Evolutionary Engineering for Industrial Microbiology

Part of the Subcellular Biochemistry book series (SCBI, volume 64)


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.


Cellular objectives Directed evolution Diversity Engineering objectives Evolutionary engineering Fitness landscapes Industrial microbiology Screening and selection 



array-based discovery of adaptive mutations


cellular objectives


ethyl methane sulfonate


engineering objectives


evolutionary engineering


multiplex automated genome engineering


nitroso-methyl guanidine




RNA sequencing


selectable evolution of ligands by exponential enrichment


solution space


staggered extension process


trackable multiplex recombineering


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© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Department of Chemical and Life Science EngineeringVirginia Commonwealth UniversityRichmondUSA

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