title: Detection of pathological biomarkers in human clinical samples via amplifying genetic switches and logic gates.
abstract: Whole-cell biosensors have several advantages for the detection of biological substances and have proven to be useful analytical tools. However, several hurdles have limited whole-cell biosensor application in the clinic, primarily their unreliable operation in complex media and low signal-to-noise ratio. We report that bacterial biosensors with genetically encoded digital amplifying genetic switches can detect clinically relevant biomarkers in human urine and serum. These bactosensors perform signal digitization and amplification, multiplexed signal processing with the use of Boolean logic gates, and data storage. In addition, we provide a framework with which to quantify whole-cell biosensor robustness in clinical samples together with a method for easily reprogramming the sensor module for distinct medical detection agendas. Last, we demonstrate that bactosensors can be used to detect pathological glycosuria in urine from diabetic patients. These next-generation whole-cell biosensors with improved computing and amplification capacity could meet clinical requirements and should enable new approaches for medical diagnosis.
authors.affiliation: Sys2Diag FRE3690-CNRS/ALCEDIAG, Cap Delta, 34090 Montpellier, France.
authors.forename: Alexis
authors.initials: A
authors.lastname: Courbet
authors.affiliation: Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
authors.forename: Drew
authors.initials: D
authors.lastname: Endy
authors.affiliation: Sys2Diag FRE3690-CNRS/ALCEDIAG, Cap Delta, 34090 Montpellier, France. Department of Bioengineering, Stanford University, Stanford, CA 94305, USA. Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital; INSERM 1411 Clinical Investigation Center; Institute of Functional Genomics, CNRS UMR 5203, INSERM U661, University of Montpellier, 34090 Montpellier, France. Centre de Biochimie Structurale, INSERM U1054, CNRS UMR5048, University of Montpellier, 29 Rue de Navacelles, 34090 Montpellier, France.
authors.forename: Eric
authors.initials: E
authors.lastname: Renard
authors.affiliation: Sys2Diag FRE3690-CNRS/ALCEDIAG, Cap Delta, 34090 Montpellier, France. jerome.bonnet@inserm.fr franck.molina@sys2diag.cnrs.fr.
authors.forename: Franck
authors.initials: F
authors.lastname: Molina
authors.affiliation: Sys2Diag FRE3690-CNRS/ALCEDIAG, Cap Delta, 34090 Montpellier, France. Department of Bioengineering, Stanford University, Stanford, CA 94305, USA. Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital; INSERM 1411 Clinical Investigation Center; Institute of Functional Genomics, CNRS UMR 5203, INSERM U661, University of Montpellier, 34090 Montpellier, France. Centre de Biochimie Structurale, INSERM U1054, CNRS UMR5048, University of Montpellier, 29 Rue de Navacelles, 34090 Montpellier, France. jerome.bonnet@inserm.fr franck.molina@sys2diag.cnrs.fr.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Bonnet
mesh_terms: D001419:Bacteria / Q000378:metabolism; D015415:Biomarkers / Q000097:blood*; D015374:Biosensing Techniques / Q000379:methods*; D001786:Blood Glucose / Q000032:analysis; D003920:Diabetes Mellitus / Q000097:blood; D005786:Gene Expression Regulation; D006029:Glycosuria / Q000097:blood / Q000150:complications; D006801:Humans; D008128:Logic; D012815:Signal Processing, Computer-Assisted
chemical_list: D015415:Biomarkers; D001786:Blood Glucose