sodium dodecyl sulphate, a strong inducer of thermostable glucanhydrolase secretion from a...

Sodium Dodecyl Sulphate, a Strong Inducer of ThermostableGlucanhydrolase Secretion from a Derepressed Mutant Strainof Bacillus alcalophilus GCBNA-4

Nadia Shamim & Sikander Ali & Ikram-Ul-Haq

Received: 18 May 2012 /Accepted: 13 February 2013 /Published online: 2 March 2013# Springer Science+Business Media New York 2013

Abstract In the present study, we report the optimisation of batch conditions for improvedα-1,4-glucan-glucanohydrolase (GGH) secretion by a nitrous acid (NA)-treated Bacillusalcalophilus. The wild (isolate GCB-18) and NA-derivative (mutant GCBNA-4) weregrown in a medium containing 10 g/L nutrient broth, 10 g/L starch, 5 g/L lactose, 2 g/Lammonium sulphate, 2 g/L CaCl2 and phosphate buffer (pH 7.6). Sodium dodecyl sulphate(SDS) was used as an enzyme inducer while batch fermentations were carried out at 40 °C.The mutant produced GGH in 40 h which was 15-fold higher than the wild in presence ofSDS. Thermodynamic studies revealed that the mutant culture exhibited the capability forimproved enzyme activity over a broad range of temperature (35–70 °C). The enzyme waspurified by cation-exchange column chromatography with ∼80 % recovery. The perfor-mance of fuzzy-logic system control was found to be highly promising for the improvedsubstrate conversion rate. The correlation (1.045E+0025) among variables demonstrated themodel terms as highly significant indicating commercial utility of the culture used (P<0.05).

Keywords Bacillus alcalophilus . Enzyme inducer . 2-factorial design . Glucanhydrolasesecretion . Sodium dodecyl sulphate . Thermal inactivation

Introduction

The enzyme α-1,4-glucan-glucanohydrolase (GGH, EC 3.2.1.1) randomly hydrolyses α-1,4glucosidic linkages in an endo-fashion throughout the starch molecule producing oligo- andmono-saccharides including maltose, glucose and alpha limit dextrins. It has commercialapplications in food-, detergent-, textile-, paper- and starch-processing industries [1]. Its

Appl Biochem Biotechnol (2013) 169:2467–2477DOI 10.1007/s12010-013-0139-9

Ikram-Ul-HaqInstitute of Industrial Biotechnology (IIB), GC University, Lahore, Pakistan

N. ShamimDepartment of Botany, GC University, Lahore, Pakistan

S. Ali (*)H. 30, St. 7, Tezab Ahata, Lahore-39, Pakistane-mail: [email protected]

microbial production has been extensively studied. The fermentation design and formulation isprimarily based on microorganism, medium composition, basal substrate, process parametersand enzyme thermostability [2]. The first step in starch processing is carried out by BacillusGGH, which depolymerises starch to maltodextrins and corn syrup solids by liquefaction [3].The metabolites are usually analysed during or after the completion of a process. The secretionof amylolytic enzyme is generally characterised by a flexible, unsteady, limited and non-lineardynamic operation [4]. The operating variables must not be altered to obtain a consistentproduct quality. However, changes in product yield may arise from deviation in specifiedtransfer routes or variation in the impurities of medium [5]. The inherent non-linearity ofGGH secretion renders its control difficult. So there is a need to fine-tune the process byintelligent control. Fuzzy logic is an approach to control the process performance and thus hasbecome a popular handling tool in fermentation-based technology [6, 7].

The secretion of GGH can be improved by adding surfactants into the production medium.Sodium dodecyl sulphate (SDS, NaC12H25SO4) is an organic compound consisting of a 12-carbon tail attached to a sulphate group, giving the material the amphiphilic properties requiredfor a detergent. It is a water-soluble, anionic compound normally used for protoplast fusion,decreasing medium surface tension or increasing cell membrane permeability, all factors thatfacilitate secretion of proteins from microbial cells [8]. Besides some previous research [9],further investigation is still needed to optimise the cultural conditions for better enzymesecretion by characterizing the surfactant SDS as an enzyme inducer. In this manuscript, weassessed Bacillus alcalophilus for enhanced GGH production after inducedmutagenesis using afuzzy-logic control system. From the available literature, we feel that this is a first report of itskind from a novel bacterial culture (B. alcalophilus) which may play a vital role in food-basedindustries and microbial biotechnology. Activation enthalpy and entropy were determined toelucidate the phenomenon involved in enzyme secretion and its thermal inactivation. A twofactorial experimental design i.e. Plackett–Burman method was further used to identify signif-icant variables influencing hyper enzyme secretion in a batch process.

Materials and Methods

All chemicals and reagents used in this study were of analytical grade, or otherwise, of thehighest possible purity. These were acquired from SigmaChemicals Inc. (St. Louis,MO, USA).

Isolation of Organism, Induced Mutagenesis and Development of Resistance

Wild cultures (14) of B. alcalophilus were isolated from saline-alkalophilic soil samplescollected from Kala-Khatai areas near Lahore (Pakistan). The isolates were grown on nutrient(NB) agar slopes, pH 7.2. GCB-18, being a hyper-producer of amylase, was subjected toinduced mutagenesis to increase its amylolytic potential. For this, different concentrations(0.05–0.2 M) of nitrous acid (NA), prepared in acetate buffer (0.45 mM, pH 4.5) were addedto centrifuged (6,000×g for 15 min) bacterial cells. The suspension was swirled for 10 min.Afterwards, 1 mL of the suspension was withdrawn and diluted 5-fold in phosphate buffer(0.2M, pH 7.6) to neutralise the mutagen. The treated suspension (0.1 mL) was inoculated ontoNB-agar plates. A control was run in parallel (without mutation).

The mutant strain was harvested during the exponential phase of growth, washed withsterile distilled water and plated on NB-agar medium supplemented with 2-deoxy-D-glucose(2dg, 0.02–0.1 mg/mL). Colonies appearing in 16–20 h were sub-cultured, selected forvigorous growth and tested for stability during GGH secretion. Samples were drawn

2468 Appl Biochem Biotechnol (2013) 169:2467–2477

periodically, washed and plated on the medium to select strains resistant to various 2dglevels. Colonies appearing 24–36 h after the incubation at 40 °C were picked up, transferredto NB-agar slopes and screened independently for enzyme activity.

The master mutant culture was preserved in liquid paraffin and stored at 4°C in a coldcabinet (440P, Sanyo, Japan).

Inoculum Preparation and Cell Count

A total of 100mL ofmedium containing 8 g/L nutrient broth, 10 g/L soluble starch and 1 g/L CaCl2in phosphate buffer (pH 7.6) was transferred to 500-mL cotton plugged Erlenmeyer flask andsterilised at 15 psi (121 °C) for 15 min. After cooling, a loop full of bacterial cells was asepticallytransferred and rotated in a shaking incubator (X.X2.C. Gallenkamp, UK) at 160 rpm (40 °C) for24 h. The cell count was made on a haemocytometer slide bridge (101 FF1, Neubauer, Germany).

Process Control and Fermentation Conditions

Hundred millilitres of the medium containing 10 g/L nutrient broth, 10 g/L soluble starch, 5 g/Llactose, 2 g/L ammonium sulphate and 2 g/L CaCl2 in phosphate buffer (pH 7.6) was transferredto separate 500-mL conical flasks (with/without surfactant) and cotton plugged. After sterilizingin an autoclave at 121 °C for 15 min and cooling to room temperature, each flask was seededwith 1 mL of the inoculum (1.325×107CFU/mL). Incubations were carried out in a shaker(200 rpm) at 40 °C for 48 h. All experiments were performed in a set of three parallel replicates.

Enzyme Assay

GGH activity was estimated after Rick and Stegbauer [10]. One unit of activity is equivalentto that amount of enzyme, which in 1 min liberates reducing group from 1 % Linter’s solublestarch corresponding to 1 mg maltose hydrate. For estimation, 1 mL of enzyme extract(pH 7.5) was incubated at 60 °C using 1 % (w/v) soluble starch solution. Reducing sugarswere determined by adding 3,5-dinitro salicylic acid reagent, boiling for 5 min, cooling andmeasuring the A546 against a maltose standard. A blank was run in parallel replacing theenzyme extract with 1 mL of distilled water.

Enzyme Purification

The culture filtrate was concentrated about 10-fold using an ultrafiltration unit at 40 °C for 2 h(Millipore Co, USA). Thereafter, ammonium sulphate was added to the concentrate to reach60 % saturation (w/v) and stirred overnight (120 rpm) on a magnetic stir plate. The precipitatedsuspension was centrifuged at 16,000×g for 30 min at 4 °C and decanted. The pellet wasdissolved in 30 mM sodium phosphate buffer (pH 6.0), dialysed against distilled water using aSpectrapor-1 tube (Funakoshi Co. Ltd, Tokyo, Japan) and subjected to cation-exchange columnchromatography. Partially purified enzyme solution (60 mL) was applied to a toyopeal column(diameter 26 mm, length 200 mm). Proteins were eluted from the column with a NaCl gradient(0–0.5 mM) in 30 mM sodium phosphate buffer (pH 6.0) at a flow rate of 4 mL/min.

Determination of Biomass, Saccharide Moiety and Protein Content

Biomass was determined turbidimetrically using a spectrophotometer. Dry cell weight wasstandardised by measuring A650. Saccharides were analysed by isocratic high-performance

Appl Biochem Biotechnol (2013) 169:2467–2477 2469

liquid chromatography system (HPLC, PerkinElmer, USA). The separation was achievedusing universal column (C18, HPX-87H ion exchange column 300×78 mm) maintained at45 °C in a column oven. Sulphuric acid (0.002 N) in HPLC grade water served as a mobilephase at 0.6 mL/min. The samples were detected using refractive index detector andquantified using Turbochron-4 software. Total protein content was determined againstbovine serum albumin as a standard after Bradford [11].

Depiction of Thermodynamical Approach

The empirical approach of Arrhenius was used to describe the relationship of temperature-dependent, irreversible inactivation of GGH production at a temperature range of 35–70°C[12]. Specific rate of product formation (qp, U/gcells/h) was used to calculate differentvariables following the equations,

qp ¼ T � kB heΔS� R= e�ΔH� RT=� ð1Þ

ln qp T=� � ¼ ln kB h=ð Þ þΔS* R= �ΔH* RT= ð2Þ

The plot of ln(qp/T) against 1/T gave a straight line whose slope was −ΔH/R and interceptwas ΔS/R+ln(kB/h), where h (Planck’s constant)=6.63×10

−34 Js and kB (Boltzman constant[R/N]=1.38×10−23J/K where N (Avogadro’s number)=6.02×1023per mole.

Fuzzy-Logic System Control by Centroid Method

The step-wise fermentation process fine-tuned and operated using a fuzzy logic control [13].The input variables were error and error rate for enzyme production (P). The lower andhigher values of operating parameters (Q) were selected as output variables. The discoursecomprised of three sets i.e. negative (NE), positive (PO) and zero (ZE). The centroid methodwas used to obtain a lower or higher P value. An initial rule base was made by stating anumber of rules that were operating in the reaction vessel. The rules were written andchecked for their correctness by an interactive process to exert control action at lower Qvalues.

Application of Plackett–Burman Factorial Design

Duncan’s multiple range tests (SPSS-18, version 6.8) were applied under one-way ANOVAand the treatment effects were compared after Snedecor and Cochran [14]. Significantvariables were optimised using a two factorial experimental design [15]. Variables weredenoted at two widely spaced intervals and the effect of individual parameters on enhancedGGH secretion was calculated by the following equations,

Eo ¼X

Mþ �X

M��

N= ð3Þ

E ¼ b1 þX

b2 þX

b3þ b123 ð4Þ

In Eq. 3, Eο is the effect of first parameter under study while M+ and M− are responses ofenzyme secretion.N is the total number of optimisations. In Eq. 4, E is the significant parameter,β1 is the linear coefficient, β2 the quadratic coefficient and β3 is the interaction coefficient.


Results and Discussion

In the present study, 14 different wild cultures of B. alcalophilus were isolated from saline-alkalophilic soil samples and compared for their α-1,4-glucan-glucanhydrolase activity.Among the isolates, GCB-18 was subjected to induced mutagenesis to further increase itsenzyme production capability. Six mutant strains of bacteria developed after nitrous acidtreatments were screened independently for enhanced production of GGH. The mutants werepicked up from the NB-agar plates having 90 % death rate on the basis of bigger zones ofstarch hydrolysis. The enzyme production was ranged from 54.5 to 89.6 U/mL/min. Themutant GCBNA-4 gave maximum production which was 1.42-fold higher than the wild-culture GCB-18 (63.2 U/mL/min). It was sub-cultured on medium containing 2-deoxy-D-glucose and its stability for GGH production was determined at various levels. Wheninitially compared, high GGH producing colonies were obtained at 2dg concentration of0.02 mg/mL; however, these cultures lost stability after approximately 2 weeks. The reason

Wild culture (GCB-18)

Mutant strain (GCBNA-4)

a

b

Fig. 1 Time course comparison of GGH secretion with control (triangles) and test (squares, with SDS 0.1%,w/vadded at the time of inoculation) by wild and mutant B. alcalophilus. Each value is an average of three parallelreplicates. Y-error bars indicate the standard deviation (±SD) from the mean value


for this instability may be the development of resistance in bacterial cells after a fewgenerations, allowing a few unstable mutants to thrive. To eradicate this problem, thesecultures were again grown on medium containing different concentrations of 2dg. Theconcentration of 0.04 mg/mL was found optimal, as at this level GCBNA-4 gavefairly consistent enzyme production. In a similar study, Esfahani et al. [16] developeda mutant strain of Bacillus subtilis, which gave 1.2-fold higher enzyme activity thanits wild counter-part.

The optimal time frame probably reflects cellular entry into the stationary phase ofgrowth as reported by Gun et al. [5]. A time course comparison of enzyme secretionwith the control and test batch cultures (wild and mutant strains) was carried out for 8–72 h. The results are given in Fig. 1a and b. The maximum enzyme secretion wasachieved 40 h after the incubation in test by the mutant strain. Further increase in theincubation period led to a decreased enzyme secretion by both the wild and mutantstrains of B. alcalophilus. This reduction was probably due to the depletion of nutrientsin the fermented broth substantiating the findings of Jin et al. [17] who pointed out thatthe decreased enzyme production was due to the proteolysis of bacterial cells during thedecline phase. Maximal GGH secretion was observed when the surfactant was added atthe time of inoculation. Addition of SDS during the fermentation period was found tobe almost insignificant for enzyme secretion which might be due to the toxic effects ofthis surfactant. The decrease in bacterial growth illustrated prolong exponential phase ofcells which subsequently delayed the onset of stationary phase [18]. Lealem and Gashe[19] however, obtained maximal enzyme accumulation at stationary phase of growth(72 h). The current results were encouraging as the fermentation period was reducedfrom 48 to 40 h.

Surfactants not only reduce surface tension of fermentation medium and increaseenzyme secretion from bacterial cells, but may also enhance enzyme stability [5]. Tostimulate GGH secretion, various concentrations (0.2–2 %) of SDS were tested. SDS ata level of 0.1 % gave significant values for enzyme secretion. The results are shown inFig. 2. Increasing SDS concentration beyond the optimal resulted in the decreased

Fig. 2 Effect of different SDS concentrations (added at the time of inoculation) on GGH secretion by wild(black squares) and mutant (white squares) B. alcalophilus. Each value is an average of three parallelreplicates. Y-error bars indicate the standard deviation (±SD) from the mean value


production of enzyme in the culture broth. To study the effect of time of SDS additionon enzyme secretion by wild (GCB-18) and mutant (GCBNA-4) strains of B.alcalophilus, the surfactant was added to the production medium separately at 4, 8,12 and 16 h in comparison with a control. Figure 3 highlights the results. The enzymesecretion was higher when SDS was added at inoculation and reduced when surfactantwas added 8–12 h post-inoculation. Sodium dodecyl sulphate contains sodium as wellas sulphates that help to solubilise membrane proteins and increase air supply which

Fig. 4 Thermophilic behavior of wild (black squares) and mutant (white squares) B. alcalophilus for GGHactivity. Each value is an average of three parallel replicates. Y-error bars indicate the standard deviation(±SD) from the mean value

Fig. 3 Effect of time of SDS addition (0.1 %, w/v) on GGH secretion by wild (black squares) and mutant(white squares) B. alcalophilus. Each value is an average of three parallel replicates. Y-error bars indicate thestandard deviation (±SD) from the mean value


might lead to an increase in cell membrane permeability, thereby enhancing secretion ofbiomolecules. Although Malhotra et al. [4] reported that the secretion of GGH wasinhibited by SDS, in the present study 0.1 % SDS, however increased enzyme secretionby the mutant B. alcalophilus GCBNA-4. A higher concentration of this surfactantprobably increased the medium viscosity which decreased the medium-oxygen transferrate as reported by Ulger and Cirakoglu [20].

The thermophilic behavior of both wild and mutant strains of B. alcalophilus wasinvestigated by varying temperature from 35 to 90 °C (Eqs. 1 and 2). GGH secretionincreased when temperature was increased from 35 to 70 °C. The results are given inFig. 4. GGH secretion by the mutant was optimal when the fermentation medium wasincubated at 70 °C. Higher temperature beyond 80 °C reduced enzyme secretionpossibly due to the sensitivity of organism [21, 22]. On the basis of thermodynamiccharacterisation, the mutated culture of B. alcalophilus (Ea=20.52±4.5 kJ/mol,78.62 mg/mL protein) was found to be over 2-fold more stable than its wild culture(Ea=32.51±3.8 kJ/mol) as it required lower energy of activation for growth in theproduction medium (Fig. 5). Thermodynamic parameters indicated that the activationenthalpy of enzyme secretion by the mutant (ΔHD=27.64±2.7 kJ/mol) was lower thanthat of its wild parent (Table 1). The activation entropy of thermal inactivation by

Fig. 5 Arrhenius plots to calculate enthalpy and entropy of activation for GGH production at differenttemperatures (35–70 °C) during growth of a wild-culture, b mutant strain (activation enthalpy (black circles)and activation entropy (white circles))


mutant cells was very low (−291.22±12 J/mol/K) and comparable to that for amylaseproduction by a thermo-tolerant bacterial culture which reflected that the cell systemexerted protection against thermal inactivation of the enzyme [23]. In the present study,the enzyme was purified by cation-exchange column chromatography and more than80 % recovery was accomplished.

In the fuzzy logic control system, production (P) was taken as controlled variable,operating parameters (Q) as manipulated variables and substrate concentration aschangeable variable. The performance of the system using the specifically designedreaction vessel for GGH production by the mutant B. alcalophilus GCBNA-4 with inputmultiplicities in the operating variables was evaluated using the closed loop blockdiagram. Scheme 1 highlights the sketch out model design. The change in error wasworked out and converted to fuzzy form. The base rules were evaluated and the controlinput was calculated from the fuzzy logic. It was prepared by centroid method usingMatlab and its related Simulink. It was further developed for the optimal reactiondesign using the fuzzy logic toolboxes. A suitable value for fuzzy implementationwas also chosen. The process performance controlled by the fuzzy logic control systemby the bacteria gave much better yield substantiating Kasperski and Miskiewicsz [7].The present design of reaction vessel led to a promising conversion rate of substrateinto the final product.

The process parameters were determined using the Plackett–Burman design for GGHsecretion at optimal levels by B. alcalophilus (Eqs. 3 and 4) and these data are given inTable 2. A statistical analysis of the responses for enzyme secretion was also performedand is shown in Table 3. SDS as an enzyme inducer was added to check the degree offreedom necessary for enzyme activity. Analysis of linear, quadratic and interactioncoefficients were undertaken on the incubation period, SDS addition and enzyme thermo-stability. A slightly differential correlation between observed and predicted values was

Scheme 1 Design of the closed loop block diagram of fuzzy logic system for GGH activity by the mutantstrain of B. alcalophilus GCBNA-4

Table 1 Thermodynamic param-eters estimated by Arrhenius ap-proach for GGH production by B.alcalophilus GCBNA-4

The values in each set differsignificantly from each other atP≤0.05± indicates standard de-viation (SD) among three paral-lel replicates

Thermodynamicparameters

Enzymeformation

Thermalinactivation

Protein content(mg/mL)

Activation enthalpy, Ea, ΔH (kJ/mol)

GCB-18 45.68±3.6 32.51±3.8 27.82

GCBNA-4 27.64±2.7 20.52±4.5 68.58

Activation entropy, ΔHD, ΔS (J/mol/K)

GCB-18 58.16±2.5 −208.45±16 31.95

GCBNA-4 −46.35±6.5 −291.22±12 78.62


observed. The optimal levels for improved GGH secretion in shaking culture wereincubation period (40 h), temperature (70 °C), pH (7.6) and 0.1 % (w/v) SDS. The lowerprobability values and correlation, A and B1+2 for C values depicted that the model termswere significant (P<0.05). Ahuja et al. [24] analysed linear, quadratic and interactioncoefficients and highlighted that enzyme secretion was a function of the independentparameters. The addition of SDS as an enzyme inducer (degree of freedom=3) mighthave an important physiological role in enzyme stability as reported by Malhotra et al. [4].

Conclusion

In the present study, the mutant B. alcalophilus GCBNA-4 exhibited a total of 15-foldincrease in enzyme production over wild-culture GCB-18 in the batch fermentations beingcarried out at 40 °C (200 rpm) using phosphate buffer (pH 7.6). It was hypothesised thatSDS helped to solubilise membrane proteins, increased medium air supply and cellmembrane permeability, thereby enhanced enzyme yield. Thermodynamic studies re-vealed that the cell system exerted protection against thermal inactivation of enzyme(27.64±2.7 kJ/mol). More than 80 % enzyme was recovered by cation-exchange columnchromatography. Fuzzy logic performance revealed highly promising substrate conversionrate of over 60 %. Further, the value of correlation (1.045E+0025) revealed that factorialterms were highly significant (P<0.05).

Table 3 Statistical analysis ofmodel at significant process pa-rameters for GGH secretion fromB. alcalophilus GCBNA-4

CM—16.92; R2—0.262

Significant processparameters

Sum meanvalues

Fvalue

Degree offreedom

Probability(p)

A 84.73 11.75 1 0.0561

B1 112.65 13.5 1 0.0672

B2 0.346E+0025 16.02 3 0.0815

C 468.55 12.94 2 0.00978

Correlation 1.045E+0025

Table 2 Application of Plackett–Burman design for enhanced GGH secretion from B. alcalophilus GCBNA-4

Process parameters at two factorial design Enzyme secretion(U/mL/min)

Fermentation periodA

(h)SDSB1+2 Incubation

temperatureC (°C)Observed Predicted

Concentration1

(%)Time of addition2

(h)

40 0.05 0 60 6.42 2.08

40 0.05 0 65 5.89 5.55

48 0.10 0 70 5.94 1.24

48 0.15 4 70 9.76 0.78

56 0.20 8 75 3.40 7.02

The letters (A, B1+2, C) represent significant process parameters for fermentation


Acknowledgments Chairman, Department of Botany is thanked for his assistance and moral support. Allauthors contributed equally in this work. The major part of the work was carried out and completed atBiotechnology Research Centre, Department of Botany. This research received no specific grant from anyfunding agency in the public, commercial or not for profit sectors.

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