首页|New Machine Learning Study Findings Have Been Reported by Investigators at Chinese Academy of Sciences (Pathway Evolution Through a Bottlenecking-debottlenecking Strategy and Machine Learning-aided Flux Balancing)
New Machine Learning Study Findings Have Been Reported by Investigators at Chinese Academy of Sciences (Pathway Evolution Through a Bottlenecking-debottlenecking Strategy and Machine Learning-aided Flux Balancing)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Machine Learning. According to news originating from Shenzhen, People's Republic of China, by NewsRx correspondents, research stated, "The evolution of pathway enzymes enhances the biosynthesis of high-value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution." Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China. Our news journalists obtained a quote from the research from the Chinese Academy of Sciences, "Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry-assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L-1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries. A biofoundry-assisted strategy for pathway bottlenecking and debottlenecking enables the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory. A machine learning model can further relax the epistasis of the evolved pathway by optimizing the corresponding promoter combinations."
ShenzhenPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesEnzymes and CoenzymesGeneticsMachine LearningChinese Academy of Sciences
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