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Autonomous Cellular Computers for Diagnosis

Periodic Reporting for period 3 - COMPUCELL (Autonomous Cellular Computers for Diagnosis)

Reporting period: 2018-05-01 to 2019-10-31

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,we will apply tools from synthetic biology, the rational engineering of biological systems, to build cell-based biosensors for multiplexed diagnosis using the non-pathogenic bacteria.

In a first research line,we aim to conceive chimeric receptors detecting extracellular biomarkers via sensing domains derived from antibodies. In a second research line, our goal is to engineer bio-molecular computing systems operating in living cells to perform multiplexed biomarkers analysis.

Our project is highly interdisciplinary and is at the cross-roads of genetic engineering, structural biology, biophysics, modeling, and clinics. On foundational point of view, we will make several breakthrough contributions to synthetic biology: (i) Advancing engineering frameworks for microorganisms based synthetic biology approaches (ii) Pushing the limits of custom ligand detection by engineered cells (iii) Exploring the frontiers of man-made biological computers. 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 biomolecular
computation like targeted therapy, drug delivery, or environmental monitoring.
In the first period of the project, we have made major progresses:

1) [Month 12] We produced collections of biological parts for the precise control of transcription, translation, RNA and protein stability in the non-pathogenic bacteria B. subtilis. Our complete promoters and RBS sequences library comprising over 135 constructs enables tuning of GFP concentration over five orders of magnitude, from 0.05 to 700 μM. This work was published this year in Nucleic acids Research (Guiziou et al, 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, 2017.

3) [Month 28] We have engineered a first set of programmable transmembrane receptors using a synthetic binder as sensing domain (Chang et al., 2017). These receptors open the road to novel sensing modalities, in particular towards the detection of ligand for which no receptor is found in nature. We are now pushing this research line to better understand the design principles of synthetic receptors and incorporate new ligand sensing domains targeting biomarkers of disease.
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 in the Gram-positive model, B.
subtilis, currently under-explored in synthetic biology, despite being a workhorse of industrial
biotechnology. (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 integrate
synthetic biology tools and concepts into a cellular chassis performing multiplexed biomarkers
analysis in a clinically relevant context. Because robust and affordable diagnostics technologies
have important implications for mortality reduction and improvements in quality of life, we anticipate
that in the long-term our project, if successful, will have a high-impact on healthcare. Importantly, the engineering principles
applied (like standardization or modularity) will support re-use of the biosensing platform to
diagnose other pathologies as well as for applications requiring custom-detection and biomolecular
computation, for example targeted therapy, drug delivery, or environmental monitoring.