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Mapping signalling perturbations in myocardial fibrosis via the integrative phosphoproteomic profiling of tissue from diverse sources

Nature Biomedical Engineering volume 4, pages 889–900 (2020)Cite this article

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Abstract

Study of the molecular basis of myocardial fibrosis is hampered by limited access to tissues from human patients and by confounding variables associated with sample accessibility, collection, processing and storage. Here, we report an integrative strategy based on mass spectrometry for the phosphoproteomic profiling of normal and fibrotic cardiac tissue obtained from surgical explants from patients with hypertrophic cardiomyopathy, from a transaortic-constriction mouse model of cardiac hypertrophy and fibrosis, and from a heart-on-a-chip model of cardiac fibrosis. We used the integrative approach to map the relative abundance of thousands of proteins, phosphoproteins and phosphorylation sites specific to each tissue source, to identify key signalling pathways driving fibrosis and to screen for anti-fibrotic compounds targeting glycogen synthase kinase 3, which has a consistent role as a key mediator of fibrosis in all three types of tissue specimen. The integrative disease-modelling strategy may reveal new insights into mechanisms of cardiac disease and serve as a test bed for drug screening.

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Fig. 1: Overview of phosphoproteomic workflows.
Fig. 2: Collagen deposition in normal and fibrotic samples.
Fig. 3: Coverage and data distribution across datasets.
Fig. 4: Comparison of merged proteomic and phosphoproteomic datasets between experimental and clinical conditions.
Fig. 5: Pathway-level comparison between datasets.
Fig. 6: Drug treatment with the selected GSK3 inhibitor GW806290X in parallel with a standard GSK3 inhibitor (CHIR 99021) after tissue maturation.
Fig. 7: Drug screening with early treatment upon tissue seeding.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. All data generated during the study, including source data and the data used to make the figures, are available via ProteomeXchange with identifier PXD016492.

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Acknowledgements

We thank H. Rakowski for initial discussions on study design and execution; GlaxoSmithKline and W. Zuercher for the gift of the published kinase inhibitor set; and J. Greenblatt and E. Macron for allowing access to instrumentation at the Donnelly Centre. This research is part of the University of Toronto’s Medicine by Design initiative which receives funding from the Canada First Research Excellence Fund. This project was funded by the Ted Rogers Centre for Heart Research Translational Biology and Engineering Program to A.G., the Heart and Stroke Richard Lewar Centres of Excellence in Cardiovascular Research and CIHR grants to A.G. (PJT-155921 and PJT-166118; MOP-106538; MOP-123320). S.-H.L. was supported by a NSERC Postgraduate Scholarship, an Ontario Graduate Scholarship and a Ted Rogers Centre for Heart Research Doctoral Fellowship. S.H.-L. was supported by a Canada Graduate Scholarship–Master’s Award from Canadian Institutes of Health Research and an Ontario Graduate Scholarship. U.K. was supported by a Ted Rogers Centre for Heart Research Postdoctoral Fellowship. This work was funded by the Canadian Institutes of Health Research Foundation grant (FDN-167274), Natural Sciences and Engineering Research Council−Canadian Institutes of Health Research Collaborative Health Research grant (CHRP 493737-16) and Killam Fellowship (7025-19-0016) awarded to M.R. E.Y.W. was supported by Alexander Graham Bell Canada Graduate Scholarship–Doctoral Award (CGS−D). A.E. acknowledges a Foundation grant (FDN-148399) from the Canadian Institutes of Health Research.

Author information

Author notes

  1. These authors contributed equally: Uros Kuzmanov, Erika Yan Wang.

Authors and Affiliations

  1. Ted Rogers Centre for Heart Research, University of Toronto, Toronto, Ontario, Canada

    Uros Kuzmanov, Da Hye Kim, Shin-Haw Lee, Sina Hadipour-Lakmehsari, Meghan McFadden & Anthony Gramolini

  2. Department of Physiology, University of Toronto, Toronto, Ontario, Canada

    Uros Kuzmanov, Da Hye Kim, Shin-Haw Lee, Sina Hadipour-Lakmehsari & Anthony Gramolini

  3. Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada

    Erika Yan Wang, Yimu Zhao & Milica Radisic

  4. Division of Cardiac Surgery, University of Toronto, Toronto, Ontario, Canada

    Rachel Vanderlaan

  5. Donnelly Center for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario, Canada

    Hongbo Guo

  6. Institute of Translational Medicine, University of Liverpool, Liverpool, UK

    Parveen Sharma

  7. Toronto General Research Institute, Toronto, Ontario, Canada

    Filio Billia & Anthony Gramolini

  8. Division of Cardiology, University Health Network, Toronto, Ontario, Canada

    Filio Billia

  9. Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario, Canada

    Milica Radisic

  10. Department of Biology, Boston University, Boston, MA, USA

    Andrew Emili

  11. Department of Biochemistry, Boston University School of Medicine, Boston, MA, USA

    Andrew Emili

  12. Center for Network Systems Biology, Boston University, Boston, MA, USA

    Andrew Emili

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Contributions

A.E., A.G., E.Y.W., M.R. and U.K. designed the study and wrote the manuscript. U.K. performed experimental preparation and bioinformatic data analysis of all (phospho)proteomics samples. E.Y.W. generated the Biowire constructs and performed all associated experimental work, including fluorescence imaging of Biowire, mouse, and patient explant samples. R.V. and F.B. assisted in the design of the study and provided patient surgical explant samples and associated clinical information. D.H.K., S.H.-L., S.-H.L. and P.S. helped in the design and performing of mouse experiments and preparation of mass spectrometry samples. H.G. and M.M. maintained and operated mass spectrometry instrumentation. Y.Z. assisted in the generation of Biowire constructs and design of the study. U.K. wrote the initial manuscript, which was edited by all authors.

Corresponding authors

Correspondence to Milica Radisic, Anthony Gramolini or Andrew Emili.

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Competing interests

M.R. and Y.Z. are co-founders and hold shares in TARA Biosystems, which uses the Biowire II platform for commercial drug testing.

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Supplementary information

Supplementary Information

Supplementary figures, tables and descriptions for the supplementary datasets.

Reporting Summary

Supplementary Dataset 1

Normalized quantitative data for unfiltered protein identifications by proteomic analysis of all three types of samples processed.

Supplementary Dataset 2

Normalized quantitative data for phosphorylation sites.

Supplementary Dataset 3

Panther DB output of annotation coverage for all (phospho)protein-level identifications in all analysed datasets for gene ontology and reactome pathways.

Supplementary Dataset 4

GSEA-enriched gene set annotations in each dataset.

Supplementary Dataset 5

Significant phosphorylation sites.

Supplementary Dataset 6

Results of echocardiography analysis of TAC and sham mouse hearts.

Supplementary Fig. 6

High-resolution version of the results of the gene set enrichment analysis visualized in Cytoscape by using the Enrichment Map plugin.

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Kuzmanov, U., Wang, E.Y., Vanderlaan, R. et al. Mapping signalling perturbations in myocardial fibrosis via the integrative phosphoproteomic profiling of tissue from diverse sources. Nat Biomed Eng 4, 889–900 (2020). https://doi.org/10.1038/s41551-020-0585-y

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