Periodic Reporting for period 4 - COMPUCELL (Autonomous Cellular Computers for Diagnosis) Reporting period: 2019-11-01 to 2021-10-31 Summary of the context and overall objectives of the project Early diagnostics based on multiple biomarkers is key in numerous diseases, yet current technologies for multiplexed detection are complicated and expensive.Living cells detect and process various environmental signals in parallel and can self-replicate, presenting an attractive platform for scalable and affordable autonomous diagnostic devices. In this project,our goal was to apply tools from synthetic biology, the rational engineering of biological systems, to build cell-based biosensors for multiplexed diagnosis using non-pathogenic bacteria.In a first research line, our aim was to conceive chimeric receptors detecting extracellular biomarkers by repurposing natural sensing domains or using antibody-like molecules. In a second research line, our goal was to engineer bio-molecular computing systems operating in living cells to perform multiplexed biomarkers analysis. Our project was highly interdisciplinary and at the crossroads of genetic engineering, structural biology, biophysics, modeling, and clinics. During this project, we have made several breakthrough contributions:(i) We have generally advanced engineering frameworks for microorganisms-based synthetic biology approaches. (ii) We have pushed the limits of custom ligand detection by engineered cells, by generating a synthetic receptor platform, called EMERALD, allowing bacteria to detect pathological biomarkers in patients' clinical samples. We validated our system by using bacteria with synthetic receptors to detect serum bile salts a biomarker of liver dysfunction, in samples from patients having undergone a liver transplant.iii) We have explored the frontiers of human-made biological computers and pioneered novel computational paradigms to allow the programming of living organisms. Because of the modular design principles applied, our sensing platform will be reusable to diagnose different pathologies as well as for applications requiring custom-detection and biomolecularcomputation like targeted therapy, drug delivery, or environmental monitoring. Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far We provide a summary of the major achievements achieved during the project:1) [Month 12] We produced collections of biological parts for the precise control of transcription, translation, RNA and protein stability in bacteria (Guiziou et al, Nucleic acids Research, 2016).2) [Month 24] We have designed a complete framework for the automated design of recombinase logic gates within multicellular systems. We generated a reduced library of computational modules distributed into different cellular subpopulations which are then composed in various manners to implement all desired logic functions at the multicellular level. Our design platform is broadly accessible via a web server taking truth tables as inputs and providing corresponding DNA designs and sequences (available at: Guiziou et al, ACS Synthetic Biology, 2017.3) [Month 28] We have engineered the first set of programmable transmembrane receptors using a synthetic binder as a sensing domain. These receptors open the road to novel sensing modalities, in particular towards the detection of ligand for which no receptor is found in nature (Chang et al., ACS Synthetic Biology, 2017). One patent application was also deposited.4) [Month 44] We have implemented a systematic framework for engineering reliable recombinase logic devices by hierarchical composition of well-characterized, optimized recombinase switches. We apply this framework to build a recombinase logic device family supporting up to 4-input Boolean logic within a multicellular system. This work enables straightforward implementation of multicellular recombinase logic and will support the predictable engineering of several classes of recombinase devices to reliably control cellular behavior Guiziou et al, Nature Communications, 2019).5) [Month 48] We have designed a workflow to expand the range of molecules detectable by cell-free biosensors capable of functioning in a variety of complex media, including human urine, in which they can be used to detect clinically relevant concentrations of small molecules. This work provides a foundation to engineer modular cell-free biosensors tailored for many applications (Voyvodic et al, Nature Communications, 2019)6) [Month 52] We have generated combinations and permutations of recombination sites, genes, and regulatory elements, for a total of 4 Billion designs supporting the implementation of 2-, 3-and 4-input logic functions. We provide a user-friendly interface, called RECOMBINATOR (Guiziou et al., BiorXiv, 2019.7) [Month 64] We implemented robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on standardized recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular, do not require cell-cell communication channels, and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed automated workflows that researchers can use to streamline program design and optimization. (Zuniga et al., Nature Communications, 2020).8) [Month 76] We have shown that novel, clinically relevant sensing modalities can be introduced into bacterial biosensors in a modular fashion. To do so, we have leveraged our synthetic receptor platform to detect bile salts, a biomarker of liver dysfunction, by repurposing sensing modules from enteropathogenic Vibrio species. We then engineer a colorimetric bacterial biosensor detecting pathological bile salt levels in serum from patients having undergone a liver transplant, providing an output detectable by the naked eye. The EMeRALD technology enables functional exploration of natural sensing modules and rapid engineering of synthetic receptors for diagnostics, environmental monitoring, and control of therapeutic microbes. (Chang et al., Nature Communications, 2021). Two patent applications were deposited. Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far) On a foundational point of view, we will make several breakthrough contributions to synthetic biology:(i) produce a toolbox for the precision control of gene expression. (ii) engineer synthetic receptors for custom ligand detection, with many applications. (iii) Exploring the frontiers of man-made biological computers. Like in the 1950’s with electronic computers, the future enabled by living biocomputers is still to be imagined. On an applied point of view, my project is one of the first attempts, to our knowledge, to integratesynthetic biology tools and concepts into a cellular chassis performing multiplexed biomarkersanalysis in a clinically relevant context. Because robust and affordable diagnostics technologieshave important implications for mortality reduction and improvements in quality of life, we anticipatethat in the long-term our project, if successful, will have a high-impact on healthcare. Importantly, the engineering principlesapplied (like standardization or modularity) will support re-use of the biosensing platform todiagnose other pathologies as well as for applications requiring custom-detection and biomolecularcomputation, for example targeted therapy, drug delivery, or environmental monitoring. untitled-2.jpg
