The overarching goal of this project is to test the hypothesis that modulation of phosphorylation-mediated signaling events in response to perturbations can establish new cellular states by altering their epigenetic landscapes. To achieve this goal, we propose performing mass spectrometry (MS)-based proteomic assays that specifically target quantitative readouts of phosphosignaling and chromatin modifications in cells on > 15,000 perturbational conditions. These perturbations will focus on modulation of signaling cascades and epigenetic marks by small molecules and gene inactivations. We will study several different cellular model systems, including comprehensive studies neuronal lineage differentiation starting from human embryonic stem cells. We propose to establish a center.in order to develop the necessary infrastructure, pipelines, data management, and analytics required to perform what would be the largest set of related experiments with MS proteomic read outs to date. We will also explore next-generation MS acquisition technologies to establish a permanently minable MS data resource that will be accessible to the public. We will contribute the resulting data and tools to the Library of Integrated Network-based Cellular Signatures (LINCS) program for the purpose of making connections among disparate perturbations through phosphoproteomic and chromatin modification signatures in concert with other data types to be contributed to LINCS by other centers. The resulting analyses will help identify novel therapeutic opportunities and synergies, as dysregulation of phosphosignaling and epigenetic systems are two of the most common molecular etiologies identified in a growing number of genetic, developmental, and environmental diseases. In this component of the project we describe the data analysis pipelines, advanced statistical and bioinformatic techniques, and data repository strategies that we will use to prosecute the project. We also discuss how end-users outside of our center will access, analyze, visualize, and interact with the data that we generate through web-based tools that we will develop.
This project is relevant because we will learn how to develop new drugs that target the common ways that diseases like cancer are caused in the cells of our bodies. We will use cutting edge scientific techniques to understand how these diseases cause normally healthy cells to become sick, and identify possible ways to block or reverse these effects.
|Abelin, Jennifer G; Patel, Jinal; Lu, Xiaodong et al. (2016) Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes. Mol Cell Proteomics 15:1622-41|
|Jaffe, Jacob D; Feeney, Caitlin M; Patel, Jinal et al. (2016) Transitioning from Targeted to Comprehensive Mass Spectrometry Using Genetic Algorithms. J Am Soc Mass Spectrom 27:1745-1751|
|Egertson, Jarrett D; MacLean, Brendan; Johnson, Richard et al. (2015) Multiplexed peptide analysis using data-independent acquisition and Skyline. Nat Protoc 10:887-903|