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An indirect optimization method for biochemical systems: description of method and application to the maximization of the rate of ethanol, glycerol, and carbohydrate production in Saccharomyces cerevisiae
Three metabolic models for the production of ethanol, glycerol, and carbohydrates in yeast are optimized with respect to different production rates. While originally nonlinear, all three optimization problems are reduced in such a way that methods of linear programming can be used. The optimizations...
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Published in: | Biotechnology and bioengineering 1997-09, Vol.55 (5), p.758-772 |
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container_title | Biotechnology and bioengineering |
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creator | Torres, N.V. (Universidad de La Launa, La Laguna, Espena.) Voit, E.O Glez-Alcon, C Rodriguez, F |
description | Three metabolic models for the production of ethanol, glycerol, and carbohydrates in yeast are optimized with respect to different production rates. While originally nonlinear, all three optimization problems are reduced in such a way that methods of linear programming can be used. The optimizations lead to profiles of enzyme activities that are compatible with the physiology of the cells, which guarantees their viability and fitness, and yield higher rates of the desired final end products than the original systems. In order to increase ethanol rate production at least three times, six enzymes must be modulated. By contrast, when the production of glycerol or carbohydrates is optimized, modulation of just one enzyme (in the case of glycerol) or two enzymes, (in the case of carbohydrates) is necessary to yield significant increases in product flux rate. Comparisons of our results with those obtained from other methods show great similarities and demonstrate that both are valid methods. The choice of one or the other method depends on the question of interest |
doi_str_mv | 10.1002/(SICI)1097-0290(19970905)55:5<758::AID-BIT6>3.0.CO;2-A |
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(Universidad de La Launa, La Laguna, Espena.) ; Voit, E.O ; Glez-Alcon, C ; Rodriguez, F</creator><creatorcontrib>Torres, N.V. (Universidad de La Launa, La Laguna, Espena.) ; Voit, E.O ; Glez-Alcon, C ; Rodriguez, F</creatorcontrib><description>Three metabolic models for the production of ethanol, glycerol, and carbohydrates in yeast are optimized with respect to different production rates. While originally nonlinear, all three optimization problems are reduced in such a way that methods of linear programming can be used. The optimizations lead to profiles of enzyme activities that are compatible with the physiology of the cells, which guarantees their viability and fitness, and yield higher rates of the desired final end products than the original systems. In order to increase ethanol rate production at least three times, six enzymes must be modulated. By contrast, when the production of glycerol or carbohydrates is optimized, modulation of just one enzyme (in the case of glycerol) or two enzymes, (in the case of carbohydrates) is necessary to yield significant increases in product flux rate. Comparisons of our results with those obtained from other methods show great similarities and demonstrate that both are valid methods. The choice of one or the other method depends on the question of interest</description><identifier>ISSN: 0006-3592</identifier><identifier>EISSN: 1097-0290</identifier><identifier>DOI: 10.1002/(SICI)1097-0290(19970905)55:5<758::AID-BIT6>3.0.CO;2-A</identifier><identifier>PMID: 18636586</identifier><identifier>CODEN: BIBIAU</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Biological and medical sciences ; Biotechnology ; carbohydrates ; ethanol ; Fundamental and applied biological sciences. Psychology ; glycerol ; linear programming ; metabolic systems ; Methods. Procedures. Technologies ; Microbial engineering. Fermentation and microbial culture technology ; Optimization ; S-system representation ; SACCHAROMYCES CEREVISIAE</subject><ispartof>Biotechnology and bioengineering, 1997-09, Vol.55 (5), p.758-772</ispartof><rights>Copyright © 1997 John Wiley & Sons, Inc.</rights><rights>1997 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=2775886$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18636586$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Torres, N.V. (Universidad de La Launa, La Laguna, Espena.)</creatorcontrib><creatorcontrib>Voit, E.O</creatorcontrib><creatorcontrib>Glez-Alcon, C</creatorcontrib><creatorcontrib>Rodriguez, F</creatorcontrib><title>An indirect optimization method for biochemical systems: description of method and application to the maximization of the rate of ethanol, glycerol, and carbohydrate production in Saccharomyces cerevisiae</title><title>Biotechnology and bioengineering</title><addtitle>Biotechnol. Bioeng</addtitle><description>Three metabolic models for the production of ethanol, glycerol, and carbohydrates in yeast are optimized with respect to different production rates. While originally nonlinear, all three optimization problems are reduced in such a way that methods of linear programming can be used. The optimizations lead to profiles of enzyme activities that are compatible with the physiology of the cells, which guarantees their viability and fitness, and yield higher rates of the desired final end products than the original systems. In order to increase ethanol rate production at least three times, six enzymes must be modulated. By contrast, when the production of glycerol or carbohydrates is optimized, modulation of just one enzyme (in the case of glycerol) or two enzymes, (in the case of carbohydrates) is necessary to yield significant increases in product flux rate. Comparisons of our results with those obtained from other methods show great similarities and demonstrate that both are valid methods. The choice of one or the other method depends on the question of interest</description><subject>Biological and medical sciences</subject><subject>Biotechnology</subject><subject>carbohydrates</subject><subject>ethanol</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>glycerol</subject><subject>linear programming</subject><subject>metabolic systems</subject><subject>Methods. Procedures. Technologies</subject><subject>Microbial engineering. Fermentation and microbial culture technology</subject><subject>Optimization</subject><subject>S-system representation</subject><subject>SACCHAROMYCES CEREVISIAE</subject><issn>0006-3592</issn><issn>1097-0290</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1997</creationdate><recordtype>article</recordtype><recordid>eNqNkt9u0zAUhyMEYmXwAlygXCDYJFLsOLbjgiaVwkqnQS-6waV16jirIYmLncLKM_JQOP23O4Rky8f2d36y5C-KzjDqY4TS1yezyWhyipHgCUoFOsFCcCQQPaV0QN9ymg8Gw8n75N3kip2RPuqPpm_SZHgv6h1a7kc9hBBLCBXpUfTI-29hy3PGHkZHOGeE0Zz1oj_DJjZNYZxWbWyXranNb2iNbeJatwtbxKV18dxYtdC1UVDFfu1bXftBXGivnFluWFvucWjCXC6rwG5uWhu3Cx3XcHuXHOjuzEGruzo0QmOrV_FNtVbadVWXosDN7WJdbLCls8VKbbpNE89AqQU4Wwfex6FH_zTegH4cPSih8vrJbj2Ors8_XI0-JpfT8WQ0vEzKjGOW5KnIEIcSOKAScii4AsFxqTNGOdeYZBTP5wQhjLUGKoQCQAwBRqTISIbJcfRymxue9WOlfStr45WuKmi0XXnJCaFEcJ4H8sU_ScxwSjgm_wEikRPKAvhsB67mtS7k0pka3FruvzQAz3cA-PBhpYNGGX_gUh7k2WBfttgvU-n1XQySnX-y0092LsnOJbnXT9IwZEiQwT7Z2SeJRHI0lakcbvYhONkGmyDK7SEY3HfJOOFUfv08lhezMRbnn5i8CPzTLV-ClXDjwluvZ4JnCFFK_gKjMu2Q</recordid><startdate>19970905</startdate><enddate>19970905</enddate><creator>Torres, N.V. 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(Universidad de La Launa, La Laguna, Espena.) ; Voit, E.O ; Glez-Alcon, C ; Rodriguez, F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-f4716-829407afa7a0fa8ad7ca971fe46577e13451bb30011eea599caa060a103d43413</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1997</creationdate><topic>Biological and medical sciences</topic><topic>Biotechnology</topic><topic>carbohydrates</topic><topic>ethanol</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>glycerol</topic><topic>linear programming</topic><topic>metabolic systems</topic><topic>Methods. Procedures. Technologies</topic><topic>Microbial engineering. Fermentation and microbial culture technology</topic><topic>Optimization</topic><topic>S-system representation</topic><topic>SACCHAROMYCES CEREVISIAE</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Torres, N.V. (Universidad de La Launa, La Laguna, Espena.)</creatorcontrib><creatorcontrib>Voit, E.O</creatorcontrib><creatorcontrib>Glez-Alcon, C</creatorcontrib><creatorcontrib>Rodriguez, F</creatorcontrib><collection>AGRIS</collection><collection>Istex</collection><collection>Pascal-Francis</collection><collection>PubMed</collection><collection>Biotechnology Research Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Biotechnology and bioengineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Torres, N.V. 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The optimizations lead to profiles of enzyme activities that are compatible with the physiology of the cells, which guarantees their viability and fitness, and yield higher rates of the desired final end products than the original systems. In order to increase ethanol rate production at least three times, six enzymes must be modulated. By contrast, when the production of glycerol or carbohydrates is optimized, modulation of just one enzyme (in the case of glycerol) or two enzymes, (in the case of carbohydrates) is necessary to yield significant increases in product flux rate. Comparisons of our results with those obtained from other methods show great similarities and demonstrate that both are valid methods. 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subjects | Biological and medical sciences Biotechnology carbohydrates ethanol Fundamental and applied biological sciences. Psychology glycerol linear programming metabolic systems Methods. Procedures. Technologies Microbial engineering. Fermentation and microbial culture technology Optimization S-system representation SACCHAROMYCES CEREVISIAE |
title | An indirect optimization method for biochemical systems: description of method and application to the maximization of the rate of ethanol, glycerol, and carbohydrate production in Saccharomyces cerevisiae |
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