Cargando…
Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures
Studying respiratory illness-specific microbial signatures and their interaction with other micro-residents could provide a better understanding of lung microbial ecology. Each respiratory illness has a specific disease etiology, however, so far no study has revealed disease—specific microbial marke...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889618/ https://www.ncbi.nlm.nih.gov/pubmed/33597669 http://dx.doi.org/10.1038/s41598-021-83524-2 |
_version_ | 1783652349199253504 |
---|---|
author | Gupta, Shashank Shariff, Malini Chaturvedi, Gaura Sharma, Agrima Goel, Nitin Yadav, Monika Mortensen, Martin S. Sørensen, Søren J. Mukerji, Mitali Chauhan, Nar Singh |
author_facet | Gupta, Shashank Shariff, Malini Chaturvedi, Gaura Sharma, Agrima Goel, Nitin Yadav, Monika Mortensen, Martin S. Sørensen, Søren J. Mukerji, Mitali Chauhan, Nar Singh |
author_sort | Gupta, Shashank |
collection | PubMed |
description | Studying respiratory illness-specific microbial signatures and their interaction with other micro-residents could provide a better understanding of lung microbial ecology. Each respiratory illness has a specific disease etiology, however, so far no study has revealed disease—specific microbial markers. The present study was designed to determine disease-specific microbial features and their interactions with other residents in chronic obstructive pulmonary diseases (stable and exacerbated), sarcoidosis, and interstitial lung diseases. Broncho-alveolar lavage samples (n = 43) were analyzed by SSU rRNA gene sequencing to study the alveolar microbiome in these diseases. A predominance of Proteobacteria followed by Firmicutes, Bacteroidetes, Actinobacteria, and Fusobacteria was observed in all the disease subsets. Shannon diversity was significantly higher in stable COPD when compared to exacerbated chronic obstructive pulmonary disease (ECOPD) (p = 0.0061), and ILD patient samples (p = 0.037). The lung microbiome of the patients with stable COPD was more diverse in comparison to ECOPD and ILD patients (p < 0.001). Lefse analysis identified 40 disease—differentiating microbial features (LDA score (log10) > 4). Species network analysis indicated a significant correlation (p < 0.05) of diseases specific microbial signature with other lung microbiome members. The current study strengthens the proposed hypothesis that each respiratory illness has unique microbial signatures. These microbial signatures could be used as diagnostic markers to differentiate among various respiratory illnesses. |
format | Online Article Text |
id | pubmed-7889618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78896182021-02-18 Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures Gupta, Shashank Shariff, Malini Chaturvedi, Gaura Sharma, Agrima Goel, Nitin Yadav, Monika Mortensen, Martin S. Sørensen, Søren J. Mukerji, Mitali Chauhan, Nar Singh Sci Rep Article Studying respiratory illness-specific microbial signatures and their interaction with other micro-residents could provide a better understanding of lung microbial ecology. Each respiratory illness has a specific disease etiology, however, so far no study has revealed disease—specific microbial markers. The present study was designed to determine disease-specific microbial features and their interactions with other residents in chronic obstructive pulmonary diseases (stable and exacerbated), sarcoidosis, and interstitial lung diseases. Broncho-alveolar lavage samples (n = 43) were analyzed by SSU rRNA gene sequencing to study the alveolar microbiome in these diseases. A predominance of Proteobacteria followed by Firmicutes, Bacteroidetes, Actinobacteria, and Fusobacteria was observed in all the disease subsets. Shannon diversity was significantly higher in stable COPD when compared to exacerbated chronic obstructive pulmonary disease (ECOPD) (p = 0.0061), and ILD patient samples (p = 0.037). The lung microbiome of the patients with stable COPD was more diverse in comparison to ECOPD and ILD patients (p < 0.001). Lefse analysis identified 40 disease—differentiating microbial features (LDA score (log10) > 4). Species network analysis indicated a significant correlation (p < 0.05) of diseases specific microbial signature with other lung microbiome members. The current study strengthens the proposed hypothesis that each respiratory illness has unique microbial signatures. These microbial signatures could be used as diagnostic markers to differentiate among various respiratory illnesses. Nature Publishing Group UK 2021-02-17 /pmc/articles/PMC7889618/ /pubmed/33597669 http://dx.doi.org/10.1038/s41598-021-83524-2 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Gupta, Shashank Shariff, Malini Chaturvedi, Gaura Sharma, Agrima Goel, Nitin Yadav, Monika Mortensen, Martin S. Sørensen, Søren J. Mukerji, Mitali Chauhan, Nar Singh Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures |
title | Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures |
title_full | Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures |
title_fullStr | Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures |
title_full_unstemmed | Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures |
title_short | Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures |
title_sort | comparative analysis of the alveolar microbiome in copd, ecopd, sarcoidosis, and ild patients to identify respiratory illnesses specific microbial signatures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889618/ https://www.ncbi.nlm.nih.gov/pubmed/33597669 http://dx.doi.org/10.1038/s41598-021-83524-2 |
work_keys_str_mv | AT guptashashank comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT shariffmalini comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT chaturvedigaura comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT sharmaagrima comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT goelnitin comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT yadavmonika comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT mortensenmartins comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT sørensensørenj comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT mukerjimitali comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures AT chauhannarsingh comparativeanalysisofthealveolarmicrobiomeincopdecopdsarcoidosisandildpatientstoidentifyrespiratoryillnessesspecificmicrobialsignatures |