Investigating Evolutionary Rate Variation in Bacteria

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Abstract

Rates of molecular evolution are known to vary between species and across all kingdoms of life. Here, we explore variation in the rate at which bacteria accumulate mutations (accumulation rates) in their natural environments over short periods of time. We have compiled estimates of the accumulation rate for over 34 species of bacteria, the majority of which are pathogens evolving either within an individual host or during outbreaks. Across species, we find that accumulation rates vary by over 3700-fold. We investigate whether accumulation rates are associated to a number potential correlates including genome size, GC content, measures of the natural selection and the time frame over which the accumulation rates were estimated. After controlling for phylogenetic non-independence, we find that the accumulation rate is not significantly correlated to any factor. Furthermore, contrary to previous results, we find that it is not impacted by the time frame of which the estimate was made. However, our study, with only 34 species, is likely to lack power to detect anything but large effects. We suggest that much of the rate variation may be explained by differences between species in the generation time in the wild.

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Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

Simon Blomberg, Anthony Ives, Theodore Garland (2003)

The primary rationale for the use of phylogenetically based statistical methods is that phylogenetic signal, the tendency for related species to resemble each other, is ubiquitous. Whether this assertion is true for a given trait in a given lineage is an empirical question, but general tools for detecting and quantifying phylogenetic signal are inadequately developed. We present new methods for continuous-valued characters that can be implemented with either phylogenetically independent contrasts or generalized least-squares models. First, a simple randomization procedure allows one to test the null hypothesis of no pattern of similarity among relatives. The test demonstrates correct Type I error rate at a nominal alpha = 0.05 and good power (0.8) for simulated datasets with 20 or more species. Second, we derive a descriptive statistic, K, which allows valid comparisons of the amount of phylogenetic signal across traits and trees. Third, we provide two biologically motivated branch-length transformations, one based on the Ornstein-Uhlenbeck (OU) model of stabilizing selection, the other based on a new model in which character evolution can accelerate or decelerate (ACDC) in rate (e.g., as may occur during or after an adaptive radiation). Maximum likelihood estimation of the OU (d) and ACDC (g) parameters can serve as tests for phylogenetic signal because an estimate of d or g near zero implies that a phylogeny with little hierarchical structure (a star) offers a good fit to the data. Transformations that improve the fit of a tree to comparative data will increase power to detect phylogenetic signal and may also be preferable for further comparative analyses, such as of correlated character evolution. Application of the methods to data from the literature revealed that, for trees with 20 or more species, 92% of traits exhibited significant phylogenetic signal (randomization test), including behavioral and ecological ones that are thought to be relatively evolutionarily malleable (e.g., highly adaptive) and/or subject to relatively strong environmental (nongenetic) effects or high levels of measurement error. Irrespective of sample size, most traits (but not body size, on average) showed less signal than expected given the topology, branch lengths, and a Brownian motion model of evolution (i.e., K was less than one), which may be attributed to adaptation and/or measurement error in the broad sense (including errors in estimates of phenotypes, branch lengths, and topology). Analysis of variance of log K for all 121 traits (from 35 trees) indicated that behavioral traits exhibit lower signal than body size, morphological, life-history, or physiological traits. In addition, physiological traits (corrected for body size) showed less signal than did body size itself. For trees with 20 or more species, the estimated OU (25% of traits) and/or ACDC (40%) transformation parameter differed significantly from both zero and unity, indicating that a hierarchical tree with less (or occasionally more) structure than the original better fit the data and so could be preferred for comparative analyses.

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Time-dependent rates of molecular evolution.

Simon Y W Ho, Robert Lanfear, Lindell Bromham … (2011)

For over half a century, it has been known that the rate of morphological evolution appears to vary with the time frame of measurement. Rates of microevolutionary change, measured between successive generations, were found to be far higher than rates of macroevolutionary change inferred from the fossil record. More recently, it has been suggested that rates of molecular evolution are also time dependent, with the estimated rate depending on the timescale of measurement. This followed surprising observations that estimates of mutation rates, obtained in studies of pedigrees and laboratory mutation-accumulation lines, exceeded long-term substitution rates by an order of magnitude or more. Although a range of studies have provided evidence for such a pattern, the hypothesis remains relatively contentious. Furthermore, there is ongoing discussion about the factors that can cause molecular rate estimates to be dependent on time. Here we present an overview of our current understanding of time-dependent rates. We provide a summary of the evidence for time-dependent rates in animals, bacteria and viruses. We review the various biological and methodological factors that can cause rates to be time dependent, including the effects of natural selection, calibration errors, model misspecification and other artefacts. We also describe the challenges in calibrating estimates of molecular rates, particularly on the intermediate timescales that are critical for an accurate characterization of time-dependent rates. This has important consequences for the use of molecular-clock methods to estimate timescales of recent evolutionary events. © 2011 Blackwell Publishing Ltd.

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A constant rate of spontaneous mutation in DNA-based microbes.

J DRAKE (1991)

In terms of evolution and fitness, the most significant spontaneous mutation rate is likely to be that for the entire genome (or its nonfrivolous fraction). Information is now available to calculate this rate for several DNA-based haploid microbes, including bacteriophages with single- or double-stranded DNA, a bacterium, a yeast, and a filamentous fungus. Their genome sizes vary by approximately 6500-fold. Their average mutation rates per base pair vary by approximately 16,000-fold, whereas their mutation rates per genome vary by only approximately 2.5-fold, apparently randomly, around a mean value of 0.0033 per DNA replication. The average mutation rate per base pair is inversely proportional to genome size. Therefore, a nearly invariant microbial mutation rate appears to have evolved. Because this rate is uniform in such diverse organisms, it is likely to be determined by deep general forces, perhaps by a balance between the usually deleterious effects of mutation and the physiological costs of further reducing mutation rates.

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Author and article information

Contributors

Adam Eyre-Walker:

ORCID: http://orcid.org/0000-0001-5527-8729

01273 678480 , a.c.eyre-walker@sussex.ac.uk

Journal

Journal ID (nlm-ta): J Mol Evol

Journal ID (iso-abbrev): J. Mol. Evol

Title: Journal of Molecular Evolution

Publisher: Springer US (New York )

ISSN (Print): 0022-2844

ISSN (Electronic): 1432-1432

Publication date (Electronic): 30 September 2019

Publication date PMC-release: 30 September 2019

Publication date (Print): 2019

Volume: 87

Issue: 9

Pages: 317-326

Affiliations

GRID grid.12082.39, ISNI 0000 0004 1936 7590, School of Life Sciences, , University of Sussex, ; Brighton, BN1 9QG UK

Author notes

Handling Editor: David Posada.

Author information

Beth Gibson http://orcid.org/0000-0001-7984-6188

Adam Eyre-Walker http://orcid.org/0000-0001-5527-8729

Article

Publisher ID: 9912

DOI: 10.1007/s00239-019-09912-5

PMC ID: 6858405

PubMed ID: 31570957

SO-VID: 6d0dae36-db5c-4fa4-b68b-61a5bacf10f5

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

History

Date received : 12 November 2018

Date accepted : 12 September 2019

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ScienceOpen disciplines: Evolutionary Biology

Keywords: bacteria,evolutionary rate,accumulation rate,mutation

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ScienceOpen disciplines: Evolutionary Biology

Keywords: bacteria, evolutionary rate, accumulation rate, mutation

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Investigating Evolutionary Rate Variation in Bacteria

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Most cited references 31

Testing for phylogenetic signal in comparative data: behavioral traits are more labile.

Time-dependent rates of molecular evolution.

A constant rate of spontaneous mutation in DNA-based microbes.

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