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Model-based assessment of mammalian cell metabolic functionalities using omics data.
Richelle, Anne; Kellman, Benjamin P; Wenzel, Alexander T; Chiang, Austin W T; Reagan, Tyler; Gutierrez, Jahir M; Joshi, Chintan; Li, Shangzhong; Liu, Joanne K; Masson, Helen; Lee, Jooyong; Li, Zerong; Heirendt, Laurent; Trefois, Christophe; Juarez, Edwin F; Bath, Tyler; Borland, David; Mesirov, Jill P; Robasky, Kimberly; Lewis, Nathan E.
Afiliación
  • Richelle A; Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Kellman BP; Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Wenzel AT; Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Chiang AWT; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.
  • Reagan T; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.
  • Gutierrez JM; Department of Medicine, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Joshi C; Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA.
  • Li S; Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Liu JK; Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Masson H; Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Lee J; Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
  • Li Z; Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Heirendt L; Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Trefois C; Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Juarez EF; Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
  • Bath T; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.
  • Borland D; Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Mesirov JP; Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
  • Robasky K; Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
  • Lewis NE; Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
Cell Rep Methods ; 1(3)2021 07 26.
Article en En | MEDLINE | ID: mdl-34761247
Omics experiments are ubiquitous in biological studies, leading to a deluge of data. However, it is still challenging to connect changes in these data to changes in cell functions because of complex interdependencies between genes, proteins, and metabolites. Here, we present a framework allowing researchers to infer how metabolic functions change on the basis of omics data. To enable this, we curated and standardized lists of metabolic tasks that mammalian cells can accomplish. Genome-scale metabolic networks were used to define gene sets associated with each metabolic task. We further developed a framework to overlay omics data on these sets and predict pathway usage for each metabolic task. We demonstrated how this approach can be used to quantify metabolic functions of diverse biological samples from the single cell to whole tissues and organs by using multiple transcriptomic datasets. To facilitate its adoption, we integrated the approach into GenePattern (www.genepattern.org-CellFie).
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genoma / Redes y Vías Metabólicas Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Cell Rep Methods Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genoma / Redes y Vías Metabólicas Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Cell Rep Methods Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos