Data curation and cross-instrument variability influence GC-MS-based metabolite profiling of endophytic fungi associated with Moringa oleifera.

Authors

Markwo Ali, Bekri Melka Abdo, Salar Hafez-Ghoran, Dorcas Osei-Safo, Robert Kingsford-Adaboh, Atia-Tul Wahab, Muhammad Iqbal Choudhary

Published in

Journal of applied microbiology. Oct 06, 2026. Epub Oct 06, 2026.

Abstract

This study presents an exploratory assessment of volatile and semi-volatile metabolites produced by endophytic fungi associated with Moringa oleifera using gas chromatography-mass spectrometry (GC-MS), emphasising metabolite occurrence and analytical consistency.
Twelve endophytic fungal isolates were recovered from leaf and twig tissues and putatively identified by morphology and internal transcribed spacer (ITS) sequencing. Each isolate was cultivated as a single, unreplicated 1 L shake-flask culture in Sabouraud dextrose broth (28°C, 120 rpm, 12-20 days), and the cell-free broth extracted with an equal volume of n-hexane. Initial spectral matching generated a broad set of compound annotations. Curation removed analytical artefacts, contaminants (including siloxanes and phthalates), and low-confidence identifications, leaving a small set of biologically plausible, tentatively identified metabolites, among them furfuryl alcohol, kojic acid, lauric acid, palmitic acid, and undecylenic acid. Cross-instrument comparison on two GC-MS platforms revealed substantial variability when instrument-specific libraries were used; commercial library matching returned twelve tentatively identified metabolites in one extract and six in the other on the second platform, and none on the first. No compound was recovered on both platforms.
Metabolite annotation proved highly sensitive to instrument configuration and to the choice of spectral library: the same extracts yielded entirely non-overlapping compound lists on two platforms from the same manufacturer using the same detector type and ionisation energy. These findings highlight the importance of stringent data curation, cautious spectral interpretation, and analytical standardisation in GC-MS-based metabolomics. All assignments are tentative, based on library matching without co-injection of authentic standards.

PMID:
42836553
Bibliographic data and abstract were imported from PubMed on 06 Oct 2026.

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