Analysis of Heterogeneous, Single-cell Kinase Signaling Dynamics

University of Michigan Cell-to-cell signaling heterogeneity is an important component of healthy and diseased physiology. Signaling activity in individual cells can be measured using fluorescent reporters, which quantify the degree of activity in specific pathways. These reporters offer real-time, live-cell outputs, meaning that they can be used to measure dynamic activities, as opposed to endpoints. Because they function in living cells, they can be used in experiments where cells are subject to continuous perturbations to measure how responses to an early stimulus bias later responses. Nevertheless, there are numerous difficulties associated with analyzing these data. It’s not always clear how to extract features from time-series data, and analysis of periodic or stochastic time-series behavior requires different approaches than traditional signaling analysis. In this talk, I’ll discuss a variety of analysis techniques for heterogeneous, single-cell data gathered from fluorescent reporters. I’ll start by describing data acquisition, and then present a variety of methods with a range of complexities and constraints, including data-driven and mechanistic modeling. I’ll also highlight a range of applications from my own work and others, with particular focus on the analysis of single-cell signaling and immune interactions. Finally, I’ll connect analysis methods described here with analysis of heterogeneous multiscale modeling. Moderator: Tomas Helikar, PhD, University of Nebraska, Lincoln To learn more see: Makowski, Emily K., Patrick C. Kinnunen, Jie Huang, Lina Wu, Matthew D. Smith, Tiexin Wang, Alec A. Desai et al. "Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space." Nature communications 13, no. 1 (2022): 3788. https://www.nature.com/articles/s41467-022-31457-3 To view the slides for this video visit: https://docs.google.com/presentation/d/19AvSLNkQjDX1UXcpSr_k9sBM1pF9CGSj/ If you found this video useful, please check out our other videos on computational modeling, infection and immunology: https://tinyurl.com/GLIMPRINTVideos Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/content/msm-viral-pandemics-meetings Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/