VagiBIOM Lactobacillus suppository improves vaginal health index in perimenopausal women with bacterial vaginosis: a randomized control trial.

Bacterial vaginosis (BV) can cause vaginal dysbiosis that may influence general vaginal health and pregnancy complications. Balancing vaginal microbiome using Lactobacillus spp. may be a new way to prevent and treat mild BV. We conducted a randomized, double-blind, placebo-controlled pilot study aimed at evaluating the effect of the product VagiBIOM, a multi-Lactobacillus vaginal suppository, on peri- and premenopausal women with BV in restoring vaginal pH and overall vaginal health by resetting the vaginal microbiome composition. Sixty-six peri- and premenopausal women with BV symptoms were randomized with a 2:1 ratio to be treated with VagiBIOM or placebo suppositories. Vaginal pH, VAS itching score, total Nugent score, and vaginal health index (VHI) were measured. Vaginal microbiome changes before and after the treatment were analyzed by 16S rRNA sequencing and bioinformatics analysis. After 4 weeks of intervention with VagiBIOM or a placebo, the mean score for vaginal pH, VAS itching, and total Nugent score was significantly decreased from the baseline. Compared to the baseline scores, the VHI scores improved significantly following 28-day intervention (p < 0.001). Our results revealed two Lactobacillus species, L. hamsteri, and L. helveticus, as indicator species occurring differentially in the VagiBIOM-treated group. Furthermore, the regression and species network analyses revealed significant bacterial associations after VagiBIOM treatment. Lactobacillus hamsteri was positively associated with the Nugent score and negatively associated with vaginal pH. L. iners and L. salivarius were positively and inversely associated with VHI. As is typical, Bacteroides fragilis was positively associated with vaginal pH and negatively associated with the Nugent score. Interestingly, the Lactobacillus spp. diversity improved after VagiBIOM treatment. The VagiBIOM suppository treatment for peri- and premenopausal women with BV significantly relieved vaginal itching by decreasing vaginal pH and Nugent scores and improving the overall VHI after 4 weeks' intervention. This effect was primarily the result of VagiBIOM improving vaginal Lactobacillus diversity.Trial Registration ClinicalTrials.gov registration: NCT05060029, first registration 09/28/2021: Title: A Pilot Study to Evaluate the Efficacy and Safety of Lactobacillus Species Suppositories on Vaginal Health and pH.

Predictive association of gut microbiome and NLR in anemic low middle-income population of Odisha- a cross-sectional study.

Background: Iron is abundant on earth but not readily available for colonizing bacteria due to its low solubility in the human body. Hosts and microbiota compete fiercely for iron. <15% Supplemented Iron is absorbed in the small bowel, and the remaining iron is a source of dysbiosis. The gut microbiome signatures to the level of predicting anemia among low-middle-income populations are unknown. The present study was conducted to identify gut microbiome signatures that have predictive potential in association with Neutrophil to lymphocytes ratio (NLR) and Mean corpuscular volume (MCV) in anemia. Methods: One hundred and four participants between 10 and 70 years were recruited from Odisha's Low Middle-Income (LMI) rural population. Hematological parameters such as Hemoglobin (HGB), NLR, and MCV were measured, and NLR was categorized using percentiles. The microbiome signatures were analyzed from 61 anemic and 43 non-anemic participants using 16 s rRNA sequencing, followed by the Bioinformatics analysis performed to identify the diversity, correlations, and indicator species. The Multi-Layered Perceptron Neural Network (MLPNN) model were applied to predict anemia. Results: Significant microbiome diversity among anemic participants was observed between the lower, middle, and upper Quartile NLR groups. For anemic participants with NLR in the lower quartile, alpha indices indicated bacterial overgrowth, and consistently, we identified R. faecis and B. uniformis were predominating. Using ROC analysis, R. faecis had better distinction (AUC = 0.803) to predict anemia with lower NLR. In contrast, E. biforme and H. parainfluenzae were indicators of the NLR in the middle and upper quartile, respectively. While in Non-anemic participants with low MCV, the bacterial alteration was inversely related to gender. Furthermore, our Multi-Layered Perceptron Neural Network (MLPNN) models also provided 89% accuracy in predicting Anemic or Non-Anemic from the top 20 OTUs, HGB level, NLR, MCV, and indicator species. Conclusion: These findings strongly associate anemic hematological parameters and microbiome. Such predictive association between the gut microbiome and NLR could be further evaluated and utilized to design precision nutrition models and to predict Iron supplementation and dietary intervention responses in both community and clinical settings.

Co-expression network analysis of protein phosphatase 2A (PP2A) genes with stress-responsive genes in Arabidopsis thaliana reveals 13 key regulators.

Abiotic and biotic stresses adversely affect plant growth and development and eventually result in less yield and threaten food security worldwide. In plants, several studies have been carried out to understand molecular responses to abiotic and biotic stresses. However, the complete circuitry of stress-responsive genes that plants utilise in response to those environmental stresses are still unknown. The protein phosphatase 2A (PP2A) gene has been known to have a crucial role in abiotic and biotic stresses; but how it regulates the stress response in plants is still not known completely. In this study, we constructed gene co-expression networks of PP2A genes with stress-responsive gene datasets from cold, drought, heat, osmotic, genotoxic, salt, and wounding stresses to unveil their relationships with the PP2A under different conditions of stress. The graph analysis identified 13 hub genes and several influential genes based on closeness centrality score (CCS). Our findings also revealed the count of unique genes present in different settings of stresses and subunits. We also formed clusters of influential genes based on the stress, CCS, and co-expression value. Analysis of cis-regulatory elements (CREs), recurring in promoters of these genes was also performed. Our study has led to the identification of 16 conserved CREs.