ABSTRACT
The SARS-CoV-2 Omicron BA.1 variant emerged in late 2021 and is characterised by multiple spike mutations across all spike domains. Here we show that Omicron BA.1 has higher affinity for ACE2 compared to Delta, and confers very significant evasion of therapeutic monoclonal and vaccine-elicited polyclonal neutralising antibodies after two doses. mRNA vaccination as a third vaccine dose rescues and broadens neutralisation. Importantly, antiviral drugs remdesevir and molnupiravir retain efficacy against Omicron BA.1. We found that in human nasal epithelial 3D cultures replication was similar for both Omicron and Delta. However, in lower airway organoids, Calu-3 lung cells and gut adenocarcinoma cell lines live Omicron virus demonstrated significantly lower replication in comparison to Delta. We noted that despite presence of mutations predicted to favour spike S1/S2 cleavage, the spike protein is less efficiently cleaved in live Omicron virions compared to Delta virions. We mapped the replication differences between the variants to entry efficiency using spike pseudotyped virus (PV) entry assays. The defect for Omicron PV in specific cell types correlated with higher cellular RNA expression of TMPRSS2, and accordingly knock down of TMPRSS2 impacted Delta entry to a greater extent as compared to Omicron. Furthermore, drug inhibitors targeting specific entry pathways demonstrated that the Omicron spike inefficiently utilises the cellular protease TMPRSS2 that mediates cell entry via plasma membrane fusion. Instead, we demonstrate that Omicron spike has greater dependency on cell entry via the endocytic pathway requiring the activity of endosomal cathepsins to cleave spike. Consistent with suboptimal S1/S2 cleavage and inability to utilise TMPRSS2, syncytium formation by the Omicron spike was dramatically impaired compared to the Delta spike. Overall, Omicron appears to have gained significant evasion from neutralising antibodies whilst maintaining sensitivity to antiviral drugs targeting the polymerase. Omicron has shifted cellular tropism away from TMPRSS2 expressing cells that are enriched in cells found in the lower respiratory and GI tracts, with implications for altered pathogenesis.
ABSTRACT
Common genetic variants modulate the cellular response to viruses and are implicated in a range of immune pathologies, including infectious and autoimmune diseases. The transcriptional antiviral response is known to vary between infected cells from a single individual, yet how genetic variants across individuals modulate the antiviral response (and its cell-to-cell variability) is not well understood. Here, we triggered the antiviral response in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-seq. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), the first statistical approach designed to identify dynamic eQTLs across a transcriptional trajectory of cell populations, without aggregating single-cell data into pseudo-bulk. This allows us to uncover the underlying architecture and variability of antiviral response across responding cells, and to identify more than two thousands eQTLs modulating the dynamic changes during this response. Many of these eQTLs colocalise with risk loci identified in GWAS of infectious and autoimmune diseases. As a case study, we focus on a COVID-19 susceptibility locus, colocalised with the antiviral OAS1 splicing QTL. We validated it in blood cells from a patient cohort and in the infected nasal cells of a patient with the risk allele, demonstrating the utility of GASPACHO to fine-map and functionally characterise a genetic locus. In summary, our novel analytical approach provides a new framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution.
ABSTRACT
[Abstract]In late 2019 and through 2020, the COVID-19 pandemic swept the world, presenting both scientific and medical challenges associated with understanding and treating a previously unknown disease. To help address the need for great understanding of COVID-19, the scientific community mobilized and banded together rapidly to characterize SARS-CoV-2 infection, pathogenesis and its distinct disease trajectories. The urgency of COVID-19 provided a pressing use-case for leveraging relatively new tools, technologies, and nascent collaborative networks. Single-cell biology is one such example that has emerged over the last decade as a powerful approach that provides unprecedented resolution to the cellular and molecular underpinnings of biological processes. Early foundational work within the single-cell community, including the Human Cell Atlas, utilized published and unpublished data to characterize the putative target cells of SARS-CoV-2 sampled from diverse organs based on expression of the viral receptor ACE2 and associated entry factors TMPRSS2 and CTSL (Muus et al., 2020; Sungnak et al., 2020; Ziegler et al., 2020). This initial characterization of reference data provided an important foundation for framing infection and pathology in the airway as well as other organs. However, initial community analysis was limited to samples derived from uninfected donors and other previously-sampled disease indications. This report provides an overview of a single-cell data resource derived from samples from COVID-19 patients along with initial observations and guidance on data reuse and exploration.
