Synthetic Circuit-Driven Expression of Heterologous Enzymes for Disease Detection.

The integration of nanotechnology and synthetic biology could lay the framework for new classes of engineered biosensors that produce amplified readouts of disease states. As a proof-of-concept demonstration of this vision, here we present an engineered gene circuit that, in response to cancer-associated transcriptional deregulation, expresses heterologous enzyme biomarkers whose activity can be measured by nanoparticle sensors that generate amplified detection readouts. Specifically, we designed an AND-gate gene circuit that integrates the activity of two ovarian cancer-specific synthetic promoters to drive the expression of a heterologous protein output, secreted Tobacco Etch Virus (TEV) protease, exclusively from within tumor cells. Nanoparticle probes were engineered to carry a TEV-specific peptide substrate in order to measure the activity of the circuit-generated enzyme to yield amplified detection signals measurable in the urine or blood. We applied our integrated sense-and-respond system in a mouse model of disseminated ovarian cancer, where we demonstrated measurement of circuit-specific TEV protease activity both in vivo using exogenously administered nanoparticle sensors and ex vivo using quenched fluorescent probes. We envision that this work will lay the foundation for how synthetic biology and nanotechnology can be meaningfully integrated to achieve next-generation engineered biosensors.

A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS).

Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain biological conditions. Synthetic Promoters with Enhanced Cell-State Specificity (SPECS) can be superior to native ones, but the design of such promoters is challenging and frequently requires gene regulation or transcriptome knowledge that is not readily available. Here, to overcome this challenge, we use a next-generation sequencing approach combined with machine learning to screen a synthetic promoter library with 6107 designs for high-performance SPECS for potentially any cell state. We demonstrate the identification of multiple SPECS that exhibit distinct spatiotemporal activity during the programmed differentiation of induced pluripotent stem cells (iPSCs), as well as SPECS for breast cancer and glioblastoma stem-like cells. We anticipate that this approach could be used to create SPECS for gene therapies that are activated in specific cell states, as well as to study natural transcriptional regulatory networks.

Synthetic RNA-Based Immunomodulatory Gene Circuits for Cancer Immunotherapy.

Despite its success in several clinical trials, cancer immunotherapy remains limited by the rarity of targetable tumor-specific antigens, tumor-mediated immune suppression, and toxicity triggered by systemic delivery of potent immunomodulators. Here, we present a proof-of-concept immunomodulatory gene circuit platform that enables tumor-specific expression of immunostimulators, which could potentially overcome these limitations. Our design comprised de novo synthetic cancer-specific promoters and, to enhance specificity, an RNA-based AND gate that generates combinatorial immunomodulatory outputs only when both promoters are mutually active. These outputs included an immunogenic cell-surface protein, a cytokine, a chemokine, and a checkpoint inhibitor antibody. The circuits triggered selective T cell-mediated killing of cancer cells, but not of normal cells, in vitro. In in vivo efficacy assays, lentiviral circuit delivery mediated significant tumor reduction and prolonged mouse survival. Our design could be adapted to drive additional immunomodulators, sense other cancers, and potentially treat other diseases that require precise immunological programming.