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Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation

BACKGROUND: Actinomycetes are excellent microbial sources for various chemical structures like enzymes, most of which are used in pharmaceutical and industrial products. Actinomycetes are preferred sources of enzymes due to their high ability to produce extracellular enzymes. l-glutaminase has prove...

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Autores principales: Wardah, Zuhour Hussein, Chaudhari, Hiral G., Prajapati, Vimalkumar, Raol, Gopalkumar G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673782/
https://www.ncbi.nlm.nih.gov/pubmed/37999820
http://dx.doi.org/10.1186/s43141-023-00618-2
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author Wardah, Zuhour Hussein
Chaudhari, Hiral G.
Prajapati, Vimalkumar
Raol, Gopalkumar G.
author_facet Wardah, Zuhour Hussein
Chaudhari, Hiral G.
Prajapati, Vimalkumar
Raol, Gopalkumar G.
author_sort Wardah, Zuhour Hussein
collection PubMed
description BACKGROUND: Actinomycetes are excellent microbial sources for various chemical structures like enzymes, most of which are used in pharmaceutical and industrial products. Actinomycetes are preferred sources of enzymes due to their high ability to produce extracellular enzymes. l-glutaminase has proven its essential role as a pharmaceutical agent in cancer therapy and an economic agent in the food industry. The current study aimed to screen the potent l-glutaminase producer and optimize the production media for maximum enzyme yield using one factor at a time (OFAT) approach and statistical approaches under solid-state fermentation (SSF). RESULTS: Out of 20 actinomycetes strains isolated from rhizosphere soil, 5 isolates produced extracellular l-glutaminase. One isolate was chosen as the most potent strain, and identified as Streptomyces pseudogriseolus ZHG20 based on 16S rRNA. The production and optimization process were carried out under SSF, after optimization using OFAT method, the enzyme production increased up to 884.61 U/gds. Further, statistical strategy, response surface methodology (RSM), and central composite design (CCD) were employed for the level optimization of significant media component (p < 0.05), i.e., wheat bran, sesame oil cake, and corn steep liquor which are leading to increase 3.21-fold l-glutaminase production as compared to unoptimized media. CONCLUSIONS: The presented investigation reveals the optimization of various physicochemical parameters using OFAT and RSM-CCD. Statistical approaches proved to be an effective method for increasing the yield of extracellular l-glutaminase from S. pseudogriseolus ZHG20 where l-glutaminase activity increased up to 1297.87 U/gds which is 3.21-fold higher than the unoptimized medium using a mixture of two solid substrates (wheat bran and sesame oil cake) incubated at pH 7.0 for 6 days at 33 °C.
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spelling pubmed-106737822023-11-24 Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation Wardah, Zuhour Hussein Chaudhari, Hiral G. Prajapati, Vimalkumar Raol, Gopalkumar G. J Genet Eng Biotechnol Research BACKGROUND: Actinomycetes are excellent microbial sources for various chemical structures like enzymes, most of which are used in pharmaceutical and industrial products. Actinomycetes are preferred sources of enzymes due to their high ability to produce extracellular enzymes. l-glutaminase has proven its essential role as a pharmaceutical agent in cancer therapy and an economic agent in the food industry. The current study aimed to screen the potent l-glutaminase producer and optimize the production media for maximum enzyme yield using one factor at a time (OFAT) approach and statistical approaches under solid-state fermentation (SSF). RESULTS: Out of 20 actinomycetes strains isolated from rhizosphere soil, 5 isolates produced extracellular l-glutaminase. One isolate was chosen as the most potent strain, and identified as Streptomyces pseudogriseolus ZHG20 based on 16S rRNA. The production and optimization process were carried out under SSF, after optimization using OFAT method, the enzyme production increased up to 884.61 U/gds. Further, statistical strategy, response surface methodology (RSM), and central composite design (CCD) were employed for the level optimization of significant media component (p < 0.05), i.e., wheat bran, sesame oil cake, and corn steep liquor which are leading to increase 3.21-fold l-glutaminase production as compared to unoptimized media. CONCLUSIONS: The presented investigation reveals the optimization of various physicochemical parameters using OFAT and RSM-CCD. Statistical approaches proved to be an effective method for increasing the yield of extracellular l-glutaminase from S. pseudogriseolus ZHG20 where l-glutaminase activity increased up to 1297.87 U/gds which is 3.21-fold higher than the unoptimized medium using a mixture of two solid substrates (wheat bran and sesame oil cake) incubated at pH 7.0 for 6 days at 33 °C. Springer Berlin Heidelberg 2023-11-24 /pmc/articles/PMC10673782/ /pubmed/37999820 http://dx.doi.org/10.1186/s43141-023-00618-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Wardah, Zuhour Hussein
Chaudhari, Hiral G.
Prajapati, Vimalkumar
Raol, Gopalkumar G.
Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation
title Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation
title_full Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation
title_fullStr Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation
title_full_unstemmed Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation
title_short Application of statistical methodology for the optimization of l-glutaminase enzyme production from Streptomyces pseudogriseolus ZHG20 under solid-state fermentation
title_sort application of statistical methodology for the optimization of l-glutaminase enzyme production from streptomyces pseudogriseolus zhg20 under solid-state fermentation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673782/
https://www.ncbi.nlm.nih.gov/pubmed/37999820
http://dx.doi.org/10.1186/s43141-023-00618-2
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