Optimizing complex phenotypes through model-guided multiplex genome engineering

Optimizing complex phenotypes through model-guided multiplex genome engineering

Abstract We present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli...

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Bibliographic Details
Main Authors: Gleb Kuznetsov, Daniel B. Goodman, Gabriel T. Filsinger, Matthieu Landon, Nadin Rohland, John Aach, Marc J. Lajoie, George M. Church
Format: Article
Language:English
Published: BMC 2017-05-01
Series:Genome Biology
Subjects:
Genome engineering
Predictive modeling
Synthetic organisms
Online Access:http://link.springer.com/article/10.1186/s13059-017-1217-z

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http://link.springer.com/article/10.1186/s13059-017-1217-z

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