DSM Biotechnology Center, Alexander Fleminglaan 1, 2600 MA, Delft, The Netherlands.
Appl Microbiol Biotechnol. 2013 Mar;97(6):2319-26. doi: 10.1007/s00253-013-4738-8. Epub 2013 Feb 10.
Systems metabolic engineering is based on systems biology, synthetic biology, and evolutionary engineering and is now also applied in industry. Industrial use of systems metabolic engineering focuses on strain and process optimization. Since ambitious yields, titers, productivities, and low costs are key in an industrial setting, the use of effective and robust methods in systems metabolic engineering is becoming very important. Major improvements in the field of proteomics and metabolomics have been crucial in the development of genome-wide approaches in strain and process development. This is accompanied by a rapid increase in DNA sequencing and synthesis capacity. These developments enable the use of systems metabolic engineering in an industrial setting. Industrial systems metabolic engineering can be defined as the combined use of genome-wide genomics, transcriptomics, proteomics, and metabolomics to modify strains or processes. This approach has become very common since the technology for generating large data sets of all levels of the cellular processes has developed quite fast into robust, reliable, and affordable methods. The main challenge and scope of this mini review is how to translate these large data sets in relevant biological leads which can be tested for strain or process improvements. Experimental setup, heterogeneity of the culture, and sample pretreatment are important issues which are easily underrated. In addition, the process of structuring, filtering, and visualization of data is important, but also, the availability of a genetic toolbox and equipment for medium/high-throughput fermentation is a key success factor. For an efficient bioprocess, all the different components in this process have to work together. Therefore, mutual tuning of these components is an important strategy.
系统代谢工程基于系统生物学、合成生物学和进化工程,现在也应用于工业领域。工业系统代谢工程的应用重点在于菌株和工艺优化。由于在工业环境中,高产量、高浓度、高生产力和低成本是关键,因此在系统代谢工程中使用有效和强大的方法变得非常重要。蛋白质组学和代谢组学领域的重大进展对于在菌株和工艺开发中开发全基因组方法至关重要。这伴随着 DNA 测序和合成能力的快速提高。这些发展使系统代谢工程能够在工业环境中使用。工业系统代谢工程可以定义为综合使用全基因组基因组学、转录组学、蛋白质组学和代谢组学来修饰菌株或工艺。自从用于生成细胞过程各个层面大数据集的技术快速发展成为强大、可靠和经济实惠的方法以来,这种方法已经变得非常普遍。本篇综述的主要挑战和范围是如何将这些大数据集转化为可用于菌株或工艺改进的相关生物学线索。实验设置、培养物的异质性和样品预处理是容易被低估的重要问题。此外,数据的结构、过滤和可视化过程很重要,但遗传工具包和中/高通量发酵设备的可用性也是一个关键的成功因素。对于高效的生物过程,这个过程中的所有不同组件都必须协同工作。因此,这些组件的相互调整是一个重要的策略。