BackgroundGamma-aminobutylate (GABA) is an important chemical in pharmacetucal field and chemical industry. GABA has mostly been produced in lactic acid bacteria by adding L-glutamate to the culture medium since L-glutamate can be converted into GABA by inherent L-glutamate decarboxylase. Recently, GABA has gained much attention for the application as a major building block for the synthesis of 2-pyrrolidone and biodegradable polyamide nylon 4, which opens its application area in the industrial biotechnology. Therefore, Corynebacterium glutamicum, the major L-glutamate producing microorganism, has been engineered to achieve direct fermentative production of GABA from glucose, but their productivity was rather low.ResultsRecombinant C. glutamicum strains were developed for enhanced production of GABA from glucose by expressing Escherichia coli glutamate decarboxylase (GAD) mutant, which is active in expanded pH range. Synthetic PH36, PI16, and PL26 promoters, which have different promoter strengths in C. glutamicum, were examined for the expression of E. coli GAD mutant. C. glutamicum expressing E. coli GAD mutant under the strong PH36 promoter could produce GABA to the concentration of 5.89 ± 0.35 g/L in GP1 medium at pH 7.0, which is 17-fold higher than that obtained by C. glutamicum expressing wild-type E. coli GAD in the same condition (0.34 ± 0.26 g/L). Fed-bath culture of C. glutamicum expressing E. coli GAD mutant in GP1 medium containing 50 μg/L of biotin at pH 6, culture condition of which was optimized in flask cultures, resulted in the highest GABA concentration of 38.6 ± 0.85 g/L with the productivity of 0.536 g/L/h.ConclusionRecombinant C. glutamicum strains developed in this study should be useful for the direct fermentative production of GABA from glucose, which allows us to achieve enhanced production of GABA suitable for its application area in the industrial biotechnology.

Microbial strains are considered promising hosts for production of flavonoids because of their rapid growth rate and suitability for large-scale manufacturing. However, productivity and titer of current recombinant strains still do not meet the requirements of industrial processes. Genetically encoded biosensors have been applied for high-throughput screening or dynamic regulation of biosynthetic pathways for enhancing the performance of microbial strains that produce valuable chemicals. Currently, few protein sensor-regulators for flavonoids exist. Unlike the protein-based trans-regulating controllers, riboswitches can respond to their ligands faster and eliminate off-target effects. Here, we developed artificial riboswitches that activate gene expression in response to naringenin, an important flavonoid. RNA aptamers for naringenin were developed using SELEX and cloned upstream of a dual selectable marker gene to construct a riboswitch library. Two in vivo selection routes were applied separately to the library by supplementing naringenin at two different concentrations during enrichments to modulate the operational ranges of the riboswitches. The selected riboswitches were responsive to naringenin and activated gene expression up to 2.91-fold. Operational ranges of the riboswitches were distinguished on the basis of their selection route. Additionally, the specificity of the riboswitches was assessed, and their applicability as dynamic regulators was confirmed. Collectively, the naringenin riboswitches reported in this work will be valuable tools in metabolic engineering of microorganisms for the production of flavonoids.

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Eukaryotic protein synthesis is an inherently stochastic process. This stochasticity stems not only from variations in cell content between cells but also from thermodynamic fluctuations in a single cell. Ultimately, these inherently stochastic processes manifest as noise in gene expression, where even genetically identical cells in the same environment exhibit variation in their protein abundances. In order to elucidate the underlying sources that contribute to gene expression noise, we quantify the contribution of each step within the process of protein synthesis along the central dogma. We uncouple gene expression at the transcriptional, translational, and post-translational level using custom engineered circuits stably integrated in human cells using CRISPR. We provide a generalized framework to approximate intrinsic and extrinsic noise in a population of cells expressing an unbalanced two-reporter system. Our decomposition shows that the majority of intrinsic fluctuations stem from transcription and that coupling the two genes along the central dogma forces the fluctuations to propagate and accumulate along the same path, resulting in increased observed global correlation between the products.