Lower Respiratory Tract Microbiome Research Articles

Integrating respiratory microbiome and host immune response through machine learning for respiratory tract infection diagnosis

At present, the diagnosis of lower respiratory tract infections (LRTIs) is difficult, and there is an urgent need for better diagnostic methods. This study enrolled 136 patients from 2020 to 2021 and collected bronchoalveolar lavage fluid (BALF) specimens. We used metatranscriptome to analyze the lower respiratory tract microbiome (LRTM) and host immune response. The diversity of the LRTM in LRTIs significantly decreased, manifested by a decrease in the abundance of normal microbiota and an increase in the abundance of opportunistic pathogens. The upregulated differentially expressed genes (DEGs) in the LRTIs group were mainly enriched in infection immune response-related pathways. Klebsiella pneumoniae had the most significant increase in abundance in LRTIs, which was strongly correlated with host infection or inflammation genes TNFRSF1B, CSF3R, and IL6R. We combined LRTM and host transcriptome data to construct a machine-learning model with 12 screened features to discriminate LRTIs and non-LRTIs. The results showed that the model trained by Random Forest in the validate set had the best performance (ROC AUC: 0.937, 95% CI: 0.832–1). The independent external dataset showed an accuracy of 76.5% for this model. This study suggests that the model integrating LRTM and host transcriptome data can be an effective tool for LRTIs diagnosis.

Lower respiratory tract microbiome and lung cancer risk prediction in patients with diffuse lung parenchymal lesions.

In clinical practice, imaging manifestations of diffuse lung parenchymal lesions are common and indicative of various diseases, making differential diagnosis difficult. Some of these lesions are eventually diagnosed as lung cancer. Because respiratory microorganisms play an important role in lung cancer development, we searched for microbial markers that could predict the risk of lung cancer by retrospectively analyzing the lower respiratory tract (LRT) microbiome of 158 patients who were hospitalized in the First Affiliated Hospital of Guangzhou Medical University (March 2021-March 2023) with diffuse lung parenchymal lesions. The final diagnosis was lung cancer in 21 cases, lung infection in 93 cases, and other conditions (other than malignancy and infections) in 44 cases. The patient's clinical characteristics and the results of metagenomic next-generation sequencing of bronchoalveolar lavage fluid (BALF) were analyzed. Body mass index (BMI) and LRT microbial diversity (Shannon, Simpson, species richness, and Choa1 index) were significantly lower (P< 0.001, respectively) and Lactobacillus acidophilus relative abundance in the LRT was significantly higher (P< 0.001) in patients with lung cancer. The relative abundance of L. acidophilus in BALF combined with BMI was a good predictor of lung cancer risk (area under the curve = 0.985, accuracy = 98.46%, sensitivity = 95.24%, and specificity = 100.00%; P< 0.001). Our study showed that an imbalance in the component ratio of the microbial community, diminished microbial diversity, and the presence of specific microbial markers in the LRT predicted lung cancer risk in patients with imaging manifestations of diffuse lung parenchymal lesions.

Comparing sputum microbiota characteristics between severe and critically ill influenza patients.

Currently, limited attention has been directed toward utilizing clinical cohorts as a starting point to elucidate alterations in the lower respiratory tract (LRT) microbiota following influenza A virus (IAV) infection. Our objective was to undertake a comparative analysis of the diversity and composition of sputum microbiota in individuals afflicted by severe and critically ill influenza patients. Sputum specimens were procured from patients diagnosed with IAV infection for the purpose of profiling the microbiota using 16S-rDNA sequencing. To ascertain taxonomic differences between the severe and critically ill influenza cohorts, we leveraged Linear Discriminant Analysis Effect Size (LEfSe). Additionally, Spearman correlation analysis was employed to illuminate associations between sputum microbiota and influenza Ct values alongside laboratory indicators. Our study encompassed a total cohort of 64 patients, comprising 48 within the severe group and 16 within the critically ill group. Intriguingly, Bacteroidetes exhibited significant depletion in the critically ill cohort (p=0.031). The sputum microbiomes of the severe influenza group were hallmarked by an overrepresentation of Neisseria, Porphyromonas, Actinobacillus, Alloprevotella, TM7x, and Clostridia_UCG-014, yielding ROC-plot AUC values of 0.71, 0.68, 0.60, 0.70, 0.70, and 0.68, respectively. Notably, Alloprevotella exhibited an inverse correlation with influenza Ct values. Moreover, C-reactive protein (CRP) manifested a positive correlation with Haemophilus and Porphyromonas. The outcomes of this investigation lay the groundwork for future studies delving into the connection between the LRT microbiome and respiratory disorders. Further exploration is warranted to elucidate the intricate mechanisms underlying the interaction between IAV and Alloprevotella, particularly in disease progression.

The upper and lower respiratory tract microbiome in severe aspiration pneumonia

Uncertainty persists whether anaerobic bacteria represent important pathogens in aspiration pneumonia. In a nested case-control study of mechanically ventilated patients classified as macro-aspiration pneumonia (MAsP, n= 56), non-macro-aspiration pneumonia (NonMAsP, n= 91), and uninfected controls (n= 11), we profiled upper (URT) and lower respiratory tract (LRT) microbiota with bacterial 16S rRNA gene sequencing, measured plasma host-response biomarkers, analyzed bacterial communities by diversity and oxygen requirements, and performed unsupervised clustering with Dirichlet Multinomial Models (DMM). MAsP and NonMAsP patients had indistinguishable microbiota profiles by alpha diversity and oxygen requirements with similar host-response profiles and 60-day survival. Unsupervised DMM clusters revealed distinct bacterial clusters in the URT and LRT, with low-diversity clusters enriched for facultative anaerobes and typical pathogens, associated with higher plasma levels of SPD and sCD14 and worse 60-day survival. The predictive inter-patient variability in these bacterial profiles highlights the importance of microbiome study in patient sub-phenotyping and precision medicine approaches for severe pneumonia.

Lower respiratory tract microbiome composition and community interactions in smokers.

The lung microbiome impacts on lung function, making any smoking-induced changes in the lung microbiome potentially significant. The complex co-occurrence and co-avoidance patterns between the bacterial taxa in the lower respiratory tract (LRT) microbiome were explored for a cohort of active (AS), former (FS) and never (NS) smokers. Bronchoalveolar lavages (BALs) were collected from 55 volunteer subjects (9 NS, 24 FS and 22 AS). The LRT microbiome composition was assessed using 16S rRNA amplicon sequencing. Identification of differentially abundant taxa and co-occurrence patterns, discriminant analysis and biomarker inferences were performed. The data show that smoking results in a loss in the diversity of the LRT microbiome, change in the co-occurrence patterns and a weakening of the tight community structure present in healthy microbiomes. The increased abundance of the genus Ralstonia in the lung microbiomes of both former and active smokers is significant. Partial least square discriminant and DESeq2 analyses suggested a compositional difference between the cohorts in the LRT microbiome. The groups were sufficiently distinct from each other to suggest that cessation of smoking may not be sufficient for the lung microbiota to return to a similar composition to that of NS. The linear discriminant analysis effect size (LEfSe) analyses identified several bacterial taxa as potential biomarkers of smoking status. Network-based clustering analysis highlighted different co-occurring and co-avoiding microbial taxa in the three groups. The analysis found a cluster of bacterial taxa that co-occur in smokers and non-smokers alike. The clusters exhibited tighter and more significant associations in NS compared to FS and AS. Higher degree of rivalry between clusters was observed in the AS. The groups were sufficiently distinct from each other to suggest that cessation of smoking may not be sufficient for the lung microbiota to return to a similar composition to that of NS.

Shared and Specific Lung Microbiota with Metabolic Profiles in Bronchoalveolar Lavage Fluid Between Infectious and Inflammatory Respiratory Diseases.

BackgroundInfiltration of the lower respiratory tract (LRT) microenvironment could be significantly associated with respiratory diseases. However, alterations in the LRT microbiome and metabolome in infectious and inflammatory respiratory diseases and their correlation with inflammation still need to be explored.MethodsBronchoalveolar lavage samples from 44 community-acquired pneumonia (CAP) patients, 29 connective tissue disease-associated interstitial disease (CTD-ILD) patients, and 30 healthy volunteers were used to detect microbiota and metabolites through 16S rRNA gene sequencing and untargeted high-performance liquid chromatography with mass spectrometry.ResultsThe composition of the LRT microbial communities and metabolites differed in disease states. CAP patients showed a significantly low abundance and both diseases presented a depletion of some genera of the phylum Bacteroidetes, including Prevotella, Porphyromonas, and health-associated metabolites, such as sphingosine (d16:1), which were negatively correlated with infectious indicators. In contrast, Bacillus and Mycoplasma were both enriched in the disease groups. Streptococcus was specifically increased in CTD-ILD. In addition, co-elevated metabolites such as FA (22:4) and pyruvic acid represented hypoxia and inflammation in the diseases. Significantly increased levels of amino acids and succinate, as well as decreased itaconic acid levels, were observed in CAP patients, whereas CTD-ILD patients showed only a handful of specific metabolic alterations. Functions related to microbial lipid and amino acid metabolism were significantly altered, indicating the possible contributions of microbial metabolism. Dual omics analysis showed a moderate positive correlation between the microbiome and metabolome. The levels of L-isoleucine and L-arginine were negatively correlated with Streptococcus, and itaconic acid positively correlated with Streptococcus.ConclusionIn the LRT microenvironment, shared and specific alterations occurred in CAP and CTD-ILD patients, which were associated with inflammatory and immune reactions, which may provide a new direction for future studies aiming to elucidate the mechanism, improve the diagnosis, and develop therapies for different respiratory diseases.

The Relationship Between Lower Respiratory Tract Microbiome and Allergic Respiratory Tract Diseases in Children

Similar to those in the upper respiratory tract, there are microbes present in the healthy human lower respiratory tract (LRT), including the lungs and bronchus. To evaluate the relationship between LRT microbiome and allergic respiratory diseases in children, we enrolled 68 children who underwent bronchoscopy from January 2018 to December 2018 in the affiliated hospital of the Capital Institute of Pediatrics. Using the total IgE (TIgE) values, children were divided into two groups: allergy sensitivity (AS) group and non-allergy sensitivity (NAS) group. Nucleic acid was extracted from samples of bronchoalveolar lavage fluid (BALF) from the two groups of children taken during bronchoscopy treatment and the 16S rDNA gene was sequenced and analyzed. The results showed that Haemophilus, Moraxella, Streptococcus, Prevotella, Neisseria, and Rothia were detected in all patients. There was a statistically significant difference in the composition and distribution of microbiota between the AS and NAS groups (p < 0.01). Analysis of the correlation of clinical indices and microbiome showed that TIgE was positively correlated with Bacteroidetes and negatively correlated with Streptococcus. Absolute lymphocyte count showed a relationship with Streptococcus, and the absolute neutrophil count or percentage of neutrophils showed a relationship with Cardiobacterium. The LRT microbiome functioned similarly to the intestinal microbiome. That is, the decrease in microbial diversity and the change in composition could lead to an increase in allergic symptoms. The microbiome of the LRT in children, especially that of Bacteriodetes and Streptococcus, showed a correlation with respiratory allergic diseases.

Functional profiling of COVID-19 respiratory tract microbiomes

In response to the ongoing global pandemic, characterizing the molecular-level host interactions of the new coronavirus SARS-CoV-2 responsible for COVID-19 has been at the center of unprecedented scientific focus. However, when the virus enters the body it also interacts with the micro-organisms already inhabiting the host. Understanding the virus-host-microbiome interactions can yield additional insights into the biological processes perturbed by viral invasion. Alterations in the gut microbiome species and metabolites have been noted during respiratory viral infections, possibly impacting the lungs via gut-lung microbiome crosstalk. To better characterize microbial functions in the lower respiratory tract during COVID-19 infection, we carry out a functional analysis of previously published metatranscriptome sequencing data of bronchoalveolar lavage fluid from eight COVID-19 cases, twenty-five community-acquired pneumonia patients, and twenty healthy controls. The functional profiles resulting from comparing the sequences against annotated microbial protein domains clearly separate the cohorts. By examining the associated metabolic pathways, distinguishing functional signatures in COVID-19 respiratory tract microbiomes are identified, including decreased potential for lipid metabolism and glycan biosynthesis and metabolism pathways, and increased potential for carbohydrate metabolism pathways. The results include overlap between previous studies on COVID-19 microbiomes, including decrease in the glycosaminoglycan degradation pathway and increase in carbohydrate metabolism. The results also suggest novel connections to consider, possibly specific to the lower respiratory tract microbiome, calling for further research on microbial functions and host-microbiome interactions during SARS-CoV-2 infection.

Highly homogeneous microbial communities dominated by Mycoplasma pneumoniae instead of increased resistance to macrolide antibiotics is the characteristic of lower respiratory tract microbiome of children with refractory Mycoplasma pneumoniae pneumonia

BackgroundAlthough researchers have found that the microbiota changed during the lower respiratory tract (LRT) infection, little was known about the association between LRT microbiome and refractory M. pneumoniae pneumonia (RMPP).MethodsFrom June 28th, 2019 to March 23rd, 2020, we enrolled fifty-two children diagnosed with RMPP or non-refractory M. pneumoniae pneumonia (NRMPP), and characterized the structure and function of microbiota in the bronchoalveolar lavage fluid (BALF) by metagenomic next generation sequencing (mNGS).ResultsBased on Bray-Curtis distance between samples, samples in RMPP group were highly homogeneous, and Shannon index in the RMPP group was much lower than NRMPP group while Simpson index, which presents the degree of dominance, was higher in RMPP group. The dominant taxon with relative abundance greater than 50% was merely Mycoplasma among RMPP and NRMPP patients, but the proportions of other taxonomic distribution were different. M. pneumoniae was the dominant species and occupied almost all niches in the vast majority of RMPP patients, whereas the other genera were dramatically lower. The NRMPP group was more enriched in antibiotic resistance genes (ARGs) than the RMPP group, and also exhibited a greater relative abundance of macrolide antibiotics resistance gene (macB) and fluoroquinolone antibiotic resistance genes (patA-B) in M. pneumoniae genome. In RMPP patients, higher relative abundance of Streptococcus pneumoniae had a strong correlation with increased hospitalization days while higher relative abundance of Streptococcus pneumoniae had a negative correlation with hospitalization days among NRMPP patients.ConclusionsThe microbiota of LRT in children with RMPP was much more homogeneous and simpler than that of the NRMPP group and with lower relative abundance of macrolide antibiotics resistance gene in M. pneumoniae genome. M. pneumoniae was absolutely dominant in the vast majority of RMPP patients. Prolonged hospitalization days was associated with relative abundance of M. pneumoniae in NRMPP patients while it was related with other pathogens’ relative abundance (e.g., Streptococcus pneumoniae) in RMPP patients.

The lower respiratory tract microbiome in pediatric patients with ventilator-associated pneumonia

Ventilator associated pneumonia(VAP)is one of the major source of nosocomial infection in PICU, of which the pathogenesis remains unclear.Recent metataxonomic and metagenomic technologies, from 16S ribosomal RNA to whole genome sequencing, have revealed that healthy lungs harbor a dynamic ecosystem of bacteria and dysbiosis of the respiratory microbiome involved in the pathogenesis and progression of VAP.Recent studies have illustrated that the imbalance of species diversity and abundance of lung microbiome might be the underlying cause of VAP through regulating local mucosal immune response.These methods offer the potential to better interrogate the relationship between an intubated individual′s respiratory microbiota and the underlying disease process to provide important insights into the pathogenesis of VAP, optimizing disease surveillance and multi-drug resistant microbes detection. Key words: Lung microbiome; Ventilator associated pneumonia; Metagenomics; 16S rRNA

Issue Highlights

IUBMB LifeVolume 71, Issue 2 p. 151-151 Issue HighlightsFree Access Issue Highlights First published: 09 January 2019 https://doi.org/10.1002/iub.2007AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat 152 Lung Inflammation and Disease: A Perspective on Microbial Homeostasis and Metabolism Roberto Mendez, Sulagna Banerjee, Sanjoy K. Bhattacharya, Santanu Banerjee The lung microbiome is significantly smaller than the gut microbiome, both in terms of diversity and biomass. The lower respiratory tract microbiome is constantly replenished by oral and upper respiratory tract microbiota and yet maintains a unique microbial signature. In this review, we provide a perspective on the role of these bacteria in health and disease. We touch upon the known challenges associated with lung microbiome studies and discuss various environmental factors and diseases where commensals are known to play a major role. Finally, we discuss the influence of bacterial metabolites in homeostasis and disease-induced microbial perturbations. 235 MicroRNA-101 Protects Bladder of BOO from Hypoxia- Induced Fibrosis by Attenuating TGF-β- smad2/3 Signaling Baimei He, Qiong Chen, Dongbo Zhou, Lijing Wang, Zhaoqian Liu Patients with benign prostatic hyperplasia often suffer from frequent micturition, the urgency of urination, the urine pain. Even the obstruction was removed, the symptom often remains. Studies have found it may be associated with the fibrosis of bladder after obstruction. Our study found hypoxia promoted the expression of ECM in bladder smooth muscle cells, and the expression of microRNA-101 was up-regulated in the bladder after obstruction. MicroRNA-101 restrained the smad2/3 signaling pathway through depressing the expression of TGFβR1. MicroRNA-101 is emerging as an anti-fibrotic miRNA in the remodeling of bladder after bladder outlet obstruction. 283 Synergistic Antifungal Activity of Isoquercitrin: Apoptosis and Membrane Permeabilization Related to Reactive Oxygen Species in Candida albicans Suhyun Kim, Eun-Rhan Woo, Dong Gun Lee Isoquercitrin (ISO) at non-antifungal concentration has synergistic effect with amphotericin B (AMB) and fluconazole (FLC). These combinations inhibited the activity of superoxide dismutase and lead to disruption of antioxidant system. The collapse of the antioxidant system highly increased reactive oxygen species (ROS) level. Their abnormal concentrations of ROS caused apoptosis in cells treated with ISO and FLC. In contrast, ROS had different effect on the cells treated with ISO and AMB by inducing membrane permeabilization. REFERENCES 1Mendez, R., Banerjee, S., Bhattacharya, S.K., and Banerjee, S. Lung Inflammation and Disease: A Perspective on Microbial Homeostasis and Metabolism. IUBMB Life. 2019, 71, 152– 165. Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 2Wang, N., Duan, L., Ding, J., Cao, Q., Qian, S., Shen, H., and Qi, J. MicroRNA-101 Protects Bladder of BOO from Hypoxia-Induced Fibrosis by Attenuating TGF-β- smad2/3 Signaling. IUBMB Life. 2019, 71, 235– 243. Wiley Online LibraryGoogle Scholar 3 Kim, S., Woo, E.-R., and Lee, D.G. Synergistic Antifungal Activity of Isoquercitrin: Apoptosis and Membrane Permeabilization Related to Reactive Oxygen Species in Candida albicans. IUBMB Life. 2019, 71, 283– 292. Wiley Online LibraryCASPubMedWeb of Science®Google Scholar Volume71, Issue2February 2019Pages 151-151 ReferencesRelatedInformation

Dysbiosis of Lower Respiratory Tract Microbiome Might Contribute to the Inflammation and Further Alter Its Function

Dysbiosis of Lower Respiratory Tract Microbiome Might Contribute to the Inflammation and Further Alter Its Function

Effects of smoking on the lower respiratory tract microbiome in mice

BackgroundRecent studies break with traditional opinion that the lower respiratory tract is sterile, and increasingly focus on the lung microbiome and disease. Smoking, as an important etiology of inflammatory lung disease, was considered as a factor influencing lung microbiome variations in our study, and we aimed to study the effect of smoking on inflammation and microbial diversity and community.MethodsForty male mice were selected and randomly divided into a smoking and a non-smoking group. Mice in the smoking group were exposed to smoke smog for 2 h/day for 90 days. Blood and lung tissues were obtained after the experiment, and ELISA was used to measure interleukin-6 and C reactive protein concentrations. 16S rRNA gene quantification and sequencing technology were used to compare microbial diversity and community between the two groups. SAS 9.1 and R software were used to analyze the data.ResultsThirty-six mice survived, and the weight of the smoking group increased more slowly than that of the non-smoking group. Denser inflammation and congestion were observed in the lungs of the smoking mice compared with the non-smoking group Higher microbial diversity was observed in the smoking group, and Enterobacter, Acidimicrobiales_norank, and Caulobacteraceae_Unclassified genus were significantly more abundant in the non-smoking group (P < 0.001).ConclusionsSmoking altered microbial diversities and communities in the lower respiratory tract of mice. Microbial variation should be considered in future studies focusing on smoking-induced inflammatory disease.

The lung microbiome in patients with pneumocystosis

BackroundPneumocystis jirovecii pneumonia (PCP) is an opportunistic fungal infection that is associated with a high morbidity and mortality in immunocompromised individuals. In this study, we analysed the microbiome of the lower respiratory tract from critically ill intensive care unit patients with and without pneumocystosis.MethodsBroncho-alveolar fluids from 65 intubated and mechanically ventilated intensive care unit patients (34 PCP+ and 31 PCP- patients) were collected. Sequence analysis of bacterial 16S rRNA gene V3/V4 regions was performed to study the composition of the respiratory microbiome using the Illumina MiSeq platform.ResultsDifferences in the microbial composition detected between PCP+ and PCP- patients were not statistically significant on class, order, family and genus level. In addition, alpha and beta diversity metrics did not reveal significant differences between PCP+ and PCP- patients. The composition of the lung microbiota was highly variable between PCP+ patients and comparable in its variety with the microbiota composition of the heterogeneous collective of PCP- patients.ConclusionsThe lower respiratory tract microbiome in patients with pneumocystosis does not appear to be determined by a specific microbial composition or to be dominated by a single bacterial species.

81 The concordance between the microbiome of the upper and lower respiratory tract is investigated in infants with cystic fibrosis

Background Nasopharyngeal (NP) and oropharyngeal samples (OP) are commonly used to direct therapy for lower respiratory tract (LRT) infections in non-expectorating infants with Cystic Fibrosis (CF). The level of concordance between microbiota of the upper respiratory tract (URT) and LRT in young children is, however, largely unknown. Objective To examine the concordance between URT and LRT microbiota in infants with CF. Methods Paired bronchoalveolar lavage fluid (BAL), NP and OP samples were longitudinally collected from 17 CF patients at the age of 3 and 12 months. We studied the concordance between the URT and LRT microbial communities by 16S-rRNA-based sequencing. Results Bacterial diversity is lower in NP compared to the OP and BAL samples. On group level, OP microbiota profiles showed more similarity with BAL microbiota compared to NP microbiota. However, potential pathogens like staphylococci , Moraxella and Haemophilus influenzae were almost exclusively observed in the NP but not in OP. Moreover, intraindividual concordance between both NP and OP microbiota profiles and paired BAL microbiota was limited. Conclusion At a population level, OP microbiota profiles resemble lung microbiota more closely than NP microbiota, however, potential respiratory pathogens are often detected in NP but not in OP samples. More importantly, within-individual concordance between the URT and LRT microbiome in CF patients is limited, restricting the diagnostic value of URT sampling during LRT infections in infancy. Whether microbiota profiling of BAL samples will indeed more reliably guide treatment of infections in CF infants compared to conventional culture remains to be studied.