Steady-state metabolite concentrations reflect a balance between maximizing enzyme efficiency and minimizing total metabolite load
Steady-state metabolite concentrations in a microorganism typically span several orders of magnitude. The underlying principles governing these concentrations remain poorly understood. Here, we hypothesize that observed variation can be explained in terms of a compromise between factors that favor m...
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description | Steady-state metabolite concentrations in a microorganism typically span several orders of magnitude. The underlying principles governing these concentrations remain poorly understood. Here, we hypothesize that observed variation can be explained in terms of a compromise between factors that favor minimizing metabolite pool sizes (e.g. limited solvent capacity) and the need to effectively utilize existing enzymes. The latter requires adequate thermodynamic driving force in metabolic reactions so that forward flux substantially exceeds reverse flux. To test this hypothesis, we developed a method, metabolic tug-of-war (mTOW), which computes steady-state metabolite concentrations in microorganisms on a genome-scale. mTOW is shown to explain up to 55% of the observed variation in measured metabolite concentrations in E. coli and C. acetobutylicum across various growth media. Our approach, based strictly on first thermodynamic principles, is the first method that successfully predicts high-throughput metabolite concentration data in bacteria across conditions. |
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The underlying principles governing these concentrations remain poorly understood. Here, we hypothesize that observed variation can be explained in terms of a compromise between factors that favor minimizing metabolite pool sizes (e.g. limited solvent capacity) and the need to effectively utilize existing enzymes. The latter requires adequate thermodynamic driving force in metabolic reactions so that forward flux substantially exceeds reverse flux. To test this hypothesis, we developed a method, metabolic tug-of-war (mTOW), which computes steady-state metabolite concentrations in microorganisms on a genome-scale. mTOW is shown to explain up to 55% of the observed variation in measured metabolite concentrations in E. coli and C. acetobutylicum across various growth media. Our approach, based strictly on first thermodynamic principles, is the first method that successfully predicts high-throughput metabolite concentration data in bacteria across conditions.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0075370</identifier><identifier>PMID: 24086517</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Bacteria ; Bioinformatics ; Clostridium acetobutylicum - metabolism ; Computational Biology - methods ; Computer science ; E coli ; Efficiency ; Enzymes - metabolism ; Escherichia coli ; Escherichia coli - metabolism ; Genomes ; Genomics ; Growth media ; Mass spectrometry ; Metabolic Networks and Pathways - physiology ; Metabolism ; Metabolites ; Metabolome - physiology ; Microorganisms ; Models, Biological ; Parameter estimation ; Plant sciences ; Scientific imaging ; Steady state ; Thermodynamics ; War</subject><ispartof>PloS one, 2013-09, Vol.8 (9), p.e75370-e75370</ispartof><rights>2013 Tepper 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. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2013 Tepper et al 2013 Tepper et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c526t-f970182b018c213d3b22675244f9a70cc73f71b51bec966f1de1f0dba171caa33</citedby><cites>FETCH-LOGICAL-c526t-f970182b018c213d3b22675244f9a70cc73f71b51bec966f1de1f0dba171caa33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3784570/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3784570/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24086517$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Thattai, Mukund</contributor><creatorcontrib>Tepper, Naama</creatorcontrib><creatorcontrib>Noor, Elad</creatorcontrib><creatorcontrib>Amador-Noguez, Daniel</creatorcontrib><creatorcontrib>Haraldsdóttir, Hulda S</creatorcontrib><creatorcontrib>Milo, Ron</creatorcontrib><creatorcontrib>Rabinowitz, Josh</creatorcontrib><creatorcontrib>Liebermeister, Wolfram</creatorcontrib><creatorcontrib>Shlomi, Tomer</creatorcontrib><title>Steady-state metabolite concentrations reflect a balance between maximizing enzyme efficiency and minimizing total metabolite load</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Steady-state metabolite concentrations in a microorganism typically span several orders of magnitude. The underlying principles governing these concentrations remain poorly understood. Here, we hypothesize that observed variation can be explained in terms of a compromise between factors that favor minimizing metabolite pool sizes (e.g. limited solvent capacity) and the need to effectively utilize existing enzymes. The latter requires adequate thermodynamic driving force in metabolic reactions so that forward flux substantially exceeds reverse flux. To test this hypothesis, we developed a method, metabolic tug-of-war (mTOW), which computes steady-state metabolite concentrations in microorganisms on a genome-scale. mTOW is shown to explain up to 55% of the observed variation in measured metabolite concentrations in E. coli and C. acetobutylicum across various growth media. 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The underlying principles governing these concentrations remain poorly understood. Here, we hypothesize that observed variation can be explained in terms of a compromise between factors that favor minimizing metabolite pool sizes (e.g. limited solvent capacity) and the need to effectively utilize existing enzymes. The latter requires adequate thermodynamic driving force in metabolic reactions so that forward flux substantially exceeds reverse flux. To test this hypothesis, we developed a method, metabolic tug-of-war (mTOW), which computes steady-state metabolite concentrations in microorganisms on a genome-scale. mTOW is shown to explain up to 55% of the observed variation in measured metabolite concentrations in E. coli and C. acetobutylicum across various growth media. Our approach, based strictly on first thermodynamic principles, is the first method that successfully predicts high-throughput metabolite concentration data in bacteria across conditions.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24086517</pmid><doi>10.1371/journal.pone.0075370</doi><oa>free_for_read</oa></addata></record> |
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subjects | Bacteria Bioinformatics Clostridium acetobutylicum - metabolism Computational Biology - methods Computer science E coli Efficiency Enzymes - metabolism Escherichia coli Escherichia coli - metabolism Genomes Genomics Growth media Mass spectrometry Metabolic Networks and Pathways - physiology Metabolism Metabolites Metabolome - physiology Microorganisms Models, Biological Parameter estimation Plant sciences Scientific imaging Steady state Thermodynamics War |
title | Steady-state metabolite concentrations reflect a balance between maximizing enzyme efficiency and minimizing total metabolite load |
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