Proinflammatory cytokines driving cardiotoxicity in COVID-19.

AIMS: Cardiac involvement is common in patients hospitalized with COVID-19 and correlates with an adverse disease trajectory. While cardiac injury has been attributed to direct viral cytotoxicity, serum-induced cardiotoxicity secondary to serological hyperinflammation constitutes a potentially amenable mechanism that remains largely unexplored. METHODS AND RESULTS: To investigate serological drivers of cardiotoxicity in COVID-19 we have established a robust bioassay that assessed the effects of serum from COVID-19 confirmed patients on human embryonic stem cell (hESC)-derived cardiomyocytes. We demonstrate that serum from COVID-19 positive patients significantly reduced cardiomyocyte viability independent of viral transduction, an effect that was also seen in non-COVID-19 acute respiratory distress syndrome (ARDS). Serum from patients with greater disease severity led to worse cardiomyocyte viability and this significantly correlated with levels of key inflammatory cytokines, including IL-6, TNF-α, IL1-ß, IL-10, CRP, and neutrophil to lymphocyte ratio with a specific reduction of CD4+ and CD8+ cells. Combinatorial blockade of IL-6 and TNF-α partly rescued the phenotype and preserved cardiomyocyte viability and function. Bulk RNA sequencing of serum-treated cardiomyocytes elucidated specific pathways involved in the COVID-19 response impacting cardiomyocyte viability, structure, and function. The observed effects of serum-induced cytotoxicity were cell-type selective as serum exposure did not adversely affect microvascular endothelial cell viability but resulted in endothelial activation and a procoagulant state. CONCLUSION: These results provide direct evidence that inflammatory cytokines are at least in part responsible for the cardiovascular damage seen in COVID-19 and characterise the downstream activated pathways in human cardiomyocytes. The serum signature of patients with severe disease indicates possible targets for therapeutic intervention.

Epicardially secreted fibronectin drives cardiomyocyte maturation in 3D-engineered heart tissues.

Ischemic heart failure is due to irreversible loss of cardiomyocytes. Preclinical studies showed that human pluripotent stem cell (hPSC)-derived cardiomyocytes could remuscularize infarcted hearts and improve cardiac function. However, these cardiomyocytes remained immature. Incorporating hPSC-derived epicardial cells has been shown to improve cardiomyocyte maturation, but the exact mechanisms are unknown. We posited epicardial fibronectin (FN1) as a mediator of epicardial-cardiomyocyte crosstalk and assessed its role in driving hPSC-derived cardiomyocyte maturation in 3D-engineered heart tissues (3D-EHTs). We found that the loss of FN1 with peptide inhibition F(pUR4), CRISPR-Cas9-mediated FN1 knockout, or tetracycline-inducible FN1 knockdown in 3D-EHTs resulted in immature cardiomyocytes with decreased contractile function, and inefficient Ca2+ handling. Conversely, when we supplemented 3D-EHTs with recombinant human FN1, we could recover hPSC-derived cardiomyocyte maturation. Finally, our RNA-sequencing analyses found FN1 within a wider paracrine network of epicardial-cardiomyocyte crosstalk, thus solidifying FN1 as a key driver of hPSC-derived cardiomyocyte maturation in 3D-EHTs.

Erratum: Author Correction: A single-cell comparison of adult and fetal human epicardium defines the age-associated changes in epicardial activity.

[This corrects the article DOI: 10.1038/s44161-022-00183-w.].

A single-cell comparison of adult and fetal human epicardium defines the age-associated changes in epicardial activity.

Re-activating quiescent adult epicardium represents a potential therapeutic approach for human cardiac regeneration. However, the exact molecular differences between inactive adult and active fetal epicardium are not known. In this study, we combined fetal and adult human hearts using single-cell and single-nuclei RNA sequencing and compared epicardial cells from both stages. We found that a migratory fibroblast-like epicardial population only in the fetal heart and fetal epicardium expressed angiogenic gene programs, whereas the adult epicardium was solely mesothelial and immune responsive. Furthermore, we predicted that adult hearts may still receive fetal epicardial paracrine communication, including WNT signaling with endocardium, reinforcing the validity of regenerative strategies that administer or reactivate epicardial cells in situ. Finally, we explained graft efficacy of our human embryonic stem-cell-derived epicardium model by noting its similarity to human fetal epicardium. Overall, our study defines epicardial programs of regenerative angiogenesis absent in adult hearts, contextualizes animal studies and defines epicardial states required for effective human heart regeneration.

BioModels-15 years of sharing computational models in life science.

Computational modelling has become increasingly common in life science research. To provide a platform to support universal sharing, easy accessibility and model reproducibility, BioModels (https://www.ebi.ac.uk/biomodels/), a repository for mathematical models, was established in 2005. The current BioModels platform allows submission of models encoded in diverse modelling formats, including SBML, CellML, PharmML, COMBINE archive, MATLAB, Mathematica, R, Python or C++. The models submitted to BioModels are curated to verify the computational representation of the biological process and the reproducibility of the simulation results in the reference publication. The curation also involves encoding models in standard formats and annotation with controlled vocabularies following MIRIAM (minimal information required in the annotation of biochemical models) guidelines. BioModels now accepts large-scale submission of auto-generated computational models. With gradual growth in content over 15 years, BioModels currently hosts about 2000 models from the published literature. With about 800 curated models, BioModels has become the world's largest repository of curated models and emerged as the third most used data resource after PubMed and Google Scholar among the scientists who use modelling in their research. Thus, BioModels benefits modellers by providing access to reliable and semantically enriched curated models in standard formats that are easy to share, reproduce and reuse.

Toward Community Standards and Software for Whole-Cell Modeling.

OBJECTIVE: Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate comprehensive models of complex cells. METHODS: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in the Systems Biology Markup Language. RESULTS: Our analysis revealed several challenges to representing WC models using the current standards. CONCLUSION: We, therefore, propose several new WC modeling standards, software, and databases. SIGNIFICANCE: We anticipate that these new standards and software will enable more comprehensive models.

BioModels: ten-year anniversary.

BioModels (http://www.ebi.ac.uk/biomodels/) is a repository of mathematical models of biological processes. A large set of models is curated to verify both correspondence to the biological process that the model seeks to represent, and reproducibility of the simulation results as described in the corresponding peer-reviewed publication. Many models submitted to the database are annotated, cross-referencing its components to external resources such as database records, and terms from controlled vocabularies and ontologies. BioModels comprises two main branches: one is composed of models derived from literature, while the second is generated through automated processes. BioModels currently hosts over 1200 models derived directly from the literature, as well as in excess of 140,000 models automatically generated from pathway resources. This represents an approximate 60-fold growth for literature-based model numbers alone, since BioModels' first release a decade ago. This article describes updates to the resource over this period, which include changes to the user interface, the annotation profiles of models in the curation pipeline, major infrastructure changes, ability to perform online simulations and the availability of model content in Linked Data form. We also outline planned improvements to cope with a diverse array of new challenges.