A scalable PDMS extraction method for profiling fungal volatile compounds

BACKGROUND: Fungal volatile organic compounds (FVOCs) play key roles in fungal ecology, physiology, and biotechnological applications, but inconsistent sampling and analytical methods limit biological interpretation and cross-study comparability, underscoring the need for a standardized, validated workflow. RESULTS: We developed and validated a polydimethylsiloxane (PDMS)-based volatilomics workflow and evaluated its performance across key methodological dimensions, including solvent extraction bias, static versus dynamic sampling, sorbent reuse, temporal emission resolution, and discrimination of physiological states. Solvent choice (dichloromethane vs. diethyl ether) influenced the quantitative recovery of individual compounds but did not affect the overall FVOC composition detected. Static PDMS and dynamic push-pull sampling produced distinct yet complementary volatilome profiles, with method-specific enrichment across compound classes. Reconditioned PDMS tubing performed equivalently to fresh tubing across repeated deployments, with no detectable decline in compound recovery and multivariate structure. Sequential 96-h sampling captured clear temporal emission patterns in both Trichoderma atroviride and Grosmannia clavigera, revealing species-specific emission trajectories consistent with metabolic stages. Application of the optimized workflow further distinguished T. atroviride morphotypes (white vs. green), which maintained distinct volatile profiles over time and exhibited morphotype-specific emission dynamics in key compounds. CONCLUSIONS: The PDMS-based workflow presented here provides a robust and reproducible framework for FVOC analysis, effectively addressing methodological biases, resolving temporal emission dynamics, and discriminating among physiological states. Standardizing PDMS sampling and extraction substantially enhance the biological interpretability and comparability of FVOC data, enabling broader and more reliable applications in fungal ecology, physiology, and biotechnology.

Authors

Institutions

Publication Details

Journal
Fungal Biology and Biotechnology
Published
2026-05-11
DOI
https://doi.org/10.1186/s40694-026-00213-3
Primary Topic
Indoor Air Quality and Microbial Exposure
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A scalable PDMS extraction method for profiling fungal volatile compounds

Rashaduz Zaman, Nadir Erbilgin, Guncha Ishangulyyeva, James F. Cahill et al.
Fungal Biology and Biotechnology
Indoor Air Quality and Microbial Exposure
article

A scalable PDMS extraction method for profiling fungal volatile compounds

Rashaduz Zaman, Nadir Erbilgin, Guncha Ishangulyyeva, James F. Cahill, Heather T. K. Anderson, Isaac Peetoom Heida
article en

Abstract

BACKGROUND: Fungal volatile organic compounds (FVOCs) play key roles in fungal ecology, physiology, and biotechnological applications, but inconsistent sampling and analytical methods limit biological interpretation and cross-study comparability, underscoring the need for a standardized, validated workflow. RESULTS: We developed and validated a polydimethylsiloxane (PDMS)-based volatilomics workflow and evaluated its performance across key methodological dimensions, including solvent extraction bias, static versus dynamic sampling, sorbent reuse, temporal emission resolution, and discrimination of physiological states. Solvent choice (dichloromethane vs. diethyl ether) influenced the quantitative recovery of individual compounds but did not affect the overall FVOC composition detected. Static PDMS and dynamic push-pull sampling produced distinct yet complementary volatilome profiles, with method-specific enrichment across compound classes. Reconditioned PDMS tubing performed equivalently to fresh tubing across repeated deployments, with no detectable decline in compound recovery and multivariate structure. Sequential 96-h sampling captured clear temporal emission patterns in both Trichoderma atroviride and Grosmannia clavigera, revealing species-specific emission trajectories consistent with metabolic stages. Application of the optimized workflow further distinguished T. atroviride morphotypes (white vs. green), which maintained distinct volatile profiles over time and exhibited morphotype-specific emission dynamics in key compounds. CONCLUSIONS: The PDMS-based workflow presented here provides a robust and reproducible framework for FVOC analysis, effectively addressing methodological biases, resolving temporal emission dynamics, and discriminating among physiological states. Standardizing PDMS sampling and extraction substantially enhance the biological interpretability and comparability of FVOC data, enabling broader and more reliable applications in fungal ecology, physiology, and biotechnology.

Fungal Biology and BiotechnologyVol. 13(1)
University of Alberta (CA)
Results Driven Agriculture Research, V. Kann Rasmussen Foundation, University of Alberta
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 7%
Indoor Air Quality and Microbial Exposure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.