Metabolite biosensors for cell factory development

Sammanfattning: Through synergy with natural sciences and engineering disciplines, biotechnology has become a broad, interdisciplinary, scientific field with many applications. One such application is the sustainable production of industrially relevant products using living systems such as microorganisms. Transforming microorganisms to cell factories is, however, a labour-intensive and cost-ineffective process, requiring many years of extensive research. Several fields together known as systems metabolic engineering, including synthetic biology, have greatly facilitated the process of customizing microorganisms to benefit human interests. Among several emerging tools are metabolite biosensors, which can be employed in high-throughput screening endeavours for identifying productive cells and in dynamic pathway regulation for optimizing metabolic systems. Developing and engineering metabolite biosensors to fit a certain application is, however, challenging. This thesis focuses on different aspects of utilizing and engineering metabolite-responsive transcription factor-based biosensors for facilitating the development of  Saccharomyces cerevisiae as a cell factory. To that end, we improved the dynamic range of a malonyl-CoA-responsive biosensor by i) evaluating different binding site locations of the bacterial transcription factor FapR within different yeast promoters and by ii) using a chimeric transcription factor based on a native repressor system from S. cerevisiae . Furthermore, we suggest the possibility of using the CRISPR (Clustered Regulatory Interspaced Short Palindromic Repeats)/Cas9 system to facilitate biosensor development by guiding binding site positioning. We also employed an acyl-CoA-responsive biosensor based on the bacterial transcription factor FadR to screen for genes boosting the fatty acyl-CoA levels, which are precursors for industrially relevant compounds such as fatty alcohols. The possibility of developing fatty acid-responsive biosensors based on other transcription factors, including the endogenous transcription factor Mga2, has also been addressed. Finally, we looked into the potential of developing an alkane-responsive biosensor based on a system from Yarrowia lipolytica . Overall, this thesis provides answers, discussions and potential future directions on using and engineering metabolite biosensors for cell factory development.