SARS-CoV-2 infection and viral load are associated with the upper respiratory tract microbiome

Abstract

Background: Little is known about the relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the respiratory virus responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic, and the upper respiratory tract (URT) microbiome.

Objective: We sought to compare the URT microbiome between SARS-CoV-2-infected and -uninfected adults and to examine the association of SARS-CoV-2 viral load with the URT microbiome during COVID-19.

Methods: We characterized the URT microbiome using 16S ribosomal RNA sequencing in 59 adults (38 with confirmed, symptomatic, mild to moderate COVID-19 and 21 asymptomatic, uninfected controls). In those with COVID-19, we measured SARS-CoV-2 viral load using quantitative reverse transcription PCR. We then examined the association of SARS-CoV-2 infection status and its viral load with the ⍺-diversity, β-diversity, and abundance of bacterial taxa of the URT microbiome. Our main models were all adjusted for age and sex.

Results: The observed species index was significantly higher in SARS-CoV-2-infected than in -uninfected adults (β linear regression coefficient = 7.53; 95% CI, 0.17-14.89; P = .045). In differential abundance testing, 9 amplicon sequence variants were significantly different in both of our comparisons, with Peptoniphilus lacrimalis, Campylobacter hominis, Prevotella 9 copri, and an Anaerococcus unclassified amplicon sequence variant being more abundant in those with SARS-CoV-2 infection and in those with high viral load during COVID-19, whereas Corynebacterium unclassified, Staphylococcus haemolyticus, Prevotella disiens, and 2 Corynebacterium_1 unclassified amplicon sequence variants were more abundant in those without SARS-CoV-2 infection and in those with low viral load during COVID-19.

Conclusions: Our findings suggest complex associations between SARS-CoV-2 and the URT microbiome in adults. Future studies are needed to examine how these viral-bacterial interactions can impact the clinical progression, severity, and recovery of COVID-19.

Keywords: 16S rRNA sequencing; COVID-19; SARS-CoV-2; coronavirus; microbiome; nasal; nasopharynx; respiratory.

Copyright © 2021 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Figures

Fig 1

Stacked bar chart of the relative abundance of the most common genera of the URT microbiome in adults with and without SARS-CoV-2 infection. The bars represent individual participant samples. Only the top 10 most abundant genera across all samples are shown. The other genera were collapsed into the “Other” category. The genera were ordered according to their relative abundance across all samples.

Fig 2

The ⍺- and β-diversity of the URT microbiome in adults with and without SARS-CoV-2 infection. A, The box-and-whisker plots show the mean (diamond), median (middle bar), first quartile (lower bar), third quartile (upper bar), minimum observation above the lowest fence (lower whisker), and maximum observation below the upper fence (upper whisker) of common ⍺-diversity metrics for each group. The P values for the comparison between groups using linear regression models including age and sex as covariates are also shown. B, The scatter plots show each participant’s microbial community composition (small circles) by group, as well as each group’s centroid (large circles) and 95% CI ellipses. The scatter plots were generated using nonmetric-multidimensional scaling (NMDS) ordination based on common β-diversity metrics. For ease of visualization, only 2 dimensions were used. The NMDS stress values and the P values for the comparison between groups using permutational multivariate ANOVA models including age and sex as covariates are also shown.

Fig 3

Differences in the abundance of taxa of the URT microbiome between adults with and without SARS-CoV-2 infection. Differential abundance testing was conducted using DESeq2 models at the ASV level including age and sex as covariates. A, Volcano plot of log2 fold change (FC) vs statistical significance. The red circles indicate ASVs that were significantly different between groups. Only the top 10 most significantly different ASVs are labeled. B, Bar plot depicting the log2 FCs and SEs for ASVs that were significantly different between groups.

Fig 4

Differences in the abundance of taxa of the URT microbiome between SARS-CoV-2–infected adults with and without high viral load (defined as a quantitative reverse transcription PCR cycle threshold value below the median for the detection of SARS-CoV-2 nucleocapside gene region 1 [N1]). Differential abundance testing was conducted using DESeq2 models at the ASV level including age and sex as covariates. A, Volcano plot of log2 fold change (FC) vs statistical significance. The red circles indicate ASVs that were significantly different between groups. Only the top 10 most significantly different ASVs are labeled. B, Bar plot depicting the log2 FCs and SEs for ASVs that were significantly different between groups. The asterisks indicate ASVs that were significantly different between groups and had a consistent direction of association in similar DESeq2 analyses that used a definition of high viral load based on a quantitative reverse transcription PCR cycle threshold value below the median for the detection of SARS-CoV-2 nucleocapside gene region 2 (N2). The striped bars indicate ASVs that were significantly different between groups and had a consistent direction of association in similar DESeq2 analyses comparing adults with and without SARS-CoV-2 infection.