Uncover a microbiota signature of upper respiratory tract in patients with SARS-CoV-2 +

Abstract

The outbreak of Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, forced us to face a pandemic with unprecedented social, economic, and public health consequences. Several nations have launched campaigns to immunize millions of people using various vaccines to prevent infections. Meanwhile, therapeutic approaches and discoveries continuously arise; however, identifying infected patients that are going to experience the more severe outcomes of COVID-19 is still a major need, to focus therapeutic efforts, reducing hospitalization and mitigating drug adverse effects. Microbial communities colonizing the respiratory tract exert significant effects on host immune responses, influencing the susceptibility to infectious agents. Through 16S rDNAseq we characterized the upper airways' microbiota of 192 subjects with nasopharyngeal swab positive for SARS-CoV-2. Patients were divided into groups based on the presence of symptoms, pneumonia severity, and need for oxygen therapy or intubation. Indeed, unlike most of the literature, our study focuses on identifying microbial signatures predictive of disease progression rather than on the probability of infection itself, for which a consensus is lacking. Diversity, differential abundance, and network analysis at different taxonomic levels were synergistically adopted, in a robust bioinformatic pipeline, highlighting novel possible taxa correlated with patients' disease progression to intubation.

Figure 1

Alpha diversity analysis. Pielou’s and Richness metric at ASV, species and genus resolutions for Outcome (i.e., presence of symptoms) covariate.

Figure 2

Beta diversity analysis. Emperor plots with axis computed as PCoA; gender is represented as spheres for females and cones for males; main outcome is represented as blue for symptomatic and red for asymptomatic; size correspond to increasing level of pneumonia severity (none, mild, moderate, severe).

Figure 3

Network analysis. Cytoscape representation of the networks for the intubation covariate, at species and genus taxonomy level. Global networks refer to all the bacterial species identified in the samples while NA first neighborhood are the subnetworks connected to DA bacterial species. Nodes are the bacterial taxa, highlighted in yellow when DA; the size of the node indicates its degree. Edges are defined by the sparCC association values, with color representing their intensity, from -1 to 1, in a heat blue-red scale.

Figure 4

Overview of the bioinformatics pipeline.