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Accelerating Evolutionary Hill Climbs in Parallel Turbidostats

Christopher N. Takahashi, Luis Zaman, Eric Klavins
doi: https://doi.org/10.1101/217273
Christopher N. Takahashi
†School of Computer Science and Engineering, University of Washington, Seattle
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Luis Zaman
‡Center for the Study of Complex Systems, University of Michigan, Ann Arbor
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Eric Klavins
¶Department of Electrical Engineering, University of Washington, Seattle
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Abstract

Evolution has been used to address many engineering problems. Within the context of metabolic engineering and synthetic biology, directed evolution has natural appli-cations. However, most research concerning optimizing microbial evolution has been focused on library generation and screening, while accelerating evolutionary hill climbs and been largely ignored. Here, we develop a model to explore how population struc-ture can accelerate evolutionary hill climbs. We show that by adjusting the population size, environmental challenge, and meta-population dynamics that the rate of evolution can be accelerated in parallel turbidostats. Our analyses leads to two surprising results: small populations are favored over conventionally large microbial populations, and propagating modest fitness improvements is favored over propagating mutants with large beneficial mutations. When combined with rational design and other optimization techniques our theory can accelerate strain development for applications such as consolidated bioprocessing, and bioremidation systems.

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Posted November 10, 2017.
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Accelerating Evolutionary Hill Climbs in Parallel Turbidostats
Christopher N. Takahashi, Luis Zaman, Eric Klavins
bioRxiv 217273; doi: https://doi.org/10.1101/217273
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Accelerating Evolutionary Hill Climbs in Parallel Turbidostats
Christopher N. Takahashi, Luis Zaman, Eric Klavins
bioRxiv 217273; doi: https://doi.org/10.1101/217273

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