Open AccessSignatures of COVID-19 Severity and Immune Response in the Respiratory Tract Microbiome
Author(s) -
Carter Merenstein,
Guanxiang Liang,
Samantha A. Whiteside,
Ana G Cobián-Güemes,
Madeline S Merlino,
Louis J. Taylor,
Abigail Glascock,
Kyle Bittinger,
Ceylan Tanes,
Jevon Graham-Wooten,
Layla A. Khatib,
Ayannah S. Fitzgerald,
Shantan Reddy,
Amy E. Baxter,
Josephine R. Giles,
Derek A. Oldridge,
Nuala J. Meyer,
E. John Wherry,
John E. McGinniss,
Frederic D. Bushman,
Ronald G. Collman
Publication year - 2021
Publication title -
mbio
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.562
H-Index - 121
eISSN - 2161-2129
pISSN - 2150-7511
DOI - 10.1128/mbio.01777-21
Subject(s) - microbiome , dysbiosis , immunology , immune system , respiratory tract , disease , medicine , respiratory tract infections , biology , respiratory system , bioinformatics
ABSTRACT Viral infection of the respiratory tract can be associated with propagating effects on the airway microbiome, and microbiome dysbiosis may influence viral disease. Here, we investigated the respiratory tract microbiome in coronavirus disease 2019 (COVID-19) and its relationship to disease severity, systemic immunologic features, and outcomes. We examined 507 oropharyngeal, nasopharyngeal, and endotracheal samples from 83 hospitalized COVID-19 patients as well as non-COVID patients and healthy controls. Bacterial communities were interrogated using 16S rRNA gene sequencing, and the commensal DNA viruses Anelloviridae and Redondoviridae were quantified by qPCR. We found that COVID-19 patients had upper respiratory microbiome dysbiosis and greater change over time than critically ill patients without COVID-19. Oropharyngeal microbiome diversity at the first time point correlated inversely with disease severity during hospitalization. Microbiome composition was also associated with systemic immune parameters in blood, as measured by lymphocyte/neutrophil ratios and immune profiling of peripheral blood mononuclear cells. Intubated patients showed patient-specific lung microbiome communities that were frequently highly dynamic, with prominence of Staphylococcus . Anelloviridae and Redondoviridae showed more frequent colonization and higher titers in severe disease. Machine learning analysis demonstrated that integrated features of the microbiome at early sampling points had high power to discriminate ultimate level of COVID-19 severity. Thus, the respiratory tract microbiome and commensal viruses are disturbed in COVID-19 and correlate with systemic immune parameters, and early microbiome features discriminate disease severity. Future studies should address clinical consequences of airway dysbiosis in COVID-19, its possible use as biomarkers, and the role of bacterial and viral taxa identified here in COVID-19 pathogenesis.