, wheat strawand rabbit food permit to obtain lower α-L-arabinofur-anosidase activity (0.14 U/ml). Arabinose and arabitol, onthe other hand, were found to be strong repressors ofenzyme secretion (data not shown).

The results pertaining to nitrogen sources presented inFig. 1b show that, except for sodium nitrate, all testednitrogen sources stimulated α-L-arabinofuranosidase pro-duction. Enzyme activity was higher particularly whenorganic nitrogen sources were used. In fact, as yeast extractwas found to give the best yields, it was used in all thesubsequent experimental essays.

Selection of significant variables by Plackett–Burmandesign

The Plackett–Burman design was used to investigate theeffects of eight variables on α-L-arabinofuranosidase produc-tion (Table 1). The design matrix selected for screening thesignificant variables in α-L-arabinofuranosidase productionand their corresponding responses are given in Table 2. Theadequacy of the model was calculated, and the variablesevidencing statistically significant effects were screened viaStudent’s t test for ANOVA (Table 3). Factors evidencing Pvalues of less than 0.01 were considered to have significanteffects on the response, and were, therefore, selected forfurther optimization studies. Among the variables screened,pH, wheat bran percentage and MgSO4 concentration wereidentified as the most significant variables influencing α-L-arabinofuranosidase production by T. thermophilus. In fact,the pH value was noted to exert a negative effect on α-L-arabinofuranosidase production. Wheat bran and MgSO4,however, were found to exert a positive effect. The values ofall the other variables were statistically insignificant and were,therefore, not considered in the subsequent analysis. Theoptimum levels of the three significant variables selected werefurther determined by performing a central composite design.

Optimization of selected variables using response surfacemethodology

A CCD was performed to determine the optimum levelsof the significant factors (wheat bran percentage (X1),pH (X2) and MgSO4 concentration (X3)) and the effect oftheir interactions on α-L-arabinofuranosidase production.The results obtained were subjected to an ANOVA todetermine the significant differences. Table 4 presents theexperimental responses for the 19 runs. It can be noted

0

0.05

0.1

0.15

0.2

0.25

0.3

OSX BIX BEX WB BB WS RFCarbon source (2% w/v)

(U/m

l)

0

0.05

0.1

0.15

0.2

0.25

0.3

1 2 3 4 5 6 7Nitrogen source (1g/l)

(U/m

l)

b a

Fig. 1 Effect of carbon (a) and nitrogen (b) sources on α-L-arabinofuranosidase production by T. thermophilus. Enzyme activitywas measured after 5 days of culture. Carbon sources at 2%: oat-speltxylan (OSX); birchwood xylan (BIX); beechwood xylan (BEX); wheat

bran (WB); wheat straw (WS); rabbit food (RF). Nitrogen sources at1 g/l: peptone (1); Yeast extract (2); Urea (3); ammonium sulphate (4);ammonium phosphate (5); sodium nitrate (6); nitrate ammonium (7)

Appl Microbiol Biotechnol (2010) 85:1361–1372 1365

that there was a considerable variation in the amount of α-L-arabinofuranosidase activity produced and that thisvariation depended heavily on the levels of the threeindependent variables in the medium that varied from0.137 U/ml (run 3) to 0.7 U/ml (run 14).

By applying a least-squares method to the experimentaldata, the following second-order polynomial equation wasfound to adequately explain the α-L-arabinofuranosidaseproduction by considering only the significant terms(Table 5).

y ¼ 0:63þ 0:12X1 � 0:07X2 þ 0:08X3

� 0:08X 21 � 0:11X 2

2 � 0:06X 23

ð3Þ

Where by is the predicted response (α-L-arabinofuranosidaseproduction); X1, X2 and X3 are the coded values of wheatbran percentage, initial pH and MgSO4 concentration,respectively.

To test the fit of the model equation, the regression baseddetermination coefficient R2 was evaluated. The closer thevalues of R2 to 1, the better the model would explain thevariability between the experimental and the model-predicted values (Sayyad et al. 2007).The model presenteda high determination coefficient (R2=0.91), which indicatesthat 91% of the variability in the response were due to thefactor effects. The statistical significance of Eq. (3) waschecked by Fischer’s F test and the results from this test aswell as those from ANOVA yielded a very low p value

Code Coefficient F. Inflation Standard error t value p value

Intercept 0.219 1 0.008 27.13 <0.01***

A −0.049 1 0.008 −5.8 <0.01***,a

B 0.007 1 0.008 0.84 41.9

C 0.106 1 0.008 13.19 <0.01***,b

D 0.010 1 0.008 1.25 23.5

E 0.042 1 0.008 5.2 0.023

F −0.003 1 0.008 −4.13 0.139

G 0.023 1 0.008 2.86 1.43

H 0.060 1 0.008 7.41 <0.01***,b

Table 3 Estimated effect,regression coefficient andcorresponding t and P values forα-L-arabinofuranosidase activityin eight variable Plackett–Burman design experiments

***P<0.01 (non-significant)a Significant negative effectb Significant positive effect

No rune Variablesa Response

(X1) Wheat bran % (X2) pH (X3) MgSO4 g/l Abf production (U/ml)

1 −1 −1 −1 0.176

2 1 −1 −1 0.540

3 −1 1 −1 0.137

4 1 1 −1 0.322

5 −1 −1 1 0.237

6 1 −1 1 0.673

7 −1 1 1 0.197

8 1 1 1 0.500

9 −1.681 0 0 0.320

10 1.681 0 0 0.544

11 0 −1.681 0 0.524

12 0 1.681 0 0.195

13 0 0 −1.681 0.280

14 0 0 1.681 0.700

15 0 0 0 0.620

16 0 0 0 0.650

17 0 0 0 0.592

18 0 0 0 0.661

19 0 0 0 0.640

Table 4 The central compositedesign matrix employed for threeindependent variables and resultof α-L-arabinofuranosidaseproduction

aX1: wheat bran % (−1.681=1.31; −1=2; 0=3; +1=4; +1.681=4.68). X2: pH (−1.681=5.31;−1=6; 0=7; +1=8; +1.681=8.68). X3: MgSO4 (g L−1 )(−1.681=0.32; −1=0.6; 0=1;+1=1.4; +1.681=1.67)

1366 Appl Microbiol Biotechnol (2010) 85:1361–1372

(p=0.025, p<0.05), thus demonstrating that the model washighly significant and reliable. The Student t distribution,the corresponding p value and the parameter estimate aregiven in Table 5. The p values are used as a tool to checkthe significance of each of the coefficients which are, inturn, necessary to understand the pattern of the mutualinteractions between the best variables. In fact, when themagnitude of the t test value is large and the P value issmall, this indicates that the corresponding coefficient ishighly significant (Karthikeyan et al. 1996). As far as thecurrent study is concerned, the estimated parameters andthe corresponding P values suggest that, among all theindependent variables, X1 (wheat bran percentage), X2

(initial pH) and X3 (MgSO4 concentration) had a significanteffect on α-L-arabinofuranosidase activity production. Theparity plot (Fig. 2) showed a satisfactory correlationbetween the experimental and the predicted values(obtained from Eq. 3) of α-L-arabinofuranosidase produc-tion, wherein, the points cluster around the diagonal lineindicated the optimal fit of the model, particularly becausethe deviation between the experimental and predictedvalues was minimal.

Localization of optimum conditions

The three-dimensional response surface and theircorresponding contour plots were obtained on the basis ofthe model equation in order to determine the optimum level ofeach factor selected for maximum α-L-arabinofuranosidaseactivity production by T. thermophilus. Figure 3a presentsthe 3D plot and its corresponding contour plot. It shows theeffects of wheat bran percentage and initial pH on α-L-arabinofuranosidase activity production when MgSO4 wasfixed at its middle level (1 g/l). It can be noted that at alow initial pH value, the increase in wheat branpercentage induced a significant increase in α-L-arabi-nofuranosidase production from 0.14 U/ml to 0.7 U/ml.At a high initial pH value, however, this increase waslower. These findings suggest that α-L-arabinofuranosi-dase was better induced at low initial pH values and athigh wheat bran concentration. By further subjecting thedata from Fig. 3a to a Nemrod-W software analysis, itwas found that the maximum predicted value of α-L-arabinofuranosidase activity production was 0.7 U/ml. Inthis case, the optimum wheat bran concentration andinitial pH value in the uncoded units were 3.7% and 6.5,respectively.

Figure 3b shows the effect of wheat bran and MgSO4

concentrations on α-L-arabinofuranosidase productionwhen the initial pH value was fixed at its middle level(pH 7). The yield of α-L-arabinofuranosidase increasedwhen MgSO4 concentration exceeded its middle level andreached a maximum activity when MgSO4 concentrationattained 1.3 g/l at high wheat bran percentage. Further-more, the inverse matrix (Eq. 3) was solved using theNemrod-W software. The maximum predicted value forα-L-arabinofuranosidase activity obtained was 0.72 U/mL.In this case, the optimum wheat bran and MgSO4 con-centration in the uncoded units were 3.8% and 1.3 g/l,respectively.

Figure 3c shows the effects of initial pH and MgSO4

concentration on α-L-arabinofuranosidase production when

Model term Coefficient F. inflation Standard error t. exp. Significance %

Intercept 0.635 1 0.012 52.18 <0.01***

X1 0.122 1 0.007 16.35 <0.01***

X2 −0.075 1 0.007 −10.16 0.050

X3 0.083 1 0.007 11.30 0.035

X12 −0.085 1.04 0.007 −11.55 0.032

X22 −0.111 1.04 0.007 −15.02 0.011

X32 −0.065 1.04 0.007 −8.77 0.093

X1X2 −0.039 1 0.009 −4.05 1.55

X1X3 0.024 1 0.009 2.46 6.90

X2X3 0.005 1 0.009 0.57 59.90

Table 5 The least-square fit andparameters (significant of re-gression coefficient)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 0.2 0.4 0.6 0.8

Actual α-L-arabinofuranosidase activity (U/ml)

Pre

dic

ted

α-L

-ara

bino

fura

nos

idas

eac

tivi

ty (

U/m

l)

Fig. 2 Parity plot showing the distribution of experimental vs. model-predicted values for α-L-arabinofuranosidase production

Appl Microbiol Biotechnol (2010) 85:1361–1372 1367

wheat bran concentration was fixed at its middle level (3%).When the initial pH of the cultivation medium was slightlyacidic, the increase of MgSO4 concentration favoured theaccumulation of α-L-arabinofuranosidase activity. Howev-er, no significant effect was observed for MgSO4 on α-L-arabinofuranosidase production at an alkalophilic pH. Inthis particular case, the maximum predicted value for α-L-arabinofuranosidase activity was 0.64 U/ml, which wasachieved when the initial pH and MgSO4 concentrationwere 6.58 and 1.26 g/l, respectively.

Validation of the model

The model was verified for the three variables within thedesign space. Four combinations of production conditionswere selected by the software and were then tested for α-L-arabinofuranosidase production (Table 6). The experimentalvalues of α-L-arabinofuranosidase production that weredetermined were found to be in good agreement with thosethat were statistically predicted by the model (R2=0.90),thus confirming the authenticity and reliability of the

Fig. 3 a Response surface plotand contour plot for the com-bined effects of wheat bran andpH on α-L-arabinofuranosidaseproduction by T. thermophiluswith constant MgSO4 concen-tration (1 g/l). b Response sur-face plot and contour plot for thecombined effects of wheat branand MgSO4 concentration onα-L-arabinofuranosidase pro-duction by T. thermophilus withconstant initial pH value (pH 7).c Response surface plot andcontour plot for the combinedeffects of initial pH and MgSO4

concentration on α-L-arabino-furanosidase production by T.thermophilus with constantwheat bran percentage (3%)

1368 Appl Microbiol Biotechnol (2010) 85:1361–1372

model. In addition, the average error (difference betweenobserved and predicted value) was close to zero, indicatingthe absence of bias in the predictions made by the model.

Time course of α-L-arabinofuranosidase productionby T. thermophilus

The time course of α-L-arabinofuranosidase production byT. thermophilus for both the optimised and unoptimisedmedia are shown in Fig. 4. In the optimum conditions, thebiosynthesis of the α-L-arabinofuranosidase began on thesecond day of culture and reached a maximum after5 days. The production of α-L-arabinofuranosidase slight-ly decreased after 6 days, and this can be attributed to anauto-degradation mechanism (Hoffman and Breuil 2002).However, the maximum of α-L-arabinofuranosidase activ-ity obtained under unoptimised conditions was only0.27 U/ml after 6 days. By optimising the mediumcomposition and the culture conditions, the production ofα-L-arabinofuranosidase was enhanced from 0.26 U/ml to0.72 U/ml in a reduced time of culture, which was only5 days instead of 6.

Enzyme characteristics

The thermoactivity and thermostability of the crude α-L-arabinofuranosidase from T. thermophilus are shown inFig. 5a. The optimum temperature ofα-L-arabinofuranosidasewas 55 °C at pH 7.0 with a half-life of 10 h at thistemperature. The enzyme retained 42% and 26% of itsactivity when incubated at 60 and 65 °C, respectively over aperiod of 10 h. Moreover, at 45 and 50 °C, the enzyme wasstable and retained more than 90% of its activity after thesame incubation period. The optimum pH of the crude of α-L-arabinofuranosidase was 7.0 and the enzyme was verystable over a considerable pH range from 4 to 9 (>80%relative activity; Fig. 5b)

Enzymatic hydrolysis and arabinose productionfrom agro-industrial residues

Different agro-industrial residues were used here to testthe ability of the α-L-arabinofuranosidase of T. thermophi-lus to act synergistically with other xylanolytic enzymes

Table 6 Data for the validation of the experimental model

Run order Variable valuesa Abf production (U/ml)

X1 (%) X2 X3 (g/l) Experimental Predicted

20 2.29 6.59 0.88 0.480 0.468

21 3.71 6.59 0.88 0.665 0.653

22 3.00 7.82 0.88 0.410 0.454

23 3.00 7.00 1.35 0.613 0.644

a X1 Wheat bran; X2 pH; X3 MgSO4; R2 =0.90

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0Time (days)

α -L

-ara

bin

ofu

ran

osi

das

e ac

tivity

U/m

l

8642

Fig. 4 Kinetics of α-L-arabinofuranosidase production by T. thermo-philus: (filled square) α-L-arabinofuranosidase production (Units permillilitre) before optimization; (open circles) α-L-arabinofuranosidaseproduction after optimization

0

20

40

60

80

100

120

0 4 8 12

pH

Rel

ativ

e ac

tivi

ty (

%)

a

0

20

40

60

80

100

120

0 20 40 60 80

Temperature

Rel

ativ

e ac

tivi

ty (

%)

b

62 10

Fig. 5 Optimal temperature (open upright triangle), thermal stability(filled square) of the crude extracellular α-L-arabinofuranosidaseproduced by T. thermophilus (a) and optimal pH of α-L-arabinofur-anosidase activity (open upright triangle) and pH stability (filledsquare; b)

Appl Microbiol Biotechnol (2010) 85:1361–1372 1369

for hemicellulose hydrolysis and arabinose production(Table 7). The hydrothermal treatment allows destabilisa-tion of the cellulose–hemicellulose network and makessubstrates more accessible for enzymes (Petersen et al.2009). After incubation at 180 °C during 30 min, allsubstrates have liberated a low quantity of reducing sugars;this showed that hydrothermal treatment conserved theoligomeric aspect of the different polymers in the liquidfraction (Petersen et al. 2009). The results summarised inTable 7 show that enzymatic hydrolysis of the differentsubstrates liberated a various concentrations of reducingsugars. These concentrations were largely depending onincubation time and lignocellulosic materials composition.The incubation time was prolonged to 4 h for all substratesbut we do not observe any increase in reducing sugarconcentration (data no shown). On the other hand, theHPLC analysis proves liberation of arabinose from allsubstrates. Sorghum straw and wheat sesame are thetow potential substrates for arabinose production with4.6 and 4.7 mg/g, respectively. Knowing that thepercentage of arabinose for these two substrates do notexceed 5% (Vazquez et al. 2007; Carvalho et al. 2001),then arabinose produced correspond to a hydrolyzing yieldof roughly 10%.

Glucose and xylose were also produced by enzymatichydrolysis proving the synergistic action between differentenzymes of T. thermophilus. Glucose is the most abundantsugar in the different substrates and is highly produced byenzyme hydrolysis, particularly in case of barley bran andwheat straw (16.5 and 16.6 mg/g, respectively).

Discussion

The use of statistical models to optimise culture mediumcomponents and conditions has enhanced in the present-daybiotechnology research, due to its ready applicability andaptness. Many researchers have attempted to inducexylanolytic enzymes production by using inexpensivecarbon and nitrogen sources in culture medium (Gomes etal. 2000). In this context, α-L-arabinofuranosidase produc-tion was investigated and we showed that it is dependent on

the availability of both carbon and nitrogen sources. Bothexert regulatory effects on enzyme synthesis.

T. thermophilus showed the highest α-L-arabinofuranosidaseproduction on wheat bran and yeast extract, used as carbon andnitrogen sources, respectively. Wheat bran is known to containhigh proportions of arabinoxylan (Beaugrand et al. 2004) and isconsidered as the most inductive and inexpensive carbon sourcefor α-L-arabinofuranosidase production (Lauruengtana andPinphanichakarn 2006). This carbon source was better thanarabitol and arabinose considering as the strong repressors ofenzyme secretion. This latter result, however, stands in sharpcontrast with previously reported studies that used arabinoseand arabitol as only carbon sources by P. purpurogenum (DeIoannes et al. 2000) and A. terreus (Le Clinche et al. 1997). Inprevious reports (Panagiotou et al. 2007), fungi producedhigher levels of α-L-arabinofuranosidase activities when grownon organic nitrogen sources and, especially, yeast extract.

The significant variables necessary to enhance α-L-arabinofuranosidase production were selected using thePlackett–Burman design. Among these variables screened,pH, wheat bran percentage and MgSO4 concentration wereidentified as the most significant variables influencing α-L-arabinofuranosidase production by T. thermophilus. Thesignificance of these three variables could be explained inthe next paragraph.

In growth media, wheat bran has been reported to be anexclusive carbon source and a strong inducer of arabinases(Beaugrand et al. 2004). The pH value has also beenreported to play an important role in the controlling of theexpression of many genes, especially carbohydrolasesgenes of filamentous fungi (Tilburn 1995). The ratio ofxylanase/cellulase production by Trichoderma reseei waspreviously reported to be highly dependent on the pH of theculture medium (Bailey et al. 1993). MgSO4 has also beenconsidered as a good stimulator of mycelium growth,decrease the dormancy of the spores and can affect enzymeproduction yields (Kirillova et al. 1975).

The CCD design plan exploited in the present studyenabled us to investigate the culture conditions that supporta threefold increase in α-L-arabinofuranosidase production.A high degree of similarity was observed between thepredicted and experimental values that reflected the

Reducing sugars mg/ga Glucose mg/g Xylose mg/g Arabinose mg/g

T0 1h 2h 3h 1h 2h 3h 1h 2h 3h 1h 2h 3h

WBb 0.7 112.6 153.6 175.6 3 5.6 6.6 1.1 1.5 3.7 0.8 1.2 1.2

BB 1 90.4 141.6 155.4 5.8 8.3 16.5 0.9 1 1 0 0.5 0.5

SS 1.2 81.4 172 183.9 7.5 13.3 14.2 0.3 1 2.2 3 4.1 4.6

WS 0.9 54.4 72.4 94 4.7 6 16.6 1.6 2 1.8 1.1 1.2 1.2

WSe 1.2 18.4 46.3 82.2 3 7.6 8.3 4 4.4 4 1 3.3 4.7

Table 7 Saccharification ofvarious agro-industrial residuesand sugars production

a Sugars concentration expressedin milligrames per gramme ofagro-industrial residuesb Agro-industrial residues (WBwheat bran, BB barley bran, SSSorghum straw, WS wheat straw,WSe wheat sesame)

1370 Appl Microbiol Biotechnol (2010) 85:1361–1372

accuracy and applicability of RSM to optimise the processfor enzyme production. Maximum α-L-arabinofuranosidaseproduction was achieved at pH 6.7, 3.7% wheat bran and1.2 g/l MgSO4. Excess or diminution in one of these valuesmay cause a disruption in enzyme production yield.However, when the percentage of wheat bran exceeded3.9%, the yield of α-L-arabinofuranosidase decreased. Thiscan be attributed to the catabolic repression and oxygendiffusion limitation. In fact, this result is in agreement withprevious reports where the excess of wheat bran concen-tration decreased xylanase production by Aspergillus nigerAN-13 (Cao et al. 2008) and Penicillium oxalicum ZH-30(Li et al. 2007).

The properties of the crude α-L-arabinofuranosidasewere also studied. The optimal temperature and pH wereat 55 °C and pH 7.0, respectively. This enzyme was verystable over a considerable pH and temperature range. Thisresult is in the range of those reported in the literatureconcerning α-L-arabinofuranosidase from different strainsof fungi (Saha 2000). Stability and activity at high temper-atures are desirable properties in this type of enzymes,considering the fact that the most industrial processeswhere xylanolytic enzymes can be useful are carried outat high temperatures (Wong and Saddler 1993). Accord-ing to their physicochemical properties, Saha havecompared the α-L-arabinofuranosidase of some fungi andshowed that the majority of these enzymes were active andstable only at acidic pH (Saha 2000) The stability of α-L-arabinofuranosidase of T. thermophilus at a large pH rangecan be attributable to other extracellular proteins which areassociated with α-L-arabinofuranosidase and which pro-tect it from denaturation by the effects of pH (Fang et al.2007). This characteristic makes this enzyme potentiallyuseful in a broad range of industrial applications.

After optimization, α-L-arabinofuranosidase productionincreased threefold and we also observed a notable enhancein the levels of other xylanolytic enzymes such as the endo-xylanase, the β-xylosidase and the β-D-mannosidase toreach 11.5 U/ml, 0.8 U/ml and 0.45 U/ml, respectively(data not shown). This xylanolytic complex can play animportant role in the saccharification of plant cell wallshemicellulosic fraction (Sunna and Antrankian 1997).According to Saha, the conversion of hemicellulose tovalue-added useful products by enzymatic and/or fermen-tation routes holds considerable promise for convertingdiscarded and underutilised agricultural residues to useableproducts (Saha 2000). In this context, the crude enzyme ofT. thermophilus rich in α-L-arabinofuranosidase activity canbe considered as a good alternative for lignocellulosic plantmaterial saccharification and particularly for arabinoseproduction. Considering the important implications of theresults obtained in the present study, further studies arecurrently under way in our laboratories to improve α-L-

arabinofuranosidase production from T. thermophilus fun-gus in different culture conditions (large-scale batchfermentation and continuous culture), to investigate itspurification and biochemical characterization, and to makethis enzyme suitable for future industrial applications.

Acknowledgements This work has been supported by grants fromthe Tunisian government “Contrat-Programme” Ministère de l’En-seignement Supérieur de la Recherche Scientifique et de la Tech-nologie of Tunisia. We would like to express our gratitude to Dr.Khemais Benhaj from CBS for his precious comments on themanuscript. Special thanks are also due to Mr. Anouar Smaoui fromthe English Unit at the Sfax Faculty of Science for carefullyproofreading and editing the manuscript of the present study.

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