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Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology

Wild-cultivated medicinal mushroom Ganoderma lucidum was morphologically identified and sequenced using phylogenetic software. In submerged-liquid fermentation (SLF), biomass, exopolysaccharide (EPS) and intracellular polysaccharide (IPS) production of the identified G. lucidum was optimised based o...

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Autores principales: Supramani, Sugenendran, Ahmad, Rahayu, Ilham, Zul, Annuar, Mohamad Suffian Mohamad, Klaus, Anita, Wan-Mohtar, Wan Abd Al Qadr Imad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIMS Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646932/
https://www.ncbi.nlm.nih.gov/pubmed/31384700
http://dx.doi.org/10.3934/microbiol.2019.1.19
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author Supramani, Sugenendran
Ahmad, Rahayu
Ilham, Zul
Annuar, Mohamad Suffian Mohamad
Klaus, Anita
Wan-Mohtar, Wan Abd Al Qadr Imad
author_facet Supramani, Sugenendran
Ahmad, Rahayu
Ilham, Zul
Annuar, Mohamad Suffian Mohamad
Klaus, Anita
Wan-Mohtar, Wan Abd Al Qadr Imad
author_sort Supramani, Sugenendran
collection PubMed
description Wild-cultivated medicinal mushroom Ganoderma lucidum was morphologically identified and sequenced using phylogenetic software. In submerged-liquid fermentation (SLF), biomass, exopolysaccharide (EPS) and intracellular polysaccharide (IPS) production of the identified G. lucidum was optimised based on initial pH, starting glucose concentration and agitation rate parameters using response surface methodology (RSM). Molecularly, the G. lucidum strain QRS 5120 generated 637 base pairs, which was commensurate with related Ganoderma species. In RSM, by applying central composite design (CCD), a polynomial model was fitted to the experimental data and was found to be significant in all parameters investigated. The strongest effect (p < 0.0001) was observed for initial pH for biomass, EPS and IPS production, while agitation showed a significant value (p < 0.005) for biomass. By applying the optimized conditions, the model was validated and generated 5.12 g/L of biomass (initial pH 4.01, 32.09 g/L of glucose and 102 rpm), 2.49 g/L EPS (initial pH 4, 24.25 g/L of glucose and 110 rpm) and 1.52 g/L of IPS (and initial pH 4, 40.43 g/L of glucose, 103 rpm) in 500 mL shake flask fermentation. The optimized parameters can be upscaled for efficient biomass, EPS and IPS production using G. lucidum.
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spelling pubmed-66469322019-08-05 Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology Supramani, Sugenendran Ahmad, Rahayu Ilham, Zul Annuar, Mohamad Suffian Mohamad Klaus, Anita Wan-Mohtar, Wan Abd Al Qadr Imad AIMS Microbiol Research Article Wild-cultivated medicinal mushroom Ganoderma lucidum was morphologically identified and sequenced using phylogenetic software. In submerged-liquid fermentation (SLF), biomass, exopolysaccharide (EPS) and intracellular polysaccharide (IPS) production of the identified G. lucidum was optimised based on initial pH, starting glucose concentration and agitation rate parameters using response surface methodology (RSM). Molecularly, the G. lucidum strain QRS 5120 generated 637 base pairs, which was commensurate with related Ganoderma species. In RSM, by applying central composite design (CCD), a polynomial model was fitted to the experimental data and was found to be significant in all parameters investigated. The strongest effect (p < 0.0001) was observed for initial pH for biomass, EPS and IPS production, while agitation showed a significant value (p < 0.005) for biomass. By applying the optimized conditions, the model was validated and generated 5.12 g/L of biomass (initial pH 4.01, 32.09 g/L of glucose and 102 rpm), 2.49 g/L EPS (initial pH 4, 24.25 g/L of glucose and 110 rpm) and 1.52 g/L of IPS (and initial pH 4, 40.43 g/L of glucose, 103 rpm) in 500 mL shake flask fermentation. The optimized parameters can be upscaled for efficient biomass, EPS and IPS production using G. lucidum. AIMS Press 2019-01-22 /pmc/articles/PMC6646932/ /pubmed/31384700 http://dx.doi.org/10.3934/microbiol.2019.1.19 Text en © 2019 the Author(s), licensee AIMS Press This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
spellingShingle Research Article
Supramani, Sugenendran
Ahmad, Rahayu
Ilham, Zul
Annuar, Mohamad Suffian Mohamad
Klaus, Anita
Wan-Mohtar, Wan Abd Al Qadr Imad
Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology
title Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology
title_full Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology
title_fullStr Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology
title_full_unstemmed Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology
title_short Optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified Ganoderma lucidum strain QRS 5120 using response surface methodology
title_sort optimisation of biomass, exopolysaccharide and intracellular polysaccharide production from the mycelium of an identified ganoderma lucidum strain qrs 5120 using response surface methodology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646932/
https://www.ncbi.nlm.nih.gov/pubmed/31384700
http://dx.doi.org/10.3934/microbiol.2019.1.19
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