Microscale System for Functional T Cell Transcriptomics

项目摘要/摘要

Project Summary / Abstract Single cell analysis technologies have transformed understanding of cellular physiology and disease, allowing deep insights into the diversity of cell composition and genomic programming. Concurrently, microscopy-based assays provide individualized measures of high-level cellular function, such as migration, secretion of chemical factors, and interaction with neighboring cells. The ability to associate these complex functions with specific -omic profiles would unite these two perspectives into a compelling framework for understanding cellular physiology, but to date has not been successfully implemented. To this end, the proposed study will combine microscopy-based analysis of cell function on micropatterned surfaces with an emerging platform for single cell RNA sequencing (scRNA-Seq). These two platforms have individually led to new avenues of investigation, and together will allow association of an individual cell’s function with its transcriptome. This new system will be pursued in the context of T cells, key modulators of adaptive immunity, and is inspired by the variation in cell migration our team has observed in cells isolated from patients undergoing treatment for chronic lymphocytic leukemia (CLL). This short-term, exploratory / developmental project will develop a first generation platform capable of processing numbers of cells that allow contemporary transcriptomic analysis, a capability not currently provided by other systems. With the proposed platform, we will carry out the first studies of how variation in cell migration is linked to differences in gene expression, leading to identification of specific transcriptomic signatures associated with cell behavior. Building on these initial discoveries, the proposal platform is well positioned to carry out analysis on complex cellular systems such as those obtained from individuals being treated for CLL or other disease. By providing new interpretation of scRNA-Seq data in the context of cell function, we envision that this system will lead to new diagnostic and prognostic tools to improve human health.