Analysis of sputum microbial flora in chronic obstructive pulmonary disease patients with different phenotypes during acute exacerbations

Association between oral microbiome diversity and chronic obstructive pulmonary disease in the US population

BACKGROUND

There is a dearth of population-based studies on the association between the diversity of the oral microbiome and the risk of chronic obstructive pulmonary disease (COPD). The study aims to investigate the association between oral microbiome diversity and COPD.

METHODS

In this cross-sectional study, data from the National Health and Nutrition Examination Survey (NHANES 2009-2012) were analyzed. The association between the oral microbiome α-diversity and COPD risk was examined via multivariable logistic regression, with Restricted cubic splines revealing potential non-linear trends. The β-diversity disparities between COPD and non-COPD groups were delineated using Principal Coordinate Analysis (PCoA) and Permutational Multivariate Analysis of Variance (PERMANOVA).

RESULTS

A total of 6061 participants were included in this study. For α-diversity, the observed ASVs were significantly associated with COPD risk (OR = 0.964, 95%CI: 0.936-0.993, P = 0.016). Similarly, Faith's phylogenetic Diversity showed a significant association with COPD risk (OR = 0.955, 95%CI: 0.919-0.993, P = 0.020). The Shannon-Weiner index was also associated with COPD risk (OR = 0.829, 95%CI: 0.702-0.981, P = 0.029). For β-diversity, PCoA and PERMANOVA analysis showed statistically significant differences in Bray-Curtis, unweighted, and weighted UniFrac distances (all P < 0.01) between the COPD and non-COPD groups.

CONCLUSIONS

Significant differences in oral microbiome α-diversity and β-diversity were found between COPD and non-COPD populations, with α-diversity (observed ASVs, Faith's Phylogenetic Diversity, Shannon-Weiner index) being negatively associated with the risk of COPD.

Analysis of the bronchoalveolar lavage fluid microbial flora in COPD patients at different lung function during acute exacerbation

There is a correlation between the dysbiosis of the respiratory microbiota and the occurrence, severity, frequency, and mortality of Chronic Obstructive Pulmonary Disease (COPD). However, it is not unclear if there are differences in the bronchoalveolar lavage fluid (BALF) microbiota among patients at differente lung function. In this study, BALF samples were collected from 70 COPD patients experiencing acute exacerbations (AECOPD). The patients were divided into a mild group (FEV1/pre ≥ 50; PFT I, n = 50) and a severe group (FEV1/pre < 50; PFT II, n = 20) according to the lung function: or a frequent exacerbation (FE, n = 41) group and a non-frequent exacerbation (NFE, n = 29) group according to their exacerbation history. Microbiota analysis of BALF samples was conducted using mNGS and bioinfromatic analysis. Compared to PFT I group, PFT II group exhibited a significant decrease in species diversity (Shannon index), as well as a significant reduction in total species count and richness (Chao1, ACE indices). NFE group demonstrated diversity similar to that of FE group. Conversely, the microbial diversity of NFE group was comparable to that of FE group. The most abundant bacterial genera were Streptococcus, Prevotella, Veillonella, Rod-shaped Bacillus, and Rothia. Aspergillus was the most dominant fungal genus in AECOPD. Lymphocryptovirus was the most prevalent virus in AECOPD.Compared to the PFT I group, Corynebacterium's abundance significantly increased in PFT II group. Furthermore, FE group showed a notable increase in Streptococcus mitis abundance relative to NFE group. Bubble plot analysis revealed a significant increase in Moraxella, Fusobacterium, Haemophilus, Pseudomonas, Streptomyces, and Klebsiella in PFT II group, including a notable increase in typical Veillonella, Actinomyces, and Gordonia. The NFE group exhibited a significant increase in Bacteroides and Prevotella's relative abundance. Spearman correlation analysis revealed strong positive correlations among certain microbial communities. There exists a significant variation in microbial composition across groups of AECOPD patients at different lung function. Specifically, patients with severe airflow limitations exhibit a significant reduction in microbial diversity. Additionally, distinct bacterial taxa are enriched in patients characterized by varying levels of airflow limitation and exacerbation frequency. These observations offer vital insights into the pathogenesis of AECOPD, suggesting a potentially crucial role for the microbiota in its development. Such findings pave the way for identifying potential therapeutic targets and intervention strategies, ultimately aiming to improve treatment outcomes for AECOPD patients.

Advancing pathogen and tumor copy number variation detection through simultaneous metagenomic next-generation sequencing: A comprehensive review

In clinical practice, timely and accurate diagnosis can effectively reduce unnecessary treatment, avoid high medical costs, and prevent adverse prognoses. However, some patients with malignant tumors and those with infection often exhibit similar symptoms, which are difficult to distinguish, posing challenges in accurate clinical diagnosis. Metagenomic next-generation sequencing (mNGS) technology has been widely applied to confirm the source of infection. Recent studies have shown that for pathogen detection, mNGS technology can be used to perform chromosomal copy number variations (CNVs) analysis in two different analytical pipelines using the same wet test. mNGS technology has further demonstrated its utility in not only the determination of pathogenic microorganisms but also of CNVs, thereby facilitating early differential diagnosis for malignant tumors. In this review, we aim to analyze the diagnostic performance of mNGS technology in the simultaneous detection of pathogenic microorganisms and CNVs in current clinical practice and discuss the advantages and limitations of mNGS-CNV dual-omics detection technology. Our review highlights the need for more large-scale prospective research data on current mNGS-CNV dual-omics detection technology to provide more evidence-based results for researchers and clinicians and to promote the greater role of this technology in future clinical practice.

A metagenomic next-generation sequencing (mNGS)-based analysis of bronchoalveolar lavage samples in patients with an acute exacerbation of chronic obstructive pulmonary disease

The role of the bronchoalveolar lavage fluid (BALF) microbiome in acute exacerbations of chronic obstructive pulmonary disease (AECOPD) remains unclear. The advent of the metagenomic next-generation sequencing (mNGS) has made it possible to reveal the complex microbiome composition of the respiratory tract. This study aimed to explore whether there are differences in the BALF microbiome of AECOPD patients with different lung functions. We enrolled 55 AECOPD patients and divided them into a mild group (n = 31) and a severe group (n = 24) according to their lung function. We collected BALF and submitted it to mNGS and bioinformatics analysis. At the species level, mNGS identified 264 bacteria, 13 fungi and 12 viruses in the mild group, and 174 bacteria, 6 fungi and 6 viruses in the severe group. Mixed bacterial and viral infection occurred in both groups. At the genus level, Rothia and Veillonella were more abundant in the mild group, while Pseudomonas and Staphylococcus were more abundant in the severe group. At the species level, compared with the mild group, the relative abundance of Haemophilus influenzae and Pseudomonas aeruginosa was increased in the severe group. Besides, the BALF microbiome composition was similar between the two groups, and there was no significant difference in α and β diversity. Forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) (%) showed no significant correlation with the Shannon or Simpson index. The microbiome abundance was different between the mild and severe groups; however, microbiome diversity was similar between the two groups. Based on our findings, Haemophilus influenzae and Pseudomonas aeruginosa may be the pathogenic bacteria that cause the difference in lung function in patients with AECOPD.

Spectrum and antimicrobial resistance in acute exacerbation of chronic obstructive pulmonary disease with pneumonia: a cross-sectional prospective study from Vietnam

BACKGROUND

Respiratory infections have long been recognized as a primary cause of acute exacerbation of chronic obstructive pulmonary disease (AE-COPD). Additionally, the emergence of antimicrobial resistance has led to an urgent and critical situation in developing countries, including Vietnam. This study aimed to investigate the distribution and antimicrobial resistance of bacteria in patients with AE-COPD using both conventional culture and multiplex real-time PCR. Additionally, associations between clinical characteristics and indicators of pneumonia in these patients were examined.

METHODS

This cross-sectional prospective study included 92 AE-COPD patients with pneumonia and 46 without pneumonia. Sputum specimens were cultured and examined for bacterial identification, and antimicrobial susceptibility was determined for each isolate. Multiplex real-time PCR was also performed to detect ten bacteria and seven viruses.

RESULTS

The detection rates of pathogens in AE-COPD patients with pneumonia were 92.39%, compared to 86.96% in those without pneumonia. A total of 26 pathogenic species were identified, showing no significant difference in distribution between the two groups. The predominant bacteria included Klebsiella pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, and Streptococcus pneumoniae, followed by Acinetobacter baumannii and Streptococcus mitis. There was a slight difference in antibiotic resistance between bacteria isolated from two groups. The frequency of H. influenzae was notably greater in AE-COPD patients who experienced respiratory failure (21.92%) than in those who did not (9.23%). S. pneumoniae was more common in patients with stage I (44.44%) or IV (36.36%) COPD than in patients with stage II (17.39%) or III (9.72%) disease. ROC curve analysis revealed that C-reactive protein (CRP) levels could distinguish patients with AE-COPD with and without pneumonia (AUC = 0.78).

CONCLUSION

Gram-negative bacteria still play a key role in the etiology of AE-COPD patients, regardless of the presence of pneumonia. This study provides updated evidence for the epidemiology of AE-COPD pathogens and the appropriate selection of antimicrobial agents in Vietnam.

Assessment and clinical utility of metagenomic next-generation sequencing for suspected lower respiratory tract infections

OBJECTIVES

This study aims to compare the diagnostic efficacy of metagenomic next-generation sequencing (mNGS) to traditional diagnostic methods in patients with lower respiratory tract infections (LRTIs), elucidate the etiological spectrum of these infections, and explore the impact of mNGS on guiding antimicrobial therapy.

METHODS

We retrospectively analyzed data from 128 patients admitted to the Respiratory Department of Anqing 116 Hospital between July 2022 and July 2023. All patients had undergone both mNGS and conventional microbiological techniques (CMT) for LRTI diagnosis. We assessed the diagnostic performance of these methods and examined the influence of mNGS on antimicrobial decision-making.

RESULTS

Overall, mNGS demonstrated superior sensitivity (96.8%) and accuracy (96.8%) compared to CMT. For Mycobacterium tuberculosis detection, the accuracy and sensitivity of mNGS was 88.8% and 77.6%, which was lower than the 94.7% sensitivity of the T-spot test and the 79.6% sensitivity of CMT. In fungal pathogen detection, mNGS showed excellent sensitivity (90.5%), specificity (86.7%), and accuracy (88.0%). Bacteria were the predominant pathogens detected (75.34%), with Mycobacterium tuberculosis (41.74%), Streptococcus pneumoniae (21.74%), and Haemophilus influenzae (16.52%) being most prevalent. Bacterial infections were most common (62.10%), followed by fungal and mixed infections (17.74%). Of the 118 patients whose treatment regimens were adjusted based on mNGS results, 102 (86.5%) improved, 7 (5.9%) did not respond favorably, and follow-up was lost for 9 patients (7.6%).

CONCLUSIONS

mNGS offers rapid and precise pathogen detection for patients with suspected LRTIs and shows considerable promise in diagnosing Mycobacterium tuberculosis and fungal infections. By broadening the pathogen spectrum and identifying polymicrobial infections, mNGS can significantly inform and refine antibiotic therapy.