Liu Nuo, Kattan Walaa E, Mead Benjamin E, Kummerlowe Conner, Cheng Thomas, Ingabire Sarah, Cheah Jaime H, Soule Christian K, Vrcic Anita, McIninch Jane K, Triana Sergio, Guzman Manuel, Dao Tyler T, Peters Joshua M, Lowder Kristen E, Crawford Lorin, Amini Ava P, Blainey Paul C, Hahn William C, Cleary Brian, Bryson Bryan, Winter Peter S, Raghavan Srivatsan, Shalek Alex K
Institute for Medical Engineering and Science (IMES) and Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.
Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nat Biotechnol. 2024 Oct 7. doi: 10.1038/s41587-024-02403-z.
High-throughput phenotypic screens using biochemical perturbations and high-content readouts are constrained by limitations of scale. To address this, we establish a method of pooling exogenous perturbations followed by computational deconvolution to reduce required sample size, labor and cost. We demonstrate the increased efficiency of compressed experimental designs compared to conventional approaches through benchmarking with a bioactive small-molecule library and a high-content imaging readout. We then apply compressed screening in two biological discovery campaigns. In the first, we use early-passage pancreatic cancer organoids to map transcriptional responses to a library of recombinant tumor microenvironment protein ligands, uncovering reproducible phenotypic shifts induced by specific ligands distinct from canonical reference signatures and correlated with clinical outcome. In the second, we identify the pleotropic modulatory effects of a chemical compound library with known mechanisms of action on primary human peripheral blood mononuclear cell immune responses. In sum, our approach empowers phenotypic screens with information-rich readouts to advance drug discovery efforts and basic biological inquiry.
使用生化扰动和高内涵读数的高通量表型筛选受到规模限制。为了解决这一问题,我们建立了一种汇集外源性扰动然后进行计算反卷积的方法,以减少所需的样本量、劳动力和成本。通过使用生物活性小分子文库和高内涵成像读数进行基准测试,我们证明了与传统方法相比,压缩实验设计的效率有所提高。然后,我们在两项生物学发现活动中应用了压缩筛选。在第一项活动中,我们使用早期传代的胰腺癌类器官来绘制对重组肿瘤微环境蛋白配体文库的转录反应,发现特定配体诱导的可重复表型变化,这些变化不同于经典参考特征,且与临床结果相关。在第二项活动中,我们确定了具有已知作用机制的化合物文库对原代人外周血单核细胞免疫反应的多效性调节作用。总之,我们的方法通过信息丰富的读数增强了表型筛选,以推进药物发现工作和基础生物学研究。