Tracking Polymicrobial Metabolism in Cystic Fibrosis Airways: Pseudomonas aeruginosa Metabolism and Physiology Are Influenced by Rothia mucilaginosa-Derived Metabolites

Multi-View Integrative Approach For Imputing Short-Chain Fatty Acids and Identifying Key factors predicting Blood SCFA

Short-chain fatty acids (SCFAs) are the main metabolites produced by bacterial fermentation of dietary fiber within gastrointestinal tract. SCFAs produced by gut microbiotas (GMs) are absorbed by host, reach bloodstream, and are distributed to different organs, thus influencing host physiology. However, due to the limited budget or the poor sensitivity of instruments, most studies on GMs have incomplete blood SCFA data, limiting our understanding of the metabolic processes within the host. To address this gap, we developed an innovative multi-task multi-view integrative approach (M2AE, Multi-task Multi-View Attentive Encoders), to impute blood SCFA levels using gut metagenomic sequencing (MGS) data, while taking into account the intricate interplay among the gut microbiome, dietary features, and host characteristics, as well as the nuanced nature of SCFA dynamics within the body. Here, each view represents a distinct type of data input (i.e., gut microbiome compositions, dietary features, or host characteristics). Our method jointly explores both view-specific representations and cross-view correlations for effective predictions of SCFAs. We applied M2AE to two in-house datasets, which both include MGS and blood SCFAs profiles, host characteristics, and dietary features from 964 subjects and 171 subjects, respectively. Results from both of two datasets demonstrated that M2AE outperforms traditional regression-based and neural-network based approaches in imputing blood SCFAs. Furthermore, a series of gut bacterial species (e.g., Bacteroides thetaiotaomicron and Clostridium asparagiforme), host characteristics (e.g., race, gender), as well as dietary features (e.g., intake of fruits, pickles) were shown to contribute greatly to imputation of blood SCFAs. These findings demonstrated that GMs, dietary features and host characteristics might contribute to the complex biological processes involved in blood SCFA productions. These might pave the way for a deeper and more nuanced comprehension of how these factors impact human health.

Antibiotic resistance alters the ability of Pseudomonas aeruginosa to invade bacteria from the respiratory microbiome

The emergence and spread of antibiotic resistance in bacterial pathogens is a global health threat. One important unanswered question is how antibiotic resistance influences the ability of a pathogen to invade the host-associated microbiome. Here we investigate how antibiotic resistance impacts the ability of a bacterial pathogen to invade bacteria from the microbiome, using the opportunistic bacterial pathogen Pseudomonas aeruginosa and the respiratory microbiome as our model system. We measure the ability of P. aeruginosa spontaneous antibiotic-resistant mutants to invade pre-established cultures of commensal respiratory microbes in an assay that allows us to link specific resistance mutations with changes in invasion ability. While commensal respiratory microbes tend to provide some degree of resistance to P. aeruginosa invasion, antibiotic resistance is a double-edged sword that can either help or hinder the ability of P. aeruginosa to invade. The directionality of this help or hindrance depends on both P. aeruginosa genotype and respiratory microbe identity. Specific resistance mutations in genes involved in multidrug efflux pump regulation are shown to facilitate the invasion of P. aeruginosa into Staphylococcus lugdunensis, yet impair invasion into Rothia mucilaginosa and Staphylococcus epidermidis. Streptococcus species provide the strongest resistance to P. aeruginosa invasion, and this is maintained regardless of antibiotic resistance genotype. Our study demonstrates how the cost of mutations that provide enhanced antibiotic resistance in P. aeruginosa can crucially depend on community context. We suggest that attempts to manipulate the microbiome should focus on promoting the growth of commensals that can increase the fitness costs associated with antibiotic resistance and provide robust inhibition of both wildtype and antibiotic-resistant pathogen strains.

Genome-scale model of Rothia mucilaginosa predicts gene essentialities and reveals metabolic capabilities

Cystic fibrosis (CF), an inherited genetic disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator gene, results in sticky and thick mucosal fluids. This environment facilitates the colonization of various microorganisms, some of which can cause acute and chronic lung infections, while others may positively impact the disease. Rothia mucilaginosa, an oral commensal, is relatively abundant in the lungs of CF patients. Recent studies have unveiled its anti-inflammatory properties using in vitro three-dimensional lung epithelial cell cultures and in vivo mouse models relevant to chronic lung diseases. Apart from this, R. mucilaginosa has been associated with severe infections. However, its metabolic capabilities and genotype-phenotype relationships remain largely unknown. To gain insights into its cellular metabolism and genetic content, we developed the first manually curated genome-scale metabolic model, iRM23NL. Through growth kinetics and high-throughput phenotypic microarray testings, we defined its complete catabolic phenome. Subsequently, we assessed the model's effectiveness in accurately predicting growth behaviors and utilizing multiple substrates. We used constraint-based modeling techniques to formulate novel hypotheses that could expedite the development of antimicrobial strategies. More specifically, we detected putative essential genes and assessed their effect on metabolism under varying nutritional conditions. These predictions could offer novel potential antimicrobial targets without laborious large-scale screening of knockouts and mutant transposon libraries. Overall, iRM23NL demonstrates a solid capability to predict cellular phenotypes and holds immense potential as a valuable resource for accurate predictions in advancing antimicrobial therapies. Moreover, it can guide metabolic engineering to tailor R. mucilaginosa's metabolism for desired performance.IMPORTANCECystic fibrosis (CF) is a genetic disorder characterized by thick mucosal secretions, leading to chronic lung infections. Rothia mucilaginosa is a common bacterium found in various parts of the human body, acting as a normal part of the flora. In people with weakened immune systems, it can become an opportunistic pathogen, while it is prevalent and active in CF airways. Recent studies have highlighted its anti-inflammatory properties in the lower pulmonary system, indicating the intricate relationship between microbes and human health. Herein, we have developed the first manually curated metabolic model of R. mucilaginosa. Our study examined the previously unknown relationships between the bacterium's genotype and phenotype and identified essential genes that impact the metabolism under various conditions. With this, we opt for paving the way for developing new strategies in antimicrobial therapy and metabolic engineering, leading to enhanced therapeutic outcomes in cystic fibrosis and related conditions.

A Critical Review on the Role of Probiotics in Lung Cancer Biology and Prognosis

Lung cancer remains the leading cause of cancer-related deaths worldwide. According to the American Cancer Society (ACS), it ranks as the second most prevalent type of cancer globally. Recent findings have highlighted bidirectional gut-lung interactions, known as the gut-lung axis, in the pathophysiology of lung cancer. Probiotics are live microorganisms that boost host immunity when consumed adequately. The immunoregulatory mechanisms of probiotics are thought to operate through the generation of various metabolites that impact both the gut and distant organs (e.g., the lungs) through blood. Several randomized controlled trials have highlighted the pivotal role of probiotics in gut health especially for the prevention and treatment of malignancies, with a specific emphasis on lung cancer. Current research indicates that probiotic supplementation positively affects patients, leading to a suppression in cancer symptoms and a shortened disease course. While clinical trials validate the therapeutic benefits of probiotics, their precise mechanism of action remains unclear. This narrative review aims to provide a comprehensive overview of the present landscape of probiotics in the management of lung cancer.

Insights into the Adolescent Cystic Fibrosis Airway Microbiome Using Shotgun Metagenomics

Cystic fibrosis (CF) is an inherited genetic disorder which manifests primarily in airway disease. Recent advances in molecular technologies have unearthed the diverse polymicrobial nature of the CF airway. Numerous studies have characterised the genus-level composition of this airway community using targeted 16S rDNA sequencing. Here, we employed whole-genome shotgun metagenomics to provide a more comprehensive understanding of the early CF airway microbiome. We collected 48 sputum samples from 11 adolescents and children with CF over a 12-month period and performed shotgun metagenomics on the Illumina NextSeq platform. We carried out functional and taxonomic analysis of the lung microbiome at the species and strain levels. Correlations between microbial diversity measures and independent demographic and clinical variables were performed. Shotgun metagenomics detected a greater diversity of bacteria than culture-based methods. A large proportion of the top 25 most-dominant species were anaerobes. Samples dominated by Staphylococcus aureus and Prevotella melaninogenica had significantly higher microbiome diversity, while no CF pathogen was associated with reduced microbial diversity. There was a diverse resistome present in all samples in this study, with 57.8% agreement between shotgun metagenomics and culture-based methods for detection of resistance. Pathogenic sequence types (STs) of S. aureus, Pseudomonas aeruginosa, Haemophilus influenzae and Stenotrophomonas maltophilia were observed to persist in young CF patients, while STs of S. aureus were both persistent and shared between patients. This study provides new insight into the temporal changes in strain level composition of the microbiome and the landscape of the resistome in young people with CF. Shotgun metagenomics could provide a very useful one-stop assay for detecting pathogens, emergence of resistance and conversion to persistent colonisation in early CF disease.

New Phage-Derived Antibacterial Enzyme PolaR Targeting Rothia spp

Rothia is an opportunistic pathogen, particularly life-threatening for the immunocompromised. It is associated with pneumonia, endocarditis, peritonitis and many other serious infections, including septicemia. Of note, Rothia mucilaginousa produces metabolites that support and increase overgrowth of Pseudomonas aeruginosa, one of the ESKAPE bacteria. Endolysins are considered as antibacterial enzymes derived from bacteriophages that selectively and efficiently kill susceptible bacteria without harming human cells or the normal microbiome. Here, we applied a computational analysis of metagenomic sequencing data of the gastric mucosa phageome extracted from human patients' stomach biopsies. A selected candidate anti-Rothia sequence was produced in an expression system, purified and confirmed as a Rothia mucilaginosa- and Rothia dentocariosa-specific endolysin PolaR, able to destroy bacterial cells even when aggregated, as in a biofilm. PolaR had no cytotoxic or antiproliferative effects on mammalian cells. PolaR is the first described endolysin selectively targeting Rothia species, with a high potential to combat infections caused by Rothia mucilaginosa and Rothia dentocariosa, and possibly other bacterial groups. PolaR is the first antibacterial enzyme selected from the gastric mucosa phageome, which underlines the biological complexity and probably underestimated biological role of the phageome in the human gastric mucosa.

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

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

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.

Impact of Cesarean Delivery and Breastfeeding on Secretory Immunoglobulin A in the Infant Gut Is Mediated by Gut Microbiota and Metabolites

How gut immunity in early life is shaped by birth in relation to delivery mode, intrapartum antibiotic prophylaxis (IAP) and labor remains undetermined. We aimed to address this gap with a study of secretory Immunoglobulin A (SIgA) in the infant gut that also tested SIgA-stimulating pathways mediated by gut microbiota and metabolites. Among 1017 Canadian full-term infants, gut microbiota of fecal samples collected at 3 and 12 months were profiled using 16S rRNA sequencing; C. difficile was quantified by qPCR; fecal metabolites and SIgA levels were measured by NMR and SIgA enzyme-linked immunosorbent assay, respectively. We assessed the putative causal relationships from birth events to gut microbiota and metabolites, and ultimately to SIgA, in statistical sequential mediation models, adjusted for maternal gravida status in 551 infants. As birth mode influences the ability to breastfeed, the statistical mediating role of breastfeeding status and milk metabolites was also evaluated. Relative to vaginal birth without maternal IAP, cesarean section (CS) after labor was associated with reduced infant gut SIgA levels at 3 months (6.27 vs. 4.85 mg/g feces, p < 0.05); this association was sequentially mediated through gut microbiota and metabolites of microbial or milk origin. Mediating gut microbiota included Enterobacteriaceae, C. difficile, and Streptococcus. The milk or microbial metabolites in CS-SIgA mediating pathways were galactose, fucose, GABA, choline, lactate, pyruvate and 1,2-propanediol. This cohort study documented the impact of birth on infant gut mucosal SIgA. It is the first to characterize gut microbe-metabolite mediated pathways for early-life SIgA maturation, pathways that require experimental verification.

Characterizing microbiota and metabolomics analysis to identify candidate biomarkers in lung cancer

Background

Lung cancer is the leading malignant disease and cause of cancer-related death worldwide. Most patients with lung cancer had insignificant early symptoms so that most of them were diagnosed at an advanced stage. In addition to factors such as smoking, pollution, lung microbiome and its metabolites play vital roles in the development of lung cancer. However, the interaction between lung microbiota and carcinogenesis is lack of systematically characterized and controversial. Therefore, the purpose of this study was to excavate the features of the lung microbiota and metabolites in patients and verify potential biomarkers for lung cancer diagnosis.

Methods

Lung tissue flushing solutions and bronchoalveolar lavage fluid samples came from patients with lung cancer and non-lung cancer. The composition and variations of the microbiota and metabolites in samples were explored using muti-omics technologies including 16S rRNA amplicon sequencing, metagenomics and metabolomics.

Results

The metabolomics analysis indicated that 40 different metabolites, such as 9,10-DHOME, sphingosine, and cysteinyl-valine, were statistically significant between two groups (VIP > 1 and P < 0.05). These metabolites were significantly enriched into 11 signal pathways including sphingolipid, autophagy and apoptosis signaling pathway (P < 0.05). The analysis of lung microbiota showed that significant changes reflected the decrease of microbial diversity, changes of distribution of microbial taxa, and variability of the correlation networks of lung microbiota in lung cancer patients. In particular, we found that oral commensal microbiota and multiple probiotics might be connected with the occurrence and progression of lung cancer. Moreover, our study found 3 metabolites and 9 species with significantly differences, which might be regarded as the potential clinical diagnostic markers associated with lung cancer.

Conclusions

Lung microbiota and metabolites might play important roles in the pathogenesis of lung cancer, and the altered metabolites and microbiota might have the potential to be clinical diagnostic markers and therapeutic targets associated with lung cancer.

The Function and Molecular Mechanism of Commensal Microbiome in Promoting Malignant Progression of Lung Cancer

The human commensal microbiome existing in an internal environment is relatively consistent with that of the host. The presence of bacterial dysbiosis, on the other hand, promptly results in the termination of this symbiotic association. The altered microbial structure in the lung may be responsible for the development of lung cancer by controlling the host's inflammatory response and influencing a variety of immunological pathways. More and more studies have pointed to the fact that the commensal microbiota plays a vital role in both the development of tumors and the body's response to lung cancer treatment. Microbiome dysbiosis, genotoxicity, virulence effect, and epigenetic dysregulations are some of the potential mechanisms that may lie behind the process of tumorigenesis that is mediated by microbiome. Other potential mechanisms include regulating host immune activity through a variety of pathogenic factors, dysregulating host metabolism as a result of microbiome alterations, and microbiome dysbiosis. In this historical overview, we go through some of the more recent mechanistic discoveries into the biological processes that are involved in lung cancer that are caused by bacteria. Without a question, obtaining a greater knowledge of the dynamic link between the lung microbiome and lung cancer has the potential to inspire the development of innovative early detection and customized treatment methods for lung cancer.

Antimicrobial Biosynthetic Potential and Phylogenetic Analysis of Culturable Bacteria Associated with the Sponge Ophlitaspongia sp. from the Yellow Sea, China

Sponge-derived bacteria are considered to be a promising source of novel drugs, owing to their abundant secondary metabolites that have diverse biological activities. In this study, we explored the antimicrobial biosynthetic potential and phylogenetics of culturable bacteria associated with the sponge Ophlitaspongia sp. from the Yellow Sea, China. Using culture-dependent methods, we obtained 151 bacterial strains, which were then analysed for their antimicrobial activities against seven indicator strains. The results indicate that 94 (62.3%) of the 151 isolated strains exhibited antimicrobial activities and inhibited at least one of the indicator strains. Fifty-two strains were selected for further phylogenetic analysis using 16S rRNA gene sequencing, as well as for the presence of polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) genes. These 52 strains belonged to 20 genera from 18 families in 4 phyla, including Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Five strains with PKS genes and ten strains with NRPS genes were detected. Among them, two strains contained both PKS and NRPS genes. Notoacmeibacter sp. strain HMA008 (class Alphaproteobacteria) exhibited potent antimicrobial activity; thus, whole genome sequencing methods were used to analyse its secondary metabolite biosynthetic gene clusters. The genome of HMA008 contained 12 biosynthetic gene clusters that potentially encode secondary metabolites belonging to compound classes such as non-ribosomal peptides, prodigiosin, terpene, β-lactones, and siderophore, among others. This study indicates that the sponge Ophlitaspongia sp. harbours diverse bacterial strains with antimicrobial properties and may serve as a potential source of bioactive compounds.

Neisseria species as pathobionts in bronchiectasis

Neisseria species are frequently identified in the bronchiectasis microbiome, but they are regarded as respiratory commensals. Using a combination of human cohorts, next-generation sequencing, systems biology, and animal models, we show that bronchiectasis bacteriomes defined by the presence of Neisseria spp. associate with poor clinical outcomes, including exacerbations. Neisseria subflava cultivated from bronchiectasis patients promotes the loss of epithelial integrity and inflammation in primary epithelial cells. In vivo animal models of Neisseria subflava infection and metabolipidome analysis highlight immunoinflammatory functional gene clusters and provide evidence for pulmonary inflammation. The murine metabolipidomic data were validated with human Neisseria-dominant bronchiectasis samples and compared with disease in which Pseudomonas-, an established bronchiectasis pathogen, is dominant. Metagenomic surveillance of Neisseria across various respiratory disorders reveals broader importance, and the assessment of the home environment in bronchiectasis implies potential environmental sources of exposure. Thus, we identify Neisseria species as pathobionts in bronchiectasis, allowing for improved risk stratification in this high-risk group.

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

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

Comparative genomics of Rothia species reveals diversity in novel biosynthetic gene clusters and ecological adaptation to different eukaryotic hosts and host niches

Rothia species are understudied members of the phylum Actinobacteria and prevalent colonizers of the human and animal upper respiratory tract and oral cavity. The oral cavity, including the palatine tonsils, is colonized by a complex microbial community, which compete for resources, actively suppress competitors and influence host physiology. We analysed genomic data from 43 new porcine Rothia isolates, together with 112 publicly available draft genome sequences of Rothia isolates from humans, animals and the environment. In all Rothia genomes, we identified biosynthetic gene clusters predicted to produce antibiotic non-ribosomal peptides, iron scavenging siderophores and other secondary metabolites that modulate microbe-microbe and potentially microbe-host interactions. In vitro overlay inhibition assays corroborated the hypothesis that specific strains produce natural antibiotics. Rothia genomes encode a large number of carbohydrate-active enzymes (CAZy), with varying CAZy activities among the species found in different hosts, host niches and environments. These findings reveal competition mechanisms and metabolic specializations linked to ecological adaptation of Rothia species in different hosts.

Pseudomonas aeruginosa polysaccharide Psl supports airway microbial community development

Pseudomonas aeruginosa dominates the complex polymicrobial cystic fibrosis (CF) airway and is a leading cause of death in persons with CF. Oral streptococcal colonization has been associated with stable CF lung function. However, no studies have demonstrated how Streptococcus salivarius, the most abundant streptococcal species found in individuals with stable CF lung disease, potentially improves lung function or becomes incorporated into the CF airway biofilm. By utilizing a two-species biofilm model to probe interactions between S. salivarius and P. aeruginosa, we discovered that the P. aeruginosa exopolysaccharide Psl promoted S. salivarius biofilm formation. Further, we identified a S. salivarius maltose-binding protein (MalE) that is required for promotion of biofilm formation both in vitro and in a Drosophila melanogaster co-infection model. Finally, we demonstrate that promotion of dual biofilm formation with S. salivarius is common among environmental and clinical P. aeruginosa isolates. Overall, our data supports a model in which S. salivarius uses a sugar-binding protein to interact with P. aeruginosa exopolysaccharide, which may be a strategy by which S. salivarius establishes itself within the CF airway microbial community.

Moving beyond descriptive studies: harnessing metabolomics to elucidate the molecular mechanisms underpinning host-microbiome phenotypes

Advances in technology and software have radically expanded the scope of metabolomics studies and allow us to monitor a broad transect of central carbon metabolism in routine studies. These increasingly sophisticated tools have shown that many human diseases are modulated by microbial metabolism. Despite this, it remains surprisingly difficult to move beyond these statistical associations and identify the specific molecular mechanisms that link dysbiosis to the progression of human disease. This difficulty stems from both the biological intricacies of host-microbiome dynamics as well as the analytical complexities inherent to microbiome metabolism research. The primary objective of this review is to examine the experimental and computational tools that can provide insights into the molecular mechanisms at work in host-microbiome interactions and to highlight the undeveloped frontiers that are currently holding back microbiome research from fully leveraging the benefits of modern metabolomics.

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

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

Rothia mucilaginosa is an anti-inflammatory bacterium in the respiratory tract of patients with chronic lung disease

Background

Chronic airway inflammation is the main driver of pathogenesis in respiratory diseases such as severe asthma, chronic obstructive pulmonary disease, cystic fibrosis (CF) and bronchiectasis. While the role of common pathogens in airway inflammation is widely recognised, the influence of other microbiota members is still poorly understood.

Methods

We hypothesised that the lung microbiota contains bacteria with immunomodulatory activity which modulate net levels of immune activation by key respiratory pathogens. Therefore, we assessed the immunomodulatory effect of several members of the lung microbiota frequently reported as present in CF lower respiratory tract samples.

Results

We show that Rothia mucilaginosa, a common resident of the oral cavity that is also often detectable in the lower airways in chronic disease, has an inhibitory effect on pathogen- or lipopolysaccharide-induced pro-inflammatory responses, in vitro (three-dimensional cell culture model) and in vivo (mouse model). Furthermore, in a cohort of adults with bronchiectasis, the abundance of Rothia species was negatively correlated with pro-inflammatory markers (interleukin (IL)-8 and IL-1β) and matrix metalloproteinase (MMP)-1, MMP-8 and MMP-9 in sputum. Mechanistic studies revealed that R. mucilaginosa inhibits NF-κB pathway activation by reducing the phosphorylation of IκBα and consequently the expression of NF-κB target genes.

Conclusions

These findings indicate that the presence of R. mucilaginosa in the lower airways potentially mitigates inflammation, which could in turn influence the severity and progression of chronic respiratory disorders.

A commensal bacterium of the lower airways, Rothia mucilaginosa, inhibits inflammation by NF-κB pathway inactivation. R. mucilaginosa abundance inversely correlates with sputum pro-inflammatory markers in chronic lung disease, indicating a beneficial role.https://bit.ly/3lNT9th

Non-tuberculous mycobacteria immunopathogenesis: Closer than they appear. a prime of innate immunity trade-off and NTM ways into virulence

Introduction

The growing incidence of non‐tuberculous mycobacteria (NTM) and changes in epidemiological factors have indicated that immune dysregulation may be associated with the emergence of NTM. Minireview entails to acknowledge complex interaction and new ways NTM are evolving around diverse immune status.

Methods

In order to perform this review, we selected peer reviewed, NLM database articles under the terms NTM, mycobacterium complex ‘AND’ ‐Host‐ immune response, immunity regulation, Disease, Single Nucleotide Polymorphism (SNP´s), and ‐pathogen‐ followed by a snow ball rolling basis search on immune components and NTM related with diseases distribution.

Results

The universal exposure and diversity of NTM are well‐documented; however, hospitals seldom establish vigilant control of water quality or immunodeficiencies for patients with NTM infections. Depending on the chemical structures and immune mechanisms presented by various NTM varieties, they can trigger different effects in dendritic and natural killer cells, which release interleukin (IL)‐17, tumour necrosis factor‐α (TNF‐α), interferon‐γ (IFN‐γ) and rIL‐1B. The T helper (Th)2‐acquired immune response is responsible for autoimmune responses in patients with NTM infections, and, quite disturbingly, immunocompetent patients have been reported to suffer from NTM infections.

Conclusion

New technologies and a comprehensive view has taught us; to acknowledge metabolic/immune determinants and trade‐offs along transit through mutualism‐parasite continuous.

Citizen-science based study of the oral microbiome in Cystic fibrosis and matched controls reveals major differences in diversity and abundance of bacterial and fungal species

Introduction: Cystic fibrosis (CF) is an autosomal genetic disease, associated with the production of excessively thick mucosa and with life-threatening chronic lung infections. The microbiota of the oral cavity can act as a reservoir or as a barrier for infectious microorganisms that can colonize the lungs. However, the specific composition of the oral microbiome in CF is poorly understood.Methods: In collaboration with CF associations in Spain, we collected oral rinse samples from 31 CF persons (age range 7-47) and matched controls, and then performed 16S rRNA metabarcoding and high-throughput sequencing, combined with culture and proteomics-based identification of fungi to survey the bacterial and fungal oral microbiome.Results: We found that CF is associated with less diverse oral microbiomes, which were characterized by higher prevalence of Candida albicans and differential abundances of a number of bacterial taxa that have implications in both the connection to lung infections in CF, as well as potential oral health concerns, particularly periodontitis and dental caries.Conclusion: Overall, our study provides a first global snapshot of the oral microbiome in CF. Future studies are required to establish the relationships between the composition of the oral and lung microbiomes in CF.

Comparing Stable Isotope Enrichment by Gas Chromatography with Time-of-Flight, Quadrupole Time-of-Flight, and Quadrupole Mass Spectrometry

Stable isotope tracers are applied for in vivo and in vitro studies to reveal the activity of enzymes and intracellular metabolic pathways. Most often, such tracers are used with gas chromatography coupled to mass spectrometry (GC-MS) owing to its ease of operation and reproducible mass spectral databases. Differences in isotope tracer performance of the classic GC-quadrupole MS instrument and newer time-of-flight instruments are not well studied. Here, we used three commercially available instruments for the analysis of identical samples from a stable isotope labeling study that used [U-13C6] d-glucose to investigate the metabolism of the bacterium Rothia mucilaginosa with respect to 29 amino acids and hydroxyl acids involved in primary metabolism. The prokaryote R. mucilaginosa belongs to the family of Micrococcaceae and is present and metabolically active in the airways and sputum of cystic fibrosis patients. Overall, all three GC-MS instruments (low-resolution GC-SQ MS, low-resolution GC-TOF MS, and high-resolution GC-QTOF MS) can be used to perform stable isotope tracing studies for glycolytic intermediates, tricarboxylic acid (TCA) metabolites, and amino acids, yielding similar biological results, with high-resolution GC-QTOF MS offering additional capabilities to identify the chemical structures of unknown compounds that might show significant isotope enrichments in biological studies.

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

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

Microbiome dysbiosis in lung cancer: from composition to therapy

The correlations between microbiota dysbiosis and cancer have gained extensive attention and been widely explored. As a leading cancer diagnosis worldwide, lung cancer poses a great threat to human health. The healthy human lungs are consistently exposed to external environment and harbor a specific pattern of microbiota, sharing many key pathological and physiological characteristics with the intestinal tract. Although previous findings uncovered the critical roles of microbiota in tumorigenesis and response to anticancer therapy, most of them were focused on the intestinal microbiota rather than lung microbiota. Notably, the considerable functions of microbiota in maintaining lung homeostasis should not be neglected as the microbiome dysbiosis may promote tumor development and progression through production of cytokines and toxins and multiple other pathways. Despite the fact that increasing studies have revealed the effect of microbiome on the induction of lung cancer and different disease status, the underlying mechanisms and potential therapeutic strategies remained unclear. Herein, we summarized the recent progresses about microbiome in lung cancer and further discussed the role of microbial communities in promoting lung cancer progression and the current status of therapeutic approaches targeting microbiome to alleviate and even cure lung cancer.

High Occurrence of Bacterial Competition Among Clinically Documented Opportunistic Pathogens Including Achromobacter xylosoxidans in Cystic Fibrosis

Cystic Fibrosis (CF) airways favor abnormal microbial development. Infections are considered as polymicrobial and competition can be observed between microorganisms. The current literature on bacterial competition in CF mostly consists of studies with limited numbers of strains, mainly focused on the major pathogens Pseudomonas aeruginosa (Pa) and Staphylococcus aureus (Sa) and does not give a comprehensive overview of the overall importance of bacterial interactions or the behavior of less often encountered emerging bacteria such as Achromobacter. In this context, we screened a panel of 39 strains from six CF patients, of either clinical or domestic environmental origin, distinguished according to genotype and belonging to four opportunistic pathogens, Pa (n = 15), Sa (n = 3), Stenotrophomonas maltophilia (Sm, n = 10) and Achromobacter xylosoxidans (Ax, n = 11). We investigated their capacity to compete in terms of growth, motility, and pigment production on agar media through 203 crossing experiments. Eleven strains selected via the initial screening results were further studied for competitive growth in liquid medium and biofilm formation. Competition was noted for 33% (67/203) of the pairs of strains with 85 modifications observed between monocultures and co-cultures, impacting growth (23.6%), motility (13.8%), and/or pigment production (6.1%). Under all conditions of the study (clinical, environmental strains; intra-, inter-patients; intra-, inter-species levels), competition was significantly more frequent among pairs of strains with at least one clinical strain. While Pa mainly outcompeted other species, in one patient with chronic colonization by Ax and sporadic colonization by Pa, we showed that some Ax inhibited the growth and pigmentation of Pa whereas biofilm formation was drastically reduced. Enlarging the panel of strains tested in competition assays gave new perspectives on the complex interactions taking place among the CF airway community. Indeed, the frequent occurrence of varied, strain-dependent interactions is revealed here. We report the first results of competition assays for Ax with the ability of certain strains to outcompete Pa. Our results are linked to the patient’s colonization history and question the importance of bacterial competitiveness in the colonization pattern of CF airways.

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.

Bacterial Community Interactions During Chronic Respiratory Disease

Chronic respiratory diseases including chronic rhinosinusitis, otitis media, asthma, cystic fibrosis, non-CF bronchiectasis, and chronic obstructive pulmonary disease are a major public health burden. Patients suffering from chronic respiratory disease are prone to persistent, debilitating respiratory infections due to the decreased ability to clear pathogens from the respiratory tract. Such infections often develop into chronic, life-long complications that are difficult to treat with antibiotics due to the formation of recalcitrant biofilms. The microbial communities present in the upper and lower respiratory tracts change as these respiratory diseases progress, often becoming less diverse and dysbiotic, correlating with worsening patient morbidity. Those with chronic respiratory disease are commonly infected with a shared group of respiratory pathogens including Haemophilus influenzae, Streptococcus pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, and Moraxella catarrhalis, among others. In order to understand the microbial landscape of the respiratory tract during chronic disease, we review the known inter-species interactions among these organisms and other common respiratory flora. We consider both the balance between cooperative and competitive interactions in relation to microbial community structure. By reviewing the major causes of chronic respiratory disease, we identify common features across disease states and signals that might contribute to community shifts. As microbiome shifts have been associated with respiratory disease progression, worsening morbidity, and increased mortality, these underlying community interactions likely have an impact on respiratory disease state.

Commensal Oral Rothia mucilaginosa Produces Enterobactin, a Metal-Chelating Siderophore

Next-generation sequencing studies of saliva and dental plaque from subjects in both healthy and diseased states have identified bacteria belonging to the Rothia genus as ubiquitous members of the oral microbiota. To gain a deeper understanding of molecular mechanisms underlying the chemical ecology of this unexplored group, we applied a genome mining approach that targets functionally important biosynthetic gene clusters (BGCs). All 45 genomes that were mined, representing Rothia mucilaginosa, Rothia dentocariosa, and Rothia aeria, harbored a catechol-siderophore-like BGC. To explore siderophore production further, we grew the previously characterized R. mucilaginosa ATCC 25296 in liquid cultures, amended with glycerol, which led to the identification of the archetype siderophore enterobactin by using tandem liquid chromatography-mass spectrometry (LC-MS/MS), high-performance liquid chromatography (HPLC), and nuclear magnetic resonance (NMR) spectroscopy. Normally attributed to pathogenic gut bacteria, R. mucilaginosa is the first commensal oral bacterium found to produce enterobactin. Cocultivation studies including R. mucilaginosa or purified enterobactin revealed that enterobactin reduced growth of certain strains of cariogenic Streptococcus mutans and pathogenic strains of Staphylococcus aureus Commensal oral bacteria were either unaffected, reduced in growth, or induced to grow adjacent to enterobactin-producing R. mucilaginosa or the pure compound. Taken together with Rothia's known capacity to ferment a variety of carbohydrates and amino acids, our findings of enterobactin production add an additional level of explanation to R. mucilaginosa's prevalence in the oral cavity. Enterobactin is the strongest Fe(III) binding siderophore known, and its role in oral health requires further investigation.IMPORTANCE The communication language of the human oral microbiota is vastly underexplored. However, a few studies have shown that specialized small molecules encoded by BGCs have critical roles such as in colonization resistance against pathogens and quorum sensing. Here, by using a genome mining approach in combination with compound screening of growth cultures, we identified that the commensal oral community member R. mucilaginosa harbors a catecholate-siderophore BGC, which is responsible for the biosynthesis of enterobactin. The iron-scavenging role of enterobactin is known to have positive effects on the host's iron pool and negative effects on host immune function; however, its role in oral health remains unexplored. R. mucilaginosa was previously identified as an abundant community member in cystic fibrosis, where bacterial iron cycling plays a major role in virulence development. With respect to iron's broad biological importance, iron-chelating enterobactin may explain R. mucilaginosa's colonization success in both health and disease.

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.

Antibiotic resistance in Pseudomonas aeruginosa - Mechanisms, epidemiology and evolution

Antibiotics are powerful drugs used in the treatment of bacterial infections. The inappropriate use of these medicines has driven the dissemination of antibiotic resistance (AR) in most bacteria. Pseudomonas aeruginosa is an opportunistic pathogen commonly involved in environmental- and difficult-to-treat hospital-acquired infections. This species is frequently resistant to several antibiotics, being in the "critical" category of the WHO's priority pathogens list for research and development of new antibiotics. In addition to a remarkable intrinsic resistance to several antibiotics, P. aeruginosa can acquire resistance through chromosomal mutations and acquisition of AR genes. P. aeruginosa has one of the largest bacterial genomes and possesses a significant assortment of genes acquired by horizontal gene transfer (HGT), which are frequently localized within integrons and mobile genetic elements (MGEs), such as transposons, insertion sequences, genomic islands, phages, plasmids and integrative and conjugative elements (ICEs). This genomic diversity results in a non-clonal population structure, punctuated by specific clones that are associated with significant morbidity and mortality worldwide, the so-called high-risk clones. Acquisition of MGEs produces a fitness cost in the host, that can be eased over time by compensatory mutations during MGE-host coevolution. Even though plasmids and ICEs are important drivers of AR, the underlying evolutionary traits that promote this dissemination are poorly understood. In this review, we provide a comprehensive description of the main strategies involved in AR in P. aeruginosa and the leading drivers of HGT in this species. The most recently developed genomic tools that allowed a better understanding of the features contributing for the success of P. aeruginosa are discussed.

Stenotrophomonas maltophilia Differential Gene Expression in Synthetic Cystic Fibrosis Sputum Reveals Shared and Cystic Fibrosis Strain-Specific Responses to the Sputum Environment

Stenotrophomonas maltophilia is a Gram-negative opportunistic pathogen that can infect the lungs of people with cystic fibrosis (CF). The highly viscous mucus in the CF lung, expectorated as sputum, serves as the primary nutrient source for microbes colonizing this site and induces virulence-associated phenotypes and gene expression in several CF pathogens. Here, we characterized the transcriptional responses of three S. maltophilia strains during exposure to synthetic CF sputum medium (SCFM2) to gain insight into how this organism interacts with the host in the CF lung. These efforts led to the identification of 881 transcripts differentially expressed by all three strains, many of which reflect the metabolic pathways used by S. maltophilia in sputum, as well as altered stress responses. The latter correlated with increased resistance to peroxide exposure after pregrowth in SCFM2 for two of the strains. We also compared the SCFM2 transcriptomes of two S. maltophilia CF isolates to that of the acute infection strain, S. maltophilia K279a, allowing us to identify CF isolate-specific signatures in differential gene expression. The expression of genes from the accessory genomes was also differentially altered in response to SCFM2. Finally, a number of biofilm-associated genes were differentially induced in SCFM2, particularly in K279a, which corresponded to increased aggregation and biofilm formation in this strain relative to both CF strains. Collectively, this work details the response of S. maltophilia to an environment that mimics important aspects of the CF lung, identifying potential survival strategies and metabolic pathways used by S. maltophilia during infections.IMPORTANCE Stenotrophomonas maltophilia is an important infecting bacterium in the airways of people with cystic fibrosis (CF). However, compared to the other CF pathogens, S. maltophilia has been relatively understudied. The significance of our research is to provide insight into the global transcriptomic changes of S. maltophilia in response to a medium that was designed to mimic important aspects of the CF lung. This study elucidates the overall metabolic changes that occur when S. maltophilia encounters the CF lung and generates a road map of candidate genes to test using in vitro and in vivo models of CF.

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-Associated Stenotrophomonas maltophilia Strain-Specific Adaptations and Responses to pH

Understanding bacterial responses to physiological conditions is an important priority for combating opportunistic infections. The majority of CF patients succumb to inflammation and necrosis in the airways, arising from chronic infection due to ineffective mucociliary clearance. Steep pH gradients characterize the CF airways but are not often incorporated in standard microbiology culture conditions. Stenotrophomonas maltophilia is a prevalent CF opportunistic pathogen also found in many disparate environments, yet this bacterium’s contribution to CF lung damage and its response to changing environmental factors remain largely understudied. Here, we show that pH impacts the physiology and antibiotic susceptibility of S. maltophilia, with implications for the development of relevant in vitro models and assessment of antibiotic sensitivity.

The airway fluids of cystic fibrosis (CF) patients contain local pH gradients and are more acidic than those of healthy individuals. pH is a critical factor that is often overlooked in studies seeking to recapitulate the infection microenvironment. We sought to determine the impact of pH on the physiology of a ubiqituous yet understudied microbe, Stenotrophomonas maltophilia. Phylogenomics was first used to reconstruct evolutionary relationships between 74 strains of S. maltophilia (59 from CF patients). Neither the core genome (2,158 genes) nor the accessory genome (11,978 genes) distinguish the CF and non-CF isolates; however, strains from similar isolation sources grouped into the same subclades. We grew two human and six CF S. maltophilia isolates from different subclades at a range of pH values and observed impaired growth and altered antibiotic tolerances at pH 5. Transcriptomes revealed increased expression of both antibiotic resistance and DNA repair genes in acidic conditions. Although the gene expression profiles of S. maltophilia in lab cultures and CF sputum were distinct, we found that the same genes associated with low pH were also expressed during infection, and the higher pH cultures were more similar to sputum metatranscriptomes. Our findings suggest that S. maltophilia is not well adapted to acidity and may cope with low pH by expressing stress response genes and colonizing less acidic microenvironments. As a whole, our study underlines the impact of microenvironments on bacterial colonization and adaptation in CF infections.

IMPORTANCE Understanding bacterial responses to physiological conditions is an important priority for combating opportunistic infections. The majority of CF patients succumb to inflammation and necrosis in the airways, arising from chronic infection due to ineffective mucociliary clearance. Steep pH gradients characterize the CF airways but are not often incorporated in standard microbiology culture conditions. Stenotrophomonas maltophilia is a prevalent CF opportunistic pathogen also found in many disparate environments, yet this bacterium’s contribution to CF lung damage and its response to changing environmental factors remain largely understudied. Here, we show that pH impacts the physiology and antibiotic susceptibility of S. maltophilia, with implications for the development of relevant in vitro models and assessment of antibiotic sensitivity.

Cystic fibrosis respiratory microbiota: unraveling complexity to inform clinical practice

INTRODUCTION

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