Parallel Analysis of Cystic Fibrosis Sputum and Saliva Reveals Overlapping Communities and an Opportunity for Sample Decontamination

The airway microbiome of persons with cystic fibrosis correlates with acquisition and microbiological outcomes of incident Stenotrophomonas maltophilia infection

Rationale

Chronic infection with Stenotrophomonas maltophilia in persons with cystic fibrosis (pwCF) has been linked to an increased risk of pulmonary exacerbations and lung function decline. We sought to establish whether baseline sputum microbiome associates with risk of S. maltophilia incident infection and persistence in pwCF.

Methods

pwCF experiencing incident S. maltophilia infections attending the Calgary Adult CF Clinic from 2010-2018 were compared with S. maltophilia-negative sex, age (+/-2 years), and birth-cohort-matched controls. Infection outcomes were classified as persistent (when the pathogen was recovered in ≥50% of cultures in the subsequent year) or transient. We assessed microbial communities from prospectively biobanked sputum using V3-V4 16S ribosomal RNA (rRNA) gene sequencing, in the year preceding (Pre) (n = 57), at (At) (n = 22), and after (Post) (n = 31) incident infection. We verified relative abundance data using S. maltophilia-specific qPCR and 16S rRNA-targeted qPCR to assess bioburden. Strains were typed using pulse-field gel electrophoresis.

Results

Twenty-five pwCF with incident S. maltophilia (56% female, median 29 years, median FEV1 61%) with 33 total episodes were compared with 56 uninfected pwCF controls. Demographics and clinical characteristics were similar between cohorts. Among those with incident S. maltophilia infection, sputum communities did not cluster based on infection timeline (Pre, At, Post). Communities differed between the infection cohort and controls (n = 56) based on Shannon Diversity Index (SDI, p = 0.04) and clustered based on Aitchison distance (PERMANOVA, p = 0.01) prior to infection. At the time of incident S. maltophilia isolation, communities did not differ in SDI but clustered based on Aitchison distance (PERMANOVA, p = 0.03) in those that ultimately developed persistent infection versus those that were transient. S. maltophilia abundance within sputum was increased in samples from patients (Pre) relative to controls, measuring both relative (p = 0.004) and absolute (p = 0.001). Furthermore, S. maltophilia abundance was increased in sputum at incident infection in those who ultimately developed persistent infection relative to those with transient infection, measured relatively (p = 0.04) or absolute (p = 0.04), respectively.

Conclusion

Microbial community composition of CF sputum associates with S. maltophilia infection acquisition as well as infection outcome. Our study suggests sputum microbiome may serve as a surrogate for identifying infection risk and persistence risk.

The implication of microbiome in lungs cancer: mechanisms and strategies of cancer growth, diagnosis and therapy

Available evidence illustrates that microbiome is a promising target for the study of growth, diagnosis and therapy of various types of cancer. Lung cancer is a leading cause of cancer death worldwide. The relationship of microbiota and their products with diverse pathologic conditions has been getting large attention. The novel research suggests that the microbiome plays an important role in the growth and progression of lung cancer. The lung microbiome plays a crucial role in maintaining mucosal immunity and synchronizing the stability between tolerance and inflammation. Alteration in microbiome is identified as a critical player in the progression of lung cancer and negatively impacts the patient. Studies suggest that healthy microbiome is essential for effective therapy. Various clinical trials and research are focusing on enhancing the treatment efficacy by altering the microbiome. The regulation of microbiota will provide innovative and promising treatment strategies for the maintenance of host homeostasis and the prevention of lung cancer in lung cancer patients. In the current review article, we presented the latest progress about the involvement of microbiome in the growth and diagnosis of lung cancer. Furthermore, we also assessed the therapeutic status of the microbiome for the management and treatment of lung cancer.

Microbial community organization designates distinct pulmonary exacerbation types and predicts treatment outcome in cystic fibrosis

Polymicrobial infection of the airways is a hallmark of obstructive lung diseases such as cystic fibrosis (CF), non-CF bronchiectasis, and chronic obstructive pulmonary disease. Pulmonary exacerbations (PEx) in these conditions are associated with accelerated lung function decline and higher mortality rates. An understanding of the microbial underpinnings of PEx is challenged by high inter-patient variability in airway microbial community profiles. We analyzed bacterial communities in 880 CF sputum samples and developed microbiome descriptors to model community reorganization prior to and during 18 PEx. We identified two microbial dysbiosis regimes with opposing ecology and dynamics. Pathogen-governed PEx showed hierarchical community reorganization and reduced diversity, whereas anaerobic bloom PEx displayed stochasticity and increased diversity. A simulation of antimicrobial treatment predicted better efficacy for hierarchically organized communities. This link between PEx type, microbiome organization, and treatment success advances the development of personalized clinical management in CF and, potentially, other obstructive lung diseases.

The Complex Role of the Microbiome in Non-Small Cell Lung Cancer Development and Progression

In recent years, there has been a growing interest in the relationship between microorganisms in the surrounding environment and cancer cells. While the tumor microenvironment predominantly comprises cancer cells, stromal cells, and immune cells, emerging research highlights the significant contributions of microbial cells to tumor development and progression. Although the impact of the gut microbiome on treatment response in lung cancer is well established, recent investigations indicate complex roles of lung microbiota in lung cancer. This article focuses on recent findings on the human lung microbiome and its impacts in cancer development and progression. We delve into the characteristics of the lung microbiome and its influence on lung cancer development. Additionally, we explore the characteristics of the intratumoral microbiome, the metabolic interactions between lung tumor cells, and how microorganism-produced metabolites can contribute to cancer progression. Furthermore, we provide a comprehensive review of the current literature on the lung microbiome and its implications for the metastatic potential of tumor cells. Additionally, this review discusses the potential for therapeutic modulation of the microbiome to establish lung cancer prevention strategies and optimize lung cancer treatment.

Emerging strategies to target virulence in Pseudomonas aeruginosa respiratory infections

Pseudomonas aeruginosa is an opportunistic pathogen that is responsible for infections in people living with chronic respiratory conditions, such as cystic fibrosis (CF) and non-CF bronchiectasis (NCFB). Traditionally, in people with chronic respiratory disorders, P. aeruginosa infection has been managed with a combination of inhaled and intravenous antibiotic therapies. However, due in part to the prolonged use of antibiotics in these people, the emergence of multi-drug resistant P. aeruginosa strains is a growing concern. The development of anti-virulence therapeutics may provide a new means of treating P. aeruginosa lung infections whilst also combatting the AMR crisis, as these agents are presumed to exert reduced pressure for the emergence of drug resistance as compared to antibiotics. However, the pipeline for developing anti-virulence therapeutics is poorly defined, and it is currently unclear as to whether in vivo and in vitro models effectively replicate the complex pulmonary environment sufficiently to enable development and testing of such therapies for future clinical use. Here, we discuss potential targets for P. aeruginosa anti-virulence therapeutics and the effectiveness of the current models used to study them. Focus is given to the difficulty of replicating the virulence gene expression patterns of P. aeruginosa in the CF and NCFB lung under laboratory conditions and to the challenges this poses for anti-virulence therapeutic development.

Realising respiratory microbiomic meta-analyses: time for a standardised framework

In microbiome fields of study, meta-analyses have proven to be a valuable tool for identifying the technical drivers of variation among studies and results of investigations in several diseases, such as those of the gut and sinuses. Meta-analyses also represent a powerful and efficient approach to leverage existing scientific data to both reaffirm existing findings and generate new hypotheses within the field. However, there are currently limited data in other fields, such as the paediatric respiratory tract, where extension of original data becomes even more critical due to samples often being difficult to obtain and process for a range of both technical and ethical reasons. Performing such analyses in an evolving field comes with challenges related to data accessibility and heterogeneity. This is particularly the case in paediatric respiratory microbiomics - a field in which best microbiome-related practices are not yet firmly established, clinical heterogeneity abounds and ethical challenges can complicate sharing of patient data. Having recently conducted a large-scale, individual participant data meta-analysis of the paediatric respiratory microbiota (n = 2624 children from 20 studies), we discuss here some of the unique barriers facing these studies and open and invite a dialogue towards future opportunities. Video Abstract.

The Cystic Fibrosis Upper and Lower Airway Metagenome

The microbial metagenome in cystic fibrosis (CF) airways was investigated by whole-genome shotgun sequencing of total DNA isolated from nasal lavage samples, oropharyngeal swabs, and induced sputum samples collected from 65 individuals with CF aged 7 to 50 years. Each patient harbored a personalized microbial metagenome unique in microbial load and composition, the exception being monocultures of the most common CF pathogens Staphylococcus aureus and Pseudomonas aeruginosa from patients with advanced lung disease. The sampling of the upper airways by nasal lavage uncovered the fungus Malassezia restricta and the bacterium Staphylococcus epidermidis as prominent species. Healthy and CF donors harbored qualitatively and quantitatively different spectra of commensal bacteria in their sputa, even in the absence of any typical CF pathogen. If P. aeruginosa, S. aureus, or Stenotrophomonas maltophilia belonged to the trio of the most abundant species in the CF sputum metagenome, common inhabitants of the respiratory tract of healthy subjects, i.e., Eubacterium sulci, Fusobacterium periodonticum, and Neisseria subflava, were present only in low numbers or not detectable. Random forest analysis identified the numerical ecological parameters of the bacterial community, such as Shannon and Simpson diversity, as the key parameters that globally distinguish sputum samples from CF and healthy donors. IMPORTANCE Cystic fibrosis (CF) is the most common life-limiting monogenetic disease in European populations and is caused by mutations in the CFTR gene. Chronic airway infections with opportunistic pathogens are the major morbidity that determines prognosis and quality of life in most people with CF. We examined the composition of the microbial communities of the oral cavity and upper and lower airways in CF patients across all age groups. From early on, the spectrum of commensals is different in health and CF. Later on, when the common CF pathogens take up residence in the lungs, we observed differential modes of depletion of the commensal microbiota in the presence of S. aureus, P. aeruginosa, S. maltophilia, or combinations thereof. It remains to be seen whether the implementation of lifelong CFTR (cystic fibrosis transmembrane conductance regulator) modulation will change the temporal evolution of the CF airway metagenome.

Alteration of the Respiratory Microbiome in Hospitalized Patients with Asthma-COPD Overlap during and after an Exacerbation

The immediate aim of this study was to comparatively examine the bacterial respiratory microbiome of patients in a stable state and during an exacerbation of asthma-COPD (chronic obstructive pulmonary disease) overlap (ACO). This prospective observational study took place in Jordan between 1 September 2021 and 30 April 2022. Sputum samples from patients with recognized ACO were acquired within 48 h of the exacerbation onset and again at 3 weeks following the exacerbation. The next-generation sequencing Illumina MiSeq was employed and uncovered significantly high bacterial diversity in the sputa. The results showed a significant decrease in the taxonomic richness in the sputum samples collected during the exacerbation episodes compared with those collected from patients in a stable state (p = 0.008), with an increase in the taxonomic evenness (p < 0.005). This change in the composition of the airway bacterial community suggests that the replacement of a significant portion of the airway microbiome with certain microorganisms may play a role in the decrease in microbial diversity observed during an ACO exacerbation. Greater knowledge of this link could allow for a more focused administration of antibiotics, especially during exacerbations, improving clinical efficacy and patient outcomes.

Non-Coding RNAs in Pulmonary Diseases: Comparison of Different Airway-Derived Biosamples

Due to their structural conservation and functional role in critical signalling pathways, non-coding RNA (ncRNA) is a promising biomarker and modulator of pathological conditions. Most research has focussed on the role of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs). These molecules have been investigated both in a cellular and an extracellular context. Sources of ncRNAs may include organ-specific body fluids. Therefore, studies on ncRNAs in respiratory diseases include those on sputum, bronchoalveolar lavage fluid (BALF) and exhaled breath condensate (EBC). It is worth identifying the limitations of these biosamples in terms of ncRNA abundance, processing and diagnostic potential. This review describes the progress in the literature on the role of ncRNAs in the pathogenesis and progression of severe respiratory diseases, including cystic fibrosis, asthma and interstitial lung disease. We showed that there is a deficit of information on lncRNAs and circRNAs in selected diseases, despite attempts to functionally bind them to miRNAs. miRNAs remain the most well-studied, but only a few investigations have been conducted on the least invasive biosample material, i.e., EBC. To summarise the studies conducted to date, we also performed a preliminary in silico analysis of the reported miRNAs, demonstrating the complexity of their role and interactions in selected respiratory diseases.

Culture independent markers of nontuberculous mycobacterial (NTM) lung infection and disease in the cystic fibrosis airway

Nontuberculous mycobacteria (NTM) are opportunistic pathogens that affect a relatively small but significant portion of the people with cystic fibrosis (CF), and may cause increased morbidity and mortality in this population. Cultures from the airway are the only test currently in clinical use for detecting NTM. Culture techniques used in clinical laboratories are insensitive and poorly suited for population screening or to follow progression of disease or treatment response. The lack of sensitive and quantitative markers of NTM in the airway impedes patient care and clinical trial design, and has limited our understanding of patterns of acquisition, latency and pathogenesis of disease. Culture-independent markers of NTM infection have the potential to overcome many of the limitations of standard NTM cultures, especially the very slow growth, inability to quantitate bacterial burden, and low sensitivity due to required decontamination procedures. A range of markers have been identified in sputum, saliva, breath, blood, urine, as well as radiographic studies. Proposed markers to detect presence of NTM or transition to NTM disease include bacterial cell wall products and DNA, as well as markers of host immune response such as immunoglobulins and the gene expression of circulating leukocytes. In all cases the sensitivity of culture-independent markers is greater than standard cultures; however, most do not discriminate between various NTM species. Thus, each marker may be best suited for a specific clinical application, or combined with other markers and traditional cultures to improve diagnosis and monitoring of treatment response.

Impact of Elexacaftor/Tezacaftor/Ivacaftor Therapy on the Cystic Fibrosis Airway Microbial Metagenome

The introduction of mutation-specific combination therapy with the cystic fibrosis transmembrane conductance regulator (CFTR) modulators elexacaftor/tezacaftor/ivacaftor (ELX/TEZ/IVA) has substantially improved lung function and quality of life of people with cystic fibrosis (CF). Collecting deep cough swabs and induced sputum, this postapproval study examined the effect of 14- and 50-week treatment with ELX/TEZ/IVA on the airway microbial metagenome of pancreatic- insufficient CF patients aged 12 years and older. Compared to pretreatment, the total bacterial load decreased, the individual species were more evenly distributed in the community, and the individual microbial metagenomes became more similar in their composition. However, the microbial network remained vulnerable to fragmentation. The initial shift of the CF metagenome was attributable to the ELX/TEZ/IVA-mediated gain of CFTR activity followed by a diversification driven by a group of commensals at the 1-year time point that are typical for healthy airways. IMPORTANCE Shotgun metagenome sequencing of respiratory secretions with spike-in controls for normalization demonstrated that 1 year of high-efficient CFTR modulation with elexacaftor/tezacaftor/ivacaftor extensively reduced the bacterial load. Longer observation periods will be necessary to resolve whether the partial reversion of the basic defect that is achieved with ELX/TEZ/IVA is sufficient in the long run to render the CF lungs robust against the recolonization with common opportunistic pathogens.

Exploring the Cystic Fibrosis Lung Microbiome: Making the Most of a Sticky Situation

Chronic lower respiratory tract infections are a leading contributor to morbidity and mortality in persons with cystic fibrosis (pwCF). Traditional respiratory tract surveillance culturing has focused on a limited range of classic pathogens; however, comprehensive culture and culture-independent molecular approaches have demonstrated complex communities highly unique to each individual. Microbial community structure evolves through the lifetime of pwCF and is associated with baseline disease state and rates of disease progression including occurrence of pulmonary exacerbations. While molecular analysis of the airway microbiome has provided insight into these dynamics, challenges remain including discerning not only "who is there" but "what they are doing" in relation to disease progression. Moreover, the microbiome can be leveraged as a multi-modal biomarker for both disease activity and prognostication. In this article, we review our evolving understanding of the role these communities play in pwCF and identify challenges in translating microbiome data to clinical practice.

Changes in airway bacterial communities occur soon after initiation of antibiotic treatment of pulmonary exacerbations in cystic fibrosis

Chronic polymicrobial airway infections are a hallmark of cystic fibrosis (CF) lung disease. Antibiotic therapy is a primary treatment of CF pulmonary exacerbations (PEx); however, the impact of episodic antibiotic treatment on airway bacterial communities has not been well described. We analyzed sputum samples from adults with CF obtained immediately before and during antibiotic treatment of PEx. Sequencing of the V4 region of the bacterial 16S ribosomal RNA gene was used to assess changes in bacterial community structure during antibiotic treatment. The peak impact of antibiotic treatment was observed by day four or five of treatment. These findings advance our understanding of bacterial community dynamics during antibiotic treatment of PEx and complement recent and ongoing studies evaluating the optimal duration of antibiotic therapy for PEx.

Antibiotics Drive Expansion of Rare Pathogens in a Chronic Infection Microbiome Model

Chronic (long-lasting) infections are globally a major and rising cause of morbidity and mortality. Unlike typical acute infections, chronic infections are ecologically diverse, characterized by the presence of a polymicrobial mix of opportunistic pathogens and human-associated commensals. To address the challenge of chronic infection microbiomes, we focus on a particularly well-characterized disease, cystic fibrosis (CF), where polymicrobial lung infections persist for decades despite frequent exposure to antibiotics. Epidemiological analyses point to conflicting results on the benefits of antibiotic treatment yet are confounded by the dependency of antibiotic exposures on prior pathogen presence, limiting their ability to draw causal inferences on the relationships between antibiotic exposure and pathogen dynamics. To address this limitation, we develop a synthetic infection microbiome model representing CF metacommunity diversity and benchmark on clinical data. We show that in the absence of antibiotics, replicate microbiome structures in a synthetic sputum medium are highly repeatable and dominated by oral commensals. In contrast, challenge with physiologically relevant antibiotic doses leads to substantial community perturbation characterized by multiple alternate pathogen-dominant states and enrichment of drug-resistant species. These results provide evidence that antibiotics can drive the expansion (via competitive release) of previously rare opportunistic pathogens and offer a path toward microbiome-informed conditional treatment strategies.

IMPORTANCE We develop and clinically benchmark an experimental model of the cystic fibrosis (CF) lung infection microbiome to investigate the impacts of antibiotic exposures on chronic, polymicrobial infections. We show that a single experimental model defined by metacommunity data can partially recapitulate the diversity of individual microbiome states observed across a population of people with CF. In the absence of antibiotics, we see highly repeatable community structures, dominated by oral microbes. Under clinically relevant antibiotic exposures, we see diverse and frequently pathogen-dominated communities, and a nonevolutionary enrichment of antimicrobial resistance on the community scale, mediated by competitive release. The results highlight the potential importance of nonevolutionary (community-ecological) processes in driving the growing global crisis of increasing antibiotic resistance.

Association of bacterial community types, functional microbial processes and lung disease in cystic fibrosis airways

Bacterial infection and inflammation of the airways are the leading causes of morbidity and mortality in persons with cystic fibrosis (CF). The ecology of the bacterial communities inhabiting CF airways is poorly understood, especially with respect to how community structure, dynamics, and microbial metabolic activity relate to clinical outcomes. In this study, the bacterial communities in 818 sputum samples from 109 persons with CF were analyzed by sequencing bacterial 16S rRNA gene amplicons. We identified eight alternative community types (pulmotypes) by using a Dirichlet multinomial mixture model and studied their temporal dynamics in the cohort. Across patients, the pulmotypes displayed chronological patterns in the transition among each other. Furthermore, significant correlations between pulmotypes and patient clinical status were detected by using multinomial mixed effects models, principal components regression, and statistical testing. Constructing pulmotype-specific metabolic activity profiles, we found that pulmotype microbiota drive distinct community functions including mucus degradation or increased acid production. These results indicate that pulmotypes are the result of ordered, underlying drivers such as predominant metabolism, ecological competition, and niche construction and can form the basis for quantitative, predictive models supporting clinical treatment decisions.

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.

The lung microbiome: progress and promise

The healthy lung was long thought of as sterile, but recent advances using molecular sequencing approaches have detected bacteria at low levels. Healthy lung bacteria largely reflect communities present in the upper respiratory tract that enter the lung via microaspiration, which is balanced by mechanical and immune clearance and likely involves limited local replication. The nature and dynamics of the lung microbiome, therefore, differ from those of ecological niches with robust self-sustaining microbial communities. Aberrant populations (dysbiosis) have been demonstrated in many pulmonary diseases not traditionally considered microbial in origin, and potential pathways of microbe-host crosstalk are emerging. The question now is whether and how dysbiotic microbiota contribute to initiation or perpetuation of injury. The fungal microbiome and virome are less well studied. This Review highlights features of the lung microbiome, unique considerations in studying it, examples of dysbiosis in selected disease, emerging concepts in lung microbiome-host interactions, and critical areas for investigation.

Microbiome Data Enhances Predictive Models of Lung Function in People With Cystic Fibrosis

BACKGROUND

Microbiome sequencing has brought increasing attention to the polymicrobial context of chronic infections. However, clinical microbiology continues to focus on canonical human pathogens, which may overlook informative, but nonpathogenic, biomarkers. We address this disconnect in lung infections in people with cystic fibrosis (CF).

METHODS

We collected health information (lung function, age, and body mass index [BMI]) and sputum samples from a cohort of 77 children and adults with CF. Samples were collected during a period of clinical stability and 16S rDNA sequenced for airway microbiome compositions. We use ElasticNet regularization to train linear models predicting lung function and extract the most informative features.

RESULTS

Models trained on whole-microbiome quantitation outperformed models trained on pathogen quantitation alone, with or without the inclusion of patient metadata. Our most accurate models retained key pathogens as negative predictors (Pseudomonas, Achromobacter) along with established correlates of CF disease state (age, BMI, CF-related diabetes). In addition, our models selected nonpathogen taxa (Fusobacterium, Rothia) as positive predictors of lung health.

CONCLUSIONS

These results support a reconsideration of clinical microbiology pipelines to ensure the provision of informative data to guide clinical practice.

The sputum microbiome associated with different sub-types of AECOPD in a Chinese cohort

Background

Chronic obstructive pulmonary disease (COPD) is one of the most prevalent diseases worldwide. Episodes of acute exacerbations of COPD (AECOPD) are associated with disease severity and progression. Although substantial progress has been made in understanding the dynamics of AECOPD, little is known about the sputum microbiome of AECOPD in the Chinese population.

Methods

In this study, we characterized the sputum microbiomes from sputum specimens collected from healthy controls (n = 10), stable (n = 4), AECOPD (n = 36), and recovery (n = 18) stages by sequencing the V3-V4 region of the 16S rRNA gene with a HiSeq sequencer.

Results

Streptococcus was the most dominant genus among all the different types of sputum. A random forest model was developed to identify bacterial taxa that differentiate AECOPD samples from others. Most of the top predictors, except Pseudomonas, were less abundant in AECOPD samples. We also developed random forest models to differentiate subtypes of AECOPD based on blood eosinophil counts, the frequency of AECOPD, and sputum eosinophils. Bacterial taxa associated with Pasteurellaceae, Fusobacterium, Solobacterium, Haemophilus, Atopobium, Corynebacterium and Streptococcus, were enriched in the sputum microbiomes of eosinophilic AECOPD. Random forest models also demonstrate that a total of 2 bacterial OTUs were needed to differentiate frequent from non-frequent AECOPDs, and 23 OTUs were enough to accurately predict sputum-eosinophilic (sputum eosinophilic concentration ≥ 3%) AECOPD.

Conclusion

This study expanded our understanding of the sputum microbiome associated with different subtypes and clinical status of patients with AECOPD in a Chinese cohort, which provides insights into novel and more targeted management of the different subtypes of AECOPD.