STEP: profiling cellular-specific targets and pathways of bioactive small molecules in tissues via integrating single-cell transcriptomics and chemoproteomics.
Jiayun ChenZheng ChuQian ZhangChen WangPiao LuoYing ZhangFei XiaLiwei GuYin Kwan WongQiaoli ShiChengchao XuHuan TangJi-Gang WangPublished in: Chemical science (2024)
Identifying the cellular targets of bioactive small molecules within tissues has been a major concern in drug discovery and chemical biology research. Compared to cell line models, tissues consist of multiple cell types and complicated microenvironments. Therefore, elucidating the distribution and heterogeneity of targets across various cells in tissues would enhance the mechanistic understanding of drug or toxin action in real-life scenarios. Here, we present a novel multi-omics integration pipeline called Single-cell TargEt Profiling (STEP) that enables the global profiling of protein targets in mammalian tissues with single-cell resolution. This pipeline integrates single-cell transcriptome datasets with tissue-level protein target profiling using chemoproteomics. Taking well-established classic drugs such as aspirin, aristolochic acid, and cisplatin as examples, we confirmed the specificity and precision of cellular drug-target profiles and their associated molecular pathways in tissues using the STEP analysis. Our findings provide more informative insights into the action modes of bioactive molecules compared to in vitro models. Collectively, STEP represents a novel strategy for profiling cellular-specific targets and functional processes with unprecedented resolution.
Keyphrases
- single cell
- rna seq
- gene expression
- high throughput
- drug discovery
- climate change
- escherichia coli
- type diabetes
- stem cells
- dna methylation
- single molecule
- cell cycle arrest
- induced apoptosis
- binding protein
- protein protein
- coronary artery disease
- cell proliferation
- signaling pathway
- acute coronary syndrome
- oxidative stress
- antiplatelet therapy
- percutaneous coronary intervention
- genome wide analysis