Vanee Niti, Fisher Adam B, Fong Stephen S
Department of Chemical and Life Science Engineering, Virginia Commonwealth University, 601 W. Main Street, Room 422, 843028, Richmond, VA, 23284-3028, USA.
Subcell Biochem. 2012;64:43-71. doi: 10.1007/978-94-007-5055-5_3.
Superficially, evolutionary engineering is a paradoxical field that balances competing interests. In natural settings, evolution iteratively selects and enriches subpopulations that are best adapted to a particular ecological niche using random processes such as genetic mutation. In engineering desired approaches utilize rational prospective design to address targeted problems. When considering details of evolutionary and engineering processes, more commonality can be found. Engineering relies on detailed knowledge of the problem parameters and design properties in order to predict design outcomes that would be an optimized solution. When detailed knowledge of a system is lacking, engineers often employ algorithmic search strategies to identify empirical solutions. Evolution epitomizes this iterative optimization by continuously diversifying design options from a parental design, and then selecting the progeny designs that represent satisfactory solutions. In this chapter, the technique of applying the natural principles of evolution to engineer microbes for industrial applications is discussed to highlight the challenges and principles of evolutionary engineering.
从表面上看，进化工程是一个平衡相互竞争利益的矛盾领域。在自然环境中，进化利用诸如基因突变等随机过程，迭代地选择和富集最适应特定生态位的亚群。在工程领域，期望的方法是利用合理的前瞻性设计来解决目标问题。当考虑进化和工程过程的细节时，可以发现更多的共性。工程依赖于对问题参数和设计属性的详细了解，以便预测作为优化解决方案的设计结果。当缺乏对系统的详细了解时，工程师通常采用算法搜索策略来确定经验性解决方案。进化通过不断地从亲本设计中多样化设计选项，然后选择代表满意解决方案的后代设计，体现了这种迭代优化。在本章中，将讨论应用进化自然原理来改造微生物以用于工业应用的技术，以突出进化工程的挑战和原理。
