Biochemistry at single-cell resolution: a new approach to understand functional heterogeneity

单细胞分辨率的生物化学：理解功能异质性的新方法

• 批准号: 10672993
• 负责人: Jay R Hesselberth
• 金额: $ 62.67万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-11 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10672993
• 关键词: Acceleration; Adoption; Allosteric Regulation; Award; Biochemical; Biochemistry; Bioinformatics; Biological Assay; Biology; Biomedical Research; Cell Cycle; Cell Extracts; Cell physiology; Cells; Cellular Assay; Chromatin; Complex; DNA; Data; Development; Dissociation; Enzyme Activation; Enzyme Inhibition; Enzyme Inhibitor Drugs; Enzymes; Event; Gene Expression; Genotype; Glean; Goals; Heterogeneity; High-Throughput DNA Sequencing; Human Biology; In Situ; Individual; Lipids; Massive Parallel Sequencing; Measurement; Measures; Messenger RNA; Methods; Modality; Modernization; Organ; Phase; Polysaccharides; Post-Translational Protein Processing; Proteins; RNA; Regulation; Resolution; Science; Tissues; Whole Organism; cell type; cofactor; enzyme activity; experimental study; functional status; human disease; in vivo; indexing; innovation; insight; mRNA Expression; novel strategies; single cell mRNA sequencing; single cell proteins; tool; tumor

Abstract New methods to study heterogeneity at cellular resolution in complex tissues are transforming our understanding of human biology and disease. These approaches measure differences in gene expression, chromatin accessibility, and protein levels across thousands to millions of cells to understand developmental trajectories of tissues, tumors, and whole organisms. But these methods rely on measurements of static levels of DNA, RNA, and proteins, and fail to capture dynamic biochemical activities that underlie complex cellular functions. Instead of developing more direct readouts of cellular function, the field has focused on inferring functional status from measurements of mRNA abundance and chromatin accessibility in single cells. To accelerate the study of biochemical heterogeneity among single cells, we developed functional assays as a new modality for single-cell experiments. Instead of measuring the abundance of molecules—i.e., levels of DNA, RNA, or protein—from single cells and predicting cell functional states (e.g., cell cycle phase), our key innovation is to directly quantify enzymatic activities in single cells by measuring the conversion of substrates to products by single cell extracts in a high-throughput DNA sequencing experiment. Our approach is compatible with existing platforms that measure gene expression in thousands to millions of individual cells and enables many different enzymatic activities to be measured simultaneously.

摘要