Genome mining and metabolomics reveal context-dependent biosynthetic potential in a core poplar dark septate endophyte
- 1Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
- 2Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, Tennessee, USA
Abstract
Dark septate endophytes (DSEs) are ubiquitous root-colonizing fungi characterized by melanized, septate hyphae and a frequent association with plants in stressful or nutrient-poor environments. Although DSEs are increasingly recognized for context-dependent effects on host stress resilience, the specialized metabolic capacity of many DSE lineages remains poorly resolved. Hyaloscypha finlandica is a recurrent root-associated fungus of Populus and other hosts, making it a useful system for understanding symbiotic mechanisms using multi-omics analyses. Here, we combined comparative biosynthetic gene cluster (BGC) prediction across 41 ascomycete genomes with untargeted metabolomics of H. finlandica PMI 746 grown in a defined minimal medium and a complex plant-derived medium. Benchmarking antiSMASH, FunBGCeX, and BGC-Prophet revealed broad conservation of PKS-, NRPS-, and terpene-associated biosynthetic capacity among DSEs. LC-MS/MS profiling detected strong medium-associated shifts in the extracellular chemical footprint of H. finlandica and identified putative terpenoid-, polyketide-, peptide-, siderophore-, and DHN-melanin-related features through spectral matching and in silico chemical-class inference. Authentic-standard comparison supported a probable assignment of 7-oxodehydroabietic acid, whereas most other annotations remain putative or class-level assignments. Integrating genomic and metabolomic evidence identified representative candidate intersections between encoded biosynthetic capacity and observed chemistry, but definitive BGC-product links remain targets for future genetic and structural validation. Together, these results provide a public paired-omics resource for a core Populus-associated DSE and a conservative framework for interpreting fungal multi-omics in non-model endophytes.
IMPORTANCE : Dark septate endophytes (DSEs) are widespread fungal symbionts that influence plant performance, yet their encoded and expressed metabolic capacities remain largely uncharacterized. This study provides a paired comparative genome-mining and untargeted metabolomics resource for Hyaloscypha finlandica, a recurrent Populus-associated DSE. By explicitly distinguishing biosynthetic gene cluster (BGC) prediction, spectral annotation, authentic-standard support, and unresolved BGC-Prophet assignment, this work provides a transparent reference for future studies of DSE specialized metabolism. The resulting data sets support comparative analyses across fungal endophytes and help prioritize candidate metabolites and gene clusters for targeted validation.
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BibTeX
@article{cosner2026genome,
title = {{Genome mining and metabolomics reveal context-dependent biosynthetic potential in a core poplar dark septate endophyte}},
author = {Julian B. Cosner and Sameer Mudbhari and Jack A. Orebaugh and Robert L. Hettich and Paul E. Abraham and Tomás A. Rush},
journal = {mSystems},
year = {2026},
month = sep,
doi = {10.1128/msystems.00838-26},
url = {https://doi.org/10.1128/msystems.00838-26},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Genome mining and metabolomics reveal context-dependent biosynthetic potential in a core poplar dark septate endophyte
AU - Julian B. Cosner
AU - Sameer Mudbhari
AU - Jack A. Orebaugh
AU - Robert L. Hettich
AU - Paul E. Abraham
AU - Tomás A. Rush
PY - 2026
DA - 2026/09/23
JO - mSystems
DO - 10.1128/msystems.00838-26
UR - https://doi.org/10.1128/msystems.00838-26
AB - Dark septate endophytes (DSEs) are ubiquitous root-colonizing fungi characterized by melanized, septate hyphae and a frequent association with plants in stressful or nutrient-poor environments. Although DSEs are increasingly recognized for context-dependent effects on host stress resilience, the specialized metabolic capacity of many DSE lineages remains poorly resolved. Hyaloscypha finlandica is a recurrent root-associated fungus of Populus and other hosts, making it a useful system for understanding symbiotic mechanisms using multi-omics analyses. Here, we combined comparative biosynthetic gene cluster (BGC) prediction across 41 ascomycete genomes with untargeted metabolomics of H. finlandica PMI 746 grown in a defined minimal medium and a complex plant-derived medium. Benchmarking antiSMASH, FunBGCeX, and BGC-Prophet revealed broad conservation of PKS-, NRPS-, and terpene-associated biosynthetic capacity among DSEs. LC-MS/MS profiling detected strong medium-associated shifts in the extracellular chemical footprint of H. finlandica and identified putative terpenoid-, polyketide-, peptide-, siderophore-, and DHN-melanin-related features through spectral matching and in silico chemical-class inference. Authentic-standard comparison supported a probable assignment of 7-oxodehydroabietic acid, whereas most other annotations remain putative or class-level assignments. Integrating genomic and metabolomic evidence identified representative candidate intersections between encoded biosynthetic capacity and observed chemistry, but definitive BGC-product links remain targets for future genetic and structural validation. Together, these results provide a public paired-omics resource for a core Populus-associated DSE and a conservative framework for interpreting fungal multi-omics in non-model endophytes. IMPORTANCE : Dark septate endophytes (DSEs) are widespread fungal symbionts that influence plant performance, yet their encoded and expressed metabolic capacities remain largely uncharacterized. This study provides a paired comparative genome-mining and untargeted metabolomics resource for Hyaloscypha finlandica, a recurrent Populus-associated DSE. By explicitly distinguishing biosynthetic gene cluster (BGC) prediction, spectral annotation, authentic-standard support, and unresolved BGC-Prophet assignment, this work provides a transparent reference for future studies of DSE specialized metabolism. The resulting data sets support comparative analyses across fungal endophytes and help prioritize candidate metabolites and gene clusters for targeted validation.
SN - 2379-5077
ER -