Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values

Detalhes bibliográficos
Autor(a) principal: Laluce, Cecilia [UNESP]
Data de Publicação: 2019
Outros Autores: Igbojionu, Longinus I. [UNESP], Silva, José L. [UNESP], Ribeiro, Clóvis A. [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1186/s13068-019-1453-4
http://hdl.handle.net/11449/189120
Resumo: Background: In the present work, the main inhibitors of the yeast cells (vanillin, furfural, formic, and levulinic acid) were generated by pretreatments or hydrolysis (sulfuric acid or enzymes) to convert reducing sugars into ethanol. Inhibitors were added at increasing concentrations to the SD-medium containing yeast extract while negative effects on yeast cells were observed. Statistical analyses were applied to predict and interpret results related to biomass production. Results: Inhibitors affected productivities and yields of biomass and ethanol when added to SD-medium. Based on the 23 full-central-composite design, predicted and observed values of ethanol and biomass were obtained in presence of the major inhibitors, which were acetic acid, formic acid, and levulinic acids. Increases in biomass and ethanol production are described in the Response surface graphs (RSM graphs) that resulted from multiple interactions between inhibitors. Positive interactions between the inhibitors occurred at low concentrations and pH values. The results were experimentally validated. Conclusions: Statistical analysis is an extremely useful tool for predicting data during process monitoring, while re-adjustments of conditions can be performed, whenever necessary. In addition, the development of new strains of yeast with high tolerance to biomass inhibitors will have a major impact on the production of second-generation ethanol. Increases in fermentation activity of the yeast Saccharomyces cerevisiae in a mixture containing low concentrations of inhibitors were observed.
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spelling Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH valuesBiomass inhibitorsFactorial designsInteractions between inhibitorsResponse optimizerRMS analysisSaccharomyces cerevisiaeBackground: In the present work, the main inhibitors of the yeast cells (vanillin, furfural, formic, and levulinic acid) were generated by pretreatments or hydrolysis (sulfuric acid or enzymes) to convert reducing sugars into ethanol. Inhibitors were added at increasing concentrations to the SD-medium containing yeast extract while negative effects on yeast cells were observed. Statistical analyses were applied to predict and interpret results related to biomass production. Results: Inhibitors affected productivities and yields of biomass and ethanol when added to SD-medium. Based on the 23 full-central-composite design, predicted and observed values of ethanol and biomass were obtained in presence of the major inhibitors, which were acetic acid, formic acid, and levulinic acids. Increases in biomass and ethanol production are described in the Response surface graphs (RSM graphs) that resulted from multiple interactions between inhibitors. Positive interactions between the inhibitors occurred at low concentrations and pH values. The results were experimentally validated. Conclusions: Statistical analysis is an extremely useful tool for predicting data during process monitoring, while re-adjustments of conditions can be performed, whenever necessary. In addition, the development of new strains of yeast with high tolerance to biomass inhibitors will have a major impact on the production of second-generation ethanol. Increases in fermentation activity of the yeast Saccharomyces cerevisiae in a mixture containing low concentrations of inhibitors were observed.Institute of Research in Bioenergy (IPBEN) Institute of Chemistry São Paulo State University (UNESP), R. Prof. Francisco Degni, 55Dept Analytical Chemistry Institute of Chemistry State University of São Paulo Júlio de Mesquita Filho-UNESP, R. Professor Francisco Degni, 55Institute of Research in Bioenergy (IPBEN) Institute of Chemistry São Paulo State University (UNESP), R. Prof. Francisco Degni, 55Dept Analytical Chemistry Institute of Chemistry State University of São Paulo Júlio de Mesquita Filho-UNESP, R. Professor Francisco Degni, 55Universidade Estadual Paulista (Unesp)Laluce, Cecilia [UNESP]Igbojionu, Longinus I. [UNESP]Silva, José L. [UNESP]Ribeiro, Clóvis A. [UNESP]2019-10-06T16:30:26Z2019-10-06T16:30:26Z2019-05-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s13068-019-1453-4Biotechnology for Biofuels, v. 12, n. 1, 2019.1754-6834http://hdl.handle.net/11449/18912010.1186/s13068-019-1453-42-s2.0-8506567730884983108918100820000-0002-7984-5908Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengBiotechnology for Biofuelsinfo:eu-repo/semantics/openAccess2022-03-03T12:26:15Zoai:repositorio.unesp.br:11449/189120Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:01:43.804813Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
title Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
spellingShingle Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
Laluce, Cecilia [UNESP]
Biomass inhibitors
Factorial designs
Interactions between inhibitors
Response optimizer
RMS analysis
Saccharomyces cerevisiae
title_short Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
title_full Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
title_fullStr Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
title_full_unstemmed Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
title_sort Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values
author Laluce, Cecilia [UNESP]
author_facet Laluce, Cecilia [UNESP]
Igbojionu, Longinus I. [UNESP]
Silva, José L. [UNESP]
Ribeiro, Clóvis A. [UNESP]
author_role author
author2 Igbojionu, Longinus I. [UNESP]
Silva, José L. [UNESP]
Ribeiro, Clóvis A. [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Laluce, Cecilia [UNESP]
Igbojionu, Longinus I. [UNESP]
Silva, José L. [UNESP]
Ribeiro, Clóvis A. [UNESP]
dc.subject.por.fl_str_mv Biomass inhibitors
Factorial designs
Interactions between inhibitors
Response optimizer
RMS analysis
Saccharomyces cerevisiae
topic Biomass inhibitors
Factorial designs
Interactions between inhibitors
Response optimizer
RMS analysis
Saccharomyces cerevisiae
description Background: In the present work, the main inhibitors of the yeast cells (vanillin, furfural, formic, and levulinic acid) were generated by pretreatments or hydrolysis (sulfuric acid or enzymes) to convert reducing sugars into ethanol. Inhibitors were added at increasing concentrations to the SD-medium containing yeast extract while negative effects on yeast cells were observed. Statistical analyses were applied to predict and interpret results related to biomass production. Results: Inhibitors affected productivities and yields of biomass and ethanol when added to SD-medium. Based on the 23 full-central-composite design, predicted and observed values of ethanol and biomass were obtained in presence of the major inhibitors, which were acetic acid, formic acid, and levulinic acids. Increases in biomass and ethanol production are described in the Response surface graphs (RSM graphs) that resulted from multiple interactions between inhibitors. Positive interactions between the inhibitors occurred at low concentrations and pH values. The results were experimentally validated. Conclusions: Statistical analysis is an extremely useful tool for predicting data during process monitoring, while re-adjustments of conditions can be performed, whenever necessary. In addition, the development of new strains of yeast with high tolerance to biomass inhibitors will have a major impact on the production of second-generation ethanol. Increases in fermentation activity of the yeast Saccharomyces cerevisiae in a mixture containing low concentrations of inhibitors were observed.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-06T16:30:26Z
2019-10-06T16:30:26Z
2019-05-09
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1186/s13068-019-1453-4
Biotechnology for Biofuels, v. 12, n. 1, 2019.
1754-6834
http://hdl.handle.net/11449/189120
10.1186/s13068-019-1453-4
2-s2.0-85065677308
8498310891810082
0000-0002-7984-5908
url http://dx.doi.org/10.1186/s13068-019-1453-4
http://hdl.handle.net/11449/189120
identifier_str_mv Biotechnology for Biofuels, v. 12, n. 1, 2019.
1754-6834
10.1186/s13068-019-1453-4
2-s2.0-85065677308
8498310891810082
0000-0002-7984-5908
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Biotechnology for Biofuels
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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