Periodic Reporting for period 1 - MAGic-MOLFUN (MAtching Genes with MOLecules for FUNctional Analysis)
Période du rapport: 2023-01-01 au 2024-12-31
Within the research program, 3 research objectives (RO) will be addressed.
We will (i) develop novel computational tools and algorithm to improve the identification and prediction quality of biosynthetic gene clusters in genomic data. Furthermore, (ii) we will use cheminformatics approaches to link metabolomics data of NPs with the genomic data of the producers, which will greatly improve the compound discovery and dereplication process. These two approaches will finally (iii) converge to be applied to find and characterize novel bioactives (antibiotics, pre-/probiotics, agrichemicals, bio-pigments) in bacteria and fungi.
The scientific training program is complemented by a comprehensive transferable skill training that will equip the DCs for todays’ demands of a successful career in industry and academia. The skills obtained in the DN will enable the DCs to work not only in natural product research but also many other data-intensive areas of biotechnology.
While the research projects are still running, several DCs already contributed to a new “Minimum Information on Tailoring Enzymes (MITE)” standard proposal, which was published as a ChemRxiv preprint (Zdouc, M. M., et al., 2024, ChemRxiv DOI: 10.26434/chemrxiv-2024-78mtl) the latest release of the MIBiG "Minimum Information on Biosynthetic Gene Clusters" standard and repository and the upcoming antiSMASH version 8.
MAGic-MOLFUN significantly contributed to several large community-driven projects, such as the latest release of the MIBIG standard and repository (version 4; publication in NAR), the new MITE standard and repository (ChemRxiv preprint) and several DCs contributed new functionalities to the gold-standard genome mining software antiSMASH (beta version of antiSMASH 8 released).