Beyond horizontal gene transfer: the role of plasmids in bacterial evolution

Rodríguez-Beltrán, Jerónimo; DelaFuente, Javier; León‐Sampedro, Ricardo; MacLean, R. Craig; Millán, Álvaro San

doi:10.1038/s41579-020-00497-1

Cited by 212 publications

(179 citation statements)

References 167 publications

(203 reference statements)

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“…Firstly, ARG-plasmids usually carry a high number of repeated sequences [50][51][52], and therefore exhibit highly entangled assembly graphs. Secondly, ARGs are frequently located on large plasmids with low copy number, and therefore have coverage values that are similar to chromosomes [49]. Consequently, finding plasmid-walks with differential coverage in the assembly graphs could be challenging for all tools relying on this strategy.…”

Section: Discussionmentioning

confidence: 99%

Recovering Escherichia coli plasmids in the absence of long-read sequencing data

Paganini

Plantinga

Arredondo-Alonso

et al. 2021

Preprint

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The incidence of infections caused by multidrug-resistant Escherichia coli strains has risen in the past years. Antibiotic resistance in E. coli is often mediated by acquisition and maintenance of plasmids. The study of E. coli plasmid epidemiology and genomics often requires long-read sequencing information, but recently a number of tools that allow plasmid prediction from short-read data have been developed. Here, we reviewed 25 available plasmid prediction tools and categorized them into binary plasmid/chromosome classification tools and plasmid reconstruction tools. We benchmarked six tools that aim to reliably reconstruct distinct plasmids, with a special focus on plasmids carrying antibiotic resistance genes (ARGs) such as extended-spectrum beta-lactamase genes. They use either assembly graph information (plasmidSPAdes, gplas), reference databases (MOB-Suite, FishingForPlasmids) or both (HyAsP and SCAPP) to produce plasmid predictions. The benchmark data set consisted of 240 E. coli strains, harboring 631 plasmids, which were representative for the diversity of E. coli in public databases. Notably, these strains were not used for training any of the tools. We found that two thirds (n=425, 66.3.%) of all plasmids were correctly reconstructed by at least one of the six tools, with a range of 92 (14.58%) to 317 (50.23%) correctly predicted plasmids. However, the majority of plasmids that carried antibiotic resistance genes (n=85, 57.8%) could not be completely recovered as distinct plasmids by any of the tools. MOB-suite was the only tool that was able to correctly reconstruct the majority of plasmids (n=317, 50.23%), and performed best at reconstructing large plasmids (n=166, 46.37%) and ARG-plasmids (n=41, 27.9%), but predictions frequently contained chromosome contamination (40%). In contrast, plasmidSPAdes reconstructed the highest fraction of plasmids smaller than 18 kbp (n=168, 61.54%). Large ARG-plasmids, however, were recovered with small precision values (median=0.47, IQR=0.61), indicating that plasmidSPAdes frequently merged sequences derived from distinct replicons. Additionally, only 63% of all plasmid-borne ARGs were correctly predicted by plasmidSPAdes. The remaining four tools (FishingForPlasmids, HyAsP, SCAPP and gplas) were able to correctly reconstruct a combined total of 18 plasmids that were missed by MOB-suite and plasmidSPAdes. Available bioinformatic tools can provide valuable insight into E. coli plasmids, but also have important limitations. This work will serve as a guideline for selecting the most appropriate plasmid reconstruction tool for studies focusing on E. coli plasmids in the absence of long-read sequencing data.

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Section: Discussionmentioning

confidence: 99%

Recovering Escherichia coli plasmids in the absence of long-read sequencing data

Paganini

Plantinga

Arredondo-Alonso

et al. 2021

Preprint

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“…This could be expected for different reasons, including plasmid transfer allowing genes for different environments to be gained and lost (Figure 1b), or plasmids conferring some other advantage not associated with horizontal gene transfer, such as allowing copy number to be conditionally adjusted (Figure 1c) 31,32,38,51 . There are a number of different ways to classify environmental variability, and so we used three different methods.…”

Section: Alternate Hypothesesmentioning

confidence: 99%

“…Consequently, we might expect to find genes for extracellular proteins on plasmids to facilitate rapid gain and loss of genes depending on environmental conditions, and not because they are cooperative per se. Alternatively, genes may be favoured to be on plasmids for reasons other than horizontal gene transfer (Figure 1c) 38 . For example, a higher plasmid copy number offers a mechanism for more expression of a gene, potentially even conditionally, in response to certain environmental conditions 38 .…”

Section: Introductionmentioning

confidence: 99%

“…Alternatively, genes may be favoured to be on plasmids for reasons other than horizontal gene transfer (Figure 1c) 38 . For example, a higher plasmid copy number offers a mechanism for more expression of a gene, potentially even conditionally, in response to certain environmental conditions 38 . The benefit of being able to regulate gene expression in this way could be higher in genes which code for molecules that are secreted outside the cell, when different quantities of molecule are required in different environments.…”

Section: Introductionmentioning

confidence: 99%

“…(c) Beyond Horizontal Gene Transfer Hypothesis. The location of a gene on a plasmid could provide a number of benefits, other than the possibility for horizontal gene transfer 38 . For example, when the quantity of extracellular protein required varies across environments (A versus B), plasmid copy number could be varied to adjust production 38 .…”

Section: Introductionmentioning

confidence: 99%

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Plasmids facilitate pathogenicity, not cooperation, in bacteria

Dewar

Thomas

Scott

et al. 2021

Preprint

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Horizontal gene transfer via plasmids could favour cooperation in bacteria, because transfer of a cooperative gene turns non-cooperative cheats into cooperators. This hypothesis has received support from both theoretical and genomic analyses. In contrast, with a comparative analysis across 51 diverse species, we found that genes for extracellular proteins, which are likely to act as cooperative ‘public goods’, were not more likely to be carried on either: (i) plasmids compared to chromosomes; or (ii) plasmids that transfer at higher rates. Our results were supported by theoretical modelling which showed that while horizontal gene transfer can help cooperative genes initially invade a population, it does not favour the longer-term maintenance of cooperation. Instead, we found that genes for extracellular proteins were more likely to be on plasmids when they coded for pathogenic virulence traits, in pathogenic bacteria with a broad host-range. Taken together, these results support an alternate hypothesis, that plasmid gene location confers benefits other than horizontal gene transfer.

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Segregational instability of multicopy plasmids: A population genetics approach

Hernandez‐Beltran

Pina

Siri‐Jégousse

et al. 2022

Ecology and Evolution

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Plasmids are extra‐chromosomal genetic elements that encode a wide variety of phenotypes and can be maintained in bacterial populations through vertical and horizontal transmission, thus increasing bacterial adaptation to hostile environmental conditions like those imposed by antimicrobial substances. To circumvent the segregational instability resulting from randomly distributing plasmids between daughter cells upon division, nontransmissible plasmids tend to be carried in multiple copies per cell, with the added benefit of exhibiting increased gene dosage and resistance levels. But carrying multiple copies also results in a high metabolic burden to the bacterial host, therefore reducing the overall fitness of the population. This trade‐off poses an existential question for plasmids: What is the optimal plasmid copy number? In this manuscript, we address this question by postulating and analyzing a population genetics model to evaluate the interaction between selective pressure, the number of plasmid copies carried by each cell, and the metabolic burden associated with plasmid bearing in the absence of selection for plasmid‐encoded traits. Parameter values of the model were estimated experimentally using Escherichia coli K12 carrying a multicopy plasmid encoding for a fluorescent protein and bla TEM‐1 , a gene conferring resistance to β ‐lactam antibiotics. By numerically determining the optimal plasmid copy number for constant and fluctuating selection regimes, we show that plasmid copy number is a highly optimized evolutionary trait that depends on the rate of environmental fluctuation and balances the benefit between increased stability in the absence of selection with the burden associated with carrying multiple copies of the plasmid.

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Beyond horizontal gene transfer: the role of plasmids in bacterial evolution

Cited by 212 publications

References 167 publications

Recovering Escherichia coli plasmids in the absence of long-read sequencing data

Recovering Escherichia coli plasmids in the absence of long-read sequencing data

Plasmids facilitate pathogenicity, not cooperation, in bacteria

Segregational instability of multicopy plasmids: A population genetics approach

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