The newly installed group aims at deciphering how environmental toxins, e.g., particles, radiation or chemicals, accelerate the aging process at the molecular level and promote the development of associated diseases.
In the past, the group leader used multi-omics approaches to examine so called alternative animal models of aging research. These are species that display exceptional lifespans often in combination with other interesting aging traits. We analyzed, e.g., samples both from very short-lived organisms, such as Nothobranchius killifishes as well as from long-lived ones, such as clownfishes and even non-aging species like Hydra. Taking an evolutionary perspective, we often compared the genomes, epigenomes, and transcriptomes of these alternative animal models with those of closely related species that do not exhibit such extreme aging traits. A special focus is on mole-rat species such as the naked mole-rat. These animals not only live to an exceptional age for rodents, with lifespans of more than 30 years, but also almost never develop cancer. In addition, aging rates and lifespans vary strongly depending on social and reproductive status within the respective colony.
As bioinformaticians, we work closely with different zoological research groups that maintain alternative model organisms. Complementing our data analyses, we are developing new tools and methods such as pipelines for genome-wide detection of positively selected genes and models to study epigenomic evolution.
In the future, we plan to use our evolutionary models to find out which genetic and epigenetic adaptations allow certain species to withstand extreme environmental stresses. For example, naked mole-rats can tolerate carbon dioxide concentrations that would kill both closely related species and humans.
In addition, we will apply our multi-omics methods to unique samples available at the IUF to identify genes and pathways that are altered by exposure to environmental toxins. In particular, we will focus on epigenetic changes that alter gene regulation in the longer term, i.e., potentially beyond the period of actual exposure. To this end, we will study bioinformatically samples from cell cultures and animal models as well as from humans exposed to e.g., air pollution, neurotoxins or radiation.