Fluctuations in airway bacterial communities associated with clinical states and disease stages in cystic fibrosis

Exploring the role of microbiome in cystic fibrosis clinical outcomes through a mediation analysis

Human microbiome plays a crucial role in host health and disease by mediating the impact of environmental factors on clinical outcomes. Mediation analysis is a valuable tool for dissecting these complex relationships. However, existing approaches are primarily designed for cross-sectional studies. Modern clinical research increasingly utilizes long follow-up periods, leading to complex data structures, particularly in metagenomic studies. To address this limitation, we introduce a novel mediation framework based on structural equation modeling that leverages linear mixed-effects models using penalized quasi-likelihood estimation with a debiased lasso. We applied this framework to a 16S rRNA sputum microbiome data set collected from patients with cystic fibrosis over 10 years to investigate the mediating role of the microbiome in the relationship between clinical states, disease aggressiveness phenotypes, and lung function. We identified richness as a key mediator of lung function. Specifically, Streptococcus was found to be significantly associated with mediating the decline in lung function on treatment compared to exacerbation, while Gemella was associated with the decline in lung function on recovery. This approach offers a powerful new tool for understanding the complex interplay between microbiome and clinical outcomes in longitudinal studies, facilitating targeted microbiome-based interventions.

IMPORTANCE

Understanding the mechanisms by which the microbiome influences clinical outcomes is paramount for realizing the full potential of microbiome-based medicine, including diagnostics and therapeutics. Identifying specific microbial mediators not only reveals potential targets for novel therapies and drug repurposing but also offers a more precise approach to patient stratification and personalized interventions. While traditional mediation analyses are ill-equipped to address the complexities of longitudinal metagenomic data, our framework directly addresses this gap, enabling robust investigation of these increasingly common study designs. By applying this framework to a decade-long cystic fibrosis study, we have begun to unravel the intricate relationships between the sputum microbiome and lung function decline across different clinical states, yielding insights that were previously unknown.

Dual oxic-anoxic co-culture enables direct study of anaerobe-host interactions at the airway epithelial interface

Strict and facultative anaerobic bacteria are widely associated with both acute and chronic airway diseases. However, their potential role(s) in disease pathophysiology remains poorly understood due to inherent limitations of existing laboratory models and conflicting oxygen demands between anaerobes and host cells. To address these limitations, here, we describe a dual oxic-anoxic culture (DOAC) approach that maintains an oxygen-limited microenvironment at the apical epithelial interface while host cells are oxygenated basolaterally. This platform enables epithelial-anaerobe co-culture for ~48 h, and we demonstrate its utility by evaluating reciprocal interactions between the oxygen-sensitive anaerobic bacterium, Fusobacterium nucleatum, and oxygen-demanding airway epithelial cells at the transcriptional level. Using bulk RNAseq, we demonstrate that epithelial colonization results in altered gene expression by F. nucleatum, highlighted by the differential expression of genes associated with virulence, ethanolamine and lysine metabolism, metal uptake, and other transport processes. We also combine DOAC with single-cell RNA sequencing to reveal a cell type-specific transcriptional response of the airway epithelium to F. nucleatum infection, including the increased expression of inflammatory marker genes and cancer-associated pathways. Together, these data illustrate the versatility of DOAC while revealing new insights into anaerobe-host interactions and their mechanistic contributions to airway disease pathophysiology.IMPORTANCEConflicting oxygen demands between anaerobes and host cells present a significant barrier to in vitro modeling of how these cell types interact. To this end, the significance of our dual oxic-anoxic culture (DOAC) approach lies in its ability to maintain anaerobe and epithelial viability during co-culture, paving the way for new insights into the role(s) of anaerobic microbiota in disease. We use DOAC to interrogate reciprocal interactions between the airway epithelium and Fusobacterium nucleatum-an anaerobic commensal with pathogenic potential. Given its link to a range of diseases, from localized infections to various cancers, these data showing how F. nucleatum bacterium re-shapes its metabolism and virulence upon epithelial colonization provide new mechanistic insight into F. nucleatum physiology and how the host responds. We use F. nucleatum as our model, but the DOAC platform motivates additional studies of the gut, lung, and oral cavity, where host-anaerobe interactions and the underlying mechanisms of pathogenesis are poorly understood.

Practical Guidance for Clinical Microbiology Laboratories: Updated guidance for processing respiratory tract samples from people with cystic fibrosis

SUMMARYThis guidance presents recommendations for clinical microbiology laboratories for processing respiratory samples from people with cystic fibrosis (pwCF). Appropriate processing of respiratory samples is crucial to detect bacterial and fungal pathogens, guide treatment, monitor the epidemiology of cystic fibrosis (CF) pathogens, and assess therapeutic interventions. Thanks to CF transmembrane conductance regulator modulator therapy, the health of pwCF has improved, but as a result, fewer pwCF spontaneously expectorate sputum. Thus, the collection of sputum samples has decreased, while the collection of other types of respiratory samples such as oropharyngeal and bronchoalveolar lavage samples has increased. To optimize the detection of microorganisms, including Pseudomonas aeruginosa, Staphylococcus aureus, Haemophilus influenzae, and Burkholderia cepacia complex; other less common non-lactose fermenting Gram-negative bacilli, e.g., Stenotrophomonas maltophilia, Inquilinus, Achromobacter, Ralstonia, and Pandoraea species; and yeasts and filamentous fungi, non-selective and selective culture media are recommended for all types of respiratory samples, including samples obtained from pwCF after lung transplantation. There are no consensus recommendations for laboratory practices to detect, characterize, and report small colony variants (SCVs) of S. aureus, although studies are ongoing to address the potential clinical impact of SCVs. Accurate identification of less common Gram-negative bacilli, e.g., S. maltophilia, Inquilinus, Achromobacter, Ralstonia, and Pandoraea species, as well as yeasts and filamentous fungi, is recommended to understand their epidemiology and clinical importance in pwCF. However, conventional biochemical tests and automated platforms may not accurately identify CF pathogens. MALDI-TOF MS provides excellent genus-level identification, but databases may lack representation of CF pathogens to the species-level. Thus, DNA sequence analysis should be routinely available to laboratories for selected clinical circumstances. Antimicrobial susceptibility testing (AST) is not recommended for every routine surveillance culture obtained from pwCF, although selective AST may be helpful, e.g., for unusual pathogens or exacerbations unresponsive to initial therapy. While this guidance reflects current care paradigms for pwCF, recommendations will continue to evolve as CF research expands the evidence base for laboratory practices.

Pseudomonas aeruginosa in chronic lung disease: untangling the dysregulated host immune response

Pseudomonas aeruginosa is a highly adaptable opportunistic pathogen capable of exploiting barriers and immune defects to cause chronic lung infections in conditions such as cystic fibrosis. In these contexts, host immune responses are ineffective at clearing persistent bacterial infection, instead driving a cycle of inflammatory lung damage. This review outlines key components of the host immune response to chronic P. aeruginosa infection within the lung, beginning with initial pathogen recognition, followed by a robust yet maladaptive innate immune response, and an ineffective adaptive immune response that propagates lung damage while permitting bacterial persistence. Untangling the interplay between host immunity and chronic P. aeruginosa infection will allow for the development and refinement of strategies to modulate immune-associated lung damage and potentiate the immune system to combat chronic infection more effectively.

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. Understanding PEx ecology is challenged by high inter-patient variability in airway microbial community profiles. We analyze bacterial communities in 880 CF sputum samples collected during an observational prospective cohort study and develop microbiome descriptors to model community reorganization prior to and during 18 PEx. We identify two microbial dysbiosis regimes with opposing ecology and dynamics. Pathogen-governed PEx show hierarchical community reorganization and reduced diversity, whereas anaerobic bloom PEx display stochasticity and increased diversity. A simulation of antimicrobial treatment predicts better efficacy for hierarchically organized communities. This link between PEx, microbiome organization, and treatment success advances the development of personalized clinical management in CF and, potentially, other obstructive lung diseases.

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.

An oral commensal attenuates Pseudomonas aeruginosa-induced airway inflammation and modulates nitrite flux in respiratory epithelium

IMPORTANCE

Respiratory infections are a leading cause of morbidity and mortality in people with cystic fibrosis (CF). These infections are polymicrobial in nature with overt pathogens and other colonizing microbes present. Microbiome data have indicated that the presence of oral commensal bacteria in the lungs is correlated with improved outcomes. We hypothesize that one oral commensal, Streptococcus parasanguinis, inhibits CF pathogens and modulates the host immune response. One major CF pathogen is Pseudomonas aeruginosa, a Gram-negative, opportunistic bacterium with intrinsic drug resistance and an arsenal of virulence factors. We have previously shown that S. parasanguinis inhibits P. aeruginosa in vitro in a nitrite-dependent manner through the production of reactive nitrogen intermediates. In this study, we demonstrate that while this mechanism is evident in a cell culture model of the CF airway, an alternative mechanism by which S. parasanguinis may improve outcomes for people with CF is through immunomodulation.

Breath of fresh insight: unraveling the evolution of our understanding of cystic fibrosis pulmonary exacerbations

PURPOSE OF REVIEW

Pulmonary exacerbations are critical events with significant negative impacts in persons with cystic fibrosis, but their diagnosis and management are highly variable. Highly effective modulator therapies have greatly improved health and reduced exacerbation events, but have also reshaped how they present. This review discusses the complexities of the diagnosis and management of pulmonary exacerbations as well as the emerging work and evidence in this area.

RECENT FINDINGS

The shifting epidemiology and our understanding of risk factors for pulmonary exacerbations are discussed. As symptoms may be more subtle in the modulator context, novel technologies including studies of remote monitoring are presented. The continued relevance of pulmonary exacerbations, the heterogeneity in their management, as well as current and forthcoming clinical trials to optimize treatment approaches are detailed.

SUMMARY

In spite of the dramatic reductions in pulmonary exacerbations, airway infections persist, a proportion of persons with cystic fibrosis either on or off modulator therapies continue to experience exacerbation events, and long-term data is lacking. Innovative approaches and studies will be crucial to enable standardized and generalizable strategies to improve outcomes in persons with cystic fibrosis.

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 (COPD). Intermittent pulmonary exacerbations (PEx) in these conditions are associated with 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 880 near-daily CF sputum samples and developed non-standard microbiome descriptors to model community reorganization prior and during 18 PEx. We identified two communal microbial regimes with opposing ecology and dynamics. Whereas pathogen-governed dysbiosis showed hierarchical community organization and reduced diversity, anaerobic bloom dysbiosis displayed stochasticity and increased diversity. Microbiome organization modulated the relevance of pathogens and a simulation of antimicrobial treatment predicted better efficacy for hierarchically organized microbiota. This causal link between PEx, microbiome organization, and treatment success advances the development of personalized dysbiosis management in CF and, potentially, other obstructive lung diseases.

Distinct community structures of the fungal microbiome and respiratory health in adults with cystic fibrosis

BACKGROUND

The respiratory tract fungal microbiome in cystic fibrosis (CF) has been understudied despite increasing recognition of fungal pathogens in CF lung disease. We sought to better understand the fungal communities in adults with CF, and to define relationships between fungal profiles and clinical characteristics.

METHODS

We enrolled 66 adults with CF and collected expectorated sputum, spirometry, Cystic Fibrosis Questionnaire-revised, and clinical data. Fungi were molecularly profiled by sequencing of the internal transcribed spacer (ITS) region. Total fungal abundance was measured by quantitative PCR. Relative abundance and qPCR-corrected abundances were determined. Selective fungus culture identified cultivable fungi. Alpha diversity and beta diversity were measured and relationships with clinical parameters were interrogated.

RESULTS

Median age was 29 years and median FEV1 percent predicted 58%. Members of the Candida genus were the most frequent dominant taxa in CF sputum. Apiotrichum, Trichosporon, Saccharomyces cerevisiae, and Scedosporium were present in high relative abundance in few samples; whereas, Aspergillus species were detected at low levels. Higher FEV1% predicted and CFTR modulator use were associated with greater alpha-diversity. Chronic azithromycin use was associated with lower alpha-diversity. Patients with acute pulmonary had distinct fungal community composition compared to clinically stable subjects. Differing yeast species were mainly responsible for the community differences.

CONCLUSION

The respiratory tract fungal microbiome in adults with CF is associated with lung function, pulmonary exacerbation status, macrolide use, and CFTR modulator use. Future work to better understand fungal diversity in the CF airway and its impact on lung health is necessary.

Microbial Epidemiology of the Cystic Fibrosis Airways: Past, Present, and Future

Progressive obstructive lung disease secondary to chronic airway infection, coupled with impaired host immunity, is the leading cause of morbidity and mortality in cystic fibrosis (CF). Classical pathogens found in the airways of persons with CF (pwCF) include Pseudomonas aeruginosa, Staphylococcus aureus, the Burkholderia cepacia complex, Achromobacter species, and Haemophilus influenzae. While traditional respiratory-tract surveillance culturing has focused on this limited range of pathogens, the use of both comprehensive culture and culture-independent molecular approaches have demonstrated complex highly personalized microbial communities. Loss of bacterial community diversity and richness, counteracted with relative increases in dominant taxa by traditional CF pathogens such as Burkholderia or Pseudomonas, have long been considered the hallmark of disease progression. Acquisition of these classic pathogens is viewed as a harbinger of advanced disease and postulated to be driven in part by recurrent and frequent antibiotic exposure driven by frequent acute pulmonary exacerbations. Recently, CF transmembrane conductance regulator (CFTR) modulators, small molecules designed to potentiate or restore diminished protein levels/function, have been successfully developed and have profoundly influenced disease course. Despite the multitude of clinical benefits, structural lung damage and consequent chronic airway infection persist in pwCF. In this article, we review the microbial epidemiology of pwCF, focus on our evolving understanding of these infections in the era of modulators, and identify future challenges in infection surveillance and clinical management.

Using metabolic potential within the airway microbiome as predictors of clinical state in persons with cystic fibrosis

Introduction

Pulmonary exacerbations (PEx) in persons with cystic fibrosis (CF) are primarily related to acute or chronic inflammation associated with bacterial lung infections, which may be caused by several bacteria that activate similar bacterial genes and produce similar by-products. The goal of our study was to perform a stratified functional analysis of bacterial genes at three distinct time points in the treatment of a PEx in order to determine the role that specific airway microbiome community members may play within each clinical state (i.e., PEx, end of antibiotic treatment, and follow-up). Our secondary goal was to compare the change between clinical states with the metabolic activity of specific airway microbiome community members.

Methods

This was a prospective observational study of persons with CF treated with intravenous antibiotics for PEx between 2016 and 2020 at Children's National Hospital. Demographic and clinical information as well as respiratory samples were collected at hospital admission for PEx, end of antibiotic treatment, and follow-up. Metagenomic sequencing was performed; MetaPhlAn3 and HUMANn3 were used to assign sequences to bacterial species and bacterial metabolic genes, respectively.

Results

Twenty-two persons with CF, with a mean age of 14.5 (range 7-23) years, experienced 45 PEx during the study period. Two-hundred twenty-one bacterial species were identified in the respiratory samples from the study cohort. Ten bacterial species had differential gene abundance across changes in the clinical state including Staphylococcus aureus, Streptococcus salivarius, and Veillonella atypica (all padj < 0.01 and log2FoldChange > |2|). These corresponded to a differential abundance of bacterial genes, with S. aureus accounting for 81% of the genes more abundant in PEx and S. salivarius accounting for 83% of the genes more abundant in follow-up, all compared to the end of treatment. Lastly, 8,653 metabolic pathways were identified across samples, with again S. aureus and S. salivarius contributing to the differential abundance of pathways (106 in PEx vs. 66 in follow-up, respectively). V. atypica was associated with a single metabolic pathway (UDP-N-acetyl-D-glucosamine biosynthesis) increased in follow-up compared to PEx.

Discussion

Taken together, these data suggest that the metabolic potential of bacterial species can provide more insight into changes across clinical states than the relative abundance of the bacteria alone.

A restructuring of microbiome niche space is associated with Elexacaftor-Tezacaftor-Ivacaftor therapy in the cystic fibrosis lung

BACKGROUND

Elexacaftor-Tezacaftor-Ivacaftor (ETI) therapy is showing promising efficacy for treatment of cystic fibrosis (CF) and is becoming more widely available since recent FDA approval. However, little is known about how these drugs will affect lung infections, which are the leading cause of morbidity and mortality among people with CF (pwCF).

METHODS

We analyzed sputum microbiome and metabolome data from pwCF (n=24) before and after ETI therapy using 16S rRNA gene sequencing and untargeted metabolomics.

RESULTS

The sputum microbiome diversity, particularly its evenness, was increased (p=0.036) and the microbiome profiles were different between individuals before and after therapy (PERMANOVA F=1.92, p=0.044). Despite these changes, the microbiomes remained more similar within an individual than across the sampled population. No specific microbial taxa differed in relative abundance before and after therapy, but the collective log-ratio of classic CF pathogens to anaerobes significantly decreased (p=0.013). The sputum metabolome also showed changes associated with ETI (PERMANOVA F=4.22, p=0.002) and was characterized by greater variation across subjects while on treatment. Changes in the metabolome were driven by a decrease in peptides, amino acids, and metabolites from the kynurenine pathway, which were associated with a decrease in CF pathogens. Metabolism of the three small molecules that make up ETI was extensive, including previously uncharacterized structural modifications.

CONCLUSIONS

ETI therapy is associated with a changing microbiome and metabolome in airway mucus. This effect was stronger on sputum biochemistry, which may reflect changing niche space for microbial residency in lung mucus as the drug's effects take hold.

FUNDING

This project was funded by a National Institute of Allergy and Infectious Disease Grant R01AI145925.

Opportunistic Pathogens in Cystic Fibrosis: Epidemiology and Pathogenesis of Lung Infection

Cystic fibrosis (CF) is one of the most common life-shortening genetic diseases in Caucasians. Due to abnormal accumulation of mucus, respiratory failure caused by chronic infections is the leading cause of mortality in this patient population. The microbiology of these respiratory infections includes a distinct set of opportunistic pathogens, including Pseudomonas aeruginosa, Burkholderia spp., Achromobacter spp., Stenotrophomonas maltophilia, anaerobes, nontuberculous mycobacteria, and fungi. In recent years, culture-independent methods have shown the polymicrobial nature of lung infections, and the dynamics of microbial communities. The unique environment of the CF airway predisposes to infections caused by opportunistic pathogens. In this review, we will highlight how the epidemiology and role in disease of these pathogens in CF differ from that in individuals with other medical conditions. Infectious diseases (ID) physicians should be aware of these differences and the specific characteristics of infections associated with CF.

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.

The Elusive Role of Airway Infection in Cystic Fibrosis Exacerbation

Cystic fibrosis (CF) pulmonary exacerbations (PEx) are clinical events that commonly result in increased treatment burden, decreased quality of life, and accelerated lung disease progression. CF PEx have historically been approached as though dealing with acute infections, and antibiotic treatments have been associated with improved outcomes. In this review, we discuss data supporting a causal role of CF airway infection in PEx as well studies that highlight our knowledge gaps in regard to PEx definitions, pathophysiology, and optimal treatment approaches. In the era of highly effective cystic fibrosis transmembrane conductance regulator modulator therapy, and the continually increasing health and longevity of persons with CF, a better understanding of PEx and further optimization of PEx antibiotic treatment approaches are needed.

Complex and unexpected outcomes of antibiotic therapy against a polymicrobial infection

Antibiotics are our primary approach to treating complex infections, yet we have a poor understanding of how these drugs affect microbial communities. To better understand antimicrobial effects on host-associated microbial communities we treated cultured sputum microbiomes from people with cystic fibrosis (pwCF, n = 24) with 11 different antibiotics, supported by theoretical and mathematical modeling-based predictions in a mucus-plugged bronchiole microcosm. Treatment outcomes we identified in vitro that were predicted in silico were: 1) community death, 2) community resistance, 3) pathogen killing, and 4) fermenter killing. However, two outcomes that were not predicted when antibiotics were applied were 5) community profile shifts with little change in total bacterial load (TBL), and 6) increases in TBL. The latter outcome was observed in 17.8% of samples with a TBL increase of greater than 20% and 6.8% of samples with an increase greater than 40%, demonstrating significant increases in community carrying capacity in the presence of an antibiotic. An iteration of the mathematical model showed that TBL increase was due to antibiotic-mediated release of pH-dependent inhibition of pathogens by anaerobe fermentation. These dynamics were verified in vitro when killing of fermenters resulted in a higher community carrying capacity compared to a no antibiotic control. Metagenomic sequencing of sputum samples during antibiotic therapy revealed similar dynamics in clinical samples. This study shows that the complex microbial ecology dictates the outcomes of antibiotic therapy against a polymicrobial infection.

A clinicians’ review of the respiratory microbiome

The respiratory microbiome and its impact in health and disease is now well characterised. With the development of next-generation sequencing and the use of other techniques such as metabolomics, the functional impact of microorganisms in different host environments can be elucidated. It is now clear that the respiratory microbiome plays an important role in respiratory disease. In some diseases, such as bronchiectasis, examination of the microbiome can even be used to identify patients at higher risk of poor outcomes. Furthermore, the microbiome can aid in phenotyping. Finally, development of multi-omic analysis has revealed interactions between the host and microbiome in some conditions. This review, although not exhaustive, aims to outline how the microbiome is investigated, the healthy respiratory microbiome and its role in respiratory disease.

The respiratory microbiome encompasses bacterial, fungal and viral communities. In health, it is a dynamic structure and dysbiotic in disease. Dysbiosis can be related to disease severity and may be utilised to predict patients at clinical risk.https://bit.ly/3pNSgnA

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.

Insights into the Unique Lung Microbiota Profile of Pulmonary Tuberculosis Patients Using Metagenomic Next-Generation Sequencing

The microbiota plays an important role in human health and disease development. The lung microbiota profile in pulmonary tuberculosis (TB) patients and the effects of anti-TB treatment on the profile need to be determined thoroughly and comprehensively. This study primarily aimed to determine the lung microbiota profile associated with pulmonary TB and characterize the longitudinal changes during anti-TB treatment. A total of 53 participants, comprising 8 healthy individuals, 12 untreated pulmonary TB patients, 15 treated pulmonary TB patients, 11 cured pulmonary TB patients, and 7 lung cancer patients, were recruited in the present study. Bronchioalveolar lavage fluid (BALF) samples were collected from the above participants, and throat swabs were taken from healthy individuals. Microbiomes in the samples were examined using metagenomic next-generation sequencing (mNGS). Differences in microbiota profiles were determined through a comparison of the indicated groups. Our findings indicated that the BALF samples displayed decreased richness and diversity of the microbiota compared to those of the throat swab samples, and these two kinds of samples exhibited obvious separation on principal-coordinate analysis (PCoA) plots. Untreated pulmonary TB patients displayed a unique lung microbiota signature distinct from that of healthy individuals and lung cancer patients. Our data first demonstrated that anti-TB treatment with first-line drugs increases alpha diversity and significantly affects the beta diversity of the lung microbiota, while it also induces antibiotic resistance genes (ARGs). IMPORTANCE Characterization of the lung microbiota could lead to a better understanding of the pathogenesis of pulmonary TB. Here, we applied the metagenomic shotgun sequencing instead of 16S rRNA sequencing method to characterize the lung microbiota using the BALF samples instead of sputum. We found that alterations in the lung microbiota are associated with TB infection and that anti-TB treatment significantly affects the alpha and beta diversity of the lung microbiota in pulmonary TB patients. These findings could help us better understand TB pathogenesis.

Metabolomic Biomarkers to Predict and Diagnose Cystic Fibrosis Pulmonary Exacerbations: A Systematic Review

INTRODUCTION

Metabolomics is an emerging area of research and has the potential to identify clinical biomarkers for predicting or diagnosing cystic fibrosis (CF) pulmonary exacerbations (PEx).

OBJECTIVE

To identify clinically promising metabolites across different sample sources that can be used to predict or diagnose PEx in CF.

EVIDENCE REVIEW

Searches for original literature were completed through EMBASE, MEDLINE, and all databases on the Web of Science with no restrictions on language or publication date. Gray literature was collected through Google Scholar. Additional studies were obtained by contacting authors and searching reference lists of candidate papers. The patient population included individuals with CF. Studies involving patients who underwent lung transplantation were excluded. The outcome was the prediction or diagnosis of pulmonary exacerbations from metabolites directly measured from biological samples. Search results were downloaded and imported into Covidence and duplicates were removed automatically. Any remaining duplicates were manually tagged and excluded. Two independent reviewers screened each abstract for eligibility and repeated this process for full texts. Risk of bias was conducted using QUADAS-2 by two independent reviewers. A third author resolved any remaining conflicts.

RESULTS

A combined 3974 relevant abstracts were identified and 115 full texts were assessed for eligibility. The final 25 studies underwent data extraction for study design, patient demographics, studied metabolites, concentration values, and diagnostic accuracy values. Included studies differed considerably in methodologies, sample specimen types (exhaled breath condensate [EBC], sputum, saliva, plasma, urine), and disease states. We identified 19 unique metabolites that were measured by two or more studies of which 2 have the potential to predict PEx (EBC 4-hydroxycyclohexylcarboxylic acid [4-HCHC] and lactic acid) and 6 to diagnose PEx (EBC 4-HCHC and lactic acid, sputum lactic acid and nitrate, and plasma arginine and methionine).

CONCLUSION AND RELEVANCE

This systematic review has identified promising metabolites for further study in CF. Certain metabolites may provide clinical potential in predicting or diagnosing PEx, but further validation studies are required. With better tools to aid in the earlier identification of PEx, clinicians can implement preventative measures to mitigate airway damage.Systematic Review Registration: https://www.crd.york.ac.uk/prospero/.

A Volatile and Dynamic Longitudinal Microbiome Is Associated With Less Reduction in Lung Function in Adolescents With Cystic Fibrosis

Progressive impairment in lung function caused by chronic polymicrobial airway infection remains the major cause of death in patients with cystic fibrosis (CF). Cross-sectional studies suggest an association between lung function decline and specific lung microbiome ecotypes. However, longitudinal studies on the stability of the airway microbiome are missing for adolescents with CF constituting the age group showing the highest rate of decline in lung function. In this study, we analyzed longitudinal lung function data and sputum samples collected over a period of 3 to 5 years from 12 adolescents with CF. The sputum microbiome was analyzed using 16S rRNA gene sequencing. Our results indicate that the individual course of the lung microbiome is associated with longitudinal lung function. In our cohort, patients with a dynamic, diverse microbiome showed a slower decline of lung function measured by FEV_1% predicted, whereas a more stable and less diverse lung microbiome was related to worse outcomes. Specifically, a higher abundance of the phyla Bacteroidetes and Firmicutes was linked to a better clinical outcome, while Proteobacteria were correlated with a decline in FEV_1% predicted. Our study indicates that the stability and diversity of the lung microbiome and the abundance of Bacteroidetes and Firmicutes are associated with the lung function decline and are one of the contributing factors to the disease severity.

Impact of Anaerobic Antibacterial Spectrum on Cystic Fibrosis Airway Microbiome Diversity and Pulmonary Function

BACKGROUND

The role of anaerobic organisms in the cystic fibrosis (CF) lung microbiome is unclear. Our objectives were to investigate the effect of broad (BS) versus narrow (NS) spectrum antianaerobic antibiotic activity on lung microbiome diversity and pulmonary function, hypothesizing that BS antibiotics would cause greater change in microbiome diversity without a significant improvement in lung function.

METHODS

Pulmonary function tests and respiratory samples were collected prospectively in persons with CF before and after treatment for pulmonary exacerbations. Treatment antibiotics were classified as BS or NS. Gene sequencing data from 16S rRNA were used for diversity analysis and bacterial genera classification. We compared the effects of BS versus NS on diversity indices, lung function and anaerobic/aerobic ratios. Statistical significance was determined by multilevel mixed-effects generalized linear models and mixed-effects regression models.

RESULTS

Twenty patients, 6-20 years of age, experienced 30 exacerbations. BS therapy had a greater effect on beta diversity than NS therapy when comparing time points before antibiotics to after and at recovery. After antibiotics, the NS therapy group had a greater return toward baseline forced expiratory volume at 1 second and forced expiratory flow 25%-75% values than the BS group. The ratio of anaerobic/aerobic organisms showed a predominance of anaerobes in the NS group with aerobes dominating in the BS group.

CONCLUSIONS

BS antianaerobic therapy had a greater and possibly longer lasting effect on the lung microbiome of persons with CF, without achieving the recovery of pulmonary function seen with the NS therapy. Specific antibiotic therapies may affect disease progression by changing the airway microbiome.

Mild Cystic Fibrosis Lung Disease Is Associated with Bacterial Community Stability

Microbial communities in the airways of persons with CF (pwCF) are variable, may include genera that are not typically associated with CF, and their composition can be difficult to correlate with long-term disease outcomes. Leveraging two large data sets characterizing sputum communities of 167 pwCF and associated metadata, we identified five bacterial community types. These communities explain 24% of the variability in lung function in this cohort, far more than single factors like Simpson diversity, which explains only 4%. Subjects with Pseudomonas-dominated communities tended to be older and have reduced percent predicted FEV₁ (ppFEV₁) compared to subjects with Streptococcus-dominated communities, consistent with previous findings. To assess the predictive power of these five communities in a longitudinal setting, we used random forests to classify 346 additional samples from 24 subjects observed 8 years on average in a range of clinical states. Subjects with mild disease were more likely to be observed at baseline, that is, not in the context of a pulmonary exacerbation, and community structure in these subjects was more self-similar over time, as measured by Bray-Curtis distance. Interestingly, we found that subjects with mild disease were more likely to remain in a mixed Pseudomonas community, providing some support for the climax-attack model of the CF airway. In contrast, patients with worse outcomes were more likely to show shifts among community types. Our results suggest that bacterial community instability may be a risk factor for lung function decline and indicates the need to understand factors that drive shifts in community composition. IMPORTANCE While much research supports a polymicrobial view of the CF airway, one in which the community is seen as the pathogenic unit, only controlled experiments using model bacterial communities can unravel the mechanistic role played by different communities. This report uses a large data set to identify a small number of communities as a starting point in the development of tractable model systems. We describe a set of five communities that explain 24% of the variability in lung function in our data set, far more than single factors like Simpson diversity, which explained only 4%. In addition, we report that patients with severe disease experienced more shifts among community types, suggesting that bacterial community instability may be a risk factor for lung function decline. Together, these findings provide a proof of principle for selecting bacterial community model systems.

Polymicrobial Interactions in the Cystic Fibrosis Airway Microbiome Impact the Antimicrobial Susceptibility of Pseudomonas aeruginosa

Pseudomonas aeruginosa is one of the most dominant pathogens in cystic fibrosis (CF) airway disease and contributes to significant inflammation, airway damage, and poorer disease outcomes. The CF airway is now known to be host to a complex community of microorganisms, and polymicrobial interactions have been shown to play an important role in shaping P. aeruginosa pathogenicity and resistance. P. aeruginosa can cause chronic infections that once established are almost impossible to eradicate with antibiotics. CF patients that develop chronic P. aeruginosa infection have poorer lung function, higher morbidity, and a reduced life expectancy. P. aeruginosa adapts to the CF airway and quickly develops resistance to several antibiotics. A perplexing phenomenon is the disparity between in vitro antimicrobial sensitivity testing and clinical response. Considering the CF airway is host to a diverse community of microorganisms or 'microbiome' and that these microorganisms are known to interact, the antimicrobial resistance and progression of P. aeruginosa infection is likely influenced by these microbial relationships. This review combines the literature to date on interactions between P. aeruginosa and other airway microorganisms and the influence of these interactions on P. aeruginosa tolerance to antimicrobials.

A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses

Computational reproducibility is a corner stone for sound and credible research. Especially in complex statistical analyses-such as the analysis of longitudinal data-reproducing results is far from simple, especially if no source code is available. In this work we aimed to reproduce analyses of longitudinal data of 11 articles published in PLOS ONE. Inclusion criteria were the availability of data and author consent. We investigated the types of methods and software used and whether we were able to reproduce the data analysis using open source software. Most articles provided overview tables and simple visualisations. Generalised Estimating Equations (GEEs) were the most popular statistical models among the selected articles. Only one article used open source software and only one published part of the analysis code. Replication was difficult in most cases and required reverse engineering of results or contacting the authors. For three articles we were not able to reproduce the results, for another two only parts of them. For all but two articles we had to contact the authors to be able to reproduce the results. Our main learning is that reproducing papers is difficult if no code is supplied and leads to a high burden for those conducting the reproductions. Open data policies in journals are good, but to truly boost reproducibility we suggest adding open code policies.

Prevotella melaninogenica, a Sentinel Species of Antibiotic Resistance in Cystic Fibrosis Respiratory Niche?

The importance and abundance of strict anaerobic bacteria in the respiratory microbiota of people with cystic fibrosis (PWCF) is now established through studies based on high-throughput sequencing or extended-culture methods. In CF respiratory niche, one of the most prevalent anaerobic genera is Prevotella, and particularly the species Prevotella melaninogenica. The objective of this study was to evaluate the antibiotic susceptibility of this anaerobic species. Fifty isolates of P. melaninogenica cultured from sputum of 50 PWCF have been included. Antibiotic susceptibility testing was performed using the agar diffusion method. All isolates were susceptible to the following antibiotics: amoxicillin/clavulanic acid, piperacillin/tazobactam, imipenem and metronidazole. A total of 96% of the isolates (48/50) were resistant to amoxicillin (indicating beta-lactamase production), 34% to clindamycin (17/50) and 24% to moxifloxacin (12/50). Moreover, 10% (5/50) were multidrug-resistant. A significant and positive correlation was found between clindamycin resistance and chronic azithromycin administration. This preliminary study on a predominant species of the lung “anaerobiome” shows high percentages of resistance, potentially exacerbated by the initiation of long-term antibiotic therapy in PWCF. The anaerobic resistome characterization, focusing on species rather than genera, is needed in the future to better prevent the emergence of resistance within lung microbiota.

Importance of beta-lactam pharmacokinetics and pharmacodynamics on the recovery of microbial diversity in the airway of persons with cystic fibrosis

Cystic fibrosis (CF) is a chronic lung disease characterized by acute pulmonary exacerbations (PExs) that are frequently treated with antibiotics. The impact of antibiotics on airway microbial diversity remains a critical knowledge gap. We sought to define the association between beta-lactam pharmacokinetic (PK) and pharmacodynamic target attainment on richness and alpha diversity. Twenty-seven children <18 years of age with CF participated in the prospective study. Airway samples were collected at hospital admission for PEx, end of antibiotic treatment (Tr), and >1 month in follow-up (FU). Metagenomic sequencing was performed to determine richness, alpha diversity, and the presence of antibiotic resistance genes. Free plasma beta-lactam levels were measured, and PK modeling was performed to determine time above the minimum inhibitory concentration (fT>MIC). 52% of study subjects had sufficient fT>MIC for optimal bacterial killing. There were no significant differences in demographics or PEx characteristics, except for F508del homozygosity. No significant differences were noted in richness or alpha diversity at individual time points, and both groups experienced a decrease in richness and alpha diversity at Tr compared with PEx. However, alpha diversity remained decreased at FU compared with PEx in those with sufficient fT>MIC but increased in those with insufficient fT>MIC (Shannon -0.222 vs +0.452, p=0.031, and inverse Simpson -1.376 vs +1.388, p=0.032). Fluoroquinolone resistance was also more frequently detected in those with insufficient fT>MIC (log2 fold change (log2FC) 2.29, p=0.025). These findings suggest sufficient beta-lactam fT>MIC is associated with suppressed recovery of alpha diversity following the antibiotic exposure period.

Cystic fibrosis airway microbiota associated with outcomes of nontuberculous mycobacterial infection

Rationale

Pulmonary infections with nontuberculous mycobacteria (NTM) are increasingly prevalent in people with cystic fibrosis (CF). Clinical outcomes following NTM acquisition are highly variable, ranging from transient self-resolving infection to NTM pulmonary disease associated with significant morbidity. Relationships between airway microbiota and variability of NTM outcomes in CF are unclear.

Objective

To identify features of CF airway microbiota associated with outcomes of NTM infection.

Methods

188 sputum samples, obtained from 24 subjects with CF, each with three or more samples collected from 3.5 years prior to, and up to 6 months following incident NTM infection, were selected from a sample repository. Sputum DNA underwent bacterial 16S rRNA gene sequencing. Airway microbiota were compared based on the primary outcome, a diagnosis of NTM pulmonary disease, using Wilcoxon rank-sum testing, autoregressive integrated moving average modelling and network analyses.

Measurements and main results

Subjects with and without NTM pulmonary disease were similar in clinical characteristics, including age and lung function at the time of incident NTM infection. Time-series analyses of sputum samples prior to incident NTM infection identified positive correlations between Pseudomonas, Streptococcus, Veillonella, Prevotella and Rothia with diagnosis of NTM pulmonary disease and with persistent NTM infection. Network analyses identified differences in clustering of taxa between subjects with and without NTM pulmonary disease, and between subjects with persistent versus transient NTM infection.

Conclusions

CF airway microbiota prior to incident NTM infection are associated with subsequent outcomes, including diagnosis of NTM pulmonary disease, and persistence of NTM infection. Associations between airway microbiota and NTM outcomes represent targets for validation as predictive markers and for future therapies.

An observational study of anaerobic bacteria in cystic fibrosis lung using culture dependant and independent approaches

Strict anaerobes are undeniably important residents of the cystic fibrosis (CF) lung but are still unknowns. The main objectives of this study were to describe anaerobic bacteria diversity in CF airway microbiota and to evaluate the association with lung function. An observational study was conducted during eight months. A hundred and one patients were enrolled in the study, and 150 sputum samples were collected using a sterile sample kit designed to preserve anaerobic conditions. An extended-culture approach on 112 sputa and a molecular approach (quantitative PCR targeting three of the main anaerobic genera in CF lung: Prevotella, Veillonella, and Fusobacterium) on 141 sputa were developed. On culture, 91.1% of sputa were positive for at least one anaerobic bacterial species, with an average of six anaerobic species detected per sputum. Thirty-one anaerobic genera and 69 species were found, which is the largest anaerobe diversity ever reported in CF lungs. Better lung function (defined as Forced Expiratory Volume in one second > 70%) was significantly associated with higher quantification of Veillonella. These results raise the question of the potential impact of anaerobes on lung function.

Cystic Fibrosis: Recent Insights into Inhaled Antibiotic Treatment and Future Perspectives

Although new inhaled antibiotics have profoundly improved respiratory diseases in cystic fibrosis (CF) patients, lung infections are still the leading cause of death. Inhaled antibiotics, i.e., colistin, tobramycin, aztreonam lysine and levofloxacin, are used as maintenance treatment for CF patients after the development of chronic Pseudomonas aeruginosa (P. aeruginosa) infection. Their use offers advantages over systemic therapy since a relatively high concentration of the drug is delivered directly to the lung, thus, enhancing the pharmacokinetic/pharmacodynamic parameters and decreasing toxicity. Notably, alternating treatment with inhaled antibiotics represents an important strategy for improving patient outcomes. The prevalence of CF patients receiving continuous inhaled antibiotic regimens with different combinations of the anti-P. aeruginosa antibiotic class has been increasing over time. Moreover, these antimicrobial agents are also used for preventing acute pulmonary exacerbations in CF. In this review, the efficacy and safety of the currently available inhaled antibiotics for lung infection treatment in CF patients are discussed, with a particular focus on strategies for eradicating P. aeruginosa and other pathogens. Moreover, the effects of long-term inhaled antibiotic therapy for chronic P. aeruginosa infection and for the prevention of pulmonary exacerbations is reviewed. Finally, how the mucus environment and microbial community richness can influence the efficacy of aerosolized antimicrobial agents is discussed.

One versus Many: Polymicrobial Communities and the Cystic Fibrosis Airway

Culture-independent studies have revealed that chronic lung infections in persons with cystic fibrosis (pwCF) are rarely limited to one microbial species. Interactions among bacterial members of these polymicrobial communities in the airways of pwCF have been reported to modulate clinically relevant phenotypes. Furthermore, it is clear that a single polymicrobial community in the context of CF airway infections cannot explain the diversity of clinical outcomes. While large 16S rRNA gene-based studies have allowed us to gain insight into the microbial composition and predicted functional capacities of communities found in the CF lung, here we argue that in silico approaches can help build clinically relevant in vitro models of polymicrobial communities that can in turn be used to experimentally test and validate computationally generated hypotheses. Furthermore, we posit that combining computational and experimental approaches will enhance our understanding of mechanisms that drive microbial community function and identify new therapeutics to target polymicrobial infections.

Outcomes of cystic fibrosis pulmonary exacerbations treated with antibiotics with activity against anaerobic bacteria

BACKGROUND

Obligate and facultative anaerobic bacteria are prevalent in cystic fibrosis (CF) airways. Increases in anaerobe relative abundance have been associated with CF pulmonary exacerbations (PEx); however, the impact of antibiotic treatment of anaerobes during PEx is unknown. We hypothesized that PEx treated with antibiotics with activity against anaerobes would improve outcomes compared to antibiotics without anaerobic activity.

METHODS

This was a single-center, retrospective study of people with CF, ages 6 years and older, treated with intravenous (IV) antibiotics for PEx. IV antibiotics were classified as either broad or minimal anaerobic activity. PEx treated with broad anaerobe coverage were propensity-score matched to PEx treated with minimal anaerobic coverage. The primary outcome, % of baseline % predicted forced expiratory volume in one second (ppFEV₁) recovered, was compared between antibiotic categories with a linear mixed model. The secondary outcome, time to next PEx, was assessed using a Prentice Williams Petersen model.

RESULTS

514 PEx from 182 patients were included. Broad anaerobe coverage was used in 27% of PEx, and was used more often for older patients (p < 0.001) with worse baseline ppFEV₁ (p < 0.001), and with Achromobacter (p < 0.001) or Burkholderia infections (p = 0.002). In the matched PEx, broad anaerobe coverage was not a significant predictor of % of baseline ppFEV₁ recovered (∆ppFEV₁ = -2.4, p = 0.09). Broad anaerobe coverage was also not a significant predictor of time to next PEx (HR 0.89, 95% CI 0.7-1.13, p = 0.35).

CONCLUSIONS

In this single center, retrospective study, antibiotics with broad activity against anaerobes were not associated with improved outcomes of CF PEx.

Metabolic Modeling to Interrogate Microbial Disease: A Tale for Experimentalists

The explosion of microbiome analyses has helped identify individual microorganisms and microbial communities driving human health and disease, but how these communities function is still an open question. For example, the role for the incredibly complex metabolic interactions among microbial species cannot easily be resolved by current experimental approaches such as 16S rRNA gene sequencing, metagenomics and/or metabolomics. Resolving such metabolic interactions is particularly challenging in the context of polymicrobial communities where metabolite exchange has been reported to impact key bacterial traits such as virulence and antibiotic treatment efficacy. As novel approaches are needed to pinpoint microbial determinants responsible for impacting community function in the context of human health and to facilitate the development of novel anti-infective and antimicrobial drugs, here we review, from the viewpoint of experimentalists, the latest advances in metabolic modeling, a computational method capable of predicting metabolic capabilities and interactions from individual microorganisms to complex ecological systems. We use selected examples from the literature to illustrate how metabolic modeling has been utilized, in combination with experiments, to better understand microbial community function. Finally, we propose how such combined, cross-disciplinary efforts can be utilized to drive laboratory work and drug discovery moving forward.

Liquid Chromatography Mass Spectrometry Detection of Antibiotic Agents in Sputum from Persons with Cystic Fibrosis

Antibiotic therapy is expected to impact host microbial communities considerably, yet many studies focused on microbiome and health are often confounded by limited information about antibiotic exposure. Given that antibiotics have diverse pharmacokinetic and antimicrobial properties, investigating the type and concentration of these agents in specific host specimens would provide much needed insight into their impact on the microbes therein. Here, we developed liquid chromatography mass spectrometry (LC-MS) methods to detect 18 antibiotic agents in sputum from persons with cystic fibrosis. Antibiotic spike-in control samples were used to compare three liquid extraction methods on the Waters Acquity Quattro Premier XE. Extraction with dithiothreitol captured the most antibiotics and was used to detect antibiotics in sputum samples from 11 people with cystic fibrosis, with results being compared to the individuals' self-reported antibiotic use. For the sputum samples, two LC-MS assays were used; the Quattro Premier detected nanomolar or micromolar concentrations of 16 antibiotics, whereas the Xevo TQ-XS detected all 18 antibiotics, most at subnanomolar levels. In 45% of tested sputum samples (71/158), at least one antibiotic that was not reported by the subject was detected by both LC-MS methods, a discordance largely explained by the thrice weekly administration and long half-life of azithromycin. For ∼37% of samples, antibiotics reported as taken by the individual were not detected by either instrument. Our results provide an approach for detecting a variety of antibiotics at the site of infection, thereby providing a means to include antibiotic usage data into microbiome studies.

Inflammation in children with cystic fibrosis: contribution of bacterial production of long-chain fatty acids

BACKGROUND

Cystic fibrosis (CF) affects >70,000 people worldwide, yet the microbiologic trigger for pulmonary exacerbations (PExs) remains unknown. The objective of this study was to identify changes in bacterial metabolic pathways associated with clinical status.

METHODS

Respiratory samples were collected at hospital admission for PEx, end of intravenous (IV) antibiotic treatment, and follow-up from 27 hospitalized children with CF. Bacterial DNA was extracted and shotgun DNA sequencing was performed. MetaPhlAn2 and HUMAnN2 were used to evaluate bacterial taxonomic and pathway relative abundance, while DESeq2 was used to evaluate differential abundance based on clinical status.

RESULTS

The mean age of study participants was 10 years; 85% received combination IV antibiotic therapy (beta-lactam plus a second agent). Long-chain fatty acid (LCFA) biosynthesis pathways were upregulated in follow-up samples compared to end of treatment: gondoate (p = 0.012), oleate (p = 0.048), palmitoleate (p = 0.043), and pathways of fatty acid elongation (p = 0.012). Achromobacter xylosoxidans and Escherichia sp. were also more prevalent in follow-up compared to PEx (p < 0.001).

CONCLUSIONS

LCFAs may be associated with persistent infection of opportunistic pathogens. Future studies should more closely investigate the role of LCFA production by lung bacteria in the transition from baseline wellness to PEx in persons with CF.

IMPACT

Increased levels of LCFAs are found after IV antibiotic treatment in persons with CF. LCFAs have previously been associated with increased lung inflammation in asthma. This is the first report of LCFAs in the airway of persons with CF. This research provides support that bacterial production of LCFAs may be a contributor to inflammation in persons with CF. Future studies should evaluate LCFAs as predictors of future PExs.

Ecological Succession of Polymicrobial Communities in the Cystic Fibrosis Airways

Antimicrobial therapies against cystic fibrosis (CF) lung infections are largely aimed at the traditional, well-studied CF pathogens such as Pseudomonas aeruginosa and Burkholderia cepacia complex, despite the fact that the CF lung harbors a complex and dynamic polymicrobial community. A clinical focus on the dominant pathogens ignores potentially important community-level interactions in disease pathology, perhaps explaining why these treatments are often less effective than predicted based on in vitro testing.

Antimicrobial therapies against cystic fibrosis (CF) lung infections are largely aimed at the traditional, well-studied CF pathogens such as Pseudomonas aeruginosa and Burkholderia cepacia complex, despite the fact that the CF lung harbors a complex and dynamic polymicrobial community. A clinical focus on the dominant pathogens ignores potentially important community-level interactions in disease pathology, perhaps explaining why these treatments are often less effective than predicted based on in vitro testing. A better understanding of the ecological dynamics of this ecosystem may enable clinicians to harness these interactions and thereby improve treatment outcomes. Like all ecosystems, the CF lung microbial community develops through a series of stages, each of which may present with distinct microbial communities that generate unique host-microbe and microbe-microbe interactions, metabolic profiles, and clinical phenotypes. While insightful models have been developed to explain some of these stages and interactions, there is no unifying model to describe how these infections develop and persist. Here, we review current perspectives on the ecology of the CF airway and present the CF Ecological Succession (CFES) model that aims to capture the spatial and temporal complexity of CF lung infection, address current challenges in disease management, and inform the development of ecologically driven therapeutic strategies.

Analysis of airway microbiota in adults from a Brazilian cystic fibrosis center

The application of next-generation sequencing tools revealed that the cystic fibrosis respiratory tract is a polymicrobial environment. We have characterized the airway bacterial microbiota of five adult patients with cystic fibrosis during a 14-month period by 16S rRNA tag sequencing using the Illumina technology. Microbial diversity, estimated by the Shannon index, varied among patient samples collected throughout the follow-up period. The beta diversity analysis revealed that the composition of the airway microbiota was highly specific for each patient, showing little variation among the samples of each patient analyzed over time. The composition of the bacterial microbiota did not reveal any emerging pathogen predictor of pulmonary disease in cystic fibrosis or of its unfavorable clinical progress, except for unveiling the presence of anaerobic microorganisms, even without any established clinical association. Our results could potentialy help us to translate and develop strategies in response to the pathobiology of this disease, particularly because it represents an innovative approach for CF centers in Brazil.

Maintenance tobramycin primarily affects untargeted bacteria in the CF sputum microbiome

RATIONALE

The most common antibiotic used to treat people with cystic fibrosis (PWCF) is inhaled tobramycin, administered as maintenance therapy for chronic Pseudomonas aeruginosa lung infections. While the effects of inhaled tobramycin on P. aeruginosa abundance and lung function diminish with continued therapy, this maintenance treatment is known to improve long-term outcomes, underscoring how little is known about why antibiotics work in CF infections, what their effects are on complex CF sputum microbiomes and how to improve these treatments.

OBJECTIVES

To rigorously define the effect of maintenance tobramycin on CF sputum microbiome characteristics.

METHODS AND MEASUREMENTS

We collected sputum from 30 PWCF at standardised times before, during and after a single month-long course of maintenance inhaled tobramycin. We used traditional culture, quantitative PCR and metagenomic sequencing to define the dynamic effects of this treatment on sputum microbiomes, including abundance changes in both clinically targeted and untargeted bacteria, as well as functional gene categories.

MAIN RESULTS

CF sputum microbiota changed most markedly by 1 week of antibiotic therapy and plateaued thereafter, and this shift was largely driven by changes in non-dominant taxa. The genetically conferred functional capacities (ie, metagenomes) of subjects' sputum communities changed little with antibiotic perturbation, despite taxonomic shifts, suggesting functional redundancy within the CF sputum microbiome.

CONCLUSIONS

Maintenance treatment with inhaled tobramycin, an antibiotic with demonstrated long-term mortality benefit, primarily impacted clinically untargeted bacteria in CF sputum, highlighting the importance of monitoring the non-canonical effects of antibiotics and other treatments to accurately define and improve their clinical impact.

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

Cystic fibrosis is an inherited disease characterized by chronic respiratory tract infection and progressive lung disease. Studies of cystic fibrosis lung microbiology often rely on expectorated sputum to reflect the microbiota present in the lower airways. Passage of sputum through the oropharynx during collection, however, contributes microbes present in saliva to the sample, which could confound interpretation of results. Using culture-independent DNA sequencing-based analyses, we characterized the bacterial communities in pairs of expectorated sputum and saliva samples to generate a model for “decontaminating” sputum in silico. Our results demonstrate that salivary contamination of expectorated sputum does not have a large effect on most sputum samples and that observations of high bacterial diversity likely accurately reflect taxa present in cystic fibrosis lower airways.

Culture-independent studies of the cystic fibrosis (CF) airway microbiome typically rely on expectorated sputum to assess the microbial makeup of lower airways. These studies have revealed rich bacterial communities. There is often considerable overlap between taxa observed in sputum and those observed in saliva, raising questions about the reliability of expectorated sputum as a sample representing lower airway microbiota. These concerns prompted us to compare pairs of sputum and saliva samples from 10 persons with CF. Using 16S rRNA gene sequencing and droplet digital PCR (ddPCR), we analyzed 37 pairs of sputum and saliva samples, each collected from the same person on the same day. We developed an in silico postsequencing decontamination procedure to remove from sputum the fraction of DNA reads estimated to have been contributed by saliva during expectoration. We demonstrate that while there was often sizeable overlap in community membership between sample types, expectorated sputum typically contains a higher bacterial load and a less diverse community compared to saliva. The differences in diversity between sputum and saliva were more pronounced in advanced disease stage, owing to increased relative abundance of the dominant taxa in sputum. Our effort to model saliva contamination of sputum in silico revealed generally minor effects on community structure after removal of contaminating reads. Despite considerable overlap in taxa observed between expectorated sputum and saliva samples, the impact of saliva contamination on measures of lower airway bacterial community composition in CF using expectorated sputum appears to be minimal.

IMPORTANCE Cystic fibrosis is an inherited disease characterized by chronic respiratory tract infection and progressive lung disease. Studies of cystic fibrosis lung microbiology often rely on expectorated sputum to reflect the microbiota present in the lower airways. Passage of sputum through the oropharynx during collection, however, contributes microbes present in saliva to the sample, which could confound interpretation of results. Using culture-independent DNA sequencing-based analyses, we characterized the bacterial communities in pairs of expectorated sputum and saliva samples to generate a model for “decontaminating” sputum in silico. Our results demonstrate that salivary contamination of expectorated sputum does not have a large effect on most sputum samples and that observations of high bacterial diversity likely accurately reflect taxa present in cystic fibrosis lower airways.

Untargeted Metagenomic Investigation of the Airway Microbiome of Cystic Fibrosis Patients with Moderate-Severe Lung Disease

Although the cystic fibrosis (CF) lung microbiota has been characterized in several studies, little is still known about the temporal changes occurring at the whole microbiome level using untargeted metagenomic analysis. The aim of this study was to investigate the taxonomic and functional temporal dynamics of the lower airway microbiome in a cohort of CF patients. Multiple sputum samples were collected over 15 months from 22 patients with advanced lung disease regularly attending three Italian CF Centers, given a total of 79 samples. DNA extracted from samples was subjected to shotgun metagenomic sequencing allowing both strain-level taxonomic profiling and assessment of the functional metagenomic repertoire. High inter-patient taxonomic heterogeneity was found with short-term compositional changes across clinical status. Each patient exhibited distinct sputum microbial communities at the taxonomic level, and strain-specific colonization of both traditional and atypical CF pathogens. A large core set of genes, including antibiotic resistance genes, were shared across patients despite observed differences in clinical status, and consistently detected in the lung microbiome of all subjects independently from known antibiotic exposure. In conclusion, an overall stability in the microbiome-associated genes was found despite taxonomic fluctuations of the communities.

Porphyromonas: A neglected potential key genus in human microbiomes

Anaerobes form a large part of microbial communities, and have begun to be specifically studied in both healthy and pathologic contexts. Porphyromonas is one of the top ten anaerobic taxa in the microbiome (anaerobiome) in healthy subjects. However, to date, most studies focused on the deleterious role of P. gingivalis, the most widely described species. Interestingly, targeted metagenomics reveals Porphyromonas other than gingivalis (POTG), highlighting other species such as P. catoniae or P. pasteri as potential biomarkers in disease progression or pathogen colonization susceptibility. From the sparse data, it appears that the Porphyromonas genus may also be a relevant target of investigation in several pulmonary diseases. Moreover, deciphering cutaneous, gastric and oral microbiomes hint that Porphyromonas may be a genus of interest in non-pulmonary diseases. This review aims to summarize the major data on POTG and to report their impact on the various human microbiomes in different clinical states.

The Respiratory Microbiome in Cystic Fibrosis: Compartment Patterns and Clinical Relationships in Early Stage Disease

We compared the bacterial microbiomes lodged in the bronchial tree, oropharynx and nose of patients with early stage cystic fibrosis (CF) not using chronic antibiotics, determining their relationships with lung function and exacerbation frequency. CF patients were enrolled in a cohort study during stability and were checked regularly over the following 9 months. Upper respiratory samples (sputum [S], oropharyngeal swab [OP] and nasal washing [N]) were collected at the first visit and every 3 months. 16S rRNA gene amplification and sequencing was performed and analyzed with QIIME. Seventeen CF patients were enrolled (16.6 SD 9.6 years). Alpha-diversity of bacterial communities between samples was significantly higher in S than in OP (Shannon index median 4.6 [IQR: 4.1–4.9] vs. 3.7 [IQR: 3-1-4.1], p = 0.003/Chao 1 richness estimator median 97.75 [IQR: 85.1–110.9] vs. 43.9 [IQR: 31.7–59.9], p = 0.003) and beta-diversity analysis also showed significant differences in the microbial composition of both respiratory compartments (Adonis test of Bray Curtis dissimilarity matrix, p = 0.001). Dominant taxa were found at baseline in five patients (29.4%), who showed lower forced expiratory volume in the first second (FEV1%, mean 74.8 [SD 19] vs. 97.2 [SD 17.8], p = 0.035, Student t test). The Staphylococcus genus had low RAs in most samples (median 0.26% [IQR 0.01–0.69%]), but patients with RA > 0.26% of Staphylococcus in bronchial secretions suffered more exacerbations during follow-up (median 2 [IQR 1–2.25] vs. 0 [0–1], p = 0.026. Mann–Whitney U test), due to S. aureus in more than a half of the cases, microorganism that often persists as bronchial colonized in these patients (9/10 [90%] vs. 2/7 [28.6%], p = 0.034, Fisher’s exact test). In conclusion, the bronchial microbiome had significantly higher diversity than the microbial flora lodged in the oropharynx in early stage CF. Although the RA of the Staphylococcus genus was low in bronchial secretions and did not reach a dominance pattern, slight overrepresentations of this genus was associated with higher exacerbation frequencies in these patients.

High-Resolution Longitudinal Dynamics of the Cystic Fibrosis Sputum Microbiome and Metabolome through Antibiotic Therapy

Microbial diversity in the cystic fibrosis (CF) lung decreases over decades as pathogenic bacteria such as Pseudomonas aeruginosa take over. The dynamics of the CF microbiome and metabolome over shorter time frames, however, remain poorly studied. Here, we analyze paired microbiome and metabolome data from 594 sputum samples collected over 401 days from six adult CF subjects (subject mean = 179 days) through periods of clinical stability and 11 CF pulmonary exacerbations (CFPE). While microbiome profiles were personalized (permutational multivariate analysis of variance [PERMANOVA] r ² = 0.79, P < 0.001), we observed significant intraindividual temporal variation that was highest during clinical stability (linear mixed-effects [LME] model, P = 0.002). This included periods where the microbiomes of different subjects became highly similar (UniFrac distance, <0.05). There was a linear increase in the microbiome alpha-diversity and in the log ratio of anaerobes to pathogens with time (n = 14 days) during the development of a CFPE (LME P = 0.0045 and P = 0.029, respectively). Collectively, comparing samples across disease states showed there was a reduction of these two measures during antibiotic treatment (LME P = 0.0096 and P = 0.014, respectively), but the stability data and CFPE data were not significantly different from each other. Metabolome alpha-diversity was higher during CFPE than during stability (LME P = 0.0085), but no consistent metabolite signatures of CFPE across subjects were identified. Virulence-associated metabolites from P. aeruginosa were temporally dynamic but were not associated with any disease state. One subject died during the collection period, enabling a detailed look at changes in the 194 days prior to death. This subject had over 90% Pseudomonas in the microbiome at the beginning of sampling, and that level gradually increased to over 99% prior to death. This study revealed that the CF microbiome and metabolome of some subjects are dynamic through time. Future work is needed to understand what drives these temporal dynamics and if reduction of anaerobes correlate to clinical response to CFPE therapy.IMPORTANCE Subjects with cystic fibrosis battle polymicrobial lung infections throughout their lifetime. Although antibiotic therapy is a principal treatment for CF lung disease, we have little understanding of how antibiotics affect the CF lung microbiome and metabolome and how much the community changes on daily timescales. By analyzing 594 longitudinal CF sputum samples from six adult subjects, we show that the sputum microbiome and metabolome are dynamic. Significant changes occur during times of stability and also through pulmonary exacerbations (CFPEs). Microbiome alpha-diversity increased as a CFPE developed and then decreased during treatment in a manner corresponding to the reduction in the log ratio of anaerobic bacteria to classic pathogens. Levels of metabolites from the pathogen P. aeruginosa were also highly variable through time and were negatively associated with anaerobes. The microbial dynamics observed in this study may have a significant impact on the outcome of antibiotic therapy for CFPEs and overall subject health.

Methods for Extraction and Detection of Pf Bacteriophage DNA from the Sputum of Patients with Cystic Fibrosis

Background: There is increasing interest in the pulmonary microbiome's bacterial and viral communities, particularly in the context of chronic airway infections in cystic fibrosis (CF). However, the isolation of microbial DNA from the sputum from patients with CF is technically challenging and the optimal protocols for the analysis of viral species, including bacteriophage, from clinical samples remains difficult. Materials and Methods: In this study, we evaluate a set of methods developed for processing and analyzing sputum from patients with CF with the goal of detecting Pf bacteriophage virion-derived nucleic acid. We evaluate the impact of bead beating, deoxyribonuclease digestion, and heating steps in these protocols focusing on the quantitative assessment of Pseudomonas aeruginosa and Pf bacteriophage in sputum. Results: Based on these comparative data, we describe an optimized protocol for processing sputum from patients with CF and isolating DNA for polymerase chain reaction or sequencing-based studies. Conclusion: These studies demonstrate the assessment of a specific bacteriophage and bacteria in sputum from patients with CF.

Bioorthogonal non-canonical amino acid tagging reveals translationally active subpopulations of the cystic fibrosis lung microbiota

Culture-independent studies of cystic fibrosis lung microbiota have provided few mechanistic insights into the polymicrobial basis of disease. Deciphering the specific contributions of individual taxa to CF pathogenesis requires comprehensive understanding of their ecophysiology at the site of infection. We hypothesize that only a subset of CF microbiota are translationally active and that these activities vary between subjects. Here, we apply bioorthogonal non-canonical amino acid tagging (BONCAT) to visualize and quantify bacterial translational activity in expectorated sputum. We report that the percentage of BONCAT-labeled (i.e. active) bacterial cells varies substantially between subjects (6-56%). We use fluorescence-activated cell sorting (FACS) and genomic sequencing to assign taxonomy to BONCAT-labeled cells. While many abundant taxa are indeed active, most bacterial species detected by conventional molecular profiling show a mixed population of both BONCAT-labeled and unlabeled cells, suggesting heterogeneous growth rates in sputum. Differentiating translationally active subpopulations adds to our evolving understanding of CF lung disease and may help guide antibiotic therapies targeting bacteria most likely to be susceptible.

Longitudinal Associations of the Cystic Fibrosis Airway Microbiome and Volatile Metabolites: A Case Study

The identification of 16S rDNA biomarkers from respiratory samples to describe the continuum of clinical disease states within persons having cystic fibrosis (CF) has remained elusive. We sought to combine 16S, metagenomics, and metabolomics data to describe multiple transitions between clinical disease states in 14 samples collected over a 12-month period in a single person with CF. We hypothesized that each clinical disease state would have a unique combination of bacterial genera and volatile metabolites as a potential signature that could be utilized as a biomarker of clinical disease state. Taxonomy identified by 16S sequencing corroborated clinical culture results, with the majority of the 109 PCR amplicons belonging to the bacteria grown in clinical cultures (Escherichia coli and Staphylococcus aureus). While alpha diversity measures fluctuated across disease states, no significant trends were present. Principle coordinates analysis showed that treatment samples trended toward a different community composition than baseline and exacerbation samples. This was driven by the phylum Bacteroidetes (less abundant in treatment, log2 fold difference -3.29, p = 0.015) and the genus Stenotrophomonas (more abundant in treatment, log2 fold difference 6.26, p = 0.003). Across all sputum samples, 466 distinct volatile metabolites were identified with total intensity varying across clinical disease state. Baseline and exacerbation samples were rather uniform in chemical composition and similar to one another, while treatment samples were highly variable and differed from the other two disease states. When utilizing a combination of the microbiome and metabolome data, we observed associations between samples dominated Staphylococcus and Escherichia and higher relative abundances of alcohols, while samples dominated by Achromobacter correlated with a metabolomics shift toward more oxidized volatiles. However, the microbiome and metabolome data were not tightly correlated; examining both the metagenomics and metabolomics allows for more context to examine changes across clinical disease states. In our study, combining the sputum microbiome and metabolome data revealed stability in the sputum composition through the first exacerbation and treatment episode, and into the second exacerbation. However, the second treatment ushered in a prolonged period of instability, which after three additional exacerbations and treatments culminated in a new lung microbiome and metabolome.

Bacterial Infections and the Respiratory Microbiome

Cystic fibrosis (CF) is a genetic, multisystem disease due to defects in the cystic fibrosis transmembrane conductance regulator (CFTR) protein, an anion channel responsible for chloride and bicarbonate trafficking. Although this channel is expressed in many tissues, its impaired function in airway epithelial cells leads to hyperviscous mucous secretions impeding effective mucociliary clearance. Impaired clearance of inhaled microorganisms results in the establishment of chronic infection, triggering an overexaggerated inflammatory response. The resulting release of inflammatory cytokines and enzymes causes pulmonary damage in the form of bronchiectasis, further impairing mucociliary action, forming a vicious cycle. Subsequent respiratory failure remains the leading cause of death in individuals with CF.