# Quantitative analysis of signaling dynamics across the BMP morphogen gradient

> **NIH NIH F32** · DUKE UNIVERSITY · 2022 · $67,582

## Abstract

ABSTRACT
Our current knowledge of BMP signaling pathway specificity is based upon foundational genetic and in vitro
experiments, but we have limited understanding as to how cells produce diverse but specific responses to
similar signaling inputs in vivo. In the Drosophila embryo, a steep gradient of BMP signaling is dynamically
established prior to gastrulation. This gradient is interpreted by different populations of cells to establish the
dorsal-ventral axis of the embryo, with cells at the dorsal midline turning on a unique set of transcripts
compared to more lateral cells. We do not know how the dynamics of gradient formation and the final
gradient pattern are interpreted by cohorts of cells in the embryo to produce the correct spatiotemporal
transcriptional response. Using new imaging tools and a quantitative systems level approach, I will be able to
interrogate how upstream inputs to the BMP signaling pathway are decoded in the nucleus to elicit correct
spatiotemporal transcriptional responses.
In this study I will explore two potential mechanisms by which BMP signaling is encoded. First, new methods
will allow me to assay the signaling dynamics of pathway activity along the BMP gradient. With these data I
will build an input-output relationship model to predict the mechanisms that drive BMP-responsive
transcriptional dynamics. Second, I will determine if different combinations of ligand and receptor pairs play a
role in specification and interpretation of the BMP gradient. I will study how both dynamic and combinatorial
signaling are used to produce the wild type pattern of BMP signaling responses in the embryo. Then, using
genetic perturbations in key pathway components that propagate and shape the morphogen gradient, I will
test if these input-output relationships in dynamics and combinatorial signaling hold true across different BMP
signaling contexts. Successful completion of this study will provide a quantitative view for how a conserved
signaling pathway is interpreted by cells in vivo across time and space.

## Key facts

- **NIH application ID:** 10386746
- **Project number:** 1F32GM145070-01
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Susanna Elizabeth Brantley
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $67,582
- **Award type:** 1
- **Project period:** 2022-06-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10386746

## Citation

> US National Institutes of Health, RePORTER application 10386746, Quantitative analysis of signaling dynamics across the BMP morphogen gradient (1F32GM145070-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10386746. Licensed CC0.

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