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Reactome Array: Forging a Link Between Metabolome and Genome.

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Title: Reactome Array: Forging a Link Between Metabolome and Genome.
Authors: Beloqui, Ana, Guazzaroni, María-Eugenia, Pazos, Florencio, Vieites, José M., Godoy, Marta, Golyshina, Olga V., Chernikova, Tatyana N., Waliczek, Agnes, Silva-Rocha, Rafael, AL-ramahi, Yamal, La Cono, Violetta, Mendez, Carmen, Salas, José A., Solano, Roberto, Yakimov, Michail M., Timmis, Kenneth N., Golyshin, Peter N., Ferrer, Manuel
Source: Science (pre-March 2025). 10/9/2009, Vol. 326 Issue 5950, p252-257. 6p.
Subjects: Genetic research, Cell metabolism, Genomics, Gene libraries, Microbial metabolites, Enzymes
Abstract: We describe a sensitive metabolite array for genome sequence-independent functional analysis of metabolic phenotypes and networks, the reactomes, of cell populations and communities. The array includes 1676 dye-linked substrate compounds collectively representing central metabolic pathways of all forms of life. Application of cell extracts to the array leads to specific binding of enzymes to cognate substrates, transformation to products, and concomitant activation of the dye signals. Proof of principle was shown by reconstruction of the metabolic maps of model bacteria. Utility of the array for unsequenced organisms was demonstrated by reconstruction of the global metabolisms of three microbial communities derived from acidic volcanic pool, deep-sea brine lake, and hydrocarbon-polluted seawater. Enzymes of interest are captured on nanoparticles coated with cognate metabolites, sequenced, and their functions unequivocally established. [ABSTRACT FROM AUTHOR]
Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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PubType: Academic Journal
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  Data: Reactome Array: Forging a Link Between Metabolome and Genome.
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  Data: <searchLink fieldCode="AR" term="%22Beloqui%2C+Ana%22">Beloqui, Ana</searchLink><br /><searchLink fieldCode="AR" term="%22Guazzaroni%2C+María-Eugenia%22">Guazzaroni, María-Eugenia</searchLink><br /><searchLink fieldCode="AR" term="%22Pazos%2C+Florencio%22">Pazos, Florencio</searchLink><br /><searchLink fieldCode="AR" term="%22Vieites%2C+José+M%2E%22">Vieites, José M.</searchLink><br /><searchLink fieldCode="AR" term="%22Godoy%2C+Marta%22">Godoy, Marta</searchLink><br /><searchLink fieldCode="AR" term="%22Golyshina%2C+Olga+V%2E%22">Golyshina, Olga V.</searchLink><br /><searchLink fieldCode="AR" term="%22Chernikova%2C+Tatyana+N%2E%22">Chernikova, Tatyana N.</searchLink><br /><searchLink fieldCode="AR" term="%22Waliczek%2C+Agnes%22">Waliczek, Agnes</searchLink><br /><searchLink fieldCode="AR" term="%22Silva-Rocha%2C+Rafael%22">Silva-Rocha, Rafael</searchLink><br /><searchLink fieldCode="AR" term="%22AL-ramahi%2C+Yamal%22">AL-ramahi, Yamal</searchLink><br /><searchLink fieldCode="AR" term="%22La+Cono%2C+Violetta%22">La Cono, Violetta</searchLink><br /><searchLink fieldCode="AR" term="%22Mendez%2C+Carmen%22">Mendez, Carmen</searchLink><br /><searchLink fieldCode="AR" term="%22Salas%2C+José+A%2E%22">Salas, José A.</searchLink><br /><searchLink fieldCode="AR" term="%22Solano%2C+Roberto%22">Solano, Roberto</searchLink><br /><searchLink fieldCode="AR" term="%22Yakimov%2C+Michail+M%2E%22">Yakimov, Michail M.</searchLink><br /><searchLink fieldCode="AR" term="%22Timmis%2C+Kenneth+N%2E%22">Timmis, Kenneth N.</searchLink><br /><searchLink fieldCode="AR" term="%22Golyshin%2C+Peter+N%2E%22">Golyshin, Peter N.</searchLink><br /><searchLink fieldCode="AR" term="%22Ferrer%2C+Manuel%22">Ferrer, Manuel</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Science+%28pre-March+2025%29%22">Science (pre-March 2025)</searchLink>. 10/9/2009, Vol. 326 Issue 5950, p252-257. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Genetic+research%22">Genetic research</searchLink><br /><searchLink fieldCode="DE" term="%22Cell+metabolism%22">Cell metabolism</searchLink><br /><searchLink fieldCode="DE" term="%22Genomics%22">Genomics</searchLink><br /><searchLink fieldCode="DE" term="%22Gene+libraries%22">Gene libraries</searchLink><br /><searchLink fieldCode="DE" term="%22Microbial+metabolites%22">Microbial metabolites</searchLink><br /><searchLink fieldCode="DE" term="%22Enzymes%22">Enzymes</searchLink>
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  Data: We describe a sensitive metabolite array for genome sequence-independent functional analysis of metabolic phenotypes and networks, the reactomes, of cell populations and communities. The array includes 1676 dye-linked substrate compounds collectively representing central metabolic pathways of all forms of life. Application of cell extracts to the array leads to specific binding of enzymes to cognate substrates, transformation to products, and concomitant activation of the dye signals. Proof of principle was shown by reconstruction of the metabolic maps of model bacteria. Utility of the array for unsequenced organisms was demonstrated by reconstruction of the global metabolisms of three microbial communities derived from acidic volcanic pool, deep-sea brine lake, and hydrocarbon-polluted seawater. Enzymes of interest are captured on nanoparticles coated with cognate metabolites, sequenced, and their functions unequivocally established. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Cell metabolism
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      – SubjectFull: Genomics
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      – SubjectFull: Gene libraries
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