The Evolution of Control and Distribution of Adaptive Mutations in a Metabolic Pathway
In an attempt to understand whether it should be expected that some genes tend to be used disproportionately often by natural selection, we investigated two related phenomena: the evolution of flux control among enzymes in a metabolic pathway and properties of adaptive substitutions in pathway enzym...
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Veröffentlicht in: | Genetics (Austin) 2010-02, Vol.184 (2), p.483-502 |
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description | In an attempt to understand whether it should be expected that some genes tend to be used disproportionately often by natural selection, we investigated two related phenomena: the evolution of flux control among enzymes in a metabolic pathway and properties of adaptive substitutions in pathway enzymes. These two phenomena are related by the principle that adaptive substitutions should occur more frequently in enzymes with greater flux control. Predicting which enzymes will be preferentially involved in adaptive evolution thus requires an evolutionary theory of flux control. We investigated the evolution of enzyme control in metabolic pathways with two models of enzyme kinetics: metabolic control theory (MCT) and Michaelis-Menten saturation kinetics (SK). Our models generate two main predictions for pathways in which reactions are moderately to highly irreversible: (1) flux control will evolve to be highly unequal among enzymes in a pathway and (2) upstream enzymes evolve a greater control coefficient then those downstream. This results in upstream enzymes fixing the majority of beneficial mutations during adaptive evolution. Once the population has reached high fitness, the trend is reversed, with the majority of neutral/slightly deleterious mutations occurring in downstream enzymes. These patterns are the result of three factors (the first of these is unique to the MCT simulations while the other two seem to be general properties of the metabolic pathways): (1) the majority of randomly selected, starting combinations of enzyme kinetic rates generate pathways that possess greater control for the upstream enzymes compared to downstream enzymes; (2) selection against large pools of intermediate substrates tends to prevent majority control by downstream enzymes; and (3) equivalent mutations in enzyme kinetic rates have the greatest effect on flux for enzymes with high levels of flux control, and these enzymes will accumulate adaptive substitutions, strengthening their control. Prediction 1 is well supported by available data on control coefficients. Data for evaluating prediction 2 are sparse but not inconsistent with this prediction. |
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These two phenomena are related by the principle that adaptive substitutions should occur more frequently in enzymes with greater flux control. Predicting which enzymes will be preferentially involved in adaptive evolution thus requires an evolutionary theory of flux control. We investigated the evolution of enzyme control in metabolic pathways with two models of enzyme kinetics: metabolic control theory (MCT) and Michaelis-Menten saturation kinetics (SK). Our models generate two main predictions for pathways in which reactions are moderately to highly irreversible: (1) flux control will evolve to be highly unequal among enzymes in a pathway and (2) upstream enzymes evolve a greater control coefficient then those downstream. This results in upstream enzymes fixing the majority of beneficial mutations during adaptive evolution. Once the population has reached high fitness, the trend is reversed, with the majority of neutral/slightly deleterious mutations occurring in downstream enzymes. These patterns are the result of three factors (the first of these is unique to the MCT simulations while the other two seem to be general properties of the metabolic pathways): (1) the majority of randomly selected, starting combinations of enzyme kinetic rates generate pathways that possess greater control for the upstream enzymes compared to downstream enzymes; (2) selection against large pools of intermediate substrates tends to prevent majority control by downstream enzymes; and (3) equivalent mutations in enzyme kinetic rates have the greatest effect on flux for enzymes with high levels of flux control, and these enzymes will accumulate adaptive substitutions, strengthening their control. Prediction 1 is well supported by available data on control coefficients. Data for evaluating prediction 2 are sparse but not inconsistent with this prediction.</description><identifier>ISSN: 0016-6731</identifier><identifier>ISSN: 1943-2631</identifier><identifier>EISSN: 1943-2631</identifier><identifier>DOI: 10.1534/genetics.109.110411</identifier><identifier>PMID: 19966064</identifier><identifier>CODEN: GENTAE</identifier><language>eng</language><publisher>United States: Genetics Soc America</publisher><subject>Adaptation, Biological - genetics ; Control theory ; Enzyme kinetics ; Enzymes - genetics ; Enzymes - metabolism ; Evolution ; Evolution, Molecular ; Investigations ; Kinetics ; Metabolic Networks and Pathways - genetics ; Models, Biological ; Mutation ; Thermodynamics</subject><ispartof>Genetics (Austin), 2010-02, Vol.184 (2), p.483-502</ispartof><rights>Copyright Genetics Society of America Feb 2010</rights><rights>Copyright © 2010 by the Genetics Society of America 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c528t-90a44db07bd20688e7d9962e3c6d28bae5f2d6c7bb210c0c250d391505b2e43e3</citedby><cites>FETCH-LOGICAL-c528t-90a44db07bd20688e7d9962e3c6d28bae5f2d6c7bb210c0c250d391505b2e43e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19966064$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wright, Kevin M</creatorcontrib><creatorcontrib>Rausher, Mark D</creatorcontrib><title>The Evolution of Control and Distribution of Adaptive Mutations in a Metabolic Pathway</title><title>Genetics (Austin)</title><addtitle>Genetics</addtitle><description>In an attempt to understand whether it should be expected that some genes tend to be used disproportionately often by natural selection, we investigated two related phenomena: the evolution of flux control among enzymes in a metabolic pathway and properties of adaptive substitutions in pathway enzymes. These two phenomena are related by the principle that adaptive substitutions should occur more frequently in enzymes with greater flux control. Predicting which enzymes will be preferentially involved in adaptive evolution thus requires an evolutionary theory of flux control. We investigated the evolution of enzyme control in metabolic pathways with two models of enzyme kinetics: metabolic control theory (MCT) and Michaelis-Menten saturation kinetics (SK). Our models generate two main predictions for pathways in which reactions are moderately to highly irreversible: (1) flux control will evolve to be highly unequal among enzymes in a pathway and (2) upstream enzymes evolve a greater control coefficient then those downstream. This results in upstream enzymes fixing the majority of beneficial mutations during adaptive evolution. Once the population has reached high fitness, the trend is reversed, with the majority of neutral/slightly deleterious mutations occurring in downstream enzymes. These patterns are the result of three factors (the first of these is unique to the MCT simulations while the other two seem to be general properties of the metabolic pathways): (1) the majority of randomly selected, starting combinations of enzyme kinetic rates generate pathways that possess greater control for the upstream enzymes compared to downstream enzymes; (2) selection against large pools of intermediate substrates tends to prevent majority control by downstream enzymes; and (3) equivalent mutations in enzyme kinetic rates have the greatest effect on flux for enzymes with high levels of flux control, and these enzymes will accumulate adaptive substitutions, strengthening their control. Prediction 1 is well supported by available data on control coefficients. Data for evaluating prediction 2 are sparse but not inconsistent with this prediction.</description><subject>Adaptation, Biological - genetics</subject><subject>Control theory</subject><subject>Enzyme kinetics</subject><subject>Enzymes - genetics</subject><subject>Enzymes - metabolism</subject><subject>Evolution</subject><subject>Evolution, Molecular</subject><subject>Investigations</subject><subject>Kinetics</subject><subject>Metabolic Networks and Pathways - genetics</subject><subject>Models, Biological</subject><subject>Mutation</subject><subject>Thermodynamics</subject><issn>0016-6731</issn><issn>1943-2631</issn><issn>1943-2631</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpdkU1vEzEQhi0EomnhFyAhiwOcNnhsr3d9QapCC0it4FC4Wv5K1tVmHdberPrvcZRQPk4jzTzz6p15EXoFZAk14-83fvA52LQEIpcAhAM8QQuQnFVUMHiKFoSAqETD4Aydp3RPCBGybp-jM5BSCCL4Av246zy-2sd-yiEOOK7xKg55jD3Wg8MfQ8pjMI-zS6d3Oew9vp2yPjQTDgPW-NZnbWIfLP6mczfrhxfo2Vr3yb881Qv0_frqbvW5uvn66cvq8qayNW1zJYnm3BnSGEeJaFvfuOKMemaFo63Rvl5TJ2xjDAViiaU1cUxCTWpDPWeeXaAPR93dZLbeWV-8617txrDV44OKOqh_J0Po1CbuFW1p29CmCLw7CYzx5-RTVtuQrO97Pfg4JdUw1pQvyrqQb_4j7-M0DuU6RYEDA0kOEDtCdowpjX79aAWIOqSmfqdWGlIdUytbr_--4s_OKaYCvD0CXdh0cxi9Slvd9wUHNc8ztFxRxVvGfgEmPKNL</recordid><startdate>20100201</startdate><enddate>20100201</enddate><creator>Wright, Kevin M</creator><creator>Rausher, Mark D</creator><general>Genetics Soc America</general><general>Genetics Society of America</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>4T-</scope><scope>4U-</scope><scope>7QP</scope><scope>7SS</scope><scope>7TK</scope><scope>7TM</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K9-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0K</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M2P</scope><scope>M7N</scope><scope>M7P</scope><scope>MBDVC</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20100201</creationdate><title>The Evolution of Control and Distribution of Adaptive Mutations in a Metabolic Pathway</title><author>Wright, Kevin M ; Rausher, Mark D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c528t-90a44db07bd20688e7d9962e3c6d28bae5f2d6c7bb210c0c250d391505b2e43e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Adaptation, Biological - genetics</topic><topic>Control theory</topic><topic>Enzyme kinetics</topic><topic>Enzymes - genetics</topic><topic>Enzymes - metabolism</topic><topic>Evolution</topic><topic>Evolution, Molecular</topic><topic>Investigations</topic><topic>Kinetics</topic><topic>Metabolic Networks and Pathways - genetics</topic><topic>Models, Biological</topic><topic>Mutation</topic><topic>Thermodynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wright, Kevin M</creatorcontrib><creatorcontrib>Rausher, Mark D</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science 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 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>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</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>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Genetics (Austin)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wright, Kevin M</au><au>Rausher, Mark D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Evolution of Control and Distribution of Adaptive Mutations in a Metabolic Pathway</atitle><jtitle>Genetics (Austin)</jtitle><addtitle>Genetics</addtitle><date>2010-02-01</date><risdate>2010</risdate><volume>184</volume><issue>2</issue><spage>483</spage><epage>502</epage><pages>483-502</pages><issn>0016-6731</issn><issn>1943-2631</issn><eissn>1943-2631</eissn><coden>GENTAE</coden><abstract>In an attempt to understand whether it should be expected that some genes tend to be used disproportionately often by natural selection, we investigated two related phenomena: the evolution of flux control among enzymes in a metabolic pathway and properties of adaptive substitutions in pathway enzymes. These two phenomena are related by the principle that adaptive substitutions should occur more frequently in enzymes with greater flux control. Predicting which enzymes will be preferentially involved in adaptive evolution thus requires an evolutionary theory of flux control. We investigated the evolution of enzyme control in metabolic pathways with two models of enzyme kinetics: metabolic control theory (MCT) and Michaelis-Menten saturation kinetics (SK). Our models generate two main predictions for pathways in which reactions are moderately to highly irreversible: (1) flux control will evolve to be highly unequal among enzymes in a pathway and (2) upstream enzymes evolve a greater control coefficient then those downstream. This results in upstream enzymes fixing the majority of beneficial mutations during adaptive evolution. Once the population has reached high fitness, the trend is reversed, with the majority of neutral/slightly deleterious mutations occurring in downstream enzymes. These patterns are the result of three factors (the first of these is unique to the MCT simulations while the other two seem to be general properties of the metabolic pathways): (1) the majority of randomly selected, starting combinations of enzyme kinetic rates generate pathways that possess greater control for the upstream enzymes compared to downstream enzymes; (2) selection against large pools of intermediate substrates tends to prevent majority control by downstream enzymes; and (3) equivalent mutations in enzyme kinetic rates have the greatest effect on flux for enzymes with high levels of flux control, and these enzymes will accumulate adaptive substitutions, strengthening their control. Prediction 1 is well supported by available data on control coefficients. Data for evaluating prediction 2 are sparse but not inconsistent with this prediction.</abstract><cop>United States</cop><pub>Genetics Soc America</pub><pmid>19966064</pmid><doi>10.1534/genetics.109.110411</doi><tpages>20</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adaptation, Biological - genetics Control theory Enzyme kinetics Enzymes - genetics Enzymes - metabolism Evolution Evolution, Molecular Investigations Kinetics Metabolic Networks and Pathways - genetics Models, Biological Mutation Thermodynamics |
title | The Evolution of Control and Distribution of Adaptive Mutations in a Metabolic Pathway |
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