Using light to control gene expression offers several advantages as compared to the traditional chemical-based control. First, light can be rapidly delivered to cells, which avoids the delay caused by the cross-membrane transportation of the chemicals. Second, the intensity and pattern of light can be easily tuned to generate reversible, temporal and spatial control of gene expression. Third, LED systems are cheaper and more durable in comparison to chemicals, expensive and with varied half-life. Our lab has developed blue light-mediated transcriptional activation and repression of gene expression in bacteria using the light-activated DNA-binding protein EL222. EL222 constitutes a one-component system that doesn’t require a transmembrane protein, providing greater portability than other solutions. Furthermore, our lab also works on the development of multi-wavelength optogenetic systems by combining several optogenetic proteins.
To actuate in an effective manner, our engineered cells need to sense their environment. By investigating and repurposing different sensor systems found in nature, we provide our engineered cells with the capability to sense our compound of interest. One example is our Vibrio cholerae biosensor. To sense this potentially deadly pathogen we adapt the CAI-1 quorum sensing mechanism of V. cholerae and incorporate it into our cell constructs, adapting it to our needs using a CRISPRi inverter. This technology is then applied to other research areas in our group, such as the design and synthesis of therapeutic cells.
Mathematical modelling constitutes a powerful tool in our continuous search for improved performance, along with the advent of the utilization of high-throughput experimental instruments and techniques in Synthetic Biology’s design-build-test process. Broadly, mathematical modelling allows a representative construct of the essential aspects of the system, capturing the system behaviour in a quantitative manner and allowing system analysis and rational design optimization. A well-implemented model is able to recapitulate essential system behaviours, and provide insights to specific questions about the system, as well as to generate new hypotheses.
In our lab, mathematical modelling forms an integral part of every project, guiding the rational design of the different bacterial constructs. This task is facilitated by developing computer aided design (CAD) tools such as the Bio-Model Selection System (BMSS). The BMSS consist of a framakework containing a library of pre-established models so different gene circuits like chemically inducible systems, constitutive systems and logic gates can be accuratelly modeled. The system also allows the generation of SBOL-compliant gene circuit configurations and SBML output files. Generated as a cross-platform library implemented in Python, all aspects of the system were programmed in a modular manner to facilitate extension and customization of models by the user.
Collagen is a valuable biomaterial with applications in areas such as tissue engineering and cell therapies. With the growing needs for collagen projected to reach US$9,372.3 millions by year 2023, no current production technology is able to generate the required yields. Extracting collagen from its natural sources is often challenging, and there is a growing concern of risk of infectious diseases transmission from animal sources. Alternatively, bacterial collagen has been reported to be a promising substitute to mammalian collagen and has been tested as non-toxic, biocompatible and with a cell-specific adhesion capability with improved spreading effects. In our lab, we are currently working to produce recombinant bacterial collagen in E. coli using a synthetic biology approach. By engineering different gene circuits, we aim to construct microbial cells factories capable to dynamically regulate the different stages of collagen synthesis, leading to productions of high quiality and yield. Furthermore, we also aim to apply the generated technologies to the production of other valuable chemicals and biomaterial.
Biofilm reactors have shown to achieve higher productivity and longer production time than conventional bioreactors. However, uncontrolled growth of biofilms remains a key challenge in the application of biofilm in bioproduction, as excessive biofilm thickness hinders diffusion of nutrients and products. To address this problem, we use a synthetic biology approach, developing synthetic gene circuits that control biofilm formation by regulating the production of colonic acid. In parallel, we are also studying genetic sensors of compounds such as pyruvate, nutrients and oxygen in order to monitor the status of the cells and biofilm. The goal of this project is to achieve an autonomous biofilm formation, with cells maintaining the biofilm at the optimum state for long periods and, when conditions become unfavorable, dispersing and forming a new biofilm.
The rapid emergence of an increasing number of resistant bacteria is accelerating the arrival of the "post-antibiotic era", when health problems due to the lack of effective antibiotic will have global dire consequences. New strategies to fight emerging pathogens are therefore of the utmost importance. Using a synthetic biology approach, we rationally design bacterial constructs to fight potentially deadly pathogens such as V. cholerae. Based on a harmless E. coli strains, our constructs sense the V. cholerae CAI-1 quorum sensing autoinducer and release the antibacterial protein Art-085 protein to kill the pathogen. This strategy allows to exert an antibacterial effect only when it is needed, therefore preventing development of resistance, and can also be expanded with a complete palette of antibacterial substances, therefore overcoming resistance to single compounds.