Respiratory Microbiome Research Articles

Detection of lumpy skin disease virus reads in the human upper respiratory tract microbiome requires further investigation.

Lumpy skin disease virus (LSDV), a double-stranded DNA virus from the Capripoxvirus genus, primarily affects Bos indicus, Bos taurus breeds, and water buffalo. Arthropod vectors, including mosquitoes and biting flies, are the main LSDV transmitters. Although LSDV is not zoonotic, this study unexpectedly detected LSDV reads in the upper respiratory tract microbiome of humans from rural and urban areas in Maharashtra, India. Nasopharyngeal and oropharyngeal swab samples collected for SARS-CoV-2 surveillance underwent whole-genome metagenomics sequencing, revealing LSDV reads in 25% of samples. Split kmer analysis provided insights into sample relatedness despite the low coverage of LSDV reads with the reference genome. Our findings, which include the detection of LSDV contigs aligning to specific locations on the reference genome, suggest a common source for LSDV reads, potentially shared water sources, or milk/milk products. Further investigation is needed to ascertain the mode of transmission and reason for the detection of LSDV reads in human upper respiratory tract.

E-Cigarette Use, Cigarette Smoking, and Sex are Associated with Nasal Microbiome Dysbiosis.

Previous research suggests that e-cigarettes can alter immune function, including in the nasal mucosa, in unique ways. The respiratory microbiome plays a key role in respiratory host defense, but the effects of e-cigarettes on the respiratory or nasal microbiome, are not well understood. Using 16S rRNA gene sequencing on nasal samples from adult e-cigarette users, smokers, and nonsmokers, we determined that e-cigarette use and cigarette smoking are associated with differential respiratory microbiome dysbiosis and substantial sex-dependent differences in the nasal microbiome, particularly in e-cigarette users. Staphylococcus aureus, a common respiratory pathogen, was more abundant in both e-cigarette users and smokers in comparison with nonsmokers, while Lactobacillus iners, often consider a protective species, was more abundant in smokers but less abundant in e-cigarette users in comparison with nonsmokers. In addition, we identified significant dysbiosis of the nasal microbiome between e-cigarette users and smokers with high versus low serum cotinine levels, an indicator of tobacco product use and toxicant exposure. We also analyzed nasal lavage fluid for immune mediators associated with host-microbiota interactions. Our analysis identified disruption of immune mediators in the nose of e-cigarette users and smokers, which is indicative of disrupted respiratory mucosal immune responses. Taken together, our data identified unique, sex-dependent host immune dysfunction associated with e-cigarette use in the nasal mucosa. More broadly, our data highlight the need for continued inclusion and careful consideration of sex as an important variable in the context of toxicant exposures. This is the first study investigating the effects of e-cigarette use and sex on the nasal microbiome, which is considered an important gatekeeper for protecting the lower respiratory tract from pathogens. We found significant sex, exposure group, and serum cotinine level associated differences in the composition of the nasal microbiome, demonstrating the importance of considering sex in future nasal microbiome studies and warranting further investigation of the mechanisms by which e-cigarette use dysregulates nasal immune homeostasis.

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

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

Cross-domain microbiomes: the interaction of gut, lung and environmental microbiota in asthma pathogenesis.

Recent experimental and epidemiological studies underscore the vital interaction between the intestinal microbiota and the lungs, an interplay known as the "gut-lung axis". The significance of this axis has been further illuminated following the identification of intestinal microbial metabolites, such as short-chain fatty acids (SCFA), as key mediators in setting the tone of the immune system. Through the gut-lung axis, the gut microbiota and its metabolites, or allergens, are directly or indirectly involved in the immunomodulation of pulmonary diseases, thereby increasing susceptibility to allergic airway diseases such as asthma. Asthma is a complex outcome of the interplay between environmental factors and genetic predispositions. The concept of the gut-lung axis may offer new targets for the prevention and treatment of asthma. This review outlines the relationships between asthma and the respiratory microbiome, gut microbiome, and environmental microbiome. It also discusses the current advancements and applications of microbiomics, offering novel perspectives and strategies for the clinical management of chronic respiratory diseases like asthma.

Time to re-set our thinking about airways disease: lessons from history, the resurgence of chronic bronchitis / PBB and modern concepts in microbiology.

In contrast to significant declines in deaths due to lung cancer and cardiac disease in Westernised countries, the mortality due to 'chronic obstructive pulmonary disease' (COPD) has minimally changed in recent decades while 'the incidence of bronchiectasis' is on the rise. The current focus on producing guidelines for these two airway 'diseases' has hindered progress in both treatment and prevention. The elephant in the room is that neither COPD nor bronchiectasis is a disease but rather a consequence of progressive untreated airway inflammation. To make this case, it is important to review the evolution of our understanding of airway disease and how a pathological appearance (bronchiectasis) and an arbitrary physiological marker of impaired airways (COPD) came to be labelled as 'diseases'. Valuable insights into the natural history of airway disease can be obtained from the pre-antibiotic era. The dramatic impacts of antibiotics on the prevalence of significant airway disease, especially in childhood and early adult life, have largely been forgotten and will be revisited as will the misinterpretation of trials undertaken in those with chronic (bacterial) bronchitis. In the past decades, paediatricians have observed a progressive increase in what is termed 'persistent bacterial bronchitis' (PBB). This condition shares all the same characteristics as 'chronic bronchitis', which is prevalent in young children during the pre-antibiotic era. Additionally, the radiological appearance of bronchiectasis is once again becoming more common in children and, more recently, in adults. Adult physicians remain sceptical about the existence of PBB; however, in one study aimed at assessing the efficacy of antibiotics in adults with persistent symptoms, researchers discovered that the majority of patients exhibiting symptoms of PBB were already on long-term macrolides. In recent decades, there has been a growing recognition of the importance of the respiratory microbiome and an understanding of the ability of bacteria to persist in potentially hostile environments through strategies such as biofilms, intracellular communities, and persister bacteria. This is a challenging field that will likely require new approaches to diagnosis and treatment; however, it needs to be embraced if real progress is to be made.

Exploring the Impact of Airway Microbiome on Asthma Morbidity: A Focus on the "Constructing a 'Eubiosis Reinstatement Therapy' for Asthma-CURE" Project.

The asthma pandemic imposes a huge burden on patients and health systems in both developed and developing countries. Despite available treatments, symptom control is generally suboptimal, and hospitalizations and deaths remain at unacceptably high levels. A pivotal aspect of asthma that warrants further exploration is the influence of the respiratory microbiome and virome in modulating disease activity. A plethora of studies report that the respiratory microbiome is characteristically dysbiotic in asthma. In addition, our data suggest that dysbiosis is also observed on the respiratory virome, partly characterized by the reduced abundance of bacteriophages (phages). Even though phages can naturally infect and control their bacterial prey, phage therapy has been grossly neglected in the Western world, although more recently it is more widely used as a novel tool against bacterial infections. However, it has never been used for tackling microbiome dysbiosis in human non-communicable diseases. This review provides an up-to-date understanding of the microbiome and virome's role within the airways in relation to asthma morbidity. It also advances the rationale and hypothesis for the CURE project. Specifically, the CURE project suggests that managing the respiratory microbiome through phage therapy is viable and may result in restoring eubiosis within the asthmatic airway. This entails controlling immune dysregulation and the clinical manifestation of the disease. To accomplish this goal, it is crucial to predict the effects of introducing specific phage mixtures into the intricate ecology of the airways and devise suitable interventions.

Deciphering Microbial Shifts in the Gut and Lung Microbiomes of COVID-19 Patients.

COVID-19, caused by SARS-CoV-2, results in respiratory and cardiopulmonary infections. There is an urgent need to understand not just the pathogenic mechanisms of this disease but also its impact on the physiology of different organs and microbiomes. Multiple studies have reported the effects of COVID-19 on the gastrointestinal microbiota, such as promoting dysbiosis (imbalances in the microbiome) following the disease's progression. Deconstructing the dynamic changes in microbiome composition that are specifically correlated with COVID-19 patients remains a challenge. Motivated by this problem, we implemented a biomarker discovery pipeline to identify candidate microbes specific to COVID-19. This involved a meta-analysis of large-scale COVID-19 metagenomic data to decipher the impact of COVID-19 on the human gut and respiratory microbiomes. Metagenomic studies of the gut and respiratory microbiomes of COVID-19 patients and of microbiomes from other respiratory diseases with symptoms similar to or overlapping with COVID-19 revealed 1169 and 131 differentially abundant microbes in the human gut and respiratory microbiomes, respectively, that uniquely associate with COVID-19. Furthermore, by utilizing machine learning models (LASSO and XGBoost), we demonstrated the power of microbial features in separating COVID-19 samples from metagenomic samples representing other respiratory diseases and controls (healthy individuals), achieving an overall accuracy of over 80%. Overall, our study provides insights into the microbiome shifts occurring in COVID-19 patients, shining a new light on the compositional changes.

Comparative microbiome analysis in cystic fibrosis and non-cystic fibrosis bronchiectasis.

Bronchiectasis is a condition characterized by abnormal and irreversible bronchial dilation resulting from lung tissue damage and can be categorized into two main groups: cystic fibrosis (CF) and non-CF bronchiectasis (NCFB). Both diseases are marked by recurrent infections, inflammatory exacerbations, and lung damage. Given that infections are the primary drivers of disease progression, characterization of the respiratory microbiome can shed light on compositional alterations and susceptibility to antimicrobial drugs in these cases compared to healthy individuals. To assess the microbiota in the two studied diseases, 35 subjects were recruited, comprising 10 NCFB and 13 CF patients and 12 healthy individuals. Nasopharyngeal swabs and induced sputum were collected, and total DNA was extracted. The DNA was then sequenced by the shotgun method and evaluated using the SqueezeMeta pipeline and R. We observed reduced species diversity in both disease cohorts, along with distinct microbial compositions and profiles of antimicrobial resistance genes, compared to healthy individuals. The nasopharynx exhibited a consistent microbiota composition across all cohorts. Enrichment of members of theBurkholderiaceaefamily and an increased Firmicutes/Bacteroidetes ratio in the CF cohort emerged as key distinguishing factors compared to NCFB group.Staphylococcus aureusand Prevotella shahii also presented differential abundance in the CF and NCFB cohorts, respectively, in the lower respiratory tract. Considering antimicrobial resistance, a high number of genes related to antibiotic efflux were detected in both disease groups, which correlated with the patient's clinical data. Bronchiectasis is associated with reduced microbial diversity and a shift in microbial and resistome composition compared to healthy subjects. Despite some similarities, CF and NCFB present significant differences in microbiome composition and antimicrobial resistance profiles, suggesting the need for customized management strategies for each disease.

Neonatal Microbiome: Is it Still Beneficial?

The neonatal microbiome includes all the microorganisms living within or on the surface of the newborn, as well as their genes (i.e., bacteria, fungi, and viruses), which are composed mainly of bacteria. The majority of these microorganisms reside in the gastrointestinal tract (GIT), which is known as the gut microbiome. They include trillions of microbes, which exceed the total number of neonate cells. In this study, we have examined factors affecting neonatal microbiome colonization, various phyla of the microbiome in neonates, and their characteristics. In addition, we have discussed symbiosis and dysbiosis, precipitating diseases, breast milk's role in the neonatal gut microbiome, prebiotics, probiotics, postbiotics, and synbiotics, as well as the airway or respiratory microbiome, and the main role of the neonatal microbiome. We have also discussed neonatal mycobiome and neonatal virome, as well as the research done on the neonatal microbiome.

Integrative analyses identify opportunistic pathogens of patients with lower respiratory tract infections based on metagenomic next-generation sequencing

Lower respiratory tract infections (LRTIs) represent some of the most globally prevalent and detrimental diseases. Metagenomic next-generation sequencing (mNGS) technology has effectively addressed the requirement for the diagnosis of clinical infectious diseases. This study aimed at identifying and classifying opportunistic pathogens from the respiratory tract-colonizing microflora in LRTI patients using data acquired from mNGS analyses. A retrospective study was performed employing the mNGS data pertaining to the respiratory samples derived from 394 LRTIs patients. Linear discriminant analysis effect size (LEfSe) analysis was conducted to discern the discriminant bacteria. Receiver operating characteristic curves (ROC) were established to demonstrate discriminant bacterial behavior to distinguish colonization from infection. A total of 443 discriminant bacteria were identified and segregated into three cohorts contingent upon their correlation profiles, detection frequency, and relative abundance in order to distinguish pathogens from colonizing microflora. Among them, 119 emerging opportunistic pathogens (cohort 2) occupied an average area under the curve (AUC) of 0.976 for exhibiting the most prominent predictability in distinguishing colonization from infection, 39 were colonizing bacteria (cohort 1, 0.961), and 285 were rare opportunistic pathogens (cohort 3, 0.887). The LTRIs patients appeared modular in the form of cohorts depicting complex microbial co-occurrence networks, reduced diversity, and a high degree of antagonistic interactions in the respiratory tract microbiome. The study findings indicate that therapeutic interventions should target interaction networks rather than individual microbes, providing an innovative perspective for comprehending and combating respiratory infections. Conclusively, this study reports a profile of LRTIs-associated bacterial colonization and opportunistic pathogens in a relatively large-scale cohort, which might serve as a reference panel for the interpretation of mNGS results in clinical practice.

Enhancing pathogen detection and characterization of respiratory microbiome signatures of infection through next-generation sequencing

Next-generation sequencing-based (NGS) methods for pathogen detection, which can capture the entire microbial composition in a clinical sample, are used strategically in parallel to culture-based methods. While NGS-based methods cannot confirm organism viability, culture-based methods can but are limited by the number of culture conditions routinely utilized in clinical microbiology laboratories. The relatively wide scope provided by sequencing compensates for the limited scope of culture-based methods but creates obstacles in distinguishing pathogens from an expected body-site-specific microbiome or benign transient colonizers. This study compares NGS-based methods for pathogen detection in respiratory samples to current diagnostics at Texas Children's Hospital in Houston, Texas. Current diagnostics include various culture-based assays, targeted PCR assays, and reference laboratory-generated sequencing. We hypothesize that employing sample metadata (source, type, etc.) and patient data (clinical history, chronic conditions, etc.) during data analysis will help distinguish pathogens from expected flora in respiratory samples. To develop these methods, 27 respiratory samples with suffcient volume for both routine diagnostic testing and this study were collected. Nucleic acid was extracted using the Qiagen DNeasy PowerSoil Pro Kit after collection, and targeted short-read sequencing (16S, 18S/ITS) was performed. These data were then analyzed using a custom bioinformatic pipeline built around Qiime2-2022. In brief, sequences are denoised and quality filtered using DADA2, an algorithm that uses a statistical model for correcting sequencing errors, after which similar amplicon sequence variants (ASVs) are clustered. Next, a feature table of ASVs that are 100% identical is generated, and taxonomy assigned using a naive Bayes taxonomy classifier against the Silva 13.2 database. Finally, unassigned and low abundance ASVs are removed. When species-level identification couldn't be determined through targeted short-read sequencing, untargeted long-read sequencing was used. In one case, we found that a bronchoalveolar lavage sample from the lung of a patient with a history of recurrent pneumonia contained a singular pathogenic bacterium, H. influenzae. This finding agreed with results obtained through reference laboratory-generated sequencing. In another case, we identified >14 unique bacteria at varying concentrations in a wash sample collected from the lung of an asymptomatic patient during a routine bronchoscopy. These findings, however, were determined to be expected respiratory flora. Our NGS-based methods’ enhanced pathogen detection compared to current diagnostics and discriminates between respiratory flora and active infections. Setting thresholds for pathogen detection, evaluating clinical relevance in the context of body site and presentation, and deploying additional molecular techniques when necessary are crucial steps to increase the accuracy of pathogen detection in the clinic. This study was supported by the Texas Children's Hospital Department of Pathology. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Sputum bacterial microbiota signature as a surrogate for predicting disease progression of nontuberculous mycobacterial lung disease

ObjectivesPredicting progression of nontuberculous mycobacterial lung disease (NTM-LD) remains challenging. This study evaluated whether sputum bacterial microbiome diversity can be the biomarker and provide novel insights into related phenotypes and treatment timing. MethodsWe analyzed 126 sputum microbiomes of 126 patients with newly diagnosed NTM-LD due to Mycobacterium avium complex, M. abscessus complex, and M. kansasii between May 2020 and December 2021. Patients were followed for 2 years to determine their disease progression status. We identified consistently representative genera that differentiated the progressor and nonprogressor by using six methodologies. These genera were used to construct a prediction model using random forest with 5-fold cross validation. ResultsDisease progression occurred in 49 (38.6%) patients. Compared with nonprogressors, α-diversity was lower in the progressors. Significant compositional differences existed in the β-diversity between groups (p=0.001). The prediction model for NTM-LD progression constructed using seven genera (Burkholderia, Pseudomonas, Sphingomonas, Candidatus Saccharibacteria, Phocaeicola, Pelomonas, and Phascolarctobacterium) with significantly differential abundance achieved an area under curve of 0.871. ConclusionsIdentification of the composition of sputum bacterial microbiome facilitates prediction of the course of NTM-LD, and maybe used to develop precision treatment involving modulating the respiratory microbiome composition to ameliorate NTM-LD.

Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease

BackgroundThe human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case–control results has made the identification of consistent and generalizable URT-disease associations difficult.ResultsIn order to address this issue, we assembled 26 independent 16S rRNA gene amplicon sequencing data sets from case–control URT studies, with approximately 2–3 studies per respiratory condition and ten distinct conditions covering common chronic and acute respiratory diseases. We leveraged the healthy control data across studies to investigate URT associations with age, sex, and geographic location, in order to isolate these associations from health and disease states.ConclusionsWe found several robust genus-level associations, across multiple independent studies, with either health or disease status. We identified disease associations specific to a particular respiratory condition and associations general to all conditions. Ultimately, we reveal robust associations between the URT microbiome, health, and disease, which hold across multiple studies and can help guide follow-up work on potential URT microbiome diagnostics and therapeutics.

Composition of the sputum bacterial microbiome of patients with different pathomorphological forms of non-small-cell lung cancer.

Recent studies have shown that the bacterial microbiome of the respiratory tract influences the development of lung cancer. Changes in the composition of the microbiome are observed in patients with chronic inflammatory processes. Such microbiome changes may include the occurrence of bacteria that cause oxidative stress and that are capable of causing genome damage in the cells of the host organism directly and indirectly. To date, the composition of the respiratory microbiome in patients with various histological variants of lung cancer has not been studied. In the present study, we determined the taxonomic composition of the sputum microbiome of 52 patients with squamous cell carcinoma of the lung, 52 patients with lung adenocarcinoma and 52 healthy control donors, using next-generation sequencing (NGS) on the V3-V4 region of the bacterial gene encoding 16S rRNA. The sputum microbiomes of patients with different histological types of lung cancer and controls did not show significant differences in terms of the species richness index (Shannon); however, the patients differed from the controls in terms of evenness index (Pielou). The structures of bacterial communities (beta diversity) in the adenocarcinoma and squamous cell carcinoma groups were also similar; however, when analyzed according to the matrix constructed by the Bray-Curtis method, there were differences between patients with squamous cell carcinoma and healthy subjects, but not between those with adenocarcinoma and controls. Using the LEFse method it was possible to identify an increase in the content of Bacillota (Streptococcus and Bacillus) and Actinomycetota (Rothia) in the sputum of patients with squamous cell carcinoma when compared with samples from patients with adenocarcinoma. There were no differences in the content of bacteria between the samples of patients with adenocarcinoma and the control ones. The content of representatives of the genera Streptococcus, Bacillus, Peptostreptococcus (phylum Bacillota), Prevotella, Macellibacteroides (phylum Bacteroidota), Rothia (phylum Actinomycetota) and Actinobacillus (phylum Pseudomonadota) was increased in the microbiome of sputum samples from patients with squamous cell carcinoma, compared with the control. Thus, the sputum bacterial microbiome of patients with different histological types of non-small-cell lung cancer has significant differences. Further research should be devoted to the search for microbiome biomarkers of lung cancer at the level of bacterial species using whole-genome sequencing.

Influence of Respiratory and Gut Microbiome on the Outcome of Tuberculosis: A Comprehensive Review

Influence of Respiratory and Gut Microbiome on the Outcome of Tuberculosis: A Comprehensive Review

Differential abundance in upper respiratory microbiome between smoking and non-smoking COVID-19 patients

The COVID-19 pandemic caused by SARS-CoV-2 has resulted in significant respiratory morbidity and mortality. Smoking is a well-established risk factor for adverse respiratory outcomes, and it may exacerbate COVID-19 outcomes by altering the upper respiratory tract (URT) microbiome. However, the association between smoking, the URT microbiome, and COVID-19 severity remains controversial. In this study, we investigated the microbial community in the UTR of smoking and non-smoking COVID-19 patients using 16S ribosomal RNA metagenomic datasets. By characterizing the microbial profiles of the URT of 88 COVID-19 patients with and without a smoking history, we examined the differences in the URT microbiome between smokers and non-smokers and identified bacteria that could serve as smoking signatures. Our study found that Prevotella was the most abundant genus in the URT microbiome of both smoking and non-smoking COVID-19 patients, followed by five other dominant genera. Notably, Fusobacterium was significantly higher in smokers than non-smokers, suggesting that smoking may affect the URT microbial composition. However, the alpha and beta diversity indices showed no significant differences within and across communities, regardless of smoking status or levels of severity. Differential abundance analysis suggested that the impact of smoking on the URT microbiome may lead to an increase in the abundance of Streptobacillus in smoking patients. Overall, this study highlights the potential impact of smoking on the URT microbiome and its relevance to COVID-19 outcomes. Thus, it provides insights into the underlying mechanisms that may lead to worsened COVID-19 outcomes due to smoking-induced alterations in the URT microbiome.

Expression of Concern: Bacteroides ihuae’ sp. nov., a new bacterial species isolated from the human respiratory microbiome

Expression of Concern: Bacteroides ihuae’ sp. nov., a new bacterial species isolated from the human respiratory microbiome

Nasopharyngeal microbiota in children is associated with severe asthma exacerbations

BackgroundThe respiratory microbiome has been associated with the etiology and disease course of asthma. ObjectiveThis study assessed the nasopharyngeal microbiota in children with a severe asthma exacerbation and their associations with medication, air quality and viral infection. MethodsA cross-sectional study was performed among children aged 2-18 years admitted to the medium (MCU; n=84) or intensive care (ICU; n=78) with an asthma exacerbation. For case-control analyses, we matched all cases aged 2-6 years (n=87) to controls in a 1:2 ratio. Controls were participants of either a prospective case-control study or a longitudinal birth cohort (n=182). The nasopharyngeal microbiome was characterized by 16S-rRNA-gene sequencing. ResultsCases showed higher Shannon diversity (ICU and MCU combined; p=0.002) and a distinct microbial community composition when compared to controls (PERMANOVA R2=1.9%, p<0.001). We observed significantly higher abundance of Staphylococcus and ‘oral’ taxa, including Neisseria, Veillonella and Streptococcus spp. and lower abundance of Dolosigranulum pigrum, Corynebacterium and Moraxella spp. (MaAsLin2, q<0.25) in cases versus controls. Furthermore, Neisseria abundance was associated with more severe disease (ICU vs MCU MaAslin2 p=0.03, q=0.30). Neisseria spp. abundance was also related with fine particulate matter exposure, whereas Haemophilus and Streptoccocus abundance was related with recent inhalation corticosteroid use. We observed no correlations with viral infection. ConclusionOur results demonstrate that children admitted with asthma exacerbations harbor a microbiome characterized by overgrowth of Staphylococcus and ‘oral’ microbes, and an underrepresentation of beneficial niche-appropriate commensals. Several of these associations may be explained by (environmental or medical) exposures, although cause-consequence relationships remain unclear and requires further investigations.

Indoor plants regulate the respiratory bacteria of high-altitude migrants and improve their environmental adaptability

Migrants traveling from plains to Ngari Prefecture, Tibet, China, with an average altitude of over 4500 m, may suffer serious respiratory function deterioration. Regulating the respiratory microbiome by altering residence indoor air microbiome is a potential approach to improve their respiratory health. To investigate the impact of indoor plants on the respiratory bacteria of high-altitude migrants and its effects on respiratory system health, based on 16S rRNA gene sequencing of 56 respiratory samples and 56 indoor air samples from the participants in Ngari, this study analyzed the effects of indoor plants on the respiratory bacteria of Ngari migrants, compared the effects of indoor plants on migrants and local Tibetans, and analyzed the association between plant-related respiratory bacteria changes and health protection. Migrants with different numbers of indoor plants exhibited significant difference in respiratory bacteria β diversity. Compared to migrants with fewer plants, migrants with more plants had an approximately 23% lower cumulative relative abundance of pathogenic genera in their respiratory dominant genera, and had 10 unique indoor air-respiratory shared core OTUs, some of which belong to plant-related genera. Migrants with different numbers of indoor plants showed greater differences in respiratory bacteria diversity and specific taxa compared to local Tibetans. Migrants with more indoor plants possessed individual unique indoor air-respiratory shared core OTUs that were significantly positively correlated with inspiratory reserve volume or expiratory reserve volume. Overall, indoor plants alter the diversity and composition of migrants' respiratory bacteria, and the changes in composition positively impact on respiratory health and high-altitude adaptability.

Detailed Characterization of the Lung-Gut Microbiome Axis Reveals the Link between PD-L1 and the Microbiome in Non-Small-Cell Lung Cancer Patients.

Next-generation sequencing technologies have started a new era of respiratory tract research in recent years. Alterations in the respiratory microbiome between healthy and malignant conditions have been revealed. However, the composition of the microbiome varies among studies, even in similar medical conditions. Also, there is a lack of complete knowledge about lung-gut microbiome interactions in lung cancer patients. The aim of this study was to explore the lung-gut axis in non-small-cell lung cancer (NSCLC) patients and the associations between lung-gut axis microbiota and clinical parameters (CRP, NLR, LPS, CD8, and PD-L1). Lung tissue and fecal samples were used for bacterial 16S rRNA sequencing. The results revealed, for the first time, that the bacterial richness in lung tumor tissue gradually decreased with an increase in the level of PD-L1 expression (p < 0.05). An analysis of β-diversity indicated a significant positive correlation between the genera Romboutsia and Alistipes in both the lung tumor biopsies and stool samples from NSCLC patients (p < 0.05). Survival analysis showed that NSCLC patients with higher bacterial richness in their stool samples had prolonged overall survival (HR: 2.06, 95% CI: 1.025-4.17, p = 0.0426).