Cystic fibrosis therapy: a community ecology perspective

Elucidating the augmented resistance profile of Scedosporium/Lomentospora species to azoles in a cystic fibrosis mimic environment

BACKGROUND

Scedosporium/Lomentospora species are ranked as the second most frequently isolated filamentous fungi from cystic fibrosis (CF) patients. Previously, we demonstrated that the minimum inhibitory concentration (MIC) for voriconazole and posaconazole increased when performed on a mucin-containing synthetic CF sputum medium (SCFM) compared to the standard medium, RPMI-1640. In this study, we have expanded the MIC comparison to four additional azoles and investigated characteristics linked to azole resistance in Scedosporium apiospermum, Scedosporium minutisporum, Scedosporium aurantiacum and Lomentospora prolificans.

METHODS

MIC was assayed by CLSI protocol, efflux pump activity was assessed by rhodamine 6G and sterols were analysed by gas chromatography-mass spectrometry (GC-MS).

RESULTS

Overall, MICs for fluconazole, itraconazole, voriconazole, posaconazole, miconazole and ketoconazole increased by least 2-fold when susceptibility tests were performed using SCFM compared to RPMI. The activity of efflux pumps was similar in both media; however, in RPMI, but not in SCFM, the activity was induced by voriconazole and fluconazole. Additionally, MICs for those antifungals decreased more noticeably in SCFM than in RPMI in the presence of the efflux pump inhibitor PaβN. The SCFM-grown cells presented fewer sterols in their composition, and consequently higher membrane fluidity, than RPMI-grown cells. GC-MS analysis demonstrated a remodulation in the sterol profile in SCFM- compared to RPMI-grown cells. Accordingly, when the MIC assay was performed in the presence of the membrane stressor NaCl (3%), the susceptibility to voriconazole and fluconazole increased more in SCFM- than RPMI-grown cells.

CONCLUSIONS

Scedosporium/Lomentospora species undergo cellular adaptations in SCFM that favours their growth in face of the challenges imposed by azole antifungals.

The lower airway microbiome in paediatric health and chronic disease

The advent of next generation sequencing has rapidly challenged the paediatric respiratory physician's understanding of lung microbiology and the role of the lung microbiome in host health and disease. In particular, the role of "microbial key players" in paediatric respiratory disease is yet to be fully explained. Accurate profiling of the lung microbiome in children is challenging since the ability to obtain lower airway samples coupled with processing "low-biomass specimens" are both technically difficult. Many studies provide conflicting results. Early microbiota-host relationships may be predictive of the development of chronic respiratory disease but attempts to correlate lower airway microbiota in premature infants and risk of developing bronchopulmonary dysplasia (BPD) have produced mixed results. There are differences in lung microbiota in asthma and cystic fibrosis (CF). The increased abundance of oral taxa in the lungs may (or may not) promote disease processes in asthma and CF. In CF, correlation between microbiota diversity and respiratory decline is commonly observed. When one considers other pathogens beyond the bacterial kingdom, the contribution and interplay of fungi and viruses within the lung microbiome further increase complexity. Similarly, the interaction between microbial communities in different body sites, such as the gut-lung axis, and the influence of environmental factors, including diet, make the co-existence of host and microbes ever more complicated. Future, multi-omics approaches may help uncover novel microbiome-based biomarkers and therapeutic targets in respiratory disease and explain how we can live in harmony with our microbial companions.

Fungal lung disease

Fungal lung disease encompasses a wide spectrum of organisms and associated clinical conditions, presenting a significant global health challenge. The type and severity of disease are determined by underlying host immunity and infecting fungal strain. The most common group of diseases are associated with the filamentous fungus Aspergillus species and include allergic bronchopulmonary aspergillosis, sensitisation, aspergilloma and chronic and invasive pulmonary aspergillosis. Fungal lung disease remains epidemiologically heterogenous and is influenced by geography, environment and host comorbidities. Diagnostic modalities continue to evolve and now include novel molecular assays and biomarkers; however, persisting challenges include achieving rapid and accurate diagnosis, particularly in resource-limited settings, and in differentiating fungal infection from other pulmonary conditions. Treatment strategies for fungal lung diseases rely mainly on antifungal agents but the emergence of drug-resistant strains poses a substantial global threat and adds complexity to existing therapeutic challenges. Emerging antifungal agents and increasing insight into the lung mycobiome may offer fresh and personalised approaches to diagnosis and treatment. Innovative methodologies are required to mitigate drug resistance and the adverse effects of treatment. This state-of-the-art review describes the current landscape of fungal lung disease, highlighting key clinical insights, current challenges and emerging approaches for its diagnosis and treatment.

Metagenomics Applied to the Respiratory Mycobiome in Cystic Fibrosis

Cystic fibrosis (CF) is a genetic disorder characterized by chronic microbial colonization and inflammation of the respiratory tract (RT), leading to pulmonary exacerbation (PEx) and lung damage. Although the lung bacterial microbiota has been extensively studied, the mycobiome remains understudied. However, its importance as a contributor to CF pathophysiology has been highlighted. The objective of this review is to provide an overview of the current state of knowledge regarding the mycobiome, as described through NGS-based studies, in patients with CF (pwCF).Several studies have demonstrated that the mycobiome in CF lungs is a dynamic entity, exhibiting a lower diversity and abundance than the bacterial microbiome. Nevertheless, the progression of lung damage is associated with a decrease in fungal and bacterial diversity. The core mycobiome of the RT in pwCFs is mainly composed of yeasts (Candida spp., Malassezia spp.) and molds with lower abundance. Some fungi (Aspergillus, Scedosporium/Pseudallescheria) have been demonstrated to play a role in PEx, while the involvement of others (Candida, Pneumocystis) remains uncertain. The "climax attack" ecological model has been proposed to explain the complexity and interplay of microbial populations in the RT, leading to PEx and lung damage. NGS-based studies also enable the detection of intra- and interkingdom correlations between fungi and bacteria. Further studies are required to ascertain the biological and pathophysiological relevance of these correlations. Finally, with the recent advent of CFTR modulators, our understanding of the pulmonary microbiome and mycobiome in pwCFs is about to change.

The past, present and future of polymicrobial infection research: Modelling, eavesdropping, terraforming and other stories

Over the last two centuries, great advances have been made in microbiology as a discipline. Much of this progress has come about as a consequence of studying the growth and physiology of individual microbial species in well-defined laboratory media; so-called "axenic growth". However, in the real world, microbes rarely live in such "splendid isolation" (to paraphrase Foster) and more often-than-not, share the niche with a plethora of co-habitants. The resulting interactions between species (and even between kingdoms) are only very poorly understood, both on a theoretical and experimental level. Nevertheless, the last few years have seen significant progress, and in this review, we assess the importance of polymicrobial infections, and show how improved experimental traction is advancing our understanding of these. A particular focus is on developments that are allowing us to capture the key features of polymicrobial infection scenarios, especially as those associated with the human airways (both healthy and diseased).

From hype to hope: Considerations in conducting robust microbiome science

Microbiome science has been one of the most exciting and rapidly evolving research fields in the past two decades. Breakthroughs in technologies including DNA sequencing have meant that the trillions of microbes (particularly bacteria) inhabiting human biological niches (particularly the gut) can be profiled and analysed in exquisite detail. This microbiome profiling has profound impacts across many fields of research, especially biomedical science, with implications for how we understand and ultimately treat a wide range of human disorders. However, like many great scientific frontiers in human history, the pioneering nature of microbiome research comes with a multitude of challenges and potential pitfalls. These include the reproducibility and robustness of microbiome science, especially in its applications to human health outcomes. In this article, we address the enormous promise of microbiome science and its many challenges, proposing constructive solutions to enhance the reproducibility and robustness of research in this nascent field. The optimisation of microbiome science spans research design, implementation and analysis, and we discuss specific aspects such as the importance of ecological principals and functionality, challenges with microbiome-modulating therapies and the consideration of confounding, alternative options for microbiome sequencing, and the potential of machine learning and computational science to advance the field. The power of microbiome science promises to revolutionise our understanding of many diseases and provide new approaches to prevention, early diagnosis, and treatment.

The phage fought the cells, and the phage won: a satellite symposium at the ASV 2023 annual meeting

This satellite symposium was focused on the molecular arms race between bacteria and their predators, the bacteriophages: who's the friend and who's the foe? This Gem recounts highlights of the talks and presents food for thought and additional reflections on the current state of the field.

Mathematical models of cystic fibrosis as a systemic disease

Cystic fibrosis (CF) is widely known as a disease of the lung, even though it is in truth a systemic disease, whose symptoms typically manifest in gastrointestinal dysfunction first. CF ultimately impairs not only the pancreas and intestine but also the lungs, gonads, liver, kidneys, bones, and the cardiovascular system. It is caused by one of several mutations in the gene of the epithelial ion channel protein CFTR. Intense research and improved antimicrobial treatments during the past eight decades have steadily increased the predicted life expectancy of a person with CF (pwCF) from a few weeks to over 50 years. Moreover, several drugs ameliorating the sequelae of the disease have become available in recent years, and notable treatments of the root cause of the disease have recently generated substantial improvements in health for some but not all pwCF. Yet, numerous fundamental questions remain unanswered. Complicating CF, for instance in the lung, is the fact that the associated insufficient chloride secretion typically perturbs the electrochemical balance across epithelia and, in the airways, leads to the accumulation of thick, viscous mucus and mucus plaques that cannot be cleared effectively and provide a rich breeding ground for a spectrum of bacterial and fungal communities. The subsequent infections often become chronic and respond poorly to antibiotic treatments, with outcomes sometimes only weakly correlated with the drug susceptibility of the target pathogen. Furthermore, in contrast to rapidly resolved acute infections with a single target pathogen, chronic infections commonly involve multi-species bacterial communities, called "infection microbiomes," that develop their own ecological and evolutionary dynamics. It is presently impossible to devise mathematical models of CF in its entirety, but it is feasible to design models for many of the distinct drivers of the disease. Building upon these growing yet isolated modeling efforts, we discuss in the following the feasibility of a multi-scale modeling framework, known as template-and-anchor modeling, that allows the gradual integration of refined sub-models with different granularity. The article first reviews the most important biomedical aspects of CF and subsequently describes mathematical modeling approaches that already exist or have the potential to deepen our understanding of the multitude aspects of the disease and their interrelationships. The conceptual ideas behind the approaches proposed here do not only pertain to CF but are translatable to other systemic diseases. This article is categorized under: Congenital Diseases > Computational Models.

Airway infections as a risk factor for Pseudomonas aeruginosa acquisition and chronic colonisation in children with cystic fibrosis

BACKGROUND

Pseudomonas aeruginosa (Pa) infection is detrimental to people with cystic fibrosis (pwCF). Several clinical and genetic factors predispose to early Pa infections. However, the role of earlier infections with other pathogens on the risk of Pa infection in paediatric pwCF remains unknown.

METHODS

Using Kaplan-Meier method, we computed the cumulative incidences of bacterial and fungal initial acquisition (IA) and chronic colonisation (CC) in 1,231 French pwCF under 18 years of age for methicillin-susceptible and resistant Staphylococcus aureus (MSSA and MRSA), Stenotrophomonas maltophilia, Haemophilus influenzae, Achromobacter xylosoxidans, and Aspergillus species. Previous infections were analysed as Pa-IA and Pa-CC risk factors using Cox regression models.

RESULTS

By 2 years of age, 65.5% pwCF had experienced at least one bacterial or fungal IA, and 27.9% had experienced at least one CC. The median age of Pa-IA was 5.1 years, and Pa-CC was present in 25% pwCF by 14.7 years. While 50% acquired MSSA at 2.1 years, 50% progressed to chronic MSSA colonisation at 8.4 years. At 7.9 and 9.7 years, 25% pwCF were infected by S. maltophilia and Aspergillus spp., respectively. The risk of Pa-IA and Pa-CC increased with IAs of all other species, with hazard ratios (HR) up to 2.19 (95% Confidence interval (CI) 1.18-4.07). The risk of Pa-IA increased with the number of previous bacterial/fungal IAs (HR=1.89, 95% CI 1.57-2.28), with a 16% increase per additional pathogen; same trend was noted for Pa-CC.

CONCLUSIONS

This study establishes that the microbial community in CF airways can modulate Pa occurrence. At the dawn of targeted therapies, it paves the way for characterizing future trends and evolution of infections.

Therapeutic interventions alter ecological interactions among cystic fibrosis airway microbiota

The airways of people with cystic fibrosis (CF) often harbor a diverse microbiota and in recent years, much effort has been invested in cataloguing these. In spite of providing a wealth of insight, this cataloguing tells us little about how the organisms interact with one another in the CF airways. However, such relationships can be inferred using the theoretical framework of the Lotka-Volterra (LV) model. In the current work, we use a generalized Lotka-Volterra model to interrogate the nationwide data collected and curated by the UK CF Registry. This longitudinal dataset (covering the period 2008-2020) contains annual depositions that record the presence/absence of microbial taxa in each patient, their medication, and their CF genotype. Specifically, we wanted to identify trends in ecological relationships between the CF microbiota at a nationwide level, and whether these are potentially affected by medication. Our results show that some medications have a distinct influence on the microbial interactome, especially those that potentially influence the "gut-lung axis" or mucus viscosity. In particular, we found that patients treated with a combination of antimicrobial agents (targeting the airway microbiota), digestive enzymes (assisting in the assimilation of dietary fats and carbohydrates), and DNase (to reduce mucus viscosity) displayed a distinctly different airway interactome compared with patients treated separately with these medications.

Scedosporium/Lomentospora Species Induce the Production of Siderophores by Pseudomonas aeruginosa in a Cystic Fibrosis Mimic Environment

Over the last years, the interkingdom microbial interactions concerning bacteria and fungi cohabiting and/or responsible for human pathologies have been investigated. In this context, the Gram-negative bacterium Pseudomonas aeruginosa and fungal species belonging to the Scedosporium/Lomentospora genera are widespread, multidrug-resistant, emergent, opportunistic pathogens that are usually co-isolated in patients with cystic fibrosis. The available literature reports that P. aeruginosa can inhibit the in vitro growth of Scedosporium/Lomentospora species; however, the complex mechanisms behind this phenomenon are mostly unknown. In the present work, we have explored the inhibitory effect of bioactive molecules secreted by P. aeruginosa (3 mucoid and 3 non-mucoid strains) on S. apiospermum (n = 6 strains), S. minutisporum (n = 3), S. aurantiacum (n = 6) and L. prolificans (n = 6) under cultivation in a cystic fibrosis mimic environment. It is relevant to highlight that all bacterial and fungal strains used in the present study were recovered from cystic fibrosis patients. The growth of Scedosporium/Lomentospora species was negatively affected by the direct interaction with either mucoid or non-mucoid strains of P. aeruginosa. Moreover, the fungal growth was inhibited by the conditioned supernatants obtained from bacteria-fungi co-cultivations and by the conditioned supernatants from the bacterial pure cultures. The interaction with fungal cells induced the production of pyoverdine and pyochelin, 2 well-known siderophores, in 4/6 clinical strains of P. aeruginosa. The inhibitory effects of these four bacterial strains and their secreted molecules on fungal cells were partially reduced with the addition of 5-flucytosine, a classical repressor of pyoverdine and pyochelin production. In sum, our results demonstrated that distinct clinical strains of P. aeruginosa can behave differently towards Scedosporium/Lomentospora species, even when isolated from the same cystic fibrosis patient. Additionally, the production of siderophores by P. aeruginosa was induced when co-cultivated with Scedosporium/Lomentospora species, indicating competition for iron and deprivation of this essential nutrient, leading to fungal growth inhibition.

Low Diversity and Instability of the Sinus Microbiota over Time in Adults with Cystic Fibrosis

Chronic rhinosinusitis (CRS) is a common, yet underreported and understudied manifestation of upper respiratory disease in people with cystic fibrosis (CF). Recently developed standard of care guidelines for the management of CF CRS suggest treatment of upper airway disease may ameliorate lower airway disease. We sought to determine whether changes to sinus microbial community diversity and specific taxa known to cause CF lung disease are associated with increased respiratory disease and inflammation. We performed 16S rRNA gene sequencing, supplemented with cytokine analyses, microscopy, and bacterial culturing, on samples from the sinuses of 27 adults with CF CRS. At each study visit, participants underwent endoscopic paranasal sinus sampling and clinical evaluation. We identified key drivers of microbial community composition and evaluated relationships between diversity and taxa with disease outcomes and inflammation. Sinus community diversity was low, and the composition was unstable, with many participants exhibiting alternating dominance between Pseudomonas aeruginosa and staphylococci over time. Despite a tendency for dominance by these two taxa, communities were highly individualized and shifted composition during exacerbation of sinus disease symptoms. Exacerbations were also associated with communities dominated by Staphylococcus spp. Reduced microbial community diversity was linked to worse sinus disease and the inflammatory status of the sinuses (including increased interleukin-1β [IL-1β]). Increased IL-1β was also linked to worse sinus endoscopic appearance, and other cytokines were linked to microbial community dynamics. Our work revealed previously unknown instability of sinus microbial communities and a link between inflammation, lack of microbial community diversity, and worse sinus disease. IMPORTANCE Together with prior sinus microbiota studies of adults with CF chronic rhinosinusitis, our study underscores similarities between sinus and lower respiratory tract microbial community structures in CF. We show how community structure tracks with inflammation and several disease measures. This work strongly suggests that clinical management of CRS could be leveraged to improve overall respiratory health in CF. Our work implicates elevated IL-1β in reduced microbiota diversity and worse sinus disease in CF CRS, suggesting applications for existing therapies targeting IL-1β. Finally, the widespread use of highly effective cystic fibrosis transmembrane conductance regulator (CFTR) modulator therapy has led to less frequent availability of spontaneous expectorated sputum for microbiological surveillance of lung infections. A better understanding of CF sinus microbiology could provide a much-needed alternative site for monitoring respiratory infection status by important CF pathogens.

Supplemental Oxygen Alters the Airway Microbiome in Cystic Fibrosis

Features of the airway microbiome in persons with cystic fibrosis (pwCF) are correlated with disease progression. Microbes have traditionally been classified for their ability to tolerate oxygen. It is unknown whether supplemental oxygen, a common medical intervention, affects the airway microbiome of pwCF. We hypothesized that hyperoxia significantly impacts the pulmonary microbiome in cystic fibrosis. In this study, we cultured spontaneously expectorated sputum from pwCF in artificial sputum medium under 21%, 50%, and 100% oxygen conditions using a previously validated model system that recapitulates microbial community composition in uncultured sputum. Culture aliquots taken at 24, 48, and 72 h, along with uncultured sputum, underwent shotgun metagenomic sequencing with absolute abundance values obtained with the use of spike-in bacteria. Raw sequencing files were processed using the bioBakery pipeline to determine changes in taxonomy, predicted function, antimicrobial resistance genes, and mobile genetic elements. Hyperoxia reduced absolute microbial load, species richness, and diversity. Hyperoxia reduced absolute abundance of specific microbes, including facultative anaerobes such as Rothia and some Streptococcus species, with minimal impact on canonical CF pathogens such as Pseudomonas aeruginosa and Staphylococcus aureus. The effect size of hyperoxia on predicted functional pathways was stronger than that on taxonomy. Large changes in microbial cooccurrence networks were noted. Hyperoxia exposure perturbs airway microbial communities in a manner well tolerated by key pathogens. Supplemental oxygen use may enable the growth of lung pathogens and should be further studied in the clinical setting. IMPORTANCE The airway microbiome in persons with cystic fibrosis (pwCF) is correlated with lung function and disease severity. Supplemental oxygen use is common in more advanced CF, yet its role in perturbing airway microbial communities is unknown. By culturing sputum samples from pwCF under normal and elevated oxygen conditions, we found that increased oxygen led to reduced total numbers and diversity of microbes, with relative sparing of common CF pathogens such as Pseudomonas aeruginosa and Staphylococcus aureus. Supplemental oxygen use may enable the growth of lung pathogens and should be further studied in the clinical setting.

Resistance evolution can disrupt antibiotic exposure protection through competitive exclusion of the protective species

Antibiotic degrading bacteria can reduce the efficacy of drug treatments by providing antibiotic exposure protection to pathogens. While this has been demonstrated at the ecological timescale, it is unclear how exposure protection might alter and be affected by pathogen antibiotic resistance evolution. Here, we utilised a two-species model cystic fibrosis (CF) community where we evolved the bacterial pathogen Pseudomonas aeruginosa in a range of imipenem concentrations in the absence or presence of Stenotrophomonas maltophilia, which can detoxify the environment by hydrolysing β-lactam antibiotics. We found that P. aeruginosa quickly evolved resistance to imipenem via parallel loss of function mutations in the oprD porin gene. While the level of resistance did not differ between mono- and co-culture treatments, the presence of S. maltophilia increased the rate of imipenem resistance evolution in the four μg/ml imipenem concentration. Unexpectedly, imipenem resistance evolution coincided with the extinction of S. maltophilia due to increased production of pyocyanin, which was cytotoxic to S. maltophilia. Together, our results show that pathogen resistance evolution can disrupt antibiotic exposure protection due to competitive exclusion of the protective species. Such eco-evolutionary feedbacks may help explain changes in the relative abundance of bacterial species within CF communities despite intrinsic resistance to anti-pseudomonal drugs.

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.

Decreased efficacy of antimicrobial agents in a polymicrobial environment

The airways of people with cystic fibrosis (CF) often harbour diverse polymicrobial communities. These airway infections can be impossible to resolve through antibiotic intervention, even though isolates of the individual species present are susceptible to the treatment when tested in vitro. In this work, we investigate how polymicrobial cultures comprised of key CF-associated pathogens respond to challenge with species-specific antimicrobial agents; colistin (targets Pseudomonas aeruginosa), fusidic acid (targets Staphylococcus aureus), and fluconazole (targets Candida albicans). We found that growth in a polymicrobial environment protects the target microorganism (sometimes by several orders of magnitude) from the effect(s) of the antimicrobial agent. This decreased antimicrobial efficacy was found to have both non-heritable (physiological) and heritable (genetic) components. Whole-genome sequencing of the colistin-resistant P. aeruginosa isolates revealed single nucleotide polymorphisms and indels in genes encoding lipopolysaccharide (LPS) biosynthesis and/or pilus biogenesis, indicating that a previously undescribed colistin resistance mechanism was in operation. This was subsequently confirmed through further genetic analyses. Our findings indicate that the polymicrobial nature of the CF airways is likely to have a significant impact on the clinical response to antimicrobial therapy.

Food-web and metabolic interactions of the lung inhabitants Streptococcus pneumoniae and Pseudomonas aeruginosa

Bacteria that successfully adapt to different substrates and environmental niches within the lung and overcome the immune defence can cause serious lung infections. Such infections are generally complex, and recognised as polymicrobial in nature. Both Pseudomonas aeruginosa and Streptococcus pneumoniae can cause chronic lung infections and were both detected in cystic fibrosis (CF) lung at different stages. In this study, single and dual species cultures of Pseudomonas aeruginosa and Streptococcus pneumoniae were studied under well controlled planktonic growth conditions. Under pH-controlled conditions, both species apparently benefited from the presence of the other. In co-culture with P. aeruginosa, S. pneumoniae grew efficiently under aerobic conditions, whereas in pure S. pneumoniae culture, growth inhibition occurred in bioreactors with dissolved oxygen concentrations above the microaerobic range. Lactic acid and acetoin that are produced by S. pneumoniae was efficiently utilised by P. aeruginosa. In pH-uncontrolled co-cultures, the low pH triggered by S. pneumoniae assimilation of glucose and lactic acid production negatively affected the growth of both strains. Nevertheless, ammonia production improved significantly, and P. aeruginosa growth dominated at later growth stages. This study revealed unreported metabolic interactions of two important pathogenic microorganisms and shed new lights into pathophysiology of bacterial lung infection. This article is protected by copyright. All rights reserved.

de la Pedrosa E, López-Campos JL, Máiz L, del Campo R, Martínez-García MÁ. The Human Mycobiome in Chronic Respiratory Diseases: Current Situation and Future Perspectives

Microbes play an important role in the pathogenesis of chronic lung diseases, such as chronic obstructive pulmonary disease, cystic fibrosis, non-cystic fibrosis bronchiectasis, and asthma. While the role of bacterial pathogens has been extensively studied, the contribution of fungal species to the pathogenesis of chronic lung diseases is much less understood. The recent introduction of next-generation sequencing techniques has revealed the existence of complex microbial lung communities in healthy individuals and patients with chronic respiratory disorders, with fungi being an important part of these communities' structure (mycobiome). There is growing evidence that the components of the lung mycobiome influence the clinical course of chronic respiratory diseases, not only by direct pathogenesis but also by interacting with bacterial species and with the host's physiology. In this article, we review the current knowledge on the role of fungi in chronic respiratory diseases, which was obtained by conventional culture and next-generation sequencing, highlighting the limitations of both techniques and exploring future research areas.

Recent Advances in Fungal Infections: From Lung Ecology to Therapeutic Strategies With a Focus on Aspergillus spp

Fungal infections are estimated to be the main cause of death for more than 1.5 million people worldwide annually. However, fungal pathogenicity has been largely neglected. This is notably the case for pulmonary fungal infections, which are difficult to diagnose and to treat. We are currently facing a global emergence of antifungal resistance, which decreases the chances of survival for affected patients. New therapeutic approaches are therefore needed to face these life-threatening fungal infections. In this review, we will provide a general overview on respiratory fungal infections, with a focus on fungi of the genus Aspergillus. Next, the immunological and microbiological mechanisms of fungal pathogenesis will be discussed. The role of the respiratory mycobiota and its interactions with the bacterial microbiota on lung fungal infections will be presented from an ecological perspective. Finally, we will focus on existing and future innovative approaches for the treatment of respiratory fungal infections.

The value of CT radiomic in differentiating mycoplasma pneumoniae pneumonia from streptococcus pneumoniae pneumonia with similar consolidation in children under 5 years

OBJECTIVE

To investigate the value of CT radiomics in the differentiation of mycoplasma pneumoniae pneumonia (MPP) from streptococcus pneumoniae pneumonia (SPP) with similar CT manifestations in children under 5 years.

METHODS

A total of 102 children with MPP (n = 52) or SPP (n = 50) with similar consolidation and surrounding halo on CT images in Qilu Hospital and Qilu Children's Hospital between January 2017 and March 2022 were enrolled in the retrospective study. Radiomic features of the both lesions on plain CT images were extracted including the consolidation part of the pneumonia or both consolidation and surrounding halo area which were respectively delineated at region of interest (ROI) areas on the maximum axial image. The training cohort (n = 71) and the validation cohort (n = 31) were established by stratified random sampling at a ratio of 7:3. By means of variance threshold, the effective radiomics features, SelectKBest and least absolute shrinkage and selection operator (LASSO) regression method were employed for feature selection and combined to calculate the radiomics score (Rad-score). Six classifiers, including k-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), logistic regression (LR), and decision tree (DT) were used to construct the models based on radiomic features. The diagnostic performance of these models and the radiomic nomogram was estimated and compared using the area under the receiver operating characteristic (ROC) curve (AUC), and the decision curve analysis (DCA) was used to evaluate which model achieved the most net benefit.

RESULTS

RF outperformed other classifiers and was selected as the backbone in the classifier with the consolidation + the surrounding halo was taken as ROI to differentiate MPP from SPP in validation cohort. The AUC value of MPP in validation cohort was 0.822, the sensitivity and specificity were 0.81 and 0.81, respectively.

CONCLUSION

The RF model has the best classification efficiency in the identification of MPP from SPP in children, and the ROI with both consolidation and surrounding halo is most suitable for the delineation.

Multi-Omics Study of Keystone Species in a Cystic Fibrosis Microbiome

Ecological networking and in vitro studies predict that anaerobic, mucus-degrading bacteria are keystone species in cystic fibrosis (CF) microbiomes. The metabolic byproducts from these bacteria facilitate the colonization and growth of CF pathogens like Pseudomonas aeruginosa. Here, a multi-omics study informed the control of putative anaerobic keystone species during a transition in antibiotic therapy of a CF patient. A quantitative metagenomics approach combining sequence data with epifluorescence microscopy showed that during periods of rapid lung function loss, the patient's lung microbiome was dominated by the anaerobic, mucus-degrading bacteria belonging to Streptococcus, Veillonella, and Prevotella genera. Untargeted metabolomics and community cultures identified high rates of fermentation in these sputa, with the accumulation of lactic acid, citric acid, and acetic acid. P. aeruginosa utilized these fermentation products for growth, as indicated by quantitative transcriptomics data. Transcription levels of P. aeruginosa genes for the utilization of fermentation products were proportional to the abundance of anaerobic bacteria. Clindamycin therapy targeting Gram-positive anaerobes rapidly suppressed anaerobic bacteria and the accumulation of fermentation products. Clindamycin also lowered the abundance and transcription of P. aeruginosa, even though this patient's strain was resistant to this antibiotic. The treatment stabilized the patient's lung function and improved respiratory health for two months, lengthening by a factor of four the between-hospitalization time for this patient. Killing anaerobes indirectly limited the growth of P. aeruginosa by disrupting the cross-feeding of fermentation products. This case study supports the hypothesis that facultative anaerobes operated as keystone species in this CF microbiome. Personalized multi-omics may become a viable approach for routine clinical diagnostics in the future, providing critical information to inform treatment decisions.

The Gut-Lung Axis in Cystic Fibrosis

Cystic fibrosis (CF) is a heritable, multiorgan disease that impacts all tissues that normally express cystic fibrosis transmembrane conductance regulator (CFTR) protein. While the importance of the airway microbiota has long been recognized, the intestinal microbiota has only recently been recognized as an important player in both intestinal and lung health outcomes for persons with CF (pwCF). Here, we summarize current literature related to the gut-lung axis in CF, with a particular focus on three key ideas: (i) mechanisms through which microbes influence the gut-lung axis, (ii) drivers of microbiota alterations, and (iii) the potential for intestinal microbiota remediation.

Draft Genome Sequence of the Multidrug-Resistant Strain Pseudomonas aeruginosa PA291, Isolated from Cystic Fibrosis Sputum

Here, we report the genome sequence of PA291, a nonmucoid, multidrug-resistant strain of Pseudomonas aeruginosa isolated from cystic fibrosis sputum. Short reads were de novo assembled into 190 contigs and scaffold assembled to a length of 6.26 Mbp. PhiSpy predicts that PA291 is free of prophages.

Long-term coexistence of Pseudomonas aeruginosa and Staphylococcus aureus using an in vitro cystic fibrosis model

Aim: To investigate the role of pre-established Staphylococcus aureus on Pseudomonas aeruginosa adaptation and antibiotic tolerance. Materials & methods: Bacteria were cultured mimicking the sequential pattern of lung colonization and exposure to ciprofloxacin. Results: In the absence of ciprofloxacin exposure, S. aureus and P. aeruginosa coexisted supported by the physicochemical characteristics of the artificial sputum medium. S. aureus had no role in P. aeruginosa tolerance against ciprofloxacin and did not select P. aeruginosa small-colony variants during antibiotic treatment. rhlR and psqE were downregulated after the contact with S. aureus indicating that P. aeruginosa attenuated its virulence potential. Conclusion: P. aeruginosa and S. aureus can cohabit in cystic fibrosis airway environment for long-term without significant impact on P. aeruginosa adaptation and antibiotic tolerance.

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.

Filamentous Bacteriophages and the Competitive Interaction between Pseudomonas aeruginosa Strains under Antibiotic Treatment: a Modeling Study

Pseudomonas aeruginosa (Pa) is a major bacterial pathogen responsible for chronic lung infections in cystic fibrosis patients. Recent work has implicated Pf bacteriophages, nonlytic filamentous viruses produced by Pa, in the chronicity and severity of Pa infections. Pf phages act as structural elements in Pa biofilms and sequester aerosolized antibiotics, thereby contributing to antibiotic tolerance. Consistent with a selective advantage in this setting, the prevalence of Pf-positive (Pf+) bacteria increases over time in these patients. However, the production of Pf phages comes at a metabolic cost to bacteria, such that Pf+ strains grow more slowly than Pf-negative (Pf-) strains in vitro. Here, we use a mathematical model to investigate how these competing pressures might influence the relative abundance of Pf+ versus Pf- strains in different settings. Our model suggests that Pf+ strains of Pa cannot outcompete Pf- strains if the benefits of phage production falls onto both Pf+ and Pf- strains for a majority of parameter combinations. Further, phage production leads to a net positive gain in fitness only at antibiotic concentrations slightly above the MIC (i.e., concentrations for which the benefits of antibiotic sequestration outweigh the metabolic cost of phage production) but which are not lethal for Pf+ strains. As a result, our model suggests that frequent administration of intermediate doses of antibiotics with low decay rates and high killing rates favors Pf+ over Pf- strains. These models inform our understanding of the ecology of Pf phages and suggest potential treatment strategies for Pf+ Pa infections. IMPORTANCE Filamentous phages are a frontier in bacterial pathogenesis, but the impact of these phages on bacterial fitness is unclear. In particular, Pf phages produced by Pa promote antibiotic tolerance but are metabolically expensive to produce, suggesting that competing pressures may influence the prevalence of Pf+ versus Pf- strains of Pa in different settings. Our results identify conditions likely to favor Pf+ strains and thus antibiotic tolerance. This study contributes to a better understanding of the unique ecology of filamentous phages in both environmental and clinical settings and may facilitate improved treatment strategies for combating antibiotic tolerance.

Clinical Remission and Psychological Management are Major Issues for the Quality of Life in Pediatric Crohn Disease

OBJECTIVES

Crohn disease (CD) can affect patient's quality of life (QOL) with physical, social, and psychological impacts. This study aimed to investigate the QOL of children with CD and its relationship with patient and disease characteristics.

METHODS

Children ages from 10 to 17 years with diagnosed CD for more than 6 months were eligible to this cross-sectional study conducted in 35 French pediatric centers. QOL was assessed by the IMPACT-III questionnaire. Patient and disease characteristics were collected.

RESULTS

A total of 218 children (42% of girls) were included at a median age of 14 years (interquartile range [IQR]: 13--16). Median duration of CD was 3.2 years (IQR: 1.7-5.1) and 63% of children were in clinical remission assessed by wPCDAI. Total IMPACT-III score was 62.8 (±11.0). The lowest score was in "emotional functioning" subdomain (mean: 42.8 ± 11.2). Clinical remission was the main independent factor associated with QOL of children with CD (5.74 points higher compared with those "with active disease", 95% confidence interval [CI] 2.77--8.70, P < 0.001). Age of patient at the evaluation was found negatively correlated with QOL (-0.76 per year, 95% CI: -1.47 to -0.06, P = 0.009). Presence of psychological disorders was associated with a lower QOL (-9.6 points lower to those without, 95% CI: -13.34 to -5.86, P < 0.0001). Total IMPACT-III and its subdomains scores were not related to sex, disease duration, or treatments.

CONCLUSIONS

These results not only confirm that clinical remission is a major issue for the QOL of patients, but also highlights the importance of psychological care.

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.

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.

Multi-dimensional clinical phenotyping of a national cohort of adult cystic fibrosis patients

BACKGROUND

Cystic Fibrosis (CF) is a multi-systemic disorder resulting from genetic variation in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene which can result in bronchiectasis, chronic sinusitis, pancreatic malabsorption, cholestatic liver disease and distal intestinal obstructive syndrome. This study generates multi-dimensional clinical phenotypes that capture the complexity and spectrum of the disease manifestations seen in adult CF patients using statistically robust techniques.

METHODS

Pre-transplant clinical data from adult (age ≥18 years) CF patients (n = 992) seen in six regionally distinct US CF centers between 1/1/2014 and 6/30/2015 were included. Demographic, spirometry, nutritional, microbiological and therapy data were used to generate clusters using the Random Forests statistical-learning and Partitioning around Medoids (PAM) clustering algorithms. Five commonly measured demographic, physiological and nutritional parameters were needed to create the final phenotypes that are highly similar to a regionally matched group of patients from the CF Foundation Patient Registry RESULTS: This approach identified high-risk phenotypes with expected characteristics including high rates of pancreatic insufficiency, diabetes and Pseudomonas aeruginosa colonization. It also identified unexpected populations including a) a male-dominated, well-nourished group with good lung function with a high prevalence of severe genotypes (i.e. 60% subjects had two minimal function CFTR variations), b) and an older, "survivor" phenotype that had high rates of chronic P. aeruginosa infection.

CONCLUSIONS

This study identified recognizable phenotypes that capture the clinical complexity in a statistically robust manner and which may aide in the identification of specific genetic and environmental factors responsible for these disease manifestation patterns.

Direct Lung Sampling Indicates That Established Pathogens Dominate Early Infections in Children with Cystic Fibrosis

Culture and sequencing have produced divergent hypotheses about cystic fibrosis (CF) lung infections. Culturing suggests that CF lungs are uninfected before colonization by a limited group of CF pathogens. Sequencing suggests diverse communities of mostly oral bacteria inhabit lungs early on and diversity decreases as disease progresses. We studied the lung microbiota of CF children using bronchoscopy and sequencing, with measures to reduce contamination. We found no evidence for oral bacterial communities in lung lavages that lacked CF pathogens. Lavage microbial diversity varied widely, but decreases in diversity appeared to be driven by increased CF pathogen abundance, which reduced the signal from contaminants. Streptococcus, Prevotella, and Veillonella DNA was detected in some lavages containing CF pathogens, but DNA from these organisms was vastly exceeded by CF pathogen DNA and was not associated with inflammation. These findings support the hypothesis that established CF pathogens are primarily responsible for CF lung infections.

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.

Respiratory mycobiome and suggestion of inter-kingdom network during acute pulmonary exacerbation in cystic fibrosis

Lung infections play a critical role in cystic fibrosis (CF) pathogenesis. CF respiratory tract is now considered to be a polymicrobial niche and advances in high-throughput sequencing allowed to analyze its microbiota and mycobiota. However, no NGS studies until now have characterized both communities during CF pulmonary exacerbation (CFPE). Thirty-three sputa isolated from patients with and without CFPE were used for metagenomic high-throughput sequencing targeting 16S and ITS2 regions of bacterial and fungal rRNA. We built inter-kingdom network and adapted Phy-Lasso method to highlight correlations in compositional data. The decline in respiratory function was associated with a decrease in bacterial diversity. The inter-kingdom network revealed three main clusters organized around Aspergillus, Candida, and Scedosporium genera. Using Phy-Lasso method, we identified Aspergillus and Malassezia as relevantly associated with CFPE, and Scedosporium plus Pseudomonas with a decline in lung function. We corroborated in vitro the cross-domain interactions between Aspergillus and Streptococcus predicted by the correlation network. For the first time, we included documented mycobiome data into a version of the ecological Climax/Attack model that opens new lines of thoughts about the physiopathology of CF lung disease and future perspectives to improve its therapeutic management.

A Continuous-Flow Model for in vitro Cultivation of Mixed Microbial Populations Associated With Cystic Fibrosis Airway Infections

The airways of people with cystic fibrosis (CF) provide a nutrient-rich environment which favours colonisation by a variety of bacteria and fungi. Although the dominant pathogen associated with CF airway infections is Pseudomonas aeruginosa, it is becoming increasingly clear that inter-species interactions between P. aeruginosa and other colonists in the airways may have a large impact on microbial physiology and virulence. However, there are currently no suitable experimental models that permit long-term co-culture of P. aeruginosa with other CF-associated pathogens. Here, we redress this problem by describing a "3R's-compliant" continuous-flow in vitro culture model which enables long-term co-culture of three representative CF-associated microbes: P. aeruginosa, Staphylococcus aureus and Candida albicans. Although these species rapidly out-compete one another when grown together or in pairs in batch culture, we show that in a continuously-fed setup, they can be maintained in a very stable, steady-state community. We use our system to show that even numerically (0.1%) minor species can have a major impact on intercellular signalling by P. aeruginosa. Importantly, we also show that co-culturing does not appear to influence species mutation rates, further reinforcing the notion that the system favours stability rather than divergence. The model is experimentally tractable and offers an inexpensive yet robust means of investigating inter-species interactions between CF pathogens.

Selective pressures during chronic infection drive microbial competition and cooperation

Chronic infections often contain complex mixtures of pathogenic and commensal microorganisms ranging from aerobic and anaerobic bacteria to fungi and viruses. The microbial communities present in infected tissues are not passively co-existing but rather actively interacting with each other via a spectrum of competitive and/or cooperative mechanisms. Competition versus cooperation in these microbial interactions can be driven by both the composition of the microbial community as well as the presence of host defense strategies. These interactions are typically mediated via the production of secreted molecules. In this review, we will explore the possibility that microorganisms competing for nutrients at the host–pathogen interface can evolve seemingly cooperative mechanisms by controlling the production of subsets of secreted virulence factors. We will also address interspecies versus intraspecies utilization of community resources and discuss the impact that this phenomenon might have on co-evolution at the host–pathogen interface.

Cystic Fibrosis Rapid Response: Translating Multi-omics Data into Clinically Relevant Information

Proper management of polymicrobial infections in patients with cystic fibrosis (CF) has extended their life span. Information about the composition and dynamics of each patient’s microbial community aids in the selection of appropriate treatment of pulmonary exacerbations. We propose the cystic fibrosis rapid response (CFRR) as a fast approach to determine viral and microbial community composition and activity during CF pulmonary exacerbations. The CFRR potential is illustrated with a case study in which a cystic fibrosis fatal exacerbation was characterized by the presence of shigatoxigenic Escherichia coli. The incorporation of the CFRR within the CF clinic could increase the life span and quality of life of CF patients.

Pulmonary exacerbations are the leading cause of death in cystic fibrosis (CF) patients. To track microbial dynamics during acute exacerbations, a CF rapid response (CFRR) strategy was developed. The CFRR relies on viromics, metagenomics, metatranscriptomics, and metabolomics data to rapidly monitor active members of the viral and microbial community during acute CF exacerbations. To highlight CFRR, a case study of a CF patient is presented, in which an abrupt decline in lung function characterized a fatal exacerbation. The microbial community in the patient’s lungs was closely monitored through the multi-omics strategy, which led to the identification of pathogenic shigatoxigenic Escherichia coli (STEC) expressing Shiga toxin. This case study illustrates the potential for the CFRR to deconstruct complicated disease dynamics and provide clinicians with alternative treatments to improve the outcomes of pulmonary exacerbations and expand the life spans of individuals with CF.

A Developing Symbiosis: Enabling Cross-Talk Between Ecologists and Microbiome Scientists

Like all interactions, the success of cross-discipline collaborations relies on effective communication. Ecology offers theoretical frameworks and lexicons to study microbiomes. Yet some of the terms and concepts borrowed from ecology are being used discordantly by microbiome studies from their traditional definitions. Here we define some of the ecological terms and concepts as they are used in ecology and the study of microbiomes. Where applicable, we have provided the historical context of the terms, highlighted examples from microbiome studies, and considered the research methods involved. We divided these concepts into four sections: Biomes, Diversity, Symbiosis, and Succession. Biomes encompass the interactions within the biotic and abiotic features of an environment. This extends to the term "microbiome," derived from "biome," and includes an environment and all the microbes within it. Diversity encompasses patterns of species richness, abundance, and biogeography, all of which are important to understanding the distribution of microbiomes. Symbiosis emphasizes the relationships between organisms within a community. Symbioses are often misunderstood to be synonymous with mutualism. We discard that implication, in favor of a broader, more historically accurate definition which spans the continuum from parasitism to mutualism. Succession includes classical succession, alternative stable states, community assembly frameworks, and r/K-selection. Our hope is that as microbiome researchers continue to apply ecological terms, and as ecologists continue to gain interest in microbiomes, each will do so in a way that enables cross-talk between them. We recommend initiating these collaborations by using a common lexicon, from which new concepts can emerge.

Neutrophilic proteolysis in the cystic fibrosis lung correlates with a pathogenic microbiome

BACKGROUND

Studies of the cystic fibrosis (CF) lung microbiome have consistently shown that lung function decline is associated with decreased microbial diversity due to the dominance of opportunistic pathogens. However, how this phenomenon is reflected in the metabolites and chemical environment of lung secretions remains poorly understood.

METHODS

Here we investigated the microbial and molecular composition of CF sputum samples using 16S rRNA gene amplicon sequencing and untargeted tandem mass spectrometry to determine their interrelationships and associations with clinical measures of disease severity.

RESULTS

The CF metabolome was found to exist in two states: one from patients with more severe disease that had higher molecular diversity and more Pseudomonas aeruginosa and the other from patients with better lung function having lower metabolite diversity and fewer pathogenic bacteria. The two molecular states were differentiated by the abundance and diversity of peptides and amino acids. Patients with severe disease and more pathogenic bacteria had higher levels of peptides. Analysis of the carboxyl terminal residues of these peptides indicated that neutrophil elastase and cathepsin G were responsible for their generation, and accordingly, these patients had higher levels of proteolytic activity from these enzymes in their sputum. The CF pathogen Pseudomonas aeruginosa was correlated with the abundance of amino acids and is known to primarily feed on them in the lung.

CONCLUSIONS

In cases of severe CF lung disease, proteolysis by host enzymes creates an amino acid-rich environment that P. aeruginosa comes to dominate, which may contribute to the pathogen's persistence by providing its preferred carbon source.

Microbiome networks and change-point analysis reveal key community changes associated with cystic fibrosis pulmonary exacerbations

Over 90% of cystic fibrosis (CF) patients die due to chronic lung infections leading to respiratory failure. The decline in CF lung function is greatly accelerated by intermittent and progressively severe acute pulmonary exacerbations (PEs). Despite their clinical impact, surprisingly few microbiological signals associated with PEs have been identified. Here we introduce an unsupervised, systems-oriented approach to identify key members of the microbiota. We used two CF sputum microbiome data sets that were longitudinally collected through periods spanning baseline health and PEs. Key taxa were defined based on three strategies: overall relative abundance, prevalence, and co-occurrence network interconnectedness. We measured the association between changes in the abundance of the key taxa and changes in patient clinical status over time via change-point detection, and found that taxa with the highest level of network interconnectedness tracked changes in patient health significantly better than taxa with the highest abundance or prevalence. We also cross-sectionally stratified all samples into the clinical states and identified key taxa associated with each state. We found that network interconnectedness most strongly delineated the taxa among clinical states, and that anaerobic bacteria were over-represented during PEs. Many of these anaerobes are oropharyngeal bacteria that have been previously isolated from the respiratory tract, and/or have been studied for their role in CF. The observed shift in community structure, and the association of anaerobic taxa and PEs lends further support to the growing consensus that anoxic conditions and the subsequent growth of anaerobic microbes are important predictors of PEs.

Episodes of significant worsening of cystic fibrosis symptoms, known as pulmonary exacerbations (PEs), are associated with oxygen-deficient (anoxic) conditions and increased activity of ‘anaerobic’ bacteria, which thrive in the absence of oxygen. Researchers in Canada, led by David Guttman at the University of Toronto, compared genetic data on microbial populations in sputum samples collected during PEs and at times of better health. The study revealed a strong correlation between the activity and interactions among anaerobic bacteria and the onset of PEs. Investigating the significance of these changes in the lung environment and its microbial populations may help design treatment strategies to reduce the frequency of PEs and their potentially fatal consequences. The authors suggest that antibiotics that specifically target anaerobic bacteria may prove beneficial, as may hyperbaric oxygen therapy, which oxygenates the lung tissue.

Viral-Bacterial Co-infections in the Cystic Fibrosis Respiratory Tract

A majority of the morbidity and mortality associated with the genetic disease Cystic Fibrosis (CF) is due to lung disease resulting from chronic respiratory infections. The CF airways become chronically colonized with bacteria in childhood, and over time commensal lung microbes are displaced by bacterial pathogens, leading to a decrease in microbial diversity that correlates with declining patient health. Infection with the pathogen Pseudomonas aeruginosa is a major predictor of morbidity and mortality in CF, with CF individuals often becoming chronically colonized with P. aeruginosa in early adulthood and thereafter having an increased risk of hospitalization. Progression of CF respiratory disease is also influenced by infection with respiratory viruses. Children and adults with CF experience frequent respiratory viral infections with respiratory syncytial virus (RSV), rhinovirus, influenza, parainfluenza, and adenovirus, with RSV and influenza infection linked to the greatest decreases in lung function. Along with directly causing severe respiratory symptoms in CF populations, the impact of respiratory virus infections may be more far-reaching, indirectly promoting bacterial persistence and pathogenesis in the CF respiratory tract. Acquisition of P. aeruginosa in CF patients correlates with seasonal respiratory virus infections, and CF patients colonized with P. aeruginosa experience increased severe exacerbations and declines in lung function during respiratory viral co-infection. In light of such observations, efforts to better understand the impact of viral-bacterial co-infections in the CF airways have been a focus of clinical and basic research in recent years. This review summarizes what has been learned about the interactions between viruses and bacteria in the CF upper and lower respiratory tract and how co-infections impact the health of individuals with CF.

Reevaluating approaches to cystic fibrosis pulmonary exacerbations

Cystic Fibrosis (CF) lung disease is characterized by intermittent acute episodes of worsening signs, symptoms, and pulmonary function; these so-called pulmonary exacerbations (PEx) appear to be important drivers of long-term declines in lung function, quality of life, and life expectancy. Surveillance for development of PEx and their treatment is a fundamental component of chronic CF management, and the merits of novel CF therapies are often judged based on their ability to reduce the frequency of PEx. Given the central role that they play, it is surprising how poorly PEx are understood, how thin is the evidence base for their treatment and how often they are left unrecognized and untreated in clinical practice. This paper reviews what is known and what is unknown regarding the nature of PEx, and discusses the impact of missed recognition and treatment of these episodes as well as the apparent variation in practice across CF care centers. The arguments supporting a liberal, highly sensitive approach to the diagnosis of PEx are presented, as well as recommendation for how care programs can achieve consistency in their early recognition and treatment. A stepwise approach to personalized treatment supported by close follow-up to ensure the successful resolution of all signs and symptoms will lead to the stabilization of patients' lung function and quality of life. Recommendations are made regarding important priorities for research into evidence-based approaches to improving the care of PEx.

An ecosystem framework for understanding and treating disease

Pathogens and cancers are pervasive health risks in the human population. I argue that if we are to better understand disease and its treatment, then we need to take an ecological perspective of disease itself. I generalize and extend an emerging framework that views disease as an ecosystem and many of its components as interacting in a community. I develop the framework for biological etiological agents (BEAs) that multiply within humans—focusing on bacterial pathogens and cancers—but the framework could be extended to include other host and parasite species. I begin by describing why we need an ecosystem framework to understand disease, and the main components and interactions in bacterial and cancer disease ecosystems. Focus is then given to the BEA and how it may proceed through characteristic states, including emergence, growth, spread and regression. The framework is then applied to therapeutic interventions. Central to success is preventing BEA evasion, the best known being antibiotic resistance and chemotherapeutic resistance in cancers. With risks of evasion in mind, I propose six measures that either introduce new components into the disease ecosystem or manipulate existing ones. An ecosystem framework promises to enhance our understanding of disease, BEA and host (co)evolution, and how we can improve therapeutic outcomes.

Cystic fibrosis respiratory microbiota: unraveling complexity to inform clinical practice

INTRODUCTION

Cystic fibrosis (CF) lung disease is characterized by chronic cycles of pulmonary infection, inflammation, and mucus obstruction, beginning early in life, and eventually leading to progressive lung damage and early mortality. During the past ~15 years, culture-independent analyses of CF respiratory samples have identified diverse bacterial communities in CF airways, and relationships between respiratory microbiota and clinical outcomes. Areas covered: This paper reviews recent advances in our understanding of the relationships between respiratory microbiota and CF lung disease. The paper focuses on measures of airway bacterial community diversity and estimates of the relative abundance of anaerobic species. Finally, this paper will review the opportunities for advancing patient care suggested by these studies and highlight some of the ongoing challenges and unmet needs in translating this knowledge into clinical practice. Expert commentary: Culture-independent analyses of respiratory microbiota have suggested new strategies for advancing CF care, but have also highlighted challenges in understanding the complexity of CF respiratory infections. Development of more sophisticated models and analytic approaches to better account for this complexity are needed to elucidate mechanistic links between CF respiratory microbiota and clinical outcomes, and to ultimately translate this knowledge into better patient care.

Niche partitioning of a pathogenic microbiome driven by chemical gradients

Environmental microbial communities are stratified by chemical gradients that shape the structure and function of these systems. Similar chemical gradients exist in the human body, but how they influence these microbial systems is more poorly understood. Understanding these effects can be particularly important for dysbiotic shifts in microbiome structure that are often associated with disease. We show that pH and oxygen strongly partition the microbial community from a diseased human lung into two mutually exclusive communities of pathogens and anaerobes. Antimicrobial treatment disrupted this chemical partitioning, causing complex death, survival, and resistance outcomes that were highly dependent on the individual microorganism and on community stratification. These effects were mathematically modeled, enabling a predictive understanding of this complex polymicrobial system. Harnessing the power of these chemical gradients could be a drug-free method of shaping microbial communities in the human body from undesirable dysbiotic states.

Quantitative assessment of individual populations within polymicrobial biofilms

Selecting appropriate tools providing reliable quantitative measures of individual populations in biofilms is critical as we now recognize their true polymicrobial and heterogeneous nature. Here, plate count, quantitative real-time polymerase chain reaction (q-PCR) and peptide nucleic acid probe-fluorescence in situ hybridization (PNA-FISH) were employed to quantitate cystic fibrosis multispecies biofilms. Growth of Pseudomonas aeruginosa, Inquilinus limosus and Dolosigranulum pigrum was assessed in dual- and triple-species consortia under oxygen and antibiotic stress. Quantification methods, that were previously optimized and validated in planktonic consortia, were not always in agreement when applied in multispecies biofilms. Discrepancies in culture and molecular outcomes were observed, particularly for triple-species consortia and antibiotic-stressed biofilms. Some differences were observed, such as the higher bacterial counts obtained by q-PCR and/or PNA-FISH (≤4 log₁₀ cells/cm²) compared to culture. But the discrepancies between PNA-FISH and q-PCR data (eg D. pigrum limited assessment by q-PCR) demonstrate the effect of biofilm heterogeneity in method’s reliability. As the heterogeneity in biofilms is a reflection of a myriad of variables, tailoring an accurate picture of communities´ changes is crucial. This work demonstrates that at least two, but preferentially three, quantification techniques are required to obtain reliable measures and take comprehensive analysis of polymicrobial biofilm-associated infections.