Sysdiag:Research

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Current revision (06:27, 7 January 2013) (view source)
 
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which are not commonly detected in combination in existing diagnostics tests. Finally, because
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
of the self-replication of biological systems, a cellular diagnostics system would have reduced
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production costs compatible with systematic screening and widespread deployment.
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production costs compatible with systematic screening and widespread deployment. 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. These constructions can also be obtained using molecular networks based on biological entities like proteins and metabolites, as compounds and signals allowing to perform Boolean logic operations. Our project also focuses on the the development of concepts and methods for the engineering of synthetic molecular networks and detection systems. This work implies several steps: establishing a methodology for the assembly of abstract biological processes (modeling), molecular implementation of such systems (bioinformatics), experimental building (biotechnology, imaging, proteomics, bacteriology, liposomes, droplets) analytical validation (biochemistry and biostatistics), and finally clinical validation (bioassays and statistics). This project also focuses on the development of biological components used in our synthetic biological systems and compatible with the clinical context: we will address the issue of choosing the system of interest (microbiological, vesicles or droplets), and the identification of logic biological elements, fine tuning of the response and information storage in the context of designing a conditional biosensor. This project falls within the context of a clinical application in medical diagnosis of complex disease.
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[[Category:Lab]]
[[Category:Lab]]

Current revision

Home        Contact        Internal        Lab Members        Publications        Research        Talks       


The Sysdiag laboratory was created in 2007 and applies synthetic biology to engineer next-generation medical diagnostics tools. Sysdiag is a joint-institute between the biotech company Bio-Rad (Hercules, USA), and the French Centre National de la Recherche Scientifique (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 biological systems to medical diagnostics
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. 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. These constructions can also be obtained using molecular networks based on biological entities like proteins and metabolites, as compounds and signals allowing to perform Boolean logic operations. Our project also focuses on the the development of concepts and methods for the engineering of synthetic molecular networks and detection systems. This work implies several steps: establishing a methodology for the assembly of abstract biological processes (modeling), molecular implementation of such systems (bioinformatics), experimental building (biotechnology, imaging, proteomics, bacteriology, liposomes, droplets) analytical validation (biochemistry and biostatistics), and finally clinical validation (bioassays and statistics). This project also focuses on the development of biological components used in our synthetic biological systems and compatible with the clinical context: we will address the issue of choosing the system of interest (microbiological, vesicles or droplets), and the identification of logic biological elements, fine tuning of the response and information storage in the context of designing a conditional biosensor. This project falls within the context of a clinical application in medical diagnosis of complex disease.

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