Research

For the inauguration of the HUMAN project, a short video was produced in which Jakob explains the research of the group to a very broad audience.

(Unfortunately, the video is only available in German.)

The mission of the Precision Microbial Genomics group is to acquire a mechanistic understanding of the variation and evolution of microbial genomes and how those are related to human disease. Towards this goal, we develop machine learning methods, innovative bioinformatics analysis approaches, and employ long-read metagenomic sequencing.

Understanding microbiome dynamics

The microbiome has been related to a large set of different diseases in humans, including colorectal cancer, inflammatory bowel disease, and even neurodegenerative diseases. The exact mechanisms underlying these associations are often unknown, though. One challenge is that many studies have used cross-sectional study designs, meaning they take a snapshot of the microbiome. This limits the conclusions that can be drawn from the data, as the dynamic nature of the microbiome is ignored. In recent years, more and more longitudinal microbiome studies have become available. These highly complex data come hand in hand with a need for novel bioinformatic tools and analysis approaches. Our group focuses on understanding microbiome dynamics more deeply, for example through quantifying strain replacement or prophage induction.

Quantifying microbial genome dynamics through long-read sequencing

Microbial genomes evolve on timescales that are clinically relevant, which is especially important when considering the dispersal of virulence factors or antimicrobial resistance genes. Most of our understanding of this evolution is based on measuring single nucleotide changes, as this type of variation is easiest to assess with common sequencing technologies. However, large structural variations, horizontal gene transfer, or infection with integrative phages are additional types of variation that have thus far been challenging to quantify. In recent years, long-read sequencing technologies have emerged, promising unrivaled power to uncover large structural variations in microbial genomes. Our group develops computational tools for the analysis of long-read metagenomic data to uncover the modes of evolution of human-associated microbes and to quantify horizontal gene transfer in complex microbial communities.

Funding

We are extremely grateful to be supported by the HUMAN (Human Microbe Alliance for Universal Health) project, financed through the joint science funding program called “zukunft.niedersachsen” of the Ministry of Science and Culture of Lower Saxony and the Volkswagen Foundation.