Saliva and Lung Microbiome Associations with Electronic Cigarette Use and Smoking

The Metabolic Potential of the Human Lung Microbiome

The human lung microbiome remains largely underexplored, despite its potential implications in the pharmacokinetics of inhaled drugs and its involvement in lung diseases. Interactions within these bacterial communities and with the host are complex processes which often involve microbial small molecules. In this study, we employed a computational approach to describe the metabolic potential of the human lung microbiome. By utilizing antiSMASH and BiG-SCAPE software, we identified 1831 biosynthetic gene clusters for the production of specialized metabolites in a carefully compiled genome database of lung-associated bacteria and fungi. It was shown that RiPPs represent the largest class of natural products within the bacteriome, while NRPs constitute the largest class of natural products in the lung mycobiome. All predicted BGCs were further categorized into 767 gene cluster families, and a subsequent network analysis highlighted that these families are widely distributed and contain many uncharacterized members. Moreover, in-depth annotation allowed the assignment of certain gene clusters to putative lung-specific functions within the microbiome, such as osmoadaptation or surfactant synthesis. This study establishes the lung microbiome as a prolific source for secondary metabolites and lays the groundwork for detailed investigation of this unique environment.

The paradox of the safer cigarette: understanding the pulmonary effects of electronic cigarettes

Electronic cigarette (e-cigarette) use continues to rise globally. E-cigarettes have been presented as safer alternatives to combustion cigarettes that can mitigate the harm associated with tobacco products; however, the degree to which e-cigarette use itself can lead to morbidity and mortality is not fully defined. Herein we describe how e-cigarettes function; discuss the current knowledge of the effects of e-cigarette aerosol on lung cell cytotoxicity, inflammation, antipathogen immune response, mucociliary clearance, oxidative stress, DNA damage, carcinogenesis, matrix remodelling and airway hyperresponsiveness; and summarise the impact on lung diseases, including COPD, respiratory infection, lung cancer and asthma. We highlight how the inclusion of nicotine or flavouring compounds in e-liquids can impact lung toxicity. Finally, we consider the paradox of the safer cigarette: the toxicities of e-cigarettes that can mitigate their potential to serve as a harm reduction tool in the fight against traditional cigarettes, and we summarise the research needed in this underinvestigated area.

Smoking Impacts Alzheimer's Disease Progression Through Oral Microbiota Modulation

Alzheimer's disease (AD) is an important public health challenge with a limited understanding of its pathogenesis. Smoking is a significant modifiable risk factor for AD progression, and its specific mechanism is often interpreted from a toxicological perspective. However, microbial infections also contribute to AD, with oral microbiota playing a crucial role in its progression. Notably, smoking alters the ecological structure and pathogenicity of the oral microbiota. Currently, there is no systematic review or summary of the relationship between these three factors; thus, understanding this association can help in the development of new treatments. This review summarizes the connections between smoking, AD, and oral microbiota from existing research. It also explores how smoking affects the occurrence and development of AD through oral microbiota, and examines treatments for oral microbiota that delay the progression of AD. Furthermore, this review emphasizes the potential of the oral microbiota to act as a biomarker for AD. Finally, it considers the feasibility of probiotics and oral antibacterial therapy to expand treatment methods for AD.

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.

Tobacco use, self-reported professional dental cleaning habits, and lung adenocarcinoma diagnosis are associated with bronchial and lung microbiome alpha diversity

RATIONALE

The lung microbiome is an inflammatory stimulus whose role in the development of lung malignancies is incompletely understood. We hypothesized that the lung microbiome associates with multiple clinical factors, including the presence of a lung malignancy.

OBJECTIVES

To assess associations between the upper and lower airway microbiome and multiple clinical factors including lung malignancy.

METHODS

We conducted a prospective cohort study of upper and lower airway microbiome samples from 44 subjects undergoing lung lobectomy for suspected or confirmed lung cancer. Subjects provided oral (2), induced sputum, nasopharyngeal, bronchial, and lung tissue (3) samples. Pathologic diagnosis, age, tobacco use, dental care history, lung function, and inhaled corticosteroid use were associated with upper and lower airway microbiome findings.

MEASUREMENTS AND MAIN RESULTS

Older age was associated with greater Simpson diversity in the oral and nasopharyngeal sites (p = 0.022 and p = 0.019, respectively). Current tobacco use was associated with greater lung and bronchus Simpson diversity (p < 0.0001). Self-reported last profession dental cleaning more than 6 months prior (vs. 6 or fewer months prior) was associated with lower lung and bronchus Simpson diversity (p < 0.0001). Diagnosis of a lung adenocarcinoma (vs. other pathologic findings) was associated with lower bronchus and lung Simpson diversity (p = 0.024). Last professional dental cleaning, dichotomized as ≤ 6 months vs. >6 months prior, was associated with clustering among lung samples (p = 0.027, R2 = 0.016). Current tobacco use was associated with greater abundance of pulmonary pathogens Mycoplasmoides and Haemophilus in lower airway samples. Self-reported professional dental cleaning ≤ 6 months prior (vs. >6 months prior) was associated with greater bronchial Actinomyces and lung Streptococcus abundance. Lung adenocarcinoma (vs. no lung adenocarcinoma) was associated with lower Lawsonella abundance in lung samples. Inhaled corticosteroid use was associated with greater abundance of Haemophilus among oral samples and greater Staphylococcus among lung samples.

CONCLUSIONS

Current tobacco use, recent dental cleaning, and a diagnosis of adenocarcinoma are associated with lung and bronchial microbiome α-diversity, composition (β-diversity), and the abundance of several respiratory pathogens. These findings suggest that modifiable habits (tobacco use and dental care) may influence the lower airway microbiome. Larger controlled studies to investigate these potential associations are warranted.

Sputum microbiome α-diversity is a key feature of the COPD frequent exacerbator phenotype

Background

The lung microbiome is an inflammatory stimulus whose role in COPD pathogenesis is incompletely understood. We hypothesised that the frequent exacerbator phenotype is associated with decreased α-diversity and increased lung inflammation. Our objective was to assess correlations between the frequent exacerbator phenotype, the microbiome and inflammation longitudinally during exacerbation-free periods.

Methods

We conducted a case-control longitudinal observational study of the frequent exacerbator phenotype and characteristics of the airway microbiome. 81 subjects (41 frequent and 40 infrequent exacerbators) provided nasal, oral and sputum microbiome samples at two visits over 2-4 months. Exacerbation phenotype, relevant clinical factors and sputum cytokine values were associated with microbiome findings.

Results

The frequent exacerbator phenotype was associated with lower sputum microbiome α-diversity (p=0.0031). This decrease in α-diversity among frequent exacerbators was enhanced when the sputum bacterial culture was positive (p<0.001). Older age was associated with decreased sputum microbiome α-diversity (p=0.0030). Between-visit β-diversity was increased among frequent exacerbators and those who experienced a COPD exacerbation between visits (p=0.025 and p=0.014, respectively). Sputum cytokine values did not differ based on exacerbation phenotype or other clinical characteristics. Interleukin (IL)-17A was negatively associated with α-diversity, while IL-6 and IL-8 were positively associated with α-diversity (p=0.012, p=0.012 and p=0.0496, respectively). IL-22, IL-17A and IL-5 levels were positively associated with Moraxella abundance (p=0.027, p=0.0014 and p=0.0020, respectively).

Conclusions

Even during exacerbation-free intervals, the COPD frequent exacerbator phenotype is associated with decreased sputum microbiome α-diversity and increased β-diversity. Decreased sputum microbiome α-diversity and Moraxella abundance are associated with lung inflammation.

[Analysis of Salivary Microbiota Characteristics in Patients With Pulmonary Nodules: A Prospective Nonrandomized Concurrent Controlled Trial]

Objective

To uncover and identify the differences in salivary microbiota profiles and their potential roles between patients with pulmonary nodules (PN) and healthy controls, and to propose new candidate biomarkers for the early warning of PN.

Methods

16S rRNA amplicon sequencing was performed with the saliva samples of 173 PN patients, or the PN group, and 40 health controls, or the HC group, to compare the characteristics, including diversity, community composition, differential species, and functional changes of salivary microbiota in the two groups. Random forest algorithm was used to identify salivary microbial markers of PN and their predictive value for PN was assessed by area under the curve (AUC). Finally, the biological functions and potential mechanisms of differentially-expressed genes in saliva samples were preliminarily investigated on the basis of predictive functional profiling of Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2).

Results

The α diversity and β diversity of salivary microbiota in the PN group were higher than those in the HC group (P<0.05). Furthermore, there were significant differences in the community composition and the abundance of oral microorganisms between the PN and the HC groups (P<0.05). Random forest algorithm was applied to identify differential microbial species. Porphyromonas, Haemophilus, and Fusobacterium constituted the optimal marker sets (AUC=0.79, 95% confidence interval: 0.71-0.86), which can be used to effectively identify patients with PN. Bioinformatics analysis of the differentially-expressed genes revealed that patients with PN showed significant enrichment in protein/molecular functions involved in immune deficiency and redox homeostasis.

Conclusion

Changes in salivary microbiota are closely associated with PN and may induce the development of PN or malignant transformation of PN, which indicates the potential of salivary microbiota to be used as a new non-invasive humoral marker for the early diagnosis of PN.

A Pilot Cross-Sectional Study of Immunological and Microbiome Profiling Reveals Distinct Inflammatory Profiles for Smokers, Electronic Cigarette Users, and Never-Smokers

Smokers (SM) have increased lung immune cell counts and inflammatory gene expression compared to electronic cigarette (EC) users and never-smokers (NS). The objective of this study is to further assess associations for SM and EC lung microbiomes with immune cell subtypes and inflammatory gene expression in samples obtained by bronchoscopy and bronchoalveolar lavage (n = 28). RNASeq with the CIBERSORT computational algorithm were used to determine immune cell subtypes, along with inflammatory gene expression and microbiome metatranscriptomics. Macrophage subtypes revealed a two-fold increase in M0 (undifferentiated) macrophages for SM and EC users relative to NS, with a concordant decrease in M2 (anti-inflammatory) macrophages. There were 68, 19, and 1 significantly differentially expressed inflammatory genes (DEG) between SM/NS, SM/EC users, and EC users/NS, respectively. CSF-1 and GATA3 expression correlated positively and inversely with M0 and M2 macrophages, respectively. Correlation profiling for DEG showed distinct lung profiles for each participant group. There were three bacteria genera-DEG correlations and three bacteria genera-macrophage subtype correlations. In this pilot study, SM and EC use were associated with an increase in undifferentiated M0 macrophages, but SM differed from EC users and NS for inflammatory gene expression. The data support the hypothesis that SM and EC have toxic lung effects influencing inflammatory responses, but this may not be via changes in the microbiome.

Microbial Biomarkers for Lung Cancer: Current Understandings and Limitations

As our "hidden organ", microbes widely co-exist at various sites on the human body. These microbes are collectively referred to as the microbiome. A considerable number of studies have already proven that the microbiome has significant impacts on human health and disease progression, including cancers. The recent discovery of cancer-specific microbiomes renders these cancer-associated microbes as potential biomarkers and therapeutic targets. While at low biomass levels, the lung microbiome still dramatically influences the initiation, progression and treatment of lung cancers. However, research on lung cancer-associated microbiomes is emerging, and most profiling studies are performed within three years. Unfortunately, there are substantial inconsistencies across these studies. Variations in microbial diversity were observed, and different microbial biomarkers for lung cancer have been proposed. In this review, we summarized the current findings of lung cancer microbiome studies and attempt to explain the potential reasons for the dissimilarities. Other than lung microbiomes, oral and airway microbiomes are highly related to lung microbiomes and are therefore included as well. In addition, several lung cancer-associated bacterial genera have been detected by different independent studies. These bacterial genera may not be perfect biomarkers, but they still serve as promising risk factors for lung cancers and show great prognostic value.

Human matters in asthma: Considering the microbiome in pulmonary health

Microbial communities form an important symbiotic ecosystem within humans and have direct effects on health and well-being. Numerous exogenous factors including airborne triggers, diet, and drugs impact these established, but fragile communities across the human lifespan. Crosstalk between the mucosal microbiota and the immune system as well as the gut-lung axis have direct correlations to immune bias that may promote chronic diseases like asthma. Asthma initiation and pathogenesis are multifaceted and complex with input from genetic, epigenetic, and environmental components. In this review, we summarize and discuss the role of the airway microbiome in asthma, and how the environment, diet and therapeutics impact this low biomass community of microorganisms. We also focus this review on the pediatric and Black populations as high-risk groups requiring special attention, emphasizing that the whole patient must be considered during treatment. Although new culture-independent techniques have been developed and are more accessible to researchers, the exact contribution the airway microbiome makes in asthma pathogenesis is not well understood. Understanding how the airway microbiome, as a living entity in the respiratory tract, participates in lung immunity during the development and progression of asthma may lead to critical new treatments for asthma, including population-targeted interventions, or even more effective administration of currently available therapeutics.