Not to be sniffed at: repurposing existing RNA-seq data to examine changes to human nasal microbiome composition in COVID-19 infection, compared to influenza and healthy controls

Abstract

Objective: The human microbiome is essential in maintaining healthy physiology; compositional changes have been implicated in numerous physical and mental diseases. Thus far, COVID-19 microbiome research has focused primarily upon gut and lung bacterial communities. However, the early stages of COVID-19 infection and immune response occur in the nasal epithelium. Therefore, investigating nasal microbiome changes in early-stage COVID-19 may yield key insights into the immune system mechanisms involved in progression from mild/no symptoms to systemic organ failure/death, why this occurs in certain individuals, and how it may be prevented with early warning. Patients and Methods: Here we repurposed existing RNA-seq data to characterise the human nasal microbiome in COVID-19 infected samples and compared the taxonomic profile to healthy control and influenza-infected control samples, to identify COVID-19 specific nasal microbiome changes and attempt to rationalise these in the context of what is already known regarding mechanisms of the immune response to COVID-19. Results: We demonstrate that existing RNA-seq reads from human nasal swabs can be repurposed to characterize the human nasal microbiome robustly and accurately in health, early-stage COVID-19, and influenza. We observe that nasal microbiome composition (presence and abundance of phyla, genera, and species) significantly differs between health and disease, and between COVID-19 and influenza. Conclusions: Our observed healthy nasal microbial profiles match the findings of previous research, demonstrating that repurposing existing RNA-seq data is as accurate as targeted methods for taxonomic classification. We also observed many differential changes in the nasal microbiome profile to be disease specific. This will be key to enabling the potential for differential diagnosis based upon nasal microbiome profiles in the future.

Keywords

• computational biology
• rna-seq
• classification
• microbiota
• covid-19
• influenza
• human.