Cells activate precise gene expression programs in response to multifactorial chemical and biological stimuli. The purposeful manipulation of this process is a principal goal of synthetic biology, and its application to human cells could lead to breakthroughs in our understanding of human biology and in the development of next-generation diagnostics and therapeutics that respond in sophisticated ways to disease. Unfortunately, tools to artificially control gene expression in mammalian cells have significant limitations, constraining our ability to study fundamental biological processes and design more effective cell-based therapies. The most widely-used tools are older generation technology, derived from bacterial transcriptional systems. These are greatly limited in number, which restricts the number of gene products that can be simultaneously controlled. Additionally and importantly, they use ?simple? one-to-one regulatory interactions, imposing fundamental restrictions on the regulatory flexibility and sophistication of designer systems. As a consequence, researchers are unable to create sophisticated gene expression controllers that can flexibly sense and integrate biochemical signals (e.g. ligands, chemical inducers, disease cues), and tune or reshape corresponding gene activation profiles. Among the many biomedical applications that would be transformed by these precision gene expression controllers in mammalian cells is the development of cell-based therapeutics for cancer, auto- immunity, and regenerative medicine, which can suffer from issues related to over-activation and tissue specificity. We propose to overcome these barriers by developing a novel synthetic toolkit for gene expression control in mammalian cells. Inspired by the natural design of metazoan transcriptional systems, our framework is based on synthetic transcription factors (synTFs) that can be programmed to assemble cooperatively in multivalent complexes. Our previous work showed that cooperative synTFs enable construction of gene expression control circuits with greatly expanded signal processing behavior in yeast. Here we will develop and characterize mammalian self-assembling synTFs that have superior properties for installation into human cells relative to existing tools. We will use these tools to develop three classes of gene expression controllers, which we will demonstrate in human immune cells, chosen for their important role in human physiology and their potential for cellular therapy: (1) Inducible controllers regulated by orthogonal, FDA-approved drugs. (2) Cell- autonomous controllers that sense and process biological stimuli, including ligand recognition by synthetic Notch receptors and microenvironmental cues. (3) Signal integration controllers that can perceive and integrate multiple biological signals to activate transcriptional programs. We anticipate that this toolkit will be broadly used by researchers to enable precision gene expression control across mammalian systems, including in biomedical applications of synthetic biology, cell reprogramming, and cell-based therapeutics. We will make our tools and design framework freely available to the academic scientific community.

Public Health Relevance

Methods that allow scientists to turn on and off genes in living cells are fundamental to biomedical research, and in particular to advancing the development of new therapies for many diseases, such as cancer and autoimmunity. However, tools for controlling gene expression in mammalian cells have significant limitations: they do not allow multiple genes to be controlled at once, cannot be triggered by many chemical and biological stimuli of interest, and do not provide precise control over how genes are expressed. To address this, we will develop a new toolkit that enables scientists to flexibly and rapidly create gene expression programs to precisely control mammalian cell behavior in response to diverse chemical and biological stimuli.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB029483-01
Application #
9947054
Study Section
Cellular and Molecular Technologies Study Section (CMT)
Program Officer
Rampulla, David
Project Start
2020-05-01
Project End
2024-01-31
Budget Start
2020-05-01
Budget End
2021-01-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Boston University
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215