Abstract
Background
The human nasopharynx is colonized by a diverse community of commensal microbiota linked to many respiratory diseases, yet their associations with the host remain unclear.Results
In this study, we introduced a dual-transcriptomics analysis strategy, which can characterize the host transcriptome and microbiome from nasal samples simultaneously. We applied this workflow to a local SARS-CoV-2 cohort with 76 asymptomatic infected patients, among whom 52 (68.42%) developed symptomatic infection during a 1-week follow-up period. Nasal swabs were collected from all 76 patients at enrollment and from 73 patients at one-week later follow-up. We detected a median of 8.94% reads that did not map to the human genome across all 149 samples, among which around half (median 49.68%) were successfully mapped to microbiome genome. Meta-transcriptomic analysis detected significantly higher SARS-related coronavirus loads in samples from the symptomatic group at enrollment (P = 0.004), and both groups showed decreased loads one week later (symptomatic, P = 0.001; asymptomatic, P = 0.035). Compared with benchmarking 16 S rRNA sequencing on 53 samples, our computational strategy showed high correlation of relative abundance in all top 20 genera (median Rho = 0.90, Pmax 2(fold change or FC) Conclusions
In summary, our dual-transcriptomic analysis strategy effectively characterized host-microbiome associations, offering insights into microbial contributions to respiratory diseases.