Evolvability describes an organism's capacity for producing descendants that are better adapted to a given environment. Mutations that elevate overall point mutation rates can make bacteria more evolvable under certain circumstances and consequently speed the progression of chronic infections and increase the incidence of antibiotic resistance. Little is currently known about how mutations affecting other cellular processes impact microbial evolvability or about how evolvability typically varies as microorganisms experience random mutations due to genetic drift or adapt by beneficial mutations to higher fitness. The proposed research systematically investigates how different kinds of mutations affect the evolvability of Escherichia coli in laboratory evolution experiments.
The first aim i s to test three strain series differing by predominantly deleterious, beneficial, or random mutations to establish baseline expectations.
The second aim i s to recover genotypes that eventually prevail over competitors of higher fitness because they are more evolvable by chronicling mutation dynamics in evolution experiments using deep sequencing, highthroughput genotyping, and deletion and microsatellite markers.
The third aim i s to construct chromosomal reporters with selectable markers for measuring gene amplification and deletion rates. These reporters will be used to isolate new kinds of genomic instability mutators and to examine whether a similar defect potentiated the evolution of a rare metabolic innovation in a 20-year evolution experiment. Throughout, evolvability will be measured on multiple time scales by comparing the initial divergence of marker trajectories in replicate evolution experiments to population genetic simulations and by performing co-culture competition assays between endpoint isolates and a reference strain. When a strain is found with unusually high or low evolvability, the causal mutation will be identified by genome re-sequencing, and its physiological consequences will be investigated to find out why it affects evolutionary potential.

Public Health Relevance

Understanding how different kinds of mutations alter the ability of microorganisms to evolve could help us keep in check disease progression in chronic infections, the evolution of antibiotic resistance, and the emergence of new pathogens. Knowledge of what mutations promote the evolutionary potential of domesticated microbes could lead to improved strains for biotechnology and biomedical research.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Transition Award (R00)
Project #
4R00GM087550-03
Application #
8213191
Study Section
Special Emphasis Panel (NSS)
Program Officer
Eckstrand, Irene A
Project Start
2009-03-01
Project End
2014-01-31
Budget Start
2011-02-01
Budget End
2012-01-31
Support Year
3
Fiscal Year
2011
Total Cost
$249,000
Indirect Cost
Name
University of Texas Austin
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
Deatherage, Daniel E; Kepner, Jamie L; Bennett, Albert F et al. (2017) Specificity of genome evolution in experimental populations of Escherichia coli evolved at different temperatures. Proc Natl Acad Sci U S A 114:E1904-E1912
Suárez, Gabriel A; Renda, Brian A; Dasgupta, Aurko et al. (2017) Reduced Mutation Rate and Increased Transformability of Transposon-Free Acinetobacter baylyi ADP1-ISx. Appl Environ Microbiol 83:
Tenaillon, Olivier; Barrick, Jeffrey E; Ribeck, Noah et al. (2016) Tempo and mode of genome evolution in a 50,000-generation experiment. Nature 536:165-70
Renda, Brian A; Chan, Cindy; Parent, Kristin N et al. (2016) Emergence of a Competence-Reducing Filamentous Phage from the Genome of Acinetobacter baylyi ADP1. J Bacteriol 198:3209-3219
Quandt, Erik M; Gollihar, Jimmy; Blount, Zachary D et al. (2015) Fine-tuning citrate synthase flux potentiates and refines metabolic innovation in the Lenski evolution experiment. Elife 4:
Maddamsetti, Rohan; Lenski, Richard E; Barrick, Jeffrey E (2015) Adaptation, Clonal Interference, and Frequency-Dependent Interactions in a Long-Term Evolution Experiment with Escherichia coli. Genetics 200:619-31
Jack, Benjamin R; Leonard, Sean P; Mishler, Dennis M et al. (2015) Predicting the Genetic Stability of Engineered DNA Sequences with the EFM Calculator. ACS Synth Biol 4:939-43
Renda, Brian A; Dasgupta, Aurko; Leon, Dacia et al. (2015) Genome instability mediates the loss of key traits by Acinetobacter baylyi ADP1 during laboratory evolution. J Bacteriol 197:872-81
Barrick, Jeffrey E; Colburn, Geoffrey; Deatherage, Daniel E et al. (2014) Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq. BMC Genomics 15:1039
Deatherage, Daniel E; Barrick, Jeffrey E (2014) Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq. Methods Mol Biol 1151:165-88

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