PhD project 1:
This project is focused on understanding the link between environmental factors, gut microbiome composition and individual’s health, in particular related to cardio-metabolic diseases. The analysis will include multi-omics analysis, taking into account the effect of host genetics and metabolic parameters. This project will be performed on 10,000 participants from the population cohort Lifelines. For these individuals gut microbiome composition is available at 4 years prior to the study and will be collected again in 2021. The project will analyze the long-term stability of the gut microbiome, relations of gut bacteria to lifestyle and other environmental factors, such as air pollution, lifestyle, medication and diet, and analysis of microbiome composition in relation to health.
The Lifelines cohort and metagenomics data is described in our recent publications: https://www.biorxiv.org/content/10.1101/2020.11.27.401125v1 and DOI:10.1126/science.aad3369
PhD project 2:
This project examines the development of gut microbiome in children in the mother-baby cohort Lifelines-NEXT. >500 mother-baby pairs have been collected and extensively studied during the first year of life. The collection of stool samples will continue yearly till kids’ age of 10 years. In a subset of these kids, a more frequent stool sampling and extensive information about environment (such as diet, air quality and others) will be collected. PhD student will be actively involved in the organization of this cohort, and in processing the micirobiome data in relation to environmental factors and babies’ health.
Both projects are covered by the ExposomeNL grant, and will be performed in collaboration with other ExposomeNL groups (https://exposome.nl/). PhD students will be embedded in Department of Genetics, UMCG, and will work in close collaboration with the Microbiome group.
PhD students working on these projects will be expected to:
- Integrate and analyze the genomic-, metagenomic-, metabolomics- and proteomics datasets.
- Design, develop, implement and maintain new algorithms, applications and infrastructure components.
- Summarize and report key analytical findings in both oral and written form at work meetings, at international scientific conferences and in scientific publications.