Lung Microbiome Research Articles

Integrative genomic analysis of the lung tissue microenvironment in SARS-CoV-2 and NL63 patients

The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-CoV-2 virus has affected over 700 million people, and caused over 7 million deaths throughout the world as of April 2024, and continues to affect people through seasonal waves. While over 675 million people have recovered from this disease globally, the lingering effects of the disease are still under study. Long term effects of SARS-CoV-2 infection, known as 'long COVID,' include a wide range of symptoms including fatigue, chest pain, cellular damage, along with a strong innate immune response characterized by inflammatory cytokine production. Three years after the pandemic, data about long covid studies are finally emerging. More clinical studies and clinical trials are needed to understand and determine the factors that predispose individuals to these long-term side effects.In this methodology paper, our goal was to apply data driven approaches in order to explore the multidimensional landscape of infected lung tissue microenvironment to better understand complex interactions between viral infection, immune response and the lung microbiome of patients with (a) SARS-CoV-2 virus and (b) NL63 coronavirus. The samples were analyzed with several machine learning tools allowing simultaneous detection and quantification of viral RNA amount at genome and gene level; human gene expression and fractions of major types of immune cells, as well as metagenomic analysis of bacterial and viral abundance. To contrast and compare specific viral response to SARS-COV-2, we analyzed deep sequencing data from additional cohort of patients infected with NL63 strain of corona virus.Our correlation analysis of three types of RNA-seq based measurements in patients i.e. fraction of viral RNA (at genome and gene level), Human RNA (transcripts and gene level) and bacterial RNA (metagenomic analysis), showed significant correlation between viral load as well as level of specific viral gene expression with the fractions of immune cells present in lung lavage as well as with abundance of major fractions of lung microbiome in COVID-19 patients.Our methodology-based proof-of-concept study has provided novel insights into complex regulatory signaling interactions and correlative patterns between the viral infection, inhibition of innate and adaptive immune response as well as microbiome landscape of the lung tissue. These initial findings could provide better understanding of the diverse dynamics of immune response and the side effects of the SARS-CoV-2 infection and demonstrates the possibilities of the various types of analyses that could be performed from this type of data.

P228 Multicentre reviewof lung microbiome for patients with cystic fibrosis treated with elexacaftor/tezacaftor/ivacaftor

P228 Multicentre reviewof lung microbiome for patients with cystic fibrosis treated with elexacaftor/tezacaftor/ivacaftor

The impact of high-salt diet on asthma in humans and mice: Effect on specific T-cell signatures and microbiome.

The rise in asthma has been linked to different environmental and lifestyle factors including dietary habits. Whether dietary salt contributes to asthma incidence, remains controversial. We aimed to investigate the impact of higher salt intake on asthma incidence in humans and to evaluate underlying mechanisms using mouse models. Epidemiological research was conducted using the UK Biobank Resource. Data were obtained from 42,976 participants with a history of allergies. 24-h sodium excretion was estimated from spot urine, and its association with asthma incidence was assessed by Cox regression, adjusting for relevant covariates. For mechanistic studies, a mouse model of mite-induced allergic airway inflammation (AAI) fed with high-salt diet (HSD) or normal-salt chow was used to characterize disease development. The microbiome of lung and feces (as proxy for gut) was analyzed via 16S rRNA gene based metabarcoding approach. In humans, urinary sodium excretion was directly associated with asthma incidence among females but not among males. HSD-fed female mice displayed an aggravated AAI characterized by increased levels of total IgE, a TH2-TH17-biased inflammatory cell infiltration accompanied by upregulation of osmosensitive stress genes. HSD induced distinct changes in serum short chain fatty acids and in both gut and lung microbiome, with a lower Bacteroidetes to Firmicutes ratio and decreased Lactobacillus relative abundance in the gut, and enriched members of Gammaproteobacteria in the lung. High dietary salt consumption correlates with asthma incidence in female adults with a history of allergies. Female mice revealed HSD-induced T-cell lung profiles accompanied by alterations of gut and lung microbiome.

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.

Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning

BackgroundLower respiratory tract infections represent prevalent ailments. Nonetheless, current comprehension of the microbial ecosystems within the lower respiratory tract remains incomplete and necessitates further comprehensive assessment. Leveraging the advancements in metagenomic next-generation sequencing (mNGS) technology alongside the emergence of machine learning, it is now viable to compare the attributes of lower respiratory tract microbial communities among patients across diverse age groups, diseases, and infection types.MethodWe collected bronchoalveolar lavage fluid samples from 138 patients diagnosed with lower respiratory tract infections and conducted mNGS to characterize the lung microbiota. Employing various machine learning algorithms, we investigated the correlation of key bacteria in patients with concurrent bronchiectasis and developed a predictive model for hospitalization duration based on these identified key bacteria.ResultWe observed variations in microbial communities across different age groups, diseases, and infection types. In the elderly group, Pseudomonas aeruginosa exhibited the highest relative abundance, followed by Corynebacterium striatum and Acinetobacter baumannii. Methylobacterium and Prevotella emerged as the dominant genera at the genus level in the younger group, while Mycobacterium tuberculosis and Haemophilus influenzae were prevalent species. Within the bronchiectasis group, dominant bacteria included Pseudomonas aeruginosa, Haemophilus influenzae, and Klebsiella pneumoniae. Significant differences in the presence of Pseudomonas phage JBD93 were noted between the bronchiectasis group and the control group. In the group with concomitant fungal infections, the most abundant genera were Acinetobacter and Pseudomonas, with Acinetobacter baumannii and Pseudomonas aeruginosa as the predominant species. Notable differences were observed in the presence of Human gammaherpesvirus 4, Human betaherpesvirus 5, Candida albicans, Aspergillus oryzae, and Aspergillus fumigatus between the group with concomitant fungal infections and the bacterial group. Machine learning algorithms were utilized to select bacteria and clinical indicators associated with hospitalization duration, confirming the excellent performance of bacteria in predicting hospitalization time.ConclusionOur study provided a comprehensive description of the microbial characteristics among patients with lower respiratory tract infections, offering insights from various perspectives. Additionally, we investigated the advanced predictive capability of microbial community features in determining the hospitalization duration of these patients.

Markers Of Progression of Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a pressing problem in the modern world. Every year, COPD increasingly leads to temporary disability and death. This is why it is so important to predict the progression of COPD in time. Progression of the disease can lead to severe shortness of breath, frequent exacerbations of COPD, respiratory failure and death. This literature review examines radiological and functional markers, clinical manifestations, sputum and blood markers, and the lung microbiome. All of this may be useful for predicting the risk of COPD progression.

Comparison of the upper and lower airway microbiome in early postoperative lung transplant recipients.

Lung transplantation is the only therapeutic option for patients with end-stage lung disease, but its outcome is much worse than other solid organ transplants. Little is known about the NS and BALF microbiome of early postoperative LTRs. Here, we compared paired samples of the nasal and lung microbiome from 17 early postoperative LTRs and showed both difference and homogeneity between the two samples. Most of the "core" microbiome in both NS and BALF samples were recognized respiratory pathogens, suggesting that both samples can reflect the diseases characteristics of transplanted lung. We also found that the differences between upper and lower airway microbiome in early postoperative LTRs mainly come from sampling sites instead of sampling individuals.

Throat microbiota drives alterations in pulmonary alveolar microbiota in patients with septic ARDS

ABSTRACT Objectives The translocation of intestinal flora has been linked to the colonization of diverse and heavy lower respiratory flora in patients with septic ARDS, and is considered a critical prognostic factor for patients. Methods On the first and third days of ICU admission, BALF, throat swab, and anal swab were collected, resulting in a total of 288 samples. These samples were analyzed using 16S rRNA analysis and the traceability analysis of new generation technology. Results On the first day, among the top five microbiota species in abundance, four species were found to be identical in BALF and throat samples. Similarly, on the third day, three microbiota species were found to be identical in abundance in both BALF and throat samples. On the first day, 85.16% of microorganisms originated from the throat, 5.79% from the intestines, and 9.05% were unknown. On the third day, 83.52% of microorganisms came from the throat, 4.67% from the intestines, and 11.81% were unknown. Additionally, when regrouping the 46 patients, the results revealed a significant predominance of throat microorganisms in BALF on both the first and third day. Furthermore, as the disease progressed, the proportion of intestinal flora in BALF increased in patients with enterogenic ARDS. Conclusions In patients with septic ARDS, the main source of lung microbiota is primarily from the throat. Furthermore, the dynamic trend of the microbiota on the first and third day is essentially consistent.It is important to note that the origin of the intestinal flora does not exclude the possibility of its origin from the throat.

Cigarette smoke-induced dysbiosis: comparative analysis of lung and intestinal microbiomes in COPD mice and patients

BackgroundThe impact of cigarette smoke (CS) on lung diseases and the role of microbiome dysbiosis in chronic obstructive pulmonary disease (COPD) have been previously reported; however, the relationships remain unclear.MethodsOur research examined the effects of 20-week cigarette smoke (CS) exposure on the lung and intestinal microbiomes in C57BL/6JNarl mice, alongside a comparison with COPD patients’ intestinal microbiome data from a public dataset.ResultsThe study found that CS exposure significantly decreased forced vital capacity (FVC), thickened airway walls, and induced emphysema. Increased lung damage was observed along with higher lung keratinocyte chemoattractant (KC) levels by CS exposure. Lung microbiome analysis revealed a rise in Actinobacteriota, while intestinal microbiome showed significant diversity changes, indicating dysbiosis. Principal coordinate analysis highlighted distinct intestinal microbiome compositions between control and CS-exposed groups. In the intestinal microbiome, notable decreases in Patescibacteria, Campilobacterota, Defferibacterota, Actinobacteriota, and Desulfobacterota were observed. We also identified correlations between lung function and dysbiosis in both lung and intestinal microbiomes. Lung interleukins, interferon-ɣ, KC, and 8-isoprostane levels were linked to lung microbiome dysbiosis. Notably, dysbiosis patterns in CS-exposed mice were similar to those in COPD patients, particularly of Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 4 patients. This suggests a systemic impact of CS exposure.ConclusionIn summary, CS exposure induces significant dysbiosis in lung and intestinal microbiomes, correlating with lung function decline and injury. These results align with changes in COPD patients, underscoring the important role of microbiome in smoke-related lung diseases.

Culture-independent Multilocus sequence typing screening for Haemophilus influenzae cross-infection in non-cystic fibrosis bronchiectasis

Whether cross-infection of respiratory pathogens between patients with non-cystic fibrosis bronchiectasis occurs is debated. Investigation with traditional microbiological culture risks simplifying the lung microbiome. We demonstrate the use of culture-independent Multilocus sequence typing to screen for Haemophilus influenzae strain types in a cohort of twenty-eight patients with non-cystic fibrosis bronchiectasis.

Widespread alterations in systemic immune profile are linked to lung function heterogeneity and airway microbes in cystic fibrosis

BackgroundExcessive inflammation and recurrent airway infections characterize people with cystic fibrosis (pwCF), a disease with highly heterogeneous clinical outcomes. How the overall immune response is affected in pwCF, its relationships with the lung microbiome, and the source of clinical heterogeneity have not been fully elucidated. MethodsPeripheral blood and sputum samples were collected from 28 pwCF and an age-matched control group. Systemic immune cell subsets and surface markers were quantified using multiparameter flow cytometry. Lung microbiome composition was reconstructed using metatranscriptomics on sputum samples, and microbial taxa were correlated to circulating immune cells and surface markers expression. ResultsIn pwCF, we found a specific systemic immune profile characterized by widespread hyperactivation and altered frequencies of several subsets. These included substantial changes in B-cell subsets, enrichment of CD35+/CD49d+ neutrophils, and reduction in dendritic cells. Activation markers and checkpoint molecule expression levels differed from healthy subjects. CTLA-4 expression was increased in Tregs and, together with impaired B-cell subsets, correlated with patients' lung function. Concentrations and frequencies of key immune cells and marker expression correlated with the relative abundance of commensal and pathogenic bacteria in the lungs. ConclusionThe CF-specific immune signature, involving hyperactivation, immune dysregulation with alteration in Treg homeostasis, and impaired B-cell function, is a potential source of lung function heterogeneity. The activity of specific microbes contributes to disrupting the balance of the immune response. Our data provide a unique foundation for identifying novel markers and immunomodulatory targets to develop the future of cystic fibrosis treatment and management.

Polylactic acid micro/nanoplastic-induced hepatotoxicity: Investigating food and air sources via multi-omics

Micro/nanoplastics (MNPs) are detected in human liver, and pose significant risks to human health. Oral exposure to MNPs derived from non-biodegradable plastics can induce toxicity in mouse liver. Similarly, nasal exposure to non-biodegradable plastics can cause airway dysbiosis in mice. However, the hepatotoxicity induced by foodborne and airborne biodegradable MNPs remains poorly understood. Here we show the hepatotoxic effects of biodegradable polylactic acid (PLA) MNPs through multi-omics analysis of various biological samples from mice, including gut, fecal, nasal, lung, liver, and blood samples. Our results show that both foodborne and airborne PLA MNPs compromise liver function, disrupt serum antioxidant activity, and cause liver pathology. Specifically, foodborne MNPs lead to gut microbial dysbiosis, metabolic alterations in the gut and serum, and liver transcriptomic changes. Airborne MNPs affect nasal and lung microbiota, alter lung and serum metabolites, and disrupt liver transcriptomics. The gut Lachnospiraceae_NK4A136_group is a potential biomarker for foodborne PLA MNP exposure, while nasal unclassified_Muribaculaceae and lung Klebsiella are potential biomarkers for airborne PLA MNP exposure. The relevant results suggest that foodborne PLA MNPs could affect the “gut microbiota-gut-liver” axis and induce hepatoxicity, while airborne PLA MNPs could disrupt the “airway microbiota-lung-liver” axis and cause hepatoxicity. These findings have implications for diagnosing PLA MNPs-induced hepatotoxicity and managing biodegradable materials in the environment. Our current study could be a starting point for biodegradable MNPs-induced hepatotoxicity. More research is needed to verify and inhibit the pathways that are crucial to MNPs-induced hepatotoxicity.

Helicobacter pylori infection in infant rhesus macaque monkeys is associated with an altered lung and oral microbiome

It is estimated that more than half of the world population has been infected with Helicobacter pylori. Most newly acquired H. pylori infections occur in children before 10 years of age. We hypothesized that early life H. pylori infection could influence the composition of the microbiome at mucosal sites distant to the stomach. To test this hypothesis, we utilized the infant rhesus macaque monkey as an animal model of natural H. pylori colonization to determine the impact of infection on the lung and oral microbiome during a window of postnatal development. From a cohort of 4–7 month-old monkeys, gastric biopsy cultures identified 44% of animals infected by H. pylori. 16S ribosomal RNA gene sequencing of lung washes and buccal swabs from animals showed distinct profiles for the lung and oral microbiome, independent of H. pylori infection. In order of relative abundance, the lung microbiome was dominated by the phyla Proteobacteria, Firmicutes, Bacteroidota, Fusobacteriota, Campilobacterota and Actinobacteriota while the oral microbiome was dominated by Proteobacteria, Firmicutes, Bacteroidota, and Fusobacteriota. In comparison to the oral cavity, the lung was composed of more genera and species that significantly differed by H. pylori status, with a total of 6 genera and species that were increased in H. pylori negative infant monkey lungs. Lung, but not plasma IL-8 concentration was also associated with gastric H. pylori load and lung microbial composition. We found the infant rhesus macaque monkey lung harbors a microbiome signature that is distinct from that of the oral cavity during postnatal development. Gastric H. pylori colonization and IL-8 protein were linked to the composition of microbial communities in the lung and oral cavity. Collectively, these findings provide insight into how H. pylori infection might contribute to the gut-lung axis during early childhood and modulate future respiratory health.

Considerations for the use of inhaled antibiotics for Pseudomonas aeruginosa in people with cystic fibrosis receiving CFTR modulator therapy

The major cause of mortality in people with cystic fibrosis (pwCF) is progressive lung disease characterised by acute and chronic infections, the accumulation of mucus, airway inflammation, structural damage and...

Analysis of the Diversity and Functional Potential of Bacterial Communities in Tuberculomas.

The dynamics of lung microbiota in tuberculosis remains poorly understood. Sequencing of variable regions of the 16S rRNA gene from surgically excised tuberculosis foci and biopsy specimens of normal lung tissue allowed characterization of the diversity and predictive potential of bacterial communities. Taxonomic diversity indices attested to differences in the structure of microbial communities between "healthy" lungs and tuberculomas. The microbial composition of "healthy" lungs varied in taxonomic diversity and was presented by both gram-positive and gram-negative bacteria with sufficiently similar metabolic potential. The microbiota of the examined tuberculomas consisted of Mycobacterium tuberculosis in 99.9% of cases. A significant part of the metabolic pathways predicted by PICRUSt2 included cholesterol catabolism, sulfate assimilation, and various pathways for the biosynthesis of cell wall components.

The impact of Sangju Qingjie Decoction on the pulmonary microbiota in the prevention and treatment of chronic obstructive pulmonary disease.

Exploring the effect of SJQJD on the pulmonary microbiota of chronic obstructive pulmonary disease (COPD) rats through 16S ribosomal RNA (rRNA) sequencing. A COPD rat model was constructed through smoking and lipopolysaccharide (LPS) stimulation, and the efficacy of SJQJD was evaluated by hematoxylin and eosin (H&E) staining and Enzyme-Linked Immunosorbnent Assay (ELISA). The alveolar lavage fluid of rats was subjected to 16S rRNA sequencing. The diversity of lung microbiota composition and community structure was analyzed and differential microbiota were screened. Additionally, machine learning algorithms were used for screening biomarkers of each group of the microbiota. SJQJD could improve lung structure and inflammatory response in COPD rats. 16s rRNA sequencing analysis showed that SJQJD could significantly improve the abundance and diversity of bacterial communities in COPD rats. Through differential analysis and machine learning methods, potential microbial biomarkers were identified as Mycoplasmataceae, Bacillaceae, and Lachnospiraceae. SJQJD could improve tissue morphology and local inflammatory response in COPD rats, and its effect may be related to improve pulmonary microbiota.

Long-Term Erythromycin Treatment Alters the Airway and Gut Microbiota: Data from Chronic Obstructive Pulmonary Disease Patients and Mice with Emphysema

Introduction: Although long-term macrolide antibiotics could reduce the recurrent exacerbation of chronic obstructive pulmonary disease (COPD), the side effect of bacterial resistance and the impact on the microbiota remain concerning. We investigated the influence of long-term erythromycin treatment on the airway and gut microbiota in mice with emphysema and patients with COPD. Methods: We conducted 16S rRNA gene sequencing to explore the effect of erythromycin treatment on the lung and gut microbiota in mice with emphysema. Liquid chromatography-mass spectrometry was used for lung metabolomics. A randomized controlled trial was performed to investigate the effect of 48-week erythromycin treatment on the airway and gut microbiota in COPD patients. Results: The mouse lung and gut microbiota were disrupted after cigarette smoke exposure. Erythromycin treatment depleted harmful bacteria and altered lung metabolism. Erythromycin treatment did not alter airway or gut microbial diversity in COPD patients. It reduced the abundance of pathogens, such as Burkholderia, in the airway of COPD patients and increased levels of symbiotic bacteria, such as Prevotella and Veillonella. The proportions of Blautia, Ruminococcus, and Lachnospiraceae in the gut were increased in COPD patients after erythromycin treatment. The time to the first exacerbation following treatment was significantly longer in the erythromycin treatment group than in the COPD group. Conclusion: Long-term erythromycin treatment reduces airway and gut microbe abundance in COPD patients but does not affect microbial diversity and restores microbiota balance in COPD patients by reducing the abundance of pathogenic bacteria.

Lower airway microbiota compositions differ between influenza, COVID-19 and bacteria-related acute respiratory distress syndromes

BackgroundAcute respiratory distress syndrome (ARDS) is responsible for 400,000 deaths annually worldwide. Few improvements have been made despite five decades of research, partially because ARDS is a highly heterogeneous syndrome including various types of aetiologies. Lower airway microbiota is involved in chronic inflammatory diseases and recent data suggest that it could also play a role in ARDS. Nevertheless, whether the lower airway microbiota composition varies between the aetiologies of ARDS remain unknown. The aim of this study is to compare lower airway microbiota composition between ARDS aetiologies, i.e. pulmonary ARDS due to influenza, SARS-CoV-2 or bacterial infection.MethodsConsecutive ARDS patients according to Berlin’s classification requiring invasive ventilation with PCR-confirmed influenza or SARS-CoV-2 infections and bacterial infections (> 105 CFU/mL on endotracheal aspirate) were included. Endotracheal aspirate was collected at admission, V3-V4 and ITS2 regions amplified by PCR, deep-sequencing performed on MiSeq sequencer (Illumina®) and data analysed using DADA2 pipeline.ResultsFifty-three patients were included, 24 COVID-19, 18 influenza, and 11 bacterial CAP-related ARDS. The lower airway bacteriobiota and mycobiota compositions (β-diversity) were dissimilar between the three groups (p = 0.05 and p = 0.01, respectively). The bacterial α-diversity was significantly lower in the bacterial CAP-related ARDS group compared to the COVID-19 ARDS group (p = 0.04). In contrast, influenza-related ARDS patients had higher lung mycobiota α-diversity than the COVID-19-related ARDS (p = 0 < 01).ConclusionComposition of lower airway microbiota (both microbiota and mycobiota) differs between influenza, COVID-19 and bacterial CAP-related ARDS. Future studies investigating the role of lung microbiota in ARDS pathophysiology should take aetiology into account.

The Oral-Lung Microbiome Axis in Connective Tissue Disease-Related Interstitial Lung Disease.

Connective tissue disease-related interstitial lung disease (CTD-ILD) is a frequent and serious complication of CTD, leading to high morbidity and mortality. Unfortunately, its pathogenesis remains poorly understood; however, one intriguing contributing factor may be the microbiome of the mouth and lungs. The oral microbiome, which is a major source of the lung microbiome through recurrent microaspiration, is altered in ILD patients. Moreover, in recent years, several lines of evidence suggest that changes in the oral and lung microbiota modulate the pulmonary immune response and thus may play a role in the pathogenesis of ILDs, including CTD-ILD. Here, we review the existing data demonstrating oral and lung microbiota dysbiosis and possible contributions to the development of CTD-ILD in rheumatoid arthritis, Sjögren's syndrome, systemic sclerosis, and systemic lupus erythematosus. We identify several areas of opportunity for future investigations into the role of the oral and lung microbiota in CTD-ILD.

Features of the lung microbiota in tuberculosis infection

Normal lung microbiota is a small number of transient microbes; however, respiratory pathology may be associated with persistent microbial colonization of the lungs. It remains a poorly understood and mysterious part of the pathogenesis of tuberculosis infection.The review considers the general pathogenetic mechanisms of the effect of lung microbiota in respiratory pathology and presents the main methodological difficulties in the study of the lung microbiome. This review is aimed at analyzing the results of the available studies on diverse microbial composition of human lungs in tuberculosis using metagenomic sequencing methods. Despite high variability of the presented data, we can conclude that dysbiosis in tuberculosis is more often characterized by a decrease in bacterial diversity and enrichment of lung microbiota with anaerobic bacteria. Acinetobacter, Campylobacter, Moraxella, Pseudomonas, Staphylococcus, and Streptococcus, as well as some other microorganisms are indicated as important pathogenetic factors of dysbiosis in pulmonary tuberculosis, the role of which is yet to be elucidated.