Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

Abstract

Influenza virus infections are major causes of morbidity and mortality. Research using cultured cells, bulk tissue, and animal models cannot fully capture human disease dynamics. Many aspects of virus-host interactions in a natural setting remain unclear, including the specific cell types that are infected and how they and neighboring bystander cells contribute to the overall antiviral response. To address these questions, we 35 performed single-cell RNA sequencing (scRNA-Seq) on cells from freshly collected nasal washes from healthy human donors and donors diagnosed with acute influenza during the 2017-18 season. We describe a previously uncharacterized goblet cell population, specific to infected individuals, with high expression of MHC class II genes. Furthermore, leveraging scRNA-Seq reads, we obtained deep viral genome coverage and developed a model to rigorously identify infected cells that detected influenza infection in all epithelial cell types 40 and even some immune cells. Our data revealed that each donor was infected by a unique influenza variant and that each variant was separated by at least one unique non-synonymous difference. Our results demonstrate the power of massively-parallel scRNA-Seq to study viral variation, as well as host and viral transcriptional activity during human infection.45 50

Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19

“…Accordingly, we find exceedingly few immune cell types producing interferons: IFNA and IFNB are absent, rare IFNL1 UMI are observed among T cells and macrophages, and IFNG is robustly produced from interferon responsive cytotoxic CD8 T cells, despite limited evidence for type II responses among epithelial cells ( Supplementary Figure 4F ). Further, we could not detect expression of any interferon types among epithelial cells, which is differs dramatically from previous observations of robust type I/III interferon expression among nasal ciliated cells during influenza A and B infection (also captured via Seq-Well S 3 84 ( Supplementary Figure 4F ). Rather, we observe robust induction of other inflammatory molecules from both immune and epithelial cell types.…”

“…Next, we aimed to differentiate SARS-CoV-2 UMI derived from ambient or low-complexity cell barcodes from those likely reflecting intracellular RNA molecules within high-complexity single-cell transcriptomes 84,88,92,93 . First, we filtered to only viral UMIs associated with cells presented in Figure 1 , thereby removing those associated with low-complexity or ambient-only cell barcodes ( Supplementary Figure 5H ).…”

“…Indeed, understanding whether heterogeneous responses in the epithelial compartment between individuals with COVID-19 underscores differences in disease manifestations will require larger cohort studies, with a focus on longitudinal responses following initial infection. Further work is required to understand how the epithelial responses to SARS-CoV-2 infection within the nasal mucosa relates to epithelial responses during other upper respiratory viral infections and inflammatory states 84,103 .…”

Heterogeneity of monocyte subsets and susceptibility to influenza virus contribute to inter-population variability of protective immunity

“…At the single-cell level, we document extreme heterogeneity in viral mRNA and protein expression, extending the observation of high cell-to-cell variation in IAV replication to circulating human mononuclear phagocytes (Cao et al, 2020;Kudo et al, 2019;Ramos et al, 2019;Russell et al, 2019;Russell et al, 2018;Steuerman et al, 2018;Sun et al, 2020;Wang et al, 2020). We also show, as documented in other cell types, that bystander cells display increased mRNA expression of IFN-stimulated genes relative to infected cells; yet, we additionally observe both an induction of ribosomal gene mRNA expression in IAV-transcribing cells and a down regulation of these genes in bystander cells at later time points.…”

“…In the context of influenza, single-cell RNAsequencing (scRNA-seq) allows for the simultaneous capture and characterization of both host and viral transcriptomes as IAV mRNAs are polyadenylated. Using this technology, extreme variation in viral replication has been reported for epithelial cell lines (Russell et al, 2018), a phenomenon that has been replicated in other systems including animal models and patient samples (Cao et al, 2020;Kudo et al, 2019;Ramos et al, 2019;Russell et al, 2019;Russell et al, 2018;Steuerman et al, 2018;Sun et al, 2020;Wang et al, 2020). Importantly, single-cell analyses can distinguish between bystander (exposed but uninfected) and infected cells, allowing the characterization of antiviral states.…”