Link phenotypic characteristics with gene expression profile of single cells at high throughput for drug discovery and cell therapy development

以高通量将表型特征与单细胞基因表达谱联系起来，用于药物发现和细胞疗法开发

• 批准号: 10482180
• 负责人: Yuchao Chen
• 金额: $ 24.68万
• 依托单位: WELLSIM BIOMEDICAL TECHNOLOGIES, INC.
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2024-02-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10482180
• 关键词: Address; Antibodies; Bar Codes; Biological; Biological Assay; Cell Line; Cell Therapy; Cells; Cellular Morphology; Characteristics; Collection; Complementary DNA; Computer software; Data; Data Analyses; Development; Devices; Dimensions; Disease; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genetic Transcription; Goals; Heterogeneity; Image; Individual; Injections; Investigation; Label; Link; Manuals; Metabolic; Microfluidic Microchips; Morphology; Names; Oligonucleotides; Outcome; Performance; Pharmaceutical Preparations; Phase; Phenotype; Population; Preparation; Proteins; Proteomics; RNA; Recovery; Research Personnel; Running; Sampling; Signal Transduction; Small Business Innovation Research Grant; Stains; Techniques; Technology; Time; Variant; base; biomarker signature; cellular imaging; data acquisition; design; drug development; drug discovery; flexibility; fluorescence imaging; improved; innovation; insight; interest; massive parallel processing; microscopic imaging; multimodality; multiple omics; new technology; novel; operation; parallel processing; phenomics; screening; single cell analysis; single-cell RNA sequencing; synthetic biology; therapy development; tool; transcriptome sequencing; transcriptomics

PROJECT SUMMARY / ABSTRACT Researchers have shown substantial interest in the integration of phenomics and transcriptomics data for novel biological insights since phenotypic characteristics are highly correlated with gene expression patterns. However, there is a lack of an efficient approach that could link gene expression profiles to cellular phenotypes (e.g., protein abundance and localization, cellular morphology, enzymatic and metabolic activity) at single-cell level in a high-throughput manner. To bridge this gap, WellSIM proposes to develop a platform which can extract phenotypic characteristics from thousands of individual cells via high-content imaging and link these features with their transcriptomic profiles. This technology will not only achieve multi-dimensional single cell studies, but also improve the performance of single-cell RNA sequencing through automatic sample preparation on a microfluidic device without using barcoded beads.

项目总结/摘要 研究人员已经对整合表型组学和转录组学数据以用于新的基因表达表现出了浓厚的兴趣。 生物学见解，因为表型特征与基因表达模式高度相关。然而，在这方面， 缺乏将基因表达谱与细胞表型联系起来的有效方法（例如， 蛋白质丰度和定位，细胞形态，酶和代谢活性）在单细胞水平， 高通量的方式。为了弥补这一差距，WellSIM建议开发一个平台， 通过高容量成像从数千个个体细胞中提取表型特征，并将这些特征联系起来 和他们的转录组图谱这项技术不仅将实现多维度的单细胞研究， 还通过自动样品制备提高单细胞RNA测序的性能， 微流体装置，而不使用条形码珠粒。