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Genome-scale models in human metabologenomics

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From Nature Reviews Genetics

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Abstract

Metabologenomics integrates metabolomics with other omics data types to comprehensively study the genetic and environmental factors that influence metabolism. These multi-omics data can be incorporated into genome-scale metabolic models (GEMs), which are highly curated knowledge bases that explicitly account for genes, transcripts, proteins and metabolites. By including all known biochemical reactions catalysed by enzymes and transporters encoded in the human genome, GEMs analyse and predict the behaviour of complex metabolic networks. Continued advancements to the scale and scope of GEMs — from cells and tissues to microbiomes and the whole body — have helped to design effective treatments and develop better diagnostic tools for metabolic diseases. Furthermore, increasing amounts of multi-omics data are incorporated into GEMs to better identify the underlying mechanisms, biomarkers and potential drug targets of metabolic diseases.

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Fig. 1: Reconstructing global human and cell- and tissue-specific GEMs.
Fig. 2: Whole-body metabolic modelling accounting for the host and microbiome interactions.
Fig. 3: Interpretation of multi-omics data using systems biology and AI.
Fig. 4: Multi-omics data throughout life.

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Acknowledgements

A.M. thanks the Knut and Alice Wallenberg Foundation. The authors also thank the Systems Medicine group members for reading and providing comments.

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Authors and Affiliations

  1. Science for Life Laboratory, KTH — Royal Institute of Technology, Stockholm, Sweden

    Adil Mardinoglu

  2. Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral and Craniofacial Sciences, King’s College London, London, UK

    Adil Mardinoglu

  3. Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA

    Bernhard Ø. Palsson

  4. Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA

    Bernhard Ø. Palsson

  5. Department of Paediatrics, University of California, San Diego, La Jolla, CA, USA

    Bernhard Ø. Palsson

  6. Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA

    Bernhard Ø. Palsson

  7. Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark

    Bernhard Ø. Palsson

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Both authors contributed equally to all aspects of the article.

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Correspondence to Adil Mardinoglu or Bernhard Ø. Palsson.

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A.M. is the co-founder of SZA Longevity, BASH Biotech, Trustlife Therapeutics, ScandiBio Therapeutics and ScandiEdge Therapeutics, and B.Ø.P. is the co-founder of Sinopia Biosciences and Conarium Bioworks.

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iNetModels Interactive Database: https://inetmodels.com

KEGG: https://www.genome.jp/kegg/pathway.html

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Mardinoglu, A., Palsson, B.Ø. Genome-scale models in human metabologenomics. Nat Rev Genet (2024). https://doi.org/10.1038/s41576-024-00768-0

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