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Engineering microorganisms in order to improve the metabolite flux needs a detailed knowledge of the concentrations and flux rates of metabolites and metabolic intermediates in vivo. Fluorescence resonance energy transfer (FRET) based genetically encoded nanosensors represent a promising tool for measuring the metabolite levels and corresponding rate changes in live cells. Here, we report the development of a series of FRET based genetically encoded nanosensor for real time measurement of lysine at cellular level, as the improvement of microbial strains for the production of L-lysine is of major interest in industrial biotechnology.
Pubmed ID: 27334743 RIS Download
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Web application for prediction of the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks.
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