Engineering metabolite-responsive transcriptional factors to sense small molecules in eukaryotes: current state and perspectives

Abstract

Nature has evolved exquisite sensing mechanisms to detect cellular and environmental signals surrounding living organisms. These biosensors have been widely used to sense small molecules, detect environmental cues and diagnose disease markers. Metabolic engineers and synthetic biologists have been able to exploit metabolites-responsive transcriptional factors (MRTFs) as basic tools to rewire cell metabolism, reprogram cellular activity as well as boost cell's productivity. This is commonly achieved by integrating sensor-actuator systems with biocatalytic functions and dynamically allocating cellular resources to drive carbon flux toward the target pathway. Up to date, most of identified MRTFs are derived from bacteria. As an endeavor to advance intelligent biomanufacturing in yeast cell factory, we will summarize the opportunities and challenges to transfer the bacteria-derived MRTFs to expand the small-molecule sensing capability in eukaryotic cells. We will discuss the design principles underlying MRTF-based biosensors in eukaryotic cells, including the choice of reliable reporters and the characterization tools to minimize background noise, strategies to tune the sensor dynamic range, sensitivity and specificity, as well as the criteria to engineer activator and repressor-based biosensors. Due to the physical separation of transcription and protein expression in eukaryotes, we argue that nuclear import/export mechanism of MRTFs across the nuclear membrane plays a critical role in regulating the MRTF sensor dynamics. Precisely-controlled MRTF response will allow us to repurpose the vast majority of transcriptional factors as molecular switches to achieve temporal or spatial gene expression in eukaryotes. Uncovering this knowledge will inform us fundamental design principles to deliver robust cell factories and enable the design of reprogrammable and predictable biological systems for intelligent biomanufacturing, smart therapeutics or precision medicine in the foreseeable future.

Unstructured kinetic models to simulate an arabinose switch that decouples cell growth from metabolite production

“…This is only one application in one host organism, whereas this is hypothetically possible in any microbial workhorse genetically tractable enough to knockout the greater TCA cycle in favor of the glyoxylate shunt. Researchers may have the flexibility to use a different inducer/actuator module with strain specific orthogonality, and other synthetic biology-based logic gates, genetically-encoded biosensors [43] , [44] and genetic switches may also be integrated to improve the system robustness and predictability.…”

A roadmap to engineering antiviral natural products synthesis in microbes

“…In addition, protein colocalization allows us to engineer enzyme clusters with minimal substrate dissipation and improved catalytic efficiency [ 23 ]. And genetically-encoded biosensors may empower us to analyze and monitor cellular process with temporal and spatial resolutions [ 24 ]. More importantly, metabolic addiction allows us to link cell growth to an end product that may selectively enrich overproduction subpopulation and improve community-level production performance [ 25 , 26 •• ].…”

Coupling metabolic addiction with negative autoregulation to improve strain stability and pathway yield

“…A large portfolio of engineering work has been dedicated to mitigate lipogenesis or redirect lipid synthesis for heterologous chemical production (Ledesma-Amaro and Nicaud 2016, Markham, Palmer et al 2018), but the heavily engineered strains, even the chromosomally-integrated cell lines, are often difficult to maintain high performance during long-term cultivations (Roth, Moodley et al 2009, Wei, Wang et al 2019. To solve this challenge, we took advantage of the transcriptional activity of metabolite-responsive promoters (Skjoedt, Snoek et al 2016, D'Ambrosio and Jensen 2017, Wan, Marsafari et al 2019, aiming to develop an end-product addiction circuit to rewire cell metabolism in Y. lipolytica. Coupled with CRISPRi-assisted lipogenic negative autoregulation, the end-product (flavonoid) addiction circuit drives gene expression (leucine synthesis) that is advantageous to productive cell or deleterious to cheater cell.…”