Model-based assessment of mammalian cell metabolic functionalities using omics data

Anne Richelle^{1

2}, Benjamin P Kellman^{2

3}, Alexander T Wenzel^{3

4

5}, Austin W T Chiang^{1

2}, Tyler Reagan², Jahir M Gutierrez⁶, Chintan Joshi^{1

2}, Shangzhong Li^{1

6}, Joanne K Liu³, Helen Masson^{1

6}, Jooyong Lee^{1

2}, Zerong Li⁷, Laurent Heirendt⁸, Christophe Trefois⁸, Edwin F Juarez^{4

5}, Tyler Bath⁹, David Borland¹⁰, Jill P Mesirov^{4

5}, Kimberly Robasky^{10

11

12

13}, Nathan E Lewis^{1

2

6}

Affiliations

¹ Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
² Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
³ Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.
⁴ Department of Medicine, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
⁵ Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA.
⁶ Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
⁷ Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093, USA.
⁸ Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
⁹ Department of Biomedical Informatics, UC San Diego Health, University of California, San Diego, La Jolla, CA 92093, USA.
¹⁰ Renaissance Computing Institute, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA.
¹¹ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
¹² School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
¹³ Carolina Health and Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

PMID: 34761247
PMCID: PMC8577426
DOI: 10.1016/j.crmeth.2021.100040

Free PMC article

Model-based assessment of mammalian cell metabolic functionalities using omics data

Anne Richelle et al. Cell Rep Methods. 2021.

Free PMC article

. 2021 Jul 26;1(3):100040.

doi: 10.1016/j.crmeth.2021.100040. Epub 2021 Jun 30.

Authors

Affiliations

¹ Novo Nordisk Foundation Center for Biosustainability at the University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
² Department of Pediatrics, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
³ Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA.
⁴ Department of Medicine, University of California, San Diego, School of Medicine, La Jolla, CA 92093, USA.
⁵ Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA.
⁶ Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.
⁷ Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093, USA.
⁸ Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
⁹ Department of Biomedical Informatics, UC San Diego Health, University of California, San Diego, La Jolla, CA 92093, USA.
¹⁰ Renaissance Computing Institute, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA.
¹¹ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
¹² School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
¹³ Carolina Health and Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

PMID: 34761247
PMCID: PMC8577426
DOI: 10.1016/j.crmeth.2021.100040

Abstract

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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Conflict of interest statement

DECLARATION OF INTERESTS The authors declare no competing interests.

References

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Model-based assessment of mammalian cell metabolic functionalities using omics data

Affiliations

Model-based assessment of mammalian cell metabolic functionalities using omics data

Authors

Affiliations

Abstract

Conflict of interest statement

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources