Project description:We profiled four healthy individuals with age between 25 to 38 years old over 10-week period longitudinally using high throughput analysis. We measured blood count, flow-based cell populations, plasma proteome, transcriptome at single cell level, and genomic region accessibility using single cell ATAC to infer immune variations in healthy individuals.
Project description:The gut microbiome has been implicated in multiple human chronic gastrointestinal (GI) disorders. Determining its mechanistic role in disease pathogenesis has been difficult due to the apparent disconnect between animal and human studies and a lack of an integrated multi-omics view in the context of disease-specific physiological changes. We integrated longitudinal multi-omics data from the gut microbiome, metabolome, host epigenome and transcriptome in the context of irritable bowel syndrome (IBS) host physiology. We identified IBS subtype-specific and symptom-related variation in microbial composition and function. A subset of identified changes in microbial metabolites correspond to host physiological mechanisms that are relevant to IBS. By integrating multiple data layers, we identified purine metabolism as a novel host-microbial metabolic pathway in IBS with translational potential. Our study highlights the importance of longitudinal sampling and integrating complementary multi-omics data to identify functional mechanisms that can serve as therapeutic targets in a comprehensive treatment strategy for chronic GI diseases.
Project description:A longitudinal multi-omics analysis was carried out over a 26-hour small-scale fermentation of B. pertussis. Fermentations were performed in batch mode and under culture conditions intended to mimic industrial processes.
Project description:Multi-omics integration is highly effective for the holistic characterization of biological systems. However, current bioinformatics tools face limitations when incorporating metabolomics data, particularly for handling untargeted annotation, and when providing alternatives to predefined knowledge bases. Advanced algorithms required for multi-omics integration typically demand programming skills and statistical background, restricting their use to specialized users. Here, we introduce TurbOmics, a user-friendly web-based platform that enables researchers with diverse backgrounds to analyze metabolomics, proteomics, and transcriptomics data using an integrative workflow that includes advanced algorithms for multi-omics integration, while addressing key challenges associated with metabolomics data. The platform is available at https://proteomics.cnic.es/TurboPutative/TurbOmicsApp.html.