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Comparative Genomics Reveals Extensive Biosynthetic Diversity and Lineage-Specific Metabolic Potential Across
Biju Vadakkemukadiyil Chellappan1, Hashem Al-Sheikh1
1Department of Biological Sciences, College of Science, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Abstract:
The genus Talaromyces is an important source of structurally diverse secondary metabolites, yet the conservation and diversification of its biosynthetic potential remain incompletely understood at the genus level. Here, we performed comparative genomic and biosynthetic analyses of 24 Talaromyces species to characterize biosynthetic gene cluster (BGC) diversity, gene cluster family (GCF) distribution, and potential relevance to antifungal natural-product discovery. Genome mining identified 1550 BGCs, ranging from 41 to 81 per species, with polyketide synthase (PKS), nonribosomal peptide synthetase (NRPS), terpene, and hybrid PKS-NRPS pathways representing the major biosynthetic classes. The BGCs were grouped into 828 GCFs, of which 567 (68.5%) were species-specific, indicating extensive lineage-level diversification. In contrast, several metabolite-associated biosynthetic systems were conserved across multiple species. Notably, squalestatin S1-associated BGCs occurred in all 24 species but were distributed among 15 distinct GCFs, demonstrating conservation of predicted biosynthetic capacity despite substantial variation in cluster architecture. GCFs associated with characterized antifungal metabolites, including ilicicolin H, leucinostatins, zopfiellin, sordarin, and monorden/monocillins, were also identified. Moreover, 553 GCFs (66.8%) lacked close matches to characterized MIBiG clusters and were classified as chemically unresolved, highlighting a substantial unexplored biosynthetic repertoire. Overall, these findings reveal extensive diversification alongside selective conservation of secondary-metabolite pathways across Talaromyces and provide a genomic framework for prioritizing species and BGCs for antifungal natural-product discovery and biocontrol-oriented investigation. These genome-based predictions require metabolomic and functional validation to confirm metabolite production and biological activity.
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