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

> **NIH NIH R35** · UNIVERSITY OF VIRGINIA · 2020 · $325,098

## Abstract

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 ...

## Key facts

- **NIH application ID:** 10132690
- **Project number:** 7R35GM133404-02
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Mohammad Fallahi-Sichani
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $325,098
- **Award type:** 7
- **Project period:** 2019-09-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10132690

## Citation

> US National Institutes of Health, RePORTER application 10132690, Decoding the Logic of Cellular Signaling Through the Integration of Dynamic, Single-Cell and Multiplexed Methods (7R35GM133404-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10132690. Licensed CC0.

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