# Measuring and modeling the dynamics of patterning in human stem cells > **NIH NIH R01** · HARVARD UNIVERSITY · 2022 · $325,214 ## Abstract Abstract The long-term goal of this project is to understand how cells in complex human tissues sense, process and respond to signal during normal human development and developmental diseases. A fundamental question in developmental biology is to understand how tissues are patterned in a developing animal. This Application will address the question in the context of the patterning of the human pluripotent cells into mesoderm and endoderm. The first question that will be investigated is how cells sense signal, followed by a closer look at how the internal gene regulatory network processes this signal to launch a transcriptional response as the cell chooses its fate. The first aim of this proposal uses a combination of novel microfluidics to control gradients of signals, genome modification techniques to fluorescently tag key transcription factors to study their dynamics using epifluorescence, and image processing and mathematical tools to analyze the data. It further follows up on the applicant’s recent discovery that key receptors that sense signals are basally localized. This study demonstrates how the (in)ability of the cell to sense active apical signal due its receptors being localized basally affect patterning. This is the first study the applicants are aware of to attempt to quantitatively understand how human stem cells are patterned. The second aim focuses on understanding how the state of the gene regulatory network within the cell affects the response to TGF-beta signal during germ layer differentiation in human and mouse. Indeed, cells even twelve hours apart in development obtained from the same region of the embryo show digitally distinct responses to the same signal. Single cell gene expression data obtained during the course of development is used to build a predictive mathematical model of the intracellular gene regulatory network. Building such predictive mathematical models has been very challenging in the past. Using these models, the goal of this aim is to uncover whether cells can respond to the same morphogenetic signal in distinct ways depending on the state of a core gene regulatory circuit. The predictions are checked experimentally in the context of early human and mouse development using imaging and molecular techniques to perturb gene expression. The discoveries made by the proposal will lead to a better understanding of how multipotent human cells respond to signal both during development and in cancer. Furthermore, the ability to build predictive models of the underlying gene regulatory network opens avenues to understand the mechanisms underlying disease states in the future. ## Key facts - **NIH application ID:** 10318976 - **Project number:** 5R01GM131105-04 - **Recipient organization:** HARVARD UNIVERSITY - **Principal Investigator:** Sharad Ramanathan - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $325,214 - **Award type:** 5 - **Project period:** 2019-01-11 → 2023-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10318976 ## Citation > US National Institutes of Health, RePORTER application 10318976, Measuring and modeling the dynamics of patterning in human stem cells (5R01GM131105-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10318976. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*