Lost microbes of COVID-19: Bifidobacterium, Faecalibacterium depletion and decreased microbiome diversity associated with SARS-CoV-2 infection severity

Abstract

Objective: The study objective was to compare gut microbiome diversity and composition in SARS-CoV-2 PCR-positive patients whose symptoms ranged from asymptomatic to severe versus PCR-negative exposed controls.

Design: Using a cross-sectional design, we performed shotgun next-generation sequencing on stool samples to evaluate gut microbiome composition and diversity in both patients with SARS-CoV-2 PCR-confirmed infections, which had presented to Ventura Clinical Trials for care from March 2020 through October 2021 and SARS-CoV-2 PCR-negative exposed controls. Patients were classified as being asymptomatic or having mild, moderate or severe symptoms based on National Institute of Health criteria. Exposed controls were individuals with prolonged or repeated close contact with patients with SARS-CoV-2 infection or their samples, for example, household members of patients or frontline healthcare workers. Microbiome diversity and composition were compared between patients and exposed controls at all taxonomic levels.

Results: Compared with controls (n=20), severely symptomatic SARS-CoV-2-infected patients (n=28) had significantly less bacterial diversity (Shannon Index, p=0.0499; Simpson Index, p=0.0581), and positive patients overall had lower relative abundances of Bifidobacterium (p<0.0001), Faecalibacterium (p=0.0077) and Roseburium (p=0.0327), while having increased Bacteroides (p=0.0075). Interestingly, there was an inverse association between disease severity and abundance of the same bacteria.

Conclusion: We hypothesise that low bacterial diversity and depletion of Bifidobacterium genera either before or after infection led to reduced proimmune function, thereby allowing SARS-CoV-2 infection to become symptomatic. This particular dysbiosis pattern may be a susceptibility marker for symptomatic severity from SARS-CoV-2 infection and may be amenable to preinfection, intrainfection or postinfection intervention.

Trial registration number: NCT04031469 (PCR-) and 04359836 (PCR+).

Keywords: BACTERIAL INFECTION; BIFIDOBACTERIA; ENTERIC BACTERIAL MICROFLORA; INTESTINAL MICROBIOLOGY.

Conflict of interest statement

Competing interests: SH declares that she has pecuniary interest in Topelia Pty Ltd in Australia, and Topelia Pty Ltd in USA where development of COVID-19 preventative/treatment options is being pursued. She has also filed patents relevant to Coronavirus treatments. She is the founder and owner of Microbiome research foundation, Progenabiome and Ventura Clinical Trials. TJB declares that he has pecuniary interest in Topelia Pty Ltd in Australia, and Topelia Therapeutics Inc. in USA developing COVID-19 preventative/treatment medications. He has also filed patents relevant to COVID-19 treatments. SD declares she has corporate affiliation to McKesson Specialty Health/Ontada and North End Advisory, LLC. SD is unaware of SARS-CoV-2 and microbiome projects and not directly involved in COVID-19 relevant projects at McKesson, but they may exist. AJP and BDB have corporate affiliations to Progenabiome. EMMQ serves as a consultant to Precisionbiotics, Novazymes, Salix, Biocodex and Axon Pharma and has received research support from 4D Pharma.

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1

Distribution of bacterial relative abundance in various (A) phlya and (B) genera for exposed control (n=20, left) and SARS-CoV-2 positive subjects (n=50, right).

Figure 2

Diversity of gut microbiome composition of SARS-CoV-2 positive patients (severely symptomatic: n=28; moderately symptomatic: n=12; mildly symptomatic: n = 6; asymptomatic: n=4) versus exposed controls (n=20). (A) Shannon index (p=0.0499), (B) Simpson index (p=0.0581). Differences between severely symptomatic positive and exposed negative controls were analysed via Kruskal-Wallis test Dunn’s post-hoc, correcting for multiple comparisons, showing significant for Shannon index at p=0.0201.

Figure 3

Graphic of relative abundance of the 12 most common (A) families and (B) genera. The top group represents the SARS-CoV-2 positive samples (n=50), stratified by severity. The bottom group represents the exposed control samples (n=20). The coloured boxes represent the fraction of the entire rectangle composed of the given family/genera of bacteria.

Figure 4

Diagram of taxa comparing the gut microbiome of SARS-CoV-2 patients and exposed controls. Red or green background indicates a significant depletion or increase (due to positivity or severity), respectively, of the genus or species in SARS-CoV-2 positive subjects.

Figure 5

Relative abundance of Bifidobacterium in SARS-CoV-2 positive patients (n=50) versus SARS-CoV-2 negative exposed controls (n=20). Data are plotted as (A) mean with error bars for 95% CI and (B) individual points of relative abundance for varying SARS-CoV-2 infection severity. Analysed via Kruskal-Wallis test, there were significant reductions in Bifidobacterium relative abundance for severely (p<0.0001) and moderately (p=0.0002) symptomatic patients. Subjects 1–28 = severely symptomatic; subjects 29–40 = moderately symptomatic; subjects 41–46 = mildly symptomatic subjects; subjects 47–50 = asymptomatic; subjects 51–70 = exposed control. Figure A, B depicts same data.

Figure 6

SARS-CoV-2 positive patients’ microbiome is more similar to each other than to that of exposed controls. (A) Weighted UniFrac distance matrix of phylum level SARS-CoV-2 positive (n=50) and exposed negative control samples (n=20). Distance of microbiome differences increases with increasing blue colour intensity (see legend top right). The centre of the diagram consists of negative subjects on both axis and is yellow indicative of less distance (ie, lessdifference in microbiome). The central area of the left as well as central-top side of diagram, consists of negative subjects on one axis and positive on the other, and are darker blue, indicative of more distance (more difference in microbiome). (B) Principal component analysis of microbiota from SARS-CoV-2 positive (n=50) and exposed negative controls (n=20). Dots closer in distance are more similar in microbiome composition. Axes depict the per cent of variance explained by principal component (PC) 1 and 2. Plots are based on bacterial genera relative abundance profiles.

Figure 7

Potential mechanism for cytokine storm and immune hyper-response in SARS-CoV-2 positive patients. In individuals infected with SARS-CoV-2, the macrophages become activated; these in turn activate T-cells, additional macrophages, and neutrophils―all of which release cytokines, including TNF-α. Bifidobacterium, when present in sufficient numbers, can bind to TNF-α and prevent the subsequent cytokine storm. Therefore, patients with a bifidobacterial dysbiosis characterised by low levels of Bifidobacterium lack this line of defense, which may lead to a cytokine storm.