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.

项目摘要 /摘要 研究人员对新颖的现象学和转录组数据的整合表现出了极大的兴趣 生物学见解由于表型特征与基因表达模式高度相关。然而， 缺乏有效的方法可以将基因表达谱与细胞表型联系起来（例如， 蛋白质丰度和定位，细胞形态，酶促和代谢活性）在单细胞水平上 高通量方式。为了弥合这一差距，Wellsim建议开发一个可以提取的平台 来自数千个单个单个单个单个单个单个单个单个细胞的表型特征，并通过这些特征链接 凭借其转录组轮廓。该技术不仅可以实现多维单细胞研究，而且还将 还可以通过自动样品制备在A上提高单细胞RNA测序的性能 微流体设备无需使用条形码珠。