Poly (γ-glutamic acid) Production Enhancement in Submerged Fermentation of Bacillus Licheniformis ATCC 9945a Using Optimization of Operating Variables and Glutamate Feeding

Document Type : Research Article

Authors

Faculty of Chemistry and Chemical Engineering, Malek Ashtar University of Technology, Tehran, I.R. IRAN

Abstract

Poly (γ-glutamic acid) is a versatile biopolymer that can be used on an industrial scale if efficient methods are developed to increase production. In this study, first, based on the central composite design method of the response surface module, the effect of operational variables including temperature in the range of 30-44 °C, pH 4.5-8.5, and stirring in the range of 600-1000 rpm on poly (γ-glutamic acid) production was investigated in the batch fermentation of Bacillus licheniformis ATCC 9945a for the first time. Under optimal conditions viz. T of 37.4 °C, pH of 6.6, and agitation rate of 784.2 rpm, 15.5 g/L γ-PGA was obtained. According to the statistical analyses, adjusted R2 was 0.9572, and analysis of variance explicated that T-T, pH-pH, and agitation-agitation effects indicated the lowest p-values and had the most significant influence on biopolymer synthesis. Under the optimal conditions, glutamate (a novel feed) pulse feeding (as poly (γ-glutamic acid)-based monomer) was optimized, for the first time, using the one-factorial method to achieve a maximum of 42.13 g/L of biopolymer production (highest in comparison with others’ studies of this strain) by the two-pulsed feeding method. The chemical confirmation and novel physical characterization of the powdered product indicated a pure poly (γ-glutamic acid) sample suitable for biological, biomedical, and biopharmaceutical applications.

Keywords

Main Subjects


[1] Luo Z., Guo Y., Liu J., Qiu H., Zhao M., Zou W., Li S., Microbial Synthesis of Poly-γ-Glutamic Acid: Current Progress, Challenges, and Future Perspectives,  Biotechnol. Biofuels, 9(1): 1-12 (2016).
[2] Bajaj I., Singhal R., Poly (Glutamic Acid)– An Emerging Biopolymer of Commercial Interest, Bioresour. Technol., 102(10): 5551-5561 (2011).
[3] Ogunleye A., Bhat A., Irorere V.U., Hill D., Williams C., Radecka I., Poly-γ-Glutamic Acid: Production, Properties and Applications, Microbiology, 161(1): 1-17 (2015).
[4] Shih L., Van Y.T., The Production of Poly-(γ-Glutamic Acid) from Microorganisms and its Various Applications, Bioresour. Technol., 79(3): 207-225 (2001).
[5] Ebrahimzadeh Kouchesfahani M., Bahrami A., Babaeipour V., Enhanced Production of Poly-γ-Glutamic Acid by Bacillus Licheniformis ATCC 9945a Using Simultaneous Pulse-Feedings of Citrate and Glutamate, Prep. Biochem. Biotechnol., (2022).
[7] Birrer G.A., Cromwick A.M., Gross R.A., γ-Poly (Glutamic Acid) Formation by Bacillus Licheniformis 9945a: Physiological and Biochemical Studies, Int. J. Biol. Macromol., 16(5): 265-275 (1994).
[8] Cromwick A.M., Gross R.A., Effects of Manganese (II) on Bacillus Licheniformis ATCC 9945A Physiology and γ-Poly (Glutamic Acid) Formation, Int. J. Biol. Macromol., 17(5): 259-267 (1995).
[9] Cromwick A.M., Birrer G.A., Gross R.A., Effects of pH and Aeration on γ‐Poly (Glutamic Acid) Formation by Bacillus Licheniformis in Controlled Batch Fermentor Cultures, Biotechnol. Bioeng., 50(2): 222-227 (1996).
[10] Feng J., Shi Q., Zhou G., Wang L., Chen A., Xie X., Huang X., Hu W., Improved Production of Poly-γ-Glutamic Acid with Low Molecular Weight under High Ferric Ion Concentration Stress in Bacillus Licheniformis ATCC 9945a, Process Biochem., 56: 30-36 (2017).
[13] Ko Y.H., Gross R.A., Effects of Glucose and Glycerol on γ‐poly (glutamic acid) Formation by Bacillus Licheniformis ATCC 9945a, Biotechnol. Bioeng., 57(4): 430-437 (1998).
[14] Mitsunaga H., Meissner L., Büchs J., Fukusaki E., Branched Chain Amino Acids Maintain the Molecular Weight of Poly (γ-glutamic acid) of Bacillus Licheniformis ATCC 9945 During the Fermentation, J. Biosci. Bioeng., 122(4): 400-405 (2016).
[15] Mitsunaga H., Meissner L., Palmen T., Bamba T., Büchs J., Fukusaki E., Metabolome Analysis Reveals the Effect of Carbon Catabolite Control on the Poly (γ-glutamic acid) Biosynthesis of Bacillus Licheniformis ATCC 9945, J. Biosci. Bioeng., 121(4): 413-419 (2016).
[16] Giannos S.A., Shah D., Gross R.A., Kaplan D.L., Mayer J.M., “Poly (glutamic acid) Produced by Bacterial Fermentation”, In: “Novel Biodegradable Microbial Polymers”, 457-460, Springer, Dordrecht (1990).
[17] Yoon S.H., Do J.H., Lee S.Y., Chang H.N., Production of Poly-γ-Glutamic Acid by Fed-Batch Culture of Bacillus Licheniformis, Biotechnol. Lett., 22(7): 585-588 (2000).
[18] Zhang C., Wu D., Ren H., Economical Production of Agricultural γ-Polyglutamic Acid Using Industrial Wastes by Bacillus Subtilis, Biochem. Eng. J., 146: 117-123 (2019).
[19] Wang D., Hwang J. S., Kim D.H., Lee S., Kim D.H., Joe M.H., A Newly Isolated Bacillus Siamensis SB1001 for Mass Production of Poly-γ-glutamic acid, Process Biochem, 92: 164-173 (2020).
[20] Zhiyi Y., Ran Q., Chang Z., Gao H., Jia C., Recovery of Low-Molecular-Weight γ-PGA by Metal Cation from the Fermentation Broth, Process Biochem, 82: 215-221 (2019).
[21] Li M., He Y., Ma X., Separation and Quantitative Detection of Fermentation γ-polyglutamic Acid,
J. Future Foods, 2(1): 42-48 (2022).
[22] Morowvat M. H., Babaeipour V., Rajabi Memari H., Vahidi H., Optimization of Fermentation Conditions for Recombinant Human Interferon Beta Production by Escherichia coli Using the Response Surface Methodology, Jundishapur J. Microbiol., 8(4): e16236 (2015).
[23] Rao R.S., Kumar C.G., Prakasham R.S., Hobbs P.J., The Taguchi Methodology as a Statistical Tool for Biotechnological Applications: A Critical Appraisal, Biotechnol. J., 3(4): 510-523 (2008).
[24] Khuri A.I., Mukhopadhyay S., Response Surface Methodology, Wiley Interdiscip. Rev. Comput. Stat., 2(2): 128-149 (2010).
[25] Bagherinia M., Babaeipour V., Soleimani A., Optimization of Bacterial Nano-Cellulose Production in Bench-Scale Rotating Biological Contact Bioreactor by Response Surface Methodology, Iran. J. Chem. Chem. Eng. (IJCCE), 40 (2): 407-416, (2021).
[26] Kasemiire A., Avohou H.T., Bleye C.D., Sacre P.Y., Dumont E., Hubert P., Ziemons E., Design of Experiments and Design Space Approaches in the Pharmaceutical Bioprocess Optimization, Eur. J. Pharm. Biopharm., 166: 144-154 (2021).
[27] Narenderan S.T., Meyyanathan S.N., Karri V.V.S.R., Experimental Design in Pesticide Extraction Methods: A Review, Food Chem., 289: 384-395 (2019).
[28] Asghar A., Raman A.A.A., Daud W.M.A.W., A Comparison of Central Composite Design and Taguchi Method for Optimizing Fenton Process, Sci. World J., (2014).
[29] Candela T., Fouet A., poly‐Gamma‐Glutamate in Bacteria, Mol. Microbiol., 60(5): 1091-1098 (2006).
[30] Zakaria A., Haouti R.E., Lhanafi S., Benafqir M., Azougarh Y., Alem N.E., Treated Digested Residue During Anaerobic Co-Digestion of Agri-Food Organic Waste: Methylene Blue Adsorption, Mechanism and CCD-RSM Design, J. Environ. Chem. Eng., 5(6): 5857-5867 (2017).
[31] Bhattacharya S., “Central Composite Design for Response Surface Methodology and its Application in Pharmacy”, In: “Response Surface Methodology in Engineering Science”, IntechOpen (2021).
[32] Zhang Z., Xiaofeng B., Comparison about the Three Central Composite Designs with Simulation, 2009 Int. Conf. Adv. Comput. Control. (ICACC), IEEE 2009: 163-167 (2009).
[33] Diaconu M., Pavel L.V., Hlihor R.M., Rosca M., Fertu D.I., Lenz M., Corvini P.X., Gavrilescu M., Characterization of Heavy Metal Toxicity in Some Plants and Microorganisms—A Preliminary Approach for Environmental Bioremediation, N. Biotechnol, 56: 130-139 (2020).
[34] Krishnan S., Suzana B.N., Wahid Z.A., Nasrullah M., Munaim M.S.A., Din M.F.B.M., Taib S.M., Li. Y.Y., Optimization of Operating Parameters for Xylose Reductase Separation through Ultrafiltration Membrane Using Response Surface Methodology, Biotechnol. Rep., 27: e00498 (2020).
[35] Kiruthika J., Murugesan S., Studies on optimization of L-glutaminase Production under Submerged Fermentation from Marine Bacillus Subtilis JK-79, Afr. J. Microbiol. Res., 14(1): 16-24 (2020).
[37] Haaland P.D., “Experimental Design in Biotechnology”, CRC press (2020).
[38] Ranganadh R.A., Vidya P.K., Venkateswarulu T.C., Krupanidh S., Bobby M.N., Abraham P.K., Sudhakar P., Vijetha P., Statistical Optimization of PolyHydroxy Butyrate (PHB) Production by Novel Acinetobacter Nosocomialis RR20 Strain Using Response Surface MethodologyCurr. Trends Biotechnol. Pharm., 14(1): 62-69 (2020).
[39] Goukanapalle P.K.R., Kanderi D.K., Rajoji G., Kumari B.S.S., Bontha R.R., Optimization of Cellulase Production by a Novel Endophytic Fungus Pestalotiopsis Microspora TKBRR Isolated from Thalakona Forest, Cellulose, 27: 6299-6316 (2020).
[40] Du G., Yang G., Qu Y., Chen J., Lun S., Effects of Glycerol on the Production of Poly (γ-glutamic acid) by Bacillus Licheniformis, Process Biochem., 40(6): 2143-2147 (2005).
[42] Rahimi T., Kahrizi D., Feyzi M., Ahmadvandi H.R., Mostafaei M., Catalytic Performance of MgO/Fe2O3-SiO2 Core-Shell Magnetic Nanocatalyst for Biodiesel Production of Camelina Sativa Seed Oil: Optimization by RSM-CCD Method, Ind. Crops Prod., 159: 113065 (2021).
[43] Yahya H.S.M., Abbas T., Amin N.A.S., Optimization of Hydrogen Production via Toluene Steam Reforming over Ni–Co Supported Modified-Activated Carbon Using ANN Coupled GA and RSM, Int. J. Hydrog. Energy, 46(48): 24632-24651 (2021).
[44] Lazzari E., dos Santos Polidoro A., Onorevoli B., Schena T., Silva A.N., Scapin E., Jacques R.A., Caramão E.B., Production of Rice Husk Bio-Oil and Comprehensive Characterization (Qualitative and Quantitative) by HPLC/PDA and GC × GC/qMS, Renew. Energy, 135: 554-565 (2019).
[45] Santhosh A.J., Tura A.D., Jiregna I.T., Gemechu W.F., Ashok N., Ponnusamy M., Optimization of CNC Turning Parameters Using Face Centred CCD Approach in RSM and ANN-Genetic Algorithm for AISI 4340 Alloy Steel, Results Eng., 11: 100251 (2021).
[46] Sharma J., A.S. Chadha, V. Pruthi, P. Anand, J. Bhatia, B.S. Kaith., Sequestration of Dyes from Artificially Prepared Textile Effluent Using RSM-CCD Optimized Hybrid Backbone Based Adsorbent-Kinetic and Equilibrium Studies, J. Environ. Manage., 190: 176-187 (2017).
[47] Foroutan R., Mohammadi R., Razeghi J., Ramavandi B., Biodiesel Production from Edible Oils Using Algal Biochar/CaO/K2CO3 as a Heterogeneous and Recyclable Catalyst, Renew. Energy, 168: 1207-1216 (2021).
[48] Ince O.K., Aydogdu B., Alp H., Ince M., Experimental Design Approach for Ultra-Fast Nickel Removal by Novel Bio-Nanocomposite Material, Adv. Nano Res., 10(1): 77-90 (2021).
[49] Igwegbe C.A., Onukwuli O.D., Ighalo J.O., Menkiti M.C., Bio-coagulation-flocculation (BCF) of Municipal Solid Waste Leachate Using Picralima Nitida Extract: RSM and ANN Modeling, Curr. Res. Green Sustain. Chem., (CRGSC), 4: 100078 (2021).
[50] Muniyasamy A., Sivaporul G., Gopinath A., Lakshmanan R., Altaee A., Achary A., Chellam P.V., Process development for the Degradation of Textile Azo Dyes (mono-, di-, poly-) by Advanced Oxidation Process-Ozonation: Experimental & Partial Derivative Modelling Approach, J. Environ. Manage., 265: 110397 (2020).
[51] Amin M., Chetpattananondh P., Ratanawilai S., Application of Extracted Marine Chlorella Sp. Residue for Bio-Oil Production as the Biomass Feedstock and Microwave Absorber, Energy Convers. Manag., 195: 819-829 (2019).
[52] Raheem A., Zhao M., Dastyar W., Channa A.Q., Ji G., Zhang Y., Parametric Gasification Process of Sugarcane Bagasse for Syngas Production, Int. J. Hydrog. Energy, 44(31): 16234-16247 (2019).
[53] Anfar Z., Amedlous A., Ait El Fakir A., Ahsaine H.A., Zbair M., Lhanafi S., El Haouti R., Jada A., El Alem N., Combined Methane Energy Recovery and Toxic Dye Removal by Porous Carbon Derived from Anaerobically Modified Digestate, ACS Omega, 4(5): 9434-9445 (2019).
[54] Ndikubwimana T., Zeng X., Liu Y., Chang J.S., Lu Y., Harvesting of Microalgae Desmodesmus sp. F51 by Bioflocculation with Bacterial Bioflocculant, Algal Res., 6: 186-193 (2014).
[56] Sirisansaneeyakul S., Cao M., Kongklom N., Chuensangjun C., Shi Z., Chisti Y., Microbial Production of poly-γ-glutamic acid, World J. Microbiol. Biotechnol., 33(9): 1-8 (2017).
[58] Park J.P., Kim S.W., Hwang H.J., Yun J.W., Optimization of Submerged Culture Conditions for the Mycelial Growth and Exo‐Biopolymer Production by Cordyceps Militaris, Lett. Appl. Microbiol., 33(1): 76-81 (2001).
[62] Zhang C., Wu D., Qiu X., Stimulatory Effects of Amino Acids on γ-polyglutamic acid Production by Bacillus Subtilis, Sci. Rep., 8(1): 1-9 (2018).
[63] Abdel-Fattah Y., Soliman N., Berekaa M., Application of Box-Behnken Design for Optimization of Poly-γ-glutamic Acid Production by Bacillus Licheniformis SAB-26, Res. J. Microbiol., 2(9): 664-670 (2007).
[64] Pereira C.L., Antunes J.C., Gonçalves R.M., Ferreira-da-Silva F., Barbosa M.A., Biosynthesis of Highly Pure Poly-γ-Glutamic Acid for Biomedical Applications, J Mater Sci Mater Med, 23(7): 1583-1591 (2012).
[65] Lin B., Li Z., Zhang H., Wu J., Luo M., Cloning and Expression of the γ-Polyglutamic Acid Synthetase Gene pgsBCA in Bacillus subtilis WB600, Biomed Res. Int., 2016: 3073949 (2016).
[66] Wang F., Liang J., Wang W., Fu D., Xiao W., A New and Efficient Method for Purification of Poly-γ-Glutamic Acid from High-Viscosity Fermentation Broth, Trop. J. Pharm. Res., 16(6): 1267-1275 (2017).
[67] Xavier J.R., Kumarr M.M.M., Natarajan G., Ramana K.V., Semwal A.D., Optimized Production of Poly (γ‐Glutamic Acid)(γ‐PGA) Using Bacillus Licheniformis and its Application as Cryoprotectant for Probiotics, Biotechnol. Appl. Biochem., 67(6): 892-902 (2020).
[68] Cao M., Geng W., Zhang W., Sun J., Wang S., Feng J., Zheng P., Jiang A., Song C., Engineering of Recombinant E Scherichia Coli Cells Co‐Expressing Poly‐γ‐Glutamic Acid (γ‐PGA) Synthetase and Glutamate Racemase for Differential Yielding of γ‐PGA, Microb. Biotechnol., 6(6): 675-684 (2013).
[69] Patra J.K., Das G., Fraceto L.F., Campos E.V.R., Rodriguez-Torres M.D.P., Acosta-Torres L.S., Diaz-Torres L.A., Grillo R., Swamy M.K., Sharma S., Habtemariam S., Shin H.S., Nano Based Drug Delivery Systems: Recent Developments and Future Prospects, J. Nanobiotechnology, 16(1): 1-33 (2018).