Microbial, host and xenobiotic diversity in the cystic fibrosis sputum metabolome

Secondary metabolite profiling of Pseudomonas aeruginosa isolates reveals rare genomic traits

Pseudomonas aeruginosa is a ubiquitous Gram-negative opportunistic pathogen with remarkable phylogenetic and phenotypic variabilities. In this work, we applied classical molecular networking analysis to secondary metabolite profiling data from seven Pseudomonas aeruginosa strains, including five clinical isolates from the lung secretions of people with cystic fibrosis (CF). We provide three vignettes illustrating how secondary metabolite profiling aids in the identification of rare genomics traits in P. aeruginosa. First, we describe the identification of a previously unreported class of acyl putrescines produced by isolate mFLRO1. Secondary analysis of publicly available metabolomics data revealed that acyl putrescines are produced by <5% of P. aeruginosa strains. Second, we show that isolate SH3A does not produce di-rhamnolipids. Whole-genome sequencing and comparative genomics revealed that SH3A cannot produce di-rhamnolipids because its genome belongs to clade 5 of the P. aeruginosa phylogenetic tree. Previous phylogenetic analysis of thousands of P. aeruginosa strains concluded that <1% of publicly available genome sequences contribute to this clade. Last, we show that isolate SH1B does not produce the phenazine pyocyanin or rhamnolipids because it has a one-base insertion frameshift mutation (678insC) in the gene rhlR, which disrupts rhl-driven quorum sensing. Secondary analysis of the tens of thousands of publicly available genomes in the National Center for Biotechnology Information (NCBI) and the Pseudomonas Genome Database revealed that this mutation was present in only four P. aeruginosa genomes. Taken together, this study highlights that secondary metabolite profiling combined with genomic analysis can identify rare genetic traits of P. aeruginosa isolates.IMPORTANCESecondary metabolite profiling of five Pseudomonas aeruginosa isolates from cystic fibrosis sputum captured three traits present in <1%-5% of publicly available data, pointing to how our current library of P. aeruginosa strains may not represent the diversity within this species or the genetic variance that occurs in the CF lung.

Longitudinal microbial and molecular dynamics in the cystic fibrosis lung after Elexacaftor-Tezacaftor-Ivacaftor therapy

BACKGROUND

Cystic fibrosis (CF) is a genetic disorder causing poor mucociliary clearance in the airways and subsequent respiratory infection. The recently approved triple therapy Elexacaftor-Tezacaftor-Ivacaftor (ETI) has significantly improved lung function and decreased airway infection in persons with CF (pwCF). This improvement has been shown to occur rapidly, within the first few weeks of treatment. The effects of longer term ETI therapy on lung infection dynamics, however, remain mostly unknown.

RESULTS

Here, we applied 16S rRNA gene amplicon sequencing, untargeted metabolomics, and neutral models to high-resolution, longitudinally collected sputum samples from pwCF on ETI therapy (162 samples, 7 patients) and compared to similarly collected data set from pwCF not taking ETI (630 samples, 9 patients). Because ETI reduces sputum production, samples were collected in freezers provided in the subject's homes at least 3 months after first taking ETI, with those on ETI collecting a sample approximately weekly. The lung function (%ppFEV1) of those in our longitudinal cohort significantly improved after ETI (6.91, SD = 7.74), indicating our study cohort was responsive to ETI. The daily variation of alpha- and beta-diversity of both the microbiome and metabolome was higher for those on ETI, reflecting a more dynamic microbial community and chemical environment during treatment. Four of the seven subjects on ETI were persistently infected with Pseudomonas or Burkholderia in their sputum throughout the sampling period while the total bacterial load significantly decreased with time (R = - 0.42, p = 0.01) in only one subject. The microbiome and metabolome dynamics on ETI were personalized, where some subjects had a progressive change with time on therapy, whereas others had no association with time on treatment. To further classify the augmented variance of the CF microbiome under therapy, we fit the microbiome data to a Hubbell neutral dynamics model in a patient-stratified manner and found that the subjects on ETI had better fit to a neutral model.

CONCLUSION

This study shows that the longitudinal microbiology and chemistry in airway secretions from subjects on ETI has become more dynamic and neutral and that after the initial improvement in lung function, many are still persistently infected with CF pathogens.

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.

Longitudinal Microbial and Molecular Dynamics in the Cystic Fibrosis Lung after Elexacaftor-Tezacaftor-Ivacaftor therapy

Background

Cystic fibrosis (CF) is a genetic disorder causing poor mucociliary clearance in the airways and subsequent respiratory infection. The recently approved triple therapy Elexacaftor-Tezacaftor-Ivacaftor (ETI) has significantly improved the lung function and decreased airway infection of persons with CF (pwCF). This improvement has been shown to occur rapidly, within the first few weeks of treatment. The effects of longer term ETI therapy on lung infection dynamics, however, remains mostly unknown.

Results

Here, we applied 16S rRNA gene amplicon sequencing, untargeted metabolomics, and neutral models to high-resolution, longitudinally collected sputum samples from pwCF on ETI therapy (162 samples, 7 patients) and compared to similarly collected data set of CF subjects not taking ETI (630 samples, 9 patients). Because ETI reduces sputum production, samples were collected in freezers provided in the subject's homes at least 3 months after first taking ETI, with those on ETI collecting a sample approximately weekly. The lung function (%ppFEV1) of those in our longitudinal cohort significantly improved after ETI (6.91, SD = 7.74), indicating our study cohort was responsive to ETI. The daily variation of alpha- and beta-diversity of both the microbiome and metabolome was higher for those on ETI, reflecting a more dynamic microbial community and chemical environment during treatment. Four of the seven subjects on ETI were persistently infected with Pseudomonas or Burkholderia in their sputum throughout the sampling period. The microbiome and metabolome dynamics on ETI were personalized, where some subjects had a progressive change with time on therapy, whereas others had no association with time on treatment. To further classify the augmented variance of the CF microbiome under therapy, we fit the microbiome data to a Hubbell neutral dynamics model in a patient-stratified manner and found that the subjects on ETI had better fit to a neutral model.

Conclusion

This study shows that the longitudinal microbiology and chemistry in airway secretions from subjects on ETI has become more dynamic and neutral, and that after the initial improvement in lung function, many are still persistently infected with CF pathogens.

Multiomic Investigations into Lung Health and Disease

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.

Uncovering the Carboxylated Metabolome in Gut Microbiota-Host Co-metabolism: A Chemical Derivatization-Molecular Networking Approach

Gut microbiota-host co-metabolites serve as essential mediators of communication between the host and gut microbiota. They provide nutrient sources for host cells and regulate gut microenvironment, which are associated with a variety of diseases. Analysis of gut microbiota-host co-metabolites is of great significance to explore the host-gut microbiota interaction. In this study, we integrated chemical derivatization, liquid chromatography-mass spectrometry, and molecular networking (MN) to establish a novel CD-MN strategy for the analysis of carboxylated metabolites in gut microbial-host co-metabolism. Using this strategy, 261 carboxylated metabolites from mouse feces were detected, which grouped to various classes including fatty acids, bile acids, N-acyl amino acids, benzoheterocyclic acids, aromatic acids, and other unknown small-scale molecular clusters in MN. Based on the interpretation of the bile acid cluster, a novel type of phenylacetylated conjugates of host bile acids was identified, which were mediated by gut microbiota and exhibited a strong binding ability to Farnesoid X receptor and Takeda G protein-coupled receptor 5. Our proposed strategy offers a promising platform for uncovering carboxylated metabolites in gut microbial-host co-metabolism.

Stratification of asthma by lipidomic profiling of induced sputum supernatant

BACKGROUND

Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features.

OBJECTIVE

We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls.

METHODS

Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes.

RESULTS

Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts.

CONCLUSION

We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.

Genome-scale model of Pseudomonas aeruginosa metabolism unveils virulence and drug potentiation

Pseudomonas aeruginosa is one of the leading causes of hospital-acquired infections. To decipher the metabolic mechanisms associated with virulence and antibiotic resistance, we have developed an updated genome-scale model (GEM) of P. aeruginosa. The model (iSD1509) is an extensively curated, three-compartment, and mass-and-charge balanced BiGG model containing 1509 genes, the largest gene content for any P. aeruginosa GEM to date. It is the most accurate with prediction accuracies as high as 92.4% (gene essentiality) and 93.5% (substrate utilization). In iSD1509, we newly added a recently discovered pathway for ubiquinone-9 biosynthesis which is required for anaerobic growth. We used a modified iSD1509 to demonstrate the role of virulence factor (phenazines) in the pathogen survival within biofilm/oxygen-limited condition. Further, the model can mechanistically explain the overproduction of a drug susceptibility biomarker in the P. aeruginosa mutants. Finally, we use iSD1509 to demonstrate the drug potentiation by metabolite supplementation, and elucidate the mechanisms behind the phenotype, which agree with experimental results.

The gut–liver axis in sepsis: interaction mechanisms and therapeutic potential

Sepsis is a potentially fatal condition caused by dysregulation of the body's immune response to an infection. Sepsis-induced liver injury is considered a strong independent prognosticator of death in the critical care unit, and there is anatomic and accumulating epidemiologic evidence that demonstrates intimate cross talk between the gut and the liver. Intestinal barrier disruption and gut microbiota dysbiosis during sepsis result in translocation of intestinal pathogen-associated molecular patterns and damage-associated molecular patterns into the liver and systemic circulation. The liver is essential for regulating immune defense during systemic infections via mechanisms such as bacterial clearance, lipopolysaccharide detoxification, cytokine and acute-phase protein release, and inflammation metabolic regulation. When an inappropriate immune response or overwhelming inflammation occurs in the liver, the impaired capacity for pathogen clearance and hepatic metabolic disturbance can result in further impairment of the intestinal barrier and increased disruption of the composition and diversity of the gut microbiota. Therefore, interaction between the gut and liver is a potential therapeutic target. This review outlines the intimate gut–liver cross talk (gut–liver axis) in sepsis.

Metabolomics of airways disease in cystic fibrosis

While discovery metabolomic studies have identified many potential biomarkers of cystic fibrosis (CF) airways disease, relatively few have been validated. We review the recent literature to identify the most promising metabolomic findings as those repeatedly observed over multiple studies. Reproducible metabolomic findings include increased airway amino acids and small peptides in CF airways, as well as changes in phospholipids and sphingolipids. Other commonly altered pathways include adenosine metabolism, polyamine synthesis, and oxidative stress. These pathways represent potential biomarkers and therapeutic targets, though findings require reevaluation in the era of highly effective modulator therapies. Analysis of airway biomarkers in exhaled breath holds promise for non-invasive detection, though technical challenges will need to be overcome.

The potential of volatile organic compound analysis for pathogen detection and disease monitoring in patients with cystic fibrosis

INTRODUCTION

Airway infection with pathogens and its associated pulmonary exacerbations (PEX) are the major causes of morbidity and premature death in cystic fibrosis (CF). Preventing or postponing chronic infections requires early diagnosis. However, limitations of conventional microbiology-based methods can hamper identification of exacerbations and specific pathogen detection. Analyzing volatile organic compounds (VOCs) in breath samples may be an interesting tool in this regard, as VOC-biomarkers can characterize specific airway infections in CF.

AREAS COVERED

We address the current achievements in VOC-analysis and discuss studies assessing VOC-biomarkers and fingerprints, i.e. a combination of multiple VOCs, in breath samples aiming at pathogen and PEX detection in people with CF (pwCF). We aim to provide bases for further research in this interesting field.

EXPERT OPINION

Overall, VOC-based analysis is a promising tool for diagnosis of infection and inflammation with potential to monitor disease progression in pwCF. Advantages over conventional diagnostic methods, including easy and non-invasive sampling procedures, may help to drive prompt, suitable therapeutic approaches in the future. Our review shall encourage further research, including validation of VOC-based methods. Specifically, longitudinal validation under standardized conditions is of interest in order to ensure repeatability and enable inclusion in CF diagnostic routine.

Valuing the Diversity of Research Methods to Advance Nutrition Science

The ASN Board of Directors appointed the Nutrition Research Task Force to develop a report on scientific methods used in nutrition science to advance discovery, interpretation, and application of knowledge in the field. The genesis of this report was growing concern about the tone of discourse among nutrition professionals and the implications of acrimony on the productive study and translation of nutrition science. Too often, honest differences of opinion are cast as conflicts instead of areas of needed collaboration. Recognition of the value (and limitations) of contributions from well-executed nutrition science derived from the various approaches used in the discipline, as well as appreciation of how their layering will yield the strongest evidence base, will provide a basis for greater productivity and impact. Greater collaborative efforts within the field of nutrition science will require an understanding that each method or approach has a place and function that should be valued and used together to create the nutrition evidence base. Precision nutrition was identified as an important emerging nutrition topic by the preponderance of task force members, and this theme was adopted for the report because it lent itself to integration of many approaches in nutrition science. Although the primary audience for this report is nutrition researchers and other nutrition professionals, a secondary aim is to develop a document useful for the various audiences that translate nutrition research, including journalists, clinicians, and policymakers. The intent is to promote accurate, transparent, verifiable evidence-based communication about nutrition science. This will facilitate reasoned interpretation and application of emerging findings and, thereby, improve understanding and trust in nutrition science and appropriate characterization, development, and adoption of recommendations.

Network Analysis to Identify Multi-Omic Correlations in the Lower Airways of Children With Cystic Fibrosis

The leading cause of morbidity and mortality in cystic fibrosis (CF) is progressive lung disease secondary to chronic airway infection and inflammation; however, what drives CF airway infection and inflammation is not well understood. By providing a physiological snapshot of the airway, metabolomics can provide insight into these processes. Linking metabolomic data with microbiome data and phenotypic measures can reveal complex relationships between metabolites, lower airway bacterial communities, and disease outcomes. In this study, we characterize the airway metabolome in bronchoalveolar lavage fluid (BALF) samples from persons with CF (PWCF) and disease control (DC) subjects and use multi-omic network analysis to identify correlations with the airway microbiome. The Biocrates targeted liquid chromatography mass spectrometry (LC-MS) platform was used to measure 409 metabolomic features in BALF obtained during clinically indicated bronchoscopy. Total bacterial load (TBL) was measured using quantitative polymerase chain reaction (qPCR). The Qiagen EZ1 Advanced automated extraction platform was used to extract DNA, and bacterial profiling was performed using 16S sequencing. Differences in metabolomic features across disease groups were assessed univariately using Wilcoxon rank sum tests, and Random forest (RF) was used to identify features that discriminated across the groups. Features were compared to TBL and markers of inflammation, including white blood cell count (WBC) and percent neutrophils. Sparse supervised canonical correlation network analysis (SsCCNet) was used to assess multi-omic correlations. The CF metabolome was characterized by increased amino acids and decreased acylcarnitines. Amino acids and acylcarnitines were also among the features most strongly correlated with inflammation and bacterial burden. RF identified strong metabolomic predictors of CF status, including L-methionine-S-oxide. SsCCNet identified correlations between the metabolome and the microbiome, including correlations between a traditional CF pathogen, Staphylococcus, a group of nontraditional taxa, including Prevotella, and a subnetwork of specific metabolomic markers. In conclusion, our work identified metabolomic characteristics unique to the CF airway and uncovered multi-omic correlations that merit additional study.

Altered fecal microbiome and metabolome in adult patients with non-cystic fibrosis bronchiectasis

Background

Emerging experimental and epidemiological evidence highlights a crucial cross-talk between the intestinal flora and the lungs, termed the “gut-lung axis”. However, the function of the gut microbiota in bronchiectasis remains undefined. In this study, we aimed to perform a multi-omics-based approach to identify the gut microbiome and metabolic profiles in patients with bronchiectasis.

Methods

Fecal samples collected from non-CF bronchiectasis patients (BE group, n = 61) and healthy volunteers (HC group, n = 37) were analyzed by 16 S ribosomal RNA (rRNA) sequencing. The BE group was divided into two groups based on their clinical status: acute exacerbation (AE group, n = 31) and stable phase (SP group, n = 30). Further, metabolome (lipid chromatography-mass spectrometry, LC-MS) analyses were conducted in randomly selected patients (n = 29) and healthy volunteers (n = 31).

Results

Decreased fecal microbial diversity and differential microbial and metabolic compositions were observed in bronchiectasis patients. Correlation analyses indicated associations between the differential genera and clinical parameters such as bronchiectasis severity index (BSI). Disease-associated gut microbiota was screened out, with eight genera exhibited high accuracy in distinguishing SP patients from HCs in the discovery cohort and validation cohort using a random forest model. Further correlation networks were applied to illustrate the relations connecting disease-associated genera and metabolites.

Conclusion

The study uncovered the relationships among the decreased fecal microbial diversity, differential microbial and metabolic compositions in bronchiectasis patients by performing a multi-omics-based approach. It is the first study to characterize the gut microbiome and metabolome in bronchiectasis, and to uncover the gut microbiota’s potentiality as biomarkers for bronchiectasis.

Trial registration: This study is registered with ClinicalTrials.gov, number NCT04490447.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02229-w.

Sweat metabolomics before and after intravenous antibiotics for pulmonary exacerbation in people with cystic fibrosis

BACKGROUND

People with cystic fibrosis (PWCF) suffer from acute unpredictable reductions in pulmonary function associated with a pulmonary exacerbation (PEx) that may require hospitalization. PEx symptoms vary between PWCF without universal diagnostic criteria for diagnosis and response to treatment.

RESEARCH QUESTION

We characterized sweat metabolomes before and after intravenous (IV) antibiotics in PWCF hospitalized for PEx to determine feasibility and define biological alterations by IV antibiotics for PEx.

STUDY DESIGN AND METHODS

PWCF with PEx requiring hospitalization for IV antibiotics were recruited from clinic. Sweat samples were collected using the Macroduct® Sweat Collection System at admission prior to initiation of IV antibiotics and after completion prior to discharge. Samples were analyzed for metabolite changes using ultra-high-performance liquid chromatography/tandem accurate mass spectrometry.

RESULTS

Twenty-six of 29 hospitalized PWCF completed the entire study. A total of 326 compounds of known identity were detected in sweat samples. Of detected metabolites, 147 were significantly different between pre-initiation and post-completion of IV antibiotics for PEx (average treatment 14 days). Global sweat metabolomes changed from before and after IV antibiotic treatment. We discovered specific metabolite profiles predictive of PEx status as well as enriched biologic pathways associated with PEx. However, metabolomic changes were similar in PWCF who failed to return to baseline pulmonary function and those who did not.

INTERPRETATION

Our findings demonstrate the feasibility of non-invasive sweat metabolomic profiling in PWCF and the potential for sweat metabolomics as a prospective diagnostic and research tool to further advance our understanding of PEx in PWCF.

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.

Alkyl-Quinolones derivatives as potential biomarkers for Pseudomonas aeruginosa infection chronicity in Cystic Fibrosis

In Cystic Fibrosis (CF), a rapid and standardized definition of chronic infection would allow a better management of Pseudomonas aeruginosa (Pa) infections, as well as a quick grouping of patients during clinical trials allowing better comparisons between studies. With this purpose, we compared the metabolic profiles of 44 in vitro cultures of Pa strains isolated from CF patients at different stages of infection in order to identify metabolites differentially synthetized according to these clinical stages. Compounds produced and secreted by each strain in the supernatant of a liquid culture were analysed by metabolomic approaches (UHPLC-DAD-ESI/QTOF, UV and UPLC-Orbitrap, MS). Multivariate analyses showed that first colonization strains could be differentiated from chronic colonization ones, by producing notably more Alkyl-Quinolones (AQs) derivatives. Especially, five AQs were discriminant: HQC5, HQNOC7, HQNOC7:1, db-PQS C9 and HQNOC9:1. However, the production of HHQ was equivalent between strain types. The HHQ/HQNOC9:1 ratio was then found to be significantly different between chronic and primo-colonising strains by using both UV (p = 0.003) and HRMS data (p = 1.5 × 10^-5). Our study suggests that some AQ derivatives can be used as biomarkers for an improved management of CF patients as well as a better definition of the clinical stages of Pa infection.

An Innovative Protocol for Metaproteomic Analyses of Microbial Pathogens in Cystic Fibrosis Sputum

Hallmarks of cystic fibrosis (CF) are increased viscosity of mucus and impaired mucociliary clearance within the airways due to mutations of the cystic fibrosis conductance regulator gene. This facilitates the colonization of the lung by microbial pathogens and the concomitant establishment of chronic infections leading to tissue damage, reduced lung function, and decreased life expectancy. Although the interplay between key CF pathogens plays a major role during disease progression, the pathophysiology of the microbial community in CF lungs remains poorly understood. Particular challenges in the analysis of the microbial population present in CF sputum is (I) the inhomogeneous, viscous, and slimy consistence of CF sputum, and (II) the high number of human proteins masking comparably low abundant microbial proteins. To address these challenges, we used 21 CF sputum samples to develop a reliable, reproducible and widely applicable protocol for sputum processing, microbial enrichment, cell disruption, protein extraction and subsequent metaproteomic analyses. As a proof of concept, we selected three sputum samples for detailed metaproteome analyses and complemented and validated metaproteome data by 16S sequencing, metabolomic as well as microscopic analyses. Applying our protocol, the number of bacterial proteins/protein groups increased from 199-425 to 392-868 in enriched samples compared to nonenriched controls. These early microbial metaproteome data suggest that the arginine deiminase pathway and multiple proteases and peptidases identified from various bacterial genera could so far be underappreciated in their contribution to the CF pathophysiology. By providing a standardized and effective protocol for sputum processing and microbial enrichment, our study represents an important basis for future studies investigating the physiology of microbial pathogens in CF in vivo – an important prerequisite for the development of novel antimicrobial therapies to combat chronic recurrent airway infection in CF.

Impact of artificial sputum media formulation on Pseudomonas aeruginosa secondary metabolite production

In vitro culture media are being developed to understand how host site-specific nutrient profiles influence microbial pathogenicity and ecology. To mimic the cystic fibrosis (CF) lung environment, a variety of artificial sputum media (ASM) have been created. However, the composition of these ASM vary in the concentration of key nutrients, including amino acids, lipids, DNA, and mucin. In this work, we used feature-based molecular networking (FBMN) to perform comparative metabolomics of Pseudomonas aeruginosa, the predominant opportunistic pathogen infecting the lungs of people with CF, cultured in nine different ASM. We found that the concentration of aromatic amino acids and iron from mucin added to the media contributes to differences in the production of P. aeruginosa virulence-associated secondary metabolites.

IMPORTANCE Different media formulations aiming to replicate in vivo infection environments contain different nutrients, which affects interpretation of experimental results. Inclusion of undefined components, such as commercial porcine gastric mucin (PGM), in an otherwise chemically defined medium can alter the nutrient content of the medium in unexpected ways and influence experimental outcomes.

Rapid ex vivo molecular fingerprinting of biofluids using laser-assisted rapid evaporative ionization mass spectrometry

Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO₂ laser) and with automation for high-throughput analysis. Laser-induced sample evaporation occurs within seconds through radiative heating with the plume guided to the MS instrument. The presented procedure includes (i) laser setup with automation, (ii) analysis of biofluids (blood/urine/stool/saliva/sputum/breast milk) and (iii) data analysis. We provide the optimal settings for biofluid analysis and quality control, enabling sensitive, precise and robust analysis. Using the automated setup, 96 samples can be analyzed in ~35-40 min per ionization mode, with no intervention required. Metabolic fingerprints are made up of 2,000-4,000 features, for which relative quantification can be achieved at high repeatability when total ion current normalization is applied. With saliva and feces as example matrices, >70% of features had a coefficient of variance ≤30%. However, to achieve acceptable long-term reproducibility, additional normalizations by, e.g., LOESS are recommended, especially for positive ionization.

Untargeted Metabolomics Reveals Species-Specific Metabolite Production and Shared Nutrient Consumption by Pseudomonas aeruginosa and Staphylococcus aureus

While bacterial metabolism is known to impact antibiotic efficacy and virulence, the metabolic capacities of individual microbes in cystic fibrosis lung infections are difficult to disentangle from sputum samples. Here, we show that untargeted metabolomic profiling of supernatants of multiple strains of Pseudomonas aeruginosa and Staphylococcus aureus grown in monoculture in synthetic cystic fibrosis media (SCFM) reveals distinct species-specific metabolic signatures despite intraspecies metabolic variability. We identify a set of 15 metabolites that were significantly consumed by both P. aeruginosa and S. aureus, suggesting that nutrient competition has the potential to impact community dynamics even in the absence of other pathogen-pathogen interactions. Finally, metabolites that were uniquely produced by one species or the other were identified. Specifically, the virulence factor precursor anthranilic acid, as well as the quinoline 2,4-quinolinediol (DHQ), were robustly produced across all tested strains of P. aeruginosa. Through the direct comparison of the extracellular metabolism of P. aeruginosa and S. aureus in a physiologically relevant environment, this work provides insight toward the potential for metabolic interactions in vivo and supports the development of species-specific diagnostic markers of infection. IMPORTANCE Interactions between P. aeruginosa and S. aureus can impact pathogenicity and antimicrobial efficacy. In this study, we aim to better understand the potential for metabolic interactions between P. aeruginosa and S. aureus in an environment resembling the cystic fibrosis lung. We find that S. aureus and P. aeruginosa consume many of the same nutrients, suggesting that metabolic competition may play an important role in community dynamics during coinfection. We further identify metabolites uniquely produced by either organism with the potential to be developed into species-specific biomarkers of infection in the cystic fibrosis lung.

The Impact of Dietary Sphingolipids on Intestinal Microbiota and Gastrointestinal Immune Homeostasis

The large surfaces of gastrointestinal (GI) organs are well adapted to their diverse tasks of selective nutritional uptake and defense against the external environment. To maintain a functional balance, a vast number of immune cells is located within the mucosa. A strictly regulated immune response is required to impede constant inflammation and to maintain barrier function. An increasing prevalence of GI diseases has been reported in Western societies over the past decades. This surge in GI disorders has been linked to dietary changes followed by an imbalance of the gut microbiome, leading to a chronic, low grade inflammation of the gut epithelium. To counteract the increasing health care costs associated with diseases, it is paramount to understand the mechanisms driving immuno-nutrition, the associations between nutritional compounds, the commensal gut microbiota, and the host immune response. Dietary compounds such as lipids, play a central role in GI barrier function. Bioactive sphingolipids (SLs), e.g. sphingomyelin (SM), sphingosine (Sph), ceramide (Cer), sphingosine-1- phosphate (S1P) and ceramide-1-phosphate (C1P) may derive from dietary SLs ingested through the diet. They are not only integral components of cell membranes, they additionally modulate cell trafficking and are precursors for mediators and second messenger molecules. By regulating intracellular calcium levels, cell motility, cell proliferation and apoptosis, SL metabolites have been described to influence GI immune homeostasis positively and detrimentally. Furthermore, dietary SLs are suggested to induce a shift in the gut microbiota. Modes of action range from competing with the commensal bacteria for intestinal cell attachment to prevention from pathogen invasion by regulating innate and immediate defense mechanisms. SL metabolites can also be produced by gut microorganisms, directly impacting host metabolic pathways. This review aims to summarize recent findings on SL signaling and functional variations of dietary SLs. We highlight novel insights in SL homeostasis and SL impact on GI barrier function, which is directly linked to changes of the intestinal microbiota. Knowledge gaps in current literature will be discussed to address questions relevant for understanding the pivotal role of dietary SLs on chronic, low grade inflammation and to define a balanced and healthy diet for disease prevention and treatment.

Microbial Metabolomics: From Methods to Translational Applications

Most microbe-associated infectious diseases severely affect human health. However, clinical diagnosis of pathogenic diseases remains challenging due to the lack of specific and highly reliable methods. To better understand the diagnosis, pathogenesis, and treatment of these diseases, systems biology-driven metabolomics goes beyond the annotated phenotype and better targets the functions than conventional approaches. As a novel strategy for analysis of metabolomes in microbes, microbial metabolomics has been recently used to study many diseases, such as obesity, urinary tract infection (UTI), and hepatitis C. In this chapter, we attempt to introduce various microbial metabolomics methods to better interpret the microbial metabolism underlying a diversity of infectious diseases and inspire scientists to pay more attention to microbial metabolomics, enabling broadly and efficiently its translational applications to infectious diseases, from molecular diagnosis to therapeutic discovery.

High-Throughput Immunochemical Method to Assess the 2-Heptyl-4-quinolone Quorum Sensing Molecule as a Potential Biomarker of Pseudomonas aeruginosa Infections

Bacterial quorum sensing (QS) is being contemplated as a promising target for developing innovative diagnostic and therapeutic strategies. Here we report for the first time the development of antibodies against 2-heptyl-4-quinolone (HHQ), a signaling molecule from the pqs QS system of Pseudomonas aeruginosa, involved in the production of important virulent factors and biofilm formation. The antibodies produced were used to develop an immunochemical diagnostic approach to assess the potential of this molecule as a biomarker of P. aeruginosa infection. The ELISA developed is able to reach a detectability in the low nM range (IC₅₀ = 4.59 ± 0.29 nM and LOD = 0.34 ± 0.13 nM), even in complex biological samples such as Müeller Hinton (MH) culture media. The ELISA developed is robust and reproducible and has been found to be specific to HHQ, with little interference from other related alkylquinolones from the pqs QS system. The ELISA has been used to analyze the HHQ production kinetics of P. aeruginosa clinical isolates grown in MH media, pointing to its potential as a biomarker of infection and at the possibility to use the technology developed to obtain additional information about the disease stage.

Airway immunometabolites fuel Pseudomonas aeruginosa infection

Pulmonary infections are associated with a brisk inflammatory reaction to bacterial surface components. Lipopolysaccharides (LPS) trigger macrophage activation and release of mitochondrial metabolites that control the intensity of the immune response. Whereas succinate induces oxidative stress (ROS), HIF1α stabilization, glycolysis and IL-1β release, itaconate suppresses inflammation by inhibiting succinate oxidation, glycolytic flux and promoting anti-oxidant Nrf2-HO-1 functions. P. aeruginosa is a major pathogen associated with acute and chronic lung infection. Although both secreted toxins, LPS and proteases are key factors to establish acute P. aeruginosa pneumonia, lack of these components in chronic P. aeruginosa isolates suggest these organisms exploit other mechanisms to adapt and persist in the lung. Upon inhalation, P. aeruginosa strains trigger airway macrophage reprograming and bacterial variants obtained from acutely and chronically infected subjects exhibit metabolic adaptation consistent with succinate and itaconate assimilation; namely, high expression of extracellular polysaccharides (EPS), reduced lptD-LPS function, increased glyoxylate shunt (GS) activity and substantial biofilm production. In this review we discuss recent findings illustrating how P. aeruginosa induces and adapts to macrophage metabolites in the human lung, and that catabolism of succinate and itaconate contribute to their formidable abilities to tolerate oxidative stress, phagocytosis and immune clearance.

Mining Public Mass Spectrometry Data to Characterize the Diversity and Ubiquity of P. aeruginosa Specialized Metabolites

Pseudomonas aeruginosa is a ubiquitous environmental bacterium that causes chronic infections of burn wounds and in the lungs of cystic fibrosis (CF) patients. Vital to its infection is a myriad of specialized metabolites that serve a variety of biological roles including quorum sensing, metal chelation and inhibition of other competing bacteria. This study employed newly available algorithms for searching individual tandem mass (MS/MS) spectra against the publicly available Global Natural Product Social Molecular Networking (GNPS) database to identify the chemical diversity of these compounds and their presence in environmental, laboratory and clinical samples. For initial characterization, the metabolomes of eight clinical isolates of P. aeruginosa were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and uploaded to GNPS for spectral searching. Quinolones, rhamnolipids, phenazines and siderophores were identified and characterized; including the discovery of modified forms of the iron chelator pyochelin. Quinolones were highly diverse with the three base forms Pseudomonas quinolone signal 2-heptyl-3-hydroxy-4(1H)-quinolone (PQS), 4-heptyl-4(1H)-quinolone (HHQ) and 2-heptyl-4-quinolone-N-oxide (HQNO) having extensive variation in the length of their acyl chain from as small as 3 carbons to as large as 17. Rhamnolipids were limited to either one or two sugars with a limited set of fatty acyl chains, but the base lipid form without the rhamnose was also detected. These specialized metabolites were identified from diverse sources including ant-fungal mutualist dens, soil, plants, human teeth, feces, various lung mucus samples and cultured laboratory isolates. Their prevalence in fecal samples was particularly notable as P. aeruginosa is not known as a common colonizer of the human gut. The chemical diversity of the compounds identified, particularly the quinolones, demonstrates a broad spectrum of chemical properties within these the metabolite groups with likely significant impacts on their biological functions. Mining public data with GNPS enables a new approach to characterize the chemical diversity of biological organisms, which includes enabling the discovery of new chemistry from pathogenic bacteria.

Metabolomics profiling of tobacco exposure in children with cystic fibrosis

BACKGROUND

Inflammation is integral to early disease progression in children with CF. The effect of modifiable environmental factors on infection and inflammation in persons with CF is poorly understood. Our prior studies determined that secondhand smoke exposure (SHSe) is highly prevalent in young children with CF. SHSe is associated with increased inflammation, heightened bacterial burden, and worsened clinical outcomes. However, the specific metabolite and signaling pathways that regulate responses to SHSe in CF are relatively unknown.

METHODS

High-resolution metabolomics was performed on plasma samples from infants (n = 25) and children (n = 40) with CF compared to non-CF controls (n = 15). CF groups were stratified according to infant or child age and SHSe status.

RESULTS

Global metabolomic profiles segregated by age and SHSe status. SHSe in CF was associated with changes in pathways related to steroid biosynthesis, fatty acid metabolism, cysteine metabolism, and oxidative stress. CF infants with SHSe demonstrated enrichment for altered metabolite localization to the small intestine, liver, and striatum. CF children with SHSe demonstrated metabolite enrichment for organs/tissues associated with oxidative stress including mitochondria, peroxisomes, and the endoplasmic reticulum. In a confirmatory analysis, SHSe was associated with changes in biomarkers of oxidative stress and cellular adhesion including MMP-9, MPO, and ICAM-1.

CONCLUSIONS

SHSe in young children and infants with CF is associated with altered global metabolomics profiles and specific biochemical pathways, including enhanced oxidative stress. SHSe remains an important but understudied modifiable variable in early CF disease.

Untargeted LC-MS Metabolomics Differentiates Between Virulent and Avirulent Clinical Strains of Pseudomonas aeruginosa

Pseudomonas aeruginosa is a facultative pathogen that can cause, inter alia, acute or chronic pneumonia in predisposed individuals. The gram-negative bacterium displays considerable genomic and phenotypic diversity that is also shaped by small molecule secondary metabolites. The discrimination of virulence phenotypes is highly relevant to the diagnosis and prognosis of P. aeruginosa infections. In order to discover small molecule metabolites that distinguish different virulence phenotypes of P. aeruginosa, 35 clinical strains were cultivated under standard conditions, characterized in terms of virulence and biofilm phenotype, and their metabolomes were investigated by untargeted liquid chromatography-mass spectrometry. The data was both mined for individual candidate markers as well as used to construct statistical models to infer the virulence phenotype from metabolomics data. We found that clinical strains that differed in their virulence and biofilm phenotype also had pronounced divergence in their metabolomes, as underlined by 332 features that were significantly differentially abundant with fold changes greater than 1.5 in both directions. Important virulence-associated secondary metabolites like rhamnolipids, alkyl quinolones or phenazines were found to be strongly upregulated in virulent strains. In contrast, we observed little change in primary metabolism. A hitherto novel cationic metabolite with a sum formula of C₁₂H₁₅N₂ could be identified as a candidate biomarker. A random forest model was able to classify strains according to their virulence and biofilm phenotype with an area under the Receiver Operation Characteristics curve of 0.84. These findings demonstrate that untargeted metabolomics is a valuable tool to characterize P. aeruginosa virulence, and to explore interrelations between clinically important phenotypic traits and the bacterial metabolome.

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.

Refinement of metabolite detection in cystic fibrosis sputum reveals heme correlates with lung function decline

The bacterial growth environment within cystic fibrosis (CF) sputum is complex, dynamic, and shaped by both host and microbial processes. Characterization of the chemical parameters within sputum that stimulate the in vivo growth of airway pathogens (e.g. Pseudomonas aeruginosa) and their associated virulence factors may lead to improved CF treatment strategies. Motivated by conflicting reports of the prevalence and abundance of P. aeruginosa-derived metabolites known as phenazines within CF airway secretions, we sought to quantify these metabolites in sputum using quadrupole time-of-flight mass spectrometry. In contrast to our previous work, all phenazines tested (pyocyanin (PYO), phenazine-1-carboxylic acid (PCA), phenazine-1-carboxamide, and 1-hydroxyphenazine) were below detection limits of the instrument (0.1 μM). Instead, we identified a late-eluting compound that shared retention time and absorbance characteristics with PCA, yet generated mass spectra and a fragmentation pattern consistent with ferriprotoporphyrin IX, otherwise known as heme B. These data suggested that UV-vis chromatographic peaks previously attributed to PCA and PYO in sputum were mis-assigned. Indeed, retrospective analysis of raw data from our prior study found that the heme B peak closely matched the peaks assigned to PCA, indicating that the previous study likely uncovered a positive correlation between pulmonary function (percent predicted forced expiratory volume in 1 second, or ppFEV1) and heme B, not PCA or any other phenazine. To independently test this observation, we performed a new tandem mass-spectrometry analysis of 71 additional samples provided by the Mountain West CF Consortium Sputum Biomarker study and revealed a positive correlation (ρ = −0.47, p<0.001) between sputum heme concentrations and ppFEV1. Given that hemoptysis is strongly associated with airway inflammation, pulmonary exacerbations and impaired lung function, these new data suggest that heme B may be a useful biomarker of CF pathophysiology.

PQS Produced by the Pseudomonas aeruginosa Stress Response Repels Swarms Away from Bacteriophage and Antibiotics

We investigate the effect of bacteriophage infection and antibiotic treatment on the coordination of swarming, a collective form of flagellum- and pilus-mediated motility in bacteria. We show that phage infection of the opportunistic bacterial pathogen Pseudomonas aeruginosa abolishes swarming motility in the infected subpopulation and induces the release of the Pseudomonas quinolone signaling molecule PQS, which repulses uninfected subpopulations from approaching the infected area. These mechanisms have the overall effect of limiting the infection to a subpopulation, which promotes the survival of the overall population. Antibiotic treatment of P. aeruginosa elicits the same response, abolishing swarming motility and repulsing approaching swarms away from the antibiotic-treated area through a PQS-dependent mechanism. Swarms are entirely repelled from the zone of antibiotic-treated P. aeruginosa, consistent with a form of antibiotic evasion, and are not repelled by antibiotics alone. PQS has multiple functions, including serving as a quorum-sensing molecule, activating an oxidative stress response, and regulating the release of virulence and host-modifying factors. We show that PQS serves additionally as a stress warning signal that causes the greater population to physically avoid cell stress. The stress response at the collective level observed here in P. aeruginosa is consistent with a mechanism that promotes the survival of bacterial populations.IMPORTANCE We uncover a phage- and antibiotic-induced stress response in the clinically important opportunistic pathogen Pseudomonas aeruginosa Phage-infected P. aeruginosa subpopulations are isolated from uninfected subpopulations by the production of a stress-induced signal. Activation of the stress response by antibiotics causes P. aeruginosa to physically be repelled from the area containing antibiotics altogether, consistent with a mechanism of antibiotic evasion. The stress response observed here could increase P. aeruginosa resilience against antibiotic treatment and phage therapy in health care settings, as well as provide a simple evolutionary strategy to avoid areas containing stress.

Early Detection of Cystic Fibrosis Acute Pulmonary Exacerbations by Exhaled Breath Condensate Metabolomics

The most common cause of death in cystic fibrosis (CF) patients is progressive lung function decline, which is punctuated by acute pulmonary exacerbations (APEs). A major challenge is to discover biomarkers for detecting an oncoming APE and allow for pre-emptive clinical interventions. Metabolic profiling of exhaled breath condensate (EBC) samples collected from CF patients before, during, and after APEs and under stable conditions (n = 210) was performed using ultraperformance liquid chromatography (UPLC) coupled to Orbitrap mass spectrometry (MS). Negative ion mode MS data showed that classification between metabolic profiles from "pre-APE" (pending APE before the CF patient had any signs of illness) and stable CF samples was possible with good sensitivities (85.7 and 89.5%), specificities (88.4 and 84.1%), and accuracies (87.7 and 85.7%) for pediatric and adult patients, respectively. Improved classification performance was achieved by combining positive with negative ion mode data. Discriminant metabolites included two potential biomarkers identified in a previous pilot study: lactic acid and 4-hydroxycyclohexylcarboxylic acid. Some of the discriminant metabolites had microbial origins, indicating a possible role of bacterial metabolism in APE progression. The results show promise for detecting an oncoming APE using EBC metabolites, thus permitting early intervention to abort such an event.

Functional effects of the microbiota in chronic respiratory disease

The composition of the lung microbiome is increasingly well characterised, with changes in microbial diversity or abundance observed in association with several chronic respiratory diseases such as asthma, cystic fibrosis, bronchiectasis, and chronic obstructive pulmonary disease. However, the precise effects of the microbiome on pulmonary health and the functional mechanisms by which it regulates host immunity are only now beginning to be elucidated. Bacteria, viruses, and fungi from both the upper and lower respiratory tract produce structural ligands and metabolites that interact with the host and alter the development and progression of chronic respiratory diseases. Here, we review recent advances in our understanding of the composition of the lung microbiome, including the virome and mycobiome, the mechanisms by which these microbes interact with host immunity, and their functional effects on the pathogenesis, exacerbations, and comorbidities of chronic respiratory diseases. We also describe the present understanding of how respiratory microbiota can influence the efficacy of common therapies for chronic respiratory disease, and the potential of manipulation of the microbiome as a therapeutic strategy. Finally, we highlight some of the limitations in the field and propose how these could be addressed in future research.

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

G-CSF and GM-CSF Modify Neutrophil Functions at Concentrations found in Cystic Fibrosis

The role of colony stimulating factors (CSFs) in cystic fibrosis (CF) circulating neutrophils has not been thoroughly evaluated, considering that the neutrophil burden of lung inflammation in these subjects is very high. The aim of this study was to assess granulocyte-CSF (G-CSF) and granulocyte-macrophage-CSF (GM-CSF) levels in CF patients in various clinical conditions and how these cytokines impact on activation and priming of neutrophils. G-CSF and GM-CSF levels were measured in sputum and serum samples of stable CF patients (n = 21) and in CF patients with acute exacerbation before and after a course of antibiotic therapy (n = 19). CSFs were tested on non CF neutrophils to investigate their effects on reactive oxygen species (ROS) production, degranulation (CD66b, elastase, lactoferrin, MMP-9), and chemotaxis. At very low concentrations found in CF patients (0.005–0.1 ng/ml), both cytokines inhibited ROS production, while higher concentrations (1–5 ng/ml) exerted a stimulatory effect. While either CSF induced elastase and MMP-9 secretion, lactoferrin levels were increased only by G-CSF. Chemotaxis was inhibited by GM-CSF, but was increased by G-CSF. However, when present together at low concentrations, CSFs increased basal and fMLP-stimulated ROS production and chemotaxis. These results suggest the CSF levels that circulating neutrophils face before extravasating into the lungs of CF patients may enhance their function contributing to the airway damage.

The expanding horizon of alkyl quinolone signalling and communication in polycellular interactomes

Population dynamics within natural ecosystems is underpinned by microbial diversity and the heterogeneity of host-microbe and microbe-microbe interactions. Small molecule signals that intersperse between species have been shown to govern many virulence-related processes in established and emerging pathogens. Understanding the capacity of microbes to decode diverse languages and adapt to the presence of 'non-self' cells will provide an important new direction to the understanding of the 'polycellular' interactome. Alkyl quinolones (AQs) have been described in the ESKAPE pathogen Pseudomonas aeruginosa, the primary agent associated with mortality in patients with cystic fibrosis and the third most prevalent nosocomial pathogen worldwide. The role of these molecules in governing the physiology and virulence of P. aeruginosa and other pathogens has received considerable attention, while a role in interspecies and interkingdom communication has recently emerged. Herein we discuss recent advances in our understanding of AQ signalling and communication in the context of microbe-microbe and microbe-host interactions. The integrated knowledge from these systems-based investigations will facilitate the development of new therapeutics based on the AQ framework that serves to disarm the pathogenesis of P. aeruginosa and competing pathogens.

The human gut microbiome - a new and exciting avenue in cardiovascular drug discovery

Introduction: Over the past decade, numerous research efforts have identified the gut microbiota as a novel regulator of human metabolic syndrome and cardiovascular disease (CVD). With the elucidation of underlying molecular mechanisms of the gut microbiota and its metabolites, the drug-discovery process of CVD therapeutics might be expedited. Areas covered: The authors describe the evidence concerning the impact of gut microbiota on metabolic disorders and CVD and summarize the current knowledge of the gut microbial mechanisms that underlie CVD with a focus on microbial metabolites. In addition, they discuss the potential impact of the gut microbiota on the drug efficacy of available cardiometabolic therapeutic agents. Most importantly, the authors review the role of the gut microbiome as a promising source of potential drug targets and novel therapeutics for the development of new treatment modalities for CVD. This review also presents the various effective strategies to investigate the gut microbiome for CVD drug-discovery approaches. Expert opinion: With the elucidation of its causative role in cardiometabolic disease and atherosclerosis, the human gut microbiome holds promises as a reservoir of novel potential therapeutic targets as well as novel therapeutic agents, paving a new and exciting avenue in cardiovascular drug discovery.

Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance

Cystic fibrosis (CF) is a genetic disease in which chronic airway infections and lung inflammation result in respiratory failure. CF airway infections are usually caused by bacterial communities that are difficult to eradicate with available antibiotics. Using species abundance data for clinically stable adult CF patients assimilated from three published studies, we developed a metabolic model of CF airway communities to better understand the interactions between bacterial species and between the bacterial community and the lung environment. Our model predicted that clinically observed CF pathogens could establish dominance over other community members across a range of lung nutrient conditions. Heterogeneity of species abundances across 75 patient samples could be predicted by assuming that sample-to-sample heterogeneity was attributable to random variations in the CF nutrient environment. Our model predictions provide new insights into the metabolic determinants of pathogen dominance in the CF lung and could facilitate the development of improved treatment strategies.

Cystic fibrosis (CF) is a fatal genetic disease characterized by chronic lung infections due to aberrant mucus production and the inability to clear invading pathogens. The traditional view that CF infections are caused by a single pathogen has been replaced by the realization that the CF lung usually is colonized by a complex community of bacteria, fungi, and viruses. To help unravel the complex interplay between the CF lung environment and the infecting microbial community, we developed a community metabolic model comprised of the 17 most abundant bacterial taxa, which account for >95% of reads across samples, from three published studies in which 75 sputum samples from 46 adult CF patients were analyzed by 16S rRNA gene sequencing. The community model was able to correctly predict high abundances of the “rare” pathogens Enterobacteriaceae, Burkholderia, and Achromobacter in three patients whose polymicrobial infections were dominated by these pathogens. With these three pathogens removed, the model correctly predicted that the remaining 43 patients would be dominated by Pseudomonas and/or Streptococcus. This dominance was predicted to be driven by relatively high monoculture growth rates of Pseudomonas and Streptococcus as well as their ability to efficiently consume amino acids, organic acids, and alcohols secreted by other community members. Sample-by-sample heterogeneity of community composition could be qualitatively captured through random variation of the simulated metabolic environment, suggesting that experimental studies directly linking CF lung metabolomics and 16S sequencing could provide important insights into disease progression and treatment efficacy.

IMPORTANCE Cystic fibrosis (CF) is a genetic disease in which chronic airway infections and lung inflammation result in respiratory failure. CF airway infections are usually caused by bacterial communities that are difficult to eradicate with available antibiotics. Using species abundance data for clinically stable adult CF patients assimilated from three published studies, we developed a metabolic model of CF airway communities to better understand the interactions between bacterial species and between the bacterial community and the lung environment. Our model predicted that clinically observed CF pathogens could establish dominance over other community members across a range of lung nutrient conditions. Heterogeneity of species abundances across 75 patient samples could be predicted by assuming that sample-to-sample heterogeneity was attributable to random variations in the CF nutrient environment. Our model predictions provide new insights into the metabolic determinants of pathogen dominance in the CF lung and could facilitate the development of improved treatment strategies.

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.

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.

Anaerobes in cystic fibrosis patients' airways

Anaerobes are known to constitute an important part of the airway microbiota in both healthy subjects and cystic fibrosis (CF) patients. Studies on the potential role of anaerobic bacteria in CF and thus their involvement in CF pathophysiology have reported contradictory results, and the question is still not elucidated. The aim of this study was to summarize anaerobe diversity in the airway microbiota and its potential role in CF, to provide an overview of the state of knowledge on anaerobe antibiotic resistances (resistome), and to investigate the detectable metabolites produced by anaerobes in CF airways (metabolome). This review emphasizes key metabolites produced by strict anaerobic bacteria (sphingolipids, fermentation-induced metabolites and metabolites involved in quorum-sensing), which may be essential for the better understanding of lung disease pathophysiology in CF.

Refining the Application of Microbial Lipids as Tracers of Staphylococcus aureus Growth Rates in Cystic Fibrosis Sputum

Chronic lung infections in cystic fibrosis (CF) could be treated more effectively if the effects of antimicrobials on pathogens in situ were known. Here, we compared changes in the microbial community composition and pathogen growth rates in longitudinal studies of seven pediatric CF patients undergoing intravenous antibiotic administration during pulmonary exacerbations. The microbial community composition was determined by counting rRNA with NanoString DNA analysis, and growth rates were obtained by incubating CF sputum with heavy water and tracing incorporation of deuterium into two branched-chain ("anteiso") fatty acids (a-C_15:0 and a-C_17:0) using gas chromatography-mass spectrometry (GC/MS). Prior to this study, both lipids were thought to be specific for Staphylococcaceae; hence, their isotopic enrichment was interpreted as a growth proxy for Staphylococcus aureus Our experiments revealed, however, that Prevotella is also a relevant microbial producer of a-C_17:0 fatty acid in some CF patients; thus, deuterium incorporation into these lipids is better interpreted as a more general pathogen growth rate proxy. Even accounting for a small nonmicrobial background source detected in some patient samples, a-C_15:0 fatty acid still appears to be a relatively robust proxy for CF pathogens, revealing a median generation time of ∼1.5 days, similar to prior observations. Contrary to our expectation, pathogen growth rates remained relatively stable throughout exacerbation treatment. We suggest two straightforward "best practices" for application of stable-isotope probing to CF sputum metabolites: (i) parallel determination of microbial community composition in CF sputum using culture-independent tools and (ii) assessing background levels of the diagnostic metabolite.IMPORTANCE In chronic lung infections, populations of microbial pathogens change and mature in ways that are often unknown, which makes it challenging to identify appropriate treatment options. A promising tool to better understand the physiology of microorganisms in a patient is stable-isotope probing, which we previously developed to estimate the growth rates of S. aureus in cystic fibrosis (CF) sputum. Here, we tracked microbial communities in a cohort of CF patients and found that anteiso fatty acids can also originate from other sources in CF sputum. This awareness led us to develop a new workflow for the application of stable-isotope probing in this context, improving our ability to estimate pathogen generation times in clinical samples.

Urinary metabolomics reveals unique metabolic signatures in infants with cystic fibrosis

BACKGROUND

Biologic pathways and metabolic mechanisms underpinning early systemic disease in cystic fibrosis (CF) are poorly understood. The Baby Observational and Nutrition Study (BONUS) was a prospective multi-center study of infants with CF with a primary aim to examine the current state of nutrition in the first year of life. Its secondary aim was to prospectively explore concurrent nutritional, metabolic, respiratory, infectious, and inflammatory characteristics associated with early CF anthropometric measurements. We report here metabolomics differences within the urine of these infants as compared to infants without CF.

METHODS

Urine metabolomics was performed for 85 infants with predefined clinical phenotypes at approximately one year of age enrolled in BONUS via Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS). Samples were stratified by disease status (non-CF controls (n = 22); CF (n = 63, All-CF)) and CF clinical phenotype: respiratory hospitalization (CF Resp, n = 22), low length (CF LL, n = 23), and low weight (CF LW, n = 15).

RESULTS

Global urine metabolomics profiles in CF were heterogeneous, however there were distinct metabolic differences between the CF and non-CF groups. Top pathways altered in CF included tRNA charging and methionine degradation. ADCYAP1 and huntingtin were identified as predicted unique regulators of altered metabolic pathways in CF compared to non-CF. Infants with CF displayed alterations in metabolites associated with bile acid homeostasis, pentose sugars, and vitamins.

CONCLUSIONS

Predicted metabolic pathways and regulators were identified in CF infants compared to non-CF, but metabolic profiles were unable to discriminate between CF phenotypes. Targeted metabolomics provides an opportunity for further understanding of early CF disease.

TRIAL REGISTRATION

United States ClinicalTrials.Gov registry NCT01424696 (clinicaltrials.gov).

Multiplatform Physiologic and Metabolic Phenotyping Reveals Microbial Toxicity

The gut microbiota is susceptible to modulation by environmental stimuli and therefore can serve as a biological sensor. Recent evidence suggests that xenobiotics can disrupt the interaction between the microbiota and host. Here, we describe an approach that combines in vitro microbial incubation (isolated cecal contents from mice), flow cytometry, and mass spectrometry- and 1H nuclear magnetic resonance (NMR)-based metabolomics to evaluate xenobiotic-induced microbial toxicity. Tempol, a stabilized free radical scavenger known to remodel the microbial community structure and function in vivo, was studied to assess its direct effect on the gut microbiota. The microbiota was isolated from mouse cecum and was exposed to tempol for 4 h under strict anaerobic conditions. The flow cytometry data suggested that short-term tempol exposure to the microbiota is associated with disrupted membrane physiology as well as compromised metabolic activity. Mass spectrometry and NMR metabolomics revealed that tempol exposure significantly disrupted microbial metabolic activity, specifically indicated by changes in short-chain fatty acids, branched-chain amino acids, amino acids, nucleotides, glucose, and oligosaccharides. In addition, a mouse study with tempol (5 days gavage) showed similar microbial physiologic and metabolic changes, indicating that the in vitro approach reflected in vivo conditions. Our results, through evaluation of microbial viability, physiology, and metabolism and a comparison of in vitro and in vivo exposures with tempol, suggest that physiologic and metabolic phenotyping can provide unique insight into gut microbiota toxicity. IMPORTANCE The gut microbiota is modulated physiologically, compositionally, and metabolically by xenobiotics, potentially causing metabolic consequences to the host. We recently reported that tempol, a stabilized free radical nitroxide, can exert beneficial effects on the host through modulation of the microbiome community structure and function. Here, we investigated a multiplatform phenotyping approach that combines high-throughput global metabolomics with flow cytometry to evaluate the direct effect of tempol on the microbiota. This approach may be useful in deciphering how other xenobiotics directly influence the microbiota.

The contribution of respiratory microbiome analysis to a treatable traits model of care

The composition of the airway microbiome in patients with chronic airway diseases, such as severe asthma, chronic obstructive pulmonary disease (COPD), bronchiectasis and cystic fibrosis (CF), has the potential to inform a precision model of clinical care. Patients with these conditions share overlapping disease characteristics, including airway inflammation and airflow limitation. The clinical management of chronic respiratory conditions is increasingly moving away from a one-size-fits-all model based on primary diagnosis, towards care targeting individual disease traits, and is particularly useful for subgroups of patients who respond poorly to conventional therapies. Respiratory microbiome analysis is an important potential contributor to such a 'treatable traits' approach, providing insight into both microbial drivers of airways disease, and the selective characteristics of the changing lower airway environment. We explore the potential to integrate respiratory microbiome analysis into a treatable traits model of clinical care and provide a practical guide to the application and clinical interpretation of respiratory microbiome analysis.

Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers

BACKGROUND

Lung epithelial lining fluid (ELF)-sampled through sputum induction-is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood.

OBJECTIVES

To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort.

METHODS

Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes.

RESULTS

The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender.

CONCLUSIONS

We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.

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.

Neutrophil elastase correlates with increased sphingolipid content in cystic fibrosis sputum

INTRODUCTION

Sphingolipids are associated with the regulation of pulmonary inflammation. Although sphingolipids have been investigated in the context of cystic fibrosis (CF), the focus has been on loss of CF transmembrane conductance regulator (CFTR) function in mice, and in CF human lung epithelial cell lines. The sphingolipid content of CF sputum and the potential link between ceramide and airway inflammation in CF remain relatively unexplored.

METHODS

Fifteen patients with CF provided two spontaneously expectorated sputum samples, one collected during a hospitalization for an acute pulmonary exacerbation and one from an outpatient visit at a time of clinical stability. Sputum was processed, and the supernatant assessed for active neutrophil elastase (NE) using a chromogenic microplate assay and sphingolipid content using reverse phase high-performance liquid chromatography/electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Relevant demographic data including age, sex, CF genotype, FEV₁ % predicted, and sputum bacteriology were assessed as possible modifying factors that could influence the correlation between NE and sputum sphingolipids. Data were analyzed for linear correlation, with statistical significance pre-defined as P < 0.05.

RESULTS

There was a significant association between the concentration of active NE and ceramide, sphingomyelin, and monohexosylceramide moieties as well as sphingosine-1-phosphate. The presence of Methicillin-resistant Staphylococcus aureus (MRSA), FEV₁ % predicted, and female gender further strengthened the association of NE and sphingolipids, but Pseudomonas aeruginosa had no effect on the association between NE and sphingolipids.

CONCLUSIONS

These data suggest that NE may increase pro-inflammatory sphingolipid signaling, and the association is strengthened in female patients and patients with MRSA.