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

基本信息

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
项目类别：
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

项目摘要

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.

抽象的研究复杂组织细胞分辨率异质性的新方法这些方法改变了我们对人类生物学和疾病的理解。测量基因表达、染色质可及性和蛋白质水平的差异跨越数千到数百万个细胞来了解组织的发育轨迹，但这些方法依赖于静态水平的测量。 DNA、RNA 和蛋白质，并且无法捕获动态生化活动是复杂细胞功能的基础，而不是开发更直接的读数。细胞功能，该领域专注于从测量中推断功能状态单细胞中 mRNA 丰度和染色质可及性的研究旨在加速研究。为了研究单细胞之间的生化异质性，我们开发了功能测定法单细胞实验的新模式，而不是测量丰度。来自单个细胞和预测细胞的分子（即 DNA、RNA 或蛋白质的水平）功能状态（例如细胞周期阶段），我们的关键创新是直接量化通过测量底物到产物的转化来测量单细胞中的酶活性通过高通量 DNA 测序实验中的单细胞提取物我们的方法。与现有平台兼容，可测量数以千计的基因表达数以百万计的单个细胞，使许多不同的酶活性能够被同时测量。