Research

The research focusses on using mathematical tools and computational methods to understand microbial evolution, with a special focus on microbiomes and antibiotic resistance evolution.

For a full list of publications, check Google Scholar

Eco-evolutionary dynamics affecting antibiotic resistance evolution

We show that eco-evolutionary dynamics can result in coexistence between two alleles of a gene conferring antibiotic resistance.

The evolution of microorganisms in constant and fluctuating environements

To understand evolution, it is great that we can study evolution in real time in the laboratory. When interpreting the results of these experiments, we have to understand well what the selection pressure in laboratory environments are. In a theoretical analysis, we have shown that the chemostat environment can lead to diversification. More recently, I have shown that in fluctuating conditions, species specialized on either low or high resource levels can coexist in an evolutionary stable manner. Below this study is explained in a shorter and longer presentation.

How do species interactions affect evolution?

Will species continue to evolve or do they reach a point where evolution ceases (stasis)? In 1973, Leigh van Valen posed the hypothesis that species keep evolving to keep up with the evolving species in their environment. This is called the Red Queen Hypothesis, after the Red Queen in Lewis Carrol's Through the Looking Glass who said so Alice: "Now, here, you see, it takes all the running you can do, to keep in the same place". Even though the hypothesis is old, it is not know under what conditions species evolve of reach stasis. Theoretically, we found that a combination of a positive and a negative feedback can lead to continual evolution.

Experimentally, I study how species interaction affect evolution using a system of a bacteriovorous roundworm Caenorhabditis elegans and a bacteria Escherichia coli. In the video below I explain how I use this system to study the predictability of evolution. We also published a review on "Towards evolutionary predictions: Current promises and challenges".

Video with Dutch subtitles

Metabolism and interactions within microbiomes

We have shown that we can caracterise metabolic pathways that optimize growth and that we can use that to understand that the trade-off between growth rate and yield is condition dependent. The use of many of these pathways allow for the use of the metabolites for other species, and therefore cross-feeding interactions. These interactions are abundant in the gut microbiome, and we study some of these interactions in more detail to understand the dynamics of the microbiome in disease. Those can be validated using synthetic microbial communities (SynComs). With a Syncom and a computational model we show that two opportunistic pathogens in the human gut microbiome, Escherichia coli and Bacteroides ovatus, have different interactions with the communitie leading to different invasion pattern.