American Journal of Food Science and Technology
ISSN (Print): 2333-4827 ISSN (Online): 2333-4835 Website: http://www.sciepub.com/journal/ajfst Editor-in-chief: Hyo Choi
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American Journal of Food Science and Technology. 2021, 9(2), 30-37
DOI: 10.12691/ajfst-9-2-1
Open AccessArticle

Optimization of Bacteriocin Production by Lactobacillus fermentum Strain COE20 from Fermenting Pentaclethra macrophylla Benth Using Response Surface Methodology

Onwuakor Chijioke E.1, , Ogbulie Jude N.2, Braide Wesley2, Ogbulie Tochukwu E.3, Nwokafor Chibuzo V.1 and Uchendu C.E.4

1Department of Microbiology, College of Natural Sciences, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria

2Department of Microbiology, School of Biological Sciences, Federal University of Technology, Owerri, Imo State, Nigeria

3Department of Biotechnology, School of Biological Sciences, Federal University of Technology, Owerri, Imo State, Nigeria

4Department of Statistics, College of Physical Sciences, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria

Pub. Date: May 07, 2021

Cite this paper:
Onwuakor Chijioke E., Ogbulie Jude N., Braide Wesley, Ogbulie Tochukwu E., Nwokafor Chibuzo V. and Uchendu C.E.. Optimization of Bacteriocin Production by Lactobacillus fermentum Strain COE20 from Fermenting Pentaclethra macrophylla Benth Using Response Surface Methodology. American Journal of Food Science and Technology. 2021; 9(2):30-37. doi: 10.12691/ajfst-9-2-1

Abstract

This study evaluated the effect of varied culture conditions (Temperature, pH, and Sodium Chloride concentration) on bacteriocin production by Lactobacillus fermentum strain COE20 isolated from fermenting African oil bean seeds (Pentaclethra macrophylla Benth) using Response Surface Methodology (RSM). A Central Composite Design (CCD) was adopted with the interest of estimating the optimal conditions for its production using the response surface regression model, which estimated the linear, squared, and interactive relationship between the response variables. The Analysis of Variance (ANOVA) showed that the coefficient of determination in terms of predicted R2 was 0.8697 which was in close agreement with an adjusted R2 of 0.7393 and was accounted for by the predictors suggesting that the model was adequate. Optimal culture condition for bacteriocin production by L. fermentum strain COE20 was found at approximately 31°C, pH 5.9, 1.9% NaCl concentration at Y = 11.75mm. Y represents the response (zone of inhibition) against Staphylococcus aureus ATCC 19095 using the agar well diffusion assay method.

Keywords:
optimization bacteriocin Pentaclethra macrophylla response surface methodology Lactobacillus fermentum

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References:

[1]  Dwivedi, S., Prajapati, P., Vyas, N., Malviya, S., and Kharia, A. A Review on Food Preservation : Methods , harmful effects and better alternatives. Asian Journal of Pharmacy and Pharmacology, 3(6), 193-199, 2017.
 
[2]  Sharif, Z., Mustapha, F., Jai, J., Mohd Yusof, N., and Zaki, N. Review on methods for preservation and natural preservatives for extending the food longevity. Chemical Engineering Research Bulletin, 19, 145, 2017.
 
[3]  Capozzi, V., Fragasso, M., Romaniello, R., Berbegal, C., Russo, P., and Spano, G. (2017). Spontaneous food fermentations and potential risks for human health. Fermentation, 3(4), 1-19.
 
[4]  Rawat, S. Food Spoilage: Microorganisms and their prevention. Asian Journal of Plant Science and Research, 5(4), 47-56, 2015.
 
[5]  Singh, V. P. Recent approaches in food bio-preservation-A review. Open Veterinary Journal, 8(1), 104-111. 2018.
 
[6]  Ganguly S. Basic Principles for Effective Food Preservation: A Review. Int. J. Pure App. Biosci, 1(6), 84-85, 2013.
 
[7]  Vaishali, J. ., Jhandai, P., Jadhav, V. J., and Gupta, R. Bio-preservation of Foods: A Review. European Journal of Nutrition and Food Safety, 11(4), 164-174, 2019.
 
[8]  Padmavathi, T., Bhargavi, R., Priyanka, P. R., Niranjan, N. R., and Pavitra, P. V. Screening of potential probiotic lactic acid bacteria and production of amylase and its partial purification. Journal of Genetic Engineering and Biotechnology, 16(2), 357-362, 2018.
 
[9]  Queipo-Ortuño, M. I., De Dios Colmenero, J., Macias, M., Bravo, M. J., and Morata, P. Preparation of bacterial DNA template by boiling and effect of immunoglobulin g as an inhibitor in real-time PCR for serum samples from patients with brucellosis. Clinical and Vaccine Immunology, 15(2), 293-296, 2008.
 
[10]  Bassey, A., Ngwai, Y. B., Bassey, B. E., Nkene, I. H., Abimiku, R. H., and Parom, S. K. Phenotypic and Molecular Detection of Extended Spectrum β-Lactamase in Escherichia coli from Patients in Nigerian National Petroleum Corporation Medical Services, Abuja, Nigeria. Annual Research and Review in Biology, 28(4), 1-7, 2018.
 
[11]  Vickery, T. W., Kofonow, J. M., and Ramakrishnan, V. R. Characterization of sinus microbiota by 16S sequencing from swabs. In Methods in Molecular Biology 1616, 23-38, 2017.
 
[12]  Ariole, C. N., Onuorah, A. A., and Stanley, H. O. Diversity and Antibacterial Potential of Siderophore Producing Bacteria Isolated from Marine Fish Species. Journal of Applied Sciences, 19(4), 343-348, 2019.
 
[13]  Zhai, Q., Yin, R., Yu, L., Wang, G., Tian, F., Yu, R., Zhao, J., Liu, X., Chen, Y. Q., Zhang, H., and Chen, W. Screening of lactic acid bacteria with potential protective effects against cadmium toxicity. Food Control, 54, 23-30, 2015.
 
[14]  Suganthi, V., and Mohanasrinivasan, V. Optimization studies for enhanced bacteriocin production by Pediococcus pentosaceus KC692718 using response surface methodology. Journal of Food Science and Technology, 52(6), 3773-3783, 2015.
 
[15]  Cladera-Olivera, F., Caron, G. R., and Brandelli, A. Bacteriocin production by Bacillus licheniformis strain P40 in cheese whey using response surface methodology. Biochemical Engineering Journal, 21(1), 53-58, 2004.
 
[16]  Leães, F. L., Vanin, N. G., Sant’Anna, V., and Brandelli, A. Use of Byproducts of Food Industry for Production of Antimicrobial Activity by Bacillus sp. P11. Food and Bioprocess Technology, 4(5), 822-828, 2011.
 
[17]  Usmiati, S., and Marwati, T. Selection and Optimization Process of Bacteriocin Production from Lactobacillus sp. Indonesian Journal of Agriculture, 2(2), 82-92, 2009.
 
[18]  Vermeulen, A., Devlieghere, F., Bernaerts, K., Van Impe, J., and Debevere, J. Growth/no growth models describing the influence of pH, lactic and acetic acid on lactic acid bacteria developed to determine the stability of acidified sauces. International Journal of Food Microbiology, 119(3), 258-269, 2007.
 
[19]  Carr, F. J., Chill, D., and Maida, N. The lactic acid bacteria: A literature survey. In Critical Reviews in Microbiology 28(4), 281-37, 2002.
 
[20]  Aswathy, R. G., Ismail, B., John, R. P., and Nampoothiri, K. M. Evaluation of the probiotic characteristics of newly isolated lactic acid bacteria. Applied Biochemistry and Biotechnology, 151(2-3), 244-255, 2008.
 
[21]  Riaz Rajoka, M. S., Mehwish, H. M., Siddiq, M., Haobin, Z., Zhu, J., Yan, L., Shao, D., Xu, X., and Shi, J. Identification, characterization, and probiotic potential of Lactobacillus rhamnosus isolated from human milk. LWT - Food Science and Technology, 84, 271-280, 2017.
 
[22]  Guo, C. F., Zhang, L. W., Han, X., Li, J. Y., Du, M., Yi, H. X., Feng, Z., Zhang, Y. C., and Xu, X. R. Short communication: A sensitive method for qualitative screening of bile salt hydrolase-active lactobacilli based on thin-layer chromatography. Journal of Dairy Science, 94(4), 1732-1737, 2011.
 
[23]  Saitou, N., and Nei, M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology and Evolution, 4(4), 406-425, 1987.
 
[24]  Tamura K, Nei M, and Kumar S. Prospects for inferring very large phylogenies by using the neighbor-joining method. Proceedings Of The National Academy Of Sciences Of The United States Of America, 101(30), 11030-11035, 2004.
 
[25]  Kumar, S., Stecher, G., Li, M., Knyaz, C., and Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Molecular Biology and Evolution, 35(6), 1547-1549, 2018.
 
[26]  Kumar, M., Jain, A. K., Ghosh, M., and Ganguli, A. Statistical optimization of physical parameters for enhanced bacteriocin production by L. casei. Biotechnology and Bioprocess Engineering, 17(3), 606-616, 2012.
 
[27]  Radha, K. R., and Padmavathi, T. Statistical optimization of bacteriocin produced from Lactobacillus delbrueckii subsp bulgaricus isolated from yoghurt. International Food Research Journal, 24(2), 803-809, 2017.
 
[28]  Abalos, A., Maximo, F., Manresa, M. A., and Bastida, J. Utilization of response surface methodology to optimize the culture media for the production of rhamnolipids by Pseudomonas aeruginosa AT10. Journal of Chemical Technology and Biotechnology, 77(7), 777-784, 2002.
 
[29]  Osório, N. M., Ferreira-Dias, S., Gusmão, J. H., and Da Fonseca, M. M. R. Response surface modelling of the production of ω-3 polyunsaturated fatty acids-enriched fats by a commercial immobilized lipase. Journal of Molecular Catalysis - B Enzymatic, 11(4-6), 677-686, 2001.
 
[30]  Khuri, A. I., and Mukhopadhyay, S. Response surface methodology. In Wiley Interdisciplinary Reviews: Computational Statistics 2(2), 128-149, 2010.
 
[31]  Kleijnen, J. P. C. Response surface methodology. In International Series in Operations Research and Management Science 216, 81-104, 2015.
 
[32]  Dey, G., Mitra, A., Banerjee, R., and Maiti, B. R. Enhanced production of amylase by optimization of nutritional constituents using response surface methodology. Biochemical Engineering Journal, 7(3), 227-231, 2001.
 
[33]  Vohra, A., and Satyanarayana, T. Statistical optimization of the medium components by response surface methodology to enhance phytase production by Pichia anomala. Process Biochemistry, 37(9), 999-1004, 2002.
 
[34]  Cheigh, C. I., Choi, H. J., Park, H., Kim, S. B., Kook, M. C., Kim, T. S., Hwang, J. K., and Pyun, Y. R. Influence of growth conditions on the production of a nisin-like bacteriocin by Lactococcus lactis subsp. lactis A164 isolated from kimchi. Journal of Biotechnology, 95(3), 225-235, 2002.
 
[35]  Juarez Tomás, M. S., Bru, E., Wiese, B., De Ruiz Holgado, A. A. P., and Nader-Macías, M. E. Influence of pH, temperature and culture media on the growth and bacteriocin production by vaginal Lactobacillus salivarius CRL 1328. Journal of Applied Microbiology, 93(4), 714-724, 2002.
 
[36]  Mataragas, M., Metaxopoulos, J., Galiotou, M., and Drosinos, E. H. Influence of pH and temperature on growth and bacteriocin production by Leuconostoc mesenteroides L124 and Lactobacillus curvatus L442. Meat Science, 64(3), 265-271, 2003.
 
[37]  Denison, S. H. pH regulation of gene expression in fungi. In Fungal Genetics and Biology 29(2), 61-71, 2000.
 
[38]  Peñalva, M. A., and Arst, H. N. Regulation of Gene Expression by Ambient pH in Filamentous Fungi and Yeasts. Microbiology and Molecular Biology Reviews, 66(3), 426-446, 2002.