Multi Omic Microbiome Study: Pregnancy Initiative (MOMS-PI)
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PROVIDER: PRJNA430482 | ENA |
REPOSITORIES: ENA
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Project description:Multi Omic Microbiome Study: Pregnancy Initiative (MOMS-PI)
| PRJNA430481 | ENA
Project description:<p>The Vaginal Microbiome Consortium team at Virginia Commonwealth University has conducted the Multi-Omic Microbiome Study: Pregnancy Initiative (MOMS-PI) in collaboration with the Global Alliance to Prevent Prematurity and Stillbirth (GAPPS) to better understand how microbiome and host profiles change throughout pregnancy and influence the establishment of the nascent microbiome in neonates. The team particularly focused on elucidation of the role of the microbiome and its components in the etiology of preterm birth, which occurs in over 10% of pregnancies and which is the leading cause of death in neonates. Samples from 1594 women and their neonates were collected throughout pregnancy, at delivery and postpartum. The group has generated a comprehensive dataset of multiple omics technologies. This longitudinal, large-scale effort was designed to provide a large-scale resource for the scientific community. The study also permits characterization of temporal dynamics of the microbiome in pregnancy and factors associated with preterm birth.</p>
| phs001523 | dbGaP
Project description:Single-nucleus multi-omic profiling of human placental syncytiotrophoblasts identifies cellular trajectories during pregnancy
| PRJNA1035951 | ENA
Project description:Understanding the gene regulatory mechanisms that establish and maintain cell type identities is a central goal in cellular and developmental biology. Single-cell RNA sequencing and multi-omic profiling have revolutionized this field, enabling high-resolution investigation of gene expression dynamics across differentiation stages. RNA velocity, which estimates gene expression changes using mechanistic models, has emerged as a powerful approach for trajectory inference. Recent advances in RNA velocity methods address key limitations such as steady-state assumptions and lack of support for multi-omic data but still fall short in multi-sample integration and differential testing. To overcome these challenges, we introduce MultiVeloVAE, a probabilistic framework for multi-sample RNA velocity inference that integrates single-cell RNA and multi-omic data. MultiVeloVAE models gene expression on a shared time scale, accounts for lineage bifurcations, and enables statistical testing of velocity parameters. Our approach achieves a good balance between batch correction and biological variance conservation and outperforms existing methods in trajectory reconstruction. Using newly generated 10X Multiome datasets from human embryoid bodies and hematopoietic cells, we demonstrate that MultiVeloVAE provides novel insights into chromatin accessibility and gene expression dynamics during development. These results highlight the potential of MultiVeloVAE as a comprehensive tool for de novo multi-omic trajectory analysis and biological discovery.
2025-10-01 | GSE284047 | GEO
Project description:Multi-omic analysis of vaginal bacteria:host immune and metabolic interactions in early adverse pregnancy outcomes
| PRJEB72306 | ENA
Project description:This study utilizes multi-omic biological data to perform deep immunophenotyping on the major immune cell classes in COVID-19 patients. 10X Genomics Chromium Single Cell Kits were used with Biolegend TotalSeq-C human antibodies to gather single-cell transcriptomic, surface protein, and TCR/BCR sequence information from 254 COVID-19 blood draws (a draw near diagnosis (-BL) and a draw a few days later (-AC)) and 16 healthy donors.
2020-10-29 | E-MTAB-9357 | biostudies-arrayexpress
Project description:We used genome-scale modeling and multi-omics (transcriptomics, proteomics, and metabolomics) analysis to assess metabolic features that are critical for macrophage activation. We constructed a genome-scale metabolic network for the RAW 264.7 cell line to determine metabolic modulators of activation. Metabolites well-known to be associated with immunoactivation (glucose and arginine) and immunosuppression (tryptophan and vitamin D3) were among the most critical effectors. Intracellular metabolic mechanisms were assessed, identifying a suppressive role for de-novo nucleotide synthesis. Finally, underlying metabolic mechanisms of macrophage activation are identified by analyzing multi-omic data obtained from LPS-stimulated RAW cells in the context of our flux-based predictions. Two condition (flagellin and LPS) time course exposure of RAW 264.7 cell line at 1, 2, 4, and 24 hours. Two replicates for each condition and time point. All conditions compared to a pool of untreated cells at a 0 hour time point.
2012-08-02 | E-GEOD-39785 | biostudies-arrayexpress
Project description:BABEL enables cross-modality translation between multi-omic profiles at single-cell resolution
2021-02-16 | GSE166797 | GEO
Project description:<p><strong>Objective </strong></p><p>To characterise the vaginal microbiota, mucosal metabolome and host immune response in early pregnancy and investigate its relationship with adverse pregnancy outcomes, including ectopic pregnancy, within the context of pregnancies of unknown location (PUL).</p><p><br></p><p><strong>Design</strong></p><p>Prospective cohort study Setting Queen Charlotte’s and Chelsea Hospital, Imperial College Healthcare NHS Trust, London, UK. Population Ninety-one pregnancies of which 22 patients had a favourable outcome of a viable intrauterine pregnancy (VIUP). The remainder had an adverse outcome including 15 with a non-viable intrauterine pregnancy (NVIUP, i.e. miscarriage), 26 a failed PUL (FPUL), 20 an ectopic pregnancy (EP) and 8 a persistent PUL (PPUL).</p><p><br></p><p><strong>Methods </strong></p><p>Two matching pairs of vaginal swab samples were collected from women as early as four weeks gestation in pregnancies that resulted in an ectopic pregnancy, miscarriage or viable intrauterine pregnancy pregnancies matched for age, gestation and body mass index. Sequencing of the V1-V2 region of the 16S rRNA gene amplicon was used to characterize and compare vaginal bacterial compositions. The second of the pair of vaginal swabs was used sequentially first for DESI-MS direct-on swab untargeted metabolite profiling followed by extraction of the protein content for quantitative analysis of chemokine and cytokine levels using a 15-plex Luminex immune-profiling assay.</p><p><br></p><p><strong>Results </strong></p><p>Adverse final pregnancy outcomes were associated with reduced Lactobacillus spp. abundance (100% vs. 75.4%, p-value=9.83 x 10-3) and higher Shannon α-diversity (p-value=1.10 x 10-3) when compared to viable pregnancies. This association was independent of vaginal bleeding and observed prior to the diagnosis of the final pregnancy outcome (i.e. before the pregnancy was visible on ultrasound). Ectopic pregnancy had an even stronger association with Lactobacillus spp. depletion when compared to viable pregnancies (30% vs 0%, p-value =5.52 x 10-3). Although a strong immune mediator signature, which included MMP-1, IL-6, CCL-2/MCP-1, TNF-α, amongst others was observed in adverse pregnancy outcomes, vaginal bleeding was identified as a major confounder and adjustment of models for bleeding removed the association with outcome. Vaginal bleeding was also found to impact metabolic profiles, increasing the abundances of multiple lipid species. The prediction of outcome based on metabolic profiles was not possible but metabolic profiles were predictive with high accuracy of vaginal microbial composition at the genera level (L. dominant vs. L. deplete), and metabolic correlates of host immune activation were identified, mainly composed of lipids.</p><p><br></p><p><strong>Conclusions </strong></p><p>Early pregnancy vaginal microbiome communities dominated by L. crispatus or L. gasseri were observed in women with a PUL who go onto have a viable intrauterine pregnancy. Conversely, a vaginal microbiota deplete in Lactobacillus spp or dominated by L. iners is associated with a diagnosis of ectopic pregnancy in a PUL population. These findings suggest that vaginal microbiota composition is a risk factor for ectopic pregnancy. Vaginal bleeding is an inevitable cofounding factor that must be taken into consideration when performing multi-omic analysis of vaginal mucosal samples in similar clinical populations. Immune and metabolic profiles were particularly impacted by bleeding and bleeding could greatly impact the diagnostic usefulness of immune marker profiling. Further studies are required to clarify the role of microbes and infection in implantation and ectopic pregnancy, as well as determine the mechanistic pathways by which sub-optimal vaginal microbial composition increases risk. Through the integration of metataxonomics, metabolomic and immune profiling data obtained from corresponding samples, our findings demonstrate the robust predictive capacity of specific metabolome signatures. These signatures enable the simultaneous prediction of both the composition of the vaginal microbiome and the inflammatory status of the host, even in the presence of bleeding. The data derived from direct on-swab metabolic profiling using DESI-MS holds promise for swiftly stratifying the risk of early pregnancy loss by rapidly assessing the dynamics between the vaginal microbiota and host. Further validation, however, is essential for future studies to confirm this potential.</p><p><br></p><p><strong>Linked cross omic data sets</strong>:</p><p>Meta-taxonomics data associated with this study are available in the European Nucleotide Archive (ENA): accession number <strong>PRJEB72306</strong>.</p>
2025-03-28 | MTBLS10098 | MetaboLights