The use of massively parallel RNA sequencing (RNA-seq) has revealed insights into human and pathogen genomes and their evolution. Dual RNA-seq allows simultaneous dissection of host and pathogen genomes and strand-specific RNA-seq provides information about the polarity of the RNA. This is important in the case of negative-strand RNA viruses like influenza virus, which generate positive (complementary and mRNA) and negative-strand RNAs (genome) that differ in their potential to trigger innate immunity.
Here, researchers from the US FDA characterize interactions between human bronchial epithelial cells and three influenza A/H3N2 strains using strand-specific dual RNA-seq. The researchers focused on this subtype because of its epidemiological importance in causing significant morbidity and mortality during influenza epidemics. They report novel elements that differ between seasonal and laboratory strains highlighting the complexity of the host-virus interplay at the RNA level.
Strand-specific dual RNA-seq and IAV/H3N2 genomics
(A) Schematic of the RNA-seq approach. RNA samples extracted from mock- and IAV/H3N2-infected cells at time points 1, 6, and 24 h were subjected to a strand-specific RNA-seq assay which maintains the polarity of host and virus RNA. (B) Total RNA-seq read counts were mapped by sample (x axis) and read fraction distribution (y axis). IAV/H3N2 viral growth curves obtained by the following means: normalized viral reads, expressed as reads per million mapped reads (RPM) for IAV/H3N2-BR10/07 (blue), PER16/09 (red), and laboratory strain UD/72 (green) (C) and viral titer in BEAS-2B cells (D). (E) Principal component analysis demonstrating similarity between samples and biological replicates for each sample. (F) Temporal expression of influenza viral RNAs. Negative (top)- and positive (bottom)-stranded RNAs of each viral segment (gray boxes) expressed as reads per kilobase of sequence per million mapped reads (RPKM) normalized to total host reads. Viral segments are ordered according to size.