Architecture and operational principle of protosensors for medical diagnosis Architecture and operational principle of protosensors for medical diagnosis.

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Architecture and operational principle of protosensors for medical diagnosis Architecture and operational principle of protosensors for medical diagnosis Arising from a clinical need to detect pathologies associated with specific patterns of biomarkers in clinical samples, medical diagnosis can be abstracted to a computational process formalized using Boolean logic in vitro and programmed into synthetic biochemical circuits. These de novo circuits can be programmed and optimized in silico, assembled from naturally occurring building blocks, and insulated in synthetic containers in vitro to yield diagnostic devices, or protosensors. Protosensors are capable of detecting patterns of specific biomarkers in human clinical samples and integrate these signals in a medical decision algorithm. If a pathological pattern of biomarker is detected, protosensors generate specific colorimetric outputs. Different types of protosensors corresponding to different clinical questions can be used at the same time to enable multiplexed detection of pathological biomarkers, subsequent logic processing, and achieve differential diagnosis of pathologies in clinical samples.Proof‐of‐concept diagnostic algorithm used in this study and programmed into protosensors circuitry to achieve differential diagnosis of diabetes acute complications and screening for diabetes. Diabetes‐associated acute complications, namely diabetic ketoacidosis, hyperglycemia hyperosmolar state, hypoglycemia, and lactic acidosis, are clinical emergencies that represent a major healthcare burden associated with severe mortality, morbidity, and frequent complications. Here, we propose a diagnostic algorithm enabling differential diagnosis of these complications, as well as a proof‐of‐concept screening assay, from markers present in urines.Logical abstraction and in silico‐automated implementation of synthetic biochemical circuits for medical diagnosis. Top: formal Boolean description depicted using basic logic gates symbols, and theoretical truth tables for three models recapitulating the medical algorithm, bottom: biochemical circuit solutions found after automated in silico search for implementation. SBML models of the synthetic circuits can be found in Appendix. Alexis Courbet et al. Mol Syst Biol 2018;14:e7845 © as stated in the article, figure or figure legend