Multiparametric Host Cell Analysis (MHC)
- Institution
- University of Chicago, IL
- Principal investigator
- Luis Bruno Barreiro
- Funding
- $254K
- Duration
- 1996–2026
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Abstract
PROJECT SUMMARY/ABSTRACT The study of complex traits in humans and model organisms has made considerable progress in recent years. Multi-dimensional high-resolution genomics data and immunological data allows to study complex biological networks, and the dynamics of cellular state and function at a resolution not possible before. The usage of these technologies require, however, highly specialized expertise in genomics, immunology, and computational biology. The primary goal of the Multiparametric Host Cell Analysis (MHC) Core is to provide members of the University of Chicago (UChicago) Digestive Diseases Research Core Center (DDRCC) for Interdisciplinary Study of Inflammatory Intestinal Disorders (C-IID) with such level of expertise, further promoting the usage of state-of-the-art genomic technologies in gastrointestinal research. Specifically, the MHC core will provide the community: (i) consulting service for human tissue isolation, analysis and cell sorting protocols adapted to the different forms of assays, (ii) consulting services and development of customized antibody panels for high resolution cellular tissue profiling of human samples using spectral flow cytometry, (iii) advanced flow cytometry sorting of 6 different populations of cells from a tissue sample based on the detection of 28 fluorescence marker using an advanced BD Biosciences sorter (FACSymphony S6 High Parameter Cell Sorter), (iv) advise with the study design of genomic experiments; (v) a series of pre-optimized genomic assays (e.g., single-cell RNA-seq, epigenetic profiles); (vi) standardized and validated analytical pipelines for the analyses of different genomic datasets, and (vii) bioinformatics support for genomic and flow cytometry data analysis. The standardization of experimental protocols and analytical pipelines offered by the core will help minimize the errors during data collection, management, maintenance, and, importantly, facilitate downstream data integration and sharing among C-IID members.
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