A virus-free cellular model recapitulates several features of severe COVID-19

Abstract

As for all newly-emergent pathogens, SARS-CoV-2 presents with a relative paucity of clinical information and experimental models, a situation hampering both the development of new effective treatments and the prediction of future outbreaks. Here, we find that a simple virus-free model, based on publicly available transcriptional data from human cell lines, is surprisingly able to recapitulate several features of the clinically relevant infections. By segregating cell lines (n = 1305) from the CCLE project on the base of their sole angiotensin-converting enzyme 2 (ACE2) mRNA content, we found that overexpressing cells present with molecular features resembling those of at-risk patients, including senescence, impairment of antibody production, epigenetic regulation, DNA repair and apoptosis, neutralization of the interferon response, proneness to an overemphasized innate immune activity, hyperinflammation by IL-1, diabetes, hypercoagulation and hypogonadism. Likewise, several pathways were found to display a differential expression between sexes, with males being in the least advantageous position, thus suggesting that the model could reproduce even the sex-related disparities observed in the clinical outcome of patients with COVID-19. Overall, besides validating a new disease model, our data suggest that, in patients with severe COVID-19, a baseline ground could be already present and, as a consequence, the viral infection might simply exacerbate a variety of latent (or inherent) pre-existing conditions, representing therefore a tipping point at which they become clinically significant.

Figure 1

Building a virus-free COVID-19 disease model based on differential ACE2 expression in human cell lines. (a) 1305 cell lines from the Cancer Cell Line Encyclopedia (CCLE) project were sorted on the base of their ACE2 TPM (Transcripts Per Million) content. Cell lines displaying a ACE2 TPM value equal to 0 (Low ACE2) or greater than 1 (High ACE2) were grouped. (b) Top 50 differentially expressed transcripts between Low ACE2 vs. High ACE2 cell lines.

Figure 2

ACE2 overexpressing cell lines mimic host immune response in COVID-19 severe infection. (a) Network built from differentially expressed datasets related to a hyperinflammatory/immune response obtained by the Gene Set Enrichment Analysis (GSEA) of Low_ACE2 vs. High_ACE2 expressing cell lines. Datasets overexpressed (b–f) or underexpressed (g) in High_ACE2 cell lines. Vertical bars represent where the members of the gene set appear in the list of ranked genes. Genes are ranked on the base of their differential expression in 'Low_ACE2' vs. 'High_ACE2' samples, with genes decreasingly overexpressed in 'Low_ACE2' samples starting from the left of the graph. IL1A (h), IL1B (i), IFNA21 (j) and IFNW1 (k) expression in Low_ACE2 vs High_ACE cell lines. FC: expression ratio of High_ACE2 vs. Low_ACE2 cell lines. FC: expression ratio of each transcript in High_ACE2 vs. Low_ACE2 cell lines. Values around the median in (j) and (k) are compressed toward the bottom because they possess mostly a zero value.

Figure 3

Impairment of several key pathways in ACE2 overexpressing cell lines. GSEA identified several gene sets downregulated in ACE2 overexpressing cell lines. Gene sets could be grouped in pathways/networks related to senescence/chromosome maintenance (a–d), antibody production (e,f), DNA repair/viral transcription (g–i), protein folding/platelet homeostasis (j), histone modifications (k).

Figure 4

Hypogonadism and estrogen response is coupled to ACE2 overexpression in male cell lines. GSEA in male cell lines identifies a downregulation of the androgen receptor signaling pathway (a,b), coupled to un upregulation of the estrogen response (c–e) and to the transcriptional downregulation of the androgen receptor (f) and to the transcriptional activation of the estrogen receptor (g).

Figure 5

Gender-preferential pathway expression links ACE2 overexpression to worse clinical outcome in males. Measurement of the gender specific activation of the pathways associated to ACE2 overexpression identified 131 gene sets with significant gender preferential activity, with the top 30 lists shown in (a). Disease-linked genes IL1A (b,c), IL1B (d,e) and IFNW1 (f,g) also show preferential activation in males.