Decoding the Logic of Cellular Signaling Through the Integration of Dynamic, Single-Cell and Multiplexed Methods

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PROJECT SUMMARY Cells respond to a wide range of stimuli through signaling pathways. These pathways modulate transcription factor activities, expression of target genes and changes in cellular states and decisions. It is now well- established that the temporal dynamics of pathway activities play a key role in signal transduction. However, decoding the logic by which these dynamic patterns determine cellular response is still a challenging goal. The challenge is particularly formidable when these responses are: (i) subject to combinatorial control by multiple pathways encoded by common or distinct ligand-receptor interactions, (ii) mediated by a multiplicity of independent or co-regulated transcription factors, and (iii) altered by the cellular context, e.g. differentiation state. These challenges, despite an increased understanding of cellular signaling mechanisms, have complicated our ability to accurately predict the response of cells to stress, ligands and drugs. Our long-term goal is to understand how cells process dynamic information from combinations of tightly regulated signaling pathways to modulate downstream transcription factor dynamics, and how such dynamics coordinate both “context-dependent” and “stimulus-specific” responses. Our proposed research program focuses on Activator Protein 1 (AP-1), a classical paradigm for transcription factors, which cells utilize to orchestrate responses to a variety of environmental changes, and thereby decide whether to divide, differentiate, adapt to environment, or die. While the molecular regulation of the AP-1 factors have been extensively investigated, how they function as a dynamic network, and how this network integrates patterns of ERK, JNK and p38 signaling to regulate gene expression programs that drive diverse and context-dependent cell decisions, have remained unclear. The gap in knowledge has been largely due to the lack of system-wide measurements, single-cell precision, and computational modeling in the previous studies of AP-1 dynamics, in which interdependencies between a whole array of AP-1 family proteins (including Jun, Fos and closely related ATF sub-families), their interactions, post-translational modifications, upstream regulators and their partners have remained incompletely mapped out. In this research program, we will develop an integrated platform, combining high- throughput, highly multiplexed measurements, single-cell technologies in live and fixed cells, genome-wide analysis and computational modeling, as a means to overcome these gaps and challenges. We will use these tools to: (1) uncover how distinct combinatorial patterns of AP-1 dynamics mediate a diverse range of seemingly unrelated functions, (2) decode the logic by which stimulus-specific information encoded in ERK, JNK and p38 pathway dynamics is transmitted to the AP-1 network, and (3) define the mechanisms by which the network integrates this information with cell-intrinsic factors to drive context-dependent decisions. From a better understanding of these fundamental mechanisms, we can learn to improve the responses of healthy cells to harmful stimuli, and develop strategies to induce selective killing in unhealthy cells when necessary.