Fine-tuning citrate synthase flux potentiates and refines metabolic innovation in the Lenski evolution experiment.

Erik M Quandt, Jimmy Gollihar, Zachary D Blount, Andrew D Ellington, George Georgiou, Jeffrey E Barrick

Journal: eLife 2016;4():e09696

PMID: 26465114

Abstract

Evolutionary innovations that enable organisms to colonize new ecological niches are rare compared to gradual evolutionary changes in existing traits. We discovered that key mutations in the gltA gene, which encodes citrate synthase (CS), occurred both before and after Escherichia coli gained the ability to grow aerobically on citrate (Cit(+) phenotype) during the Lenski long-term evolution experiment. The first gltA mutation, which increases CS activity by disrupting NADH-inhibition of this enzyme, is beneficial for growth on the acetate and contributed to preserving the rudimentary Cit(+) trait from extinction when it first evolved. However, after Cit(+) was refined by further mutations, this potentiating gltA mutation became deleterious to fitness. A second wave of beneficial gltA mutations then evolved that reduced CS activity to below the ancestral level. Thus, dynamic reorganization of central metabolism made colonizing this new nutrient niche contingent on both co-opting and overcoming a history of prior adaptation.

Address: Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, United States.; BEACON Center for the Study of Evolution in Action, Michigan State University, East Lansing, United States.; Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, United States.; Department of Molecular Biosciences, The University of Texas at Austin, Austin, United States.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, United States.; Department of Chemical Engineering, The University of Texas at Austin, Austin, United States.; Department of Biomedical Engineering, The University of Texas at Austin, Austin, United States.; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, United States.
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