Dissection of key factors correlating with H5N1 avian influenza virus driven inflammatory lung injury of chicken identified by single-cell analysis

Abstract

Chicken lung is an important target organ of avian influenza virus (AIV) infection, and different pathogenic virus strains lead to opposite prognosis. Using a single-cell RNA sequencing (scRNA-seq) assay, we systematically and sequentially analyzed the transcriptome of 16 cell types (19 clusters) in the lung tissue of chickens infected with H5N1 highly pathogenic avian influenza virus (HPAIV) and H9N2 low pathogenic avian influenza virus (LPAIV), respectively. Notably, we developed a valuable catalog of marker genes for these cell types. Compared to H9N2 AIV infection, H5N1 AIV infection induced extensive virus replication and the immune reaction across most cell types simultaneously. More importantly, we propose that infiltrating inflammatory macrophages (clusters 0, 1, and 14) with massive viral replication, pro-inflammatory cytokines (IFN-β, IL1β, IL6 and IL8), and emerging interaction of various cell populations through CCL4, CCL19 and CXCL13, potentially contributed to the H5N1 AIV driven inflammatory lung injury. Our data revealed complex but distinct immune response landscapes in the lung tissue of chickens after H5N1 and H9N2 AIV infection, and deciphered the potential mechanisms underlying AIV-driven inflammatory reactions in chicken. Furthermore, this article provides a rich database for the molecular basis of different cell-type responses to AIV infection.

Fig 1. Single-cell profiling of cell populations in the lung collected from H9N2 AIV infected, H5N1 AIV infected and control chickens.

(A) Overview of the study design. The lung cell suspension from three chickens were mixed together as the pulmonary cell pool for each treatment group. Equal number of MHC Class II and CD3 positive cells in each pulmonary cell pool were sorted out and mixed together as one sample for single-cell sequencing analysis. (B) t-Distributed Stochastic Neighbor Embedding (t-SNE) projection representing the 19 clusters of cells identified in the chicken pulmonary cell pools (unified set of control, H9N2 AIV and H5N1 AIV infection samples). (C) Heatmap showing the normalized expression (Z-score) of characteristic genes in each cluster. (D) Cell type annotation and dot plot representing characteristic genes (y-axis) in each cluster (x-axis). Dot size represents the proportion of cells in the cluster that express the gene; intensity indicates the mean expression level (Z-score) in the cells, relative to those from other clusters. (E) Uniform Manifold Approximation and Projection (UMAP) displaying all identified cell types. (F) Table displaying the total contribution of each cell type aggregated for the control, H5N1 group and H9N2 group samples in percentage of prepared cell suspension, respectively. (G) Gating of macrophages with the KUL01⁺ (PE) and MHC Class II⁺ (FITC) antibodies. (H) The percentage or number of macrophages from lung single cell suspensions in the H5N1 group, H9N2 group and Control group, respectively. The data were collected from three biological samples. Statistical analysis was performed using one-way ANOVA. *P < 0.05, **P < 0.01, ***P < 0.001.

Fig 2. Global infection signature of cell types in the lung after H9N2 or H5N1 AIV infection.

Histogram showing the number of up-regulated (red) and down-regulated DEGs (green) in H5N1-infected cells (A) or H9N2-infected cells (D) compared to control cells within each cell type. Heatmap showing the normalized expression (Z-score) of the top DEGs in H5N1-infected cells (B) or H9N2-infected cells (E) compared to control cells within each cell type. Histogram showing the significantly up-regulated DEGs (log2 fold change≥0.36, and p value_ adj≤0.05) in each cell type enriched in the gene ontology term of “defense response to virus” (GO: 0051607). The ranking of genes from top to bottom is based on the mean expression level in H5N1-infected cells (C) or H9N2-infected cells (F) compared to control cells within each cell type.

Fig 3. Viral load detection within various cell populations of H5N1 group, H9N2 group and Control group.

(A) t-Distributed Stochastic Neighbor Embedding (t-SNE) projection representing 16 cell types. t-SNE displaying the normalized expression (Z-score) of viral genes in control cells (B), H9N2-infected cells (C), and H5N1-infected cells (D). Violin plots showing the expression levels of H5N1 AIV genes (E) or H9N2 AIV genes (F) in various cell types. (G) The cells in various cell types susceptible to AIV infection were divided into highly infected cells (represented by I, total UMI counts of viral transcripts ≥ 8), potential or lowly infected cells (represented by P, total UMI counts of viral transcripts ≥ 1), and undetected cells (represented by N, UMI counts of viral transcripts = 0). The percentages of highly infected cells (brown), potential or lowly infected cells (yellow), and undetected cells (light yellow) were shown in y axis.

Fig 4. The landscape of inflammatory response within each cell type in the lung after H5N1 or H9N2 AIV infection.

(A) The sum UMI counts expression of host 301 genes related to inflammatory response in different cell types (X-axis) (GO: 0006954). The dots indicate the cells from different groups, colored according to the samples. (B) Up-regulated genes (log2 fold change ≥0.36) in each cell type of H5N1 group enriched in the gene ontology term of “inflammatory response”. The ranking of genes from top to bottom is based on the mean expression level in each cell type. (C) Up-regulated genes (log2 fold change ≥0.36) in each cell type of H9N2 group enriched in the gene ontology term of “inflammatory response”. The ranking of genes from top to bottom is based on the mean expression level in each cell type.

Fig 5. The key immune cells and genes contribute to the H5N1 AIV-driven pneumonia.

(A) The normalized expression (UMI counts) of pro-inflammatory genes including IL6, CCL19, CCL4, CXCL13, IL1β, IL8, and TNFAIP3 in different cell populations. (B) Pearson’s Correlation analysis between the SMART-Seq2 data of macrophages (KUL01⁺CLASS II⁺) and lung clusters in scRNA-seq based on levels of gene expression. (C) Analysis expression of 21 differentially expressed genes (DEGs) in macrophages of single-cell lung suspensions from H9N2 AIV infected chickens at 3DPI by qRT-PCR. (D) Analysis expression of 21 DEGs in macrophages of single-cell lung suspensions from H5N1 AIV infected chickens at 1DPI by qRT-PCR. Total RNA of sorted macrophages was extracted from three chickens of the two infection groups and control groups, respectively. The data were collected from three biological samples, and each sample was tested in triplicate. The results are presented as mean ± SEM. Statistical comparisons were performed with paired t-test, and significance was assessed as P-values using GraphPad Prism. *P < 0.05, **P < 0.01, ***P < 0.001. (E) Predicted interaction map through CCL4, CCL19, and CXCL13 after H5N1 AIV challenge, respectively. Purple line indicates interactions emerging only after H5N1 AIV challenge.