Optogenetic tools provide a new and efficient way to dynamically program gene expression with unmatched spatiotemporal precision. To date, their vast potential remains untapped in the field of cell-free synthetic biology, largely due to the lack of simple and efficient light-switchable systems. Here, to bridge the gap between cell-free systems and optogenetics, we studied our previously engineered one component-based blue light-inducible Escherichia coli promoter in a cell-free environment through experimental characterization and mathematical modeling. We achieved >10-fold dynamic expression and demonstrated rapid and reversible activation of the target gene to generate oscillatory response. The deterministic model developed was able to recapitulate the system behavior and helped to provide quantitative insights to optimize dynamic response. This in vitro optogenetic approach could be a powerful new high-throughput screening technology for rapid prototyping of complex biological networks in both space and time without the need for chemical induction.

New strategies to control cholera are urgently needed. This study develops an in vitro proof-of-concept sense-and-kill system in a wild-type Escherichia coli strain to target the causative pathogen Vibrio cholerae using a synthetic biology approach. Our engineered E. coli specifically detects V. cholerae via its quorum-sensing molecule CAI-1 and responds by expressing the lysis protein YebF-Art-085, thereby self-lysing to release the killing protein Art-085 to kill V. cholerae. For this report, we individually characterized YebF-Art-085 and Art-085 expression and their activities when coupled to our previously developed V. cholerae biosensing circuit. We show that, in the presence of V. cholerae supernatant, the final integrated sense-and-kill system in our engineered E. coli can effectively inhibit the growth of V. cholerae cells. This work represents the first step toward a novel probiotic treatment modality that could potentially prevent and treat cholera in the future.

Constructing a complex functional gene circuit composed of different modular biological parts to achieve the desired performance remains challenging without a proper understanding of how the individual module behaves. To address this, mathematical models serve as an important tool toward better interpretation by quantifying the performance of the overall gene circuit, providing insights, and guiding the experimental designs. As different gene circuits might require exclusively different mathematical representations in the form of ordinary differential equations to capture their transient dynamic behaviors, a recurring challenge in model development is the selection of the appropriate model. Here, we developed an automated biomodel selection system (BMSS) which includes a library of pre-established models with intuitive or unintuitive features derived from a vast array of expression profiles. Selection of models is built upon the Akaike information criteria (AIC). We tested the automated platform using characterization data of routinely used inducible systems, constitutive expression systems, and several different logic gate systems (NOT, AND, and OR gates). The BMSS achieved a good agreement for all the different characterization data sets and managed to select the most appropriate model accordingly. To enable exchange and reproducibility of gene circuit design models, the BMSS platform also generates Synthetic Biology Open Language (SBOL)compliant gene circuit diagrams and Systems Biology Markup Language (SBML) output files. All aspects of the algorithm were programmed in a modular manner to ease the efforts on model extensions or customizations by users. Taken together, the BMSS which is implemented in Python supports users in deriving the best mathematical model candidate in a fast, efficient, and automated way using part/circuit characterization data.

To program cells in a dynamic manner, synthetic biologists require precise control over the threshold levels and timing of gene expression. However, in practice, modulating gene expression is widely carried out using prototypical ligand-inducible promoters, which have limited tunability and spatiotemporal resolution. Here, we built two dual-input hybrid promoters, each retaining the function of the ligand-inducible promoter while being enhanced with a blue-light-switchable tuning knob. Using the new promoters, we show that both ligand and light inputs can be synchronously modulated to achieve desired amplitude or independently regulated to generate desired frequency at a specific amplitude. We exploit the versatile programmability and orthogonality of the two promoters to build the first reprogrammable logic gene circuit capable of reconfiguring into logic OR and N-IMPLY logic on the fly in both space and time without the need to modify the circuit. Overall, we demonstrate concentration- and time-based combinatorial regulation in live bacterial cells with potential applications in biotechnology and synthetic biology.

Temperature is a physical cue that is easy to apply, allowing cellular behaviors to be controlled in a contactless and dynamic manner via heat-inducible/repressible systems. However, existing heat-repressible systems are limited in number, rely on thermal sensitive mRNA or transcription factors that function at low temperatures, lack tunability, suffer delays, and are overly complex. To provide an alternative mode of thermal regulation, we developed a library of compact, reversible, and tunable thermalrepressible split-T7 RNA polymerase systems (Thermal-T7RNAPs), which fused temperature-sensitive domains of Tlpa protein with split-T7RNAP to enable direct thermal control of the T7RNAP activity between 30 and 42 °C. We generated a large mutant library with varying thermal performances via an automated screening framework to extend temperature tunability. Lastly, using the mutants, novel thermal logic circuitry was implemented to regulate cell growth and achieve active thermal control of the cell proportions within co-cultures. Overall, this technology expanded avenues for thermal control in biotechnology applications.