Abstract
AbstractMining filamentous fungal genomes have revealed a high proportion of specialised metabolites in the past few years. However, many of these metabolites, produced by biosynthetic gene clusters, remain silent in the laboratory, and one hypothesis for soliciting their production lies in modifying their growth conditions. Though, it remains a time-consuming and costly process. Therefore, the preliminary use ofin silicomodelling, such Genome-Scale Metabolic Network (GSMN), might be a clever alternative to explore and understand the production potential of a given organism. Consequently,Penicillium rubensWisconsin 54-1255 strain was selected as the model organism. Following current convention standards and quality criteria, the proposed reconstruction results from the following four elements. In parallel, (1) an updated functional annotation of theP. rubensgenome was carried out and supplemented by (2) an orthology search with different GSMNs templates. This first draft was enriched (3) by integrating data fromP. rubensprevious GSMN reconstructions and complemented (4) by manual curation steps targeting basal and specialised metabolites. The proposed high-quality GSMN,iPrub22, has a MEMOTE score of 68% and a metabolic coverage of 45%. The reconstruction is composed of 5,192 metabolites interconnected by 5,897 reactions, of which 5,033 are at least supported by a genomic sequence.In fine, the presence withiniPrub22 of the specialised metabolisms highlights that many bottlenecks still exist. Solving such problems is the mandatory step to get access to specialised metabolic dedicated GSMN suitable for the exploration of metabolic regulation responsible for natural product synthesis.
Publisher
Cold Spring Harbor Laboratory