Macrophage ACE2 is necessary for SARS-CoV-2 replication and subsequent cytokine responses that restrict continued virion release.

Macrophages are key cellular contributors to the pathogenesis of COVID-19, the disease caused by the virus SARS-CoV-2. The SARS-CoV-2 entry receptor ACE2 is present only on a subset of macrophages at sites of SARS-CoV-2 infection in humans. Here, we investigated whether SARS-CoV-2 can enter macrophages, replicate, and release new viral progeny; whether macrophages need to sense a replicating virus to drive cytokine release; and, if so, whether ACE2 is involved in these mechanisms. We found that SARS-CoV-2 could enter, but did not replicate within, ACE2-deficient human primary macrophages and did not induce proinflammatory cytokine expression. By contrast, ACE2 overexpression in human THP-1-derived macrophages permitted SARS-CoV-2 entry, processing and replication, and virion release. ACE2-overexpressing THP-1 macrophages sensed active viral replication and triggered proinflammatory, antiviral programs mediated by the kinase TBK-1 that limited prolonged viral replication and release. These findings help elucidate the role of ACE2 and its absence in macrophage responses to SARS-CoV-2 infection.

Single-cell expression profiling reveals dynamic flux of cardiac stromal, vascular and immune cells in health and injury.

Besides cardiomyocytes (CM), the heart contains numerous interstitial cell types which play key roles in heart repair, regeneration and disease, including fibroblast, vascular and immune cells. However, a comprehensive understanding of this interactive cell community is lacking. We performed single-cell RNA-sequencing of the total non-CM fraction and enriched (Pdgfra-GFP+) fibroblast lineage cells from murine hearts at days 3 and 7 post-sham or myocardial infarction (MI) surgery. Clustering of >30,000 single cells identified >30 populations representing nine cell lineages, including a previously undescribed fibroblast lineage trajectory present in both sham and MI hearts leading to a uniquely activated cell state defined in part by a strong anti-WNT transcriptome signature. We also uncovered novel myofibroblast subtypes expressing either pro-fibrotic or anti-fibrotic signatures. Our data highlight non-linear dynamics in myeloid and fibroblast lineages after cardiac injury, and provide an entry point for deeper analysis of cardiac homeostasis, inflammation, fibrosis, repair and regeneration.

Prediction of kinase-specific phosphorylation sites through an integrative model of protein context and sequence.

Identifying kinase substrates and the specific phosphorylation sites they regulate is an important factor in understanding protein function regulation and signalling pathways. Computational prediction of kinase targets - assigning kinases to putative substrates, and selecting from protein sequence the sites that kinases can phosphorylate - requires the consideration of both the cellular context that kinases operate in, as well as their binding affinity. This consideration enables investigation of how phosphorylation influences a range of biological processes. We report here a novel probabilistic model for classifying kinase-specific phosphorylation sites from sequence across three model organisms: human, mouse and yeast. The model incorporates position-specific amino acid frequencies, and counts of co-occurring amino acids from kinase binding sites. We show how this model can be seamlessly integrated with protein interactions and cell-cycle abundance profiles. When evaluating the prediction accuracy of our method, PhosphoPICK, on an independent hold-out set of kinase-specific phosphorylation sites, it achieved an average specificity of 97%, with 32% sensitivity. We compared PhosphoPICK's ability, through cross-validation, to predict kinase-specific phosphorylation sites with alternative methods, and show that at high levels of specificity PhosphoPICK obtains greater sensitivity for most comparisons made. We investigated the relationship between kinase-specific phosphorylation sites and nuclear localisation signals. We show that kinases PKA, Akt1 and AurB have an over-representation of predicted binding sites at particular positions downstream from predicted nuclear localisation signals, demonstrating an important role for these kinases in regulating the nuclear import of proteins. PhosphoPICK is freely available as a web-service at http://bioinf.scmb.uq.edu.au/phosphopick.