Sharon Bewick

Antibiotics as a selective driver for conjugation dynamics

It is generally assumed that antibiotics can promote horizontal gene transfer. However, because of a variety of confounding factors that complicate the interpretation of previous studies, the mechanisms by which antibiotics modulate horizontal gene transfer remain poorly understood. In particular, it is unclear whether antibiotics directly regulate the efficiency of horizontal gene transfer, serve as a selection force to modulate population dynamics after such gene transfer has occurred, or both. Here, we address this question by quantifying conjugation dynamics in the presence and absence of antibiotic-mediated selection. Surprisingly, we find that sublethal concentrations of antibiotics from the most widely used classes do not significantly increase the conjugation efficiency. Instead, our modelling and experimental results demonstrate that conjugation dynamics are dictated by antibiotic-mediated selection, which can both promote and suppress conjugation dynamics. Our findings suggest that the contribution of antibiotics to the promotion of horizontal gene transfer may have been overestimated. These findings have implications for designing effective antibiotic treatment protocols and for assessing the risks of antibiotic use.

PERSISTENCE AND SPREAD OF A SPECIES WITH A SHIFTING HABITAT EDGE

We study a reaction-diffusion model that describes the growth and spread of a species along a shifting habitat gradient on which the species growth increases. It is assumed that the linearized species growth rate is positive near positive infinity and is negative near negative infinity. We show that the persistence and spreading dynamics depend on the speed of the shifting habitat edge

How Resource Phenology Affects Consumer Population Dynamics

c

Phenologically explicit models for studying plant–pollinator interactions under climate change

and a number

Phylogenetic prediction of the maximum per capita rate of population growth

c^*(infty)

Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data

that is determined by the maximum linearized growth rate and the diffusion coefficient. We demonstrate that if

Mathematical model of Zika virus with vertical transmission

c>c^*(infty)

Zika Virus: Endemic Versus Epidemic Dynamics and Implications for Disease Spread in the Americas

, then the species will become extinct in the habitat, and that if

A mathematical model for within-host Toxoplasma gondii invasion dynamics.

c<c^*(infty)

Epidemiology of La Crosse Virus Emergence, Appalachia Region, United States.

, then the species will persist and spread along the shifting habitat gradient at an asymptotic spreading speed