Strategies to Improve the Performance of Microbial Biosensors: Artificial Intelligence, Genetic Engineering, Nanotechnology and Synthetic Biology

Abstract

A microbial biosensor is an analytical device that integrates microorganisms with a physical transducer to generate a measurable signal proportional to the concentration of target analytes. In this chapter we will focus in some new strategies that are currently used to improve the performance of microbial biosensors. Among the topics we will discuss are the different immobilization methods, the typically used transducers (electrochemical, optical) as well as some new transduction strategies. We present different set-ups, the simpler of them use just a single microbial species, with a complexity increasing to a blend of some, and reaching a complete and non-defined microbial community used as bioreceptors. By applying genetic engineering methods, tailored microorganisms can be designed to increase the microbial biosensor selectivity, one of the main drawback to be solved. We dedicate a part of this chapter to show some new platforms that are used to integrate and analyze the data obtained from microbial biosensors, as the application of artificial intelligence and empirical models that can be applied, to develop intelligent biosensors able to collaborate with the automatic control of different industrial processes. We briefly present new developments that can find a place in the market, and future trends of microbial biosensors.