Development, calibration, and validation of a novel human ventricular myocyte model in health, disease, and drug block

  1. Jakub Tomek  Is a corresponding author
  2. Alfonso Bueno-Orovio
  3. Elisa Passini
  4. Xin Zhou
  5. Ana Minchole
  6. Oliver Britton
  7. Chiara Bartolucci
  8. Stefano Severi
  9. Alvin Shrier
  10. Laszlo Virag
  11. Andras Varro
  12. Blanca Rodriguez  Is a corresponding author
  1. University of Oxford, United Kingdom
  2. University of Bologna, Italy
  3. McGill University, Canada
  4. University of Szeged, Hungary

Abstract

Human-based modelling and simulations are becoming ubiquitous in biomedical science due to their ability to augment experimental and clinical investigations. Cardiac electrophysiology is one of the most advanced areas, with cardiac modelling and simulation being considered for virtual testing of pharmacological therapies and medical devices. Current models present inconsistencies with experimental data, which limit further progress. In this study, we present the design, development, calibration and independent validation of a human-based ventricular model (ToR-ORd) for simulations of electrophysiology and excitation-contraction coupling, from ionic to whole-organ dynamics, including the electrocardiogram. Validation based on substantial multiscale simulations supports the credibility of the ToR-ORd model under healthy and key disease conditions, as well as drug blockade. In addition, the process uncovers new theoretical insights into the biophysical properties of the L-type calcium current, which are critical for sodium and calcium dynamics. These insights enable the reformulation of L-type calcium current, as well as replacement of the hERG current model.

Data availability

No new experimental data were created. However, codes for simulations are available at https://github.com/jtmff/torord.

Article and author information

Author details

  1. Jakub Tomek

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    For correspondence
    jakub.tomek.mff@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0157-4386
  2. Alfonso Bueno-Orovio

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Elisa Passini

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Xin Zhou

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Ana Minchole

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Oliver Britton

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Chiara Bartolucci

    Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi', University of Bologna, Bologna, Italy
    Competing interests
    The authors declare that no competing interests exist.
  8. Stefano Severi

    Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi', University of Bologna, Bologna, Italy
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4306-8294
  9. Alvin Shrier

    Department of Physiology, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  10. Laszlo Virag

    Department of Pharmacology and Pharmacotherapy, University of Szeged, Szeged, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  11. Andras Varro

    Department of Pharmacology and Pharmacotherapy, University of Szeged, Szeged, Hungary
    Competing interests
    The authors declare that no competing interests exist.
  12. Blanca Rodriguez

    Department of Computer Science, University of Oxford, Oxford, United Kingdom
    For correspondence
    Blanca.Rodriguez@cs.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.

Funding

Wellcome (100246/Z/12/Z)

  • Blanca Rodriguez

Amazon Web Services (Machine learning research award)

  • Blanca Rodriguez

Wellcome (214290/Z/18/Z)

  • Blanca Rodriguez

British Heart Foundation (FS/17/22/32644)

  • Alfonso Bueno-Orovio

European Commission (675451)

  • Blanca Rodriguez

National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/P001076/1)

  • Blanca Rodriguez

TransQST (116030)

  • Blanca Rodriguez

BHF Centre of Research Excellence, Oxford (RE/13/1/30181)

  • Blanca Rodriguez

UK National Supercomputing (Archer RAP award (322 00180))

  • Blanca Rodriguez

UK National Supercomputing (PRACE (2017174226))

  • Blanca Rodriguez

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. José D Faraldo-Gómez, National Heart, Lung and Blood Institute, National Institutes of Health, United States

Publication history

  1. Received: May 29, 2019
  2. Accepted: December 18, 2019
  3. Accepted Manuscript published: December 23, 2019 (version 1)
  4. Accepted Manuscript updated: December 24, 2019 (version 2)
  5. Version of Record published: January 20, 2020 (version 3)
  6. Version of Record updated: May 13, 2020 (version 4)

Copyright

© 2019, Tomek et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 4,080
    Page views
  • 521
    Downloads
  • 53
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Jakub Tomek
  2. Alfonso Bueno-Orovio
  3. Elisa Passini
  4. Xin Zhou
  5. Ana Minchole
  6. Oliver Britton
  7. Chiara Bartolucci
  8. Stefano Severi
  9. Alvin Shrier
  10. Laszlo Virag
  11. Andras Varro
  12. Blanca Rodriguez
(2019)
Development, calibration, and validation of a novel human ventricular myocyte model in health, disease, and drug block
eLife 8:e48890.
https://doi.org/10.7554/eLife.48890

Further reading

    1. Cell Biology
    Saskia-Larissa Jauch-Speer et al.
    Research Article Updated

    The proinflammatory alarmins S100A8 and S100A9 are among the most abundant proteins in neutrophils and monocytes but are completely silenced after differentiation to macrophages. The molecular mechanisms of the extraordinarily dynamic transcriptional regulation of S100a8 and S100a9 genes, however, are only barely understood. Using an unbiased genome-wide CRISPR/Cas9 knockout (KO)-based screening approach in immortalized murine monocytes, we identified the transcription factor C/EBPδ as a central regulator of S100a8 and S100a9 expression. We showed that S100A8/A9 expression and thereby neutrophil recruitment and cytokine release were decreased in C/EBPδ KO mice in a mouse model of acute lung inflammation. S100a8 and S100a9 expression was further controlled by the C/EBPδ antagonists ATF3 and FBXW7. We confirmed the clinical relevance of this regulatory network in subpopulations of human monocytes in a clinical cohort of cardiovascular patients. Moreover, we identified specific C/EBPδ-binding sites within S100a8 and S100a9 promoter regions, and demonstrated that C/EBPδ-dependent JMJD3-mediated demethylation of H3K27me3 is indispensable for their expression. Overall, our work uncovered C/EBPδ as a novel regulator of S100a8 and S100a9 expression. Therefore, C/EBPδ represents a promising target for modulation of inflammatory conditions that are characterized by S100a8 and S100a9 overexpression.

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Haikel Dridi et al.
    Research Article Updated

    Age-dependent loss of body wall muscle function and impaired locomotion occur within 2 weeks in Caenorhabditis elegans (C. elegans); however, the underlying mechanism has not been fully elucidated. In humans, age-dependent loss of muscle function occurs at about 80 years of age and has been linked to dysfunction of ryanodine receptor (RyR)/intracellular calcium (Ca2+) release channels on the sarcoplasmic reticulum (SR). Mammalian skeletal muscle RyR1 channels undergo age-related remodeling due to oxidative overload, leading to loss of the stabilizing subunit calstabin1 (FKBP12) from the channel macromolecular complex. This destabilizes the closed state of the channel resulting in intracellular Ca2+ leak, reduced muscle function, and impaired exercise capacity. We now show that the C. elegans RyR homolog, UNC-68, exhibits a remarkable degree of evolutionary conservation with mammalian RyR channels and similar age-dependent dysfunction. Like RyR1 in mammals, UNC-68 encodes a protein that comprises a macromolecular complex which includes the calstabin1 homolog FKB-2 and is immunoreactive with antibodies raised against the RyR1 complex. Furthermore, as in aged mammals, UNC-68 is oxidized and depleted of FKB-2 in an age-dependent manner, resulting in ‘leaky’ channels, depleted SR Ca2+ stores, reduced body wall muscle Ca2+ transients, and age-dependent muscle weakness. FKB-2 (ok3007)-deficient worms exhibit reduced exercise capacity. Pharmacologically induced oxidization of UNC-68 and depletion of FKB-2 from the channel independently caused reduced body wall muscle Ca2+ transients. Preventing FKB-2 depletion from the UNC-68 macromolecular complex using the Rycal drug S107 improved muscle Ca2+ transients and function. Taken together, these data suggest that UNC-68 oxidation plays a role in age-dependent loss of muscle function. Remarkably, this age-dependent loss of muscle function induced by oxidative overload, which takes ~2 years in mice and ~80 years in humans, occurs in less than 2–3 weeks in C. elegans, suggesting that reduced antioxidant capacity may contribute to the differences in lifespan among species.