Sysdiag:Research

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The Sysdiag laboratory was created in 2007 and applies synthetic biology principles for the engineering of next-generation medical diagnostics tools. Sysdiag is a joint-institute between the biotech company Bio-Rad (Hercules, USA), and the French National Center for Scientific Research (CNRS). Sysdiag focuses on :

i) identifying new biomarkers of complex diseases(cancer, neurodegenerative diseases, diabetes and its complications) and the related pilot assays.
ii) Engineer innovative diagnostics tools based on biologically-inspired nano-objects.
iii) develop composition frameworks supporting in silico biological networks conception.


Medical diagnostics: a societal and scientific challenge
Longer life expectancy and an increasing number of risk factors lead to a global increase in infectious diseases, cancers, cardiovascular diseases and diabetes. Many of these diseases require an early diagnostics and a systematic screening of populations at risk. To be reliable, medical diagnostics must often be based on a pattern of biomarkers, increasing the complexity and the cost of the test, and therefore limiting its widespread deployment. Thus, the demand for simple, robust, and inexpensive diagnostics systems is constantly increasing. Biological systems offer an attractive alternative to perform inexpensive detection.


Applications of synthetic biological systems to medical diagnostics
Biosensors comprise a biologically derived sensing element associated with transducing, processing and actuating elements that triggers a signal induced reaction of the system with the production of an output signal reflecting the concentration of one or more chosen biomarkers. Biological systems and their components can be compared to nano-machines operating independently, analyzing their internal state and their environment and computing an appropriate phenotypic response. The natural repertoire from which to retrieve useful biological functions is immense. Importantly, biological systems are able to integrate various kinds of clinically relevant physical and chemical signals (ligands, osmolarity, pH, temperature) which are not commonly detected in combination in existing diagnostics tests. Finally, because of the self-replication of biological systems, a cellular diagnostics system would have reduced production costs compatible with systematic screening and widespread deployment. For this reasons, the systematic engineering of biological systems is of particular interest for the generation of next-generation biosensors capable of complex signal processing. Our project also focuses on the the development of concepts and methods for the engineering of synthetic molecular computing networks and detection systems from a bottom-up approach. Molecular networks based on biological entities like proteins, nucleic acids and metabolites can be used as biosensing devices, perform computation processes, and generate sophisticated outputs. This work implies several steps: establishing a methodology for the assembly of abstract biological processes, development of bioinformatics and microfluidic tools for silico and in vitro molecular implementation, experimental construction and analytical validation, and finally clinical validation. We also focus on the engineering and standardization of robust synthetic biological components, systems and devices capable of operating in clinical contexts or harsh environnements.

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