Functional lower airways genomic profiling of the microbiome to capture active microbial metabolism.

Animals Bacteria / genetics Genomics Metagenome Mice Microbiota RNA, Ribosomal, 16S / genetics

Journal

The European respiratory journal
ISSN: 1399-3003
Titre abrégé: Eur Respir J
Pays: England
ID NLM: 8803460

Informations de publication

Date de publication:
07 2021
Historique:
received: 16 10 2020
accepted: 19 12 2020
pubmed: 16 1 2021
medline: 10 8 2021
entrez: 15 1 2021
Statut: epublish

Résumé

Microbiome studies of the lower airways based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short-chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary. Here we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole-genome shotgun (WGS) and RNA metatranscriptome sequencing. SCFAs were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed. Functional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome data were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing. Functional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.

Sections du résumé

BACKGROUND
Microbiome studies of the lower airways based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short-chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary.
METHODS
Here we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole-genome shotgun (WGS) and RNA metatranscriptome sequencing. SCFAs were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed.
RESULTS
Functional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome data were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing.
CONCLUSIONS
Functional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.

Identifiants

DOI: 10.1183/13993003.03434-2020 PMID: 33446604 PMC: PMC8643072
pubmed: 33446604
pii: 13993003.03434-2020
doi: 10.1183/13993003.03434-2020
pmc: PMC8643072
mid: NIHMS1687573
pii:
doi:

Substances chimiques

RNA, Ribosomal, 16S 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NHLBI NIH HHS
ID : R01 HL125816
Pays : United States
Organisme : NIAID NIH HHS
ID : K23 AI102970
Pays : United States
Organisme : NCI NIH HHS
ID : R37 CA244775
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI129958
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM111400
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM136312
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright ©The authors 2021. For reproduction rights and permissions contact permissions@ersnet.org.

Déclaration de conflit d'intérêts

Conflict of interest: I. Sulaiman has nothing to disclose. Conflict of interest: B.G. Wu has nothing to disclose. Conflict of interest: Y. Li has nothing to disclose. Conflict of interest: J-C. Tsay has nothing to disclose. Conflict of interest: M. Sauthoff has nothing to disclose. Conflict of interest: A.S. Scott has nothing to disclose. Conflict of interest: K. Ji has nothing to disclose. Conflict of interest: S.B. Koralov has nothing to disclose. Conflict of interest: M. Weiden has nothing to disclose. Conflict of interest: J.C. Clemente has nothing to disclose. Conflict of interest: D. Jones has nothing to disclose. Conflict of interest: Y.J. Huang has nothing to disclose. Conflict of interest: K.A. Stringer has nothing to disclose. Conflict of interest: L. Zhang has nothing to disclose. Conflict of interest: A. Geber has nothing to disclose. Conflict of interest: S. Banakis has nothing to disclose. Conflict of interest: L. Tipton has nothing to disclose. Conflict of interest: E. Ghedin has nothing to disclose. Conflict of interest: L.N. Segal has nothing to disclose.

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Auteurs

Imran Sulaiman (I)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.
ORCID: 0000-0003-1992-0280

Benjamin G Wu (BG)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.

Yonghua Li (Y)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.

Jun-Chieh Tsay (JC)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.

Maya Sauthoff (M)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.

Adrienne S Scott (AS)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.

Kun Ji (K)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.

Sergei B Koralov (SB)

Dept of Pathology, New York University School of Medicine, New York, NY, USA.

Michael Weiden (M)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA.

Jose C Clemente (JC)

Dept of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Drew Jones (D)

Dept of Biochemistry and Molecular Pharmacology and Dept of Radiation Oncology, New York University School of Medicine, New York, NY, USA.
ORCID: 0000-0001-8732-9818

Yvonne J Huang (YJ)

Division of Pulmonary and Critical Care Medicine, Dept of Medicine, University of Michigan Medical School, Ann Arbor, MI, USA.

Kathleen A Stringer (KA)

Dept of Clinical Pharmacy, College of Pharmacy, and Division of Pulmonary and Critical Care Medicine, Dept of Medicine, School of Medicine, University of Michigan, Ann Arbor, MI, USA.
ORCID: 0000-0003-0238-7774

Lingdi Zhang (L)

Center for Genomics and Systems Biology, Dept of Biology, New York University, New York, NY, USA.

Adam Geber (A)

Center for Genomics and Systems Biology, Dept of Biology, New York University, New York, NY, USA.
ORCID: 0000-0003-3022-0525

Stephanie Banakis (S)

Center for Genomics and Systems Biology, Dept of Biology, New York University, New York, NY, USA.

Laura Tipton (L)

Center for Genomics and Systems Biology, Dept of Biology, New York University, New York, NY, USA.

Elodie Ghedin (E)

Center for Genomics and Systems Biology, Dept of Biology, New York University, New York, NY, USA.
Dept of Epidemiology, School of Global Public Health, New York University, New York, NY, USA.

Leopoldo N Segal (LN)

Division of Pulmonary, Critical Care, and Sleep Medicine, Dept of Medicine, New York University School of Medicine, New York, NY, USA Leopoldo.Segal@nyumc.org.
ORCID: 0000-0003-3559-9431

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questionsmedicales.fr › Eucaryotes › Animaux › Functional lower airways genomic profiling of...
questionsmedicales.fr › Bactéries › Functional lower airways genomic profiling of...
questionsmedicales.fr › Disciplines des sciences naturelles › Disciplines des sciences biologiques › Biologie › Génétique › Génomique › Functional lower airways genomic profiling of...
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questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Rodentia › Muridae › Murinae › Souris › Functional lower airways genomic profiling of...
questionsmedicales.fr › Environnement et santé publique › Environnement › Écosystème › Biodiversité › Biote › Microbiote › Functional lower airways genomic profiling of...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Acides nucléiques › ARN › ARN ribosomique › ARN ribosomique 16S › Functional lower airways genomic profiling of...