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• W2936789044 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." @default.
• W2936789044 created "2019-04-25" @default.
• W2936789044 creator A5023377991 @default.
• W2936789044 creator A5050588220 @default.
• W2936789044 creator A5068442955 @default.
• W2936789044 date "2019-03-26" @default.
• W2936789044 modified "2023-10-14" @default.
• W2936789044 title "Engineering metabolite-responsive transcriptional factors to sense small molecules in eukaryotes: current state and perspectives" @default.
• W2936789044 cites W1540714253 @default.
• W2936789044 cites W1606047558 @default.
• W2936789044 cites W1856836325 @default.
• W2936789044 cites W1928744202 @default.
• W2936789044 cites W1953614311 @default.
• W2936789044 cites W1970877840 @default.
• W2936789044 cites W1971961101 @default.
• W2936789044 cites W1974263946 @default.
• W2936789044 cites W1978134451 @default.
• W2936789044 cites W1982492875 @default.
• W2936789044 cites W1984924041 @default.
• W2936789044 cites W2001781591 @default.
• W2936789044 cites W2005275397 @default.
• W2936789044 cites W2006257929 @default.
• W2936789044 cites W2008276633 @default.
• W2936789044 cites W2009204231 @default.
• W2936789044 cites W2027556857 @default.
• W2936789044 cites W2037135781 @default.
• W2936789044 cites W2037312364 @default.
• W2936789044 cites W2037630877 @default.
• W2936789044 cites W2041618640 @default.
• W2936789044 cites W2047331819 @default.
• W2936789044 cites W2051223300 @default.
• W2936789044 cites W2055501372 @default.
• W2936789044 cites W2065868407 @default.
• W2936789044 cites W2073265884 @default.
• W2936789044 cites W2075149828 @default.
• W2936789044 cites W2078272501 @default.
• W2936789044 cites W2087576311 @default.
• W2936789044 cites W2096423191 @default.
• W2936789044 cites W2101749257 @default.
• W2936789044 cites W2102585686 @default.
• W2936789044 cites W2114151755 @default.
• W2936789044 cites W2114154858 @default.
• W2936789044 cites W2120831623 @default.
• W2936789044 cites W2126916325 @default.
• W2936789044 cites W2128062051 @default.
• W2936789044 cites W2128262259 @default.
• W2936789044 cites W2134771103 @default.
• W2936789044 cites W2160998060 @default.
• W2936789044 cites W2161782059 @default.
• W2936789044 cites W2162642438 @default.
• W2936789044 cites W2208196644 @default.
• W2936789044 cites W2209464357 @default.
• W2936789044 cites W2228099278 @default.
• W2936789044 cites W2274155767 @default.
• W2936789044 cites W2297132887 @default.
• W2936789044 cites W2322336584 @default.
• W2936789044 cites W2325427926 @default.
• W2936789044 cites W2471393621 @default.
• W2936789044 cites W2522890841 @default.
• W2936789044 cites W2539204259 @default.
• W2936789044 cites W2554448368 @default.
• W2936789044 cites W2562243586 @default.
• W2936789044 cites W2619310901 @default.
• W2936789044 cites W2619839312 @default.
• W2936789044 cites W2724339814 @default.
• W2936789044 cites W2741075794 @default.
• W2936789044 cites W2747583138 @default.
• W2936789044 cites W2754946718 @default.
• W2936789044 cites W2757181707 @default.
• W2936789044 cites W2765868087 @default.
• W2936789044 cites W2768547619 @default.
• W2936789044 cites W2769457226 @default.
• W2936789044 cites W2790456375 @default.
• W2936789044 cites W2797780355 @default.
• W2936789044 cites W2800233075 @default.
• W2936789044 cites W2800650489 @default.
• W2936789044 cites W2883828272 @default.
• W2936789044 cites W2900498998 @default.
• W2936789044 cites W2902540448 @default.
• W2936789044 cites W2903216094 @default.
• W2936789044 cites W2912224528 @default.
• W2936789044 cites W796291325 @default.
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• W2936789044 doi "https://doi.org/10.1186/s12934-019-1111-3" @default.
• W2936789044 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6434827" @default.
• W2936789044 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30914048" @default.
• W2936789044 hasPublicationYear "2019" @default.
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