Stimulus amplifying biohybrid materials for highly sensitive drug and toxin detection

摘要

Introduction: Smart materials have the ability to change one or more properties in response to external stimuli making them highly valuable tools for a variety of diagnostic and biomedical applications. Here, we combine synthetic biological switches with biohybrid materials for constructing highly sensitive analytic signal detector devices. Synthetic biology-derived switches have been used as sensors for the detection of external signals such as light, metabolites or drugs. Hence, they are considered as promising candidates for the development of detectors sensing specific compounds like antibiotics or toxins in biological samples. To enable (ⅰ) simple detection of an input signal and (ⅱ) sensitive response characteristics we designed a signal amplifying hydrogel system. Materials and Methods: Drug-responsive protein switches such as GyrB were recombinantly produced in Escherichia coli, purified by metal affinity chromatography and applied to cross-link nitrilotriacetic acid-functionalized polyacrylamide to a hydrogel. Stimulus-induced hydrogel dissolution was monitored by fluorescence measurements of the fluorescent protein mCherry previously embedded into the hydrogel. Results: The generation of a stimulus amplifying system was realized by synthesizing antibiotic- and/or protease-sensitive protein-polymer hybrid hydrogels. The resulting modules were analyzed individually for their response characteristics and connected in a positive feedback topology for signal amplification and detection of minimal amounts of the analyte. We demonstrate the system's sensitive response characteristics at different input signal concentrations which can be used to detect minimal amounts of drugs or toxins. Conclusion: This work illustrates the applicability of biological building blocks for transferring sensing and responding properties from synthetic biology to hydrogels thereby enabling the construction of highly sensitive signal detection systems.