# Connecting Single-Cell Signaling Dynamics to Multicellular Decision Making

> **NIH NIH R35** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2021 · $150,000

## 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, our funded grant supports developing and
implementing new technologies for simultaneous quantitative visualization and control of intra- and intercellular
biochemical dynamics driving these decisions. This equipment supplement is requesting funding to support a
high-throughput, highly-reproducible imaging system to support the screening of genetically-encoded tools and
imaging conditions to interrogate these signaling dynamics. The behaviors we seek to understand occur over
hours and days, and adapting tools for quantifying and controlling these dynamics to new questions requires a
high-throughput approach. 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. This supplement will both allow us to develop a new predictive understanding of the single-
cell dynamics used to coordinate collectives and by demonstrating we can control these behaviors ourselves,
laying the groundwork for reprogramming these behaviors for transformative new disease and injury
treatments, as well as develop well-characterized toolbox for interrogating and controlling these behaviors in
multiple model systems that we will disseminate to the broader medical science community.

## Key facts

- **NIH application ID:** 10389561
- **Project number:** 3R35GM133616-03S1
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Allyson E Sgro
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $150,000
- **Award type:** 3
- **Project period:** 2019-09-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10389561

## Citation

> US National Institutes of Health, RePORTER application 10389561, Connecting Single-Cell Signaling Dynamics to Multicellular Decision Making (3R35GM133616-03S1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10389561. Licensed CC0.

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