Analysis of bacterial genomes from an evolution experiment with horizontal gene transfer shows that recombination can sometimes overwhelm selection

Maddamsetti, Rohan; Lenski, Richard E.

doi:10.1101/186759

Cited by 11 publications

(13 citation statements)

References 36 publications

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“…This is likely the case for some MGEs and lysogenic viruses, what we call ‘infectious’ genes, which are most likely deleterious but gained at high rates. For example, deleterious polymorphisms can become prevalent in a bacterial population due to the effect of high recombination mediated by conjugative plasmids 32 , and inteins with high fitness costs seem to be maintained in genomes 33 .…”

Section: Discussionmentioning

confidence: 99%

Selection-based model of prokaryote pangenomes

Domingo-Sananes

McInerney

2019

Preprint

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10The genomes of different individuals of the same prokaryote species can vary widely in gene 11 content, displaying different proportions of core genes, which are present in all genomes, and 12 accessory genes, whose presence varies between genomes. Together, these core and 13 accessory genes make up a species' pangenome. The reasons behind this extensive diversity 14 in gene content remain elusive, and there is an ongoing debate about the contribution of 15 accessory genes to fitness, that is, whether their presence is on average advantageous, 16 neutral, or deleterious. In order to explore this issue, we developed a mathematical model to 17 simulate the gene content of prokaryote genomes and pangenomes. Our model focuses on 18 testing how the fitness effects of genes and their rates of gene gain and loss would affect the 19 properties of pangenomes. We first show that pangenomes with large numbers of low-20 frequency genes can arise due to the gain and loss of neutral and nearly neutral genes in a 21 population. However, pangenomes with large numbers of highly beneficial, low-frequency 22 genes can arise as a consequence of genotype-by-environment interactions when multiple 23 niches are available to a species. Finally, pangenomes can arise, irrespective of the fitness 24 effect of the gained and lost genes, as long as gene gain and loss rates are high. We argue 25 that in order to understand the contribution of different mechanisms to pangenome diversity, 26it is crucial to have empirical information on population structure, gene-by-environment 27 interactions, the distributions of fitness effects and rates of gene gain and loss in different 28 prokaryote groups. 30 42 43Pangenomes arise as a consequence of gene acquisition via horizontal gene transfer (HGT), 44 and gene loss 2 . These processes ultimately result in general patterns observed across 45 prokaryotes, which include an increase in the number of known accessory genes as more 46 genomes from the same species are sequenced -along with a slower decrease in the number 47 of core genes-and a U-shaped gene frequency distribution or spectrum 2,10,11 . The U shape 48 2 of this distribution indicates that there is a large proportion of genes present in a single or very 49 few genomes, few genes present at intermediate frequencies, and substantial proportion of 50 core genes. Although across prokaryotic life there is a certain amount of commonality in the 51 shape of the gene content frequency distributions, different prokaryote species manifest 52 significant differences in the proportions of core and accessory genes [12][13][14] . 54Although we know that HGT and gene loss result in pangenomes, what is less clear are the 55 forces that lead to high diversity in gene content and U-shaped gene frequency distributions. 56According to mathematical models, gain and loss of entirely neutral genes along a simulated 57 phylogeny or population can in principle predict the U-shaped gene frequency distributions of 58 pangenomes 11,15 . However, the fit to real data i...

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Section: Discussionmentioning

confidence: 99%

Selection-based model of prokaryote pangenomes

Domingo-Sananes

McInerney

2019

Preprint

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“…In several studies of sets of plasmids, researchers have noted plasmids that appear to be ‘mosaics;’ in other words, they contain genes from several ancestral genetic sources, likely due to recombination (though the exact definition of mosaic depends on the analysis) (1, 4–7). Because the effects of recombination are highly variable, even in controlled settings (8), the study of mosaic plasmids has been largely observational, with scope restricted by the number of plasmid sequences available. In 2011, Bosi et al (9) identified putative ‘atypical’ genes in the set of plasmid sequences available at the time, using the parametric methods of GC content and dinucleotide profiling.…”

Section: Introductionmentioning

confidence: 99%

Mosaic Plasmids are Abundant and Unevenly Distributed Across Prokaryotic Taxa

Pesesky

Tilley

Beck

2018

Preprint

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24Mosaic plasmids, plasmids composed of genetic elements from distinct 25 sources, are associated with the spread of antibiotic resistance genes. Transposons 26 are considered the primary mechanism for mosaic plasmid formation, though other 27 mechanisms have been observed in specific instances. The frequency with which 28 mosaic plasmids have been described suggests they may play an important role in 29 plasmid population dynamics. Our survey of the confirmed plasmid sequences 30 available from complete and draft genomes in the RefSeq database shows that 46% 31 of them fit a strict definition of mosaic. Mosaic plasmids are also not evenly 32 distributed over the taxa represented in the database. Plasmids from some genera, 33 including Piscirickettsia and Yersinia, are almost all mosaic, while plasmids from 34 other genera, including Borrelia, are rarely mosaic. While some mosaic plasmids 35 share identical regions with hundreds of others, the median mosaic plasmid only 36 shares with 8 other plasmids. 37 When considering only plasmids from finished genomes (51.6% of the total), 38 mosaic plasmids have significantly higher proportions of transposases and 39 antibiotic resistance genes. Conversely, only 56.6% of mosaic fragments (DNA 40 fragments shared between mosaic plasmids) contain a recognizable transposase, 41 and only 1.2% of mosaic fragments are flanked by inverted repeats. Mosaic 42 fragments associated with the IS26 transposase are 3.8-fold more abundant than 43 any other sequence shared between mosaic plasmids in the database, though this is 44 at least partly due to overrepresentation of Enterobacteriaceae plasmids. 45 Mosaic plasmids are a complicated trait of some plasmid populations, only 46 partly explained by transposition. Though antibiotic resistance genes led to the 47 identification of many mosaic plasmids, mosaic plasmids are a broad phenomenon 48 encompassing many more traits than just antibiotic resistance. Further research 49 will be required to determine the influence of ecology, host repair mechanisms, 50 conjugation, and plasmid host range on the formation and influence of mosaic 51 plasmids. 52 53 Author Summary 54 Plasmids are extrachromosomal genetic entities that are found in many 55 prokaryotes. They serve as flexible storage for genes, and individual cells can make 56 substantial changes to their characteristics by acquiring, losing, or modifying a 57 plasmid. In some pathogenic bacteria, such as Escherichia coli, antibiotic resistance 58 genes are known to spread primarily on plasmids. By analyzing a database of 8,59259 plasmid sequences we determined that many of these plasmids have exchanged 60 genes with each other, becoming mosaics of genes from different sources. We next 61 separated these plasmids into groups based on the organism they were isolated 62 from and found that different groups had different fractions of mosaic plasmids. 63 This result was unexpected and suggests that the mechanisms and selective 64 pressures causing mosaic plasmids do not occur evenly over all s...

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“…One of the main reasons for this is that many model laboratory organisms, such as E. coli, S. cerevisiae or Pseudomonas species, do not undergo recombination or HGT under commonly used experimental conditions. These challenges can be overcome by engineering strains of S. cerevisiae [44,111,[119][120][121] and E. coli [122][123][124] that are capable of repeated bouts of sex, or conjugative gene exchange, in an experimental evolution setting.…”

Section: Clonal Interference and Recombination Impact Evolutionary Oumentioning

confidence: 99%

Microbial Experimental Evolution – a proving ground for evolutionary theory and a tool for discovery

McDonald

2019

EMBO Reports

122

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Microbial experimental evolution uses controlled laboratory populations to study the mechanisms of evolution. The molecular analysis of evolved populations enables empirical tests that can confirm the predictions of evolutionary theory, but can also lead to surprising discoveries. As with other fields in the life sciences, microbial experimental evolution has become a tool, deployed as part of the suite of techniques available to the molecular biologist. Here, I provide a review of the general findings of microbial experimental evolution, especially those relevant to molecular microbiologists that are new to the field. I also relate these results to design considerations for an evolution experiment and suggest future directions for those working at the intersection of experimental evolution and molecular biology.

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Analysis of bacterial genomes from an evolution experiment with horizontal gene transfer shows that recombination can sometimes overwhelm selection

Cited by 11 publications

References 36 publications

Selection-based model of prokaryote pangenomes

Selection-based model of prokaryote pangenomes

Mosaic Plasmids are Abundant and Unevenly Distributed Across Prokaryotic Taxa

Microbial Experimental Evolution – a proving ground for evolutionary theory and a tool for discovery

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