Abstract

Understanding under which conditions conjugative plasmids encoding antibiotic resistance can invade bacterial communities in the gut is of particular interest to combat the spread of antibiotic resistance within and between animals and humans. We extended a one-compartment model of conjugation to a two-compartment model, to analyse how differences in plasmid dynamics in the gut lumen and at the gut wall affect the invasion of plasmids. We compared scenarios with one and two compartments, different migration rates between the lumen and wall compartments, and different population dynamics. We focused on the effect of attachment and detachment rates on plasmid dynamics, explicitly describing pair formation followed by plasmid transfer in the pairs. The parameter space allowing plasmid invasion in the one-compartment model is affected by plasmid costs and intrinsic conjugation rates of the transconjugant, but not by these characteristics of the donor. The parameter space allowing plasmid invasion in the two-compartment model is affected by attachment and detachment rates in the lumen and wall compartment, and by the bacterial density at the wall. The one- and two-compartment models predict the same parameter space for plasmid invasion if the conditions in both compartments are equal to the conditions in the one-compartment model. In contrast, the addition of the wall compartment widens the parameter space allowing invasion compared with the one-compartment model, if the density at the wall is higher than in the lumen, or if the attachment rate at the wall is high and the detachment rate at the wall is low. We also compared the pair-formation models with bulk-conjugation models that describe conjugation by instantaneous transfer of the plasmid at contact between cells, without explicitly describing pair formation. Our results show that pair-formation and bulk-conjugation models predict the same parameter space for plasmid invasion. From our simulations, we conclude that conditions at the gut wall should be taken into account to describe plasmid dynamics in the gut and that transconjugant characteristics rather than donor characteristics should be used to parameterize the models.

Highlights

  • IntroductionSince the 1970s mathematical models have been used to determine under which conditions plasmids (extra-chromosomal DNA molecules) can invade and persist in populations of plasmid-free bacteria (Freter et al, 1983a; Simonsen, 1991; Stewart and Levin, Abbreviations: D, donors; L, lumen; MDT, donor-transconjugant pairs; MRD, recipient-donor pairs; MRT, recipient-transconjugant pairs; MTT, transconjuganttransconjugant pairs; R, recipients; S, nutrients; T, transconjugants; W, wall.⇑ Corresponding author.1977)

  • Since the 1970s mathematical models have been used to determine under which conditions plasmids can invade and persist in populations of plasmid-free bacteria

  • The plasmid can invade in 28% of the combinations of attachment and detachment rates if the default parameter values listed in Table 1 are used (Fig. 2)

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Summary

Introduction

Since the 1970s mathematical models have been used to determine under which conditions plasmids (extra-chromosomal DNA molecules) can invade and persist in populations of plasmid-free bacteria (Freter et al, 1983a; Simonsen, 1991; Stewart and Levin, Abbreviations: D, donors; L, lumen; MDT, donor-transconjugant pairs; MRD, recipient-donor pairs; MRT, recipient-transconjugant pairs; MTT, transconjuganttransconjugant pairs; R, recipients; S, nutrients; T, transconjugants; W, wall.⇑ Corresponding author.1977). Since the 1970s mathematical models have been used to determine under which conditions plasmids (extra-chromosomal DNA molecules) can invade and persist in populations of plasmid-free bacteria Plasmids often carry antibiotic resistance genes, making the invasion of plasmids into new populations, such as the gut microbiota of animals and humans, of particular interest to combat the spread of antibiotic resistance within and between animals and humans (Dame-Korevaar et al, 2019; McInnes et al, 2020; Shintani et al, 2015; Shterzer and Mizrahi, 2015). Plasmids can impose fitness costs on the host, lowering their growth rate

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