Association of sputum microbiome with clinical outcome of initial antibiotic treatment in hospitalized patients with acute exacerbations of COPD

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

BACKGROUND

Increasing studies have shown that the imbalance of the respiratory microbial flora is related to the occurrence of COPD, the severity and frequency of exacerbations and mortality.However, it remains unclear how the sputum microbial flora differs during exacerbations in COPD patients manifesting emphysema phenotype, chronic bronchitis with emphysema phenotype and asthma-COPD overlap phenotype.

METHODS

Sputum samples were obtained from 29 COPD patients experiencing acute exacerbations who had not received antibiotics or systemic corticosteroids within the past four weeks.Patients were divided into three groups;emphysema phenotype(E);chronic bronchitis with emphysema phenotype(B+E) and asthma-COPD overlap phenotype(ACO).We utilized metagenomic Next Generation Sequencing (mNGS) technology to analyze the sputum microbial flora in COPD patients with different phenotypes during exacerbations.

RESULTS

There was no significant difference in alpha diversity and beta diversity among three groups.The microbial flora composition was similar in all three groups during exacerbations except for a significant increase in Streptococcus mitis in ACO.Through network analysis,we found Candidatus Saccharibacteria oral taxon TM7x and Fusobacterium necrophorum were the core nodes of the co-occurrence network in ACO and E respectively.They were positively correlated with some species and play a synergistic role.In B+E,Haemophilus pittmaniae and Klebsiella pneumoniae had a synergistic effect.Besides,some species among the three groups play a synergistic or antagonistic role.Through Spearman analysis,we found the relative abundance of Streptococcus mitis was negatively correlated with the number of hospitalizations in the past year(r = -0.410,P = 0.027).We also observed that the relative abundance of Prevotella and Prevotella melaninogenica was negatively correlated with age(r = -0.534,P = 0.003;r = -0.567,P = 0.001),while the relative abundance of Streptococcus oralis and Actinomyces odontolyticus was positively correlated with age(r = 0.570,P = 0.001;r = 0.480,P = 0.008).In addition,the relative abundance of Prevotella melaninogenica was negatively correlated with peripheral blood neutrophil ratio and neutrophil to lymphocyte ratio(r = -0.479,P = 0.009;r = -0.555,P = 0.002),while the relative abundance of Streptococcus sanguinis was positively correlated with peripheral blood neutrophil ratio and neutrophil to lymphocyte ratio (r = 0.450,P = 0.014;r = 0.501,P = 0.006).There was also a significant positive correlation between Oribacterium and blood eosinophil counts(r = 0.491,P = 0.007).

CONCLUSION

Overall,we analyzed the sputum microbiota of COPD patients with different phenotypes and its relationship with clinical indicators, and explored the relationships between microbiota and inflammation in COPD.We hope to alter the prognosis of patients by inhibiting specific bacterial taxa related to inflammation and using guide individualized treatment in the future research.

The application of multi-omics in the respiratory microbiome: Progresses, challenges and promises

The study of the respiratory microbiome has entered a multi-omic era. Through integrating different omic data types such as metagenome, metatranscriptome, metaproteome, metabolome, culturome and radiome surveyed from respiratory specimens, holistic insights can be gained on the lung microbiome and its interaction with host immunity and inflammation in respiratory diseases. The power of multi-omics have moved the field forward from associative assessment of microbiome alterations to causative understanding of the lung microbiome in the pathogenesis of chronic, acute and other types of respiratory diseases. However, the application of multi-omics in respiratory microbiome remains with unique challenges from sample processing, data integration, and downstream validation. In this review, we first introduce the respiratory sample types and omic data types applicable to studying the respiratory microbiome. We next describe approaches for multi-omic integration, focusing on dimensionality reduction, multi-omic association and prediction. We then summarize progresses in the application of multi-omics to studying the microbiome in respiratory diseases. We finally discuss current challenges and share our thoughts on future promises in the field.

The Lung Microbiome in COPD and Lung Cancer: Exploring the Potential of Metal-Based Drugs

Chronic obstructive pulmonary disease (COPD) and lung cancer 17 are two of the most prevalent and debilitating respiratory diseases worldwide, both associated with high morbidity and mortality rates. As major global health concerns, they impose a substantial burden on patients, healthcare systems, and society at large. Despite their distinct aetiologies, lung cancer and COPD share common risk factors, clinical features, and pathological pathways, which have spurred increasing research interest in their co-occurrence. One area of particular interest is the role of the lung microbiome in the development and progression of these diseases, including the transition from COPD to lung cancer. Exploring novel therapeutic strategies, such as metal-based drugs, offers a potential avenue for targeting the microbiome in these diseases to improve patient outcomes. This review aims to provide an overview of the current understanding of the lung microbiome, with a particular emphasis on COPD and lung cancer, and to discuss the potential of metal-based drugs as a therapeutic strategy for these conditions, specifically concerning targeting the microbiome.

Airway dysbiosis accelerates lung function decline in chronic obstructive pulmonary disease

Progressive lung function decline is a hallmark of chronic obstructive pulmonary disease (COPD). Airway dysbiosis occurs in COPD, but whether it contributes to disease progression remains unknown. Here, we show, through a longitudinal analysis of two cohorts involving four UK centers, that baseline airway dysbiosis in COPD patients, characterized by the enrichment of opportunistic pathogenic taxa, associates with a rapid forced expiratory volume in 1 s (FEV1) decline over 2 years. Dysbiosis associates with exacerbation-related FEV1 fall and sudden FEV1 fall at stability, contributing to long-term FEV1 decline. A third cohort in China further validates the microbiota-FEV1-decline association. Human multi-omics and murine studies show that airway Staphylococcus aureus colonization promotes lung function decline through homocysteine, which elicits a neutrophil apoptosis-to-NETosis shift via the AKT1-S100A8/A9 axis. S. aureus depletion via bacteriophages restores lung function in emphysema mice, providing a fresh approach to slow COPD progression by targeting the airway microbiome.

Respiratory microbiota and radiomics features in the stable COPD patients

BACKGROUNDS

The respiratory microbiota and radiomics correlate with the disease severity and prognosis of chronic obstructive pulmonary disease (COPD). We aim to characterize the respiratory microbiota and radiomics features of COPD patients and explore the relationship between them.

METHODS

Sputa from stable COPD patients were collected for bacterial 16 S rRNA gene sequencing and fungal Internal Transcribed Spacer (ITS) sequencing. Chest computed tomography (CT) and 3D-CT analysis were conducted for radiomics information, including the percentages of low attenuation area below - 950 Hounsfield Units (LAA%), wall thickness (WT), and intraluminal area (Ai). WT and Ai were adjusted by body surface area (BSA) to WT/[Formula: see text] and Ai/BSA, respectively. Some key pulmonary function indicators were collected, which included forced expiratory volume in one second (FEV1), forced vital capacity (FVC), diffusion lung carbon monoxide (DLco). Differences and correlations of microbiomics with radiomics and clinical indicators between different patient subgroups were assessed.

RESULTS

Two bacterial clusters dominated by Streptococcus and Rothia were identified. Chao and Shannon indices were higher in the Streptococcus cluster than that in the Rothia cluster. Principal Co-ordinates Analysis (PCoA) indicated significant differences between their community structures. Higher relative abundance of Actinobacteria was detected in the Rothia cluster. Some genera were more common in the Streptococcus cluster, mainly including Leptotrichia, Oribacterium, Peptostreptococcus. Peptostreptococcus was positively correlated with DLco per unit of alveolar volume as a percentage of predicted value (DLco/VA%pred). The patients with past-year exacerbations were more in the Streptococcus cluster. Fungal analysis revealed two clusters dominated by Aspergillus and Candida. Chao and Shannon indices of the Aspergillus cluster were higher than that in the Candida cluster. PCoA showed distinct community compositions between the two clusters. Greater abundance of Cladosporium and Penicillium was found in the Aspergillus cluster. The patients of the Candida cluster had upper FEV1 and FEV1/FVC levels. In radiomics, the patients of the Rothia cluster had higher LAA% and WT/[Formula: see text] than those of the Streptococcus cluster. Haemophilus, Neisseria and Cutaneotrichosporon positively correlated with Ai/BSA, but Cladosporium negatively correlated with Ai/BSA.

CONCLUSIONS

Among respiratory microbiota in stable COPD patients, Streptococcus dominance was associated with an increased risk of exacerbation, and Rothia dominance was relevant to worse emphysema and airway lesions. Peptostreptococcus, Haemophilus, Neisseria and Cutaneotrichosporon probably affected COPD progression and potentially could be disease prediction biomarkers.

Lung and Gut Microbiome in COPD

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide. The association between lung and gut microbiomes in the pathogenesis of COPD has been recently uncovered. The goal of this study was to discuss the role of the lung and gut microbiomes in COPD pathophysiology. A systematic search of the PubMed database for relevant articles submitted up to June 2022 was performed. We examined the association between the lung and gut microbiome dysbiosis, reflected in bronchoalveolar lavage (BAL), lung tissue, sputum, and feces samples, and the pathogenesis and progression of COPD. It is evident that the lung and gut microbiomes affect each other and both play a vital role in the pathogenesis of COPD. However, more research needs to be carried out to find the exact associations between microbiome diversity and COPD pathophysiology and exacerbation genesis. Another field that research should focus on is the impact of treatment interventions targeting the human microbiome in preventing COPD genesis and progression.

Sputum Microbiome and Chronic Obstructive Pulmonary Disease in a Rural Ugandan Cohort of Well-Controlled HIV Infection

Sub-Saharan Africa has increased morbidity and mortality related to chronic obstructive pulmonary disease (COPD). COPD among people living with HIV (PLWH) has not been well studied in this region, where HIV/AIDS is endemic. Increasing evidence suggests that respiratory microbial composition plays a role in COPD severity. Therefore, we aimed to investigate microbiome patterns and associations among PLWH with COPD in Sub-Saharan Africa. We conducted a cross-sectional study of 200 adults stratified by HIV and COPD in rural Uganda. Induced sputum samples were collected as an easy-to-obtain proxy for the lower respiratory tract microbiota. We performed 16S rRNA gene sequencing and used PICRUSt2 (version 2.2.3) to infer the functional profiles of the microbial community. We used a statistical tool to detect changes in specific taxa that searches and adjusts for confounding factors such as antiretroviral therapy (ART), age, sex, and other participant characteristics. We could cluster the microbial community into three community types whose distribution was shown to be significantly impacted by HIV. Some genera, e.g., Veillonella, Actinomyces, Atopobium, and Filifactor, were significantly enriched in HIV-infected individuals, while the COPD status was significantly associated with Gammaproteobacteria and Selenomonas abundance. Furthermore, reduced bacterial richness and significant enrichment in Campylobacter were associated with HIV-COPD comorbidity. Functional prediction using PICRUSt2 revealed a significant depletion in glutamate degradation capacity pathways in HIV-positive patients. A comparison of our findings with an HIV cohort from the United Kingdom revealed significant differences in the sputum microbiome composition, irrespective of viral suppression. IMPORTANCE Even with ART available, HIV-infected individuals are at high risk of suffering comorbidities, as shown by the high prevalence of noninfectious lung diseases in the HIV population. Recent studies have suggested a role for the respiratory microbiota in driving chronic lung inflammation. The respiratory microbiota was significantly altered among PLWH, with disease persisting up to 3 years post-ART initiation and HIV suppression. The community structure and diversity of the sputum microbiota in COPD are associated with disease severity and clinical outcomes, both in stable COPD and during exacerbations. Therefore, a better understanding of the sputum microbiome among PLWH could improve COPD prognostic and risk stratification strategies. In this study, we observed that in a virologically suppressed HIV cohort in rural Uganda, we could show differences in sputum microbiota stratified by HIV and COPD, reduced bacterial richness, and significant enrichment in Campylobacter associated with HIV-COPD comorbidity.

Applying Next-Generation Sequencing and Multi-Omics in Chronic Obstructive Pulmonary Disease

Microbiomics have significantly advanced over the last decade, driven by the widespread availability of next-generation sequencing (NGS) and multi-omic technologies. Integration of NGS and multi-omic datasets allow for a holistic assessment of endophenotypes across a range of chronic respiratory disease states, including chronic obstructive pulmonary disease (COPD). Valuable insight has been attained into the nature, function, and significance of microbial communities in disease onset, progression, prognosis, and response to treatment in COPD. Moving beyond single-biome assessment, there now exists a growing literature on functional assessment and host-microbe interaction and, in particular, their contribution to disease progression, severity, and outcome. Identifying specific microbes and/or metabolic signatures associated with COPD can open novel avenues for therapeutic intervention and prognosis-related biomarkers. Despite the promise and potential of these approaches, the large amount of data generated by such technologies can be challenging to analyze and interpret, and currently, there remains a lack of standardized methods to address this. This review outlines the current use and proposes future avenues for the application of NGS and multi-omic technologies in the endophenotyping, prognostication, and treatment of COPD.

The human lung microbiome-A hidden link between microbes and human health and diseases

Once thought to be sterile, the human lung is now well recognized to harbor a consortium of microorganisms collectively known as the lung microbiome. The lung microbiome is altered in an array of lung diseases, including chronic lung diseases such as chronic obstructive pulmonary disease, asthma, and bronchiectasis, acute lung diseases caused by pneumonia, sepsis, and COVID-19, and other lung complications such as those related to lung transplantation, lung cancer, and human immunodeficiency virus. The effects of lung microbiome in modulating host immunity and inflammation in the lung and distal organs are being elucidated. However, the precise mechanism by which members of microbiota produce structural ligands that interact with host genes and pathways remains largely uncharacterized. Multiple unique challenges, both technically and biologically, exist in the field of lung microbiome, necessitating the development of tailored experimental and analytical approaches to overcome the bottlenecks. In this review, we first provide an overview of the principles and methodologies in studying the lung microbiome. We next review current knowledge of the roles of lung microbiome in human diseases, highlighting mechanistic insights. We finally discuss critical challenges in the field and share our thoughts on broad topics for future investigation.

The current understanding and future directions for sputum microbiome profiling in chronic obstructive pulmonary disease

PURPOSE OF REVIEW

Next-generation sequencing (NGS) has deepened our understanding of the respiratory microbiome in health and disease. The number of microbiome studies employing sputum as an airway surrogate has continued to increase over the past decade to include multiple large multicentre and longitudinal studies of the microbiome in chronic obstructive pulmonary disease (COPD). In this review, we summarize the recent advances to our understanding of the bacteriome, virome and mycobiome in COPD.

RECENT FINDINGS

Diverse microbiome profiles are reported in COPD. The neutrophilic Haemophilus-predominant bacteriome remains a prominent COPD phenotype, relatively stable over time and during exacerbations. Studies of the virome remain limited but reveal a potential involvement of viruses and bacteriophages particularly during COPD exacerbations and advancing disease severity. Mycobiome signatures, even in stable COPD are associated with poorer clinical outcomes including mortality.

SUMMARY

The sputum microbiome in COPD is being increasingly recognized for its clinical relevance, even in the stable state. Future studies integrating microbial kingdoms holistically (i.e. bacterial, viral and fungal) will provide deeper insight into its functionality including the relevance of microbial interactions and effect of treatment on microbiome-associated clinical outcomes.

Informatic analysis of the pulmonary microecology in non-cystic fibrosis bronchiectasis at three different stages

This study explored the impact of pulmonary microecological changes on disease progression in non-cystic fibrosis bronchiectasis (nCFB). A careful search of the NCBI BioProject database revealed the 16S rRNA-based microbiological testing results of 441 pulmonary sputum samples from patients in the relatively stable (baseline), acute exacerbation, or recovery stage. After preliminary analysis and screening, we selected 152 samples for further analyses, including determination of the operational taxonomic unit (OTU) distribution at the phylum, class, order, family and genus levels, community structure, alpha diversity, beta diversity, microbial multivariables, correlations, and community structure after the abundances of intragroup samples were averaged. The recovery group showed significant differences in pulmonary microbiological changes (P < 0.05) compared with the other groups. There were 30 differentially abundant OTUs, with 27 and 7 at the genus and phylum levels, respectively. The Chao1 value of the recovery group was comparable to that of the baseline group, and the Shannon and Simpson values of the recovery group were the highest. Rhodococcus in Actinobacteria was positively correlated with Ochrobactrum in Firmicutes. The differences in pulmonary microecological changes at different nCFB stages may serve as a biologically predictive indicator of nCFB progression.

A Risk Prediction Model for Prolonged Length of Stay in Patients with Acute Exacerbations of Chronic Obstructive Pulmonary Disease: A Retrospective Study of 225 Patients in a Single Center in Kunming, China

Background

We aimed to develop an effective prediction model of prolonged length of stay (LOS) in patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD).

Material/Methods

We systematically enrolled 225 patients admitted for AECOPD to our hospital and divided them into a normal LOS group (≤7 days) and prolonged LOS group (>7 days). To analyze differences in laboratory data at different times, 3 logistic regression models were established. To develop the prediction model, all variables with statistical significance were included in the model. The area under the curve (AUC) was used to evaluate discrimination, and the Hosmer-Lemeshow test was used to assess the calibration of the model.

Results

Factors found to be independently associated with the increased risk of prolonged LOS included the use of corticosteroids during hospitalization, elevated HCO₃⁻, decreased pH, and reductions in platelets (PLTs) and procalcitonin (PCT) between the fourth and first day of hospitalization. The risk prediction model including these factors had an AUC of 0.795, suggesting the good discrimination of our model. The Hosmer-Lemeshow test also showed good calibration of the model, which confirmed its good predictive performance.

Conclusions

A clinical prediction model was developed with good predictive performance, which could help clinicians identify patients with a higher risk of prolonged LOS, help shorten hospital stay, reduce the disease burden of patients, and improve the outcomes of AECOPD.

Predicting the recurrence of chronic rhinosinusitis with nasal polyps using nasal microbiota

BACKGROUND

Recent studies have revealed that the nasal microbiota in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) is profoundly altered and is correlated with systemic inflammation. However, little is known regarding whether the microbiota can be utilized to predict nasal polyp recurrence. This study is aimed to determine whether altered nasal microbiota constituents could be used as biomarkers to predict CRSwNP recurrence.

METHODS

Nasal microbiota constituents were quantified and characterized using bacterial 16S ribosomal RNA gene sequencing. Selected features for least absolute shrinkage and selection operator regression-based predictors were the nasal microbiota community composition and CRSwNP patient clinical characteristics. The primary outcome was recurrence, which was determined post-admission.

RESULTS

By distinguishing recurrence-associated nasal microbiota taxa and exploiting the distinct nasal microbiota abundance between patients with recurrent and non-recurrent CRSwNP, we developed a predictive classifier for the diagnosis of nasal polyps' recurrence with 91.4% accuracy.

CONCLUSIONS

Key taxonomical features of the nasal microbiome could predict recurrence in CRSwNP patients. The nasal microbiome is an understudied source of clinical variation in CRSwNP and represents a novel therapeutic target for future prevention and treatment.

Investigation on the Pathological Mechanism of Frequent Exacerbators With Chronic Obstructive Pulmonary Disease Based on the Characteristics of Respiratory Flora

Chronic obstructive pulmonary disease (COPD) is a common obstructive respiratory disease characterized by persistent respiratory symptoms and limited airflow due to airway obstruction. The present study investigates the distribution characteristics of respiratory tract flora in both frequent and infrequent exacerbators of COPD. The 16S sequencing technique was adopted to differentiate the inherent differences of respiratory tract flora between frequent exacerbators and infrequent exacerbators. Additionally, cell counting kit 8 (CCK8), lactate dehydrogenase (LDH) test, flow cytometry, enzyme-linked immunosorbent assay (ELISA), and western blot were carried out in human bronchial epithelial cells cultured in vitro and the regulatory effects of differential flora were verified. The results revealed that the observed species index, Chao1 index, and the ACE estimator of COPD frequent exacerbators were markedly higher than those of COPD infrequent exacerbators. The top five strains of COPD frequent exacerbators included g_Streptococcus (15.565%), g_Prevotella (10.683%), g_Veillonella (6.980%), g_Haemophilus (5.601%), and g_Neisseria (4.631%). Veillonella parvula generated obvious cytotoxicity and substantially reduced the activity of human bronchial epithelial cells (p < 0.01). Furthermore, the results of flow cytometry indicated that the proportion of human bronchial epithelial cells in both the S phase and G2 phase decreased following Veillonella parvula treatment indicated that Veillonella parvula inhibited cell proliferation. Meanwhile, being treated using Veillonella parvula, the expressions of interleukin-1 (IL-1), IL-6, Tumor Necrosis Factor α (TNF-α), and p-nuclear factor kappa B (NF-κB) of the cells were increased markedly (p < 0.01). Taken together, the current research demonstrated that the relative abundance of Veillonella in COPD frequent exacerbators was higher than that of infrequent exacerbators. Veillonella parvula activated the inflammatory pathway, ultimately destroyed the cell viability, and greatly impaired the activity of human bronchial epithelial cells, thereby inhibiting cell proliferation.

Prevalence, Pattern, Risks Factors and Consequences of Antibiotic Resistance in COPD: A Systematic Review

A concern of antibiotic use in chronic obstructive pulmonary disease (COPD) is the emergence and propagation of antimicrobial resistance (AMR). A systematic review was conducted to determine prevalence, pattern, risk factors and consequences of AMR in COPD. Bibliographic databases were searched from inception to November 2020, with no language restrictions, including studies of any design that included patients with COPD and reported prevalence and pattern of AMR. 2748 unique titles and abstracts were identified, of which 63 articles, comprising 26,387 patients, met inclusion criteria. Forty-four (69.8%) studies were performed during acute exacerbation. The median prevalence of AMR ranged from 0-100% for Pseudomonas aeruginosa, Moraxella catarrhalis, Klebsiella pneumoniae and Acinetobacter baumannii. Median resistance rates of H influenzae and S pneumoniae were lower by comparison, with maximum rates ≤40% and ≤46%, respectively, and higher for Staphylococcus aureus. There was a trend towards higher rates of AMR in patients with poorer lung function and greater incidence of previous antibiotic exposure and hospitalisation. The impact of AMR on mortality was unclear. Data regarding antimicrobial susceptibility testing techniques and the impact of other risk factors or consequences of AMR were variable or not reported. This is the first review to systematically unify data regarding AMR in COPD. AMR is relatively common and strategies to optimise antibiotic use could be valuable to prevent the currently under-investigated potential adverse consequences of AMR.Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2021.2000957 .

Unmet needs in the management of exacerbations of chronic obstructive pulmonary disease

Exacerbations of chronic obstructive pulmonary disease (COPD) are episodes of acute worsening of respiratory symptoms that require additional therapy. These events play a pivotal role in the natural course of the disease and are associated with a progressive decline in lung function, reduced health status, a low physical activity level, tremendous health care costs, and increased mortality. Although most exacerbations have an infectious origin, the underlying mechanisms are heterogeneous and specific predictors of their occurrence in individual patients are currently unknown. Accurate prediction and early diagnosis of exacerbations is essential to develop novel targets for prevention and personalized treatments to reduce the impact of these events. Several potential biomarkers have previously been studied, these however lack specificity, accuracy and do not add value to the available clinical predictors. At present, microbial composition and host-microbiome interactions in the lung are increasingly recognized for their role in affecting the susceptibility to exacerbations, and may steer towards a novel direction in the management of COPD exacerbations. This narrative review describes the current challenges and unmet needs in the management of acute exacerbations of COPD. Exacerbation triggers, biological clusters, current treatment strategies, and their limitations, previously studied biomarkers and prediction tools, the lung microbiome and its role in COPD exacerbations as well as future directions are discussed.