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Background <p>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.</p> Results <p>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 <i>Trichoderma atroviride</i> and <i>Grosmannia clavigera</i>, revealing species-specific emission trajectories consistent with metabolic stages. Application of the optimized workflow further distinguished <i>T. atroviride</i> morphotypes (white vs. green), which maintained distinct volatile profiles over time and exhibited morphotype-specific emission dynamics in key compounds.</p> Conclusions <p>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.</p>

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A scalable PDMS extraction method for profiling fungal volatile compounds

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月11日

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

摘要

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.