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Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease

Author

Listed:
  • Adil Mardinoglu

    (Chalmers University of Technology, Kamivangen 10, Gothenburg SE-412 96, Sweden)

  • Rasmus Agren

    (Chalmers University of Technology, Kamivangen 10, Gothenburg SE-412 96, Sweden)

  • Caroline Kampf

    (Genetics and Pathology, Science for Life Laboratory, Uppsala University)

  • Anna Asplund

    (Genetics and Pathology, Science for Life Laboratory, Uppsala University)

  • Mathias Uhlen

    (KTH—Royal Institute of Technology
    Science for Life Laboratory, KTH—Royal Institute of Technology)

  • Jens Nielsen

    (Chalmers University of Technology, Kamivangen 10, Gothenburg SE-412 96, Sweden
    Science for Life Laboratory, KTH—Royal Institute of Technology)

Abstract

Several liver disorders result from perturbations in the metabolism of hepatocytes, and their underlying mechanisms can be outlined through the use of genome-scale metabolic models (GEMs). Here we reconstruct a consensus GEM for hepatocytes, which we call iHepatocytes2322, that extends previous models by including an extensive description of lipid metabolism. We build iHepatocytes2322 using Human Metabolic Reaction 2.0 database and proteomics data in Human Protein Atlas, which experimentally validates the incorporated reactions. The reconstruction process enables improved annotation of the proteomics data using the network centric view of iHepatocytes2322. We then use iHepatocytes2322 to analyse transcriptomics data obtained from patients with non-alcoholic fatty liver disease. We show that blood concentrations of chondroitin and heparan sulphates are suitable for diagnosing non-alcoholic steatohepatitis and for the staging of non-alcoholic fatty liver disease. Furthermore, we observe serine deficiency in patients with NASH and identify PSPH, SHMT1 and BCAT1 as potential therapeutic targets for the treatment of non-alcoholic steatohepatitis.

Suggested Citation

  • Adil Mardinoglu & Rasmus Agren & Caroline Kampf & Anna Asplund & Mathias Uhlen & Jens Nielsen, 2014. "Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease," Nature Communications, Nature, vol. 5(1), pages 1-11, May.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4083
    DOI: 10.1038/ncomms4083
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    Cited by:

    1. Oveis Jamialahmadi & Sameereh Hashemi-Najafabadi & Ehsan Motamedian & Stefano Romeo & Fatemeh Bagheri, 2019. "A benchmark-driven approach to reconstruct metabolic networks for studying cancer metabolism," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-29, April.
    2. André Schultz & Amina A Qutub, 2016. "Reconstruction of Tissue-Specific Metabolic Networks Using CORDA," PLOS Computational Biology, Public Library of Science, vol. 12(3), pages 1-33, March.
    3. Chaitra Sarathy & Marian Breuer & Martina Kutmon & Michiel E Adriaens & Chris T Evelo & Ilja C W Arts, 2021. "Comparison of metabolic states using genome-scale metabolic models," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-25, November.
    4. 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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