Single-cell RNA-sequencing technologies suffer from many sources of technical noise, including under-sampling of mRNA molecules, often termed ‘dropout’, which can severely obscure important gene-gene relationships. To address this, we developed MAGIC (Markov Affinity-based Graph Imputation of Cells), a method that shares information across similar cells, via data diffusion, to denoise the cell count matrix and fill in missing transcripts. We validate MAGIC on several biological systems and find it effective at recovering gene-gene relationships and additional structures. MAGIC reveals a phenotypic continuum, with the majority of cells residing in intermediate states that display stem-like signatures and uncovers known and previously uncharacterized regulatory interactions, demonstrating that our approach can successfully uncover regulatory relations without perturbations.

Although COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Yet, there is no consensus on the consequences of CNS infections. Here, we used three independent approaches to probe the capacity of SARS-CoV-2 to infect the brain. First, using human brain organoids, we observed clear evidence of infection with accompanying metabolic changes in infected and neighboring neurons. However, no evidence for type I interferon responses was detected. We demonstrate that neuronal infection can be prevented by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Second, using mice overexpressing human ACE2, we demonstrate SARS-CoV-2 neuroinvasion in vivo. Finally, in autopsies from patients who died of COVID-19, we detect SARS-CoV-2 in cortical neurons and note pathological features associated with infection with minimal immune cell infiltrates. These results provide evidence for the neuroinvasive capacity of SARS-CoV-2 and an unexpected consequence of direct infection of neurons by SARS-CoV-2.

The high-dimensional data created by high-throughput technologies require visualization tools that reveal data structure and patterns in an intuitive form. We present PHATE, a visualization method that captures both local and global nonlinear structure using an information-geometric distance between datapoints. We compared PHATE to other tools on a variety of artificial and biological *

Identification of host genes essential for SARS-CoV-2 infection may reveal novel therapeutic targets and inform our understanding of COVID-19 pathogenesis. Here, we performed genome-wide CRISPR screens in Vero-E6 cells with SARS-CoV-2, MERS-CoV, bat coronavirus HKU5 expressing the SARS-CoV-1 spike, and VSV expressing the SARS-CoV-2 spike. We identify known SARS-CoV-2 host factors including the receptor ACE2 and protease Cathepsin L. We additionally discovered pro-viral genes and pathways including HMGB1 and the SWI/SNF chromatin remodeling complex that are SARS-lineage and pan-coronavirus specific, respectively. We show HMGB1 regulates ACE2 expression and is critical for viral entry of SARS-CoV-2, SARS-CoV-1, and NL63. We also show that small molecule antagonists of identified gene products inhibited SARS-CoV-2 infection in monkey and human cells, demonstrating the conserved role of these genetic hits across species. Together this identifies potential therapeutic targets for SARS-CoV-2 and reveals SARS-lineage specific and pan-coronavirus host factors that regulate susceptibility to highly pathogenic coronaviruses.

Although COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Reports indicate that 30-60% of patients with COVID-19 suffer from CNS symptoms. Yet, there is no consensus whether the virus can infect the brain, or what the consequences of infection are. Following SARS-CoV-2 infection of human brain organoids, clear evidence of infection was observed, with accompanying metabolic changes in the infected and neighboring neurons. Further, no evidence for the type I interferon responses was detected. We demonstrate that neuronal infection can be prevented either by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Finally, using mice overexpressing human ACE2, we demonstrate in vivo that SARS-CoV-2 neuroinvasion, but not respiratory infection, is associated with mortality. These results provide evidence for the neuroinvasive capacity of SARS-CoV2, and an unexpected consequence of direct infection of neurons by SARS-CoV2.

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Objective The goal of this study was to develop a prognostic tool of early hospital respiratory failure among emergency department (ED) patients admitted with COVID-19. Methods This was an observational, retrospective cohort study from a nine ED health system in the United States of admitted adult patients with SARS-CoV-2 (COVID-19) and a ≤ 6 L/min oxygen requirement. We sought to predict respiratory failure within 24 hours of admission as defined by oxygen requirement of ≥ 10 L/min, any high-flow device, non-invasive or invasive ventilation, or death. Predictive models were compared to the Elixhauser comorbidity index, quick serial organ failure assessment (qSOFA), and the CURB-65 pneumonia severity score. Results During the study period from March 1 to April 27, 2020, 1,792 patients were admitted with COVID-19, 620 (35%) of whom had respiratory failure in the ED. Of the remaining 1,172 admitted patients, 144 (12.3%) met the composite endpoint within the first 24 hours of hospitalization. Using area under receiver-operating characteristic curves, we compared the performance of a novel bedside scoring system, the quick COVID-19 severity index (qCSI) composed of respiratory rate, oxygen saturation, and oxygen flow rate (mean [95% CI]) (0.81 [0.73-0.89]), a machine- learning model, the COVID-19 severity index (0.76 [0.65-0.86]), to the Elixhauser mortality index (0.61 [0.51-0.70])), CURB-65 (0.50 [0.40-0.60]), and qSOFA (0.59 [0.50-0.68]). A low qCSI score (≤ 3) had a sensitivity of 0.79 [0.65- 0.93] and specificity of 0.78 [0.72-0.83] in predicting respiratory decompensation with a less than 5% risk of outcome in the validation cohort. Conclusions A significant proportion of admitted COVID-19 patients progress to respiratory failure within 24 hours of admission. These events are accurately predicted using bedside respiratory exam findings within a simple scoring system.

Multisystem inflammatory syndrome in children (MIS-C) is a life-threatening post-infectious complication occurring unpredictably weeks after mild or asymptomatic SARS-CoV-2 infection. We profiled MIS-C, adult COVID-19, and healthy pediatric and adult individuals using single-cell RNA sequencing, flow cytometry, antigen receptor repertoire analysis, and unbiased serum proteomics, which collectively identified a signature in MIS-C patients that correlated with disease severity. Despite having no evidence of active infection, MIS-C patients had elevated S100A-family alarmins and decreased antigen presentation signatures, indicative of myeloid dysfunction. MIS-C patients showed elevated expression of cytotoxicity genes in NK and CD8 + T cells and expansion of specific IgG-expressing plasmablasts. Clinically severe MIS-C patients displayed skewed memory T cell TCR repertoires and autoimmunity characterized by endothelium-reactive IgG. The alarmin, cytotoxicity, TCR repertoire, and plasmablast signatures we defined have potential for application in the clinic to better diagnose and potentially predict disease severity early in the course of MIS-C.