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Evolutionary Engineering for Industrial Microbiology

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Reprogramming Microbial Metabolic Pathways

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

Abstract

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.

The authors Niti Vanee and Adam B. Fisher are contributed equally.

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Abbreviations

ADAM:

array-based discovery of adaptive mutations

CO:

cellular objectives

EMS:

ethyl methane sulfonate

EO:

engineering objectives

EvoEng:

evolutionary engineering

MAGE:

multiplex automated genome engineering

NTG:

nitroso-methyl guanidine

Oligo(s):

oligonucleotide(s)

RNAseq:

RNA sequencing

SELEX:

selectable evolution of ligands by exponential enrichment

SS:

solution space

StEP:

staggered extension process

TRMR:

trackable multiplex recombineering

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  1. Department of Chemical and Life Science Engineering, Virginia Commonwealth University, 601 W. Main Street, Room 422, 843028, Richmond, VA, 23284-3028, USA

    Niti Vanee, Adam B. Fisher & Stephen S. Fong

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  1. Niti Vanee
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  2. Adam B. Fisher
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Correspondence to Stephen S. Fong .

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  1. , State Key Laboratory, Jiangnan University, Lihu Avenue 1800, Wuxi, 214122, Jiangsu, China, People's Republic

    Xiaoyuan Wang

  2. School of Biotechnology, Jiangnan University, Lihu Avenue 1800, Wuxi, 214122, China, People's Republic

    Jian Chen

  3. , Div. of Life Sciences, King's College London, Stamford Street 150, London, SE1 9NH, United Kingdom

    Peter Quinn

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Vanee, N., Fisher, A.B., Fong, S.S. (2012). Evolutionary Engineering for Industrial Microbiology. In: Wang, X., Chen, J., Quinn, P. (eds) Reprogramming Microbial Metabolic Pathways. Subcellular Biochemistry, vol 64. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5055-5_3

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