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

Anne Richelle; Benjamin P Kellman; Alexander T Wenzel; Austin W T Chiang; Tyler Reagan; Jahir M Gutierrez; Chintan Joshi; Shangzhong Li; Joanne K Liu; Helen Masson; Jooyong Lee; Zerong Li; Laurent Heirendt; Christophe Trefois; Edwin F Juarez; Tyler Bath; David Borland; Jill P Mesirov; Kimberly Robasky; Nathan E Lewis

doi:10.1016/j.crmeth.2021.100040

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

Cell Rep Methods. 2021 Jul 26;1(3):100040. doi: 10.1016/j.crmeth.2021.100040. Epub 2021 Jun 30.

Authors

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.

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).

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Animals
Cell Physiological Phenomena
Gene Expression Profiling
Genome*
Mammals / genetics
Metabolic Networks and Pathways* / genetics
Transcriptome / genetics

Abstract

Publication types

MeSH terms

Grants and funding