Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species
The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species t...
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creator | Freilich, Shiri Kreimer, Anat Borenstein, Elhanan Gophna, Uri Sharan, Roded Ruppin, Eytan |
description | The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species to endure genetic perturbations. Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species' lifestyle (specialized/generalist); the second, environmental-independent, is associated (correlation = approximately 0.6) with the intrinsic metabolic capacities of a species-higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets. |
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Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species' lifestyle (specialized/generalist); the second, environmental-independent, is associated (correlation = approximately 0.6) with the intrinsic metabolic capacities of a species-higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1000690</identifier><identifier>PMID: 20195496</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Bacteria - genetics ; Bacterial genetics ; Bacterial Physiological Phenomena ; Computational Biology - methods ; Computational Biology/Metabolic Networks ; Computer Simulation ; Environment ; Evolution ; Evolutionary Biology/Microbial Evolution and Genomics ; Genes ; Genetic Variation ; Metabolic Networks and Pathways ; Metabolites ; Microbiology ; Microbiology/Microbial Evolution and Genomics ; Models, Genetic ; Mutation ; Selection, Genetic ; Studies ; Systems Biology - methods</subject><ispartof>PLoS computational biology, 2010-02, Vol.6 (2), p.e1000690-e1000690</ispartof><rights>COPYRIGHT 2010 Public Library of Science</rights><rights>Freilich et al. 2010</rights><rights>2010 Freilich et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Freilich S, Kreimer A, Borenstein E, Gophna U, Sharan R, et al. (2010) Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species. 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Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species' lifestyle (specialized/generalist); the second, environmental-independent, is associated (correlation = approximately 0.6) with the intrinsic metabolic capacities of a species-higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. Finally, we identify reactions that are uniquely susceptible to perturbations in human pathogens, potentially serving as novel drug-targets.</description><subject>Analysis</subject><subject>Bacteria - genetics</subject><subject>Bacterial genetics</subject><subject>Bacterial Physiological Phenomena</subject><subject>Computational Biology - methods</subject><subject>Computational Biology/Metabolic Networks</subject><subject>Computer Simulation</subject><subject>Environment</subject><subject>Evolution</subject><subject>Evolutionary Biology/Microbial Evolution and Genomics</subject><subject>Genes</subject><subject>Genetic Variation</subject><subject>Metabolic Networks and Pathways</subject><subject>Metabolites</subject><subject>Microbiology</subject><subject>Microbiology/Microbial Evolution and Genomics</subject><subject>Models, Genetic</subject><subject>Mutation</subject><subject>Selection, Genetic</subject><subject>Studies</subject><subject>Systems Biology - methods</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>DOA</sourceid><recordid>eNpVUsmO1DAQjRCIWeAPEOTGKY3X2L4gDbPR0khILDcky3YqjVtpO9jJSPw97un0aEZ1qOdyveeqclXVO4xWmAr8aRvnFMywGp31K4wQahV6UZ1izmkjKJcvn-CT6iznLUIFqvZ1dUIQVpyp9rT6fQUuzuPgw6a-Dvc-xbCDMDVXMELoCqpN6Op1gcfzLQSYvKu_RzvnKUDOtXEpFvfFuAmSN0P9YwTnIb-pXvVmyPB28efVr5vrn5dfm7tvt-vLi7vGcdpODVgpuHAOi9YioC2VErtOAGsdxQ4DQlJgYjohnVAKGUukQACqbRXvDGP0vPpw0B2HmPUymKwxLSYIFrxkrA8ZXTRbPSa_M-mfjsbrh0BMG21S6WoAbQkzwlrZKyIYkQX0HFFLrRDAuaJF6_Py2mx30LkylGSGZ6LPb4L_ozfxXhNJFGJ7gY-LQIp_Z8iT3vnsYBhMgDhnLShthcJ0X_bqkLkxpTIf-lgEXbEOdt7FAL0v8QtCEMOYEVwI7EB4-JEE_WNZGOn92hyno_dro5e1KbT3T1t6JB33hP4HYyPBZw</recordid><startdate>20100226</startdate><enddate>20100226</enddate><creator>Freilich, Shiri</creator><creator>Kreimer, Anat</creator><creator>Borenstein, Elhanan</creator><creator>Gophna, Uri</creator><creator>Sharan, Roded</creator><creator>Ruppin, Eytan</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20100226</creationdate><title>Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species</title><author>Freilich, Shiri ; Kreimer, Anat ; Borenstein, Elhanan ; Gophna, Uri ; Sharan, Roded ; Ruppin, Eytan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c536t-eb8757cc176b0e363881cd7e46c31c1e008712ad78c7990ab2870ee96695da443</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Analysis</topic><topic>Bacteria - genetics</topic><topic>Bacterial genetics</topic><topic>Bacterial Physiological Phenomena</topic><topic>Computational Biology - methods</topic><topic>Computational Biology/Metabolic Networks</topic><topic>Computer Simulation</topic><topic>Environment</topic><topic>Evolution</topic><topic>Evolutionary Biology/Microbial Evolution and Genomics</topic><topic>Genes</topic><topic>Genetic Variation</topic><topic>Metabolic Networks and Pathways</topic><topic>Metabolites</topic><topic>Microbiology</topic><topic>Microbiology/Microbial Evolution and Genomics</topic><topic>Models, Genetic</topic><topic>Mutation</topic><topic>Selection, Genetic</topic><topic>Studies</topic><topic>Systems Biology - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Freilich, Shiri</creatorcontrib><creatorcontrib>Kreimer, Anat</creatorcontrib><creatorcontrib>Borenstein, Elhanan</creatorcontrib><creatorcontrib>Gophna, Uri</creatorcontrib><creatorcontrib>Sharan, Roded</creatorcontrib><creatorcontrib>Ruppin, Eytan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Freilich, Shiri</au><au>Kreimer, Anat</au><au>Borenstein, Elhanan</au><au>Gophna, Uri</au><au>Sharan, Roded</au><au>Ruppin, Eytan</au><au>Sauro, Herbert M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2010-02-26</date><risdate>2010</risdate><volume>6</volume><issue>2</issue><spage>e1000690</spage><epage>e1000690</epage><pages>e1000690-e1000690</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>The evolutionary origins of genetic robustness are still under debate: it may arise as a consequence of requirements imposed by varying environmental conditions, due to intrinsic factors such as metabolic requirements, or directly due to an adaptive selection in favor of genes that allow a species to endure genetic perturbations. Stratifying the individual effects of each origin requires one to study the pertaining evolutionary forces across many species under diverse conditions. Here we conduct the first large-scale computational study charting the level of robustness of metabolic networks of hundreds of bacterial species across many simulated growth environments. We provide evidence that variations among species in their level of robustness reflect ecological adaptations. We decouple metabolic robustness into two components and quantify the extents of each: the first, environmental-dependent, is responsible for at least 20% of the non-essential reactions and its extent is associated with the species' lifestyle (specialized/generalist); the second, environmental-independent, is associated (correlation = approximately 0.6) with the intrinsic metabolic capacities of a species-higher robustness is observed in fast growers or in organisms with an extensive production of secondary metabolites. 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subjects | Analysis Bacteria - genetics Bacterial genetics Bacterial Physiological Phenomena Computational Biology - methods Computational Biology/Metabolic Networks Computer Simulation Environment Evolution Evolutionary Biology/Microbial Evolution and Genomics Genes Genetic Variation Metabolic Networks and Pathways Metabolites Microbiology Microbiology/Microbial Evolution and Genomics Models, Genetic Mutation Selection, Genetic Studies Systems Biology - methods |
title | Decoupling Environment-Dependent and Independent Genetic Robustness across Bacterial Species |
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