Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures

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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.

In: Scientific Reports, Vol. 11, 3963, 2021.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Gupta, S, Shariff, M, Chaturvedi, G, Sharma, A, Goel, N, Yadav, M, Mortensen, MS, Sørensen, SJ, Mukerji, M & Chauhan, NS 2021, 'Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures', Scientific Reports, vol. 11, 3963. https://doi.org/10.1038/s41598-021-83524-2

APA

Gupta, S., Shariff, M., Chaturvedi, G., Sharma, A., Goel, N., Yadav, M., Mortensen, M. S., Sørensen, S. J., Mukerji, M., & Chauhan, N. S. (2021). Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures. Scientific Reports, 11, [3963]. https://doi.org/10.1038/s41598-021-83524-2

Vancouver

Gupta S, Shariff M, Chaturvedi G, Sharma A, Goel N, Yadav M et al. Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures. Scientific Reports. 2021;11. 3963. https://doi.org/10.1038/s41598-021-83524-2

Author

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. In: Scientific Reports. 2021 ; Vol. 11.

Bibtex

@article{4fae5f1a469743719c34996c976bb2ea,
title = "Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures",
abstract = "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.",
author = "Shashank Gupta and Malini Shariff and Gaura Chaturvedi and Agrima Sharma and Nitin Goel and Monika Yadav and Mortensen, {Martin S.} and S{\o}rensen, {S{\o}ren J.} and Mitali Mukerji and Chauhan, {Nar Singh}",
year = "2021",
doi = "10.1038/s41598-021-83524-2",
language = "English",
volume = "11",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "nature publishing group",

}

RIS

TY - JOUR

T1 - Comparative analysis of the alveolar microbiome in COPD, ECOPD, Sarcoidosis, and ILD patients to identify respiratory illnesses specific microbial signatures

AU - Gupta, Shashank

AU - Shariff, Malini

AU - Chaturvedi, Gaura

AU - Sharma, Agrima

AU - Goel, Nitin

AU - Yadav, Monika

AU - Mortensen, Martin S.

AU - Sørensen, Søren J.

AU - Mukerji, Mitali

AU - Chauhan, Nar Singh

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

U2 - 10.1038/s41598-021-83524-2

DO - 10.1038/s41598-021-83524-2

M3 - Journal article

C2 - 33597669

AN - SCOPUS:85100877937

VL - 11

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 3963

ER -

ID: 258374900