The role of hosts, plasmids and environment in determining plasmid transfer rates: A meta-analysis

Sheppard, Richard; Beddis, Alice E.; Barraclough, Timothy G.

doi:10.1016/j.plasmid.2020.102489

Cited by 46 publications

(46 citation statements)

References 46 publications

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“…Another important factor is the rate of horizontal gene transfer. While plasmids clearly transmit fast enough to influence evolution, the transfer rates per cell per generation do not appear high enough to significantly influence relatedness at the locus for cooperation 50 .…”

Section: Theoretical Stability Of Cooperationmentioning

confidence: 97%

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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Section: Theoretical Stability Of Cooperationmentioning

confidence: 97%

Plasmids facilitate pathogenicity, not cooperation, in bacteria

Dewar

Thomas

Scott

et al. 2021

Preprint

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“…Liquid [18], Plate [10,13] (Plasmid) Transfer rate [10,18], Plasmid transfer efficiency [15], Conjugation rate per mating pair [11], Conjugation coefficient [22] Table 1: Measures of conjugation proficiency and plasmid prevalence or spread reported in the literature. Here D, R, T stands for the population density of donors, recipients, and transconjugants at the time point of measurement, N is the total population density N = D + R + T , N 0 is the initial total population density, R 0 is the initial population density of recipients, ψ max is the maximum growth rate of the mating culture.…”

Section: Measurementioning

confidence: 99%

“…However, these measures 33 vary as a function of the initial population densities, the initial donor to recipient ratio, and the length 34 of the conjugation assay [13,18]. Thus, experimental results reported with such measures are not 35 comparable between studies without detailed information on the experimental conditions [10,13]. 36 In addition, this ratio is not only determined by a plasmid's conjugation rate, but also by its clonal 37 expansion [14].…”

Section: Introductionmentioning

confidence: 99%

“…There is no gold standard to determine and report conjugation rates, and this has complicated the 245 comparison of experimental values obtained by different research groups or under different condi-246 tions [10]. 247 We extended the Simonsen model for conjugation rate estimation to include the effects of differential 248 population growth and conjugation rates from donors and transconjugants.…”

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confidence: 99%

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Estimating plasmid conjugation rates: a new computational tool and a critical comparison of methods

Huisman

Benz

Duxbury

et al. 2020

Preprint

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Plasmids are important vectors for the spread of genes among diverse populations of bacteria.However, there is no standard method to determine the rate at which they spread horizontally via conjugation. Here, we compare commonly used methods on simulated data, and show that the conjugation rate estimates often depend strongly on the time of measurement, the initial population densities, or the initial ratio of donor to recipient populations. We derive a new 'end-point' measure to estimate conjugation rates, which extends the Simonsen method to include the effects of differences in population growth and conjugation rates from donors and transconjugants.We further derive analytical expressions for the parameter range in which these approximations remain valid. All tools to estimate conjugation rates are available in an R package and Shiny app.The result is a set of guidelines for easy, accurate, and comparable measurement of conjugation rates and tools to verify these rates.Plasmids are extra-chromosomal, self-replicating genetic elements that can spread between bac-1 teria via conjugation. They spread genes within and between bacterial species and are a primary 2 source of genetic innovation in the prokaryotic realm [1,2]. Genes disseminated by plasmids include 3 virulence factors, heavy metal and antibiotic resistance, metabolic genes, as well as genes involved 4 in cooperation and spite [2,3,4,5]. To understand how these traits shape the ecology and evolution 5 of bacteria [6], it is of fundamental importance to understand how plasmids spread. 6

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“…Amelioration can occur in a diversity of environments ranging from antagonistic to mutualistic ( Harrison et al, 2015 ), and pulses of positive selection ( San Millan et al, 2014b ; Stevenson et al, 2018 ) facilitates plasmid maintenance. Likewise, distinct plasmids affect the host differently ( Hall et al, 2015 ; Di Luca et al, 2017 ; San Millan et al, 2018 ) and vice versa, meaning that the same plasmid behaves differently in response to different hosts, varying its fitness/physiological effect ( Harr and Schlötterer, 2006 ; Kottara et al, 2018 ), conjugative efficiency ( Dionisio et al, 2002 ; De Gelder et al, 2005 ; Sheppard et al, 2020 ) and stability ( De Gelder et al, 2007 ). Therefore, plasmid behavior may also differ in populations composed of multiple hosts and/or plasmids ( De Gelder et al, 2008 ; Hall et al, 2016 ; Kottara et al, 2016 ; Harrison et al, 2018 ; Jordt et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Plasmid Interactions Can Improve Plasmid Persistence in Bacterial Populations

2020

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It is difficult to understand plasmid maintenance in the absence of selection and theoretical models predict the conditions for plasmid persistence to be limited. Plasmid-associated fitness costs decrease bacterial competitivity, while imperfect partition allows the emergence of plasmid-free cells during cell division. Although plasmid conjugative transfer allows mobility into plasmid-free cells, the rate of such events is generally not high enough to ensure plasmid persistence. Experimental data suggest several factors that may expand the conditions favorable for plasmid maintenance, such as compensatory mutations and accessory genes that allow positive selection. Most of the previous studies focus on bacteria that carry a single plasmid. However, there is increasing evidence that multiple plasmids inhabit the same bacterial population and that interactions between them affect their transmission and persistence. Here, we adapt previous mathematical models to include multiple plasmids and perform computer simulations to study how interactions among them affect plasmid maintenance. We tested the contribution of different plasmid interaction parameters that impact three biological features: host fitness, conjugative transfer and plasmid loss – which affect plasmid persistence. The interaction affecting conjugation was studied in the contexts of intracellular and intercellular interactions, i.e., the plasmids interact when present in the same cell or when in different cells, respectively. First, we tested the effect of each type of interaction alone and concluded that only interactions affecting fitness (epistasis) prevented plasmid extinction. Although not allowing plasmid maintenance, intracellular interactions increasing conjugative efficiencies had a more determinant impact in delaying extinction than the remaining parameters. Then, we allowed multiple interactions between plasmids and concluded that, in a few cases, a combined effect of (intracellular) interactions increasing conjugation and fitness lead to plasmid maintenance. Our results show a hierarchy among these interaction parameters. Those affecting fitness favor plasmid persistence more than those affecting conjugative transfer and lastly plasmid loss. These results suggest that interactions between different plasmids can favor their persistence in bacterial communities.

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The role of hosts, plasmids and environment in determining plasmid transfer rates: A meta-analysis

Cited by 46 publications

References 46 publications

Plasmids facilitate pathogenicity, not cooperation, in bacteria

Plasmids facilitate pathogenicity, not cooperation, in bacteria

Estimating plasmid conjugation rates: a new computational tool and a critical comparison of methods

Plasmid Interactions Can Improve Plasmid Persistence in Bacterial Populations

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