I am a bioinformatician with a passion for microbial ecosystems, bacterial evolution and developing computational systems to tackle these subjects in a combined perspective.

During my early career I was working at the University of Constance (Germany) and the University of Sussex (UK) on bacterial evolution and tracking outbreaks of pathogens through following changes in their genomes. Moving from a genome centric view to a metagenomic view of whole microbial ecosystems, I was working during my PhD at the University of Brussels (Belgium) on bacterial associations to complex diseases such as IBD, obesity and Diabetes. For this, I developed bioinformatic pipelines to process 16S data (LotuS,) as well as the statistical tools.

In my postdoc at EMBL Heidelberg (Germany), I was continuing my research on association to the human microbiome of complex diseases such as Diabetes and Parkinson’s disease, among others. My interests soon developed to track strains in the metagenomic datasets. Further, I de novo assembled and binned so far unknown species, one of which I could associate to antibiotic usage. In parallel to this I was interested in environmental metagenomics, where I could show that the Arctic and Antarctic microbial communities are more similar than expected under isolation as well as a strong association between antibiotics and the ratio of bacteria-to-fungi on a global scale. For these projects, I further refined my pipelines, developing the tools necessary to process shotgun metagenomics data (MATAFILER) to handle extremely large metagenomic datasets computationally (rtk; sdm).

I joined the Quadram Institute and Earlham Institute in early 2019 and my group develops metagenomic tools to track bacterial strains at high resolutions, predict their genomic capabilities and explore their associations to diseases.

Key Publications

Hildebrand, F., Moitinho-Silva, L., Blasche, S., Jahn, M.T., Gossmann, T.I., Huerta-Cepas, J., Hercog, R., Luetge, M., Bahram, M., Pryszlak, A., et al. (2019). Antibiotics-induced monodominance of a novel gut bacterial order. Gut 68, 1781–1790 https://doi.org/10.1136/gutjnl-2018-317715

Bahram* M, Hildebrand* F, Forslund K, et al. (2018) Towards the structure and function of the global topsoil microbiome. Nature 560:233–. https://doi.org/10.1038/s41586-018-0386-6

Costea* P, Hildebrand* F, Arumugam M, Baeckhed F, et al. (2018) Enterotypes in the landscape of gut microbial community composition. Nature Microbiology 3(1): 816. https://doi.org/10.1038/s41564-017-0072-8

Forslund* K, Hildebrand* F, Nielsen* T, et al. (2015). Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature, 528(7581), 262266. https://doi.org/10.1038/nature15766

*Hildebrand F, *Nguyen ATL, Brinkman B, et al. (2013). Inflammation-associated enterotypes, host genotype, cage and inter-individual effects drive gut microbiota variation in common laboratory mice. Genome Biology, 14(1) https://doi.org/10.1186/gb-2013-14-1-r4