Electrically active field-effect transistors (FET) based biosensors are of paramount importance in life science applications, as they offer direct, fast, and highly sensitive label-free detection capabilities of several biomolecules of specific interest. In this work, we report a
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Electrically active field-effect transistors (FET) based biosensors are of paramount importance in life science applications, as they offer direct, fast, and highly sensitive label-free detection capabilities of several biomolecules of specific interest. In this work, we report a detailed investigation on surface functionalization and covalent immobilization of biomarkers using biocompatible ethanolamine and poly(ethylene glycol) derivate coatings, as compared to the conventional approaches using silica monoliths, in order to substantially increase both the sensitivity and molecular selectivity of nanowire-based FET biosensor platforms. Quantitative fluorescence, atomic and Kelvin probe force microscopy allowed detailed investigation of the homogeneity and density of immobilized biomarkers on different biofunctionalized surfaces. Significantly enhanced binding specificity, biomarker density, and target biomolecule capture efficiency were thus achieved for DNA as well as for proteins from pathogens. This optimized functionalization methodology was applied to InP nanowires that due to their low surface recombination rates were used as new active transducers for biosensors. The developed devices provide ultrahigh label-free detection sensitivities ∼1 fM for specific DNA sequences, measured via the net change in device electrical resistance. Similar levels of ultrasensitive detection of ∼6 fM were achieved for a Chagas Disease protein marker (IBMP8-1). The developed InP nanowire biosensor provides thus a qualified tool for detection of the chronic infection stage of this disease, leading to improved diagnosis and control of spread. These methodological developments are expected to substantially enhance the chemical robustness, diagnostic reliability, detection sensitivity, and biomarker selectivity for current and future biosensing devices.
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