Design and Engineering of Synthetic Biological Systems for Medical Diagnosis
Francisco Schneider  1, *@  , Alexis Courbet  1@  , Julien Espeut  1@  , Joris Huguenin  1@  , Laurence Molina  1@  , Patrick Amar  2@  , Molina Franck  1@  
1 : Sys2Diag CNRS/Alcediag (UMR9005)  (Sys2Diag)
Centre National de la Recherche Scientifique - CNRS : UMR9005
1682 Rue de la Valsière, Cap Delta -  France
2 : Laboratoire de Recherche en Informatique  (LRI)  -  Website
Université Paris-Sud - Paris 11, Institut National de Recherche en Informatique et en Automatique, Centre National de la Recherche Scientifique : UMR8623, CentraleSupélec
LRI - Bâtiments 650-660 Université Paris-Sud 91405 Orsay Cedex -  France
* : Corresponding author

Bioinformatics and microfluidics provide useful tools for answering complex biological questions. On the one hand, bioinformatics allows us to design, model and simulate biological processes, resulting in the reduction of experimental tests. On the other hand, microfluidics provides miniaturization, automatization and portability, diminishing the required amount of samples and reagents. Together, they provide ways to create non-expensive devices which could be used in personalized medicine and provide new ways to probe, monitor and interface human physiopathology. In this work, we have applied engineering principles to design and build an artificial biological system, clinically compliant, that we have applied to Type 2 Diabetes Mellitus (T2DM) early diagnosis. Using two original softwares, we have constructed a synthetic biochemical network and created algorithms decision rules based on medical needs. To allow automatization and miniaturization of the process we have also conceived and produced microfluidic devices capable of producing highly stable and homogeneous double emulsion vesicles containing our biochemical networks. The diagnosis test-containing liposomes were used in biological samples (i.e. urine) and were capable of detecting T2DM early biomarkers, which could help medical decision. Thus, our methods based on a synthetic biology pipeline take advantage of both bioinformatics and microfluidic approaches, which enable simplified and efficient design of next generation devices for testing of human complex diseases.

 


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