Metagenomic Sequencing of the Chronic Obstructive Pulmonary Disease Upper Bronchial Tract Microbiome Reveals Functional Changes Associated with Disease Severity

Informed development of a multi-species biofilm in chronic obstructive pulmonary disease

Recent evidence indicates that microbial biofilm aggregates inhabit the lungs of COPD patients and actively contribute towards chronic colonization and repeat infections. However, there are no contextually relevant complex biofilm models for COPD research. In this study, a meta-analysis of the lung microbiome in COPD was used to inform development of an optimized biofilm model composed of genera highly associated with COPD. Bioinformatic analysis showed that although diversity matrices of COPD microbiomes were similar to healthy controls, and internal compositions made it possible to accurately differentiate between these cohorts (AUC = 0.939). Genera that best defined these patients included Haemophilus, Moraxella and Streptococcus. Many studies fail to account for fungi; therefore, Candida albicans was included in the creation of an interkingdom biofilm model. These organisms formed a biofilm capable of tolerating high concentrations of antimicrobial therapies with no significant reductions in viability. However, combined therapies of antibiotics and an antifungal resulted in significant reductions in viable cells throughout the biofilm (p < 0.05). This biofilm model is representative of the COPD lung microbiome and results from in vitro antimicrobial challenge experiments indicate that targeting both bacteria and fungi in these interkingdom communities will be required for more positive clinical outcomes.

Chronic obstructive pulmonary disease and the airway microbiome: A review for clinicians

Chronic obstructive pulmonary disease (COPD) is a complex heterogeneous disease characterized by progressive airflow limitation and chronic inflammation. The progressive development and long-term repeated acute exacerbation of COPD make many patients still unable to control the deterioration of the disease after active treatment, and even eventually lead to death. An increasing number of studies have shown that the occurrence and development of COPD are closely related to the composition and changes of airway microbiome. This article reviews the interaction between COPD and airway microbiome, the potential mechanisms of interaction, and the treatment methods related to microbiome. We elaborated the internal correlation between airway microbiome and different stages of COPD, inflammatory endotypes, glucocorticoid and antibiotic treatment, analyze the pathophysiological mechanisms such as the "vicious cycle" hypothesis, abnormal inflammation-immune response of the host and the "natural selection" of COPD to airway microbiome, introduce the treatment of COPD related to microbiome and emphasize the predictive value of airway microbiome for the progression, exacerbation and prognosis of COPD, as well as the guiding role for clinical management of patients, in order to provide a new perspective for exploring the pathogenesis of COPD, and also provide clues and guidance for finding new treatment targets.

Respiratory Microbiome Profiles Associated With Distinct Inflammatory Phenotype and Clinical Indexes in Chronic Obstructive Pulmonary Disease

Introduction/Objective

Respiratory microbiome studies have fostered our understanding of the various phenotypes and endotypes of heterogeneous chronic obstructive pulmonary disease (COPD). This study aimed to identify microbiome-driven clusters that reflect the clinical features and dominant microbiota of COPD.

Methods

This cross-sectional study included 32 patients with stable COPD between December 2019 and December 2020 from the outpatient clinic of the China-Japan Friendship Hospital. Sputum samples were tested for 16S rRNA. Patients were classified according to the species level using an unsupervised clustering method to compare the inflammatory phenotypes of 2 clusters and analyze the correlation between the main bacteria and clinical indicators in each cluster. Patients were further divided into 2 clusters according to microorganisms.

Results

Neutrophils in cluster 1 were significantly increased compared with cluster 2. Cluster 1 was predominantly Bacteroides, while cluster 2 was dominated by Prevotella and Fusobacterium at the genus level. Fusobacterium was negatively correlated with the COPD Assessment Test (CAT) score, and Bacteroides were positively correlated with the number of acute exacerbations of COPD.

Conclusion

This study found that differential flora was negatively associated with CAT scores and the number of acute exacerbations of COPD. This microbiome-driven, unbiased clustering method for COPD can help identify new endotype-related COPD phenotypes.

Distinctive features of the oropharyngeal microbiome in Inuit of Nunavik and correlations of mild to moderate bronchial obstruction with dysbiosis

Inuit of Nunavik are coping with living conditions that can influence respiratory health. Our objective was to investigate associations between respiratory health in Inuit communities and their airway microbiome. Oropharyngeal samples were collected during the Qanuilirpitaa? 2017 Inuit Health Survey and subjected to metagenomic analyses. Participants were assigned to a bronchial obstruction group or a control group based on their clinical history and their pulmonary function, as monitored by spirometry. The Inuit microbiota composition was found to be distinct from other studied populations. Within the Inuit microbiota, differences in diversity measures tend to distinguish the two groups. Bacterial taxa found to be more abundant in the control group included candidate probiotic strains, while those enriched in the bronchial obstruction group included opportunistic pathogens. Crossing taxa affiliation method and machine learning consolidated our finding of distinct core microbiomes between the two groups. More microbial metabolic pathways were enriched in the control participants and these were often involved in vitamin and anti-inflammatory metabolism, while a link could be established between the enriched pathways in the disease group and inflammation. Overall, our results suggest a link between microbial abundance, interactions and metabolic activities and respiratory health in the Inuit population.

Virsearcher: Identifying Bacteriophages from Metagenomes by Combining Convolutional Neural Network and Gene Information

Metagenome sequencing provides an unprecedented opportunity for the discovery of unknown microbes and viruses. A large number of phages and prokaryotes are mixed together in metagenomes. To study the influence of phages on human bodies and environments, it is of great significance to isolate phages from metagenomes. However, it is difficult to identify novel phages because of the diversity of their sequences and the frequent presence of short contigs in metagenomes. Here, virSearcher is developed to identify phages from metagenomes by combining the convolutional neural network (CNN) and the gene information of input sequences. Firstly, an input sequence is encoded in accordance with the different functions of its coding and the non-coding regions and then is converted into word embedding code through a word embedding layer before a convolutional layer. Meanwhile, the hit ratio of the virus genes is combined with the output of the CNN to further improve the performance of the network. The genes used by virSearcher consist of complete and incomplete genes. Experiments on several metagenomes have showed that, compared with others, virSearcher can significantly improve the performance for the identification of short sequences, while maintaining the performance for long ones. The source code of virSearcher is freely available from http://github.com/DrJackson18/virSearcher.

The Effects and Pathogenesis of PM2.5 and Its Components on Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD), a heterogeneous disease, is the leading cause of death worldwide. In recent years, air pollution, especially particulate matter (PM), has been widely studied as a contributing factor to COPD. As an essential component of PM, PM2.5 is associated with COPD prevalence, morbidity, and acute exacerbations. However, the specific pathogenic mechanisms were still unclear and deserve further research. The diversity and complexity of PM2.5 components make it challenging to get its accurate effects and mechanisms for COPD. It has been determined that the most toxic PM2.5 components are metals, polycyclic aromatic hydrocarbons (PAHs), carbonaceous particles (CPs), and other organic compounds. PM2.5-induced cytokine release and oxidative stress are the main mechanisms reported leading to COPD. Nonnegligibly, the microorganism in PM 2.5 may directly cause mononuclear inflammation or break the microorganism balance contributing to the development and exacerbation of COPD. This review focuses on the pathophysiology and consequences of PM2.5 and its components on COPD.

Meta-analysis of sputum microbiome studies identifies airway disease-specific taxonomic and functional signatures

Introduction. Studying taxonomic and functional signatures of respiratory microbiomes provide a better understanding of airway diseases.Gap Statement. Several human airway metagenomics studies have identified taxonomic and functional features restricted to a single disease condition and the findings are not comparable across airway diseases due to use of different samples, NGS platforms, and bioinformatics databases and tools.Aim. To study the microbial taxonomic and functional components of sputum microbiome across airway diseases and healthy smokers.Methodology. Here, 57 whole metagenome shotgun sequencing (WMSS) runs coming from the sputum of five airway diseases: asthma, bronchiectasis, chronic obstructive pulmonary diseases (COPD), cystic fibrosis (CF), tuberculosis (TB), and healthy smokers as the control were reanalysed using a common WMSS analysis pipeline.Results. Shannon's index (alpha diversity) of the healthy smoker group was the highest among all. The beta diversity showed that the sputum microbiome is distinct in major airway diseases such as asthma, COPD and cystic fibrosis. The microbial composition based on differential analysis showed that there are specific markers for each airway disease like Acinetobacter bereziniae as a marker for COPD and Achromobacter xylosoxidans as a marker of cystic fibrosis. Pathways and metabolites identified from the sputum microbiome of these five diseases and healthy smokers also show specific markers. 'ppGpp biosynthesis' and 'purine ribonucleosides degradation' pathways were identified as differential markers for bronchiectasis and COPD. In this meta-analysis, besides bacteria kingdom, Aspergillus fumigatus was detected in asthma and COPD, and Roseolovirus human betaherpesvirus 7 was detected in COPD. Our analysis showed that the majority of the gene families specific to the drug-resistant associated genes were detected from opportunistic pathogens across all the groups.Conclusion. In summary, the specific species in the sputum of airway diseases along with the microbial features like specific gene families, pathways, and metabolites were identified which can be explored for better diagnosis and therapy.

Complex Evaluation of Surfactant Protein A and D as Biomarkers for the Severity of COPD

Purpose

Pulmonary surfactant proteins A (SP-A) and D (SP-D) are lectins, involved in host defense and regulation of pulmonary inflammatory response. However, studies on the assessment of COPD progress are limited.

Patients and Methods

Pulmonary surfactant proteins were obtained from the COPD mouse model induced by cigarette and lipopolysaccharide, and the specimens of peripheral blood and bronchoalveolar lavage (BALF) in COPD populations. H&E staining and RT-PCR were performed to demonstrate the successfully established of the mouse model. The expression of SP-A and SP-D in mice was detected by Western Blot and immunohistochemistry, while the proteins in human samples were measured by ELISA. Pulmonary function test, inflammatory factors (CRP, WBC, NLR, PCT, EOS, PLT), dyspnea index score (mMRC and CAT), length of hospital stay, incidence of complications and ventilator use were collected to assess airway remodeling and progression of COPD.

Results

COPD model mice with emphysema and airway wall thickening were more prone to have decreased SP-A, SP-D and increased TNF-α, TGF-β, and NF-kb in lung tissue. In humans, SP-A and SP-D decreased in BALF, but increased in serum. The serum SP-A and SP-D were negatively correlated with FVC, FEV1, FEV1/FVC, and positively correlated with CRP, WBC, NLR, mMRC and CAT scores (P < 0.05, respectively). The lower the SP-A and SP-D in BALF, the worse the lung function and the increased probability of complications and ventilator use. Moreover, the same trend emerged in COPD patients grouped according to GOLD severity grade (Gold 1–2 group vs Gold 3–4 group). The worse the patient’s condition, the more pronounced the change.

Conclusion

This study suggests that SP-A and SP-D may be related to the progression and prognostic evaluation of COPD in terms of airway remodeling, inflammatory response and clinical symptoms, and emphasizes the necessity of future studies of surfactant protein markers in COPD.

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.

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

Objective:

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

Methods:

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

Results:

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

Conclusion:

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

Analysis of sputum microbial metagenome in COPD based on exacerbation frequency and lung function: a case control study

Background

The role of the sputum microbiome in chronic obstructive pulmonary disease (COPD) progression remains elusive. As the advent of the new culture-independent microbial sequencing technique makes it possible to disclose the complex microbiome community of the respiratory tract. The aim of this study was to use metagenomic next-generation sequencing (mNGS) to confirm whether there are differences in sputum microbiome of COPD between different exacerbation frequencies and lung function.

Methods

Thirty-nine COPD patients were divided into a frequent exacerbators (FE) group (n = 20) and a non-frequent exacerbators (NFE) (n = 19) group according to their exacerbation history, or a mild group (FEV₁/pre ≥ 50%, n = 20) and a severe group (FEV₁/pre < 50%, n = 19) according to the lung function. Sputum was collected during their stable phase, followed by DNA extraction, untargeted metagenomic next-generation sequencing (mNGS) and bioinformatic analysis.

Results

mNGS identified 3355 bacteria, 71 viruses and 22 fungi at the specie level. It was found that Shannon index and Simpson index in FE group was lower than that in NFE group (p = 0.005, 0.008, respectively) but similar between mild and severe groups. Out of top 10 bacteria taxa, Veillonella, Fusobacterium and Prevotella jejuni had a higher abundance in NFE group, Rothia had a higher abundance in mild group. Linear discriminant analysis revealed that many bacterial taxa were more abundant in NFE group, and they mostly belonged to Actinobacteria, Bacteroidetes and Fusobacteria phyla. Frequency of exacerbations was also found to be negatively correlated with alpha diversity (with Shannon index, r = − 0.423, p = 0.009; with Simpson index, r = − 0.482, p = 0.002). No significant correlation was observed between alpha diversity and FEV₁/pre.

Conclusions

Microbiome diversity in FE group was lower than that in NFE group. There was a significant difference in microbiome taxa abundance between FE and NFE groups, or mild and severe groups. These findings demonstrated that sputum microbiome community dysbiosis was associated with different exacerbation frequencies and lung function in stable COPD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02246-9.

Fungal Dysbiosis Correlates with the Development of Tumor-Induced Cachexia in Mice

Cachexia (CC) is a devastating metabolic syndrome associated with a series of underlying diseases that greatly affects life quality and expectancy among cancer patients. Studies involving mouse models, in which CC was induced through inoculation with tumor cells, originally suggested the existence of a direct correlation between the development of this syndrome and changes in the relative proportions of several bacterial groups present in the digestive tract. However, these analyses have focus solely on the characterization of bacterial dysbiosis, ignoring the possible existence of changes in the relative populations of fungi, during the development of CC. Thus, the present study sought to expand such analyses, by characterizing changes that occur in the gut fungal population (mycobiota) of mice, during the development of cancer-induced cachexia. Our results confirm that cachectic animals, submitted to Lewis lung carcinoma (LLC) transplantation, display significant differences in their gut mycobiota, when compared to healthy controls. Moreover, identification of dysbiotic fungi showed remarkable consistency across successive levels of taxonomic hierarchy. Many of these fungi have also been associated with dysbioses observed in a series of gut inflammatory diseases, such as obesity, colorectal cancer (CRC), myalgic encephalomyelitis (ME) and inflammatory bowel disease (IBD). Nonetheless, the dysbiosis verified in the LLC model of cancer cachexia seems to be unique, presenting features observed in both obesity (reduced proportion of Mucoromycota) and CRC/ME/IBD (increased proportions of Sordariomycetes, Saccharomycetaceae and Malassezia). One species of Mucoromycota (Rhyzopus oryzae) stands out as a promising probiotic candidate in adjuvant therapies, aimed at treating and/or preventing the development of CC.

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.

Microbiome in Chronic Obstructive Pulmonary Disease: Role of Natural Products Against Microbial Pathogens

The "microbiome" is the operative term to refer to a collection of all taxa constituting microbial communities, such as bacteria, archaea, fungi and protists (originally microbiota). The microbiome consists of the indigenous microbial communities and of the host environment that they inhabit. Actually, it has been shown that there is a close relationship between the microbiome and human health and disease condition. Although, initially, the lung was considered sterile, actually, the existence of a healthy lung microbiome is usually accepted. Lung microbiome changes are reported in Chronic Obstructive Pulmonary Disease (COPD) and in its exacerbation. Viral and bacterial infections of the respiratory system are a major cause of COPD exacerbations (AECOPD) leading to increased local and systemic inflammation. Detection rates of virus in AECOPD are variable between 25-62% according to the detection method. The study of human airway and lung disease virome is quite recent and still very limited. The purpose of this review is to summarize recent findings on the lung microbiome composition with a special emphasis on virome in COPD and in AECOPD. Some drugs of natural origins active against resistant bacteria and virus are described.

Improved Metagenomic Taxonomic Profiling Using a Curated Core Gene-Based Bacterial Database Reveals Unrecognized Species in the Genus Streptococcus

Shotgun metagenomics is of great importance in order to understand the composition of the microbial community associated with a sample and the potential impact it may exert on its host. For clinical metagenomics, one of the initial challenges is the accurate identification of a pathogen of interest and ability to single out that pathogen within a complex community of microorganisms. However, in absence of an accurate identification of those microorganisms, any kind of conclusion or diagnosis based on misidentification may lead to erroneous conclusions, especially when comparing distinct groups of individuals. When comparing a shotgun metagenomic sample against a reference genome sequence database, the classification itself is dependent on the contents of the database. Focusing on the genus Streptococcus, we built four synthetic metagenomic samples and demonstrated that shotgun taxonomic profiling using the bacterial core genes as the reference database performed better in both taxonomic profiling and relative abundance prediction than that based on the marker gene reference database included in MetaPhlAn2. Additionally, by classifying sputum samples of patients suffering from chronic obstructive pulmonary disease, we showed that adding genomes of genomospecies to a reference database offers higher taxonomic resolution for taxonomic profiling. Finally, we show how our genomospecies database is able to identify correctly a clinical stool sample from a patient with a streptococcal infection, proving that genomospecies provide better taxonomic coverage for metagenomic analyses.

BMC3C: binning metagenomic contigs using codon usage, sequence composition and read coverage

Motivation

Metagenomics investigates the DNA sequences directly recovered from environmental samples. It often starts with reads assembly, which leads to contigs rather than more complete genomes. Therefore, contig binning methods are subsequently used to bin contigs into genome bins. While some clustering-based binning methods have been developed, they generally suffer from problems related to stability and robustness.

Results

We introduce BMC3C, an ensemble clustering-based method, to accurately and robustly bin contigs by making use of DNA sequence Composition, Coverage across multiple samples and Codon usage. BMC3C begins by searching the proper number of clusters and repeatedly applying the k-means clustering with different initializations to cluster contigs. Next, a weight graph with each node representing a contig is derived from these clusters. If two contigs are frequently grouped into the same cluster, the weight between them is high, and otherwise low. BMC3C finally employs a graph partitioning technique to partition the weight graph into subgraphs, each corresponding to a genome bin. We conduct experiments on both simulated and real-world datasets to evaluate BMC3C, and compare it with the state-of-the-art binning tools. We show that BMC3C has an improved performance compared to these tools. To our knowledge, this is the first time that the codon usage features and ensemble clustering are used in metagenomic contig binning.

Availability and implementation

The codes of BMC3C are available at http://mlda.swu.edu.cn/codes.php?name=BMC3C.

Supplementary information

Supplementary data are available at Bioinformatics online.

Profiling of lung microbiota discloses differences in adenocarcinoma and squamous cell carcinoma

The lung is a complex ecosystem of host cells and microbes often disrupted in pathological conditions. Although bacteria have been hypothesized as agents of carcinogenesis, little is known about microbiota profile of the most prevalent cancer subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). To characterize lung cancer (LC) microbiota a first a screening was performed through a pooled sequencing approach of 16S ribosomal RNA gene (V3-V6) using a total of 103 bronchoalveaolar lavage fluid samples. Then, identified taxa were used to inspect 1009 cases from The Cancer Genome Atlas and to annotate tumor unmapped RNAseq reads. Microbial diversity was analyzed per cancer subtype, history of cigarette smoking and airflow obstruction, among other clinical data. We show that LC microbiota is enriched in Proteobacteria and more diverse in SCC than ADC, particularly in males and heavier smokers. High frequencies of Proteobacteria were found to discriminate a major cluster, further subdivided into well-defined communities’ associated with either ADC or SCC. Here, a SCC subcluster differing from other cases by a worse survival was correlated with several Enterobacteriaceae. Overall, this study provides first evidence for a correlation between lung microbiota and cancer subtype and for its influence on patient life expectancy.

The lung microbiome dynamics between stability and exacerbation in chronic obstructive pulmonary disease (COPD): Current perspectives

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disorder with a course that is not uniform for all COPD patients. Although smoking is considered as the major cause of the disease, persistent or recurrent infections seem to play a particular role in the disease establishment and progression. COPD is characterized by dysregulated immunity that has been associated with the bacterial colonization and infections. The establishment of culture-independent techniques has shed new light on the relationships between bacterial ecology and health status and expanded our knowledge on the lung microbiome. Interactions between the host and lung microbiome result in inflammation and activation of resident cells. The lung microbiome contains populations of symbionts and pathobionts in balance which lose their equilibrium and disturb the balance of T-helper and regulatory T-cells (Treg) upon infection, or lung disease. In COPD factors such as disease severity, exacerbations, degree of inflammation, and type of treatment used (e.g inhaled or systemic steroids and antibiotics) affect the composition of lung microbiota. Recent data indicate that the presence of specific bacterial taxa in the airways has the potential to influence the host immune response and possibly to interfere with disease phenotype. Although, there is a growing body of evidence for the role of microbiome in COPD several unanswered questions still exist for its clinical relevance.

Microfluidics-Based Enrichment and Whole-Genome Amplification Enable Strain-Level Resolution for Airway Metagenomics

Dysbiosis of airway microbiomes has been found in various respiratory diseases, but its molecular details in terms of taxonomic profile, metabolic characteristics, defensive function, and inhabit adaption are far from clear. Shotgun metagenome sequencing provides detailed information for microbes, whereas its application is rather limited in airways due to host DNA contaminants that overwhelm a minute amount of microbial content. Here, we describe a microfluidics-based enrichment device and an emulsion-based whole-genome amplification procedure (MEEA) for the preparation of DNA from sputa for shotgun sequencing in a metagenomics study. The two protocols coupled in MEEA are first separately assayed with mock samples and are both promising in efficiency and bias. The efficiency and consistency of MEEA are further evaluated in six clinical sputum samples against direct sequencing without enrichment, and MEEA enables 2 to 14 times enrichment for microbial reads, which take 14.68% to 33.52% of total reads. The dominant pathogens detected in MEEA are in excellent agreement with those from clinical etiological tests. Meanwhile, MEEA presents much more microbiome complexity and genome information at a strain level than direct sequencing, exhibiting high sensitivity for identifying prophages and DNA viruses. MEEA provides better microbiome profiling than direct sequencing without a preference for specific microorganisms. The more detailed functional and taxonomic characterization of their species constituents, including both bacterium and virus, facilitates metagenomics studies on the pathogenesis of respiratory microbiomes.IMPORTANCE The airway microbial community, which takes important pathogenic roles for respiratory diseases, is far from clear in terms of taxonomy and gene functions. One of the critical reasons is the heavy contamination of host cell/DNA in airway samples, which hinders the subsequent sequencing of the whole genomic contents of the microbial community-the metagenome. Here, we describe a protocol for airway sample preparation which couples a microbe enrichment microfluidic device and a DNA amplification method performed in numerous droplets. When evaluated with mock and clinical sputum samples, the microfluidics-based enrichment device and emulsion-based whole-genome amplification (MEEA) procedure efficiently removes host cells, amplifies the microbial genome, and shows no obvious bias among microbes. The efficiency of MEEA makes it a promising method in research of respiratory microbial communities and their roles in diseases.

Airway microbiome is associated with respiratory functions and responses to ambient particulate matter exposure

BACKGROUND

Ambient particulate matter (PM) exposure has been associated with respiratory function decline in epidemiological studies. We hypothesize that a possible underlying mechanism is the perturbation of airway microbiome by PM exposure.

METHODS

During October 2016-October 2017, on two human cohorts (n = 115 in total) in Shanghai China, we systematically collected three categories of data: (1) respiratory functions, (2) airway microbiome from sputum, and (3) PM2.5 (PM of ≤ 2.5 µm in diameter) level in ambient air. We investigated the impact of PM2.5 on airway microbiome as well as the link between airway microbiome and respiratory functions using linear mixed regression models.

RESULTS

The respiratory function of our primary interest includes forced vital capacity (FVC) and forced expiratory volume in 1st second (FEV1). FEV1/FVC, an important respiratory function trait and key diagnosis criterion of COPD, was significantly associated with airway bacteria load (p = 0.0038); and FEV1 was associated with airway microbiome profile (p = 0.013). Further, airway microbiome was significantly influenced by PM2.5 exposure (p = 4.48E-11).

CONCLUSIONS

To our knowledge, for the first time, we demonstrated the impact of PM2.5 on airway microbiome, and reported the link between airway microbiome and respiratory functions. The results expand our understanding on the scope of PM2.5 exposure's influence on human respiratory system, and point to novel etiological mechanism of PM2.5 exposure induced diseases.

Transcriptionally Active Lung Microbiome and Its Association with Bacterial Biomass and Host Inflammatory Status

Recent studies of the microbiome proposed that resident microbes play a beneficial role in maintaining human health. Although lower respiratory tract disease is a leading cause of sickness and mortality, how the lung microbiome interacts with human health remains largely unknown. Here we assessed the association between the lung microbiome and host gene expression, cytokine concentration, and over 20 clinical features. Intriguingly, we found a stratified structure of the active lung microbiome which was significantly associated with bacterial biomass, lymphocyte proportion, human Th17 immune response, and COPD exacerbation frequency. These observations suggest that the microbiome plays a significant role in lung homeostasis. Not only microbial composition but also active functional elements and host immunity characteristics differed among different individuals. Such diversity may partially account for the variation in susceptibility to particular diseases.

Alteration of the lung microbiome has been observed in several respiratory tract diseases. However, most previous studies were based on 16S ribosomal RNA and shotgun metagenome sequencing; the viability and functional activity of the microbiome, as well as its interaction with host immune systems, have not been well studied. To characterize the active lung microbiome and its associations with host immune response and clinical features, we applied metatranscriptome sequencing to bronchoalveolar lavage fluid (BALF) samples from 25 patients with chronic obstructive pulmonary disease (COPD) and from nine control cases without known pulmonary disease. Community structure analyses revealed three distinct microbial compositions, which were significantly correlated with bacterial biomass, human Th17 immune response, and COPD exacerbation frequency. Specifically, samples with transcriptionally active Streptococcus, Rothia, or Pseudomonas had bacterial loads 16 times higher than samples enriched for Escherichia and Ralstonia. These high-bacterial-load samples also tended to undergo a stronger Th17 immune response. Furthermore, an increased proportion of lymphocytes was found in samples with active Pseudomonas. In addition, COPD patients with active Streptococcus or Rothia infections tended to have lower rates of exacerbations than patients with active Pseudomonas and patients with lower bacterial biomass. Our results support the idea of a stratified structure of the active lung microbiome and a significant host-microbe interaction. We speculate that diverse lung microbiomes exist in the population and that their presence and activities could either influence or reflect different aspects of lung health.

IMPORTANCE Recent studies of the microbiome proposed that resident microbes play a beneficial role in maintaining human health. Although lower respiratory tract disease is a leading cause of sickness and mortality, how the lung microbiome interacts with human health remains largely unknown. Here we assessed the association between the lung microbiome and host gene expression, cytokine concentration, and over 20 clinical features. Intriguingly, we found a stratified structure of the active lung microbiome which was significantly associated with bacterial biomass, lymphocyte proportion, human Th17 immune response, and COPD exacerbation frequency. These observations suggest that the microbiome plays a significant role in lung homeostasis. Not only microbial composition but also active functional elements and host immunity characteristics differed among different individuals. Such diversity may partially account for the variation in susceptibility to particular diseases.

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

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

Face mask sampling reveals antimicrobial resistance genes in exhaled aerosols from patients with chronic obstructive pulmonary disease and healthy volunteers

Introduction

The degree to which bacteria in the human respiratory tract are aerosolised by individuals is not established. Building on our experience sampling bacteria exhaled by individuals with pulmonary tuberculosis using face masks, we hypothesised that patients with conditions frequently treated with antimicrobials, such as chronic obstructive pulmonary disease (COPD), might exhale significant numbers of bacteria carrying antimicrobial resistance (AMR) genes and that this may constitute a previously undefined risk for the transmission of AMR.

Methods

Fifteen-minute mask samples were taken from 13 patients with COPD (five paired with contemporaneous sputum samples) and 10 healthy controls. DNA was extracted from cell pellets derived from gelatine filters mounted within the mask. Quantitative PCR analyses directed to the AMR encoding genes: blaTEM (β-lactamase), ErmB (target methylation), mefA (macrolide efflux pump) and tetM (tetracycline ribosomal protection protein) and six additional targets were investigated. Positive signals above control samples were obtained for all the listed genes; however, background signals from the gelatine precluded analysis of the additional targets.

Results

9 patients with COPD (69%), aerosolised cells containing, in order of prevalence, mefA, tetM, ErmB and blaTEM, while three healthy controls (30%) gave weak positive signals including all targets except blaTEM. Maximum estimated copy numbers of AMR genes aerosolised per minute were mefA: 3010, tetM: 486, ErmB: 92 and blaTEM: 24. The profile of positive signals found in sputum was not concordant with that in aerosol in multiple instances.

Discussion

We identified aerosolised AMR genes in patients repeatedly exposed to antimicrobials and in healthy volunteers at lower frequencies and levels. The discrepancies between paired samples add weight to the view that sputum content does not define aerosol content. Mask sampling is a simple approach yielding samples from all subjects and information distinct from sputum analysis. Our results raise the possibility that patient-generated aerosols may be a significant means of AMR dissemination that should be assessed further and that consideration be given to related control measures.

Lung cancer: a new frontier for microbiome research and clinical translation

The lung microbiome has been shown to reflect a range of pulmonary diseases—for example: asthma, chronic obstructive pulmonary disease (COPD) and cystic fibrosis. Studies have now begun to show microbiological changes in the lung that correlate with lung cancer (LC) which could provide new insights into lung carcinogenesis and new biomarkers for disease screening. Clinical studies have suggested that infections with tuberculosis or pneumonia increased the risk of LC possibly through inflammatory or immunological changes. These have now been superseded by genomic-based microbiome sequencing studies based on bronchoalveolar lavage, sputum or saliva samples. Although some discrepancies exist, many have suggested changes in particular bacterial genera in LC samples particularly, Granulicatella, Streptococcus and Veillonella. Granulicatella is of particular interest, as it appeared to show LC stage-specific increases in abundance. We propose that these microbial community changes are likely to reflect biochemical changes in the LC lung, linked to an increase in anaerobic environmental niches and altered pyridoxal/polyamine/nitrogenous metabolism to which Granulicatella could be particularly responsive. These are clearly preliminary observations and many more expansive studies are required to develop our understanding of the LC microbiome.

Symptom-related sputum microbiota in stable chronic obstructive pulmonary disease

Background

The role of airway microbiota in COPD is highly debated. Symptomology assessment is vital for the management of clinically stable COPD patients; however, the link between symp toms and the airway microbiome is currently unknown.

Purpose

The present study aimed to evaluate the relationship among stable COPD patients.

Patients and methods

We conducted pyrosequencing of bacterial 16S rRNA using induced sputum samples in a Han Chinese cohort that included 40 clinically stable COPD patients and 19 healthy controls.

Results

Alterations in community composition and core bacte rial taxa (Neisseria subflava, etc.) were observed in patients with severe symptoms compared with controls. The co-occurrence network indicated that the key microbiota enriched in COPD patients showed higher expression in patients with severe symptoms. The association pattern of symptoms with the sputum microbiome was obviously different from that of lung function in COPD patients.

Conclusion

These findings broaden our insights into the relationship between the sputum microbiota and the symptom severity in COPD patients, emphasizing the role of symptoms in the airway microbiome, independent of lung function.

Role of the Lung Microbiome in the Pathogenesis of Chronic Obstructive Pulmonary Disease

OBJECTIVE

The development of culture-independent techniques for microbiological analysis shows that bronchial tree is not sterile in either healthy or chronic obstructive pulmonary disease (COPD) individuals. With the advance of sequencing technologies, lung microbiome has become a new frontier for pulmonary disease research, and such advance has led to better understanding of the lung microbiome in COPD. This review aimed to summarize the recent advances in lung microbiome, its relationships with COPD, and the possible mechanisms that microbiome contributed to COPD pathogenesis.

DATA SOURCES

Literature search was conducted using PubMed to collect all available studies concerning lung microbiome in COPD. The search terms were "microbiome" and "chronic obstructive pulmonary disease", or "microbiome" and "lung/pulmonary".

STUDY SELECTION

The papers in English about lung microbiome or lung microbiome in COPD were selected, and the type of articles was not limited.

RESULTS

The lung is a complex microbial ecosystem; the microbiome in lung is a collection of viable and nonviable microbiota (bacteria, viruses, and fungi) residing in the bronchial tree and parenchymal tissues, which is important for health. The following types of respiratory samples are often used to detect the lung microbiome: sputum, bronchial aspirate, bronchoalveolar lavage, and bronchial mucosa. Disordered bacterial microbiome is participated in pathogenesis of COPD; there are also dynamic changes in microbiota during COPD exacerbations. Lung microbiome may contribute to the pathogenesis of COPD by manipulating inflammatory and/or immune process.

CONCLUSIONS

Normal lung microbiome could be useful for prophylactic or therapeutic management in COPD, and the changes of lung microbiome could also serve as biomarkers for the evaluation of COPD.

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.

Exploring the microbiome in health and disease

The analysis of human microbiome is an exciting and rapidly expanding field of research. In the past decade, the biological relevance of the microbiome for human health has become evident. Microbiome comprises a complex collection of microorganisms, with their genes and metabolites, colonizing different body niches. It is now well known that the microbiome interacts with its host, assisting in the bioconversion of nutrients and detoxification, supporting immunity, protecting against pathogenic microbes, and maintaining health. Remarkable new findings showed that our microbiome not only primarily affects the health and function of the gastrointestinal tract but also has a strong influence on general body health through its close interaction with the nervous system and the lung. Therefore, a perfect and sensitive balanced interaction of microbes with the host is required for a healthy body. In fact, growing evidence suggests that the dynamics and function of the indigenous microbiota can be influenced by many factors, including genetics, diet, age, and toxicological agents like cigarette smoke, environmental contaminants, and drugs. The disruption of this balance, that is called dysbiosis, is associated with a plethora of diseases, including metabolic diseases, inflammatory bowel disease, chronic obstructive pulmonary disease, periodontitis, skin diseases, and neurological disorders. The importance of the host microbiome for the human health has also led to the emergence of novel therapeutic approaches focused on the intentional manipulation of the microbiota, either by restoring missing functions or eliminating harmful roles. In the present review, we outline recent studies devoted to elucidate not only the role of microbiome in health conditions and the possible link with various types of diseases but also the influence of various toxicological factors on the microbial composition and function.

Individual Patterns of Complexity in Cystic Fibrosis Lung Microbiota, Including Predator Bacteria, over a 1-Year Period

Cystic fibrosis (CF) lung microbiota composition has recently been redefined by the application of next-generation sequencing (NGS) tools, identifying, among others, previously undescribed anaerobic and uncultivable bacteria. In the present study, we monitored the fluctuations of this ecosystem in 15 CF patients during a 1-year follow-up period, describing for the first time, as far as we know, the presence of predator bacteria in the CF lung microbiome. In addition, a new computational model was developed to ascertain the hypothetical ecological repercussions of a prey-predator interaction in CF lung microbial communities. Fifteen adult CF patients, stratified according to their pulmonary function into mild (n = 5), moderate (n = 9), and severe (n = 1) disease, were recruited at the CF unit of the Ramón y Cajal University Hospital (Madrid, Spain). Each patient contributed three or four induced sputum samples during a 1-year follow-up period. Lung microbiota composition was determined by both cultivation and NGS techniques and was compared with the patients’ clinical variables. Results revealed a particular microbiota composition for each patient that was maintained during the study period, although some fluctuations were detected without any clinical correlation. For the first time, Bdellovibrio and Vampirovibrio predator bacteria were shown in CF lung microbiota and reduced-genome bacterial parasites of the phylum Parcubacteria were also consistently detected. The newly designed computational model allows us to hypothesize that inoculation of predators into the pulmonary microbiome might contribute to the control of chronic colonization by CF pathogens in early colonization stages.

The application of NGS to sequential samples of CF patients demonstrated the complexity of the organisms present in the lung (156 species) and the constancy of basic individual colonization patterns, although some differences between samples from the same patient were observed, probably related to sampling bias. Bdellovibrio and Vampirovibrio predator bacteria were found for the first time by NGS as part of the CF lung microbiota, although their ecological significance needs to be clarified. The newly designed computational model allows us to hypothesize that inoculation of predators into the lung microbiome can eradicate CF pathogens in early stages of the process. Our data strongly suggest that lower respiratory microbiome fluctuations are not necessarily related to the patient’s clinical status.

Potential of Health and Demographic Surveillance System in Asthma and Chronic Obstructive Pulmonary Disease Microbiome Research

Health and demographic surveillance system (HDSS) is a population-based health and vital event registration system that monitors demographic and health events in a geographically defined population at regular intervals. Human microbiome research in the past decade has been the field of increasingly intense research much due to its demonstrated impact upon various health conditions including human chronic airway diseases such as asthma and chronic obstructive pulmonary disease (COPD). Many confounding factors have been revealed to play a role in shaping the microbiome in chronic airway diseases. Asthma and COPD follows a typical pattern of disease progression, which includes stable and exacerbation state in which the microbiota is known to vary. However, many such studies lack extensive and longitudinal sampling with inadequate metadata, which has resulted in the inconsistencies in the observations. HDSS provides such a platform, which can offer a deeper understanding of the role of the microbiome in human health. In this review, we highlight opportunities and limitations in microbiome research with the help of studies conducted on chronic airway diseases like asthma and COPD. In addition, we also emphasize on the benefits of HDSS and future directions in lung microbiome research.

A pilot study using metagenomic sequencing of the sputum microbiome suggests potential bacterial biomarkers for lung cancer

Lung cancer (LC) is the most prevalent cancer worldwide, and responsible for over 1.3 million deaths each year. Currently, LC has a low five year survival rates relative to other cancers, and thus, novel methods to screen for and diagnose malignancies are necessary to improve patient outcomes. Here, we report on a pilot-sized study to evaluate the potential of the sputum microbiome as a source of non-invasive bacterial biomarkers for lung cancer status and stage. Spontaneous sputum samples were collected from ten patients referred with possible LC, of which four were eventually diagnosed with LC (LC⁺), and six had no LC after one year (LC^-). Of the seven bacterial species found in all samples, Streptococcus viridans was significantly higher in LC⁺ samples. Seven further bacterial species were found only in LC^-, and 16 were found only in samples from LC⁺. Additional taxonomic differences were identified in regards to significant fold changes between LC⁺ and LC^-cases, with five species having significantly higher abundances in LC⁺, with Granulicatella adiacens showing the highest level of abundance change. Functional differences, evident through significant fold changes, included polyamine metabolism and iron siderophore receptors. G. adiacens abundance was correlated with six other bacterial species, namely Enterococcus sp. 130, Streptococcus intermedius, Escherichia coli, S. viridans, Acinetobacter junii, and Streptococcus sp. 6, in LC⁺ samples only, which could also be related to LC stage. Spontaneous sputum appears to be a viable source of bacterial biomarkers which may have utility as biomarkers for LC status and stage.

An update on the pharmacotherapeutic management of lower respiratory tract infections

INTRODUCTION

Our knowledge about lower respiratory tract infections (LRTIs) has improved substantially in the last years, but the management of respiratory infections is still a challenge and we are still far from using precision medicine in their treatment. Areas covered: The approaches developed in recent years to improve the pharmacotherapeutic management of LRTIs, such as novel diagnostic assays to facilitate medical decision-making, attempts for selecting an optimal empiric antibiotic regimen, and the role of new and possibly unproven adjunctive therapies, are described. Expert opinion: Early and appropriate antibiotics remain the cornerstone in the treatment of LRTIs. The updated trend is to apply antimicrobial stewardship principles and initiatives to optimize both the management and the outcomes of LTRIs. Biomarkers, mainly C-reactive protein (CRP) and procalcitonin (PCT), can improve the diagnostic and prognostic assessment of LRTIs and aid to guide antibiotic therapy. The widespread use of antimicrobial agents has greatly contributed to faster development of antibiotic resistance and the emergence of opportunistic pathogens, which substitute the indigenous microbiota. However, very few new antibiotics in development to overcome existing resistance and ensure continued success in the treatment of LRTIs have been approved, likely because antibiotic stewardship programs discourage the use of new agents.

Associations between ambient wood smoke and other particulate pollutants and biomarkers of systemic inflammation, coagulation and thrombosis in cardiac patients

BACKGROUND

Increased particulate air pollution has been associated with both an increased risk of myocardial infarction (MI) and adverse changes in cardiac biomarkers. Up to 30% of ambient wintertime fine particles (PM_2.5) in Rochester, NY are from wood burning. Our study examined associations between ambient levels of a marker of wood smoke (Delta-C) and other particulate air pollutants and biomarkers of inflammation, coagulation and thrombosis.

METHODS

We measured blood concentrations of C-reactive protein (CRP), D-dimer, fibrinogen, P-selectin, platelet factor 4 (PF-4), von Willebrand factor (vWF), and myeloperoxidase (MPO) of 135 patients undergoing cardiac catheterization during the winters of 2011-2013. We coupled these data with hourly ambient concentrations of Delta-C, black carbon (BC; marker of traffic pollution), and ultrafine (10-100nm; UFP), accumulation mode (100-500nm; AMP), and fine particles (<2.5µm; PM_2.5). Using linear regression models, we estimated the change in each biomarker associated with increased pollutant concentrations at intervals between 1 and 96h preceding blood collection.

RESULTS

Each 0.13µg/m³ increase in Delta-C concentration in the prior 12h was associated with a 0.91% increase in fibrinogen levels (95% CI=0.23%, 1.59%), but unexpectedly in the prior 48h, each 0.17µg/m³ increase in Delta-C concentration was associated with a 2.75% decrease in MPO levels (95% CI=-5.13%,-0.37%). We did not see associations between Delta-C concentrations and any other biomarkers. Interquartile range (IQR) increases in PM_2.5, BC, UFP, and AMP concentrations were generally associated with increased CRP and fibrinogen, but not PF4, D-dimer, vWF, or P-selectin.

CONCLUSIONS

In a population of cardiac patients, we noted adverse changes in fibrinogen associated with increased concentrations of a marker of wood smoke. Increases in PM_2.5, BC, AMP, and UFP concentrations in the previous 96h were also associated with adverse changes in markers of systemic inflammation and coagulation, but not with markers of endothelial cell dysfunction or platelet activation.

Understanding COPD-overlap syndromes

INTRODUCTION

Chronic obstructive pulmonary disease accounts for a large burden of lung disease. It can 'overlap' with other respiratory diseases including bronchiectasis, fibrosis and obstructive sleep apnea (OSA). While COPD alone confers morbidity and mortality, common features with contrasting clinical outcomes can occur in COPD 'overlap syndromes'. Areas covered: Given the large degree of heterogeneity in COPD, individual variation to treatment is adopted based on its observed phenotype, which in turn overlaps with features of other respiratory disease states such as asthma. This is coined asthma-COPD overlap syndrome ('ACOS'). Other examples of such overlapping clinical states include bronchiectasis-COPD ('BCOS'), fibrosis-COPD ('FCOS') and OSA-COPD ('OCOS'). The objective of this review is to highlight similarities and differences between the COPD-overlap syndromes in terms of risk factors, pathophysiology, diagnosis and potential treatment differences. Expert commentary: As a consequence of COPD overlap syndromes, a transition from the traditional 'one size fits all' treatment approach is necessary. Greater treatment stratification according to clinical phenotype using a precision medicine approach is now required. In this light, it is important to recognize and differentiate COPD overlap syndromes as distinct disease states compared to individual diseases such as asthma, COPD, fibrosis or bronchiectasis.

Impact of sample processing on human airways microbial metagenomes

Whole metagenome shotgun sequencing provides information about the gene content and the composition of microbial communities provided that the processing of the samples does not introduce a methodology-driven bias. We tested the impact of DNA isolation and storage period on the metagenome profile. Deep throat swabs were collected from healthy adults and an infected infant. DNA was isolated by sonification or enzymatic lysis either immediately or after 24h storage in agar gel Amies transport medium at room temperature. Disruption of cells and subsequent fragmentation of DNA by sonification was as suitable as the common enzymatic lysis to generate high-quality metagenomes particularly for low total DNA input of less than ten nanograms. Conversely, storage of samples for 24h produced severely distorted metagenomes. The majority of species became less abundant or even extinct, whereas a few Streptococcus, Neisseria and Haemophilus spp. proliferated so that the total number of bacterial reads increased at the expense of human reads. We recommend that samples for metagenome analysis should be immediately processed or frozen at -80°C.

The human gut microbiome as source of innovation for health: Which physiological and therapeutic outcomes could we expect?

From the moment of birth, each human being builds a microbe-host symbiosis which is key for the preservation of its health and well-being. This personal symbiotic coexistence is the result of progressive enrichments in microorganism diversity through external supplies. This diversity is nowadays massively overthrown by drastic changes related to clinical practice in birth management, environmental exposure, nutrition and healthcare behaviors. The last two generations have been the frame of massive modifications in life and food habits, with people being more and more sedentary, overfed and permeated with drugs and pollutants. We are now able to measure the impact of these changes on the gut microbiota diversity. Concomitantly, these modifications of lifestyle were associated with a dramatic increase in incidence of immune-mediated diseases including metabolic, allergic and inflammatory diseases and most likely neurodegenerative and psychiatric disorders. Microbiota is becoming a hot topic in the scientific community and in the mainstream media. The number of scientific publications increased by up to a factor three over the last five years, with gastrointestinal and metabolic diseases being the most productive areas. In the intellectual property landscape, the patent families on microbiota have more than doubled in the meantime. In parallel, funding either from National Institutes (e.g. from NIH which funds research mainly in the field of allergies, infections, cancer and cardiovascular diseases, from the White House which launched the national microbiome initiative) or by pharmaceutical companies follow the same trend, showing a boost and a strong support in the research field on microbiota. All major health players are investing in microbiome research as shown by the number of deals signed and by funding during 2015. The Giens round table addressed how the medicine of tomorrow, considering human beings as a human-microbe symbiotic supraorganism, could leverage microbiome knowledge and tools. The rationale for our working group has been structured around four domains of innovation that could derive from ongoing efforts in deciphering the interactions between human cells and intestinal microbiome as a central component of human health, namely: (1) development of stratification and monitoring tools; (2) identification of new target and drug discovery, as a part of our supra-genome; (4) exploitation of microbiota as a therapeutic target that can be modulated; (4) and finally as a source of live biotherapeutics and adjuvants. These four streams will exemplify how microbiota has changed the way we consider a wide range of chronic and incurable diseases and the consequences of long-lasting dysbiosis. In-depth microbiota analysis is opening one of the broadest fields of investigation for improving human and animal health and will be a source of major therapeutic innovations for tackling today's medical unmet needs. We thus propose a range of recommendations for basic researchers, care givers as well as for health authorities to gain reliability in microbiome analysis and accelerate discovery processes and their translation into applications for the benefits of the people. Finally, les Ateliers de Giens round table on microbiota benefited from the richness of the French ecosystem. France represents a center of excellence in the microbiota research field, with French institutions as Institut national de la recherche agronomique (INRA [Metagenopolis, Micalis]), Centre national de la recherché scientifique (CNRS), Unité de recherche sur les maladies infectieuses et tropicales émergentes (URMITE), Institut of Cardiometabolism and Nutrition (ICAN), Institut des maladies métaboliques et cardiovasculaires (I2MC), Institut national de la santé et de la recherche médicale (Inserm), Pasteur Institute and Gustave-Roussy being top-players for the number of publications.

The microbiome-metabolome crosstalk in the pathogenesis of respiratory fungal diseases

Filamentous fungi of the genus Aspergillus are responsible for several superficial and invasive infections and allergic syndromes. The risk of infection and its clinical outcome vary significantly even among patients with similar predisposing clinical factors and pathogen exposure. There is increasing evidence that the individual microbiome supervises the outcome of the host-fungus interaction by influencing mechanisms of immune regulation, inflammation, metabolism, and other physiological processes. Microbiome-mediated mechanisms of resistance allow therefore the control of fungal colonization, preventing the onset of overt disease, particularly in patients with underlying immune dysfunction. Here, we review this emerging area of research and discuss the contribution of the microbiota (and its dysbiosis), including its immunoregulatory properties and relationship with the metabolic activity of commensals, to respiratory fungal diseases. Finally, we highlight possible strategies aimed at decoding the microbiome-metabolome dialog and at its exploitation toward personalized medical interventions in patients at high risk of infection.