I have been awarded a NWA Idea Generator grant of 50.000 euro to study evolution in the infant gut microbiome. The summary of the proposal:
Our body consists of similar numbers of human and microbial cells, and while human cells cannot evolve within our life-time, fast-growing microorganisms do. Is their evolution important or are they replaced by strains from the environment? This study will reveal the prevalence of evolution in the infant gut microbiome
I am looking for a bioinformatician to support this project for 6 months. Contact me if you are interested!
Students interested in species interactions, metabolic interactions and evolution in micro-organisms and host-microbe systems (human gut microbiome, C. elegans-microbe interactions) are welcome to contact me. Below two outlines of computational projects:
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 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.
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 pressuren in laboratory environments are. In a theoretical analysis, we have shown that the chemostat environment can lead to diversification.
Ongoing work is showing the effect of serial dilutions.