Li Jun, Chi Jun, Yang Yang, Song Zhongya, Yang Yong, Zhou Xin, Liu Yang, Zhao Yang
State Key Laboratory of Natural and Biomimetic Drugs, MOE Key Laboratory of Cell Proliferation and Differentiation, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, 100871, China.
Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
Cell Regen. 2023 Jun 2;12(1):22. doi: 10.1186/s13619-023-00164-9.
High-throughput phenotypic screening is a cornerstone of drug development and the main technical approach for stem cell research. However, simultaneous detection of activated core factors responsible for cell fate determination and accurate assessment of directional cell transition are difficult using conventional screening methods that focus on changes in only a few biomarkers. The PHDs-seq (Probe Hybridization based Drug screening by sequencing) platform was developed to evaluate compound function based on their transcriptional effects in a wide range of signature biomarkers. In this proof-of-concept demonstration, several sets of markers related to cell fate determination were profiled in adipocyte reprogramming from dermal fibroblasts. After validating the accuracy, sensitivity and reproducibility of PHDs-seq data in molecular and cellular assays, a panel of 128 signalling-related compounds was screened for the ability to induce reprogramming of keloid fibroblasts (KF) into adipocytes. Notably, the potent ATP-competitive VEGFR/PDGFR inhibitor compound, ABT869, was found to promote the transition from fibroblasts to adipocytes. This study highlights the power and accuracy of the PHDs-seq platform for high-throughput drug screening in stem cell research, and supports its use in basic explorations of the molecular mechanisms underlying disease development.
高通量表型筛选是药物开发的基石，也是干细胞研究的主要技术手段。然而，使用仅关注少数生物标志物变化的传统筛选方法，很难同时检测负责细胞命运决定的激活核心因子，也难以准确评估细胞的定向转变。PHDs-seq（基于测序的探针杂交药物筛选）平台的开发旨在基于化合物在多种标志性生物标志物中的转录效应来评估其功能。在这个概念验证演示中，对从真皮成纤维细胞进行脂肪细胞重编程过程中与细胞命运决定相关的几组标志物进行了分析。在分子和细胞实验中验证了PHDs-seq数据的准确性、敏感性和可重复性后，筛选了一组128种与信号传导相关的化合物，以检测它们诱导瘢痕疙瘩成纤维细胞（KF）重编程为脂肪细胞的能力。值得注意的是，发现强效的ATP竞争性VEGFR/PDGFR抑制剂化合物ABT869能促进成纤维细胞向脂肪细胞的转变。这项研究突出了PHDs-seq平台在干细胞研究高通量药物筛选中的强大功能和准确性，并支持其在疾病发生分子机制基础探索中的应用。
