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A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations
A large proportion of the 6,000 genes present in the genome of Saccharomyces cerevisiae , and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are “silent,” that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are de...
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| Published in: | Nature biotechnology 2001-01, Vol.19 (1), p.45-50 |
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| Main Authors: | , , , , , , , , , , , , |
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| cites | cdi_FETCH-LOGICAL-c560t-221f80b740949bf62b6bcccf67ec96232ffa67d6f7e247d83f351a50d400684d3 |
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| container_title | Nature biotechnology |
| container_volume | 19 |
| creator | Oliver, Stephen G Raamsdonk, Léonie M Teusink, Bas Broadhurst, David Zhang, Nianshu Hayes, Andrew Walsh, Michael C Berden, Jan A Brindle, Kevin M Kell, Douglas B Rowland, Jem J Westerhoff, Hans V van Dam, Karel |
| description | A large proportion of the 6,000 genes present in the genome of
Saccharomyces cerevisiae
, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are “silent,” that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing “metabolic snapshots,” can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY—an abbreviation for functional analysis by co-responses in yeast. |
| doi_str_mv | 10.1038/83496 |
| format | article |
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, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are “silent,” that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing “metabolic snapshots,” can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY—an abbreviation for functional analysis by co-responses in yeast.</description><identifier>ISSN: 1087-0156</identifier><identifier>EISSN: 1546-1696</identifier><identifier>DOI: 10.1038/83496</identifier><identifier>PMID: 11135551</identifier><identifier>CODEN: NABIF9</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>Adenine Nucleotides - metabolism ; Agriculture ; Bioinformatics ; Biological and medical sciences ; Biomedical and Life Sciences ; Biomedical Engineering/Biotechnology ; Biomedicine ; Biotechnology ; Cluster Analysis ; Energy Metabolism - genetics ; Fundamental and applied biological sciences. Psychology ; Genome, Fungal ; Genomics ; Genomics - methods ; Genotype ; Growth, nutrition, metabolism, transports, enzymes. Molecular biology ; Hexosephosphates - metabolism ; Life Sciences ; Metabolites ; Microbiology ; Mutation ; Mycology ; Phenotype ; Proteins ; Pyruvates - metabolism ; Saccharomyces cerevisiae ; Saccharomyces cerevisiae - genetics ; Saccharomyces cerevisiae - growth & development ; Saccharomyces cerevisiae - metabolism ; Yeast ; Yeasts</subject><ispartof>Nature biotechnology, 2001-01, Vol.19 (1), p.45-50</ispartof><rights>Nature America Inc. 2001</rights><rights>2001 INIST-CNRS</rights><rights>COPYRIGHT 2001 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Jan 2001</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c560t-221f80b740949bf62b6bcccf67ec96232ffa67d6f7e247d83f351a50d400684d3</citedby><cites>FETCH-LOGICAL-c560t-221f80b740949bf62b6bcccf67ec96232ffa67d6f7e247d83f351a50d400684d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,2727,4024,27923,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=955898$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/11135551$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Oliver, Stephen G</creatorcontrib><creatorcontrib>Raamsdonk, Léonie M</creatorcontrib><creatorcontrib>Teusink, Bas</creatorcontrib><creatorcontrib>Broadhurst, David</creatorcontrib><creatorcontrib>Zhang, Nianshu</creatorcontrib><creatorcontrib>Hayes, Andrew</creatorcontrib><creatorcontrib>Walsh, Michael C</creatorcontrib><creatorcontrib>Berden, Jan A</creatorcontrib><creatorcontrib>Brindle, Kevin M</creatorcontrib><creatorcontrib>Kell, Douglas B</creatorcontrib><creatorcontrib>Rowland, Jem J</creatorcontrib><creatorcontrib>Westerhoff, Hans V</creatorcontrib><creatorcontrib>van Dam, Karel</creatorcontrib><title>A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations</title><title>Nature biotechnology</title><addtitle>Nat Biotechnol</addtitle><addtitle>Nat Biotechnol</addtitle><description>A large proportion of the 6,000 genes present in the genome of
Saccharomyces cerevisiae
, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are “silent,” that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing “metabolic snapshots,” can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY—an abbreviation for functional analysis by co-responses in yeast.</description><subject>Adenine Nucleotides - metabolism</subject><subject>Agriculture</subject><subject>Bioinformatics</subject><subject>Biological and medical sciences</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedical Engineering/Biotechnology</subject><subject>Biomedicine</subject><subject>Biotechnology</subject><subject>Cluster Analysis</subject><subject>Energy Metabolism - genetics</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Genome, Fungal</subject><subject>Genomics</subject><subject>Genomics - methods</subject><subject>Genotype</subject><subject>Growth, nutrition, metabolism, transports, enzymes. Molecular biology</subject><subject>Hexosephosphates - metabolism</subject><subject>Life Sciences</subject><subject>Metabolites</subject><subject>Microbiology</subject><subject>Mutation</subject><subject>Mycology</subject><subject>Phenotype</subject><subject>Proteins</subject><subject>Pyruvates - metabolism</subject><subject>Saccharomyces cerevisiae</subject><subject>Saccharomyces cerevisiae - genetics</subject><subject>Saccharomyces cerevisiae - growth & development</subject><subject>Saccharomyces cerevisiae - metabolism</subject><subject>Yeast</subject><subject>Yeasts</subject><issn>1087-0156</issn><issn>1546-1696</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><recordid>eNqNkk9r3DAQxU1padI0X6GIlgZ6cCpZliwfl9C0gUCg_65ClkdeB1vaauTQ_fZVukuW5NJKBwn0e2-YpymKU0bPGeXqo-J1K58Vx0zUsmSylc_znaqmpEzIo-IV4i2lVNZSviyOGGNcCMGOi35F3OJtGoM3ExnAh3m0SDBFk2DYkrQ2iSwISGZIpgtTmIH0JhmSAolwB1mV1kA26yxN2w2Q4AiOE_hE5iWZe2N8XbxwZkI43Z8nxY_LT98vvpTXN5-vLlbXpRWSprKqmFO0a2ra1m3nZNXJzlrrZAO2lRWvnDOy6aVroKqbXnHHBTOC9nVuTNU9PynOdr6bGH4tgEnPI1qYJuMhLKgbKmRLOfsnyBrFBK2aDL59At6GJeaoUFd5ScVbnqHzHTSYCfToXcjp2bx7yGEGDy7noVeszR_QCkGz4MMjQWYS_E6DWRD11bev_8_e_HzMvt-xNgbECE5v4jibuNWM6vsp0X-nJHNv9l0t3Qz9gdqPRQbe7QGD1kwuGm9HfOByMdWqQ4qYH_wA8RDO03pkB3qTlggPPr5LlFGma8H_ABcR19A</recordid><startdate>200101</startdate><enddate>200101</enddate><creator>Oliver, Stephen G</creator><creator>Raamsdonk, Léonie M</creator><creator>Teusink, Bas</creator><creator>Broadhurst, David</creator><creator>Zhang, Nianshu</creator><creator>Hayes, Andrew</creator><creator>Walsh, Michael C</creator><creator>Berden, Jan A</creator><creator>Brindle, Kevin M</creator><creator>Kell, Douglas B</creator><creator>Rowland, Jem J</creator><creator>Westerhoff, Hans V</creator><creator>van Dam, Karel</creator><general>Nature Publishing Group US</general><general>Nature</general><general>Nature Publishing Group</general><scope>IQODW</scope><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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7QR</scope><scope>7T7</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</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>L6V</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M2P</scope><scope>M7P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>200101</creationdate><title>A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations</title><author>Oliver, Stephen G ; Raamsdonk, Léonie M ; Teusink, Bas ; Broadhurst, David ; Zhang, Nianshu ; Hayes, Andrew ; Walsh, Michael C ; Berden, Jan A ; Brindle, Kevin M ; Kell, Douglas B ; Rowland, Jem J ; Westerhoff, Hans V ; van Dam, Karel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c560t-221f80b740949bf62b6bcccf67ec96232ffa67d6f7e247d83f351a50d400684d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Adenine Nucleotides - metabolism</topic><topic>Agriculture</topic><topic>Bioinformatics</topic><topic>Biological and medical sciences</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedical Engineering/Biotechnology</topic><topic>Biomedicine</topic><topic>Biotechnology</topic><topic>Cluster Analysis</topic><topic>Energy Metabolism - genetics</topic><topic>Fundamental and applied biological sciences. 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Saccharomyces cerevisiae
, and of those sequenced in other organisms, encode proteins of unknown function. Many of these genes are “silent,” that is, they show no overt phenotype, in terms of growth rate or other fluxes, when they are deleted from the genome. We demonstrate how the intracellular concentrations of metabolites can reveal phenotypes for proteins active in metabolic regulation. Quantification of the change of several metabolite concentrations relative to the concentration change of one selected metabolite can reveal the site of action, in the metabolic network, of a silent gene. In the same way, comprehensive analyses of metabolite concentrations in mutants, providing “metabolic snapshots,” can reveal functions when snapshots from strains deleted for unstudied genes are compared to those deleted for known genes. This approach to functional analysis, using comparative metabolomics, we call FANCY—an abbreviation for functional analysis by co-responses in yeast.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>11135551</pmid><doi>10.1038/83496</doi><tpages>6</tpages></addata></record> |
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| identifier | ISSN: 1087-0156 |
| ispartof | Nature biotechnology, 2001-01, Vol.19 (1), p.45-50 |
| issn | 1087-0156 1546-1696 |
| language | eng |
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| source | Nature Journals Online |
| subjects | Adenine Nucleotides - metabolism Agriculture Bioinformatics Biological and medical sciences Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Biotechnology Cluster Analysis Energy Metabolism - genetics Fundamental and applied biological sciences. Psychology Genome, Fungal Genomics Genomics - methods Genotype Growth, nutrition, metabolism, transports, enzymes. Molecular biology Hexosephosphates - metabolism Life Sciences Metabolites Microbiology Mutation Mycology Phenotype Proteins Pyruvates - metabolism Saccharomyces cerevisiae Saccharomyces cerevisiae - genetics Saccharomyces cerevisiae - growth & development Saccharomyces cerevisiae - metabolism Yeast Yeasts |
| title | A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations |
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