A Different Microbiome Gene Repertoire in the Airways of Cystic Fibrosis Patients with Severe Lung Disease

Microbiome's Universe: Impact on health, disease and cancer treatment

The human microbiome is a diverse ecosystem of microorganisms that reside in the body and influence various aspects of health and well-being. Recent advances in sequencing technology have brought to light microbial communities in organs and tissues that were previously considered sterile. The gut microbiota plays an important role in host physiology, including metabolic functions and immune modulation. Disruptions in the balance of the microbiome, known as dysbiosis, have been linked to diseases such as cancer, inflammatory bowel disease and metabolic disorders. In addition, the administration of antibiotics can lead to dysbiosis by disrupting the structure and function of the gut microbial community. Targeting strategies are the key to rebalancing the microbiome and fighting disease, including cancer, through interventions such as probiotics, fecal microbiota transplantation (FMT), and bacteria-based therapies. Future research must focus on understanding the complex interactions between diet, the microbiome and cancer in order to optimize personalized interventions. Multidisciplinary collaborations are essential if we are going to translate microbiome research into clinical practice. This will revolutionize approaches to cancer prevention and treatment.

Exploring the Complexity of the Human Respiratory Virome through an In Silico Analysis of Shotgun Metagenomic Data Retrieved from Public Repositories

BACKGROUND

Respiratory viruses significantly impact global morbidity and mortality, causing more disease in humans than any other infectious agent. Beyond pathogens, various viruses and bacteria colonize the respiratory tract without causing disease, potentially influencing respiratory diseases' pathogenesis. Nevertheless, our understanding of respiratory microbiota is limited by technical constraints, predominantly focusing on bacteria and neglecting crucial populations like viruses. Despite recent efforts to improve our understanding of viral diversity in the human body, our knowledge of viral diversity associated with the human respiratory tract remains limited.

METHODS

Following a comprehensive search in bibliographic and sequencing data repositories using keyword terms, we retrieved shotgun metagenomic data from public repositories (n = 85). After manual curation, sequencing data files from 43 studies were analyzed using EVEREST (pipEline for Viral assEmbly and chaRactEriSaTion). Complete and high-quality contigs were further assessed for genomic and taxonomic characterization.

RESULTS

Viral contigs were obtained from 194 out of the 868 FASTQ files processed through EVEREST. Of the 1842 contigs that were quality assessed, 8% (n = 146) were classified as complete/high-quality genomes. Most of the identified viral contigs were taxonomically classified as bacteriophages, with taxonomic resolution ranging from the superkingdom level down to the species level. Captured contigs were spread across 25 putative families and varied between RNA and DNA viruses, including previously uncharacterized viral genomes. Of note, airway samples also contained virus(es) characteristic of the human gastrointestinal tract, which have not been previously described as part of the lung virome. Additionally, by performing a meta-analysis of the integrated datasets, ecological trends within viral populations linked to human disease states and their biogeographical distribution along the respiratory tract were observed.

CONCLUSION

By leveraging publicly available repositories of shotgun metagenomic data, the present study provides new insights into viral genomes associated with specimens from the human respiratory tract across different disease spectra. Further studies are required to validate our findings and evaluate the potential impact of these viral communities on respiratory tract physiology.

Insights on Pseudomonas aeruginosa Carbohydrate Binding from Profiles of Cystic Fibrosis Isolates Using Multivalent Fluorescent Glycopolymers Bearing Pendant Monosaccharides

Pseudomonas aeruginosa contributes to frequent, persistent, and, often, polymicrobial respiratory tract infections for individuals with cystic fibrosis (CF). Chronic CF infections lead to bronchiectasis and a shortened lifespan. P. aeruginosa expresses numerous adhesins, including lectins known to bind the epithelial cell and mucin glycoconjugates. Blocking carbohydrate-mediated host-pathogen and intra-biofilm interactions critical to the initiation and perpetuation of colonization offer promise as anti-infective treatment strategies. To inform anti-adhesion therapies, we profiled the monosaccharide binding of P. aeruginosa from CF and non-CF sources, and assessed whether specific bacterial phenotypic characteristics affected carbohydrate-binding patterns. Focusing at the cellular level, microscopic and spectrofluorometric tools permitted the solution-phase analysis of P. aeruginosa binding to a panel of fluorescent glycopolymers possessing distinct pendant monosaccharides. All P. aeruginosa demonstrated significant binding to glycopolymers specific for α-D-galactose, β-D-N-acetylgalactosamine, and β-D-galactose-3-sulfate. In each culture, a small subpopulation accounted for the binding. The carbohydrate anomeric configuration and sulfate ester presence markedly influenced binding. While this opportunistic pathogen from CF hosts presented with various colony morphologies and physiological activities, no phenotypic, physiological, or structural feature predicted enhanced or diminished monosaccharide binding. Important to anti-adhesive therapeutic strategies, these findings suggest that, regardless of phenotype or clinical source, P. aeruginosa maintain a small subpopulation that may readily associate with specific configurations of specific monosaccharides. This report provides insights into whole-cell P. aeruginosa carbohydrate-binding profiles and into the context within which successful anti-adhesive and/or anti-virulence anti-infective agents for CF must contend.

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.

Positioning the preventive potential of microbiome treatments for cystic fibrosis in the context of current therapies

Antibiotics and cystic fibrosis transmembrane conductance regulator (CFTR) modulators play a pivotal role in cystic fibrosis (CF) treatment, but both have limitations. Antibiotics are linked to antibiotic resistance and disruption of the airway microbiome, while CFTR modulators are not widely accessible, and structural lung damage and pathogen overgrowth still occur. Complementary strategies that can beneficially modulate the airway microbiome in a preventive way are highly needed. This could be mediated via oral probiotics, which have shown some improvement of lung function and reduction of airway infections and exacerbations, as a cost-effective approach. However, recent data suggest that specific and locally administered probiotics in the respiratory tract might be a more targeted approach to prevent pathogen outgrowth in the lower airways. This review aims to summarize the current knowledge on the CF airway microbiome and possibilities of microbiome treatments to prevent bacterial and/or viral infections and position them in the context of current CF therapies.

The Cystic Fibrosis Upper and Lower Airway Metagenome

The microbial metagenome in cystic fibrosis (CF) airways was investigated by whole-genome shotgun sequencing of total DNA isolated from nasal lavage samples, oropharyngeal swabs, and induced sputum samples collected from 65 individuals with CF aged 7 to 50 years. Each patient harbored a personalized microbial metagenome unique in microbial load and composition, the exception being monocultures of the most common CF pathogens Staphylococcus aureus and Pseudomonas aeruginosa from patients with advanced lung disease. The sampling of the upper airways by nasal lavage uncovered the fungus Malassezia restricta and the bacterium Staphylococcus epidermidis as prominent species. Healthy and CF donors harbored qualitatively and quantitatively different spectra of commensal bacteria in their sputa, even in the absence of any typical CF pathogen. If P. aeruginosa, S. aureus, or Stenotrophomonas maltophilia belonged to the trio of the most abundant species in the CF sputum metagenome, common inhabitants of the respiratory tract of healthy subjects, i.e., Eubacterium sulci, Fusobacterium periodonticum, and Neisseria subflava, were present only in low numbers or not detectable. Random forest analysis identified the numerical ecological parameters of the bacterial community, such as Shannon and Simpson diversity, as the key parameters that globally distinguish sputum samples from CF and healthy donors. IMPORTANCE Cystic fibrosis (CF) is the most common life-limiting monogenetic disease in European populations and is caused by mutations in the CFTR gene. Chronic airway infections with opportunistic pathogens are the major morbidity that determines prognosis and quality of life in most people with CF. We examined the composition of the microbial communities of the oral cavity and upper and lower airways in CF patients across all age groups. From early on, the spectrum of commensals is different in health and CF. Later on, when the common CF pathogens take up residence in the lungs, we observed differential modes of depletion of the commensal microbiota in the presence of S. aureus, P. aeruginosa, S. maltophilia, or combinations thereof. It remains to be seen whether the implementation of lifelong CFTR (cystic fibrosis transmembrane conductance regulator) modulation will change the temporal evolution of the CF airway metagenome.

Colonizing microbiota is associated with clinical outcomes in diabetic wound healing

With the development of society and the improvement of life quality, more than 500 million people are affected by diabetes. More than 10 % of people with diabetes will suffer from diabetic wounds, and 80 % of diabetic wounds will reoccur, so the development of new diabetic wound treatments is of great importance. The development of skin microbe research technology has gradually drawn people's attention to the complex relationship between microbes and diabetic wounds. Many studies have shown that skin microbes are associated with the outcome of diabetic wounds and can even be used as one of the indicators of wound prognosis. Skin microbes have also been found to have the potential to treat diabetic wounds. The wound colonization of different bacteria can exert opposing therapeutic effects. It is necessary to fully understand the skin microbes in diabetic wounds, which can provide valuable guidance for clinical diabetic wound treatment.

Therapeutic beta-lactam dosages and broad-spectrum antibiotics are associated with reductions in microbial richness and diversity in persons with cystic fibrosis

Persons with cystic fibrosis (PwCF) suffer from pulmonary exacerbations (PEx) related in part to lung infection. While higher microbial diversity is associated with higher lung function, the data on the impact of short-term antibiotics on changes in microbial diversity is conflicting. Further, Prevotella secretes beta-lactamases, which may influence recovery of lung function. We hypothesize that sub-therapeutic and broad spectrum antibiotic exposure leads to decreasing microbial diversity. Our secondary aim was to evaluate the concerted association of beta-lactam pharmacokinetics (PK), antibiotic spectrum, microbial diversity, and antibiotic resistance on lung function recovery using a pathway analysis. This was a retrospective observational study of persons with CF treated with IV antibiotics for PEx between 2016 and 2020 at Children's National Hospital; respiratory samples and clinical information were collected at hospital admission for PEx (E), end of antibiotic treatment (T), and follow-up (F). Metagenomic sequencing was performed; PathoScope 2.0 and AmrPlusPlus were used for taxonomic assignment of sequences to bacteria and antibiotic resistance genes (ARGs). M/W Pharm was used for PK modeling. Comparison of categorical and continuous variables and pathway analysis were performed in STATA. Twenty-two PwCF experienced 43 PEx. The study cohort had a mean age of 14.6 years. Only 12/43 beta-lactam courses had therapeutic PK, and 18/43 were broad spectrum. A larger decrease in richness between E and T was seen in the therapeutic PK group (sufficient - 20.1 vs. insufficient - 1.59, p = 0.025) and those receiving broad spectrum antibiotics (broad - 14.5 vs. narrow - 2.8, p = 0.030). We did not detect differences in the increase in percent predicted forced expiratory volume in one second (ppFEV1) at end of treatment compared to PEx based on beta-lactam PK (sufficient 13.6% vs. insufficient 15.1%) or antibiotic spectrum (broad 11.5% vs. narrow 16.6%). While both therapeutic beta-lactam PK and broad-spectrum antibiotics decreased richness between PEx and the end of treatment, we did not detect longstanding changes in alpha diversity or an association with superior recovery of lung function compared with subtherapeutic PK and narrow spectrum antimicrobials.

Real-life efficacy and safety of elexacaftor/tezacaftor/ivacaftor on severe cystic fibrosis lung disease patients

Elexacaftor/tezacaftor/ivacaftor (ETI) is a cystic fibrosis (CF) transmembrane conductance regulator modulator, which has shown efficacy in CF patients (≥6 years) with ≥1 Phe508del mutation and a minimal function mutation. In October 2019, ETI became available on compassionate use basis for Dutch CF patients with severe lung disease. Our objective was to investigate safety and efficacy of ETI in this patient group in a real-life setting. A multicenter longitudinal observational study was conducted to examine changes in FEV1 , BMI, and adverse events at initiation and 1, 3, 6, and 12 months after starting ETI. The number of exacerbations was recorded in the 12 months before and the 12 months after ETI treatment. Patients eligible for compassionate use had a FEV1 <40% predicted. Wilcoxon signed-rank test analyzed changes over time. Twenty subjects were included and followed up for up to 12 months after starting ETI. Treatment was well tolerated with mild side effects reported, namely, rash (15%) and stomach ache (20%) with 80% resolving within 1 month. Mean absolute increase of FEV1 was 11.8/13.7% (p ≤ .001) and BMI was 0.49/1.87 kg/m2 (p < .001-0.02) after 1/12 months, respectively. In comparison to the number of exacerbations pretrial, there was a marked reduction in exacerbations after initiation. Our findings show long-term effects of treatment with ETI in patients with severe CF lung disease in a real-life setting. Treatment with ETI is associated with increased lung function and BMI, less exacerbations, and only mild side effects.

Impact of Elexacaftor/Tezacaftor/Ivacaftor Therapy on the Cystic Fibrosis Airway Microbial Metagenome

The introduction of mutation-specific combination therapy with the cystic fibrosis transmembrane conductance regulator (CFTR) modulators elexacaftor/tezacaftor/ivacaftor (ELX/TEZ/IVA) has substantially improved lung function and quality of life of people with cystic fibrosis (CF). Collecting deep cough swabs and induced sputum, this postapproval study examined the effect of 14- and 50-week treatment with ELX/TEZ/IVA on the airway microbial metagenome of pancreatic- insufficient CF patients aged 12 years and older. Compared to pretreatment, the total bacterial load decreased, the individual species were more evenly distributed in the community, and the individual microbial metagenomes became more similar in their composition. However, the microbial network remained vulnerable to fragmentation. The initial shift of the CF metagenome was attributable to the ELX/TEZ/IVA-mediated gain of CFTR activity followed by a diversification driven by a group of commensals at the 1-year time point that are typical for healthy airways. IMPORTANCE Shotgun metagenome sequencing of respiratory secretions with spike-in controls for normalization demonstrated that 1 year of high-efficient CFTR modulation with elexacaftor/tezacaftor/ivacaftor extensively reduced the bacterial load. Longer observation periods will be necessary to resolve whether the partial reversion of the basic defect that is achieved with ELX/TEZ/IVA is sufficient in the long run to render the CF lungs robust against the recolonization with common opportunistic pathogens.

Antibiotic resistance in chronic respiratory diseases: from susceptibility testing to the resistome

The development of resistome analysis, i.e. the comprehensive analysis of antibiotic-resistance genes (ARGs), is enabling a better understanding of the mechanisms of antibiotic-resistance emergence. The respiratory microbiome is a dynamic and interactive network of bacteria, with a set of ARGs that could influence the response to antibiotics. Viruses such as bacteriophages, potential carriers of ARGs, may also form part of this respiratory resistome. Chronic respiratory diseases (CRDs) such as cystic fibrosis, severe asthma, chronic obstructive pulmonary disease and bronchiectasis, managed with long-term antibiotic therapies, lead to multidrug resistance. Antibiotic susceptibility testing provides a partial view of the bacterial response to antibiotics in the complex lung environment. Assessing the ARG network would allow personalised, targeted therapeutic strategies and suitable antibiotic stewardship in CRDs, depending on individual resistome and microbiome signatures. This review summarises the influence of pulmonary antibiotic protocols on the respiratory microbiome, detailing the variable consequences according to antibiotic class and duration of treatment. The different resistome-profiling methods are explained to clarify their respective place in antibiotic-resistance analysis in the lungs. Finally, this review details current knowledge on the respiratory resistome related to therapeutic strategies and provides insight into the application of resistome analysis to counter the emergence of multidrug-resistant respiratory pathogens.

Dynamic alterations in the lung microbiota in a rat model of lipopolysaccharide-induced acute lung injury

The lung microbiota have been found to be substantially altered in numerous pulmonary disorders, and crosstalk between the host pathophysiology and lung microbiota plays critical roles in the regulation of disease states. The aim of this study was to investigate dynamic changes in the lung microbiota during different stages of acute lung injury and acute respiratory distress syndrome (ALI/ARDS). Rats receiving an intraperitoneal administration of lipopolysaccharide (LPS) were sacrificed at 12 and 48 h after injection, and the hematological parameters, serum cytokine levels, and histological characteristics of the lung tissue and lung microbiota were assessed. After LPS injection, along with fluctuations of systemic cytokine levels and the onset and regression of pulmonary edema, the diversity, components, and functionalities of the pulmonary microbiota underwent significant dynamic changes. The volatility of the α-diversity indices narrowed after LPS injection, and the indices significantly decreased 48 h later. The abundance of 18 genera and functionality of adenosine triphosphate–binding cassette (ABC) transporters, pentose phosphate, and bacterial chemotaxis pathways were found to significantly differ between specified time points. Several significant correlations between the components and functionalities of the lung microbiota and indicative symptoms of ALI/ARDS were also observed. Brevibacterium was correlated with cytokines tumor necrosis factor (TNF)-α, interleukin (IL)-10, and IL-6 and with hematological percentage of neutrophils (NEU%); Wnt, Notch, and chronic myeloid leukemia signaling pathways were correlated with IL-1β; mitogen-activated protein kinase (MAPK) signaling pathway–yeast was correlated with IL-10; and the pathways of ascorbate and aldarate metabolism and basal transcription factors were correlated with platelet-related indicators. The correlations between the lung microbiota and indicative symptoms of ALI/ARDS identified in this study support further investigation into the underlying mechanism of host–microbiota interactions during lung injury and repair.

Mapping bacterial diversity and metabolic functionality of the human respiratory tract microbiome

Background

The Human Respiratory Tract (HRT) is colonized by various microbial taxa, known as HRT microbiota, in a manner that is indicative of mutualistic interaction between such microorganisms and their host.

Aim

To investigate the microbial composition of the HRT and its possible correlation with the different compartments of the respiratory tract.

Methods

In the current study, we performed an in-depth meta-analysis of 849 HRT samples from public shotgun metagenomic datasets obtained through several distinct collection methods.

Results

The statistical robustness provided by this meta-analysis allowed the identification of 13 possible HRT-specific Community State Types (CSTs), which appear to be specific to each anatomical region of the respiratory tract. Furthermore, functional characterization of the metagenomic datasets revealed specific microbial metabolic features correlating with the different compartments of the respiratory tract.

Conclusion

The meta-analysis here performed suggested that the variable presence of certain bacterial species seems to be linked to a location-related abundance gradient in the HRT and seems to be characterized by a specific microbial metabolic capability.

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

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

Factors Influencing Lung Function in Patients with Cystic Fibrosis in Western Romania

PURPOSE

The aim of this cross-sectional study was to identify the major factors influencing pulmonary function in CF patients from western side of Romania.

PATIENTS AND METHODS

The study enrolled 51 patients with CF between the ages of 6 and 27.8 years who were monitored at regular visits to the National Cystic Fibrosis Centre and Pius Branzeu County Hospital in Timisoara, Romania, over a period of 2 years. The relationships between lung function, as measured by forced expiratory volume in 1 s (FEV1), with patient age, sex, body mass index (BMI), pancreatic insufficiency (PI), microbial infection, CF-related diabetes (CFRD), CF-associated liver disease (CFLD), and physical activity <30 min/day, were evaluated by multivariate regression analysis.

RESULTS

The results showed that FEV1 was 0.32% higher for each increase in percentile of BMI (95% confidence interval: 0.034-0.619). In addition, mean FEV1 was 1.52% lower with every year rise of age. PI and female sex increased the risk of impaired lung function (FEV1 <60%). The factors most closely correlated with pulmonary function in pediatric CF patients were current age (negative) and BMI (positive).

CONCLUSION

The findings of this study, in combination with what is known from other studies in CF, suggest that a better nutritional status and infection prophylaxis should be part of a comprehensive clinical management strategy for pediatric CF in Romania.

Metaproteomics to Decipher CF Host-Microbiota Interactions: Overview, Challenges and Future Perspectives

Cystic fibrosis (CF) is a hereditary disease caused by mutations in the CF transmembrane conductance regulator (CFTR) gene, triggering dysfunction of the anion channel in several organs including the lung and gut. The main cause of morbidity and mortality is chronic infection. The microbiota is now included among the additional factors that could contribute to the exacerbation of patient symptoms, to treatment outcome, and more generally to the phenotypic variability observed in CF patients. In recent years, various omics tools have started to shed new light on microbial communities associated with CF and host-microbiota interactions. In this context, proteomics targets the key effectors of the responses from organisms, and thus their phenotypes. Recent advances are promising in terms of gaining insights into the CF microbiota and its relation with the host. This review provides an overview of the contributions made by proteomics and metaproteomics to our knowledge of the complex host-microbiota partnership in CF. Considering the strengths and weaknesses of proteomics-based approaches in profiling the microbiota in the context of other diseases, we illustrate their potential and discuss possible strategies to overcome their limitations in monitoring both the respiratory and intestinal microbiota in sample from patients with CF.

The Lung Microbiome in Young Children with Cystic Fibrosis: A Prospective Cohort Study

The cystic fibrosis (CF) lung harbours a diverse microbiome and reduced diversity in the CF lung has been associated with advancing age, increased inflammation and poorer lung function. Data suggest that the window for intervention is early in CF, yet there is a paucity of studies on the lung microbiome in children with CF. The objective of this study was to thoroughly characterise the lower airway microbiome in pre-school children with CF. Bronchoalveolar lavage (BAL) samples were collected annually from children attending the three clinical centres. Clinical and demographic data were collated on all subjects alongside BAL inflammatory markers. 16S rRNA gene sequencing was performed on the Illumina MiSeq platform. Bioinformatics and data analysis were performed using Qiime and R project software. Data on 292 sequenced BALs from 101 children with CF and 51 without CF show the CF lung microbiome, while broadly similar to that in non-CF children, is distinct. Alpha diversity between the two cohorts was indistinguishable at this early age. The CF diagnosis explained only 1.1% of the variation between the cohort microbiomes. However, several key genera were significantly differentially abundant between the groups. While the non-CF lung microbiome diversity increased with age, diversity reduced in CF with age. Pseudomonas and Staphylococcus were more abundant with age, while genera such as Streptococcus, Porphyromonas and Veillonella were less abundant with age. There was a negative correlation between alpha diversity and interleukin-8 and neutrophil elastase in the CF population. Neither current flucloxacillin or azithromycin prophylaxis, nor previous oral or IV antibiotic exposure, was correlated with microbiome diversity. Consecutive annual BAL samples over 5 years from a subgroup of children demonstrated diverse patterns of development in the first years of life.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

IMPACT

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

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.

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

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

The Microbiome in Cystic Fibrosis Pulmonary Disease

Cystic fibrosis (CF) is a genetic disease with mutational changes leading to profound dysbiosis, both pulmonary and intestinal, from a very young age. This dysbiosis plays an important role in clinical manifestations, particularly in the lungs, affected by chronic infection. The range of microbiological tools has recently been enriched by metagenomics based on next-generation sequencing (NGS). Currently applied essentially in a gene-targeted manner, metagenomics has enabled very exhaustive description of bacterial communities in the CF lung niche and, to a lesser extent, the fungi. Aided by progress in bioinformatics, this now makes it possible to envisage shotgun sequencing and opens the door to other areas of the microbial world, the virome, and the archaeome, for which almost everything remains to be described in cystic fibrosis. Paradoxically, applying NGS in microbiology has seen a rebirth of bacterial culture, but in an extended manner (culturomics), which has proved to be a perfectly complementary approach to NGS. Animal models have also proved indispensable for validating microbiome pathophysiological hypotheses. Description of pathological microbiomes and correlation with clinical status and therapeutics (antibiotic therapy, cystic fibrosis transmembrane conductance regulator (CFTR) modulators) revealed the richness of microbiome data, enabling description of predictive and follow-up biomarkers. Although monogenic, CF is a multifactorial disease, and both genotype and microbiome profiles are crucial interconnected factors in disease progression. Microbiome-genome interactions are thus important to decipher.

Toward a dynamical understanding of microbial communities

The challenge of moving beyond descriptions of microbial community composition to the point where understanding underlying eco-evolutionary dynamics emerges is daunting. While it is tempting to simplify through use of model communities composed of a small number of types, there is a risk that such strategies fail to capture processes that might be specific and intrinsic to complexity of the community itself. Here, we describe approaches that embrace this complexity and show that, in combination with metagenomic strategies, dynamical insight is increasingly possible. Arising from these studies is mounting evidence of rapid eco-evolutionary change among lineages and a sense that processes, particularly those mediated by horizontal gene transfer, not only are integral to system function, but are central to long-term persistence. That such dynamic, systems-level insight is now possible, means that the study and manipulation of microbial communities can move to new levels of inquiry. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

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

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

Characterization of antibiotic resistance and host-microbiome interactions in the human upper respiratory tract during influenza infection

BACKGROUND

The abundance and diversity of antibiotic resistance genes (ARGs) in the human respiratory microbiome remain poorly characterized. In the context of influenza virus infection, interactions between the virus, the host, and resident bacteria with pathogenic potential are known to complicate and worsen disease, resulting in coinfection and increased morbidity and mortality of infected individuals. When pathogenic bacteria acquire antibiotic resistance, they are more difficult to treat and of global health concern. Characterization of ARG expression in the upper respiratory tract could help better understand the role antibiotic resistance plays in the pathogenesis of influenza-associated bacterial secondary infection.

RESULTS

Thirty-seven individuals participating in the Household Influenza Transmission Study (HITS) in Managua, Nicaragua, were selected for this study. We performed metatranscriptomics and 16S rRNA gene sequencing analyses on nasal and throat swab samples, and host transcriptome profiling on blood samples. Individuals clustered into two groups based on their microbial gene expression profiles, with several microbial pathways enriched with genes differentially expressed between groups. We also analyzed antibiotic resistance gene expression and determined that approximately 25% of the sequence reads that corresponded to antibiotic resistance genes mapped to Streptococcus pneumoniae and Staphylococcus aureus. Following construction of an integrated network of ARG expression with host gene co-expression, we identified several host key regulators involved in the host response to influenza virus and bacterial infections, and host gene pathways associated with specific antibiotic resistance genes.

CONCLUSIONS

This study indicates the host response to influenza infection could indirectly affect antibiotic resistance gene expression in the respiratory tract by impacting the microbial community structure and overall microbial gene expression. Interactions between the host systemic responses to influenza infection and antibiotic resistance gene expression highlight the importance of viral-bacterial co-infection in acute respiratory infections like influenza. Video abstract.

Longitudinal survey of microbiome associated with particulate matter in a megacity

BACKGROUND

While the physical and chemical properties of airborne particulate matter (PM) have been extensively studied, their associated microbiome remains largely unexplored. Here, we performed a longitudinal metagenomic survey of 106 samples of airborne PM_2.5 and PM₁₀ in Beijing over a period of 6 months in 2012 and 2013, including those from several historically severe smog events.

RESULTS

We observed that the microbiome composition and functional potential were conserved between PM_2.5 and PM₁₀, although considerable temporal variations existed. Among the airborne microorganisms, Propionibacterium acnes, Escherichia coli, Acinetobacter lwoffii, Lactobacillus amylovorus, and Lactobacillus reuteri dominated, along with several viral species. We further identified an extensive repertoire of genes involved in antibiotic resistance and detoxification, including transporters, transpeptidases, and thioredoxins. Sample stratification based on Air Quality Index (AQI) demonstrated that many microbial species, including those associated with human, dog, and mouse feces, exhibit AQI-dependent incidence dynamics. The phylogenetic and functional diversity of air microbiome is comparable to those of soil and water environments, as its composition likely derives from a wide variety of sources.

CONCLUSIONS

Airborne particulate matter accommodates rich and dynamic microbial communities, including a range of microbial elements that are associated with potential health consequences.

Methods in Lung Microbiome Research

The lung microbiome is associated with host immune response and health outcomes in experimental models and patient cohorts. Lung microbiome research is increasing in volume and scope; however, there are no established guidelines for study design, conduct, and reporting of lung microbiome studies. Standardized approaches to yield reliable and reproducible data that can be synthesized across studies will ultimately improve the scientific rigor and impact of published work and greatly benefit microbiome research. In this review, we identify and address several key elements of microbiome research: conceptual modeling and hypothesis framing; study design; experimental methodology and pitfalls; data analysis; and reporting considerations. Finally, we explore possible future directions and research opportunities. Our goal is to aid investigators who are interested in this burgeoning research area and hopefully provide the foundation for formulating consensus approaches in lung microbiome research.

Deciphering the Ecology of Cystic Fibrosis Bacterial Communities: Towards Systems-Level Integration

Despite over a decade of cystic fibrosis (CF) microbiome research, much remains to be learned about the overall composition, metabolic activities, and pathogenicity of the microbes in CF airways, limiting our understanding of the respiratory microbiome's relation to disease. Systems-level integration and modeling of host-microbiome interactions may allow us to better define the relationships between microbiological characteristics, disease status, and treatment response. In this way, modeling could pave the way for microbiome-based development of predictive models, individualized treatment plans, and novel therapeutic approaches, potentially serving as a paradigm for approaching other chronic infections. In this review, we describe the challenges facing this effort and propose research priorities for a systems biology approach to CF lung disease.

Nasal Resistome Development in Infants With Cystic Fibrosis in the First Year of Life

Polymicrobial infections of the respiratory tract due to antibiotic resistant bacteria are a great concern in patients with cystic fibrosis (CF). We therefore aimed at establishing a functional metagenomic method to analyze the nasal resistome in infants with CF within the first year of life. We included samples from patients before antibiotic treatment, which allowed obtaining information regarding natural status of the resistome. In total, we analyzed 130 nasal swabs from 26 infants with CF and screened for β-lactams (ampicillin, amoxicillin-clavulanic acid, and cefuroxime) and other classes of antibiotic resistances (tetracycline, chloramphenicol and trimethoprim-sulfamethoxazole). For 69 swabs (53% of total), we found at least one non-susceptible phenotype. Analyses of the inserts recovered from non-susceptible clones by nanopore MinION sequencing revealed a large reservoir of resistance genes including mobile elements within the antibiotic naïve samples. Comparing the data of the resistome with the microbiota composition showed that the bacterial phyla and operational taxonomic units (OTUs) of the microbiota rather than the antibiotic treatment were associated with the majority of non-susceptible phenotypes in the resistome. Future studies will reveal if characterization of the resistome can help in clinical decision-making in patients with CF.

Antibiotic multidrug resistance in the cystic fibrosis airway microbiome is associated with decreased diversity

Background

Cystic fibrosis (CF) is associated with significant morbidity and early mortality due to recurrent acute and chronic lung infections. The chronic use of multiple antibiotics increases the possibility of multidrug resistance (MDR). Antibiotic susceptibility determined by culture-based techniques may not fully represent the resistance profile. The study objective was to detect additional antibiotic resistance using molecular methods and relate the presence of MDR to airway microbiome diversity and pulmonary function.

Methods

Bacterial DNA was extracted from sputum samples and amplified for the V4 region of the 16S rRNA gene. An qPCR array was used to detect antibiotic resistance genes. Clinical culture results and pulmonary function were also noted for each encounter.

Results

Six study participants contributed samples from 19 encounters. Those samples with MDR (n = 7) had significantly lower diversity measured by inverse Simpson's index than those without (n = 12) (2.193 ± 0.427 vs 6.023 ± 1.564, p = 0.035). Differential abundance showed that samples with MDR had more Streptococcus (p = 0.002) and Alcaligenaceae_unclassified (p = 0.002). Pulmonary function was also decreased when MDR was present (FEV₁, 51 ± 22.9 vs 77 ± 26.7, p = 0.054; FVC, 64.5 ± 22.7 vs 91.6 ± 27.7, p = 0.047).

Conclusions

The presence of MDR within the CF airway microbiome was associated with decreased microbial diversity, the presence of Alcaligenes, and decreased pulmonary function.

Benchmark Evaluation of True Single Molecular Sequencing to Determine Cystic Fibrosis Airway Microbiome Diversity

Cystic fibrosis (CF) is an autosomal recessive disease associated with recurrent lung infections that can lead to morbidity and mortality. The impact of antibiotics for treatment of acute pulmonary exacerbations on the CF airway microbiome remains unclear with prior studies giving conflicting results and being limited by their use of 16S ribosomal RNA sequencing. Our primary objective was to validate the use of true single molecular sequencing (tSMS) and PathoScope in the analysis of the CF airway microbiome. Three control samples were created with differing amounts of Burkholderia cepacia, Pseudomonas aeruginosa, and Prevotella melaninogenica, three common bacteria found in cystic fibrosis lungs. Paired sputa were also obtained from three study participants with CF before and >6 days after initiation of antibiotics. Antibiotic resistant B. cepacia and P. aeruginosa were identified in concurrently obtained respiratory cultures. Direct sequencing was performed using tSMS, and filtered reads were aligned to reference genomes from NCBI using PathoScope and Kraken and unique clade-specific marker genes using MetaPhlAn. A total of 180–518 K of 6–12 million filtered reads were aligned for each sample. Detection of known pathogens in control samples was most successful using PathoScope. In the CF sputa, alpha diversity measures varied based on the alignment method used, but similar trends were found between pre- and post-antibiotic samples. PathoScope outperformed Kraken and MetaPhlAn in our validation study of artificial bacterial community controls and also has advantages over Kraken and MetaPhlAn of being able to determine bacterial strains and the presence of fungal organisms. PathoScope can be confidently used when evaluating metagenomic data to determine CF airway microbiome diversity.

Airway microbial metagenomics

High-throughput untargeted metagenome sequencing provides information about the composition of the microbial communities of viruses, bacteria, archaea and unicellular eukaryotes in the habitat of interest. This review outlines the sampling, processing, sequencing and bioinformatic analysis of secretions of the respiratory tract and summarizes our current knowledge of the upper and lower human airways metagenome in health and disease.

A Metagenomic and in Silico Functional Prediction of Gut Microbiota Profiles May Concur in Discovering New Cystic Fibrosis Patient-Targeted Probiotics

Cystic fibrosis (CF) is a life-limiting hereditary disorder that results in aberrant mucosa in the lungs and digestive tract, chronic respiratory infections, chronic inflammation, and the need for repeated antibiotic treatments. Probiotics have been demonstrated to improve the quality of life of CF patients. We investigated the distribution of gut microbiota (GM) bacteria to identify new potential probiotics for CF patients on the basis of GM patterns. Fecal samples of 28 CF patients and 31 healthy controls (HC) were collected and analyzed by 16S rRNA-based pyrosequencing analysis of GM, to produce CF-HC paired maps of the distribution of operational taxonomic units (OTUs), and by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) for Kyoto Encyclopedia of Genes and Genomes (KEGG) biomarker prediction. The maps were scanned to highlight the distribution of bacteria commonly claimed as probiotics, such as bifidobacteria and lactobacilli, and of butyrate-producing colon bacteria, such as Eubacterium spp. and Faecalibacterium prausnitzii. The analyses highlighted 24 OTUs eligible as putative probiotics. Eleven and nine species were prevalently associated with the GM of CF and HC subjects, respectively. Their KEGG prediction provided differential CF and HC pathways, indeed associated with health-promoting biochemical activities in the latter case. GM profiling and KEGG biomarkers concurred in the evaluation of nine bacterial species as novel putative probiotics that could be investigated for the nutritional management of CF patients.