bioRxiv Science⌕ Search

Biology subjects

Siedentop, B.

Publications and source records attributed to Siedentop, B..

3 recordsLinked to original sources

Assessing the role of bacterial innate and adaptive immunity as barriers to conjugative plasmids

Plasmids are ubiquitous mobile genetic elements, that can be either costly or beneficial for their bacterial host. In response to constant viral threat, bacteria have evolved various immune systems, such as the prevalent restriction modification (RM) (innate immunity) and CRISPR-Cas systems (adaptive immunity). At the molecular level, both systems also target plasmids, but the consequences of these interactions for plasmid spread are unclear. Using a modeling approach, we show that RM and CRISPR-Cas are effective as barriers against the spread of costly plasmids, but not against beneficial ones. Consequently, bacteria can profit from the adaptive advantages that beneficial plasmids confer even in the presence of bacterial immunity. While plasmids that are costly for bacteria may persist for a certain period in the bacterial population, RM and CRISPR-Cas pose a substantial burden for such plasmids, which can eventually drive them to extinction. Finally, we demonstrate that the selection pressure imposed by bacterial immunity on costly plasmids can be circumvented through a diversity of escape mechanisms and highlight how plasmid carriage might be common despite bacterial immunity. In summary, the population-level outcome of interactions between plasmids and defense systems in a bacterial population is closely tied to plasmid cost: Beneficial plasmids can persist at high prevalence in bacterial populations despite defense systems, while costly plasmids may face substantial reduction in prevalence or even extinction.

microbiology↗

My host's enemy is my enemy: plasmids carrying CRISPR-Cas as a defence against phages

Bacteria are infected by mobile genetic elements like plasmids and virulent phages, and those infections significantly impact bacterial ecology and evolution. Recent discoveries reveal that some plasmids carry anti-phage immune systems like CRISPR-Cas, suggesting that plasmids may participate in the coevolutionary arms-race between virulent phages and bacteria. Intuitively, this seems reasonable as virulent phages kill the plasmids obligate host. However, the efficiency of CRISPR-Cas systems carried by plasmids can be expected to be lower than those carried by the chromosome due to continuous segregation loss, creating susceptible cells for phage amplification. To evaluate the anti-phage protection efficiency of CRISPR-Cas on plasmids, we develop a stochastic model describing the dynamics of a virulent phage infection against which a conjugative plasmid defends using CRISPR-Cas. We show that CRISPR-Cas on plasmids provides robust protection, except in limited parameter-sets. In these cases, high segregation favours phage outbreaks by generating a population of defenceless cells on which the phage can evolve and escape CRISPR-Cas immunity. We show that the phages ability to exploit segregation loss depends strongly on the evolvability of both CRISPR-Cas and the phage itself.

microbiology↗

Plasmid co-infection: linking biological mechanisms to ecological and evolutionary dynamics

As infectious agents of bacteria and vehicles of horizontal gene transfer, plasmids play a key role in bacterial ecology and evolution. Plasmid dynamics are shaped not only by plasmid-host interactions, but also by ecological interactions between plasmid variants. These interactions are complex: plasmids can co-infect the same host cell and the consequences for the co-resident plasmid can be either beneficial or detrimental. Many of the biological processes that govern plasmid co-infection-from systems to exclude infection by other plasmids to interactions in the regulation of plasmid copy number per cell-are well characterised at a mechanistic level. Modelling plays a central role in translating such mechanistic insights into predictions about plasmid dynamics, and in turn, the impact of these dynamics on bacterial evolution. Theoretical work in evolutionary epidemiology has shown that formulating models of co-infection is not trivial, as some modelling choices can introduce unintended ecological assumptions. Here, we review how the biological processes that govern co-infection can be represented in a mathematical model, discuss potential modelling pitfalls, and analyse this model to provide general insights into how co-infection impacts eco-evolutionary outcomes. In particular, we demonstrate how beneficial and detrimental effects of co-infection give rise to frequency-dependent selection.

microbiology↗