Optimization of polyhydroxybutyrate production by mixed cultures submitted to aerobic dynamic feeding conditions

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International Journal of Biological Macromolecules 60 (2013) 253– 261

Contents lists available at SciVerse ScienceDirect

International Journal of Biological Macromolecules

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ptimization of polyhydroxybutyrate production by marineacillus megaterium MSBN04 under solid state culture

. Sathiyanarayanana, G. Seghal Kiranb, Joseph Selvinc,∗, G. Saibabad

School of Life Sciences, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu, IndiaDepartment of Food Science and Technology, Pondicherry University, R.V. Nagar, Kalapet, Puducherry 605014, IndiaCentre for Microbiology, Pondicherry University, R.V. Nagar, Kalapet, Puducherry 605014, IndiaDepartment of Animal Science, Center for Pheromone Technology, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu,

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rticle history:eceived 29 April 2013eceived in revised form 17 May 2013ccepted 29 May 2013vailable online 5 June 2013

eywords:

a b s t r a c t

A marine sponge-associated bacterium Bacillus megaterium MSBN04 was used for the production of poly-hydroxybutyrate (PHB) under solid state culture (SSC). A central composite design (CCD) was employedto optimize the production medium and to find out the interactive effects of four independent variables,viz. tapioca industry waste, palm jaggery, horse gram flour and trace element solution on PHB produc-tion. The maximum yield of PHB 8.637 mg g−1 of substrate (tapioca industry waste) was achieved frombiomass 15.203 mg g−1 of substrate, using statistically optimized medium. The horse gram flour (nitro-

olyhydroxybutyrateptimizationapioca industry wasteolid state cultureacillus megaterium, PHB nanoparticles

gen source) and trace element solution were found to be critical control factors for PHB synthesis. The1H NMR analysis revealed that the polymer was a PHB monomer. PHB obtained from this study havinghigh molecular weight (6.7 × 105 Da) with low polydispersity index (PDI) value (1.71) and produced PHBwas used to synthesize PHB polymeric nanoparticles using solvent displacement approach. Therefore, B.megaterium MSBN04 is an ideal candidate that can be exploited biotechnologically for the commercialproduction of PHB under solid state culture.

. Introduction

Polyhydroxyalkanoates (PHAs) are group of biodegradable poly-ers of biological origin and PHAs are attractive substitutes

ver conventional petrochemical plastics to avoid the pollutionroblems and having similar material properties of various thermo-lastics. [1,2]. Different constituents of PHAs have been identifiednd characterized so far [3,4]; poly (3-hydroxybutyrate) (PHB) onef the PHAs is the most widely studied and best-characterizederivative. PHB normally accumulated in bacteria due to excessarbon and energy sources as well as the limitation of oxygen,itrogen and phosphorus. When the supply of limiting nutrient is

estored, the PHB can be degraded by intracellular depolymerasesnd subsequently metabolized as a carbon and energy source,hese can also be degraded by hydrolytic degradation [5,6]. PHB

Abbreviations: ANOVA, analysis of variance; CCD, central composite design;T-IR, Fourier transform infrared spectroscopy; GC, gas chromatography; GPC, gelermeation chromatography; NMR, nuclear magnetic resonance; PHAs, polyhy-roxyalkanoates; PHB, polyhydroxybutyrate; RSM, response surface methodology;AS, sterilized aged seawater; SSC, solid state culture; ZMA, Zobell marine agar;EM, transmission electron microscope.∗ Corresponding author. Tel.: +91 413 2655358; fax: +91 413 2655358.

E-mail address: [email protected] (J. Selvin).

141-8130/$ – see front matter © 2013 Elsevier B.V. All rights reserved.ttp://dx.doi.org/10.1016/j.ijbiomac.2013.05.031

© 2013 Elsevier B.V. All rights reserved.

is immensely used in medicine due their non-toxic nature, alsoapplied in pharmacy, agriculture, food industry even as raw mate-rial for enantiomerically pure chemicals and paint industry [7].The main advantage of using PHB in medicinal field is their bio-compatibleness and the end product of degradation, 3-hydroxybutyric acid is normally present in the human blood (1.3 mmol L−1)[8]. In addition, PHB fibers were used to stitch wounds in mousemodels and the polymeric materials were degraded significantly[9]. Moreover, PHB can be converted to nanoparticles, which canenhance the delivery of drugs to all parts of the body even throughthe smallest capillaries having diameter in the range of 5–6 mm[10]. Nevertheless, the production cost of PHB is high as comparedto that of the non-biodegradable plastics of fossil origin. A great dealof effort has been devoted in reducing the production cost by devel-oping more efficient bacterial strains and fermentation/recoveryprocesses [11].

Production cost of PHB is increased due to expensive raw mate-rials and it is estimated up to 20–50% of the total production cost.Thus reducing the higher PHB production cost is desirable usingcheaper raw materials [12]. One possible strategy for reducing costs

is to utilize the alternative substrates such as natural products,industrial wastes and agro industrial residues for PHB productionby different fermentation process [13,14]. Nowadays different agroindustrial residues like wheat bran, soy molasses oligosaccharides,

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ugarcane molasses sesame oil cake, groundnut oil cake, corn steepiquor etc., have been reported for PHB production [15–18]. Tapiocaydrolysate have been used for the production of PHB macro-olecule [19], however the production process and optimization

sing tapioca industry waste in solid state cultivation has not beeneported for the production of PHB. Tapioca industries are one ofhe source of pollution in India, as 25% of cassava root materials areonverted into waste with appreciable organic load with strongdor, if disposed untreated these wastes could cause considerablenvironmental pollution.

Optimization of bioprocess is one the major factor to reducehe production cost of all biotechnological commercial products20]. The classical optimization process always utilize that the ‘oneariable at a time’ approach produces non reliable results and inter-ctive effects of different variables for the production also cannote resolved by this approach [21]. Statistical experimental strate-ies including factorial design and response surface methodologyRSM) are more reliable than classical experiments [22]. Centralomposite design (CCD) is one of the most conventional experi-ental design among different classes of RSM and this strategy

articularly helps us to predict the better concentrations of sub-trates with less accidental errors. [23]. Statistical optimizationethods have been successfully employed for the optimization of

HB production through different submerged fermentation process24,25] Improved PHB production using industrial wastes by Bacil-us sp. and Azotobacter beijerinckii have been examined throughSM [26,27]. Unfortunately, statistical methods are not widelysed in the optimization of PHB production through solid stateulture. The current industrial processes use gram-negative bac-eria for the production of PHB, whereas gram-positive bacteriauch as Bacillus spp. are not much focused on the commercial con-ern [28]. Diverse bacteria from various environments have beenourced for feasible production of PHB and marine microbes arearely investigated for PHB production [29–31]. Marine spongesre usually having symbiotic relationship with different microor-anisms and the marine sponge-associated symbionts have beenccepted as prosperous resource of biological macromolecules [32].esearch on sponge-associated bacteria, will provide remarkableew avenues for biopolymer research in future. Considering theeed of potential PHB producers and economic production pro-esses using industrial waste, the present study aims to explorehe marine sponge-associated bacteria as PHB producers utilizingndustrial wastes under solid state culture (SSC), its an economi-ally efficient greener process scarcely employed for the productionf PHB for commercial applications. The special emphasis has beeniven to synthesize the PHB nanoparticles from high moleculareight produced PHB.

. Materials and methods

.1. Isolation, screening and identification of PHA polymerroducing marine sponge-associated bacteria

Marine sponge Spongia officinalis was collected from the south-ast coast of India at 10–15 m depth and the sponge-associatedacteria were isolated using Sponge agar 1, Sponge agar 2 [32]nd Zobell marine agar plates (ZMA). Amphotericin B (30 �g/�L)as added to inhibit the fungal contamination and the plates were

ncubated at 28 ◦C for 7 days in dark. The morphologically distinctolonies were re-isolated and maintained on ZMA (HiMedia) at 4 ◦C33]. Screening of PHA production was done by viable colony stain-

ng method. ZMA plates were amended with Nile blue A to give finalolume of 0.5 �g dye (mL medium)−1. The colonies were directlyxamined for fluorescence by exposing to UV light to detect theccumulation of polymer producers. The effective PHA producers

iological Macromolecules 60 (2013) 253– 261

were further confirmed by Sudan black B staining method [34].The morphological and biochemical characteristics of the PHA pro-ducer MSBN04 were identified according to Bergeys’s manual ofdeterminative bacteriology [35]. For molecular characterization,the genomic DNA was extracted [36] and nearly full-length 16SrRNA sequences were amplified by using primers 8F (5′-AGA GTTTGA TCC TGG CTC AG-3′) and 1492R (5′-GGT TAC CTT GTT ACG ACTT-3′). The 16S rRNA gene sequence obtained from the MSBN04 wasdeposited into GenBank (NCBI).

2.2. Selection of substrates and optimization of PHB productionunder solid-state fermentation (SSC)

For the development of SSC, various cheaper and eco-friendlysubstrates were screened including green gram flour, horse gramflour, palm jaggery, rice bran, wheat bran, groundnut oil cake andindustrial wastes from starch industry (pretreated sludge), sugarindustry (pretreated and treated molasses), dairy industry (pre-treated sludge), tapioca industry, mango pulp industry (pretreatedsludge), brewery industry and paper pulp industry (pretreatedsludge). Based on the screening results, eight substrates such aswheat bran, horse gram flour, palm jaggery, starch industry waste(pretreated sludge), sugar industry waste (treated molasses), sugarindustry waste (pretreated molasses), pulp industry waste (pre-treated sludge) and tapioca industry waste were further selectedfor SSC development. All the substrates were dried in a hot airoven at 60 ◦C. The dry weight of the substrate and moisture contentwere determined gravimetrically after drying of samples. Consid-ering the significance of moisture content on the development ofSSC, the moisture content was evaluated from the water evapo-ration rate of the non-inoculated medium at 30 ◦C for 7 days andwas weighed every 24 h. During evaporation 4% of moisture con-tent was declined every 24 h. At least 50% moisture content wasessential for optimal biomass production (data not shown). Thus,the moisture content was controlled during the incubation period(7 days) by starting experiment with 83% moisture content in theSSC. In the present study, new SSC media (tapioca industry waste,palm jaggery, horse gram flour and trace element solution) wasdeveloped for the optimization of PHA production. The produc-tion of PHA was performed triplicate in 250 mL Erlenmeyer flasks.To develop the SSC, 10 g dried substrate mixed with 5 mL of traceelement solution (moistening media) and 10 mL of sterile distilledwater. The trace element solution which contain in mg mL−1 of dis-tilled water viz.: Na2SO4, 25 mg; FeSO4·7H2O, 25 mg, MnSO4·4H2O,4.06 mg; ZnSO4·7H2O, 4.40 mg; CuSO4·5H2O, 0.79 mg; CaCl2·2H2O,73.4 mg; pH 7.0. The contents were double sterilized by autoclavingat 15 lb for 20 min and the sterilized solid substrates were inocu-lated with 3 mg of bacteria as inoculum for one gram of substrate,mixed properly and incubated at 30 ◦C for 4 days. Optimizationof PHB production was carried out by search one at a time tech-nique. Appropriate experimental models were developed to studythe interaction between the different factors such as carbon andnitrogen sources, inoculum size and salt concentration. The opti-mization process was completed with the effective concentrationof chosen carbon and nitrogen source to maximize the produc-tion under SSC conditions. Most appropriate carbon and nitrogensources were selected from the range of these sources used in theoptimization.

2.3. Optimization of physical parameters for the production ofPHB using one-factor-at-a-time experiments

For the optimization of PHB production, factors affecting cellgrowth and PHB production were investigated using one factorat a time method. The time course experiment was carried out in250 mL flask containing 20 g of the production medium up to seven

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ays. To determine the optimum initial pH for PHB production, theH (5–12) of the medium was adjusted by the addition of 1 M HClnd 1 M NaOH before sterilization. To find out the optimum tem-erature for PHB production, production medium was incubated at5, 20, 25, 30, 35, 40, 45 and 50 ◦C, respectively.

.4. Statistical optimization of PHA production using responseurface methodology

After the critical medium components were identified bylassical optimization, RSM was employed to optimize the com-onents concentration to maximize the PHB production. Fouractors (tapioca industry waste, palm jaggery, horse gram flour andrace element solution) that significantly affected PHB productionere optimized by RSM using 5-level-4-factorial central compos-

te design (CCD). A CCD obtained by using the software Designxpert (State-Ease, Inc., Minneapolis, USA, trial version 8.0.4.1) waspplied to elucidate the interaction of different variables on theiomass and PHB production. An experimental design of 30 experi-ents with six central points were formulated and the experimentsere conducted in 500 ml Erlenmeyer flasks containing produc-

ion medium prepared according to the design and inoculated with mg of seed culture per gram of substrate. The flasks were placed

n an incubator with humidified air injection at 30 ◦C for 4 days.iomass and PHB production were used as the dependent variablesresponses). The 3D contour graphs were created to understand thenteraction of different factors, and used to evaluate the optimizedomponents of the medium which influences the responses [23,37].

.5. Statistical analysis

Statistical analysis (means) of the experimental data was carriedut by Microsoft excel 2007. Design Expert software (trial version.0.4.1, Stat-Ease Inc., Minneapolis, USA) was used for the experi-ental designs and regression analysis of the experimental data.

tatistical analysis of the model was performed to evaluate thenalysis of variance (ANOVA). The quality of the polynomial modelquation was judged by determination of coefficient R2, and itstatistical significance was determined by F-test. The whole exper-ment was repeated thrice.

.6. Extraction and purification of polymer

For the extraction of polymer, 30 mL distilled water was addedo fermented substrate and stirred for 20 min, filtered through AP5 paper (Millipore) and remaining residues washed with 10 mLf water and filtered. The combined filtrates were centrifuged for0 min at 3500 × g and washed with water twice. The final bacte-ial pellet was used for polymer (PHB) quantification and for dryeight determination at 60 ◦C. Biomass data was expressed as cellry weight (cdw) of biomass (mg biomass) per initial dry weightdw) of medium (g medium). PHA polymer was extracted by modi-ed protocol from the lyophilized cell mass using 4 to 6% sodiumypochlorite solution (Rankem). Then the extracted polymer wasissolved in chloroform and precipitated in cold methanol to geture polymer. Finally, the obtained pellet was dried in rotary evap-rator (Yamato) and weighed. The amount of polymer (PHB) waselated to dry weight of medium and is given as mg PHB (mg PHB)er initial dry weight of medium (g medium). The yield of PHB wasxpressed as % of PHB from cell dry weight.

.7. Characterization of polymer

The purified polymer was thoroughly mixed with Potassiumromide (KBr) and dried. The dried sample was subjected to

iological Macromolecules 60 (2013) 253– 261 255

IR spectrum using Fourier Transform Infrared Spectrophotome-ter (PerkinElmer, USA) with spectral range of 4000–400 cm−1.The spectrum obtained was compared with that of the commer-cially available PHB (Sigma, USA). A constituent of the polymerwas investigated by using Gas chromatography (GC) (PerkinElmerAutosystem XL GC-TurboMass, USA). The lyophilized cell mass wassubjected to methanolysis and the resulting methyl esters of poly-mer were assayed. The peaks of the gas chromatography weresubjected to mass-spectral analysis and the spectra were analyzedby NIST MS search (version 2.0). Molecular mass analysis was con-ducted with purified polymer, which was dissolved in chloroformand introduced into a Gel permeation chromatography (GPC) (Shi-madzu, Japan). 1H NMR spectra was acquired by dissolving the PHBin deutrated chloroform (CDCl3) at a concentration of 10 mg/mLand analyzed on a Bruker Avance II 500 Spectrophotometer (BrukerBioSpin AG, Switzerland) at 22 ◦C [38].

2.8. Synthesis of PHB nanoparticles and characterization

PHB nanoparticles were synthesized using modified methodcalled nano-precipitation by solvent displacement approach. Inbrief, 10 mg of produced PHB was dissolved in acetone and injecteddrop-by-drop into distilled water with continuous stirring alongwith Polysorbate 80 [39]. When acetone gets miscible with aqueousenvironment the PHB nanoparticles were formed due to displace-ment of acetone by water under pressure. The high water activityresults the synthesis of PHB nanoparticles in the solution. Theresulting solution was centrifuged at 10,000 × g for 20 min and pel-let was dissolved in distilled water to separate the nanoparticlesalone. The synthesized PHB nanoparticles were negatively stainedwith 2% phosphotungstic acid and characterized by using brightfield transmission electron microscope (TEM).

3. Results and discussion

3.1. Isolation, screening and identification of PHB producerMSBN04

Currently plastic waste management is a major global issuebecause synthetic polymers are hazardous to our natural environ-ment and it has generated great interest in the development ofnovel plastics [40]. Exploration of PHB producers from marine envi-ronment could potentially replace synthetic polymers which arecurrently used. Among the 28 stable isolates, six strains showedpositive for PHB production, from these MSBN04 and MSBN08 wereconsidered as potential PHB producers. The scope of the presentreport is optimization, production, characterization of biopolymerfrom MSBN04, which was screened as effective PHA polymer pro-ducer based on the growth rate, the high intensity of fluorescenceunder UV-light (viable Nile blue A staining), presence of lipophilicinclusions in sudan black B staining (Fig. 1) and dry weight ofthe extracted PHB. Sponge isolate MSBN04 was identified by cul-tural, morphological, biochemical, physiological characteristics and16S rRNA based phylogenetic analysis. Microbiological proper-ties were tested according to Bergey’s manual of determinativebacteriology [35]. The sponge bacterial isolate was characterizedas gram-positive, spore forming, aerobic, non-motile, rod shaped,hydrolyzing casein and gelatin and citrate positive. The strain pro-duced acid by fermenting fructose, glucose, mannitol, sorbitol,trehalose, esculine, and D-arabitol. Based on these characteristics,the isolate was identified as genus Bacillus. Taxonomic affiliation of

the isolate was retrieved from the classifier program of RibosomalDatabase Project II (RDPII) using 16S rRNA sequence. Representa-tive of maximum homologous (97–99%) sequences of the isolatewas obtained from seqmatch program of RDPII and were used for the

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ig. 1. Sudan black B stained Bacillus megaterium MSBN04 under bright-field micro-cope. PHA granules appears dark blue in saffranin stained cytoplasm.

onstruction of phylogenetic tree. The sponge isolate MSBN04 waslustered between Bacillus sp. KA1 and B. megaterium ZmR-4 (Fig. 2).he phylogenetic analysis and RDPII search confirmed that the iso-ate as B. megaterium. 16S rRNA sequence of MSBN04 has beeneposited in the Gen-Bank database (GenBank ID: HQ874436). Inhis study, an effective PHB producing strain B. megaterium MSBN04as isolated from marine sponge S. officinalis.

.2. PHB production in SSC condition

Among the substrates screened, tapioca industry waste wasound to be most suitable substrate for the production of PHB by. megaterium MSBN04 (52% of PHB) followed by wheat bran, riceran and industrial wastes such as dairy industry waste, brewery

ndustry waste and mango pulp industry waste. This study aimedt developing efficient bioprocesses to transform these industrial

astes into value added product. The influence of carbon sources

uch as palm jaggery, wheat bran, rice bran and ground nut oil cakeere evaluated under SSC conditions to enhance the production of

HB by MSBN04. The palm jaggery invariably increased the PHB

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Fig. 2. NJ bootstrapping consensus phylogenetic tree of isolate MSBN04 and th

iological Macromolecules 60 (2013) 253– 261

production with various substrates such as tapioca industry waste(55%), starch industry waste (52%), sugar industry waste (pre-treated molasses) (50%), sugar industry waste (treated molasses)(47%) and pulp industry waste (pretreated sludge) (45%) (Fig. 3).Based on these findings, palm jaggery was found to be the bestcarbon source for the production of PHB when compared to othercarbon sources. Palm jaggery is quite popular in southern India,processed from the unfermented Palmyra tree sap [34] and con-tains various forms of sugars, calcium, iron and vitamins capableof enhancing the growth and PHB accumulation in B. megateriumMSBN04. Supplementation of nitrogen sources in the produc-tion media showed substantial increase in the PHB production byMSBN04. However the effect of nitrogen sources on the PHB pro-duction was greatly influenced by substrates under SSC conditions.The horse gram flour as nitrogen source and tapioca industry wasteas substrate showed significant increase in the production of PHB(55%) by MSBN04. Horse gram is a legume plant agro-product andeasily available resource in southern part of India, however, itsapplication as nitrogen source in SSC and/or bioprocess optimiza-tion has not been reported. The present report brings out a newprospect on the microbial production of PHB with legume basedagro-products as nitrogen source. The moisture content requiredfor the maximum production of PHB by MSBN04 under SSC wasdetermined to be >75%.

Production of PHB polymer at different incubation period wasdetermined using one-factor-at-a-time experiment and it wasobserved that the MSBN04 started to produce PHB from 12 h whichwas increased to 57% of the dry cell weight at 48 h and thendecreased 48% at 96 h of incubation (Fig. 4a). The present studyreports the efficacy of the strain B. megaterium MSBN04 whichshows maximum productivity within a short incubation period (i.e.,48 h) in solid state fermentation ultimately reduces production costof PHB polymer. It was found that the pH had a specific influence onthe production of PHB by strain B. megaterium MSBN04. The betterPHB production (55%) by MSBN04 was attained at pH 7.5 (Fig. 4b).

The production was consistent at pH 7.5 on all the substrates used.The production was drastically declined at low pH compared toalkaline pH, where the production was nearly stable. The produc-tion of PHB reached maximum (58%) at 30 ◦C with tapioca industry

Bacill us clausii Bacill us alcalophilus YB380 Paenibacill us chitinolyticus IFO 15660 Bacill us halodurans ATCC27557 Bacill us sp. Papandayan Vibrio halodenitrificans ATCC49067 Bacill us sporothermodurans M215 Bacill us sp. J2046 s Bacill us pumilus IARI- L-54 Bacill us licheniformis MSBN12 Bacill us subtilis MSBN17 Bacillus amyloliquefaciens PBT-3 Bacill us simplex IARI- L-13 Bacill us megaterium Jz11 Bacill us horikoshii RB10 Bacill us megaterium NM27 Bacill us megaterium ZmR-4

Bacill us megaterium MSBN04 Bacill us sp. KA1 Bacill us aryabhatt ai LS15 Bacill us cereus GM3 16 S Bacillus flexus AIMST Nae10 Bacill us thu ringiensis AIMST Shewanell a psychrophila 82346

eir closest NCBI (BLASTn) strains based on the 16S rRNA gene sequences.

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Fig. 3. Production of PHB using agro industrial residues and industrial wa

aste as substrate (Fig. 4c). The strain showed maximum PHBroduction with the supplementation of 2.5% NaCl. The PHB pro-uction was increased significantly with tapioca industry wasteollowed by sugar industry waste (pretreated molasses) as sub-trates supplemented with metal ions (trace element solution) forhe development of SSC. The peak production was attained at 4 daysf incubation under the optimized SSC conditions. In this study, theptimization process was completed with effective concentrationf chosen carbon and nitrogen sources to maximize the productionnder SSC conditions. The PHB production by MSBN04 was consis-ently increased with the substrates such as tapioca industry wastend pulp industry waste (pretreated sludge) with 2.5% palm jaggerys carbon source. The 1.5% of horse gram flour as nitrogen sourcehowed maximum production with tapioca industry waste as mainubstrate. Notably the production was consistent over the range ofubstrates such as sugar industry waste (treated molasses), starch

ndustry waste, mango pulp industry waste (pretreated sludge),

heat bran, rice bran and groundnut oil cake in slightly decreasingrder. The maximum production of PHB by MSBN04 occurred at a

able 1NOVA analysis of CCD based optimization of PHB production by B. megaterium MSBN04

Biomass

Factors and source P-value

Model <0.0001**

Tapioca industry waste (A) <0.0001**

Palm jaggery (B) 0.0004*

Horse gram flour (C) <0.0001**

Trace element solution (D) 0.0004*

AB 0.7196

AC 0.0377*

AD 0.1134

BC 0.0222*

BD 0.8908

CD 0.0121*

A2 <0.0001**

B2 0.0003*

C2 <0.0001**

D2 <0.0001**

* Significant.** Most Significant.

s substrates with palm jaggery as carbon source under solid state culture.

C/N ratio of 0.5 envisaging that a higher amount of carbon source isrequired by the organism compared to that of the nitrogen source.

3.3. Optimization of PHB production using RSM

The production was optimized by CCD with six central points,the responses such as biomass and PHB yield was studied and theoverall second-order polynomial equations for biomass and PHBproduction were given below:

Biomass(Y1) = +334.48 + 42.08 ∗ A + 8.63 ∗ B + 13.12 ∗ C

− 8.70 ∗ D − 0.85 ∗ A ∗ B + 5.30 ∗ A ∗ C

+ 3.91 ∗ A ∗ D − 5.93 ∗ B ∗ C − 0.32 ∗ B ∗ D

+ 6.63 ∗ C ∗ D24.92 ∗ A2 − 8.35 ∗ B2 − 12.06 ∗ C2

− 20.07 ∗ D2 (1)

.

PHB yield

Factors and source P-value

Model <0.0001**

Tapioca industry waste (A) <0.0001**

Palm jaggery (B) 0.0013*

Horse gram flour (C) <0.0001**

Trace element solution (D) 0.3810AB 0.0664AC 0.7376AD 0.0137*

BC 0.2020BD 0.2255CD 0.8175A2 <0.0001**

B2 <0.0001**

C2 <0.0001**

D2 <0.0001**

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Fig. 5. Three dimensional response surface curves showing the interactive effectsof different medium components on the biomass (a) and accumulation of PHB (b

ig. 4. Physical parameters influencing PHB production in MSBN04. a) Effect of incu-ation period on PHB production. b) Effect of pH on PHB production. c) Effect ofemperature on PHB production.

HBYield(Y2) = +190.03 + 18.40 ∗ A + 6.02 ∗ B − 10.57 ∗ C

− 1.38 ∗ D − 3.70 ∗ A ∗ B + 0.64 ∗ A ∗ C

− 5.22 ∗ A ∗ D + 2.49 ∗ B ∗ C − 2.36 ∗ B ∗ D

− 0.44 ∗ C ∗ D − 17.84 ∗ A2 − 8.68 ∗ B2

− 16.76 ∗ C2 − 15.49 ∗ D2 (2)

here Y1 and Y2 were the responses, i.e. biomass and PHB con-ent per total gram of substrate and A, B, C and D were the codederms for the four test variables, i.e. tapioca industry waste, palmaggery, horse gram flour and trace element solution respectively.he statistical significance of the model equation was calculated byhe F-test for analysis of variance (ANOVA), which indicates thathe regression is strongly significant at 99% (P < 0.05) confidenceevel. In the aspect of biomass (Y1) A, B, C, D, AC, BC, CD, A2, B2,2, and D2 were significant model terms. In PHB yield (Y2) A, B,

, AD, A2, B2, C2, and D2 were significant model terms (Table 1).-values indicate the significance of each of the coefficient andhich is important to understand the pattern of the mutual inter-

ction between the each variables. ANOVA for biomass and PHB

and c) by the sponge isolate MSBN04.

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ield exibited the model F-values of 64.48 and 39.40 respectivelymplies the models are significant at prob > F-value was <0.0001.Adequate precision’ measures the signal (responses) to noise (devi-tion) ratio. The obtained ratios of 27.938 and 20.478 indicates andequate singal in the case of optimization (media) for biomassnd PHB production respectively. The R2 values of 0.9837 and.9735 which are closer to 1 shows the models to be strongerhich can better predict the responses and model could explain

8% and 97% of the variability in the biomass and PHB yield respec-ively. The high values of adjusted R2 (0.9684 and 0.9488) furtherupported the accuracy of the model. Three dimentional responseurves were plotted to the interaction of substrates on the biomassnd PHB production. For biomass interaction of AC, BC, CD wouldontribute positively for the maximum biomass production. Onther hand the interactive model terms AB, AD, BD did not depictignificant impacts on the biomass production. As such interac-ion of AB, AD, BD showed positive effects than AC, BC, CD forHB production (Fig. 5). In RSM studies the nitrogen source horseram flour and trace element solution were found to be the limit-ng factors for the production of PHA. From the response study its obvious that all substrates have significant impact on biomassnd PHB yield. Based on the SSC results the maximum biomass34.48 mg/total gram of substrate (15.203 mg g−1 of substrate) andaximum PHB 190 .03 mg/total gram of substrate (8.637 mg g−1 of

ubstrate) were obtained. The PHB production was achived throughSC from B. megaterium MSBN04 is 56.81%. The predicted andhe actual (experimental) responses of PHB production was highlyomparable (Fig. 6). The yield of PHB obtained from MSBN04 uti-

izing tapioca industry waste is highly considerable than previouseports [11] and B. megaterium MSBN04 can be used as poten-ial strain for the commercial production of PHB under solid stateulture.

Fig. 7. a. GC-Mass spectrum of purified PHB polymer from MSBN04; b. 1H

Fig. 6. Actual vs. predicted amount of PHB obtained from the CCD optimization.

3.4. Characterization of PHB

The chemical composition of PHB purified from MSBN04 wascompletely studied by various characterization methods. FTIR

spectroscopy gives peaks at 1720 cm−1 and 1287 cm−1 correspondto the C O and C O stretching group, respectively. The bands at1232 cm−1, 1384 cm−1 and 1187 cm−1 are CH2, CH3 and C O Crespectively. The absorption band at and around 3670 cm−1

NMR spectra of Poly (3-hydroxybutyrate) purified form MSBN04.

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260 G. Sathiyanarayanan et al. / International Journal of B

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[31] G. Wang, J. Ind. Microbio. Biotechnol. 33 (2006) 545–551.[32] J. Selvin, Soniya Joseph, K.R.T. Asha, W.A. Manjusha, V.S. Sangeetha, D.M.

Jayaseema, M.C. Antony, A.J. Denslin Vinitha, FEMS. Microbiol. Ecol. 50 (2004)

Fig. 8. Bright-field TEM micrograph of synthesized PHB nanoparticles.

orresponds to the terminal OH group. The peaks from the FTIRpectrum corroborates with peaks reported by Arun et al. andandian et al. [13,31]. The spectra confirm that the strain wasn active biopolymer producer. GC-MS analysis carried out toetermine the constituents present in the PHB revealed the majoreak, resembling to methyl 3-hydroxybutyrate with retentionime of 2.6 min (Fig. 7a) and thus our finding agrees with result ofeddy et al. [41]. Molecular mass of the polymer was detected byPC analysis, showed that the weight average molecular weight

Mw) is 6.7 × 105 Da; number average molecular weight (Mn) is.9 × 105 Da and low polydispersity index (Mw/Mn) (PDI) is 1.71hich is similar to earlier report [42] and the obtained polymerould be applicable in various medical fields. 1H NMR spectraas extrapolated with peaks at 1.2 ppm, 2.5 ppm and 5.2 ppmere due to the resonance absorption of methyl (CH3), methylene

CH2) and methane (CH) groups, respectively, it confirms theroduced polymer was PHB monomer, and this result correlatesith the results of Khardenavis et al. [19] (Fig. 7b). The overall

esults confirmed the production of PHB in marine sponge isolateSBN04.

.5. PHB nanoparticles synthesis and characterization

The PHB produced from SSC having high molecular weight andhus, it was used to synthesize PHB nanoparticles for biomed-cal applications. The produced PHB was dissolved in acetone

hich results the synthesis of PHB nanoparticles when it wasnjected into an aqueous solution. HR-TEM analysis was per-ormed to determine the size and morphology of negatively stainedHB nanoparticles. The bright field HR-TEM images revealedhe average size of particles as 90–120 nm and they were rel-tively uniform in diameter with polydispersed spherical shapeFig. 8). The obtained result was corroborates with result of pre-ious study [39] and the nanoparticles were significantly smallerhan previous reports and it can be used as a valid biomateri-ls for tissue engineering as well as in targeted drug delivery.gglomerated particles were not observed in TEM analysis. In

his study we adopted solvent displacement method and it isn economical and greener approach to synthesis polymericanoparticles.

. Conclusion

To the best our knowledge, there are no reports of opti-

ization of PHB production by B. megaterium under solid state

ulture. The statistical approach showed significant results forptimizing the process parameters for maximal biomass andHB production under SSC. The present study also highlights the

[

[

iological Macromolecules 60 (2013) 253– 261

utilization of industrial wastes for the production of PHB under SSCcondition and also serve as an efficient end-of-pipe technology fordisposing tapioca industry waste. In this study, it is evident thatvarious process parameters like substrate concentration, nitrogensource and trace element solution were significantly influencedthe PHB production. The biopolymer produced by MSBN04 wascharacterized as high molecular weight PHB with low PDI value.The PHB nanoparticles were synthesized from high molecularweight PHB and it can be used for preparing biodegradabledrug carriers for biomedical applications. Considering the resultsobtained in the current study, we can conclude that the strain usedin this study offers great potential for further investigation on PHBproduction under solid state culture.

Acknowledgement

This paper is a part of GS Ph.D research. JS is thankful to Depart-ment of Biotechnology (DBT), New Delhi, India for research grant.

References

[1] Y.B. Kim, R.W. Lenz, Adv. Biochem. Eng. Biotechnol. 71 (2001) 51–79.[2] S. Khanna, A.K. Srivastava, Process Biochem. 40 (2005) 2173–2182.[3] M.B.T. Joa∼o, M. Cavalheiro, C.M.D.D. Almeida, G. Christian, M.M.R. Fonseca,

Process Biochem. 44 (2009) 509–515.[4] S. Cheema, M. Bassas-Galia, P.M. Sarma, B. Lal, S. Arias, Bioresour. Technol. 103

(2012) 322–328.[5] J. Choi, Y.L. Sang, Bioprocess. Eng. 17 (1997) 335–342.[6] A. Nath, M. Dixit, A. Bandiya, S. Chavda, A.J. Desai, Bioresour. Technol. 99 (2008)

5749–5755.[7] A.J. Anderson, E.A. Dawes, Microbiol. Rev. 54 (1990) 450–472.[8] M. Zinn, B. Witholt, T. Egli, Adv. Drug. Deliv. Rev. 53 (2001) 5–21.[9] T.G. Volova, E.I. Shishatskaya, V.I. Sevastianov, S. Efremov, O. Mogilnaya,

Biochem. Eng. 16 (2003) 125–133.10] M.L. Hans, A.M. Lowman, Curr. Opin. Solid. State. Mater. Sci. 6 (2002)

319–327.11] R. Li, H. Zhang, Q. Qi, Bioresour. Technol. 98 (2007) 2313–2320.12] B.S. Kim, Enzyme Microb. Technol. 27 (2000) 774–777.13] S.R. Pandian, V. Deepak, K. Kalishwaralal, N. Rameshkumar, M. Jayaraj, S.

Gurunathan, Bioresour. Technol. 101 (2010) 705–711.14] L.R. Castillo, D.A. Mitchell, D.M.G. Freire, Bioresour. Technol 100 (2009)

5996–6009.15] D.V. Thuoc, J. Quillaguaman, G. Mamo, B. Mattiasson, J. App. Microbiol. 104

(2008) 420–428.16] N.V. Ramadas, S.K. Singh, C.R. Soccol, A. Pandey, Braz. Arch. Biol. Technol. 52

(2009) 17–23.17] T.D. Full, D.O. Jung, M.T. Madigan, Lett. App. Microbiol. 43 (2006) 377–384.18] M.K. Gouda, A.E. Swellam, S.H. Omar, Microbiol. Res. 156 (2001) 201–207.19] A. Khardenavis, M.S. Kumar, S.N. Mudliar, T. Chakrabarti, Bioresour. Technol.

98 (2007) 3579–3584.20] K. Sangkharak, P. Prasertsan, J. Biotechnol. 13 (2007) 2331–2340.21] J. Zhang, C. Marcin, M.A. Shifflet, P. Salmon, T. Brix, R. Greasham, et al., App.

Microbiol. Biotechnol. 44 (1996) 568–575.22] P.I. Nikel, M.J. Pettinari, B.S. Mendez, M.A. Galvagno, Int. Microbiol. 8 (2005)

243–250.23] D.C. Montgomery, Design and Analysis of Experiments, Wiley, New York, 2001,

pp. 455–492.24] K. Shilpi, A.K. Srivastava, Process. Biochem. 40 (2005) 2173–2182.25] S.V.N. Vijayendra, N.K. Rastogi, T.R. Shamala, P.K. Anil Kumar, L. Kshama, G.J.

Joshi, Indian J. Microbiol. 47 (2007) 170–175.26] M. Purushothaman, R.K.I. Anderson, S. Narayana, V.K. Jayaraman, Bioprocess.

Biosyst. Eng. 24 (2001) 131–136.27] S.P. Velappil, A.R. Boccaccini, C. Bucke, I. Roy, Antonie von Leeuwenhoek 91

(2007) 1–17.28] R.M. Weiner, Trends. Biotechnol. 15 (1997) 390–394.29] C.C. Chien, C.C. Chen, M.H. Choi, S.S. Kung, Y.H. Wei, J. Biotechnol. 132 (2007)

259–263.30] A. Arun, R. Arthi, V. Shanmugabalaji, M. Eyini, Bioresour. Technol. 100 (2009)

2320–2323.

117–122.33] G. Sathiyanarayanan, G.S. Kiran, J. Selvin, Colloids Surf. B: Biointerfaces 102

(2013) 13–20.34] G. Sathiyanarayanan, G. Saibaba, G.S. Kiran, J. Selvin, Int. J. Biol. Macromol. 59

(2013) 170–177.

Page 9

al of B

[

[

[

[

[

G. Sathiyanarayanan et al. / International Journ

35] J.G. Holt, N.R. Krieg, P.H.A. Sneath, J.T. Staley, S.T. Williams, Bergey’s Manual ofDeterminative Bacteriology, 9th ed., Williamsons and Wilkins, Baltimore, 1994.

36] J.J. Enkicknap, M. Kelly, O. Peraud, R.T. Hill, Appl. Environ. Microbiol. 72 (2006)

3724–3732.

37] B. Ryu, K.H. Kang, D.H. Ngo, Z.J. Qian, S.K. Kim, Bioresour. Technol. 107 (2012)307–313.

38] S.P. Valappil, S.K. Misra, A.R. Boccaccini, T. Keshavarz, C. Bucke, I. Roya, J.Biotechnol. 132 (2007) 251–258.

[

[

[

iological Macromolecules 60 (2013) 253– 261 261

39] S.R.K. Pandian, V. Deepak, K. Kalishwaralal, J. Muniyandi, N. Rameshku-mar, S. Gurunathan, Colloids Surf. B: Biointerfaces. 74 (2009)266–273.

40] B. Panda, P. Jain, L. Sharma, N. Mallick, Bioresour. Technol. 99 (2006)1296–1301.

41] V.S. Reddy, M. Thirumala, S.K. Mahmood, W. J. Microbiol. Biotechnol. 25 (2009)391–397.

42] S. Chaijamrus, N. Udpuay, Agric. Eng. Int.: the CICR E journal X (2008) 1–12.