Symptom-related sputum microbiota in stable chronic obstructive pulmonary disease

Wenqi Diao1 Department of Respiratory Medicine, Peking University Third Hospital, Beijing 100191, China, [email protected]

Ning Shen1 Department of Respiratory Medicine, Peking University Third Hospital, Beijing 100191, China, [email protected]

Yipeng Du1 Department of Respiratory Medicine, Peking University Third Hospital, Beijing 100191, China, [email protected]

John R Erb-Downward2 Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA

Xiaoyan Sun1 Department of Respiratory Medicine, Peking University Third Hospital, Beijing 100191, China, [email protected]

Chenxia Guo1 Department of Respiratory Medicine, Peking University Third Hospital, Beijing 100191, China, [email protected]

Qian Ke1 Department of Respiratory Medicine, Peking University Third Hospital, Beijing 100191, China, [email protected]

Gary B Huffnagle2 Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA;3 Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, USA

Margaret R Gyetko2 Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA

Bei He1 Department of Respiratory Medicine, Peking University Third Hospital, Beijing 100191, China, [email protected]Correspondence[email protected]

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Abstract

Background

The role of airway microbiota in COPD is highly debated. Symptomology assessment is vital for the management of clinically stable COPD patients; however, the link between symp toms and the airway microbiome is currently unknown.

Purpose

The present study aimed to evaluate the relationship among stable COPD patients.

Patients and methods

We conducted pyrosequencing of bacterial 16S rRNA using induced sputum samples in a Han Chinese cohort that included 40 clinically stable COPD patients and 19 healthy controls.

Results

Alterations in community composition and core bacte rial taxa (Neisseria subflava, etc.) were observed in patients with severe symptoms compared with controls. The co-occurrence network indicated that the key microbiota enriched in COPD patients showed higher expression in patients with severe symptoms. The association pattern of symptoms with the sputum microbiome was obviously different from that of lung function in COPD patients.

Conclusion

These findings broaden our insights into the relationship between the sputum microbiota and the symptom severity in COPD patients, emphasizing the role of symptoms in the airway microbiome, independent of lung function.

Keywords:

Supplementary materials

Figure S1 Community composition was not altered between controls and patients with different severity of lung function.

Notes: Unsupervised PCoA and PERMANOVA were used to determine the discrepancy of community level between controls, patients with different severity of lung function using Bray–Curtis distance. No statistical difference was identified between groups (control vs GOLD I, II, P=0.162; control vs GOLD III, IV, P=0.105; GOLD I, II vs GOLD III, IV, P=0.723).

Abbreviations: GOLD, Global Initiative for Obstructive Lung Disease; PCoA, principal coordinate analysis; PERMANOVA, permutational multivariate analysis of variance.

Figure S1 Community composition was not altered between controls and patients with different severity of lung function.Notes: Unsupervised PCoA and PERMANOVA were used to determine the discrepancy of community level between controls, patients with different severity of lung function using Bray–Curtis distance. No statistical difference was identified between groups (control vs GOLD I, II, P=0.162; control vs GOLD III, IV, P=0.105; GOLD I, II vs GOLD III, IV, P=0.723).Abbreviations: GOLD, Global Initiative for Obstructive Lung Disease; PCoA, principal coordinate analysis; PERMANOVA, permutational multivariate analysis of variance.

Figure S2 Community composition was not affected by the use of inhaled corticosteroid.

Notes: Unsupervised PCoA and PERMANOVA were used to determine the discrepancy of community level between controls and patients with or without the use of ICS using Bray–Curtis distance. No statistical difference was identified between groups (control vs ICS, P=0.221; control vs non-ICS, P=0.145; ICS vs non-ICS, P=0.957).

Abbreviations: ICS, inhaled corticosteroid; PCoA, principal coordinate analysis; PERMANOVA, permutational multivariate analysis of variance.

Figure S2 Community composition was not affected by the use of inhaled corticosteroid.Notes: Unsupervised PCoA and PERMANOVA were used to determine the discrepancy of community level between controls and patients with or without the use of ICS using Bray–Curtis distance. No statistical difference was identified between groups (control vs ICS, P=0.221; control vs non-ICS, P=0.145; ICS vs non-ICS, P=0.957).Abbreviations: ICS, inhaled corticosteroid; PCoA, principal coordinate analysis; PERMANOVA, permutational multivariate analysis of variance.

Figure S3 Potential contaminated OTUs in negative control.

Note: The potentially contaminated OTUs in sterile water and AE buffer were present, which showed extremely low abundance in experimental samples and did not include the previously identified core microbiota (Neisseria subflava, etc.).

Abbreviations: AE, acute exacerbation; OTU, operational taxonomic unit.

Figure S3 Potential contaminated OTUs in negative control.Note: The potentially contaminated OTUs in sterile water and AE buffer were present, which showed extremely low abundance in experimental samples and did not include the previously identified core microbiota (Neisseria subflava, etc.).Abbreviations: AE, acute exacerbation; OTU, operational taxonomic unit.

Table S1 Relationship between clinical index and sputum microbiome by PERMANOVA

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Acknowledgments

The authors thank Jie Li (BGI, Shenzhen, China) for advice on bioinformatics and statistical analyses in this study. The present study was funded by the National Natural Science Foundation of China (grant nos: 81270097, 81470235, and 81670034) and Beijing Medical University (grant nos: 20110176 and 20160529).

Author contributions

All authors declared their personal contributions to this manuscript: BH conducted the study design and critically revised the article; WD conducted bioinformatics analyses and interpretation and wrote the manuscript; NS and YD were involved in statistical analyses and enrolled subjects; XS and CG collected throat samples and performed lung function tests for the subjects; QK gathered clinical information from the subjects; and JRE-D, GBH, and MRG were involved in the study design. All authors contributed toward data analysis, drafting and revising the paper and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.