Sputum DNA sequencing in cystic fibrosis: non-invasive access to the lung microbiome and to pathogen details

Clinical application of targeted next-generation sequencing utilizing bronchoalveolar lavage fluid in thoracic surgery ICU patients with suspected pulmonary infections

AIMS

The aim of this prospective study was to evaluate the diagnostic value of targeted next-generation sequencing (tNGS) in identifying pathogens from bronchoalveolar lavage fluid (BALF) in thoracic surgery ICU patients, offering additional diagnostic methods for clinical practice.

METHODS AND RESULTS

We collected clinical data from patients with suspected pulmonary infections in the thoracic surgery ICU of the Second Affiliated Hospital of Air Force Medical University. A total of 50 patients were enrolled in this study. Traditional pathogen detection (TPD), involving culture and loop-mediated isothermal amplification assays for 12 pathogens, along with tNGS, was employed for pathogen identification in BALF samples. Our findings demonstrated that the positive rate of tNGS was significantly greater than that of TPD (96% vs. 68%). Among the 50 samples analyzed, tNGS identified a total of 165 pathogens, whereas TPD detected only 48 pathogens. The TPD method primarily detected bacteria and fungi, whereas tNGS exhibited broader capabilities, identifying 104 cases with bacteria, 19 with fungi, 34 with DNA viruses, and 8 with RNA viruses. Notably, tNGS displayed enhanced efficiency in detecting atypical pathogens such as fungi, DNA viruses and RNA viruses. Furthermore, compared with TPD, tNGS demonstrated superior sensitivity (95.83% vs. 68.75%).

CONCLUSIONS

tNGS technology, characterized by its high sensitivity, specificity, and cost-effectiveness, holds great promise as a reliable diagnostic tool for assessing pulmonary infections in the thoracic surgery ICU patients.

Metrological evaluation of DNA extraction method effects on the bacterial microbiome and resistome in sputum

Targeted high-throughput sequencing (HTS) has revolutionized the way we look at bacterial communities. It can be used for the species-specific detection of bacteria as well as for the determination of the microbiome and resistome and can be applied to samples from almost any environment. However, the results of targeted HTS can be influenced by many factors, which poses a major challenge for its use in clinical diagnostics. In this study, we investigated the impact of the DNA extraction method on the determination of the bacterial microbiome and resistome by targeted HTS using principles from metrology and diagnostics such as repeatability and analytical sensitivity. Sputum samples spiked with Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa at three different concentrations (103-106 cells/mL) were used. DNA was extracted from each sample on 2 separate days in three replicates each using three different extraction methods based on cetrimonium bromide, magnetic beads, and silica membranes. All three spiked bacteria were detected in sputum, and the DNA extraction method had no significant effect on detection. However, the DNA extraction method had significant effects on the composition of the microbiome and the resistome. The sequencing results were repeatable in the majority of cases. The silica membrane-based DNA extraction kit provided the most repeatable results and the highest diversity of the microbiome and resistome. Targeted HTS has been shown to be a reliable tool for determining the microbiome and resistome; however, the method of DNA extraction should be carefully selected to minimize its impact on the results.

IMPORTANCE

High-throughput sequencing (HTS) is one of the crucial new technologies that gives us insights into previously hidden parts of microbial communities. The DNA extraction method is an important step that can have a major impact on the results, and understanding this impact is of paramount importance for their reliable interpretation. Our results are of great value for the interpretation of sputum microbiome and resistome results obtained by targeted HTS. Our findings allow for a more rational design of future microbiome studies, which would lead to higher repeatability of results and easier comparison between different laboratories. This could also facilitate the introduction of targeted HTS in clinical microbiology for reliable identification of pathogenic bacteria and testing for antimicrobial resistance (AMR). As AMR is a major threat to public health, the improved methods for determining AMR would bring great benefits to both the healthcare system and society as a whole.

Microbiome-Mucosal Immunity Nexus: Driving Forces in Respiratory Disease Progression

The importance of the complex interplay between the microbiome and mucosal immunity, particularly within the respiratory tract, has gained significant attention due to its potential implications for the severity and progression of lung diseases. Therefore, this review summarizes the specific interactions through which the respiratory tract-specific microbiome influences mucosal immunity and ultimately impacts respiratory health. Furthermore, we discuss how the microbiome affects mucosal immunity, considering tissue-specific variations, and its capacity in respiratory diseases containing asthma, chronic obstructive pulmonary disease, and lung cancer. Additionally, we investigate the external factors which affect the relationship between respiratory microbiome and mucosal immune responses. By exploring these intricate interactions, this review provides valuable insights into the potential for microbiome-based interventions to modulate mucosal immunity and alleviate the severity of respiratory diseases.

Clinical characteristics and microbial signatures in the lower airways of diabetic and nondiabetic patients with pneumonia

Background

The microbial signatures in diabetes with pneumonia and the risk factors of severe pneumonia (SP) in diabetic patients are not clear. Our study explored microbial signatures and the association between clinical characteristics and SP then constructed a risk model to find effective biomarkers for predicting pneumonia severity.

Methods

Our study was conducted among 273 patients with pneumonia diagnosed and treated in our hospital from January 2018 to May 2021. Bronchoalveolar lavage fluid (BALF) samples and clinical data were collected. Metagenomic sequencing was applied after extracting the DNA from samples. Appropriate statistical methods were used to compare the microbial signatures and clinical characteristics in patients with or without diabetes mellitus (DM).

Results

In total, sixty-one pneumonia patients with diabetes and 212 pneumonia patients without diabetes were included. Sixty-six differential microorganisms were found to be associated with SP in diabetic patients. Some microbes correlated with clinical indicators of SP. The prediction model for SP was established and the receiver operating characteristic (ROC) curve demonstrated its accuracy, with the sensitivity and specificity of 0.82 and 0.91, respectively.

Conclusions

Some microorganisms affect the severity of pneumonia. We identified the microbial signatures in the lower airways and the association between clinical characteristics and SP. The predictive model was more accurate in predicting SP by combining microbiological indicators and clinical characteristics, which might be beneficial to the early identification and management of patients with SP.

Clinical applications and challenges of metagenomic next-generation sequencing in the diagnosis of pediatric infectious disease

Infectious diseases seriously threaten the lives of children. Timely and accurate detection of pathogenic microorganisms and targeted medication are the keys to the diagnosing and treatment of infectious diseases in children. The next-generation metagenomic sequencing technology has attracted great attention in infectious diseases because of its characteristics such as no culture, high throughput, short detection cycle, wide coverage, and a good application prospect. In this paper, we review the studies of metagenomic next-generation sequencing in pediatric infectious diseases and analyze the challenges of its application in pediatric diseases.

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.

Genomic and Metagenomic Insights into the Distribution of Nicotine-degrading Enzymes in Human Microbiota

Introduction

Nicotine degradation is a new strategy to block nicotine-induced pathology. The potential of human microbiota to degrade nicotine has not been explored.

Aims

This study aimed to uncover the genomic potentials of human microbiota to degrade nicotine.

Methods

To address this issue, we performed a systematic annotation of Nicotine-Degrading Enzymes (NDEs) from genomes and metagenomes of human microbiota. A total of 26,295 genomes and 1,596 metagenomes for human microbiota were downloaded from public databases and five types of NDEs were annotated with a custom pipeline. We found 959 NdhB, 785 NdhL, 987 NicX, three NicA1, and three NicA2 homologs.

Results

Genomic classification revealed that six phylum-level taxa, including Proteobacteria, Firmicutes, Firmicutes_A, Bacteroidota, Actinobacteriota, and Chloroflexota, can produce NDEs, with Proteobacteria encoding all five types of NDEs studied. Analysis of NicX prevalence revealed differences among body sites. NicX homologs were found in gut and oral samples with a high prevalence but not found in lung samples. NicX was found in samples from both smokers and non-smokers, though the prevalence might be different.

Conclusion

This study represents the first systematic investigation of NDEs from the human microbiota, providing new insights into the physiology and ecological functions of human microbiota and shedding new light on the development of nicotine-degrading probiotics for the treatment of smoking-related diseases.

The alterations of oral, airway and intestine microbiota in chronic obstructive pulmonary disease: a systematic review and meta-analysis

Background

Increasing evidence indicates the microbial ecology of chronic obstructive pulmonary disease (COPD) is intricately associated with the disease's status and severity, and distinct microbial ecological variations exist between COPD and healthy control (HC). This systematic review and meta-analysis aimed to summarize microbial diversity indices and taxa relative abundance of oral, airway, and intestine microbiota of different stages of COPD and HC to make comparisons.

Methods

A comprehensive systematic literature search was conducted in PubMed, Embase, the Web of Science, and the Cochrane Library databases to identify relevant English articles on the oral, airway, and intestine microbiota in COPD published between 2003 and 8 May 2023. Information on microbial diversity indices and taxa relative abundance of oral, airway, and intestine microbiota was collected for comparison between different stages of COPD and HC.

Results

A total of 20 studies were included in this review, involving a total of 337 HC participants, 511 COPD patients, and 154 AECOPD patients. We observed that no significant differences in alpha diversity between the participant groups, but beta diversity was significantly different in half of the included studies. Compared to HC, Prevotella, Streptococcus, Actinomyces, and Veillonella of oral microbiota in SCOPD were reduced at the genus level. Most studies supported that Haemophilus, Lactobacillus, and Pseudomonas were increased, but Veillonella, Prevotella, Actinomyces, Porphyromonas, and Atopobium were decreased at the genus level in the airway microbiota of SCOPD. However, the abundance of Haemophilus, Lactobacillus and Pseudomonas genera exhibited an increase, whereas Actinomyces and Porphyromonas showed a decrease in the airway microbiota of AECOPD compared to HC. And Lachnospira of intestine microbiota in SCOPD was reduced at the genus level.

Conclusion

The majority of published research findings supported that COPD exhibited decreased alpha diversity compared to HC. However, our meta-analysis does not confirm it. In order to further investigate the characteristics and mechanisms of microbiome in the oral-airway- intestine axis of COPD patients, larger-scale and more rigorous studies are needed.

Systematic review registration

PROSPERO (https://www.crd.york.ac.uk/prospero/), identifier CRD42023418726.

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.

Genomic attributes of airway commensal bacteria and mucosa

Microbial communities at the airway mucosal barrier are conserved and highly ordered, in likelihood reflecting co-evolution with human host factors. Freed of selection to digest nutrients, the airway microbiome underpins cognate management of mucosal immunity and pathogen resistance. We show here the initial results of systematic culture and whole-genome sequencing of the thoracic airway bacteria, identifying 52 novel species amongst 126 organisms that constitute 75% of commensals typically present in heathy individuals. Clinically relevant genes encode antimicrobial synthesis, adhesion and biofilm formation, immune modulation, iron utilisation, nitrous oxide (NO) metabolism and sphingolipid signalling. Using whole-genome content we identify dysbiotic features that may influence asthma and chronic obstructive pulmonary disease. We match isolate gene content to transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways to sustain host interactions with microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosa in lung diseases of global significance.

Lung microbiome: new insights into the pathogenesis of respiratory diseases

The lungs were long thought to be sterile until technical advances uncovered the presence of the lung microbial community. The microbiome of healthy lungs is mainly derived from the upper respiratory tract (URT) microbiome but also has its own characteristic flora. The selection mechanisms in the lung, including clearance by coughing, pulmonary macrophages, the oscillation of respiratory cilia, and bacterial inhibition by alveolar surfactant, keep the microbiome transient and mobile, which is different from the microbiome in other organs. The pulmonary bacteriome has been intensively studied recently, but relatively little research has focused on the mycobiome and virome. This up-to-date review retrospectively summarizes the lung microbiome's history, composition, and function. We focus on the interaction of the lung microbiome with the oropharynx and gut microbiome and emphasize the role it plays in the innate and adaptive immune responses. More importantly, we focus on multiple respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), fibrosis, bronchiectasis, and pneumonia. The impact of the lung microbiome on coronavirus disease 2019 (COVID-19) and lung cancer has also been comprehensively studied. Furthermore, by summarizing the therapeutic potential of the lung microbiome in lung diseases and examining the shortcomings of the field, we propose an outlook of the direction of lung microbiome research.

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.

Saponin treatment for eukaryotic DNA depletion alters the microbial DNA profiles by reducing the abundance of Gram-negative bacteria in metagenomics analyses

Background: Recent advances in microbiome sequencing techniques have provided new insights into the role of the microbiome on human health with potential diagnostic implications. However, these developments are often hampered by the presence of a large amount of human DNA interfering with the analysis of the bacterial content. Nowadays, extensive scientific literature focuses on eukaryotic DNA depletion methods, which successfully remove host DNA in microbiome studies, even if a precise assessment of the impact on bacterial DNA is often missing. Methods: Here, we have investigated a saponin-based DNA isolation protocol commonly applied to different biological matrices to deplete the released host DNA. Results: The bacterial DNA obtained was used to assess the relative abundance of bacterial and human DNA, revealing that the inclusion of 2.5% wt/vol saponin allowed the depletion of most of the host's DNA in favor of bacterial DNA enrichment. However, shotgun metagenomic sequencing showed inaccurate microbial profiles of the DNA samples, highlighting an erroneous increase in Gram-positive DNA. Even the application of 0.0125% wt/vol saponin altered the bacterial profile by depleting Gram-negative bacteria, resulting in an overall increase of Gram-positive bacterial DNA. Conclusion: The application of the saponin-based protocol drastically changes the detection of the microbial composition of human-related biological specimens. In this context, we revealed that saponin targets not only host cells but also specific bacterial cells, thus inducing a drastic reduction in the profiling of Gram-negative bacterial DNA.

Genomic Analyses of Longitudinal Mycobacterium abscessus Isolates in a Multicenter Cohort Reveal Parallel Signatures of In-Host Adaptation

BACKGROUND

Nontuberculous mycobacteria (NTM) are ubiquitous in the environment and an increasingly frequent cause of opportunistic infections. Mycobacterium abscessus complex (MABC) is one of the major NTM lung pathogens that disproportionately colonize and infect the lungs of individuals with cystic fibrosis (CF). MABC infection can persist for years, and antimicrobial treatment is frequently ineffective.

METHODS

We sequenced the genomes of 175 isolates longitudinally collected from 30 patients with MABC lung infection. We contextualized our cohort amidst the broader MABC phylogeny and investigated genes undergoing parallel adaptation across patients. Finally, we tested the phenotypic consequences of parallel mutations by conducting antimicrobial resistance and mercury-resistance assays.

RESULTS

We identified highly related isolate pairs across hospital centers with low likelihood of transmission. We further annotated nonrandom parallel mutations in 22 genes and demonstrated altered macrolide susceptibility co-occurring with a nonsynonymous whiB1 mutation. Finally, we highlighted a 23-kb mercury-resistance plasmid whose loss during chronic infection conferred phenotypic susceptibility to organic and nonorganic mercury compounds.

CONCLUSIONS

We characterized parallel genomic processes through which MABC is adapting to promote survival within the host. The within-lineage polymorphisms we observed have phenotypic effects, potentially benefiting fitness in the host at the putative detriment of environmental survival.

Genome-scale metabolic modeling of Aspergillus fumigatus strains reveals growth dependencies on the lung microbiome

Aspergillus fumigatus, an opportunistic human pathogen, frequently infects the lungs of people with cystic fibrosis and is one of the most common causes of infectious-disease death in immunocompromised patients. Here, we construct 252 strain-specific, genome-scale metabolic models of this important fungal pathogen to study and better understand the metabolic component of its pathogenic versatility. The models show that 23.1% of A. fumigatus metabolic reactions are not conserved across strains and are mainly associated with amino acid, nucleotide, and nitrogen metabolism. Profiles of non-conserved reactions and growth-supporting reaction fluxes are sufficient to differentiate strains, for example by environmental or clinical origin. In addition, shotgun metagenomics analysis of sputum from 40 cystic fibrosis patients (15 females, 25 males) before and after diagnosis with an A. fumigatus colonization suggests that the fungus shapes the lung microbiome towards a more beneficial fungal growth environment associated with aromatic amino acid availability and the shikimate pathway. Our findings are starting points for the development of drugs or microbiome intervention strategies targeting fungal metabolic needs for survival and colonization in the non-native environment of the human lung.

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.

Utilizing Metagenomic Next-Generation Sequencing (mNGS) for Rapid Pathogen Identification and to Inform Clinical Decision-Making: Results from a Large Real-World Cohort

INTRODUCTION

Clinical metagenomic next-generation sequencing (mNGS) has proven to be a powerful diagnostic tool in pathogen detection. However, its clinical utility has not been thoroughly evaluated.

METHODS

In this single-center prospective study at the First Affiliated Hospital of Soochow University, a total of 228 samples from 215 patients suspected of having acute or chronic infections between June 2018 and December 2018 were studied. Samples that met the mNGS quality control (QC) criteria (N = 201) were simultaneously analyzed using conventional tests (CTs), including multiple clinical microbiological tests and real-time PCR (if applicable).

RESULTS

Pathogen detection results of mNGS in the 201 QC-passed samples were compared to CTs and exhibited a sensitivity of 98.8%, specificity of 38.5%, and accuracy of 87.1%. Specifically, 109 out of 160 (68.1%) CT+/mNGS+ samples exhibited concordant results at the species/genus level, 25 samples (15.6%) showed overlapping results, while the remaining 26 samples (16.3%) had discordant results between the CT and mNGS assays. In addition, mNGS could identify pathogens at the species level, whereas only the genera of some pathogens could be identified by CT. In this cohort, mNGS results were used to guide treatment plans in 24 out of 41 cases that had available follow-up information, and the symptoms were improved in over 70% (17/24) of them.

CONCLUSION

Our data demonstrated the analytic performance of our mNGS pipeline for pathogen detection using a large clinical cohort and strongly supports the notion that in clinical practice, mNGS represents a valuable supplementary tool to CTs to rapidly determine etiological factors of various types of infection and to guide treatment decision-making.

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.

The impact of infection with COVID-19 on the respiratory microbiome: A narrative review

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has affected millions of individuals with various implications. Consistent with the crucial role of the microbiome in determining health and disease in humans, various studies have investigated the gut and respiratory microbiome effect on the COVID-19. Microbiota dysbiosis might support the entry, replication, and establishment of SARS-CoV-2 infection by modulating various mechanisms. One of the main mechanisms that the modulation of respiratory microbiota composition during the COVID-19 infection affects the magnitude of the disease is changes in innate and acquired immune responses, including inflammatory markers and cytokines and B- and T-cells. The diversity of respiratory microbiota in COVID-19 patients is controversial; some studies reported low microbial diversity, while others found high diversity, suggesting the role of respiratory microbiota in this disease. Modulating microbiota diversity and profile by supplementations and nutrients can be applied prophylactic and therapeutic in combating COVID-19. Here, we discussed the lung microbiome dysbiosis during various lung diseases and its interaction with immune cells, focusing on COVID-19.

Comparative analysis of the lung microbiota in patients with respiratory infections, tuberculosis, and lung cancer: A preliminary study

Recent evidence suggests that lung microbiota can be recognized as one of the ecological determinants of various respiratory diseases. However, alterations in the lung microbiota and associated lung immunity in these respiratory diseases remain unclear. To compare the lung microbiota and lung immune profiles in common respiratory diseases, a total of 78 patients were enrolled in the present study, including 21 patients with primary pulmonary tuberculosis (PTB), eight patients with newly diagnosed lung cancer (LC), and 49 patients with community-acquired pneumonia (CAP). Bronchoalveolar lavage fluid (BALF) was collected for microbiota and cytokine analyses. With MiSeq sequencing system, increased bacterial alpha-diversity and richness were observed in patients with LC than in those with PTB and CAP. Linear discriminant analysis effect size revealed that CAP-associated pulmonary microbiota were significantly different between the PTB and LC groups. More key functionally different genera were found in the PTB and LC groups than in the CAP group. The interaction network revealed stronger positive and negative correlations among these genera in the LC group than in the other two groups. However, increased BALF cytokine profiles were observed in the PTB group than in the other two groups, while BALF cytokines were correlated with key functional bacteria. This comparative study provides evidence for the associations among altered lung microbiota, BALF inflammation, and different respiratory disorders, which provides insight into the possible roles and mechanisms of pulmonary microbiota in the progression of respiratory disorders.

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.

Genome Capture Sequencing Selectively Enriches Bacterial DNA and Enables Genome-Wide Measurement of Intrastrain Genetic Diversity in Human Infections

Within-host evolution produces genetic diversity in bacterial strains that cause chronic human infections. However, the lack of facile methods to measure bacterial allelic variation in clinical samples has limited understanding of intrastrain diversity's effects on disease. Here, we report a new method termed genome capture sequencing (GenCap-Seq) in which users inexpensively make hybridization probes from genomic DNA or PCR amplicons to selectively enrich and sequence targeted bacterial DNA from clinical samples containing abundant human or nontarget bacterial DNA. GenCap-Seq enables accurate measurement of allele frequencies over targeted regions and is scalable from specific genes to entire genomes, including the strain-specific accessory genome. The method is effective with samples in which target DNA is rare and inhibitory and DNA-degrading substances are abundant, including human sputum and feces. In proof-of-principle experiments, we used GenCap-Seq to investigate the responses of diversified Pseudomonas aeruginosa populations chronically infecting the lungs of people with cystic fibrosis to in vivo antibiotic exposure, and we found that treatment consistently reduced intrastrain genomic diversity. In addition, analysis of gene-level allele frequency changes suggested that some genes without conventional resistance functions may be important for bacterial fitness during in vivo antibiotic exposure. GenCap-Seq's ability to scalably enrich targeted bacterial DNA from complex samples will enable studies on the effects of intrastrain and intraspecies diversity in human infectious disease. IMPORTANCE Genetic diversity evolves in bacterial strains during human infections and could affect disease manifestations and treatment resistance. However, the extent of diversity present in vivo and its changes over time are difficult to measure by conventional methods. We developed a novel approach, GenCap-Seq, to enrich microbial DNA from complex human samples like sputum and feces for genome-wide measurements of bacterial allelic diversity. The approach is inexpensive, scalable to encompass entire targeted genomes, and works in the presence of abundant untargeted nucleic acids and inhibiting substances. We used GenCap-Seq to investigate in vivo responses of diversified bacterial strains to antibiotic treatment. This method will enable new ideas about the effects of intrastrain diversity on human infections to be tested.

Quick and wide-range taxonomical repertoire establishment of the cystic fibrosis lung microbiota by tandem mass spectrometry on sputum samples

Microorganisms proteotyping by tandem mass spectrometry has been recently shown as a powerful methodology to identify the wide-range taxonomy and biomass of microbiota. Sputum is the recommended specimen for routine microbiological monitoring of Cystic Fibrosis (CF) patients but has been rarely submitted to tandem mass spectrometry-based proteotyping. In this study, we compared the microbial components of spontaneous and induced sputum samples from three cystic fibrosis patients. Although the presence of microbial proteins is much lower than host proteins, we report that the microbiota’s components present in the samples can be identified, as well as host biomarkers and functional insights into the microbiota. No significant difference was found in microorganism abundance between paired spontaneous and induced sputum samples. Microbial proteins linked to resistance, iron uptake, and biofilm-forming ability were observed in sputa independently of the sampling method. This unbiased and enlarged view of the CF microbiome could be highly complementary to culture and relevant for the clinical management of CF patients by improving knowledge about the host-pathogen dynamics and CF pathophysiology.

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.

The respiratory microbiota alpha-diversity in chronic lung diseases: first systematic review and meta-analysis

Background

While there seems to be a consensus that a decrease in gut microbiome diversity is related to a decline in health status, the associations between respiratory microbiome diversity and chronic lung disease remain a matter of debate. We provide a systematic review and meta-analysis of studies examining lung microbiota alpha-diversity in patients with asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF) or bronchiectasis (NCFB), in which a control group based on disease status or healthy subjects is provided for comparison.

Results

We reviewed 351 articles on title and abstract, of which 27 met our inclusion criteria for systematic review. Data from 24 of these studies were used in the meta-analysis. We observed a trend that CF patients have a less diverse respiratory microbiota than healthy individuals. However, substantial heterogeneity was present and detailed using random-effects models, which limits the comparison between studies.

Conclusions

Knowledge on respiratory microbiota is under construction, and for the moment, it seems that alpha-diversity measurements are not enough documented to fully understand the link between microbiota and health, excepted in CF context which represents the most studied chronic respiratory disease with consistent published data to link alpha-diversity and lung function. Whether differences in respiratory microbiota profiles have an impact on chronic respiratory disease symptoms and/or evolution deserves further exploration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02132-4.

Reducing human DNA bias in cystic fibrosis airway specimens for microbiome analysis

Next generation sequencing (NGS) has transformed our understanding of airway microbiology, however there are methodology limitations that require consideration. The presence of high concentrations of human DNA in clinical specimens can significantly impact sequencing of the microbiome, especially in low biomass samples. Here we compared three different methods (0.025% saponin, NEBNext Microbiome DNA enrichment kit, QIAamp DNA microbiome kit) for the reduction of human DNA from six CF sputum samples and determined the impact on the microbiome detected using 16S rRNA gene sequencing. Human DNA in undepleted CF sputum accounted for 94.3% of the total DNA. Saponin, the NEBNext kit and the QIAamp kit reduced human DNA levels by an average of 38.7%, 61.8% and 94.8%, respectively. None of the depletion methods reduced total bacterial DNA concentrations. QIAamp depletion did not influence taxa richness or alpha diversity however alterations to the core genera were noted following depletion. While all methods reduced human DNA in the CF sputum samples, the QIAamp DNA microbiome kit reduced Human DNA levels significantly while leaving bacterial DNA levels unchanged. Human DNA depletion in low biomass, human DNA-dense CF sputum samples is vital for improving bacterial resolution in the CF airway microbiome.

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.

Evaluation of Host Depletion and Extraction Methods for Shotgun Metagenomic Analysis of Bovine Vaginal Samples

The reproductive tract metagenome plays a significant role in the various reproductive system functions, including reproductive cycles, health, and fertility. One of the major challenges in bovine vaginal metagenome studies is host DNA contamination, which limits the sequencing capacity for metagenomic content and reduces the accuracy of untargeted shotgun metagenomic profiling. This is the first study comparing the effectiveness of different host depletion and DNA extraction methods for bovine vaginal metagenomic samples. The host depletion methods evaluated were slow centrifugation (Soft-spin), NEBNext Microbiome DNA Enrichment kit (NEBNext), and propidium monoazide (PMA) treatment, while the extraction methods were DNeasy Blood and Tissue extraction (DNeasy) and QIAamp DNA Microbiome extraction (QIAamp). Soft-spin and QIAamp were the most effective host depletion method and extraction methods, respectively, in reducing the number of cattle genomic content in bovine vaginal samples. The reduced host-to-microbe ratio in the extracted DNA increased the sequencing depth for microbial reads in untargeted shotgun sequencing. Bovine vaginal samples extracted with QIAamp presented taxonomical profiles which closely resembled the mock microbial composition, especially for the recovery of Gram-positive bacteria. Additionally, samples extracted with QIAamp presented extensive functional profiles with deep coverage. Overall, a combination of Soft-spin and QIAamp provided the most robust representation of the vaginal microbial community in cattle while minimizing host DNA contamination.

IMPORTANCE In addition to the host tissue collected during the sampling process, bovine vaginal samples are saturated with large amounts of extracellular DNA and secreted proteins that are essential for physiological purposes, including the reproductive cycle and immune defense. Due to the high host-to-microbe genome ratio, which hampers the sequencing efficacy for metagenome samples and the recovery of the actual metagenomic profiles, bovine vaginal samples cannot benefit from the full potential of shotgun sequencing. This is the first investigation on the most effective host depletion and extraction methods for bovine vaginal metagenomic samples. This study demonstrated an effective combination of host depletion and extraction methods, which harvested higher percentages of 16S rRNA genes and microbial reads, which subsequently led to a taxonomical profile that resembled the actual community and a functional profile with deeper coverage. A representative metagenomic profile is essential for investigating the role of the bovine vaginal metagenome for both reproductive function and susceptibility to infections.

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.

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

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

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation

Many pathways for hydrocarbon degradation have been discovered, yet there are no dedicated tools to identify and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Here we present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database of 37 HMMs of marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate its application in analyzing high-throughput sequence data by predicting hydrocarbon utilization in large metagenomic datasets from diverse environments. CANT-HYD is available at https://github.com/dgittins/CANT-HYD-HydrocarbonBiodegradation.

A population-level strain genotyping method to study pathogen strain dynamics in human infections

A hallmark of chronic bacterial infections is the long-term persistence of 1 or more pathogen species at the compromised site. Repeated detection of the same bacterial species can suggest that a single strain or lineage is continually present. However, infection with multiple strains of a given species, strain acquisition and loss, and changes in strain relative abundance can occur. Detecting strain-level changes and their effects on disease is challenging because most methods require labor-intensive isolate-by-isolate analyses, and thus, only a few cells from large infecting populations can be examined. Here, we present a population-level method for enumerating and measuring the relative abundance of strains called population multi-locus sequence typing (PopMLST). The method exploits PCR amplification of strain-identifying polymorphic loci, next-generation sequencing to measure allelic variants, and informatic methods to determine whether variants arise from sequencing errors or low-abundance strains. These features enable PopMLST to simultaneously interrogate hundreds of bacterial cells that are cultured en masse from patient samples or are present in DNA directly extracted from clinical specimens without ex vivo culture. This method could be used to detect epidemic or super-infecting strains, facilitate understanding of strain dynamics during chronic infections, and enable studies that link strain changes to clinical outcomes.

Impact of Anaerobic Antibacterial Spectrum on Cystic Fibrosis Airway Microbiome Diversity and Pulmonary Function

BACKGROUND

The role of anaerobic organisms in the cystic fibrosis (CF) lung microbiome is unclear. Our objectives were to investigate the effect of broad (BS) versus narrow (NS) spectrum antianaerobic antibiotic activity on lung microbiome diversity and pulmonary function, hypothesizing that BS antibiotics would cause greater change in microbiome diversity without a significant improvement in lung function.

METHODS

Pulmonary function tests and respiratory samples were collected prospectively in persons with CF before and after treatment for pulmonary exacerbations. Treatment antibiotics were classified as BS or NS. Gene sequencing data from 16S rRNA were used for diversity analysis and bacterial genera classification. We compared the effects of BS versus NS on diversity indices, lung function and anaerobic/aerobic ratios. Statistical significance was determined by multilevel mixed-effects generalized linear models and mixed-effects regression models.

RESULTS

Twenty patients, 6-20 years of age, experienced 30 exacerbations. BS therapy had a greater effect on beta diversity than NS therapy when comparing time points before antibiotics to after and at recovery. After antibiotics, the NS therapy group had a greater return toward baseline forced expiratory volume at 1 second and forced expiratory flow 25%-75% values than the BS group. The ratio of anaerobic/aerobic organisms showed a predominance of anaerobes in the NS group with aerobes dominating in the BS group.

CONCLUSIONS

BS antianaerobic therapy had a greater and possibly longer lasting effect on the lung microbiome of persons with CF, without achieving the recovery of pulmonary function seen with the NS therapy. Specific antibiotic therapies may affect disease progression by changing the airway microbiome.

A Microbial World: Could Metagenomic Next-Generation Sequencing Be Involved in Acute Respiratory Failure?

Background

The usefulness of metagenomic next-generation sequencing (mNGS) in identifying pathogens is being investigated. We aimed to compare the power of microbial identification between mNGS and various methods in patients with acute respiratory failure.

Methods

We reviewed 130 patients with respiratory failure, and 184 specimens including blood, bronchoalveolar lavage fluid (BALF), sputum, pleural effusion, ascitic fluid, and urine were tested by mNGS and conventional methods (culture, PCR). We also enrolled 13 patients to evaluate the power of mNGS and pathogen targets NGS (ptNGS) in microbial identifications. Clinical features and microbes detected were analyzed.

Results

mNGS outperformed the conventional method in the positive detection rate of Mycobacterium tuberculosis (MTB) (OR, ∞; 95% CI, 1–∞; P < 0.05), bacteria (OR, 3.7; 95% CI, 2.4–5.8; P < 0.0001), fungi (OR, 4.37; 95% CI, 2.7–7.2; P < 0.0001), mycoplasma (OR, 10.5; 95% CI, 31.8–115; P = 0.005), and virus (OR, ∞; 95% CI, 180.7–∞; P < 0.0001). We showed that 20 patients (28 samples) were detected with Pneumocystis jirovecii (P. jirovecii) by mNGS, but not by the conventional method, and most of those patients were immunocompromised. Read numbers of Klebsiella pneumoniae (K. pneumoniae), Acinetobacter baumannii (A. baumannii), Pseudomonas aeruginosa (P. aeruginosa), P. jirovecii, cytomegalovirus (CMV), and Herpes simplex virus 1 (HSV1) in BALF were higher than those in other sample types, and the read number of Candida albicans (C. albicans) in blood was higher than that in BALF. We found that orotracheal intubation and type 2 diabetes mellitus (T2DM) were associated with a higher detection rate of bacteria and virus by mNGS, immunosuppression was associated with a higher detection rate of fungi and virus by mNGS, and inflammatory markers were associated with mNGS-positive detection rate of bacteria. In addition, we observed preliminary results of ptNGS.

Conclusion

mNGS outperformed the conventional method in the detection of MTB, bacteria, fungi, mycoplasma, and virus. Orotracheal intubation, T2DM, immunosuppression, and inflammatory markers were associated with a higher detection rate of bacteria, fungi, and virus by mNGS. In addition, ptNGS results were consistent with the detection of abundant bacteria, fungi, and mycoplasma in our specimens.

Divergence of bacterial communities in the lower airways of CF patients in early childhood

Rationale

Chronic airway infection and inflammation resulting in progressive, obstructive lung disease is the leading cause of morbidity and mortality in cystic fibrosis. Understanding the lower airway microbiota across the ages can provide valuable insight and potential therapeutic targets.

Objectives

To characterize and compare the lower airway microbiota in cystic fibrosis and disease control subjects across the pediatric age spectrum.

Methods

Bronchoalveolar lavage fluid samples from 191 subjects (63 with cystic fibrosis) aged 0 to 21 years were collected along with relevant clinical data. We measured total bacterial load using quantitative polymerase chain reaction and performed 16S rRNA gene sequencing to characterize bacterial communities with species-level sensitivity for select genera. Clinical comparisons were investigated.

Measurements and main results

Cystic fibrosis samples had higher total bacterial load and lower microbial diversity, with a divergence from disease controls around 2–5 years of age, as well as higher neutrophilic inflammation relative to bacterial burden. Cystic fibrosis samples had increased abundance of traditional cystic fibrosis pathogens and decreased abundance of the Streptococcus mitis species group in older subjects. Interestingly, increased diversity in the heterogeneous disease controls was independent of diagnosis and indication. Sequencing was more sensitive than culture, and antibiotic exposure was more common in disease controls, which showed a negative relationship with load and neutrophilic inflammation.

Conclusions

Analysis of lower airway samples from people with cystic fibrosis and disease controls across the ages revealed key differences in airway microbiota and inflammation. The divergence in subjects during early childhood may represent a window of opportunity for intervention and additional study.

A LAMP-based system for rapid detection of eight common pathogens causing lower respiratory tract infections

Lower respiratory tract infections (LRTIs) are a leading cause of morbidity and mortality worldwide and lack a rapid diagnostic method. To improve the diagnosis of LRTIs, we established an available loop-mediated isothermal amplification (LAMP) assay for the detection of eight common lower respiratory pathogens, including Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Staphylococcus aureus, Escherichia coli, Haemophilus influenzae, Streptococcus pneumoniae, and Moraxella catarrhalis. The whole process can be achieved within 1 h (sample to results read out). We established an extraction free isothermal system. 528 sputum samples collected from patients suspected to have LRTIs were analyzed by the system (8 tests in each sample, a total of 4224 tests) and compared with the standard culture method (SCM). The samples with inconsistent results were further verified by Sanger sequencing and High-throughput sequencing (NGS). The detection limits of the LAMP assay for the 8 pathogens ranged from 10³ to 10⁴ CFU/mL. Upon testing 528 samples, the Kappa coefficients of all pathogens ranged between 0.5 and 0.7 indicated a moderate agreement between the LAMP assay and the SCM. All inconsistent samples were further verified by Sanger sequencing, we found that the developed LAMP assay had a higher consistency level with Sanger sequencing than the SCM for all pathogens. Additionally, when the NGS was set to a diagnostic gold standard, the specificity and sensitivity of the LAMP assay for LRTIs were 94.49% and 75.00%. The present study demonstrated that the developed LAMP has high consistency with the sequencing methods. Meanwhile, the LAMP assay has a higher detection rate compared to the SCM. It may be a powerful tool for rapid and reliable clinical diagnosis of LRTIs in primary hospitals.

The role of microbiota in respiratory health and diseases, particularly in tuberculosis

Trillions of beneficial and hostile microorganisms live in the human respiratory and gastrointestinal tracts, which act as gatekeepers in maintaining human health, i.e., protecting the body from pathogens by colonizing mucosal surfaces with microbiota-derived antimicrobial metabolites such as short-chain fatty acids or host-derived cytokines and chemokines. It is widely accepted that the microbiome interacts with each other and with the host in a mutually beneficial relationship. Microbiota in the respiratory tract may also play a crucial role in immune homeostasis, maturation, and maintenance of respiratory physiology. Anti-TB antibiotics may cause dysbiosis in the lung and intestinal microbiota, affecting colonization resistance and making the host more susceptible to Mycobacterium tuberculosis (M. tuberculosis) infection. This review discusses recent advances in our understanding of the lung microbiota composition, the lungs and intestinal microbiota related to respiratory health and diseases, microbiome sequencing and analysis, the bloodstream, and the lymphatic system that underpin the gut-lung axis in M. tuberculosis-infected humans and animals. We also discuss the gut-lung axis interactions with the immune system, the role of the microbiome in TB pathogenesis, and the impact of anti-TB antibiotic therapy on the microbiota in animals, humans, and drug-resistant TB individuals.

Altered Microbial Composition of Drug-Sensitive and Drug-Resistant TB Patients Compared with Healthy Volunteers

Mycobacterium tuberculosis infection has three discernible outcomes: active tuberculosis, latent tuberculosis, or clearance of the bacterium. The outcome of the infection depends on the interaction of the bacterium, the immune system, and the microbiome of the host. The current study uses 16S rRNA sequencing to determine the diversity and composition of the respiratory microbiome of drug-resistant and drug-sensitive tuberculosis patients as well as healthy volunteers. Tuberculosis patients exhibited increased microbial diversity and differentially abundant bacteria than healthy volunteers. Compositional differences were also observed when comparing drug-sensitive or -resistant tuberculosis patients. Finally, we defined and assessed the differences in the core sputum microbiota between tuberculosis patients and healthy volunteers. Our observations collectively suggest that in sputum, Mycobacterium tuberculosis infection is related to altered bacterial diversity and compositional differences of core members of the microbiome, with potential implications for the bacterial pulmonary ecosystem's stability and function.

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.

Pre-digest of unprotected DNA by Benzonase improves the representation of living skin bacteria and efficiently depletes host DNA

BACKGROUND

The identification of microbiota based on next-generation sequencing (NGS) of extracted DNA has drastically improved our understanding of the role of microbial communities in health and disease. However, DNA-based microbiome analysis cannot per se differentiate between living and dead microorganisms. In environments such as the skin, host defense mechanisms including antimicrobial peptides and low cutaneous pH result in a high microbial turnover, likely resulting in high numbers of dead cells present and releasing substantial amounts of microbial DNA. NGS analyses may thus lead to inaccurate estimations of microbiome structures and consequently functional capacities.

RESULTS

We investigated in this study the feasibility of a Benzonase-based approach (BDA) to pre-digest unprotected DNA, i.e., of dead microbial cells, as a method to overcome these limitations, thus offering a more accurate assessment of the living microbiome. A skin mock community as well as skin microbiome samples were analyzed using 16S rRNA gene sequencing and metagenomics sequencing after DNA extraction with and without a Benzonase digest to assess bacterial diversity patterns. The BDA method resulted in less reads from dead bacteria both in the skin mock community and skin swabs spiked with either heat-inactivated bacteria or bacterial-free DNA. This approach also efficiently depleted host DNA reads in samples with high human-to-microbial DNA ratios, with no obvious impact on the microbiome profile. We further observed that low biomass samples generate an α-diversity bias when the bacterial load is lower than 105 CFU and that Benzonase digest is not sufficient to overcome this bias.

CONCLUSIONS

The BDA approach enables both a better assessment of the living microbiota and depletion of host DNA reads. Video abstract.

Strain-Resolved Dynamics of the Lung Microbiome in Patients with Cystic Fibrosis

Cystic fibrosis patients frequently suffer from recurring respiratory infections caused by colonizing pathogenic and commensal bacteria. Although modern therapies can sometimes alleviate respiratory symptoms by ameliorating residual function of the protein responsible for the disorder, management of chronic respiratory infections remains an issue.

In cystic fibrosis, dynamic and complex communities of microbial pathogens and commensals can colonize the lung. Cultured isolates from lung sputum reveal high inter- and intraindividual variability in pathogen strains, sequence variants, and phenotypes; disease progression likely depends on the precise combination of infecting lineages. Routine clinical protocols, however, provide a limited overview of the colonizer populations. Therefore, a more comprehensive and precise identification and characterization of infecting lineages could assist in making corresponding decisions on treatment. Here, we describe longitudinal tracking for four cystic fibrosis patients who exhibited extreme clinical phenotypes and, thus, were selected from a pilot cohort of 11 patients with repeated sampling for more than a year. Following metagenomics sequencing of lung sputum, we find that the taxonomic identity of individual colonizer lineages can be easily established. Crucially, even superficially clonal pathogens can be subdivided into multiple sublineages at the sequence level. By tracking individual allelic differences over time, an assembly-free clustering approach allows us to reconstruct multiple lineage-specific genomes with clear structural differences. Our study showcases a culture-independent shotgun metagenomics approach for longitudinal tracking of sublineage pathogen dynamics, opening up the possibility of using such methods to assist in monitoring disease progression through providing high-resolution routine characterization of the cystic fibrosis lung microbiome.

Pulmonary Micro-Ecological Changes and Potential Microbial Markers in Lung Cancer Patients

The relationship between the microbiome and disease has been investigated for many years. As a highly malignant tumor, biomarkers for lung cancer are diverse. However, precision of these biomarkers has not yet been achieved. It has been confirmed that lung microecology changes in lung cancer patients compared with healthy individuals. Furthermore, the abundance of some bacterial species shows obvious changes, suggesting their potential use as a microbial marker for the detection of lung cancer. In addition, recent studies have confirmed that inflammation, immune response, virulence factors, and metabolism may be potential mechanisms linking the microbiome with carcinogenesis. In this review, microbiome studies of lung cancer, potential mechanisms, potential microbial markers, and the influence of the microbiome on the diagnosis and treatment of lung cancer are summarized, providing theoretical strategies for the diagnosis and treatment of lung cancer.

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.

[Analysis of Pulmonary Microbial Diversity in Patients with Advanced Lung Cancer Based on High-throughput Sequencing Technology]

BACKGROUND

The pulmonary microbiome is closely related to the occurrence of pulmonary diseases. The morbidity and mortality of lung cancer are relatively high in the world. It has been confirmed that lung microecology changes in lung cancer patients compared with healthy individuals. Furthermore, the abundance of some bacterial species shows obvious changes, suggesting their potential use as a microbial marker for the detection of lung cancer. The composition of the pulmonary microbiome in patients with different histological types of lung cancer has not been determined. We aim to study the correlation and difference of microbiome between different histological types of lung cancer.

METHODS

Illumina HiSeq high-throughput sequencing technology was used to sequenced the 16S rDNA V3-V4 region of bacterial in sputum samples of patients with advanced lung cancer.

RESULTS

It was found that Streptococcus, Neisseria and Prevotella were the main bacteria of lung cancer patients. Advantage bacterium group differ between different histological types of lung cancer. Adenocarcinoma (AD) group was dominated by Streptococcus and Neisseria, followed by Veillonella. Small cell lung cancer (SCLC) group was dominated by Neisseria, followed by Streptococcus. Squamous carcinoma (SCC) group was dominated by Streptococcus, followed by Veillonella. Combined small cell lung cancer (C-SCLC) group was dominated by Streptococcus, followed by Prevotella.

CONCLUSIONS

The pulmonary bacterial microbiome of lung cancer of different histological types is different. This experiment enrichs the pulmonary bacterial microbiome data of lung cancer and fills the gap of pulmonary microbiome of small cell lung cancer.

Application of next generation sequencing-based rapid detection platform for microbiological diagnosis and drug resistance prediction in acute lower respiratory infection

Background

Acute lower respiratory infections (ALRIs) have a high mortality rate. We aimed to apply a platform that rapidly detects 36 microorganisms and 49 antibiotic resistance markers in the clinical diagnosis of ALRI and drug resistance prediction.

Methods

Multicenter collection of clinical samples from patients with ALRIs was carried out from 2017 to 2018. Sputum culture (SC) was performed, which provided two outcomes: the detected pathogens and the resistance to different antibiotics. Additionally, each sputum sample was used to extract deoxyribonucleic acids (DNAs) followed by high-throughput sequencing.

Results

Eleven commonly observed pathogens were surveyed, and for all samples with positive SC results (137 cases), the overall coverage was 95.62% according to the sequencing results. The receiver operating characteristic (ROC) curve was drawn, and cutoff reads of the most frequently detected pathogens were acquired. Overall, sequencing exhibited significantly higher sensitivity in the detection of pathogens compared with the traditional SC method, with a generally satisfactory specificity. Furthermore, we investigated the correlation between antibiotic resistance gene phenotypes and the actual outcomes of the drug sensitivity test, and some significant correlations were found, especially for the resistance to Amikacin in the presence of blaOXA7.

Conclusions

Sequencing-based sputum metagenomics can reveal a profile of the lung pathogen microbiome. The sequencing method offers both sufficient accuracy and significantly higher sensitivity in the detection of pathogens, and can be at least a complementary approach to traditional SC reporting. The sequencing technique also revealed some novel potential correlations between the presence of different pathogens, as well as new antimicrobial-resistant genes.

Role of pulmonary microorganisms in the development of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a chronic obstructive respiratory disease characterized by irreversible airway limitation and persistent respiratory symptoms. The main clinical symptoms of COPD are dyspnoea, chronic cough, and sputum. COPD is often accompanied by other respiratory diseases, which can cause worsening of the disease. COPD patients with dyspnoea and aggravation of cough and sputum symptoms represent acute exacerbations of COPD (AECOPD). There is mounting evidence suggesting that dysbiosis of pulmonary microbiota participates in the disease. However, investigations of dysbiosis of pulmonary microbiota and the disease are still in initial phases. To screen, diagnose, and treat this respiratory disease, integrating data from different studies can improve our understanding of the occurrence and development of COPD and AECOPD. In this review, COPD epidemiology and the primary triggering mechanism are explored. Emerging knowledge regarding the association of inflammation, caused by pulmonary microbiome imbalance, and changes in lung microbiome flora species involved in the development of the disease are also highlighted. These data will further our understanding of the pathogenesis of COPD and AECOPD and may yield novel strategies for the use of pulmonary microbiota as a potential therapeutic intervention.

Multi-Omics Approaches: The Key to Improving Respiratory Health in People With Cystic Fibrosis?

The advent of high-throughput multi-omics technologies has underpinned the expansion in lung microbiome research, increasing our understanding of the nature, complexity and significance of the polymicrobial communities harbored by people with CF (PWCF). Having established that structurally complex microbial communities exist within the airways, the focus of recent research has now widened to investigating the function and dynamics of the resident microbiota during disease as well as in health. With further refinement, multi-omics approaches present the opportunity to untangle the complex interplay between microbe-microbe and microbe-host interactions in the lung and the relationship with respiratory disease progression, offering invaluable opportunities to discover new therapeutic approaches for our management of airway infection in CF.

Maintenance tobramycin primarily affects untargeted bacteria in the CF sputum microbiome

RATIONALE

The most common antibiotic used to treat people with cystic fibrosis (PWCF) is inhaled tobramycin, administered as maintenance therapy for chronic Pseudomonas aeruginosa lung infections. While the effects of inhaled tobramycin on P. aeruginosa abundance and lung function diminish with continued therapy, this maintenance treatment is known to improve long-term outcomes, underscoring how little is known about why antibiotics work in CF infections, what their effects are on complex CF sputum microbiomes and how to improve these treatments.

OBJECTIVES

To rigorously define the effect of maintenance tobramycin on CF sputum microbiome characteristics.

METHODS AND MEASUREMENTS

We collected sputum from 30 PWCF at standardised times before, during and after a single month-long course of maintenance inhaled tobramycin. We used traditional culture, quantitative PCR and metagenomic sequencing to define the dynamic effects of this treatment on sputum microbiomes, including abundance changes in both clinically targeted and untargeted bacteria, as well as functional gene categories.

MAIN RESULTS

CF sputum microbiota changed most markedly by 1 week of antibiotic therapy and plateaued thereafter, and this shift was largely driven by changes in non-dominant taxa. The genetically conferred functional capacities (ie, metagenomes) of subjects' sputum communities changed little with antibiotic perturbation, despite taxonomic shifts, suggesting functional redundancy within the CF sputum microbiome.

CONCLUSIONS

Maintenance treatment with inhaled tobramycin, an antibiotic with demonstrated long-term mortality benefit, primarily impacted clinically untargeted bacteria in CF sputum, highlighting the importance of monitoring the non-canonical effects of antibiotics and other treatments to accurately define and improve their clinical impact.