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Gut Microbes ; 14(1): 2031840, 2022.
Article in English | MEDLINE | ID: covidwho-1692369


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. 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. 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 ssp.). 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. 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.

COVID-19/microbiology , Dysbiosis/microbiology , Gastrointestinal Microbiome , Aged , Bacteria/classification , Bacteria/genetics , Bacteria/isolation & purification , COVID-19/complications , COVID-19/mortality , Disease Progression , Dysbiosis/etiology , Feces/microbiology , Female , Humans , Male , Microbiota , Middle Aged , SARS-CoV-2 , Saliva/microbiology , Severity of Illness Index
Viruses ; 13(2)2021 02 03.
Article in English | MEDLINE | ID: covidwho-1060774


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.

COVID-19/immunology , Lymphocyte Activation , Mucosal-Associated Invariant T Cells/immunology , Adaptive Immunity , COVID-19/physiopathology , Cytokines/metabolism , Female , Granzymes/metabolism , HLA-DR Antigens , Humans , Interleukin-17/metabolism , Killer Cells, Natural/immunology , Male , Mucosal-Associated Invariant T Cells/metabolism , Severity of Illness Index , T-Lymphocyte Subsets/immunology , Tumor Necrosis Factor-alpha/metabolism