Chapter 9 Applications of Biosensors for Metabolic Engineering of Microorganisms and Its Impact on Biofuel Production Amirhossein Nazhand Abstract Quantifying and regulating the metabolic pathways are among the main parameters to optimize the microbial production processes. Much attention has now been drawn to metabolic engineering related to its different ability to optimize the biosynthetic pathway of microorganisms to produce valuable molecules in various industries, e.g. biofuels, pharmaceuticals, and nutraceuticals. The purpose of this review article was to evaluate the characteristics and applications of biosensors in biofuel production. Keywords Biosensors · Biofuels · Metabolic engineering · Synthetic biology · Förster resonance energy transfer (FRET)-based biosensors · Riboswitches · Transcription factor-based biosensors 9.1 Introduction Metabolic engineering has experienced extensive advances in biofuels, pharmaceu- ticals, and nutraceuticals (Alper 2019; Alper and Wittmann 2019; Bathe and Tissier 2019; Lu et al. 2019; Nazhand et al. 2019; Nielsen 2019; Presnell and Alper 2019; Wang et al. 2019; Yuan and Alper 2019; Nazhand 2020; Santini and Novellino 2014). However, the above mentioned compounds are inadequately produced by microorganisms (Yu et al. 2019b), prompting the research for new strategies, including the use of biosensors, to optimize the biosynthetic pathway of microor- ganisms at the commercial scale (Mahr and Frunzke 2016; Mehrotra 2016; Morgan et al. 2016; Vilela et al. 2019). Some of these techniques include developing a dynamic regulation network for biosynthesis (Hoynes-O’Connor and Moon 2015; Lalwani et al. 2018; Xu 2018), as well as screening and monitoring the generation of key intermediates (Li et al. 2019) (Figs. 9.1 and 9.2). Accordingly, the current study A. Nazhand (*) Department of Biotechnology, Sari Agriculture Science and Natural Resource University, Sari, Mazandaran, Iran © Springer Nature Singapore Pte Ltd. 2021 N. Srivastava et al. (eds.), Bioprocessing for Biofuel Production, Clean Energy Production Technologies, https://doi.org/10.1007/978-981-15-7070-4_9 203