Microbial Composition of the Human Nasopharynx Varies According to Influenza Virus Type and Vaccination Status.


Journal

mBio
ISSN: 2150-7511
Titre abrégé: mBio
Pays: United States
ID NLM: 101519231

Informations de publication

Date de publication:
02 07 2019
Historique:
entrez: 4 7 2019
pubmed: 4 7 2019
medline: 24 4 2020
Statut: epublish

Résumé

Factors that contribute to enhanced susceptibility to severe bacterial disease after influenza virus infection are not well defined but likely include the microbiome of the respiratory tract. Vaccination against influenza, while having variable effectiveness, could also play a role in microbial community stability. We collected nasopharyngeal samples from 215 individuals infected with influenza A/H3N2 or influenza B virus and profiled the microbiota by target sequencing of the 16S rRNA gene. We identified signature taxonomic groups by performing linear discriminant analysis and effective size comparisons (LEfSe) and defined bacterial community types using Dirichlet multinomial mixture (DMM) models. Influenza infection was shown to be significantly associated with microbial composition of the nasopharynx according to the virus type and the vaccination status of the patient. We identified four microbial community types across the combined cohort of influenza patients and healthy individuals with one community type most representative of the influenza virus-infected group. We also identified microbial taxa for which relative abundance was significantly higher in the unvaccinated elderly group; these taxa include species known to be associated with pneumonia.

Identifiants

pubmed: 31266874
pii: mBio.01296-19
doi: 10.1128/mBio.01296-19
pmc: PMC6606809
pii:
doi:

Substances chimiques

DNA, Ribosomal 0
Influenza Vaccines 0
RNA, Ribosomal, 16S 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NIAID NIH HHS
ID : R21 AI124141
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI111598
Pays : United States

Informations de copyright

Copyright © 2019 Ding et al.

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Auteurs

Tao Ding (T)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA.

Timothy Song (T)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA.

Bin Zhou (B)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA.

Adam Geber (A)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA.

Yixuan Ma (Y)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA.

Lingdi Zhang (L)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA.

Michelle Volk (M)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA.

Shashi N Kapadia (SN)

Department of Medicine, Weill Cornell Medical College, New York, New York, USA.

Stephen G Jenkins (SG)

Department of Pathology, Weill Cornell Medical College, New York, New York, USA.

Mirella Salvatore (M)

Department of Medicine, Weill Cornell Medical College, New York, New York, USA mis2053@med.cornell.edu elodie.ghedin@nyu.edu.

Elodie Ghedin (E)

Center for Genomics & Systems Biology, Department of Biology, New York University, New York, New York, USA mis2053@med.cornell.edu elodie.ghedin@nyu.edu.
Department of Epidemiology, College of Global Public Health, New York University, New York, New York, USA.

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Classifications MeSH