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

Solid-state NMR compositional analysis of sputum from people with cystic fibrosis

People with the genetic disease cystic fibrosis (CF) often have chronic airway infections and produce airway secretions called sputum. A better understanding of sputum composition is desired in order to track changes in response to CF therapeutics and to improve laboratory models for the study of CF airway infections. The glycosylated protein mucin is a primary component. Along with extracellular DNA, mucin gives rise to the high viscoelasticity of sputum, which inhibits airway clearance and is thought to promote chronic airway infections in people with CF. Past studies of sputum composition identified additional biomolecular components of sputum including other proteins, both glycosylated and not glycosylated, free amino acids, and lipids. Typically, studies of sputum, as well as other complex biological materials, have focused on soluble or isolated components. Solid-state NMR is not limited to the study of soluble components. Instead, it can provide molecular-level information about insoluble biological samples. Additionally, solid-state NMR can provide information about sample composition without requiring any processing of the sample, eliminating the possibility of misestimating certain components due to insolubility or potential sample loss in isolation steps. In this study, we used both 13C and 31P CPMAS to investigate the total composition of sputum samples obtained from six people with CF. We compared these spectra to those of commercially available mucin, DNA, and phospholipid samples. Lastly, we performed complementary biochemical analyses to identify specific proteins present in the sputum samples. Overall, our findings provide insight into the composition of unprocessed sputum samples from people with CF, which can be used as a benchmark for future investigations of CF and infections in the airways of people with CF. Further, this study provides opportunities to expand the solid-state NMR approach to include dynamic nuclear polarization (DNP) to obtain high-resolution information of sputum and similar biological samples that are not feasible to isotopically enrich.

Metabolomics analysis of bronchoalveolar lavage fluid predicts unique features of the lower airway in pediatric cystic fibrosis

BACKGROUND

Progressive, obstructive lung disease resulting from chronic infection and inflammation is the leading cause of morbidity and mortality in persons with cystic fibrosis (PWCF). Metabolomics and next -generation sequencing (NGS) of airway secretions can allow for better understanding of cystic fibrosis (CF) pathophysiology. In this study, global metabolomic profiling on bronchoalveolar lavage fluid (BALF) obtained from pediatric PWCF and disease controls (DCs) was performed and compared to lower airway microbiota, inflammation, and lung function.

METHODS

BALF was collected from children undergoing flexible bronchoscopies for clinical indications. Metabolomic profiling was performed using a platform developed by Metabolon Inc. Total bacterial load (TBL) was measured using quantitative polymerase chain reaction (qPCR), and bacterial communities were characterized using 16S ribosomal RNA (rRNA) sequencing. Random Forest Analysis (RFA), principal component analysis (PCA), and hierarchical clustering analysis (HCA) were performed.

RESULTS

One hundred ninety-five BALF samples were analyzed, 142 (73 %) from PWCF. Most metabolites (425/665) and summed categories (7/9) were significantly increased in PWCF. PCA of the metabolomic data revealed CF BALF exhibited more dispersed clustering compared to DC BALF. Higher metabolite concentrations correlated with increased inflammation, increased abundance of Staphylococcus, and decreased lung function.

CONCLUSIONS

The lower airway metabolome of PWCF was defined by a complex expansion of metabolomic activity. These findings could be attributed to heightened inflammation in PWCF and aspects of the CF airway polymicrobial ecology. CF-specific metabolomic features are associated with the unique underlying biology of the CF airway.

Microbiome and metabolome patterns after lung transplantation reflect underlying disease and chronic lung allograft dysfunction

BACKGROUND

Progression of chronic lung disease may lead to the requirement for lung transplant (LTx). Despite improvements in short-term survival after LTx, chronic lung allograft dysfunction (CLAD) remains a critical challenge for long-term survival. This study investigates the molecular and microbial relationships between underlying lung disease and the development of CLAD in bronchoalveolar lavage fluid (BALF) from subjects post-LTx, which is crucial for tailoring treatment strategies specific to allograft dysfunctions.

METHODS

Paired 16S rRNA gene amplicon sequencing and untargeted LC-MS/MS metabolomics were performed on 856 BALF samples collected over 10 years from LTx recipients (n = 195) with alpha-1-antitrypsin disease (AATD, n = 23), cystic fibrosis (CF, n = 47), chronic obstructive pulmonary disease (COPD, n = 78), or pulmonary fibrosis (PF, n = 47). Data were analyzed using random forest (RF) machine learning and multivariate statistics for associations with underlying disease and CLAD development.

RESULTS

The BALF microbiome and metabolome after LTx differed significantly according to the underlying disease state (PERMANOVA, p = 0.001), with CF and AATD demonstrating distinct microbiome and metabolome profiles, respectively. Uniqueness in CF was mainly driven by Pseudomonas abundance and its metabolites, whereas AATD had elevated levels of phenylalanine and a lack of shared metabolites with the other underlying diseases. BALF microbiome and metabolome composition were also distinct between those who did or did not develop CLAD during the sample collection period (PERMANOVA, p = 0.001). An increase in the average abundance of Veillonella (AATD, COPD) and Streptococcus (CF, PF) was associated with CLAD development, and decreases in the abundance of phenylalanine-derivative alkaloids (CF, COPD) and glycerophosphorylcholines (CF, COPD, PF) were signatures of the CLAD metabolome. Although the relative abundance of Pseudomonas was not associated with CLAD, the abundance of its virulence metabolites, including siderophores, quorum-sensing quinolones, and phenazines, were elevated in those with CF who developed CLAD. There was a positive correlation between the abundance of these molecules and the abundance of Pseudomonas in the microbiome, but there was no correlation between their abundance and the time in which BALF samples were collected post-LTx.

CONCLUSIONS

The BALF microbiome and metabolome after LTx are particularly distinct in those with underlying CF and AATD. These data reflect those who developed CLAD, with increased virulence metabolite production from Pseudomonas, an aspect of CF CLAD cases. These findings shed light on disease-specific microbial and metabolic signatures in LTx recipients, offering valuable insights into the underlying causes of allograft rejection. Video Abstract.

Neutrophil-Derived Proteases in Lung Inflammation: Old Players and New Prospects

Neutrophil-derived proteases are critical to the pathology of many inflammatory lung diseases, both chronic and acute. These abundant enzymes play roles in key neutrophil functions, such as neutrophil extracellular trap formation and reactive oxygen species release. They may also be released, inducing tissue damage and loss of tissue function. Historically, the neutrophil serine proteases (NSPs) have been the main subject of neutrophil protease research. Despite highly promising cell-based and animal model work, clinical trials involving the inhibition of NSPs have shown mixed results in lung disease patients. As such, the cutting edge of neutrophil-derived protease research has shifted to proteases that have had little-to-no research in neutrophils to date. These include the cysteine and serine cathepsins, the metzincins and the calpains, among others. This review aims to outline the previous work carried out on NSPs, including the shortcomings of some of the inhibitor-orientated clinical trials. Our growing understanding of other proteases involved in neutrophil function and neutrophilic lung inflammation will then be discussed. Additionally, the potential of targeting these more obscure neutrophil proteases will be highlighted, as they may represent new targets for inhibitor-based treatments of neutrophil-mediated lung inflammation.

Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.

A GMR enzymatic assay for quantifying nuclease and peptidase activity

Hydrolytic enzymes play crucial roles in cellular processes, and dysregulation of their activities is implicated in various physiological and pathological conditions. These enzymes cleave substrates such as peptide bonds, phosphodiester bonds, glycosidic bonds, and other esters. Detecting aberrant hydrolase activity is vital for understanding disease mechanisms and developing targeted therapeutic interventions. This study introduces a novel approach to measuring hydrolase activity using giant magnetoresistive (GMR) spin valve sensors. These sensors change resistance in response to magnetic fields, and here, they are functionalized with specific substrates for hydrolases conjugated to magnetic nanoparticles (MNPs). When a hydrolase cleaves its substrate, the tethered magnetic nanoparticle detaches, causing a measurable shift in the sensor's resistance. This design translates hydrolase activity into a real-time, activity-dependent signal. The assay is simple, rapid, and requires no washing steps, making it ideal for point-of-care settings. Unlike fluorescent methods, it avoids issues like autofluorescence and photobleaching, broadening its applicability to diverse biofluids. Furthermore, the sensor array contains 80 individually addressable sensors, allowing for the simultaneous measurement of multiple hydrolases in a single reaction. The versatility of this method is demonstrated with substrates for nucleases, Bcu I and DNase I, and the peptidase, human neutrophil elastase. To demonstrate a clinical application, we show that neutrophil elastase in sputum from cystic fibrosis patients hydrolyze the peptide-GMR substrate, and the cleavage rate strongly correlates with a traditional fluorogenic substrate. This innovative assay addresses challenges associated with traditional enzyme measurement techniques, providing a promising tool for real-time quantification of hydrolase activities in diverse biological contexts.

Influence of highly effective modulator therapy on the sputum proteome in cystic fibrosis

BACKGROUND

There have been dramatic clinical improvements in people with cystic fibrosis (PwCF) commenced on the cystic fibrosis conductance regulator (CFTR) modulator elexacaftor/tezacaftor/ivacaftor (ETI). Sputum proteomics is a powerful research technique capable of identifying important airway disease mechanisms. Using this technique, we evaluated how ETI changes the sputum proteome in PwCF.

METHODS

Sputum samples from 21 CF subjects pre- and post- ETI, 6 CF controls ineligible for ETI, and 15 healthy controls were analysed by liquid chromatography mass spectrometry.

RESULTS

Post-ETI, mean FEV1 % increased by 13.7 % (SD 7.9). Principal component and hierarchical clustering analysis revealed that the post-ETI proteome shifted to an intermediate state that was distinct from pre-ETI and healthy controls, even for those achieving normal lung function. Functional analysis showed incomplete resolution of neutrophilic inflammation. The CF control sputum proteome did not alter. At the protein-level many more proteins increased in abundance than decreased following ETI therapy (80 vs 30; adjusted p value <0.05), including many that have anti-inflammatory properties. Of those proteins that reduced in abundance many were pro-inflammatory neutrophil-derived proteins. Several important respiratory proteases were unchanged.

CONCLUSIONS

Sputum proteomics can provide insights into CF lung disease mechanisms and how they are modified by therapeutic intervention, in this case ETI. This study identifies imbalances in pro- and anti- inflammatory proteins in sputum that partially resolve with ETI even in those achieving normal spirometry values. This post-ETI intermediate state could contribute to ongoing airway damage and therefore its relevance to clinical outcomes needs to be established.

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.

Effect of seven anti-tuberculosis treatment regimens on sputum microbiome: a retrospective analysis of the HIGHRIF study 2 and PanACEA MAMS-TB clinical trials

BACKGROUND

Respiratory tract microbiota has been described as the gatekeeper for respiratory health. We aimed to assess the impact of standard-of-care and experimental anti-tuberculosis treatment regimens on the respiratory microbiome and implications for treatment outcomes.

METHODS

In this retrospective study, we analysed the sputum microbiome of participants with tuberculosis treated with six experimental regimens versus standard-of-care who were part of the HIGHRIF study 2 (NCT00760149) and PanACEA MAMS-TB (NCT01785186) clinical trials across a 3-month treatment follow-up period. Samples were from participants in Mbeya, Kilimanjaro, Bagamoyo, and Dar es Salaam, Tanzania. Experimental regimens were composed of different combinations of rifampicin (R), isoniazid (H), pyrazinamide (Z), ethambutol (E), moxifloxacin (M), and a new drug, SQ109 (Q). Reverse transcription was used to create complementary DNA for each participant's total sputum RNA and the V3-V4 region of the 16S rRNA gene was sequenced using the Illumina metagenomic technique. Qiime was used to analyse the amplicon sequence variants and estimate alpha diversity. Descriptive statistics were applied to assess differences in alpha diversity pre-treatment and post-treatment initiation and the effect of each treatment regimen.

FINDINGS

Sequence data were obtained from 397 pre-treatment and post-treatment samples taken between Sept 26, 2008, and June 30, 2015, across seven treatment regimens. Pre-treatment microbiome (206 genera) was dominated by Firmicutes (2860 [44%] of 6500 amplicon sequence variants [ASVs]) at the phylum level and Streptococcus (2340 [36%] ASVs) at the genus level. Two regimens had a significant depressing effect on the microbiome after 2 weeks of treatment, HR20mg/kgZM (Shannon diversity index p=0·0041) and HR35mg/kgZE (p=0·027). Gram-negative bacteria were the most sensitive to bactericidal activity of treatment with the highest number of species suppressed being under the moxifloxacin regimen. By week 12 after treatment initiation, microbiomes had recovered to pre-treatment level except for the HR35mg/kgZE regimen and for genus Mycobacterium, which did not show recovery across all regimens. Tuberculosis culture conversion to negative by week 8 of treatment was associated with clearance of genus Neisseria, with a 98% reduction of the pre-treatment level.

INTERPRETATION

HR20mg/kgZM was effective against tuberculosis without limiting microbiome recovery, which implies a shorter efficacious anti-tuberculosis regimen with improved treatment outcomes might be achieved without harming the commensal microbiota.

FUNDING

European and Developing Countries Clinical Trials Partnership and German Ministry of Education and Research.

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.

Metabolomics identifies disturbances in arginine, phenylalanine, and glycine metabolism as differentiating features of exacerbating atopic asthma in children

Background

Asthma exacerbations are highly prevalent in children, but only a few studies have examined the biologic mechanisms underlying exacerbations in this population.

Objective

High-resolution metabolomics analyses were performed to understand the differences in metabolites in children with exacerbating asthma who were hospitalized in a pediatric intensive care unit for status asthmaticus. We hypothesized that compared with a similar population of stable outpatients with asthma, children with exacerbating asthma would have differing metabolite abundance patterns with distinct clustering profiles.

Methods

A total of 98 children aged 6 through 17 years with exacerbating asthma (n = 69) and stable asthma (n = 29) underwent clinical characterization procedures and submitted plasma samples for metabolomic analyses. High-confidence metabolites were retained and utilized for pathway enrichment analyses to identify the most relevant metabolic pathways that discriminated between groups.

Results

In all, 118 and 131 high-confidence metabolites were identified in positive and negative ionization mode, respectively. A total of 103 unique metabolites differed significantly between children with exacerbating asthma and children with stable asthma. In all, 8 significantly enriched pathways that were largely associated with alterations in arginine, phenylalanine, and glycine metabolism were identified. However, other metabolites and pathways of interest were also identified.

Conclusion

Metabolomic analyses identified multiple perturbed metabolites and pathways that discriminated children with exacerbating asthma who were hospitalized for status asthmaticus. These results highlight the complex biology of inflammation in children with exacerbating asthma and argue for additional studies of the metabolic determinants of asthma exacerbations in children because many of the identified metabolites of interest may be amenable to targeted interventions.

Pyochelin biotransformation by Staphylococcus aureus shapes bacterial competition with Pseudomonas aeruginosa in polymicrobial infections

Pseudomonas aeruginosa and Staphylococcus aureus are among the most frequently isolated bacterial species from polymicrobial infections of patients with cystic fibrosis and chronic wounds. We apply mass spectrometry guided interaction studies to determine how chemical interaction shapes the fitness and community structure during co-infection of these two pathogens. We demonstrate that S. aureus is equipped with an elegant mechanism to inactivate pyochelin via the yet uncharacterized methyltransferase Spm (staphylococcal pyochelin methyltransferase). Methylation of pyochelin abolishes the siderophore activity of pyochelin and significantly lowers pyochelin-mediated intracellular reactive oxygen species (ROS) production in S. aureus. In a murine wound co-infection model, an S. aureus mutant unable to methylate pyochelin shows significantly lower fitness compared with its parental strain. Thus, Spm-mediated pyochelin methylation is a mechanism to increase S. aureus survival during in vivo competition with P. aeruginosa.

Effects of Lumacaftor-Ivacaftor on Airway Microbiota-Mycobiota and Inflammation in Patients with Cystic Fibrosis Appear To Be Linked to Pseudomonas aeruginosa Chronic Colonization

The management of cystic fibrosis has been transformed recently by the advent of CFTR modulators, including lumacaftor-ivacaftor. However, the effects of such therapies on the airway ecosystem, particularly on the microbiota-mycobiota and local inflammation, which are involved in the evolution of pulmonary damage, are unclear.

α-Tocopherol Pharmacokinetics in Adults with Cystic Fibrosis: Benefits of Supplemental Vitamin C Administration

BACKGROUND

Numerous abnormalities in cystic fibrosis (CF) could influence tocopherol absorption, transportation, storage, metabolism and excretion. We hypothesized that the oxidative distress due to inflammation in CF increases vitamin E utilization, which could be positively influenced by supplemental vitamin C administration.

METHODS

Immediately before and after receiving vitamin C (500 mg) twice daily for 3.5 weeks, adult CF patients (n = 6) with moderately advanced respiratory tract (RT) disease consumed a standardized breakfast with 30% fat and a capsule containing 50 mg each hexadeuterium (d₆)-α- and dideuterium (d₂)-γ-tocopheryl acetates. Blood samples were taken frequently up to 72 h; plasma tocopherol pharmacokinetics were determined. During both trials, d₆-α- and d₂-γ-tocopherols were similarly absorbed and reached similar maximal plasma concentrations ~18-20 h. As predicted, during vitamin C supplementation, the rates of plasma d₆-α-tocopherol decline were significantly slower.

CONCLUSIONS

The vitamin C-induced decrease in the plasma disappearance rate of α-tocopherol suggests that vitamin C recycled α-tocopherol, thereby augmenting its concentrations. We conclude that some attention should be paid to plasma ascorbic acid concentrations in CF patients, particularly to those individuals with more advanced RT inflammatory disease and including those with severe exacerbations.

Competitive fitness of Pseudomonas aeruginosa isolates in human and murine precision-cut lung slices

Chronic respiratory infections with the gram-negative bacterium Pseudomonas aeruginosa are an important co-morbidity for the quality of life and prognosis of people with cystic fibrosis (CF). Such long-term colonization, sometimes lasting up to several decades, represents a unique opportunity to investigate pathogen adaptation processes to the host. Our studies aimed to resolve if and to what extent the bacterial adaptation to the CF airways influences the fitness of the pathogen to grow and to persist in the lungs. Marker-free competitive fitness experiments of serial P. aeruginosa isolates differentiated by strain-specific SNPs, were performed with murine and human precision cut lung slices (PCLS). Serial P. aeruginosa isolates were selected from six mild and six severe CF patient courses, respectively. MPCLS or hPCLS were inoculated with a mixture of equal numbers of the serial isolates of one course. The temporal change of the composition of the bacterial community during competitive growth was quantified by multi-marker amplicon sequencing. Both ex vivo models displayed a strong separation of fitness traits between mild and severe courses. Whereas the earlier isolates dominated the competition in the severe courses, intermediate and late isolates commonly won the competition in the mild courses. The status of the CF lung disease rather than the bacterial genotype drives the adaptation of P. aeruginosa during chronic CF lung infection. This implies that the disease status of the lung habitat governed the adaptation of P. aeruginosa more strongly than the underlying bacterial clone-type and its genetic repertoire.

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.

Smoking related environmental microbes affecting the pulmonary microbiome in Chinese population

BACKGROUND

Smoking is a serious public health problem that affects human health conditions. Although there is evidence that microorganisms are associated with smoking-related lung diseases, the relationship between the rich lung microbiome of upper respiratory tract groups and smoking has not been studied.

OBJECTIVE

In this study, we investigated the effects of smoking on environmental microbes and lung microbiome in the Chinese population and provided clues for the role of smoking in the development of respiratory disease.

METHODS

Bronchoalveolar lavage fluid samples were collected from 55 individuals with a history of smoking. Microbial gene sequencing was carried out through NGS technology. We analyzed and compared the diversity, community structure, and species abundance of bronchoalveolar lavage microbiome between smokers and nonsmokers, to speculate the effects of smoking on the lung microbiome.

RESULTS

Smoking hardly affected the α diversity of microbial groups of bronchoalveolar lavage, but it had a huge influence on the microbiome composition. The relative abundance of Rothia, Actinomycetes, Haemophilus, Porphyrins, Neisseria, Acinetobacter, and Streptococcus genera had a remarkable increase in the smoking group. On the other hand, the relative abundance of Plusella and Veronella decreased significantly.

CONCLUSION

Smoking may change the environmental microbes and then alter the structure of the lung microbiome, which may lead to smoking-related diseases.

Macrophage PD-1 associates with neutrophilia and reduced bacterial killing in early cystic fibrosis airway disease

BACKGROUND

Macrophages are the major resident immune cells in human airways coordinating responses to infection and injury. In cystic fibrosis (CF), neutrophils are recruited to the airways shortly after birth, and actively exocytose damaging enzymes prior to chronic infection, suggesting a potential defect in macrophage immunomodulatory function. Signaling through the exhaustion marker programmed death protein 1 (PD-1) controls macrophage function in cancer, sepsis, and airway infection. Therefore, we sought to identify potential associations between macrophage PD-1 and markers of airway disease in children with CF.

METHODS

Blood and bronchoalveolar lavage fluid (BALF) were collected from 45 children with CF aged 3 to 62 months and structural lung damage was quantified by computed tomography. The phenotype of airway leukocytes was assessed by flow cytometry, while the release of enzymes and immunomodulatory mediators by molecular assays.

RESULTS

Airway macrophage PD-1 expression correlated positively with structural lung damage, neutrophilic inflammation, and infection. Interestingly, even in the absence of detectable infection, macrophage PD-1 expression was elevated and correlated with neutrophilic inflammation. In an in vitro model mimicking leukocyte recruitment into CF airways, soluble mediators derived from recruited neutrophils directly induced PD-1 expression on recruited monocytes/macrophages, suggesting a causal link between neutrophilic inflammation and macrophage PD-1 expression in CF. Finally, blockade of PD-1 in a short-term culture of CF BALF leukocytes resulted in improved pathogen clearance.

CONCLUSION

Taken together, these findings suggest that in early CF lung disease, PD-1 upregulation associates with airway macrophage exhaustion, neutrophil takeover, infection, and structural damage.

Sputum Bacterial Metacommunities in Distinguishing Heterogeneity in Respiratory Health and Disease

Background and Objective

Cluster-based analysis, or community typing, has been attempted as a method for studying the human microbiome in various body niches with the aim of reducing variations in the bacterial composition and linking the defined communities to host health and disease. In this study, we have presented the bacterial subcommunities in the healthy and the diseased population cohorts and have assessed whether these subcommunities can distinguish different host health conditions.

Methods

We performed community typing analysis on the sputum microbiome dataset obtained from a healthy Korean twin-family cohort (n = 202) and an external chronic obstructive pulmonary disease (COPD) cohort (n = 324) and implemented a networks analysis to investigate the associations of bacterial metacommunities with host health parameters and microbial interactions in disease.

Results

The analysis of the sputum microbiome of a healthy Korean cohort revealed high levels of interindividual variation, which was driven by two dominant bacteria: Neisseria and Prevotella. Community typing of the cohort samples identified three metacommunities, namely, Neisseria 1 (N1), Neisseria 2 (N2), and Prevotella (P), each of which showed different functional potential and links to host traits (e.g., triglyceride levels, waist circumference, and levels of high-sensitivity C-reactive protein). In particular, the Prevotella-dominant metacommunity showed a low-community diversity, which implies an adverse health association. Network analysis of the healthy twin cohort illustrated co-occurrence of Prevotella with pathogenic anaerobic bacteria; this bacterial cluster was negatively associated with high-density lipoproteins but positively correlated with waist circumference, blood pressure, and pack-years. Community typing of the external COPD cohort identified three sub-metacommunities: one exclusively comprising healthy subjects (HSs) and the other two (CS1 and CS2) comprising patients. The two COPD metacommunities, CS1 and CS2, showed different abundances of specific pathogens, such as Serratia and Moraxella, as well as differing functional potential and community diversity. Network analysis of the COPD cohort showed enhanced bacterial coexclusions in the CS metacommunities when compared with HS metacommunity.

Conclusion

Overall, our findings point to a potential association between pulmonary Prevotella and host health and disease, making it possible to implement community typing for the diagnosis of heterogenic respiratory disease.

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.

Multi-omics analyses of the ulcerative colitis gut microbiome link Bacteroides vulgatus proteases with disease severity

Ulcerative colitis (UC) is driven by disruptions in host-microbiota homoeostasis, but current treatments exclusively target host inflammatory pathways. To understand how host-microbiota interactions become disrupted in UC, we collected and analysed six faecal- or serum-based omic datasets (metaproteomic, metabolomic, metagenomic, metapeptidomic and amplicon sequencing profiles of faecal samples and proteomic profiles of serum samples) from 40 UC patients at a single inflammatory bowel disease centre, as well as various clinical, endoscopic and histologic measures of disease activity. A validation cohort of 210 samples (73 UC, 117 Crohn's disease, 20 healthy controls) was collected and analysed separately and independently. Data integration across both cohorts showed that a subset of the clinically active UC patients had an overabundance of proteases that originated from the bacterium Bacteroides vulgatus. To test whether B. vulgatus proteases contribute to UC disease activity, we first profiled B. vulgatus proteases found in patients and bacterial cultures. Use of a broad-spectrum protease inhibitor improved B. vulgatus-induced barrier dysfunction in vitro, and prevented colitis in B. vulgatus monocolonized, IL10-deficient mice. Furthermore, transplantation of faeces from UC patients with a high abundance of B. vulgatus proteases into germfree mice induced colitis dependent on protease activity. These results, stemming from a multi-omics approach, improve understanding of functional microbiota alterations that drive UC and provide a resource for identifying other pathways that could be inhibited as a strategy to treat this disease.

Potential Association Between Changes in Microbiota Level and Lung Diseases: A Meta-Analysis

Objective:

Lung microbiota is increasingly implicated in multiple types of respiratory diseases. However, no study has drawn a consistent conclusion regarding the relationship between changes in the microbial community and lung diseases. This study verifies the association between microbiota level and lung diseases by performing a meta-analysis.

Methods:

Literature databases, including PubMed, ISI Web of Science, Embase, Google Scholar, PMC, and CNKI, were used to collect related articles published before March 20, 2021. The standard mean deviation (SMD) and related 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup, sensitivity, and publication bias analyses were also conducted.

Results:

Six studies, comprising 695 patients with lung diseases and 176 healthy individuals, were included in this meta-analysis. The results indicated that the microbiota level was higher in patients with lung diseases than in healthy individuals (SMD = 0.39, 95% CI = 0.22–0.55, I² = 91.5%, P < 0.01). Subgroup analysis based on country demonstrated that the microbiota level was significantly higher in Chinese (SMD = 1.90, 95% CI = 0.87–2.93, I² = 62.3%, P < 0.01) and Korean (SMD = 0.24, 95% CI = 0.13–0.35, I² = 78.7%, P < 0.01) patients with lung diseases. The microbiota level of patients with idiopathic pulmonary fibrosis (IPF) (SMD = 1.40, 95% CI = 0.42–2.38, I² = 97.3%, P = 0.005), chronic obstructive pulmonary disease (COPD) (SMD = 0.30, 95% CI = 0.09–0.50, I² = 83.9%, P = 0.004), and asthma (SMD = 0.19, 95% CI = 0.06–0.32, I² = 69.4%, P = 0.004) were significantly higher than those of the healthy group, whereas a lower microbiota level was found in patients with chronic hypersensitivity pneumonitis (CHP). The microbiota level significantly increased when the disease sample size was >50. Subgroup analysis based on different microbiota genera, indicated that Acinetobacter baumannii and Pseudomonas aeruginosa were significantly increased in COPD and asthma diseases.

Conclusion:

We observed that patients with IPF, COPD, and asthma had a higher microbiota level, whereas patients with CHP had a lower microbiota level compared to the healthy individuals. The level of A. baumannii and P. aeruginosa were significantly higher in patients with COPD and asthma, and thus represented as potential microbiota markers in the diagnosis and treatment of lung diseases.

Single-cell RNA Seq reveals cellular landscape-specific characteristics and potential etiologies for adolescent idiopathic scoliosis

BACKGROUNDS

Abnormal vertebral growth and development have been found in adolescent idiopathic scoliosis (AIS) patients, and the proliferation and differentiation of bone development-related cells play important roles in its pathogenesis. However, a comprehensive single-cell-level differentiation roadmap in AIS has not been achieved.

METHODS

The present study compared the single-cell level cellular landscapes of spinal cancellous bone tissues between AIS patients and healthy subjects using high throughput single-cell RNA sequencing (scRNA-seq), which covers multiple cellular lineages including osteoblast, chondrocyte, osteoclast and related immunocytes. We constructed the differentiation trajectories of bone development-related cell lineages through pseudotime analysis, and the intercellular-communication networks between bone development-related cells and immunocytes were further developed.

RESULTS

A total of 11 distinct cell clusters were identified according to the genome-wide transcriptome profiles. t-Distributed stochastic neighbor embedding (t-SNE) analysis showed that mesenchymal stem cells (MSC) were classified into three subtypes: MSC-LOXL2, MSC-IGFBP5, and MSC-GJA1. Gene ontology (GO) analysis showed that MSC-GJA1 might possess greater osteoblast differentiation potential than the others. MSC-IGFBP5 was the specific MSC subtype observed only in AIS. There were two distinct gene expression clusters: OB-DPT and OB-OLFML2B, and the counts of osteoblasts derived from AIS was significantly less than that of non-AIS subjects. In AIS patients, MSC-IGFBP5 failed to differentiate into osteoblasts and exhibited negative regulation of cell proliferation and enhanced cell death. CPC-PCNA was found to be the specific chondrocyte progenitor cell (CPC) subtype observed only in AIS patients. The cell counts of OC-BIRC3 in AIS were less than those in controls. Pseudotime analysis suggested two possible distinct osteoclast differentiation patterns in AIS and control subjects. Monocytes in AIS mainly differentiated into OC-CRISP3.

CONCLUSIONS

Our single-cell analysis first revealed differences existed in the cellular states between AIS patients and healthy subjects and found the differentiation disruption of specific MSC and CPC clusters in AIS. Cell communication analysis provided the possible pathogenesis of osteoblast and chondrocyte differentiation dysfunction in AIS.

The cystic fibrosis lung microenvironment alters antibiotic activity: causes and effects

Chronic airway colonisation by Pseudomonas aeruginosa, a hallmark of cystic fibrosis (CF) lung disease, is associated with increased morbidity and mortality and despite aggressive antibiotic treatment, P. aeruginosa is able to persist in CF airways. In vitro antibiotic susceptibility assays are poor predictors of antibiotic efficacy to treat respiratory tract infections in the CF patient population and the selection of the antibiotic(s) is often made on an empirical base. In the current review, we discuss the factors that are responsible for the discrepancies between antibiotic activity in vitro and clinical efficacy in vivo We describe how the CF lung microenvironment, shaped by host factors (such as iron, mucus, immune mediators and oxygen availability) and the microbiota, influences antibiotic activity and varies widely between patients. A better understanding of the CF microenvironment and population diversity may thus help improve in vitro antibiotic susceptibility testing and clinical decision making, in turn increasing the success rate of antibiotic treatment.

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.

The Sputum Microbiome in Pulmonary Tuberculosis and Its Association With Disease Manifestations: A Cross-Sectional Study

Each day, approximately 27,000 people become ill with tuberculosis (TB), and 4,000 die from this disease. Pulmonary TB is the main clinical form of TB, and affects the lungs with a considerably heterogeneous manifestation among patients. Immunomodulation by an interplay of host-, environment-, and pathogen-associated factors partially explains such heterogeneity. Microbial communities residing in the host's airways have immunomodulatory effects, but it is unclear if the inter-individual variability of these microbial communities is associated with the heterogeneity of pulmonary TB. Here, we investigated this possibility by characterizing the microbial composition in the sputum of 334 TB patients from Tanzania, and by assessing its association with three aspects of disease manifestations: sputum mycobacterial load, severe clinical findings, and chest x-ray (CXR) findings. Compositional data analysis of taxonomic profiles based on 16S-rRNA gene amplicon sequencing and on whole metagenome shotgun sequencing, and graph-based inference of microbial associations revealed that the airway microbiome of TB patients was shaped by inverse relationships between Streptococcus and two anaerobes: Selenomonas and Fusobacterium. Specifically, the strength of these microbial associations was negatively correlated with Faith's phylogenetic diversity (PD) and with the accumulation of transient genera. Furthermore, low body mass index (BMI) determined the association between abnormal CXRs and community diversity and composition. These associations were mediated by increased abundance of Selenomonas and Fusobacterium, relative to the abundance of Streptococcus, in underweight patients with lung parenchymal infiltrates and in comparison to those with normal chest x-rays. And last, the detection of herpesviruses and anelloviruses in sputum microbial assemblage was linked to co-infection with HIV. Given the anaerobic metabolism of Selenomonas and Fusobacterium, and the hypoxic environment of lung infiltrates, our results suggest that in underweight TB patients, lung tissue remodeling toward anaerobic conditions favors the growth of Selenomonas and Fusobacterium at the expense of Streptococcus. These new insights into the interplay among particular members of the airway microbiome, BMI, and lung parenchymal lesions in TB patients, add a new dimension to the long-known association between low BMI and pulmonary TB. Our results also drive attention to the airways virome in the context of HIV-TB coinfection.

Current and Emerging Therapies to Combat Cystic Fibrosis Lung Infections

The ultimate aim of any antimicrobial treatment is a better infection outcome for the patient. Here, we review the current state of treatment for bacterial infections in cystic fibrosis (CF) lung while also investigating potential new treatments being developed to see how they may change the dynamics of antimicrobial therapy. Treatment with antibiotics coupled with regular physical therapy has been shown to reduce exacerbations and may eradicate some strains. Therapies such as hypertonic saline and inhaled PulmozymeTM (DNase-I) improve mucus clearance, while modifier drugs, singly and more successfully in combination, re-open certain mutant forms of the cystic fibrosis transmembrane conductance regulator (CFTR) to enable ion passage. No current method, however, completely eradicates infection, mainly due to bacterial survival within biofilm aggregates. Lung transplants increase lifespan, but reinfection is a continuing problem. CFTR modifiers normalise ion transport for the affected mutations, but there is conflicting evidence on bacterial clearance. Emerging treatments combine antibiotics with novel compounds including quorum-sensing inhibitors, antioxidants, and enzymes, or with bacteriophages, aiming to disrupt the biofilm matrix and improve antibiotic access. Other treatments involve bacteriophages that target, infect and kill bacteria. These novel therapeutic approaches are showing good promise in vitro, and a few have made the leap to in vivo testing.

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.

Sweat metabolome and proteome: Recent trends in analytical advances and potential biological functions

Metabolome and proteome profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, omics analyses of sweat, one of the most readily available human biofluids, have lagged behind. This review capitalizes on the current knowledge and state of the art analytical advances of sweat metabolomics and proteomics. Moreover, current applications of sweat omics such as the discovery of disease biomarkers and monitoring athletic performance are also presented in this review. Another area of emerging knowledge that has been highlighted herein lies in the role of skin host-microbiome interactions in shaping the sweat metabolite-protein profiles. Discussion of future research directions describes the need to have a better grasp of sweat chemicals and to better understand how they function as aided by advances in omics tools. Overall, the role of sweat as an information-rich biofluid that could complement the exploration of the skin metabolome/proteome is emphasized.

Response of the critically endangered Przewalski's gazelle (Procapra przewalskii) to selenium deprived environment

Selenium (Se) is an essential mineral nutrient for animals. Se deprivation can lead to many disorders and even death. This study investigated the response of Przewalski's gazelle (P. przewalskii) to Se-deprived environment. We found that Se deprivation in soil and forage not only influenced the mineral contents of the blood and hair in P. przewalskii, but also severely disrupted their blood parameters. We identified significant changes in the abundance of 146 proteins and 25 metabolites (P < 0.05) in serum, including the selenoproteins L8IG93 (glutathione peroxidase) and F4YD09 (Cu/Zn superoxide dismutase). Furthermore, the major known proteins and metabolites associated with the Se stress response in P. przewalskii were Cu/Zn superoxide dismutase, the vitamin K-dependent protein C, the C4b-binding protein alpha chain, complement component C7, lipase linoleic acid, peptidase D, thymidine, pseudo-uridine, L-phenylalanine, L-glutamine, PGA1, and 15-deoxy-delta-12,14-PGJ2. The main signaling pathways involved included complement and coagulation cascades, metabolic pathways, and stress granule formation. Our results indicate that the intake of Se-deficient forage elicited an oxidative stress response in P. przewalskii. These findings provide insights into the response mechanisms of this threatened gazelle to Se stress, and enable the development of conservation strategies to protect populations on the Qinghai-Tibetan Plateau. SIGNIFICANCE: This study is the first to point out the presence of oxidative stress in P. przewalskii in selenium-deficient areas through proteomics and metabolomics studies. These findings should prove helpful for conservation efforts aimed at P. przewalskii populations and maintenance of the integrity of their ecological environment.

Pseudomonas aeruginosa: An Audacious Pathogen with an Adaptable Arsenal of Virulence Factors

Pseudomonas aeruginosa is a dominant pathogen in people with cystic fibrosis (CF) contributing to morbidity and mortality. Its tremendous ability to adapt greatly facilitates its capacity to cause chronic infections. The adaptability and flexibility of the pathogen are afforded by the extensive number of virulence factors it has at its disposal, providing P. aeruginosa with the facility to tailor its response against the different stressors in the environment. A deep understanding of these virulence mechanisms is crucial for the design of therapeutic strategies and vaccines against this multi-resistant pathogen. Therefore, this review describes the main virulence factors of P. aeruginosa and the adaptations it undergoes to persist in hostile environments such as the CF respiratory tract. The very large P. aeruginosa genome (5 to 7 MB) contributes considerably to its adaptive capacity; consequently, genomic studies have provided significant insights into elucidating P. aeruginosa evolution and its interactions with the host throughout the course of infection.

Metabotypes of Pseudomonas aeruginosa Correlate with Antibiotic Resistance, Virulence and Clinical Outcome in Cystic Fibrosis Chronic Infections

Pseudomonas aeruginosa (P.a) is one of the most critical antibiotic resistant bacteria in the world and is the most prevalent pathogen in cystic fibrosis (CF), causing chronic lung infections that are considered one of the major causes of mortality in CF patients. Although several studies have contributed to understanding P.a within-host adaptive evolution at a genomic level, it is still difficult to establish direct relationships between the observed mutations, expression of clinically relevant phenotypes, and clinical outcomes. Here, we performed a comparative untargeted LC/HRMS-based metabolomics analysis of sequential isolates from chronically infected CF patients to obtain a functional view of P.a adaptation. Metabolic profiles were integrated with expression of bacterial phenotypes and clinical measurements following multiscale analysis methods. Our results highlighted significant associations between P.a “metabotypes”, expression of antibiotic resistance and virulence phenotypes, and frequency of clinical exacerbations, thus identifying promising biomarkers and therapeutic targets for difficult-to-treat P.a infections

Therapeutic peptides for the treatment of cystic fibrosis: Challenges and perspectives

Cystic fibrosis (CF) is the most common amongst rare genetic diseases, affecting more than 70.000 people worldwide. CF is characterized by a dysfunctional chloride channel, termed cystic fibrosis conductance regulator (CFTR), which leads to the production of a thick and viscous mucus layer that clogs the lungs of CF patients and traps pathogens, leading to chronic infections and inflammation and, ultimately, lung damage. In recent years, the use of peptides for the treatment of respiratory diseases, including CF, has gained growing interest. Therapeutic peptides for CF include antimicrobial peptides, inhibitors of proteases, and modulators of ion channels, among others. Peptides display unique features that make them appealing candidates for clinical translation, like specificity of action, high efficacy, and low toxicity. Nevertheless, the intrinsic properties of peptides, together with the need of delivering these compounds locally, e.g. by inhalation, raise a number of concerns in the development of peptide therapeutics for CF lung disease. In this review, we discuss the challenges related to the use of peptides for the treatment of CF lung disease through inhalation, which include retention within mucus, proteolysis, immunogenicity and aggregation. Strategies for overcoming major shortcomings of peptide therapeutics will be presented, together with recent developments in peptide design and optimization, including computational analysis and high-throughput screening.

Relationship between airway dysbiosis, inflammation and lung function in adults with cystic fibrosis

Airway dysbiosis has been associated with lung disease severity in patients with cystic fibrosis (CF). However, the relationship between dysbiosis, airway inflammation and lung function impairement remains poorly understood. The aim of this study was therefore to determine how the structure of the sputum microbiota, airway inflammation markers and spirometry are related in patients with CF. Sputum samples were collected from 106 CF patients between 12 and 72 years. These were analyzed by 16S rRNA gene amplicon sequencing. Moreover, levels of pro-inflammatory cytokines (IL-1β, IL-8, IL-6 and TNF-α) and Neutrophil elastase (NE) were determined. The relationship between the microbiota, inflammation markers and forced expiratory volume in one second percent predicted (FEV₁% predicted) was evaluated by multi-parameter analysis. The microbiota α-diversity correlated inverse with inflammation markers IL-1β, IL-8, TNF-α, NE and positively with FEV₁% predicted. Patients could be divided into 7 clusters based on their microbiota structure. The most diverse cluster was defined by oropharyngeal-like flora (OF) while the others were characterized by the dominance of a single pathogen. Patients with the diverse OF microbiota cluster had lower sputum inflammatory markers and higher FEV₁% predicted compared to patients with a pathogen-dominated microbiota including Pseudomonas aeruginosa. Our results suggest that the diversity of the airway microbiota is an important biomarker of the severity of airway inflammation linking dysbiosis to lung function decline in patients with CF.

The Lung Microbiome of Three Young Brazilian Patients With Cystic Fibrosis Colonized by Fungi

Microbial communities infiltrate the respiratory tract of cystic fibrosis patients, where chronic colonization and infection lead to clinical decline. This report aims to provide an overview of the diversity of bacterial and fungal species from the airway secretion of three young CF patients with severe pulmonary disease. The bacterial and fungal microbiomes were investigated by culture isolation, metataxonomics, and metagenomics shotgun. Virulence factors and antibiotic resistance genes were also explored. A. fumigatus was isolated from cultures and identified in high incidence from patient sputum samples. Candida albicans, Penicillium sp., Hanseniaspora sp., Torulaspora delbrueckii, and Talaromyces amestolkiae were isolated sporadically. Metataxonomics and metagenomics detected fungal reads (Saccharomyces cerevisiae, A. fumigatus, and Schizophyllum sp.) in one sputum sample. The main pathogenic bacteria identified were Staphylococcus aureus, Pseudomonas aeruginosa, Burkholderia cepacia complex, and Achromobacter xylosoxidans. The canonical core CF microbiome is composed of species from the genera Streptococcus, Neisseria, Rothia, Prevotella, and Haemophilus. Thus, the airways of the three young CF patients presented dominant bacterial genera and interindividual variability in microbial community composition and diversity. Additionally, a wide diversity of virulence factors and antibiotic resistance genes were identified in the CF lung microbiomes, which may be linked to the clinical condition of the CF patients. Understanding the microbial community is crucial to improve therapy because it may have the opposite effect, restructuring the pathogenic microbiota. Future studies focusing on the influence of fungi on bacterial diversity and microbial interactions in CF microbiomes will be welcome to fulfill this huge gap of fungal influence on CF physiopathology.

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.

Dysregulated signalling pathways in innate immune cells with cystic fibrosis mutations

Cystic fibrosis (CF) is one of the most common life-limiting recessive genetic disorders in Caucasians, caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR). CF is a multi-organ disease that involves the lungs, pancreas, sweat glands, digestive and reproductive systems and several other tissues. This debilitating condition is associated with recurrent lower respiratory tract bacterial and viral infections, as well as inflammatory complications that may eventually lead to pulmonary failure. Immune cells play a crucial role in protecting the organs against opportunistic infections and also in the regulation of tissue homeostasis. Innate immune cells are generally affected by CFTR mutations in patients with CF, leading to dysregulation of several cellular signalling pathways that are in continuous use by these cells to elicit a proper immune response. There is substantial evidence to show that airway epithelial cells, neutrophils, monocytes and macrophages all contribute to the pathogenesis of CF, underlying the importance of the CFTR in innate immune responses. The goal of this review is to put into context the important role of the CFTR in different innate immune cells and how CFTR dysfunction contributes to the pathogenesis of CF, highlighting several signalling pathways that may be dysregulated in cells with CFTR mutations.

Host-microbe cross-talk in the lung microenvironment: implications for understanding and treating chronic lung disease

Chronic respiratory diseases are highly prevalent worldwide and will continue to rise in the foreseeable future. Despite intensive efforts over recent decades, the development of novel and effective therapeutic approaches has been slow. However, there is new and increasing evidence that communities of micro-organisms in our body, the human microbiome, are crucially involved in the development and progression of chronic respiratory diseases. Understanding the detailed mechanisms underlying this cross-talk between host and microbiota is critical for development of microbiome- or host-targeted therapeutics and prevention strategies. Here we review and discuss the most recent knowledge on the continuous reciprocal interaction between the host and microbes in health and respiratory disease. Furthermore, we highlight promising developments in microbiome-based therapies and discuss the need to employ more holistic approaches of restoring both the pulmonary niche and the microbial community.

The reciprocal interaction between microbes and host in the lung is increasingly recognised as an important determinant of health. The complexity of this cross-talk needs to be taken into account when studying diseases and developing future new therapies.https://bit.ly/2VKYUfT

Lung Microbiome Participation in Local Immune Response Regulation in Respiratory Diseases

The lung microbiome composition has critical implications in the regulation of innate and adaptive immune responses. Next-generation sequencing techniques have revolutionized the understanding of pulmonary physiology and pathology. Currently, it is clear that the lung is not a sterile place; therefore, the investigation of the participation of the pulmonary microbiome in the presentation, severity, and prognosis of multiple pathologies, such as asthma, chronic obstructive pulmonary disease, and interstitial lung diseases, contributes to a better understanding of the pathophysiology. Dysregulation of microbiota components in the microbiome-host interaction is associated with multiple lung pathologies, severity, and prognosis, making microbiome study a useful tool for the identification of potential therapeutic strategies. This review integrates the findings regarding the activation and regulation of the innate and adaptive immune response pathways according to the microbiome, including microbial patterns that could be characteristic of certain diseases. Further studies are required to verify whether the microbial profile and its metabolites can be used as biomarkers of disease progression or poor prognosis and to identify new therapeutic targets that restore lung dysbiosis safely and effectively.

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.

Giant magnetoresistive biosensors for real-time quantitative detection of protease activity

Proteases are enzymes that cleave proteins and are crucial to physiological processes such as digestion, blood clotting, and wound healing. Unregulated protease activity is a biomarker of several human diseases. Synthetic peptides that are selectively hydrolyzed by a protease of interest can be used as reporter substrates of unregulated protease activity. We developed an activity-based protease sensor by immobilizing magnetic nanoparticles (MNPs) to the surface of a giant magnetoresistive spin-valve (GMR SV) sensor using peptides. Cleavage of these peptides by a protease releases the magnetic nanoparticles resulting in a time-dependent change in the local magnetic field. Using this approach, we detected a significant release of MNPs after 3.5 minutes incubation using just 4 nM of the cysteine protease, papain. In addition, we show that proteases in healthy human urine do not release the MNPs, however addition of 20 nM of papain to the urine samples resulted in a time-dependent change in magnetoresistance. This study lays the foundation for using GMR SV sensors as a platform for real-time, quantitative detection of protease activity in biological fluids.

Interplay between host-microbe and microbe-microbe interactions in cystic fibrosis

The respiratory tract of individuals with cystic fibrosis is host to polymicrobial infections that persist for decades and lead to significant morbidity and mortality. Improving our understanding of CF respiratory infections requires coordinated efforts from researchers in the fields of microbial physiology, genomics, and ecology, as well as epithelial biology and immunology. Here, we have highlighted examples from recent CF microbial pathogenesis literature of how the host nutritional environment, immune response, and microbe-microbe interactions can feedback onto each other, leading to diverse effects on lung disease pathogenesis in CF.

The Signature Microbiota Drive Rumen Function Shifts in Goat Kids Introduced to Solid Diet Regimes

The feeding regime of early, supplementary solid diet improved rumen development and production in goat kids. However, the signature microbiota responsible for linking dietary regimes to rumen function shifts are still unclear. This work analyzed the rumen microbiome and functions affected by an early solid diet regime using a combination of machine learning algorithms. Volatile fatty acids (i.e., acetate, propionate and butyrate) fermented by microbes were found to increase significantly in the supplementary solid diet groups. Predominant genera were found to alter significantly from unclassified Sphingobacteriaceae (non-supplementary group) to Prevotella (supplementary solid diet groups). Random Forest classification model revealed signature microbiota for solid diet that positively correlated with macronutrient intake, and linearly increased with volatile fatty acid production. Bacteria associated with carbohydrate and protein metabolism were also identified. Utilization of a Fish Taco analysis portrayed a set of intersecting core species contributed to rumen function shifts by the solid diet regime. The core community structures consisted of the specific, signature microbiota and the manipulation of their symbiotic partners are manipulated by extra nutrients from concentrate and/or forage, and then produce more volatile fatty acids to promote rumen development and functions eventually host development. Our study provides mechanisms of the microbiome governed by a solid diet regime early in life, and highlights the signature microbiota involved in animal health and production.