Development of Synthetic Metabolic and Genetic Networks for the Detection of Urogenital Cancers

The assumption is that researchers can engineer synthetic metabolic and genetic networks to expand the panel of molecules that are currently known to be detected by natural systems. The investigators also hypothesize synthetic metabolic and genetic networks can be tuned for decisions making and in particular to diagnose diseases from biomarkers detections.

This project proposes for the first time a hybrid analogue / digital solution for the multiplexed detection of biomarkers using bacterial and paper-based biosensors. Biosensors can be designed using analog or digital devices. Digital devices in synthetic and natural systems are noise-resistant and useful for decision-making. Analog devices are useful for signal transmission and processing. Here the investigators take advantage of signal transmission and processing via analog transducers and adders, and then decision-making via genetic switches. Such a hybrid analogue / digital approach has not yet been developed for biosensing. Another novelty of the project is to use synthetic metabolic pathways to develop analog devices. The advantage in term of treatment, for example, consists in the fact that the speed of enzymatic reactions in an analog adder far exceeds the speed of gene expression required to create a genetic logic matrix; it becomes even more pronounced when the devices are connected in series. The methodology will be illustrated for the detection of biomarkers of prostate tumors, but it is broad enough to be applicable to other diagnoses. The choice to develop biosensors for prostate disease is of practical relevance since the current screening strategy (based on PSA measurement) can lead to overdiagnosis and cannot differentiate between patients with aggressive tumors and those with an indolent illness.This study propose to mainly develop a bacterial and paper-based biosensor system