Department of Chemical Engineering, The University of Manchester, UK
Krishna Persaud, PhD, FRSC, FInstMC, graduated with BSc Hons Biochemistry at the University of Newcastle-upon-Tyne, UK in 1976, MSc in Molecular Enzymology at the University of Warwick, UK, in 1977 and a PhD specialising in olfactory biochemistry in 1980. He subsequently worked at the University of Newcastle-upon-Tyne, University of Pisa and the Medical College of Virginia extending his knowledge in the Chemical Senses. He is Professor of Chemoreception at the University of Manchester, Department of Chemical Engineering. In his career, he has carried out research in chemoreception, crossing disciplines from biological aspects of olfaction to sensor arrays, electronics, signal processing and pattern recognition, and commercial development of artificial olfaction technologies. He is a current director of Multisensor Systems Ltd, UK.
The principle of combinatorial selectivity has been the main paradigm for the development of electronic noses. This concept is taken from the biological system where generally individual olfactory receptors are not highly selective for a given odorant thus odorants and responses across large numbers of receptors are encoded in combinatorial patterns whose interpretation leads to the odorant identification. The technological implementation of this principle led to a standard electronic nose model made of a combination of cross-selective sensors matched with a machine- learning algorithm. Until recently these sensors were based on traditional semiconductor gas sensors, mass sensitive transducers or electrochemical sensors. Sensing elements involved in olfaction in natural environments, such as Olfactory Receptors (ORs) or Odorant Binding Proteins (OBPs), are bringing great impetus to the development of electronic noses. Indeed, by contrast with e-noses that traditionally rely on chemical sensors, bio-electronic noses may benefit from the naturally optimized molecular affinities and intrinsic sensitivities of bioreceptors towards odorants. Individual receptors can bind different odorants with distinct affinities and specificities, therefore broadly selective arrays can be designed, and associated with multiparametric data analysis and pattern recognition algorithms. Odorant binding proteins (OBPs) are small water-soluble polypeptides found in the secretory glands and in the sensory organs of insects and vertebrates. While the mechanisms of interaction between OBPs or OBP/ligand complex with olfactory receptors are still not well understood, it has been shown that many OBPs contribute to olfactory perception at various levels. The insect OBP is one of the most promising candidates in bio interface technology due to its high conformational stability and can play a critical role in improving bioelectronic nose performance for the monitoring of volatile organic chemicals (VOCs). Developing artificial biosensor arrays brings several challenges, which include: (i) the selection and expression of wild type bioreceptors eventually combined with biomolecular engineering in order to design mutants that are tuned to reach optimum affinities with target odorants, (ii) the immobilization of the biosensing elements onto chemical transducers’ surfaces while preserving the biological functionality of the probe, (iii) and finally the use of highly sensitive transducers with appropriate sensing interface to stabilize the sensitive layer. Utilizing OBPs, we show how an array of diverse odour sensors can be achieved for targeted applications. We demonstrate that the combinatorial concepts can be applied to these bioelectronic “noses”, and the odorant proteins can be modified by single point mutations of the binding pocket to give affinity to non-native ligands. Hence it is possible to produce systems that can be dedicated to detection of diverse chemicals such as explosives and drugs for security applications, volatile decomposition products for bio-composting applications or pheromone detection for agricultural applications.