Ribonucleic acid sensing and programming platforms for mammalian synthetic Biology

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, 2019Cataloged from PDF version of thesis.Includes bibliographical references (pages 153-173).The field of synthetic biology aims to control cellular behavior using programmable gene circuits. Generally these gene circuits sense molecular biomarkers, process these inputs and execute a desired calculated response. This is especially relevant for gene and cell therapies where integrating multiple disease-related inputs and/or sophisticated control could lead to safer and more effective approaches. While mammalian synthetic biology has made great progress, few gene circuit-based therapies have entered the clinic. Regulatory issues aside, this lag may be due to several technical impediments. First, the computing part of circuits is often accomplished via transcriptional regulation, which presents challenges as we move toward the clinic. Second, the field relies on a limited set of sensors; the detection of other types of disease biomarkers will help robustly identify cell state.Finally, the design cycle currently used to develop gene circuits is laborious and slow, which is not suitable for clinical development, especially applications in personalized medicine. In this thesis I describe how I address these three limitations. I develop a new posttranscriptional regulation platform based on RNA cleavage that I term "PERSIST" (Programmable Endonucleolytic RNA Scission-Induced Stability Tuning). CRISPR-specific endonucleases are adapted as RNA-level regulators for the platform and we demonstrate several genetic devices including cascades, feedback, logic functions and a bistable switch. I explore sensor designs for relevant biomolecules including mRNAs, miRNAs and proteins via the PERSIST and other platforms. Finally, I present a "poly-transfection" method, associated advanced data analysis pipelines, and computational models that make circuit engineering faster and more predictive.Taken together, the expanded RNA toolkit that the PERSIST platform offers as well as advancements in sensing and circuit design will enable the more straightforward creation of robust gene circuits for gene and cell therapies.by Breanna Elizabeth DiAndreth.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Biological Engineerin

Programming gene and engineered-cell therapies with synthetic biology

Gene and engineered-cell therapies promise to treat diseases by genetically modifying cells to carry out therapeutic tasks. Although the field has had some success in treating monogenic disorders and hematological malignancies, current approaches are limited to overexpression of one or a few transgenes, constraining the diseases that can be treated with this approach and leading to potential concerns over safety and efficacy. Synthetic gene networks can regulate the dosage, timing, and localization of gene expression and therapeutic activity in response to small molecules and disease biomarkers. Such “programmable” gene and engineered-cell therapies will provide new interventions for incurable or difficult-to-treat diseases.United States. Defense Advanced Research Projects Agency (Grant DARPA-BAA-11-23)National Institutes of Health (U.S.) (Grant CA207029)National Science Foundation (U.S.) (Grant CNS-1446607)National Science Foundation (U.S.) (Grant GRFP 1122374

PERSIST platform provides programmable RNA regulation using CRISPR endoRNases

AbstractRegulated transgene expression is an integral component of gene therapies, cell therapies and biomanufacturing. However, transcription factor-based regulation, upon which most applications are based, suffers from complications such as epigenetic silencing that limit expression longevity and reliability. Constitutive transgene transcription paired with post-transcriptional gene regulation could combat silencing, but few such RNA- or protein-level platforms exist. Here we develop an RNA-regulation platform we call “PERSIST" which consists of nine CRISPR-specific endoRNases as RNA-level activators and repressors as well as modular OFF- and ON-switch regulatory motifs. We show that PERSIST-regulated transgenes exhibit strong OFF and ON responses, resist silencing for at least two months, and can be readily layered to construct cascades, logic functions, switches and other sophisticated circuit topologies. The orthogonal, modular and composable nature of this platform as well as the ease in constructing robust and predictable gene circuits promises myriad applications in gene and cell therapies.</jats:p

A ‘poly-transfection’ method for rapid, one-pot characterization and optimization of genetic systems

Biological research is relying on increasingly complex genetic systems and circuits to perform sophisticated operations in living cells. Performing these operations often requires simultaneous delivery of many genes, and optimizing the stoichiometry of these genes can yield drastic improvements in performance. However, sufficiently sampling the large design space of gene expression stoichiometries in mammalian cells using current methods is cumbersome, complex, or expensive. We present a 'poly-transfection' method as a simple yet high-throughput alternative that enables comprehensive evaluation of genetic systems in a single, readily-prepared transfection sample. Each cell in a poly-transfection represents an independent measurement at a distinct gene expression stoichiometry, fully leveraging the single-cell nature of transfection experiments. We first benchmark poly-transfection against co-transfection, showing that titration curves for commonly-used regulators agree between the two methods. We then use poly-transfections to efficiently generate new insights, for example in CRISPRa and synthetic miRNA systems. Finally, we use poly-transfection to rapidly engineer a difficult-to-optimize miRNA-based cell classifier for discriminating cancerous cells. One-pot evaluation enabled by poly-transfection accelerates and simplifies the design of genetic systems, providing a new high-information strategy for interrogating biology. ©2019National Institutes of Health (no. R01CA173712)National Institutes of Health (no. R01CA207029)National Institutes of Health (no. P50GM098792)National Science Foundation (no. 1745645)Cancer Center Support Grant (no. P30CCA14051

An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells

© 2020, The Author(s). Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device’s output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression

Engineering modular intracellular protein sensor-actuator devices

Understanding and reshaping cellular behaviors with synthetic gene networks requires the ability to sense and respond to changes in the intracellular environment. Intracellular proteins are involved in almost all cellular processes, and thus can provide important information about changes in cellular conditions such as infections, mutations, or disease states. Here we report the design of a modular platform for intrabody-based protein sensing-actuation devices with transcriptional output triggered by detection of intracellular proteins in mammalian cells. We demonstrate reporter activation response (fluorescence, apoptotic gene) to proteins involved in hepatitis C virus (HCV) infection, human immunodeficiency virus (HIV) infection, and Huntington’s disease, and show sensor-based interference with HIV-1 downregulation of HLA-I in infected T cells. Our method provides a means to link varying cellular conditions with robust control of cellular behavior for scientific and therapeutic applications

DataSheet_1_Geometric parameters that affect the behavior of logic-gated CAR T cells.pdf

Clinical applications of CAR-T cells are limited by the scarcity of tumor-specific targets and are often afflicted with the same on-target/off-tumor toxicities that plague other cancer treatments. A new promising strategy to enforce tumor selectivity is the use of logic-gated, two-receptor systems. One well-described application is termed Tmod™, which originally utilized a blocking inhibitory receptor directed towards HLA-I target antigens to create a protective NOT gate. Here we show that the function of Tmod blockers targeting non-HLA-I antigens is dependent on the height of the blocker antigen and is generally compatible with small, membrane-proximal targets. We compensate for this apparent limitation by incorporating modular hinge units to artificially extend or retract the ligand-binding domains relative to the effector cell surface, thereby modulating Tmod activator and blocker function. By accounting for structural differences between activator and blocker targets, we developed a set of simple geometric parameters for Tmod receptor design that enables targeting of blocker antigens beyond HLA-I, thereby broadening the applications of logic-gated cell therapies.</p