Back

Genomic characterization and enhanced fermentation of the endophyte Stemphylium sp. (Aa22), a producer of bioactive alkyl-resorcinols

Rojas Lopez-Menchero, J.; Imperial, J.; Andres, M. F.; Diaz, C. E.; Gonzalez-Coloma, A.

2025-04-03 microbiology
10.1101/2025.04.02.646934 bioRxiv
Show abstract

The genome of the previously described endophytic fungus Stemphylium sp. (strain Aa22) has been sequenced to near completion. Phylogenomic analysis placed strain Aa22 in close proximity to Stemphylium lycopersici. Strain Aa22 had been previously reported as the producer of the bioactive alkyl-resorcinol stemphol and derivative stempholones A and B in solid culture on rice. Genome mining for biosynthetic gene clusters (BGCs) identified 42 genomic regions predicted to encode secondary metabolites production. Among them, a single type III polyketide synthase (T3PKS)-encoding ORF (FUN_008199) was identified that shared similarity with other fungal T3PKSs. T3PKSs are responsible for the biosynthesis of alkyl-resorcinols from fatty acyl-CoA substrates. This makes the T3PKS gene a likely candidate for stempholone biosynthesis and a target for future manipulation to enhance production of bioactive alkyl-resorcinols. We also studied the production of these compounds in solid rice media and in liquid PDB medium with or without the addition of talcum powder. The highest extract yield was obtained with PDB cultures, and GC-MS analysis revealed the presence of high levels of the bioactive compound stempholone A, along with two unknown compounds (retention times of 20.96 and 24.37 min). Addition of talcum powder suppressed stempholone A production and reduced chemical diversity, with accumulation of oleamide. In contrast, the rice solid media fermentation resulted in methylated fatty acids and oleamide, with no detectable stempholone.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.