Intrinsic OASL expression licenses interferon induction during influenza A virus infection

Abstract

Effective control of viral infection requires rapid induction of the innate immune response, especially the type I and type III interferon (IFN) systems. Despite the critical role of IFN induction in host defense, numerous studies have established that most cells fail to produce IFNs in response to viral stimuli. The specific factors that govern cellular heterogeneity in IFN induction potential during infection are not understood. To identify specific host factors that license some cells but not others to mount an IFN response to viral infection, we developed an approach for analyzing temporal scRNA-seq data of influenza A virus (IAV)-infected cells. This approach identified the expression of several interferon stimulated genes (ISGs) within pre-infection cells as correlates of IFN induction potential of those cells, post-infection. Validation experiments confirmed that intrinsic expression of the ISG OASL is essential for robust IFNL induction during IAV infection. Altogether, our findings reveal an important role for IFN-independent, intrinsic expression of ISGs in promoting IFN induction and provide new insights into the mechanisms that regulate cell-to-cell heterogeneity in innate immune activation.

Keywords: OASL; RNA sensing; RNA velocity; antiviral response; cellular heterogeneity; influenza A virus; innate immunity; interferon; interferon-stimulated genes; scRNA-seq.

Figure 1.. Temporal scRNA-seq analysis of A549 cells infected with H3N2.

A) A549 cells were infected with Perth09 (MOI of 0.5 NPEU/cell) and collected at different times post-infection. Cells were sorted based on surface expression of the viral glycoprotein HA prior to library preparation for scRNA-seq. B) Collected scRNA-seq libraries were clustered based on transcriptional profiles and colored according to time. C) IFNL1-positive cells, highlighted in red, were identified at different times post-infection. D) Quantification of the fraction of infected cells expressing IFNL1 and E) expression counts at different timepoints.

Figure 2.. Identifying transcriptional terminal states and transition probabilities during H3N2 infection

A) Trajectory mapping of A549 cells transitioning through transcriptional state space, with cells from each timepoint represented by a distinct color and IFNL-positive cells highlighted in red. B) Trajectory map of A549 cells colored by IFNL1 expression log10(1+counts). C) Distribution of inferred probabilities for all cells transitioning into the high-IFNL terminal state. D) Fraction of cells at each timepoint with transition probabilities greater than 0.3 for reaching the high-IFNL terminal state.

Figure 3.. Identification of regulators of IFNL using pseudotime reconstruction analysis

A) Top 20 ranked genes according to correlation between inferred transition probabilities to the high IFNL terminal state and their expression at 0 hrs. B) STRING database network analysis of the top 20 correlated genes, colored by annotated cellular pathways. Genes in red cluster are defined as associated with interferon responses while the yellow and green clusters are associated with IL-10 and apoptosis respectively. C) Quantification of the fraction of cells expressing candidate genes at 0 hrs. D) Expression counts (log10) of candidate genes at the 0 hrs timepoint.

Figure 4.. Intrinsic OASL is required for robust IFNL expression in response to IAV infection

A) Detection of IFNL in the supernatant of A549 cells transfected with siRNA targeting candidate genes for 48 hrs, followed by infection with H3N2 (MOI 1 NPEU/cell) for 16 hrs. B) Detection of active secreted IFNL and C) IFNL1 mRNA in siRNA-treated A549 cells infected at MOI 1 for 8 hpi. D) Detection of pSTAT1, NP, OASL, and $\beta$-Actin levels in A549 WT and STAT1−/− cells infected with H3N2 (MOI of 1 NPEU/cell) at 0, 8, and 16 hrs post-infection (hpi). E) Measurement of secreted functional IFNL in STAT1−/− A549 cells transfected with siRNA and infected at MOI 1 for 8 hpi. F) Quantification of IFNL1 expression in siRNA-treated A549 cells infected with H3N2 (MOI of 5 NPEU/cell) and subsequently incubated with cycloheximide (CHX) ($10\mu \mathrm{g}/\text{mL}$) for 8 hrs. G) Detection of levels of pSTAT1, NP, OASL, and $\beta$-Actin in A549 cells treated with CHX ($10\mu \mathrm{g}/\text{mL}$) or DMSO for 8 hrs. Data are shown as mean with SD; N = 9 (3 independent experiment with 3 replicates each). One-way ANOVAS with Dunnett’s multiple comparison tests were used for statistical analysis. Western blots are shown as a representative of three independent experiments.

Figure 5.. Identification of intrinsic ISGs in primary human bronchial epithelial cells by scRNA-seq

A) UMAP visualization of scRNA-seq data from HBECs, with cells labeled based on cell types. B) Proportion of cells expressing OASL, IFIT3, DDX60, ISG15, or IRF1 and C) expression counts divided by donor. D) The cell type composition of positive cells for each candidate gene separated and colored by cell types. E) Fraction of cells within each cell type expressing the candidate ISGs.