2023
Barrick J E; Blount Z D; Lake D M; Dwenger J H; Chavarria-Palma J E; Izutsu M; Wiser M J
Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli Journal Article
Journal of Visualized Experiments, 198 , pp. e65342, 2023, ISSN: 1940-087X.
Abstract | Links | BibTeX | Altmetric | Tags: Fitness Trajectories, Methods and Miscellaneous
@article{Barrick2023,
title = {Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli},
author = {Jeffrey E. Barrick and Zachary D. Blount and Devin M. Lake and Jack H. Dwenger and Jesus E. Chavarria-Palma and Minako Izutsu and Michael J. Wiser},
doi = {10.3791/65342},
issn = {1940-087X},
year = {2023},
date = {2023-08-18},
urldate = {2023-08-18},
journal = {Journal of Visualized Experiments},
volume = {198},
pages = {e65342},
abstract = {The Long-Term Evolution Experiment (LTEE) has followed twelve populations of \textit{Escherichia coli} as they have adapted to a simple laboratory environment for more than 35 years and 77,000 bacterial generations. The setup and procedures used in the LTEE epitomize reliable and reproducible methods for studying microbial evolution. In this protocol, we first describe how the LTEE populations are transferred to fresh medium and cultured each day. Then, we describe how the LTEE populations are regularly checked for possible signs of contamination and archived to provide a permanent frozen "fossil record" for later study. Multiple safeguards included in these procedures are designed to prevent contamination, detect various problems when they occur, and recover from disruptions without appreciably setting back the progress of the experiment. One way that the overall tempo and character of evolutionary changes are monitored in the LTEE is by measuring the competitive fitness of populations and strains from the experiment. We describe how co-culture competition assays are conducted and provide both a spreadsheet and an R package (fitnessR) for calculating relative fitness from the results. Over the course of the LTEE, the behaviors of some populations have changed in interesting ways, and new technologies like whole-genome sequencing have provided additional avenues for investigating how the populations have evolved. We end by discussing how the original LTEE procedures have been updated to accommodate or take advantage of these changes. This protocol will be useful for researchers who use the LTEE as a model system for studying connections between evolution and genetics, molecular biology, systems biology, and ecology. More broadly, the LTEE provides a tried-and-true template for those who are beginning their own evolution experiments with new microbes, environments, and questions. },
keywords = {Fitness Trajectories, Methods and Miscellaneous},
pubstate = {published},
tppubtype = {article}
}
The Long-Term Evolution Experiment (LTEE) has followed twelve populations of Escherichia coli as they have adapted to a simple laboratory environment for more than 35 years and 77,000 bacterial generations. The setup and procedures used in the LTEE epitomize reliable and reproducible methods for studying microbial evolution. In this protocol, we first describe how the LTEE populations are transferred to fresh medium and cultured each day. Then, we describe how the LTEE populations are regularly checked for possible signs of contamination and archived to provide a permanent frozen "fossil record" for later study. Multiple safeguards included in these procedures are designed to prevent contamination, detect various problems when they occur, and recover from disruptions without appreciably setting back the progress of the experiment. One way that the overall tempo and character of evolutionary changes are monitored in the LTEE is by measuring the competitive fitness of populations and strains from the experiment. We describe how co-culture competition assays are conducted and provide both a spreadsheet and an R package (fitnessR) for calculating relative fitness from the results. Over the course of the LTEE, the behaviors of some populations have changed in interesting ways, and new technologies like whole-genome sequencing have provided additional avenues for investigating how the populations have evolved. We end by discussing how the original LTEE procedures have been updated to accommodate or take advantage of these changes. This protocol will be useful for researchers who use the LTEE as a model system for studying connections between evolution and genetics, molecular biology, systems biology, and ecology. More broadly, the LTEE provides a tried-and-true template for those who are beginning their own evolution experiments with new microbes, environments, and questions.
2021
Izutsu M; Lake D M; Matson Z W D; Dodson J P; Lenski R E
Effects of periodic bottlenecks on the dynamics of adaptive evolution in microbial populations Unpublished
2021.
Abstract | Links | BibTeX | Altmetric | Tags: Descendant Experiments, Fitness Trajectories, Theory and Simulations
@unpublished{,
title = {Effects of periodic bottlenecks on the dynamics of adaptive evolution in microbial populations},
author = {Minako Izutsu and Devin M. Lake and Zachary W. D. Matson and Jack P. Dodson and Richard E. Lenski},
doi = {10.1101/2021.12.29.474457},
year = {2021},
date = {2021-12-30},
urldate = {2021-12-30},
journal = {10.1101/2021.12.29.474457},
publisher = {LTEE},
abstract = {Population bottlenecks are common in nature, and they can impact the rate of adaptation in evolving populations. On the one hand, each bottleneck reduces the genetic variation that fuels adaptation. On the other hand, fewer founders can undergo more generations and leave more descendants in a resource-limited environment, which allows surviving beneficial mutations to spread more quickly. Here we investigate the impact of repeated bottlenecks on the dynamics of adaptation in experimental populations of Escherichia coli. We propagated 48 populations under four dilution regimes (2-, 8-, 100-, and 1000-fold), all reaching the same final size each day, for 150 days. A simple model in which adaptation is limited by the supply rate of beneficial mutations predicts that fitness gains should be maximized with ∼8-fold dilutions. The model also assumes that selection acts only on the overall growth rate and is otherwise identical across dilution regimes. However, we found that selection in the 2-fold regime was qualitatively different from the other treatments. Moreover, we observed earlier and greater fitness gains in the populations subjected to 100- and 1000-fold dilutions than in those that evolved in the 8-fold regime. We also ran simulations using parameters estimated independently from a long-term experiment using the same ancestral strain and environment. The simulations produced dynamics similar to our empirical results under these regimes, and they indicate that the simple model fails owing to the assumption that the supply of beneficial mutations limits adaptation.},
keywords = {Descendant Experiments, Fitness Trajectories, Theory and Simulations},
pubstate = {published},
tppubtype = {unpublished}
}
Population bottlenecks are common in nature, and they can impact the rate of adaptation in evolving populations. On the one hand, each bottleneck reduces the genetic variation that fuels adaptation. On the other hand, fewer founders can undergo more generations and leave more descendants in a resource-limited environment, which allows surviving beneficial mutations to spread more quickly. Here we investigate the impact of repeated bottlenecks on the dynamics of adaptation in experimental populations of Escherichia coli. We propagated 48 populations under four dilution regimes (2-, 8-, 100-, and 1000-fold), all reaching the same final size each day, for 150 days. A simple model in which adaptation is limited by the supply rate of beneficial mutations predicts that fitness gains should be maximized with ∼8-fold dilutions. The model also assumes that selection acts only on the overall growth rate and is otherwise identical across dilution regimes. However, we found that selection in the 2-fold regime was qualitatively different from the other treatments. Moreover, we observed earlier and greater fitness gains in the populations subjected to 100- and 1000-fold dilutions than in those that evolved in the 8-fold regime. We also ran simulations using parameters estimated independently from a long-term experiment using the same ancestral strain and environment. The simulations produced dynamics similar to our empirical results under these regimes, and they indicate that the simple model fails owing to the assumption that the supply of beneficial mutations limits adaptation.