Active Smoking Induces Aberrations in Digestive Tract Microbiota of Rats

Current Approaches to Prevent or Reverse Microbiome Dysbiosis in Chronic Inflammatory Rheumatic Diseases

Advances in knowledge of the microbiome and its relationship with the immune system have led to a better understanding of the pathogenesis of chronic inflammatory rheumatic diseases (CIRD). Indeed, the microbiome dysbiosis now occupies a particular place with implications for the determinism and clinical expression of CIRD, as well as the therapeutic response of affected patients. Several approaches exist to limit the impact of the microbiome during CIRD. This review aimed to present current strategies to prevent or reverse microbiome dysbiosis based on existing knowledge, in order to provide practical information to healthcare professionals treating patients suffering from CIRD.

Association of nicotine dependence and gut microbiota: a bidirectional two-sample Mendelian randomization study

Background

Nicotine dependence is a key factor influencing the diversity of gut microbiota, and targeting gut microbiota may become a new approach for the prevention and treatment of nicotine dependence. However, the causal relationship between the two is still unclear. This study aims to investigate the causal relationship between nicotine dependence and gut microbiota.

Methods

A two-sample bidirectional Mendelian randomization (MR) study was conducted using the largest existing gut microbiota and nicotine dependence genome-wide association studies (GWAS). Causal relationships between genetically predicted nicotine dependence and gut microbiota abundance were examined using inverse variance weighted, MR-Egger, weighted median, simple mode, weighted mode, and MR-PRESSO approaches. Cochrane's Q test, MR-Egger intercept test, and leave-one-out analysis were performed as sensitivity analyses to assess the robustness of the results. Multivariable Mendelian randomization analysis was also conducted to eliminate the interference of smoking-related phenotypes. Reverse Mendelian randomization analysis was then performed to determine the causal relationship between genetically predicted gut microbiota abundance and nicotine dependence.

Results

Genetically predicted nicotine dependence had a causal effect on Christensenellaceae (β: -0.52, 95% CI: -0.934-0.106, P = 0.014). The Eubacterium xylanophilum group (OR: 1.106, 95% CI: 1.004-1.218), Lachnoclostridium (OR: 1.118, 95% CI: 1.001-1.249) and Holdemania (OR: 1.08, 95% CI: 1.001-1.167) were risk factors for nicotine dependence. Peptostreptococcaceae (OR: 0.905, 95% CI: 0.837-0.977), Desulfovibrio (OR: 0.014, 95% CI: 0.819-0.977), Dorea (OR: 0.841, 95% CI. 0.731-0.968), Faecalibacterium (OR: 0.831, 95% CI: 0.735-0.939) and Sutterella (OR: 0.838, 95% CI: 0.739-0.951) were protective factor for nicotine dependence. The sensitivity analysis showed consistent results.

Conclusion

The Mendelian randomization study confirmed the causal link between genetically predicted risk of nicotine dependence and genetically predicted abundance of gut microbiota. Gut microbiota may serve as a biomarker and offer insights for addressing nicotine dependence.

Imbalance of gut microbiota is involved in the development of chronic obstructive pulmonary disease: A review

Chronic obstructive pulmonary disease (COPD) is a common chronic disease characterized by chronic airway inflammation and remodeling, which seriously endangers human health. Recent developments in genomics and metabolomics have revealed the roles of the gut microbiota and its metabolites in COPD. Dysbiosis of the gut microbiota directly increases gut permeability, thereby promoting the translocation of pathological bacteria. The gut microbiota and associated metabolites may influence the development and progression of COPD by modulating immunity and inflammation. Furthermore, the systemic hypoxia and oxidative stress that occur in COPD may also be involved in intestinal dysfunction. The cross-talk between the gut and lungs is known as the gut-lung axis; however, an overview of its mechanism is lacking. This review highlights the critical and complex interplay of gut microbiota and immune responses in the gut-lung axis, further explores possible links between the gut and lungs, and summarizes new interventions through diet, probiotics, vitamins, and fecal microbiota transplantation, which are critical to COPD.

The Impact of Smoking on Microbiota: A Narrative Review

Cigarette smoke is a classic risk factor for many diseases. The microbiota has been recently indicated as a new, major player in human health. Its deregulation-dysbiosis-is considered a new risk factor for several illnesses. Some studies highlight a cross-interaction between these two risk factors-smoke and dysbiosis-that may explain the pathogenesis of some diseases. We searched the keywords "smoking OR smoke AND microbiota" in the title of articles on PubMed^®, UptoDate^®, and Cochrane^®. We included articles published in English over the last 25 years. We collected approximately 70 articles, grouped into four topics: oral cavity, airways, gut, and other organs. Smoke may impair microbiota homeostasis through the same harmful mechanisms exerted on the host cells. Surprisingly, dysbiosis and its consequences affect not only those organs that are in direct contact with the smoke, such as the oral cavity or the airways, but also involve distant organs, such as the gut, heart, vessels, and genitourinary tract. These observations yield a deeper insight into the mechanisms implicated in the pathogenesis of smoke-related diseases, suggesting a role of dysbiosis. We speculate that modulation of the microbiota may help prevent and treat some of these illnesses.

Batch effects removal for microbiome data via conditional quantile regression

Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Strategies designed for genomic data to mitigate batch effects usually fail to address the zero-inflated and over-dispersed microbiome data. Most strategies tailored for microbiome data are restricted to association testing or specialized study designs, failing to allow other analytic goals or general designs. Here, we develop the Conditional Quantile Regression (ConQuR) approach to remove microbiome batch effects using a two-part quantile regression model. ConQuR is a comprehensive method that accommodates the complex distributions of microbial read counts by non-parametric modeling, and it generates batch-removed zero-inflated read counts that can be used in and benefit usual subsequent analyses. We apply ConQuR to simulated and real microbiome datasets and demonstrate its advantages in removing batch effects while preserving the signals of interest.

Cangma Huadu granules attenuate H1N1 virus-induced severe lung injury correlated with repressed apoptosis and altered gut microbiome

Severe influenza A virus infection leads to overwhelming inflammatory responses and cellular apoptosis, which causes lung injury and contributes to high mortality and morbidity. The gut microbiome altered in response to the infection might influence the disease progression and the treatment outcome. Cangma Huadu (CMHD) granules, an in-hospital preparation of traditional Chinese medicine, have been shown to be favorable in the clinical treatment of influenza. However, the effects and mechanisms of CMHD granules on severe influenza pneumonia and its mechanisms are not well-known. In this study, a lethal influenza A (H1N1) A/Puerto Rico/8/34 virus (PR8)-infected mice model was established, and the 16S ribosomal RNA (16S rRNA) V3–V4 region sequencing of the intestinal microbiome was conducted. We revealed that the oral administration of CMHD granules protects mice against higher mortality, enhanced weight loss, overwhelmed interferon-γ concentration, lung viral titers, and severe lung pathological injury in PR8-infected mice. CMHD granules’ administration downregulated the levels of interleukin (IL)-1β, tumor necrosis factor-α, and malondialdehyde, while it upregulated the levels of IL-10, superoxide dismutase, and glutathione peroxidase. Subsequently, it decreased the protein ratio of B-cell lymphoma-2/Bcl-2-associated X and the expression of cleaved caspase-3. The diversity and compositions of the gut microbes were altered profoundly after the administration of CMHD granules in PR8-infected mice. A higher abundance of Bifidobacterium, Parasutterella, Bacteroides, and Faecalibaculum was observed in the CMHD group, and a higher abundance of Lactobacillus and Turicibacter was observed in the positive drug Ribavirin group. The linear discriminant analysis effect size also revealed a higher proportion of Bacteroides and Bifidobacterium_pseudolongum characterized in the CMHD group. These results demonstrated that CMHD granules are a promising strategy for managing severe influenza and attenuating severe lung damage via reducing viral titer, inflammatory responses, and oxidative stress. The mechanisms are involved in repressed Bcl-2-regulated apoptosis and altered composition and diversity of the gut microbiome.