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>
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.
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.
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.