报告人：Dr. Marnix H. Medema, Professor
Marnix Medema is an Assistant Professor of Bioinformatics at Wageningen University. His research group develops and applies algorithms for the (meta)genomic identification and functional prediction of microbial biosynthetic pathways, with the aim to unravel the chemical language of microbiomes. He built and co-coordinates the development of the antiSMASH software for identification of biosynthetic gene clusters and developed various additional algorithms to chart their diversity and identify their functional roles in microbiomes. Medema is recipient of NWO Rubicon, Veni and Vidi fellowships and an ERC Starting Grant, and has coordinated several international consortia studying bacterial specialized metabolites. He received several prizes for his work, including the NBIC Young Investigator Award. He is editorial board member of Natural Product Reports, mSystems and FEMS Microbes, senior editor of ISME Communications. Also, he is member of the scientific advisory board of Hexagon Bio and co-founder of Design Pharmaceuticals. From 2020-2022, he also serves as Van der Klaauw visiting professor of theoretical biology at Leiden University. He has published more than 100 peer-reviewed articles, in Science, Cell, Nature Chemical Biology, etc. With a total citation of 19000+, his current H-index is 52.
An important challenge in microbiome science is to obtain an understanding of the mechanistic basis for many microbe-associated phenotypes. Microbial specialized metabolites are important mediators of molecular interactions between microbes as well as with the host, and in a way constitute the ‘chemical language’ of the microbiome. Hence, they are of great importance from both ecological and clinical perspectives. A range of computational methods have been developed to identify these molecules and the metabolic gene clusters that encode their production, and to assess their biological activities. Here, I will highlight recent work performed in my research group on developing and applying these approaches to accelerate natural product discovery, as well as to study the roles of these pathways in microbe-microbe and host-microbe interactions in microbiomes.