Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data (preprint)

Resolving chromatin remodeling-linked gene expression changes at cell type resolution is important for understanding disease states. We describe MAGICAL, a hierarchical Bayesian approach that leverages paired scRNA-seq and scATAC-seq data from different conditions to map disease-associated transcription factors, chromatin sites, and genes as regulatory circuits. By simultaneously modeling signal variation across cells and conditions in both omics data types, MAGICAL achieved high accuracy on circuit inference. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single-cell data that we generated from infected subjects with bloodstream infection and from uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be activated by bacterial sepsis. We addressed the challenging problem of distinguishing host regulatory circuit responses to methicillin-resistant- (MRSA) and methicillin-susceptible Staphylococcus aureus (MSSA) infections. While differential expression analysis failed to show predictive value, MAGICAL identified epigenetic circuit biomarkers that distinguished MRSA from MSSA.

Double-stranded RNA drives SARS-CoV-2 nucleocapsid protein to undergo phase separation at specific temperatures (preprint)

Betacoronavirus SARS-CoV-2 infections caused the global Covid-19 pandemic. The nucleocapsid protein (N-protein) is required for multiple steps in the betacoronavirus replication cycle. SARS-CoV-2-N-protein is known to undergo liquid-liquid phase separation (LLPS) with specific RNAs at particular temperatures to form condensates. We show that N-protein recognizes at least two separate and distinct RNA motifs, both of which require double-stranded RNA (dsRNA) for LLPS. These motifs are separately recognized by N-protein's two RNA binding domains (RBDs). Addition of dsRNA accelerates and modifies N-protein LLPS in vitro and in cells and controls the temperature condensates form. The abundance of dsRNA tunes N-protein-mediated translational repression and may confer a switch from translation to genome packaging. Thus, N-protein's two RBDs interact with separate dsRNA motifs, and these interactions impart distinct droplet properties that can support multiple viral functions. These experiments demonstrate a paradigm of how RNA structure can control the properties of biomolecular condensates.

SARS-CoV-2 receptor networks in diabetic kidney disease, BK-Virus nephropathy and COVID-19 associated acute kidney injury (preprint)

COVID-19 morbidity and mortality is increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease (DKD) and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of healthy living donor (LD) and DKD kidney biopsies revealed ACE2 expression primarily in proximal tubular epithelial cells (PTEC). This cell specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin angiotensin aldosterone system inhibitors in DKD. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing PTEC in DKD (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The DKD ACE2-positive PTEC module overlapped with expression patterns seen in SARS-CoV-2 infected cells. Similar cellular programs were seen in ACE2-positive PTEC obtained from urine samples of 13 COVID-19 patients who were hospitalized, suggesting a consistent ACE2-coregulated PTEC expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19 related kidney damage. Translational statementTo understand the overwhelming burden of kidney disease in COVID-19, we mapped the expression of the SARS-CoV-2 receptor, ACE2, in healthy kidney, early diabetic (DKD) and COVID-19 associated kidney diseases. Single cell RNA sequencing of 111035 cells identified ACE2 predominantly in proximal tubular epithelial cells. ACE2 upregulation was observed in DKD, but was not associated with RAAS inhibition, arguing against an increased risk of COVID-19 among patients taking RAAS inhibitors. Molecular network analysis linked ACE2 expression to innate immune response and viral entry machinery, thereby revealing potential therapeutic strategies against COVID-19.