SP 3

Host genetics meets microbiome - a systems approach

Numerous microorganisms live in and on the human body, where these microbes outnumber the human cells by a factor of ten and the gene set is 150-fold larger than the set of human genes. Most of them colonize the gut playing a key role in amino acid and vitamin biosynthesis, dietary energy harvest, and immune development. This collection of microorganisms (the microbiome) plays a role in diseases such as adiposity and bowel inflammation, and thus serves as a promising avenue for clinical application via directed manipulation.

The aim of this subproject is to characterize the capacity of the human microbiome, its interaction with the host (= human) and its environment, and its contribution to disease.


The "normal" microbiota is influenced by genetic, phenotypic and environmental factors and is different compared to the "diseased" state. 

To characterize microbial profiles, stool samples are collected. DNA is extracted and the 16S rRNA gene is amplified and sequenced. The 16S rRNA gene is present in all bacteria, but varies between bacterial species, enabling classification through molecular "barcoding".

To investigate the “normal” microbiome we use stool samples of ~1000 healthy individuals from Northern Germany (PopGen study) as well as 1500 healthy and 500 obese individuals from a second study (Food Chain Plus = "FoCus").
Stool samples of individuals suffering from inflammatory bowel diseases (IBD, KINDRED study) (ulcerative colitis, Crohn´s disease), but also other inflammatory diseases like lupus, rheumatoid arthritis, ankylosing spondylitis, irritable bowel syndrome or intestinal infections represent the diseased microbiome.
Besides the microbial composition of stool samples, we also have phenotypic- (smoking, food patterns), genetic- as well as serum and stool metabolite data at hand. The comprehension of all these data allows a characterization of factors influencing the normal and the diseased microbiome. Furthermore, disease progression and related changes in the microbiome can be investigated, enabling a differentiation between diseases as well as a prediction of patients with a severe course of disease or adverse response to therapy.

Keywords: microbiome, genotype, phenotype

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