No abstract

Coronavirus disease 2019 (COVID-19), caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), comprises mild courses of disease as well as progression to severe disease, characterised by lung and other organ failure. The immune system is considered to play a crucial role for the pathogenesis of COVID-19, although especially the contribution of innate-like T cells remains poorly understood. Here, we analysed the phenotype and function of mucosal-associated invariant T (MAIT) cells, innate-like T cells with potent antimicrobial effector function, in patients with mild and severe COVID-19 by multicolour flow cytometry. Our data indicate that MAIT cells are highly activated in patients with COVID-19, irrespective of the course of disease, and express high levels of proinflammatory cytokines such as IL-17A and TNFα ex vivo. Of note, expression of the activation marker HLA-DR positively correlated with SAPS II score, a measure of disease severity. Upon MAIT cell-specific in vitro stimulation, MAIT cells however failed to upregulate expression of the cytokines IL-17A and TNFα, as well as cytolytic proteins, that is, granzyme B and perforin. Thus, our data point towards an altered cytokine expression profile alongside an impaired antibacterial and antiviral function of MAIT cells in COVID-19 and thereby contribute to the understanding of COVID-19 immunopathogenesis.

Objective: There is a growing debate about the involvement of the gut microbiome in COVID-19, although it is not conclusively understood whether the microbiome has an impact on COVID-19, or vice versa, especially as analysis of amplicon data in hospitalized patients requires sophisticated cohort recruitment and integration of clinical parameters. Here, we analyzed fecal and saliva samples from SARS-CoV-2 infected and post COVID-19 patients and controls considering multiple influencing factors during hospitalization. Design: 16S rRNA gene sequencing was performed on fecal and saliva samples from 108 COVID-19 and 22 post COVID-19 patients, 20 pneumonia controls and 26 asymptomatic controls. Patients were recruited over the first and second corona wave in Germany and detailed clinical parameters were considered. Serial samples per individual allowed intra-individual analysis. Results: We found the gut and oral microbiota to be altered depending on number and type of COVID-19-associated complications and disease severity. The occurrence of individual complications was correlated with low-risk (e.g., Faecalibacterium prausznitzii) and high-risk bacteria (e.g., Parabacteroides). We demonstrated that a stable gut bacterial composition was associated with a favorable disease progression. Based on gut microbial profiles, we identified a model to estimate mortality in COVID-19. Conclusion: Gut microbiota are associated with the occurrence of complications in COVID-19 and may thereby influencing disease severity. A stable gut microbial composition may contribute to a favorable disease progression and using bacterial signatures to estimate mortality could contribute to diagnostic approaches. Importantly, we highlight challenges in the analysis of microbial data in the context of hospitalization.