Towards high resolution analysis of metabolic flux in cells and tissues
•The metabolic state of a cell is an important determinant of cellular phenotype.•Current methods for global metabolic flux quantification characterize bulk behavior.•Genome-scale models offer promise for analyses involving multiple cell types.•Advances in metabolic imaging could afford spatiotempor...
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Veröffentlicht in: | Current opinion in biotechnology 2013-10, Vol.24 (5), p.933-939 |
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description | •The metabolic state of a cell is an important determinant of cellular phenotype.•Current methods for global metabolic flux quantification characterize bulk behavior.•Genome-scale models offer promise for analyses involving multiple cell types.•Advances in metabolic imaging could afford spatiotemporally resolved analysis.
Metabolism extracts chemical energy from nutrients, uses this energy to form building blocks for biosynthesis, and interconverts between various small molecules that coordinate the activities of cellular pathways. The metabolic state of a cell is increasingly recognized to determine the phenotype of not only metabolically active cell types such as liver, muscle, and adipose, but also other specialized cell types such as neurons and immune cells. This review focuses on methods to quantify intracellular reaction flux as a measure of cellular metabolic activity, with emphasis on studies involving cells of mammalian tissue. Two key areas are highlighted for future development, single cell metabolomics and noninvasive imaging, which could enable spatiotemporally resolved analysis and thereby overcome issues of heterogeneity, a distinctive feature of tissue metabolism |
doi_str_mv | 10.1016/j.copbio.2013.07.001 |
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Metabolism extracts chemical energy from nutrients, uses this energy to form building blocks for biosynthesis, and interconverts between various small molecules that coordinate the activities of cellular pathways. The metabolic state of a cell is increasingly recognized to determine the phenotype of not only metabolically active cell types such as liver, muscle, and adipose, but also other specialized cell types such as neurons and immune cells. This review focuses on methods to quantify intracellular reaction flux as a measure of cellular metabolic activity, with emphasis on studies involving cells of mammalian tissue. Two key areas are highlighted for future development, single cell metabolomics and noninvasive imaging, which could enable spatiotemporally resolved analysis and thereby overcome issues of heterogeneity, a distinctive feature of tissue metabolism</description><identifier>ISSN: 0958-1669</identifier><identifier>EISSN: 1879-0429</identifier><identifier>DOI: 10.1016/j.copbio.2013.07.001</identifier><identifier>PMID: 23906926</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Animals ; biosynthesis ; Cells - metabolism ; energy ; Genomics ; Humans ; image analysis ; Internal Medicine ; liver ; mammals ; Mammals - metabolism ; Metabolism ; Metabolomics ; Molecular Imaging ; muscles ; neurons ; nutrients ; Organ Specificity ; phenotype ; Single-Cell Analysis ; Spatio-Temporal Analysis ; tissues</subject><ispartof>Current opinion in biotechnology, 2013-10, Vol.24 (5), p.933-939</ispartof><rights>Elsevier Ltd</rights><rights>2013 Elsevier Ltd</rights><rights>Copyright © 2013 Elsevier Ltd. All rights reserved.</rights><rights>2013 Elsevier Ltd. All rights reserved. 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c674t-5b8b5e0528359b4f55fd8df9828698e0448503d70092d32e90734c41f68978853</citedby><cites>FETCH-LOGICAL-c674t-5b8b5e0528359b4f55fd8df9828698e0448503d70092d32e90734c41f68978853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0958166913006071$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23906926$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sims, James K</creatorcontrib><creatorcontrib>Manteiga, Sara</creatorcontrib><creatorcontrib>Lee, Kyongbum</creatorcontrib><title>Towards high resolution analysis of metabolic flux in cells and tissues</title><title>Current opinion in biotechnology</title><addtitle>Curr Opin Biotechnol</addtitle><description>•The metabolic state of a cell is an important determinant of cellular phenotype.•Current methods for global metabolic flux quantification characterize bulk behavior.•Genome-scale models offer promise for analyses involving multiple cell types.•Advances in metabolic imaging could afford spatiotemporally resolved analysis.
Metabolism extracts chemical energy from nutrients, uses this energy to form building blocks for biosynthesis, and interconverts between various small molecules that coordinate the activities of cellular pathways. The metabolic state of a cell is increasingly recognized to determine the phenotype of not only metabolically active cell types such as liver, muscle, and adipose, but also other specialized cell types such as neurons and immune cells. This review focuses on methods to quantify intracellular reaction flux as a measure of cellular metabolic activity, with emphasis on studies involving cells of mammalian tissue. Two key areas are highlighted for future development, single cell metabolomics and noninvasive imaging, which could enable spatiotemporally resolved analysis and thereby overcome issues of heterogeneity, a distinctive feature of tissue metabolism</description><subject>Animals</subject><subject>biosynthesis</subject><subject>Cells - metabolism</subject><subject>energy</subject><subject>Genomics</subject><subject>Humans</subject><subject>image analysis</subject><subject>Internal Medicine</subject><subject>liver</subject><subject>mammals</subject><subject>Mammals - metabolism</subject><subject>Metabolism</subject><subject>Metabolomics</subject><subject>Molecular Imaging</subject><subject>muscles</subject><subject>neurons</subject><subject>nutrients</subject><subject>Organ Specificity</subject><subject>phenotype</subject><subject>Single-Cell Analysis</subject><subject>Spatio-Temporal Analysis</subject><subject>tissues</subject><issn>0958-1669</issn><issn>1879-0429</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkk9vEzEQxVcIREPhGyDYI5cs4__2BQlV0CJV4tD2bHm93sTBWQd7tyXfHm8TKuCSkw_-zZt586aq3iJoECD-cdPYuGt9bDAg0oBoANCzaoGkUEugWD2vFqCYXCLO1Vn1KucNADAi4GV1hokCrjBfVJe38cGkLtdrv1rXyeUYptHHoTaDCfvscx37eutG08bgbd2H6Vfth9q6EHJhunr0OU8uv65e9CZk9-b4nld3X7_cXlwtr79ffrv4fL20XNBxyVrZMgcMS8JUS3vG-k52vZJYciUdUCoZkE4AKNwR7BQIQi1FPZdKSMnIefXpoLub2q3rrBvGZILeJb81aa-j8frfn8Gv9SreayJKSzYLfDgKpPizDD7qrc-zHTO4OGWNy5agdKL8JIoYB4Qwp-Q0SglnvKSiCkoPqE0x5-T6p-ER6DlZvdGHZPWcrAahS7Kl7N3fxp-K_kRZgPcHoDdRm1XyWd_dFAVe_GAmH4nj7lwJ6N67pLP1brCu88nZUXfRn5rhfwEb_OCtCT_c3uVNnFK5muJWZ6xB38z3N58fIgAcBCK_ATeL0xg</recordid><startdate>20131001</startdate><enddate>20131001</enddate><creator>Sims, James K</creator><creator>Manteiga, Sara</creator><creator>Lee, Kyongbum</creator><general>Elsevier Ltd</general><scope>FBQ</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>7X8</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope></search><sort><creationdate>20131001</creationdate><title>Towards high resolution analysis of metabolic flux in cells and tissues</title><author>Sims, James K ; Manteiga, Sara ; Lee, Kyongbum</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c674t-5b8b5e0528359b4f55fd8df9828698e0448503d70092d32e90734c41f68978853</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Animals</topic><topic>biosynthesis</topic><topic>Cells - metabolism</topic><topic>energy</topic><topic>Genomics</topic><topic>Humans</topic><topic>image analysis</topic><topic>Internal Medicine</topic><topic>liver</topic><topic>mammals</topic><topic>Mammals - metabolism</topic><topic>Metabolism</topic><topic>Metabolomics</topic><topic>Molecular Imaging</topic><topic>muscles</topic><topic>neurons</topic><topic>nutrients</topic><topic>Organ Specificity</topic><topic>phenotype</topic><topic>Single-Cell Analysis</topic><topic>Spatio-Temporal Analysis</topic><topic>tissues</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sims, James K</creatorcontrib><creatorcontrib>Manteiga, Sara</creatorcontrib><creatorcontrib>Lee, Kyongbum</creatorcontrib><collection>AGRIS</collection><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>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Current opinion in biotechnology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sims, James K</au><au>Manteiga, Sara</au><au>Lee, Kyongbum</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Towards high resolution analysis of metabolic flux in cells and tissues</atitle><jtitle>Current opinion in biotechnology</jtitle><addtitle>Curr Opin Biotechnol</addtitle><date>2013-10-01</date><risdate>2013</risdate><volume>24</volume><issue>5</issue><spage>933</spage><epage>939</epage><pages>933-939</pages><issn>0958-1669</issn><eissn>1879-0429</eissn><abstract>•The metabolic state of a cell is an important determinant of cellular phenotype.•Current methods for global metabolic flux quantification characterize bulk behavior.•Genome-scale models offer promise for analyses involving multiple cell types.•Advances in metabolic imaging could afford spatiotemporally resolved analysis.
Metabolism extracts chemical energy from nutrients, uses this energy to form building blocks for biosynthesis, and interconverts between various small molecules that coordinate the activities of cellular pathways. The metabolic state of a cell is increasingly recognized to determine the phenotype of not only metabolically active cell types such as liver, muscle, and adipose, but also other specialized cell types such as neurons and immune cells. This review focuses on methods to quantify intracellular reaction flux as a measure of cellular metabolic activity, with emphasis on studies involving cells of mammalian tissue. Two key areas are highlighted for future development, single cell metabolomics and noninvasive imaging, which could enable spatiotemporally resolved analysis and thereby overcome issues of heterogeneity, a distinctive feature of tissue metabolism</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>23906926</pmid><doi>10.1016/j.copbio.2013.07.001</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animals biosynthesis Cells - metabolism energy Genomics Humans image analysis Internal Medicine liver mammals Mammals - metabolism Metabolism Metabolomics Molecular Imaging muscles neurons nutrients Organ Specificity phenotype Single-Cell Analysis Spatio-Temporal Analysis tissues |
title | Towards high resolution analysis of metabolic flux in cells and tissues |
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