# Multiscale tools and approaches for understanding and engineering cell-fate transitions > **NIH NIH R35** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2021 · $387,750 ## Abstract Project summary Synthetic biology aims to harness the power of biological systems to dynamically access information in the cell, enabling synthetic biomedical tasks such as tumor surveillance, pathogen identification, or cell-fate reprogramming. Such tasks in cellular engineering rely on robust mechanisms to regulate transgenes for the delivery of enzymes, genetic corrections, and cellular therapies. To unleash its full potential, mammalian synthetic biology requires foundational tools for implementing reliable control of gene expression in primary cells. For example, transgene silencing (e.g. loss of expression) remains a common challenge to effectively engineering primary cells. Layers of regulation across a range of length- and time-scales coordinate events from molecular binding to cell signaling regulate gene expression and thus cell fate. Multiscale approaches are needed to integrate the diverse processes that control cell-fate transitions. Cell-fate transitions represent pivotal events requiring coordination of multiple processes from epigenetic and cytoskeletal remodeling to proliferation and transcription. Understanding these transitions may illuminate how oncogenes coopt these processes to drive cellular transformation. Here, we propose a multiscale approach for understanding and engineering cell-fate transitions (e.g. reprogramming, differentiation). From our previous work to identify principles of cell-fate transitions, we identified systems-level constraints that limited reprogramming and developed a cocktail that increased reprograming 100-fold in mouse cells. Comparing the human and mouse response to reprogramming, we identified species-specific differences in proliferation, signaling, and the innate immune response during reprogramming that may contribute to lower reprogramming rates for human cells. We propose to examine these molecular correlates to determine how each impacts the reprogramming process and outcomes. We will use these insights to design genetic controllers to guide cells through reprogramming. Already we have identified a strategy to optimize reprogramming by inducing a transient “erase” phase followed by a “write” phase to establish the new cell fate. We propose to develop controllers capable of autonomously guiding cells through these competing objectives to enhance the efficiency of reprogramming. Genetic controllers are composed from synthetic gene circuits connected to native gene regulatory networks. While significant efforts have been devoted to the logical design of enhanced synthetic circuitry (e.g. circuits for synchronized quorum sensing, edge-detection), less is understood regarding how cellular hardware and the emergent three-dimensional structure of genetic elements affect circuits. Here, we propose to improve our understanding how transcription reshapes DNA and how it impacts the performance of gene circuits. Defining the role of chromatin structure in cellular identity will guide molecular engine... ## Key facts - **NIH application ID:** 10276773 - **Project number:** 1R35GM143033-01 - **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY - **Principal Investigator:** Kate Elizabeth Galloway - **Activity code:** R35 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $387,750 - **Award type:** 1 - **Project period:** 2021-08-01 → 2026-07-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10276773 ## Citation > US National Institutes of Health, RePORTER application 10276773, Multiscale tools and approaches for understanding and engineering cell-fate transitions (1R35GM143033-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10276773. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*