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Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN

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  • Maria Masid

    (École Polytechnique Fédérale de Lausanne (EPFL))

  • Meric Ataman

    (University of Basel)

  • Vassily Hatzimanikatis

    (École Polytechnique Fédérale de Lausanne (EPFL))

Abstract

Altered metabolism is associated with many human diseases. Human genome-scale metabolic models (GEMs) were reconstructed within systems biology to study the biochemistry occurring in human cells. However, the complexity of these networks hinders a consistent and concise physiological representation. We present here redHUMAN, a workflow for reconstructing reduced models that focus on parts of the metabolism relevant to a specific physiology using the recently established methods redGEM and lumpGEM. The reductions include the thermodynamic properties of compounds and reactions guaranteeing the consistency of predictions with the bioenergetics of the cell. We introduce a method (redGEMX) to incorporate the pathways used by cells to adapt to the medium. We provide the thermodynamic curation of the human GEMs Recon2 and Recon3D and we apply the redHUMAN workflow to derive leukemia-specific reduced models. The reduced models are powerful platforms for studying metabolic differences between phenotypes, such as diseased and healthy cells.

Suggested Citation

  • Maria Masid & Meric Ataman & Vassily Hatzimanikatis, 2020. "Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16549-2
    DOI: 10.1038/s41467-020-16549-2
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    Cited by:

    1. Marco Sciacovelli & Aurelien Dugourd & Lorea Valcarcel Jimenez & Ming Yang & Efterpi Nikitopoulou & Ana S. H. Costa & Laura Tronci & Veronica Caraffini & Paulo Rodrigues & Christina Schmidt & Dylan Ge, 2022. "Dynamic partitioning of branched-chain amino acids-derived nitrogen supports renal cancer progression," Nature Communications, Nature, vol. 13(1), pages 1-20, December.
    2. Marina Maurizio & Maria Masid & Kerry Woods & Reto Caldelari & John G. Doench & Arunasalam Naguleswaran & Denis Joly & Martín González-Fernández & Jonas Zemp & Mélanie Borteele & Vassily Hatzimanikati, 2024. "Host cell CRISPR genomics and modelling reveal shared metabolic vulnerabilities in the intracellular development of Plasmodium falciparum and related hemoparasites," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

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