BERTRAND, S. | bioRxiv Science

bioRxiv2023

Global metabolome changes induced by environnementaly relevant conditions in a marine-sourced Penicillium restrictum

Marine fungi have been found in all habitats and are able to adapt to their environmental niche conditions. In this study, a combination of LC-HRMS and GC-MS analytical approaches was used to analyse the whole metabolic changes of a marine sourced Penicillium restrictum strain isolated from a marine shellfish area. The P. restrictum MMS417 strain was grown on seven different media including an ecological one with two different water sources (synthetic sea water and distilled water) conditions following the OSMAC approach. Extracts of all media were analysed by LC-HRMS (lipids and specialised metabolites profiling) and GC-MS (fatty acids profiling). Aquired data were analysed using a multiblock strategy to highlight metabolic modification in regards to water conditions and to environmentally relevant conditions (mussel-based culture medium). This revealed that fatty acid composition of lipids was the most altered part of the explored metabolisms either looking to water effect and to environmentally relevant conditions. In particular, data showed that P. restrictum MMS417 is able to produce lipids that include fatty acids usually produced by the mussel itself. This study also provides insight into the P. restrictum adaptation to marine salinity through fatty acids alteration. and shows that lipid metabolisms if far more altered in an OSMAC approach than the specialized metabolism. This study finally highlights the need for using environnementmimicking culture conditions to reveal the metabolic potentialities of marine microbes.

microbiology↗

bioRxiv2022

Reconciliation and Evolution of Penicillium rubens Genome-Scale Metabolic Networks - What about Specialised Metabolism?

In recent years, genome sequencing of filamentous fungi has revealed a high proportion of specialised metabolites with growing pharmaceutical interest. However, detecting such metabolites through in silico genome analysis does not necessarily guarantee their expression under laboratory conditions. However, one plausible strategy for enabling their production lies in modifying the growth conditions. Devising a comprehensive experimental design testing in different culture environments is time-consuming and expensive. Therefore, using in silico modelling as a preliminary step, such as Genome-Scale Metabolic Network (GSMN), represents a promising approach to predicting and understanding the observed specialised metabolite production in a given organism. To address these questions, we reconstructed a new high-quality GSMN for the Penicillium rubens Wisconsin 54-1255 strain, a commonly used model organism. Our reconstruction, iPrub22, adheres to current convention standards and quality criteria, incorporating updated functional annotations, orthology searches with different GSMN templates, data from previous reconstructions, and manual curation steps targeting primary and specialised metabolites. With a MEMOTE score of 74% and a metabolic coverage of 45%, iPrub22 includes 5,192 unique metabolites interconnected by 5,919 reactions, of which 5,033 are supported by at least one genomic sequence. Of the metabolites present in iPrub22, 13% are categorised as belonging to specialised metabolism. While our high-quality GSMN provides a valuable resource for investigating known phenotypes expressed in P. rubens, our analysis identifies bottlenecks related, in particular, to the definition of what is a specialised metabolite, which requires consensus within the scientific community. It also points out the necessity of accessible, standardised and exhaustive databases of specialised metabolites. These questions must be addressed to fully unlock the potential of natural product production in P. rubens and other filamentous fungi. Our work represents a foundational step towards the objective of rationalising the production of natural products through GSMN modelling.

bioinformatics↗