Industrial systems biology of Saccharomyces cerevisiae enables novel succinic acid cell factory
Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought afte...
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description | Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the α-keto-glutarate dehydrogenase catalyzed conversion of α-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2(nd)-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals. |
doi_str_mv | 10.1371/journal.pone.0054144 |
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Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the α-keto-glutarate dehydrogenase catalyzed conversion of α-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2(nd)-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0054144</identifier><identifier>PMID: 23349810</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aldehyde-Lyases - genetics ; Aldehyde-Lyases - metabolism ; Amino acids ; Bioengineering ; bioethanol ; Biofuels ; Bioinformatics ; Biological products ; Biology ; Biomass ; Biotechnology ; Carbon ; Chemicals ; Citric Acid Cycle ; Clonal deletion ; Conversion ; Data analysis ; Data processing ; Dehydrogenase ; Directed evolution ; Directed Molecular Evolution - methods ; Engineering ; Ethanol ; Evolution ; Evolutionary algorithms ; Factories ; Fermentation ; Fluxes ; Gene deletion ; Genetic engineering ; Genomes ; Genomics ; Glucose metabolism ; Glycine ; Glycolysis ; growth ; Growth rate ; Hypotheses ; in-silico ; Industrial Microbiology - methods ; Industrial production ; Information management ; Intermediates ; Interruption ; Isocitrate lyase ; Metabolic engineering ; Metabolic Engineering - methods ; Metabolism ; Metabolites ; Microorganisms ; Models, Genetic ; Molecular biology ; Mutation ; Oligonucleotide Array Sequence Analysis ; Overexpression ; Phosphoglycerate dehydrogenase ; products ; R&D ; reconstruction ; Reproducibility of Results ; Research & development ; Saccharomyces cerevisiae ; Saccharomyces cerevisiae - genetics ; Saccharomyces cerevisiae - growth & development ; Saccharomyces cerevisiae - metabolism ; Saccharomyces cerevisiae Proteins - genetics ; Saccharomyces cerevisiae Proteins - metabolism ; scale metabolic model ; Serine ; strains ; Succinate dehydrogenase ; Succinic acid ; Succinic Acid - metabolism ; Systems Biology - methods ; Target recognition ; Transaminases - genetics ; Transaminases - metabolism ; Transcriptome - genetics ; Tricarboxylic acid cycle ; validation ; Yeast</subject><ispartof>PloS one, 2013-01, Vol.8 (1), p.e54144-e54144</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Otero et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the α-keto-glutarate dehydrogenase catalyzed conversion of α-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2(nd)-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals.</description><subject>Aldehyde-Lyases - genetics</subject><subject>Aldehyde-Lyases - metabolism</subject><subject>Amino acids</subject><subject>Bioengineering</subject><subject>bioethanol</subject><subject>Biofuels</subject><subject>Bioinformatics</subject><subject>Biological products</subject><subject>Biology</subject><subject>Biomass</subject><subject>Biotechnology</subject><subject>Carbon</subject><subject>Chemicals</subject><subject>Citric Acid Cycle</subject><subject>Clonal deletion</subject><subject>Conversion</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Dehydrogenase</subject><subject>Directed evolution</subject><subject>Directed Molecular Evolution - methods</subject><subject>Engineering</subject><subject>Ethanol</subject><subject>Evolution</subject><subject>Evolutionary algorithms</subject><subject>Factories</subject><subject>Fermentation</subject><subject>Fluxes</subject><subject>Gene deletion</subject><subject>Genetic engineering</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Glucose metabolism</subject><subject>Glycine</subject><subject>Glycolysis</subject><subject>growth</subject><subject>Growth rate</subject><subject>Hypotheses</subject><subject>in-silico</subject><subject>Industrial Microbiology - methods</subject><subject>Industrial production</subject><subject>Information management</subject><subject>Intermediates</subject><subject>Interruption</subject><subject>Isocitrate lyase</subject><subject>Metabolic engineering</subject><subject>Metabolic Engineering - methods</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Microorganisms</subject><subject>Models, Genetic</subject><subject>Molecular biology</subject><subject>Mutation</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Overexpression</subject><subject>Phosphoglycerate dehydrogenase</subject><subject>products</subject><subject>R&D</subject><subject>reconstruction</subject><subject>Reproducibility of Results</subject><subject>Research & development</subject><subject>Saccharomyces cerevisiae</subject><subject>Saccharomyces cerevisiae - 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metabolism</topic><topic>scale metabolic model</topic><topic>Serine</topic><topic>strains</topic><topic>Succinate dehydrogenase</topic><topic>Succinic acid</topic><topic>Succinic Acid - metabolism</topic><topic>Systems Biology - methods</topic><topic>Target recognition</topic><topic>Transaminases - genetics</topic><topic>Transaminases - metabolism</topic><topic>Transcriptome - genetics</topic><topic>Tricarboxylic acid cycle</topic><topic>validation</topic><topic>Yeast</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Otero, José Manuel</creatorcontrib><creatorcontrib>Cimini, Donatella</creatorcontrib><creatorcontrib>Patil, Kiran R</creatorcontrib><creatorcontrib>Poulsen, Simon G</creatorcontrib><creatorcontrib>Olsson, Lisbeth</creatorcontrib><creatorcontrib>Nielsen, Jens</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SWEPUB Chalmers tekniska högskola full text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Chalmers tekniska högskola</collection><collection>SwePub Articles full text</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Otero, José Manuel</au><au>Cimini, Donatella</au><au>Patil, Kiran R</au><au>Poulsen, Simon G</au><au>Olsson, Lisbeth</au><au>Nielsen, Jens</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Industrial systems biology of Saccharomyces cerevisiae enables novel succinic acid cell factory</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2013-01-21</date><risdate>2013</risdate><volume>8</volume><issue>1</issue><spage>e54144</spage><epage>e54144</epage><pages>e54144-e54144</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the α-keto-glutarate dehydrogenase catalyzed conversion of α-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2(nd)-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>23349810</pmid><doi>10.1371/journal.pone.0054144</doi><tpages>e54144</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2013-01, Vol.8 (1), p.e54144-e54144 |
issn | 1932-6203 1932-6203 |
language | eng |
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source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; SWEPUB Freely available online; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
subjects | Aldehyde-Lyases - genetics Aldehyde-Lyases - metabolism Amino acids Bioengineering bioethanol Biofuels Bioinformatics Biological products Biology Biomass Biotechnology Carbon Chemicals Citric Acid Cycle Clonal deletion Conversion Data analysis Data processing Dehydrogenase Directed evolution Directed Molecular Evolution - methods Engineering Ethanol Evolution Evolutionary algorithms Factories Fermentation Fluxes Gene deletion Genetic engineering Genomes Genomics Glucose metabolism Glycine Glycolysis growth Growth rate Hypotheses in-silico Industrial Microbiology - methods Industrial production Information management Intermediates Interruption Isocitrate lyase Metabolic engineering Metabolic Engineering - methods Metabolism Metabolites Microorganisms Models, Genetic Molecular biology Mutation Oligonucleotide Array Sequence Analysis Overexpression Phosphoglycerate dehydrogenase products R&D reconstruction Reproducibility of Results Research & development Saccharomyces cerevisiae Saccharomyces cerevisiae - genetics Saccharomyces cerevisiae - growth & development Saccharomyces cerevisiae - metabolism Saccharomyces cerevisiae Proteins - genetics Saccharomyces cerevisiae Proteins - metabolism scale metabolic model Serine strains Succinate dehydrogenase Succinic acid Succinic Acid - metabolism Systems Biology - methods Target recognition Transaminases - genetics Transaminases - metabolism Transcriptome - genetics Tricarboxylic acid cycle validation Yeast |
title | Industrial systems biology of Saccharomyces cerevisiae enables novel succinic acid cell factory |
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