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Gene flow networks in animals, the food chain and the environment

This project is part of the overarching project 'DiSSeMINATE - Drivers of Selection and Spread of Mobile Genetic Elements INvolved in Antimicrobial Resistance'.

Timeline

2019 – 2023

Group and collaboration

Collaboration: Prof. Rob Willems (UMC Utrecht), Dr. Anita Schürch (UMC Utrecht)

PhD student: Jesse Kerkvliet

Project description

Dissemination of important traits between different hosts and environments can create new phenotypes, shape microbial composition and strongly contribute to health and disease in humans and animals. Particularly traits encoded on mobile genetic elements (MGEs), such as plasmids, integrons and transposons, are highly dynamic because they transmit with ease and result in extensive gene flow. The most prominent example is the spread of antimicrobial resistance genes through different hosts and environments.

Our objective is to develop novel methods to reconstruct dissemination networks of mobile genes (including antimicrobial resistance genes) from metagenomic data of the microbial community of food-producing animals, the environment or farm environment, as well as the potentially exposed healthy population. Across these sources and ecosystems we will assess gene flow networks.

This will enable us to estimate whether gene pool distributions are influenced by geography, as a result of direct transmission events, or by ecology as a result of selection. This insight will generate a detailed picture of bacterial, viral and MGE epidemiology and will contribute to a better understanding of factors influencing the composition of networks of these genetic vehicles in complex ecosystems and their contribution to human and animal health.


Complex Systems & Metagenomics is the overarching theme for more than 10 PhD tracks in NCOH projects to create new interdisciplinary, inter-thematic, and inter-institutional research collaborations.

PhD student interview

Interview: ‘I value that my research has social relevance’

Jesse Kerkvliet, a bio-computer scientist, likes working with interesting model systems, but also thinks it’s important his research aims at solving real world problems.

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