# Connecting Single-Cell Signaling Dynamics to Multicellular Decision Making

> **NIH NIH R35** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2020 · $412,500

## Abstract

SUMMARY
 Cures for many diseases and injuries have remained elusive because the systems they affect are
highly adaptable multicellular collectives that harness biochemical communication to reprogram themselves to
circumvent our treatment strategies. The goal of my research program is to identify how single cells interpret
their environments and modulate their behaviors to control these multicellular decisions. Our current
understanding of this connection has been limited due to the conceptual and technological challenges
presented by connecting the small-scale, fast dynamics inside single cells to larger-scale behaviors unfolding
over hours and days in cellular populations. During this award, we will address these challenges and focus on
resolving several key gaps in our understanding, specifically (1) identifying single-cell regulatory mechanisms
for modulating population-wide behaviors and (2) elucidating how the interplay between signaling and
mechanics drives cellular populations to work together to remodel themselves. To enable us to directly link
single-cell dynamics to population-wide decision making, we are developing and implementing new
technologies for simultaneous quantitative visualization and control of intra- and intercellular biochemical
dynamics driving these decisions. These techniques, in combination with quantitative modeling, will allow us to
make causal links between intracellular signaling and multicellular behaviors. Our work will be performed in a
classic model organism for collective behaviors, the social amoeba Dictyostelium discoideum, as well as a
biomimetic wound healing model where we can directly link intracellular signaling to mechanical environmental
cues. The tools we develop in these systems to link signaling dynamics to population behaviors will also
enable us to interrogate these behaviors and develop models of these behaviors with real predictive power.
With our new predictive understanding of the single-cell dynamics used to coordinate collectives and by
demonstrating we can control these behaviors ourselves, we will be laying the groundwork for reprogramming
these behaviors for transformative new disease and injury treatments.

## Key facts

- **NIH application ID:** 10001585
- **Project number:** 5R35GM133616-02
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Allyson E Sgro
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $412,500
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10001585

## Citation

> US National Institutes of Health, RePORTER application 10001585, Connecting Single-Cell Signaling Dynamics to Multicellular Decision Making (5R35GM133616-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10001585. Licensed CC0.

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