Abstract

SAM (S-adenosylmethionine) is an important metabolite that operates as a major donor of methyl groups and is a controller of various physiological processes. Its availability is also believed to be a major bottleneck in the biological production of numerous high-value metabolites. Here, we constructed SAM-sensing systems using MetJ, an SAM-dependent transcriptional regulator, as a core component. SAM is a corepressor of MetJ, which suppresses the MetJ promoter with an increasing cellular concentration of SAM (SAM-OFF sensor). The application of transcriptional interference and evolutionary tuning effectively inverted its response, yielding a SAM-ON sensor (signal increases with increasing SAM concentration). By linking two genes encoding fluorescent protein reporters in such a way that their transcription events interfere with each other's and by placing one of them under the control of MetJ, we could increase the effective signal-to-noise ratio of the SAM sensor while decreasing the batch-to-batch deviation in signal output, likely by canceling out the growth-associated fluctuation in translational resources. By taking the ratio of SAM-ON/SAM-OFF signals and by resetting the default pool size of SAM, we could rapidly identify SAM synthetase (MetK) mutants with increased cellular activity from a random library. The strategy described herein should be widely applicable for identifying activity mutants, which would be otherwise overlooked because of the strong homeostasis of metabolic networks.

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