Figure 4.
Identification and functional annotations of respiratory syncytial virus (RSV) and microbiota-specific differentially expressed genes between patients with RSV and healthy control (HC) subjects. (A) Heat maps depict differentially expressed genes between HC subjects and each microbiota cluster (limma, stringent filter: P < 0.01, log2-fold change > 1.25, Benjamini–Hochberg multiple test correction), adjusted for age and sex. Normalized expression is indicated as overexpressed (red) or underexpressed (blue) compared with the median expression of HC subjects (yellow). Heat maps were scaled according to number of samples and transcripts per comparison. The highest number of differentially expressed transcripts was observed in the Streptococcus (STR; 1,435 genes) and Haemophilus influenzae (HPH) clusters (1,315 genes) compared with the other microbiota clusters. (B) Venn diagram showing the intersection between differentially expressed genes derived from pairwise comparisons between patients with RSV stratified by microbiome profiles and HC subjects (A). We observed a considerable overlap between the STR and HPH clusters (464 genes). In contrast, the Corynebacterium (COR, 323 genes), Moraxella (MOR, 651 genes), and Staphylococcus aureus clusters (STA, 207 genes) showed a small number of differentially expressed genes versus HC subjects. Using ingenuity pathway analysis, shared and cluster-specific genes were extracted and functionally annotated: (C) genes for each of the clusters were intersected and those shared between all or all but one clusters (209 genes; common RSV signature); (D) genes shared between or unique to the STR and HPH clusters (1,257 genes; shared STR/HPH signature); and (E) genes shared between COR, MOR, and STA, but not the STR and HPH clusters (258 genes; shared COR/MOR/STA signature), were extracted. For each gene list of interest, the 10 strongest associated over-/underexpressed pathways were visualized; Benjamini-Hochberg–corrected P values (q values) associated with a specific pathway were calculated using Fisher’s exact test and visualized on a log10 scale. (C) We hypothesized that the genes shared between all or four out of five clusters would represent the common RSV signature, as this feature is shared between all clusters. Indeed, we observed these genes were strongly associated with IFN signaling (q value = 8.1 × 10−8). (D) Genes shared between or unique to the HPH and STR clusters were involved (q value ranging from 6.5 × 10−4 to 5.9 × 10−6) in the activation of neutrophils (N-formylmethionyl-leucyl-phenylalanine [fMLP], triggering receptor expressed on myeloid cells [TREM]-1, IL-8, and IL-17A signaling) and macrophages (inducible nitric oxide synthase [iNOS] signaling and production of nitric oxide and reactive oxygen species [ROS]). In addition, genes related to the pattern recognition of bacteria and viruses were up-regulated, including Toll-like receptor (TLR) genes TLR4, TLR6, and TLR8. (E) Genes shared between COR, MOR, and STA, but not the STR and HPH clusters, were not significantly associated with any of the 10 highest-ranking canonical pathways (q = 0.48). EIF = eukaryotic initiation factor; mTOR = mechanistic target of rapamycin; PRRs = pattern recognition receptors; trx = transcripts.