Dynamic changes of gut and lung microorganisms during chronic obstructive pulmonary disease exacerbations

Abstract

Increasing evidence has indicated the intimate relationship between the gastrointestinal tract and respiratory tract. The microbial ecosystem has been confirmed to share key conceptual features with gut-lung microbiome disorder and dysregulation during chronic obstructive pulmonary disease (COPD) exacerbations. However, the dynamic changes of the gut-lung microbiome during COPD exacerbations and its potential role in disease etiology remain poorly understood. The present study investigated the dynamic changes of gut and lung microorganisms during acute exacerbation of chronic obstructive pulmonary disease (AECOPD). A longitudinal 16S ribosomal DNA survey of the gut and lung microbiome was completed on 90 feces and sputum samples collected from 15 subjects with AECOPD at three visits, which were defined as exacerbation, seven-day stable state. The present analysis revealed a dynamic gut-lung microbiota, where changes appeared to be associated with exacerbation events indicative of specific exacerbation phenotypes. Antibiotic and steroid treatments appeared to have differential effects on the gut-lung microbiome, and the microbiome was associated with disease progression, but not with severity. The abundance and diversity of the microbiome was strongly influenced by the disease progression and therapy. Using culture-independent methods to impact the gut and lung microbiota on AECOPD may be the key to understanding the interactions between the gut and lung, highlighting its potential as a biomarker, and possibly a target for future respiratory therapeutics.

Keywords: acute exacerbations of chronic obstructive pulmonary disease; dynamic changes; gut-lung; microbiome.

Figure 1

Alpha diversity analysis/Shannon‐Wiener of 90 samples. OTU with 97% similarity was used to calculate Shannon and Simpson values under different random samples with mothur, and curve curves were made with R language tools. The x‐coordinate is the number of sequences per sample, and the y‐coordinate is rarefaction measure. When the curve tends to be flat, it indicates that the sequencing data volume is large enough to reflect the majority of microbial information in the sample. The higher the y value is, the higher the community diversity is. The sequence number in the figure represents the sequence number of the sample. OTU, operational taxonomic unit

Figure 2

Alpha diversity analysis/Simpson of 90 samples. OTU with 97% similarity was used to calculate Simpson values under different random samples with mothur, and curve curves were made with R language tools. The x‐coordinate is the number of sequences per sample, and the y‐coordinate is rarefaction measure. When the curve tends to be flat, it indicates that the sequencing data volume is large enough to reflect the majority of microbial information in the sample. The higher the y value is, the less the community diversity is. The sequence number in the figure represents the sequence number of the sample. OTU, operational taxonomic unit

Figure 3

Relative abundance of core bacterial phyla in sputum at different periods day 1: acute phase, day 7: treatment phase; day 14: stability

Figure 4

Principal component analysis (PCA) used OTU, pc‐ord, or CANOCO with 97% similarity. PC1 and PC2, respectively, represent the suspected influencing factors for the deviation of the microbial composition of the two groups of 90 samples. The more similar the composition of the sample is, the closer the distance is reflected in the PCA diagram, and the sample shows the distribution of aggregation, indicating that the flora in feces and sputum is relatively similar. The sequence number in the figure represents the sequence number of the sample. OTU, operational taxonomic unit

Figure 5

Relative abundance of bacterial phyla in microbiota of faces samples (n = 45)