Using metabolite-responsive gene regulators to improve microbial biosynthesis

Abstract

In microorganisms, ligand-induced gene regulators (proteins and nucleic acids) orchestrate complex changes in gene expression in response to changes in the cellular environment and metabolic status. This review highlights two increasingly popular applications of these types of regulation systems as genetically-encoded biosensors. As molecular reporters, transcription factors and riboswitches are being used to search gene libraries for enhanced production (or in some cases depletion) of the corresponding ligand. Similar genetic constructions allow for growth-coupled product formation and continuous evolution of strain productivity. Meanwhile, whereas gene expression systems for metabolic engineering have traditionally been static or externally tunable, an expanding toolbox of metabolite-responsive gene regulators coupled with deeper insights into metabolic bottlenecks have given rise to dynamic control over engineered pathways. These synthetic "sensing" gene circuits balance metabolite flux and enhance strain productivity. Such innovative applications of metabolite biosensors present new directions in metabolic engineering.

Characterisation of a 3-hydroxypropionic acid-inducible system from Pseudomonas putida for orthogonal gene expression control in Escherichia coli and Cupriavidus necator

“…Both the native and synthetic systems, in combination with a reporter gene, have been used to screen for metabolically engineered microbial strains enabling selection for microorganisms with improved production of target compounds 35 – 38 . They have also been applied as metabolite-responsive gene switches and dynamic regulators of metabolic pathways, in which levels of upstream or downstream gene expression are continuously adjusted to balance metabolic intermediate levels increasing the flux towards the product of interest 37 , 39 .…”

Fine‐tuning the (2S)‐naringenin synthetic pathway using an iterative high‐throughput balancing strategy

“…Perhaps the greatest challenge in preforming IHTB is establishing a universally used high‐throughput screening procedure. Inspired by previous biosensor studies (Liu et al, ; Qian & Cirino, ; Wang, Tang, & Yang, ; Xiong et al, ), combining the advantages of transcriptomic and biosensor technology will allow many inducible promoters to be screened and novel biosensors constructed that respond to different concentrations of target chemicals for the high‐throughput screening of high‐titer strains.…”

Dynamic control of endogenous metabolism with combinatorial logic circuits

“…Dynamic gene expression has begun to be implemented in academic metabolic engineering projects (Liu et al , ; Qian & Cirino, ; Min et al , ; Liu & Zhang, ; Zhou et al , ). These projects depend on genetically encoded sensors that respond to external environmental signals (O 2 , temperature, pH), the internal cell state (metabolites, growth phase, stress response, redox), the depletion of carbon feedstock (glucose), cell density, or the accumulation of products and by‐products (acetate) (Farmer & Liao, ; Bayly et al , ; March & Bentley, ; Boccazzi et al , ; Nevoigt et al , ; Kang et al , ; Tsao et al , ; Liang et al , ; Michener et al , ; Zhang et al , ; Anesiadis et al , ; Siedler et al , ; Afroz et al , ; Liu & Lu, ; Soma & Hanai, ; Xie et al , ; Guan et al , ; Immethun et al , ; Lo et al , ; Qian & Cirino, ; Rajkumar et al , ; preprint: Borkowski et al , ; Bothfeld et al , ; Gupta et al , ; He et al , ; Juarez et al , ; Klamt et al , ; Pham et al , ; Kasey et al , ). The information transmitted by these sensors can be used to implement feedback control or switch the carbon flux through alternative pathways at the opportune time (Xu et al , ; Brockman & Prather, ; Liu et al , ; Ceroni et al , ).…”