Neuroscience Research, Novartis Institutes for Biomedical Research, 250 Massachusetts, Cambridge, MA, 02139, USA.
Blueprint Medicines, 45 Sidney St, Cambridge, MA, 02139, USA.
Nat Commun. 2018 Oct 17;9(1):4307. doi: 10.1038/s41467-018-06500-x.
Here we report Digital RNA with pertUrbation of Genes (DRUG-seq), a high-throughput platform for drug discovery. Pharmaceutical discovery relies on high-throughput screening, yet current platforms have limited readouts. RNA-seq is a powerful tool to investigate drug effects using transcriptome changes as a proxy, yet standard library construction is costly. DRUG-seq captures transcriptional changes detected in standard RNA-seq at 1/100 the cost. In proof-of-concept experiments profiling 433 compounds across 8 doses, transcription profiles generated from DRUG-seq successfully grouped compounds into functional clusters by mechanism of actions (MoAs) based on their intended targets. Perturbation differences reflected in transcriptome changes were detected for compounds engaging the same target, demonstrating the value of using DRUG-seq for understanding on and off-target activities. We demonstrate DRUG-seq captures common mechanisms, as well as differences between compound treatment and CRISPR on the same target. DRUG-seq provides a powerful tool for comprehensive transcriptome readout in a high-throughput screening environment.
我们在此报告一种新的高通量药物筛选平台，即基因扰动的数字 RNA（DRUG-seq）。药物发现依赖于高通量筛选，但目前的平台的检测结果有限。RNA-seq 是一种通过转录组变化作为替代物来研究药物作用的强大工具，但标准文库构建成本高昂。DRUG-seq 以 1/100 的成本捕获标准 RNA-seq 中检测到的转录变化。在对 8 个剂量的 433 种化合物进行的概念验证实验中，从 DRUG-seq 生成的转录谱成功地根据其预期靶点的作用机制（MoAs）将化合物分组为功能簇。对作用于同一靶点的化合物进行分析，发现转录组变化反映了扰动差异，这证明了使用 DRUG-seq 来了解靶内和靶外活性的价值。我们证明，DRUG-seq 能够捕捉常见机制，以及化合物处理和同一靶标上的 CRISPR 之间的差异。DRUG-seq 为高通量筛选环境中的全面转录组检测提供了一种强大的工具。
