Robert Armon,
Technion-Israel Institute of Technology, Israel
Title: Macromolecular fi ngerprinting in sol-gel materials for rapid bacterial recognition in water samples via QCM detection
Biography
Biography: Robert Armon,
Abstract
Currently, the importance of early detection for microbial contamination of water samples is substantial in areas like food production, water supply or recreational water. Well established chemical and biological detection methods are highly suitable for this task and yield the desired detection limits, but their main drawback is analysis time interval being time consuming for a rapid real-time detection. Th is attribute was the basis for the idea of using molecularly imprinted sol-gel based QCM biosensor for rapid and selective bacterial recognition in liquid samples. Molecularly imprinted sol-gel derived thin fi lms with diff erent pathogenic microbial cells previously showed to be an easy and selective method for specifi c bacterial recognition from liquid. An important feature in the imprinting process is molecular fi ngerprints left by microorganisms alongside morphology, into imprinted fi lm cavities that are complementary to the template molecule in size, shape and chemical functionality. In the present study, a method for rapid and selective bacterial recognition was developed as a quartz crystal microbalance (QCM) based biosensor. QCM probes were coated with sol-gel derived thin fi lms and modifi ed with a surface-imprinting process using diff erent bacteria (including pathogens) such as: Staphylococcus aureus, Deinococcus radiodurans, E. coli CN13, Pseudomonas aeruginosa and Flavobacterium breve. Preliminary results show that imprinted fi lms on sensor surface showed high selectivity and sensitivity towards the experimental template bacteria (S. aureus) along the adsorption process from water. Th e sensitivity of present QCM imprinted probes is ~102 CFU/ml, allowing this method to be a promising technique for selective detection and quantifi cation of bacteria present in liquids in real time intervals.