SARS-CoV-2 infection in nonhuman primates alters the composition and functional activity of the gut microbiota.

The current pandemic of coronavirus disease (COVID) 2019 constitutes a global public health issue. Regarding the emerging importance of the gut-lung axis in viral respiratory infections, analysis of the gut microbiota's composition and functional activity during a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection might be instrumental in understanding and controling COVID 19. We used a nonhuman primate model (the macaque), that recapitulates mild COVID-19 symptoms, to analyze the effects of a SARS-CoV-2 infection on dynamic changes of the gut microbiota. 16S rRNA gene profiling and analysis of ß diversity indicated significant changes in the composition of the gut microbiota with a peak at 10-13 days post-infection (dpi). Analysis of bacterial abundance correlation networks confirmed disruption of the bacterial community at 10-13 dpi. Some alterations in microbiota persisted after the resolution of the infection until day 26. Some changes in the relative bacterial taxon abundance associated with infectious parameters. Interestingly, the relative abundance of Acinetobacter (Proteobacteria) and some genera of the Ruminococcaceae family (Firmicutes) was positively correlated with the presence of SARS-CoV-2 in the upper respiratory tract. Targeted quantitative metabolomics indicated a drop in short-chain fatty acids (SCFAs) and changes in several bile acids and tryptophan metabolites in infected animals. The relative abundance of several taxa known to be SCFA producers (mostly from the Ruminococcaceae family) was negatively correlated with systemic inflammatory markers while the opposite correlation was seen with several members of the genus Streptococcus. Collectively, SARS-CoV-2 infection in a nonhuman primate is associated with changes in the gut microbiota's composition and functional activity.

Gut Dysbiosis during Influenza Contributes to Pulmonary Pneumococcal Superinfection through Altered Short-Chain Fatty Acid Production.

Secondary bacterial infections often complicate viral respiratory infections. We hypothesize that perturbation of the gut microbiota during influenza A virus (IAV) infection might favor respiratory bacterial superinfection. Sublethal infection with influenza transiently alters the composition and fermentative activity of the gut microbiota in mice. These changes are attributed in part to reduced food consumption. Fecal transfer experiments demonstrate that the IAV-conditioned microbiota compromises lung defenses against pneumococcal infection. In mechanistic terms, reduced production of the predominant short-chain fatty acid (SCFA) acetate affects the bactericidal activity of alveolar macrophages. Following treatment with acetate, mice colonized with the IAV-conditioned microbiota display reduced bacterial loads. In the context of influenza infection, acetate supplementation reduces, in a free fatty acid receptor 2 (FFAR2)-dependent manner, local and systemic bacterial loads. This translates into reduced lung pathology and improved survival rates of double-infected mice. Lastly, pharmacological activation of the SCFA receptor FFAR2 during influenza reduces bacterial superinfection.

Proposal of a consensus set of hypervariable mycobacterial interspersed repetitive-unit-variable-number tandem-repeat loci for subtyping of Mycobacterium tuberculosis Beijing isolates.

Mycobacterium tuberculosis Beijing strains represent targets of special importance for molecular surveillance of tuberculosis (TB), especially because they are associated with spread of multidrug resistance in some world regions. Standard 24-locus mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing lacks resolution power for accurately discriminating closely related clones that often compose Beijing strain populations. Therefore, we evaluated a set of 7 additional, hypervariable MIRU-VNTR loci for better resolution and tracing of such strains, using a collection of 535 Beijing isolates from six world regions where these strains are known to be prevalent. The typeability and interlaboratory reproducibility of these hypervariable loci were lower than those of the 24 standard loci. Three loci (2163a, 3155, and 3336) were excluded because of their redundant variability and/or more frequent noninterpretable results compared to the 4 other markers. The use of the remaining 4-locus set (1982, 3232, 3820, and 4120) increased the number of types by 52% (from 223 to 340) and reduced the clustering rate from 58.3 to 36.6%, when combined with the use of the standard 24-locus set. Known major clonal complexes/24-locus-based clusters were all subdivided, although the degree of subdivision varied depending on the complex. Only five single-locus variations were detected among the hypervariable loci of an additional panel of 92 isolates, representing 15 years of clonal spread of a single Beijing strain in a geographically restricted setting. On this calibrated basis, we propose this 4-locus set as a consensus for subtyping Beijing clonal complexes and clusters, after standard typing.