Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1080187 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Clinical treatment protocols for infertility with in vitro fertilization-embryo transfer (IVF-ET) provide a unique opportunity to assess the human vaginal microbiome in defined hormonal milieu. Herein, we have investigated the association of circulating ovarian-derived estradiol (E2) and progesterone (P4) concentrations to the vaginal microbiome. Thirty IVF-ET patients were enrolled in this study, after informed consent. Blood was drawn at four time points during the IVF-ET procedure. In addition, if a pregnancy resulted, blood was drawn at 4-to-6 weeks of gestation. The serum concentrations of E2 and P4 were measured. Vaginal swabs were obtained in different hormonal milieu. Two independent genome-based technologies (and the second assayed in two different ways) were employed to identify the vaginal microbes. The vaginal microbiome underwent a transition with a decrease in E2 (and/or a decrease in P4). Novel bacteria were found in the vagina of 33% of the women undergoing IVF-ET. Our approach has enabled the discovery of novel, previously unidentified bacterial species in the human vagina in different hormonal milieu. While the relationship of hormone concentration and vaginal microbes was found to be complex, the data support a shift in the microbiome of the human vagina during IVF-ET therapy using standard protocols. The data also set the foundation for further studies examining correlations between IVF-ET outcome and the vaginal microbiome within a larger study population.
2011-10-24 | E-MEXP-2958 | biostudies-arrayexpress
Project description:The goal of this study was to identify amylases that might be present in the vaginal fluid from four individual donors coming either from the microbiome or expressed by the human donors in these fluids. We collected cervicovaginal mucus from 4 donors, characterized the species composition of vaginal communities by genome sequencing. Samples were digested with trypsin, then analyzed by LC-MS/MS. Data was searched with MaxQuant and downstream data analysis was performed using RomicsProcessor.
2020-05-05 | MSV000085378 | MassIVE
Project description:Characterization of the microbiome in vaginal and stool samples self-sampled from endometrial cancer survivors enrolled in the Carolina Endometrial Cancer Study.
2025-12-16 | GSE305725 | GEO
Project description:We explore whether a low-energy diet intervention for Metabolic dysfunction-associated steatohepatitis (MASH) improves liver disease by means of modulating the gut microbiome. 16 individuals were given a low-energy diet (880 kcal, consisting of bars, soups, and shakes) for 12 weeks, followed by a stepped re-introduction to whole for an additional 12 weeks. Stool samples were obtained at 0, 12, and 24 weeks for microbiome analysis. Fecal microbiome were measured using 16S rRNA gene sequencing. Positive control (Zymo DNA standard D6305) and negative control (PBS extraction) were included in the sequencing. We found that low-energy diet improved MASH disease without lasting alterations to the gut microbiome.
2024-12-31 | E-MTAB-14061 | biostudies-arrayexpress
Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
2022-02-21 | MODEL2202170012 | BioModels
Project description:To comprehensively describe both host gene expression and microbiome composition in a single sample, parallel experimental and computational workflows -mRNA sequencing and either 16S or metagenomics- have been traditionally applied. Here, following in vitro validation of the reliability of Poly(A)-enriched mRNA sequencing in reconstructing the microbiota composition on a defined microbial mock community, we process a cohort of 30 vulvar mRNA-seq samples to fully analyze not only the transcriptome of the vulvar cells, but also the composition of microbial communities and their parallel changes. This three-level analysis on the very same specimens further enables a gene-level exploration of the reciprocal molecular crosstalk between host and microbes. The vulvar milieu represents an area of emerging research for its role in health and disease. Being at the anatomical intersection between the vaginal milieu and the perineal area, the vulvar microbiome displays an intermediate signature, with contamination from both ecosystems. Using this unified framework, we reveal marked heterogeneity and high inter-individual variability in the vulvar microbiota of healthy individuals, identifying community state types that mirror those described in the vaginal ecosystem. Importantly, we show that distinct microbial configurations are associated with specific host transcriptional programs: Lactobacillus crispatus dominated communities correlate with epithelial differentiation and barrier integrity, whereas communities enriched in taxa associated with dysbiosis exhibit transcriptional signatures linked to inflammation. Beyond providing new biological insights into an understudied anatomical niche, our study introduces a broadly applicable strategy with substantial impact for the field. With tens of thousands of human RNA-seq datasets already available in public repositories, our approach enables retrospective extraction of microbiome information and host-microbe interaction signals from existing transcriptomic data, without the need for additional sequencing or specialized microbiome protocols. This unlocks a powerful and cost-effective opportunity to revisit archived RNA-seq studies across tissues, diseases, and low-biomass environments, revealing previously inaccessible layers of host-microbiome crosstalk and maximizing the scientific value of data that already exist.
2026-04-30 | GSE314734 | GEO
Project description:isolates from the human vaginal microbiome: genome sequencing and assembly
| PRJNA394757 | ENA