Anirudh Sivakumar
BME PhD Defense Presentation
Date: 2024-06-27
Time: 10:00 AM
Location / Meeting Link: IBB Suddath Seminar Room 1128 // Virtual Link: https://gatech.zoom.us/j/99889269613?pwd=TnB0SEhqMi90Z2JVVFhGMjRhejBwUT09
Committee Members:
Gabe Kwong, PhD (Advisor); M.G. Finn, PhD; Peng Qiu, PhD; Leslie Chan, PhD; John Blazeck, PhD
Title: Logic-gated activity sensors for programmable detection of antitumor immunity
Abstract:
Advances in synthetic biology have historically focused on the genetic circuit paradigm to assemble sense-and-respond biocircuits that regulate transcription in response to molecular, environmental, or exogenous stimuli. Gene circuits implemented in a variety of prokaryotic and eukaryotic cells have improved detection precision for biomedical applications like cell therapies, drug delivery, molecular imaging, and biosensors. While genetic circuits will remain at the forefront of development, cell- and gene-free biocircuits are now gaining increased attention based on their potential to lower barriers for clinical translation while retaining the ability to perform logical functions. Most of these demonstrations use RNA- or protein-based circuits to transiently regulate protein translation, secretion, and activity without primarily relying on genetic engineering. Moreover, fully synthetic computational nanomaterials can be designed to implement logic in the complete absence of a cellular chassis, including systems like hydrogels that program the release of a drug in response to light or redox potential, peptide-caged liposomes that perform analog-to-digital conversion of protease activity, and imaging probes that selectively highlight tumor margins based on the expression of multiple enzymes to improve surgical resection. These examples highlight the potential of computational nanomaterials that, despite being cell- and gene-free, can apply logic as a means to increase detection precision. Activity-based sensors constitute a growing class of gene-free molecular probes that leverage the pathological dysregulation of protease activity to produce synthetic reporters for detection. Activity-based sensors activated by proteases associated with cancer progression and immunity have demonstrated sensitive detection of indications like cancer, transplant rejection, bacterial infection, and responses to immunotherapy. The central goal of this thesis is to integrate design principles from synthetic biology with activity-based sensors for programmable immune sensing. While immune checkpoint blockade therapy (ICBT) is a first-line treatment option for several cancers, most patients do not respond to ICBT, and many responders acquire drug resistance. In Aim 1, I demonstrate that activity-based detection of the cytotoxic T cell protease granzyme B (GzmB) can identify early antitumor responses induced by ICBT, and I apply a multiplexed library of sensors cleaved by immune- and tumor-associated proteases to classify mechanisms of resistance. As expression of proteases like GzmB and caspases is a conserved mechanism across immune responses to malignancies like cancer, infection, and autoimmunity, in Aim 2 I develop AND-gated sensors that detect concomitant activity from GzmB and tumor-associated matrix metalloproteinases, enabling discrimination of tumor responses to ICBT from off-tumor immunity in the lung due to influenza infection. In Aim 3, to quantitatively understand how AND-gated sensor design parameters influence detection specificity, I develop a mathematical model of AND-gated activity and use the model to predict cooperative sensor activation, leading to higher signal-to-noise ratios that can be tuned by substrate kinetics. This thesis provides a foundation for the rational design of next-generation activity-based sensors to assess tumor responses and resistance to immunotherapy, improve on-tumor specificity based on AND-gate logic, and increase detection precision via model-guided design.