Gut microbiome dysbiosis during COVID-19 is associated with increased risk for bacteremia and microbial translocation

Abstract

The microbial populations in the gut microbiome have recently been associated with COVID-19 disease severity. However, a causal impact of the gut microbiome on COVID-19 patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. Antibiotics and other treatments during COVID-19 can potentially confound microbiome associations. We therefore first demonstrate that the gut microbiome is directly affected by SARS-CoV-2 infection in a dose-dependent manner in a mouse model, causally linking viral infection and gut microbiome dysbiosis. Comparison with stool samples collected from 97 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, paralleling our observations in the animal model. Specifically, we observed blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species in hospitalized COVID-19 patients. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data obtained from these patients suggest that bacteria translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID 19.

Figure 1.. SARS-CoV-2 infection causes gut microbiome alterations in mice.

a Timelines of fecal microbiota composition measured by 16S rRNA gene sequencing in mice infected with high (HD, 10⁴PFU), or low doses (LD, 10PFU) and in uninfected control mice (CTRL); time of infection=Day 1. Bars represent the composition of the 30 most abundant bacterial families per sample, blocks of samples correspond to an individual mouse’s time course. b α-diversity (Shannon) in the final samples per infection group; **: HDI95<0 BEST. c log₁₀-relative family abundances at the final time point. heavy breathing, reduced activity and hunched posture (Supplementary Table S1).

Figure 2.. Gut microbiome bacterial compositions during COVID-19 in patients from NYU Langone Health and Yale New Haven Hospital.

a Bacterial family composition in stool samples identified by 16S rRNA gene sequencing; bars represent the relative abundances of bacterial families; red circles indicate samples with single taxa >50%. Samples are sorted by the bacterial α-diversity (inverse Simpson index, b). c α-diversity in samples from NYU Langone Health and Yale New Haven Hospital. d Average phylum level composition per center. e-g Principal coordinate plots of all samples shown in a, labeled by center (e), most abundant bacterial family (f) and domination status of the sample (g).

Figure 3.. Microbiome composition is associated with secondary bloodstream infections.

a Principal coordinate plot of all samples, BSI associated samples in orange. b Posterior coefficient estimates from a Bayesian logistic regression regressing log₁₀ relative abundances of the top 10 most abundant bacterial genera on BSI status. c Posterior prediction of BSI risk based on bacterial composition contrasting the predicted risk of the average composition across all samples (red) with the risk estimated for the same composition changed such that Faecalibacterium was increased by 10% (blue). d Log₁₀ relative abundances of Faecalibacterium correlated with α-diversity, shaded region: 95%CI. e Sample compositions with BSIs indicated; left: Staphylococcus BSI associated samples; right: other BSI associated samples, the BSI causing microbial genus annotated in colors corresponding to the colors in stool microbiome compositions. f Rank analysis of abundance patterns in stool samples from different BSI categories; a filled circle indicates the calculated rank of the focal BSI category (row) in terms of the corresponding taxon stool abundance relative to samples from other BSI categories (only 5 out of 7 BSI categories are shown because fungal BSIs and the uninfected category have no corresponding bacterial stool abundances). g Posterior coefficients of the statistical association between bacterial order log₁₀ relative abundances of BSI causing bacteria and BSI events from a hierarchical Bayesian categorical regression; **: 95%HDI>0, *: 90%HDI>0, .:85% HDI>0.