Farré Gemma, Twyman Richard M, Christou Paul, Capell Teresa, Zhu Changfu
Metabolic Biology Department, John Innes Centre, Norwich, UK.
TRM Ltd, York, UK.
Curr Opin Biotechnol. 2015 Apr;32:54-60. doi: 10.1016/j.copbio.2014.11.004. Epub 2014 Nov 25.
Plant metabolic pathways are complex and often feature multiple levels of regulation. Until recently, metabolic engineering in plants relied on the laborious testing of ad hoc modifications to achieve desirable changes in the metabolic profile. However, technological advances in data mining, modeling, multigene engineering and genome editing are now taking away much of the guesswork by allowing the impact of modifications to be predicted more accurately. In this review we discuss recent developments in knowledge-based metabolic engineering strategies, that is the gathering and mining of genomic, transcriptomic, proteomic and metabolomic data to generate models of metabolic pathways that help to define and refine optimal intervention strategies.
植物代谢途径复杂，常常具有多层次的调控。直到最近，植物代谢工程还依赖于对临时修饰进行费力的测试，以实现代谢谱中理想的变化。然而，数据挖掘、建模、多基因工程和基因组编辑等技术进步，现在通过更准确地预测修饰的影响，减少了许多猜测工作。在本综述中，我们讨论了基于知识的代谢工程策略的最新进展，即收集和挖掘基因组、转录组、蛋白质组和代谢组数据，以生成代谢途径模型，帮助定义和完善最佳干预策略。
