Pino James C, Lubbock Alexander L R, Harris Leonard A, Gutierrez Danielle B, Farrow Melissa A, Muszynski Nicole, Tsui Tina, Sherrod Stacy D, Norris Jeremy L, McLean John A, Caprioli Richard M, Wikswo John P, Lopez Carlos F
Chemical and Physical Biology Graduate Program, Vanderbilt University, Nashville, TN, USA.
Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, TN, USA.
iScience. 2022 Oct 19;25(11):105341. doi: 10.1016/j.isci.2022.105341. eCollection 2022 Nov 18.
Technological advances have made it feasible to collect multi-condition multi-omic time courses of cellular response to perturbation, but the complexity of these datasets impedes discovery due to challenges in data management, analysis, visualization, and interpretation. Here, we report a whole-cell mechanistic analysis of HL-60 cellular response to bendamustine. We integrate both enrichment and network analysis to show the progression of DNA damage and programmed cell death over time in molecular, pathway, and process-level detail using an interactive analysis framework for multi-omics data. Our framework, Mechanism of Action Generator Involving Network analysis (MAGINE), automates network construction and enrichment analysis across multiple samples and platforms, which can be integrated into our annotated gene-set network to combine the strengths of networks and ontology-driven analysis. Taken together, our work demonstrates how multi-omics integration can be used to explore signaling processes at various resolutions and demonstrates multi-pathway involvement beyond the canonical bendamustine mechanism.
技术进步使得收集细胞对扰动的多条件多组学时间进程数据成为可能，但由于数据管理、分析、可视化和解释方面的挑战，这些数据集的复杂性阻碍了发现。在此，我们报告了对HL-60细胞对苯达莫司汀反应的全细胞机制分析。我们整合了富集分析和网络分析，使用一个多组学数据交互式分析框架，从分子、通路和过程层面详细展示了DNA损伤和程序性细胞死亡随时间的进展。我们的框架，即涉及网络分析的作用机制生成器（MAGINE），可自动跨多个样本和平台构建网络并进行富集分析，它可以整合到我们注释的基因集网络中，以结合网络和本体驱动分析的优势。综上所述，我们的工作展示了多组学整合如何用于在不同分辨率下探索信号传导过程，并证明了苯达莫司汀经典机制之外的多通路参与情况。
