Related Experiment Video
Updated: Mar 17, 2026
Isolation of Culturable Yeasts and Molds from Soils to Investigate Fungal Population Structure
Published on: May 27, 2022
eNose technology can detect and classify human pathogenic molds in vitro: a proof-of-concept study of Aspergillus
K de Heer1,2, S I Vonk1, M Kok1
1Department of Hematology, Academic Medical Center, Amsterdam, The Netherlands.
Abstract:
Invasive pulmonary mold disease (IPMD) is often fatal in neutropenic patients. This is because IPMD is difficult to diagnose timely, especially when non-Aspergillus molds are the causative agent, as they are usually not associated with a positive galactomannan assay. In 2013 we showed that exhaled breath analysis might be used to diagnose invasive aspergillosis through profiling of patterns in exhaled volatile organic compounds (VOCs) by electronic nose (eNose) technology. The current study aimed to determine (1) whether molds can be discriminated from other microorganisms (using two mold species: Aspergillus fumigatus and a pathogenic mold not associated with a positive galactomannan assay, i.c. Rhizopus oryzae) and (2) whether both molds can be discriminated from each other. First, we cultured strains of Streptococcus pneumoniae, Escherichia coli, Pseudomonas aeruginosa, Candida albicans, A. fumigatus and R. oryzae in separate airtight bottles. We examined whether an eNose (Cyranose 320) could discriminate the headspaces of bottles with molds from those with bacteria/yeasts. Second, we examined whether an eNose could discriminate A. fumigatus and R. oryzae. Diagnostic algorithms were created using canonical discriminant analysis after principle component analysis. Primary outcome parameter was the validated accuracy. The eNose discriminated A. fumigatus from bacteria/yeasts with a cross-validated accuracy of 92.9% (sensitivity 95.2%, specificity 91.9%). The eNose had an accuracy (validated using split-half analysis) of 100% in discriminating A. fumigatus from R. oryzae. Our study suggests that an eNose can identify and classify molds in vitro. This warrants prospective in vivo studies aimed at detecting and classifying IPMD using exhaled breath.
Insights
An electronic nose (eNose) shows promise for diagnosing invasive pulmonary mold disease (IPMD). This technology can accurately identify molds, including Aspergillus fumigatus and Rhizopus oryzae, in vitro, paving the way for breath-based diagnostics.
Area of Science:
- Medical Mycology
- Diagnostic Technology
- Respiratory Medicine
Background:
- Invasive pulmonary mold disease (IPMD) poses a significant threat to neutropenic patients, often due to delayed diagnosis.
- Current diagnostic methods, like galactomannan assays, are limited, particularly for non-Aspergillus molds.
- Exhaled breath analysis using electronic nose (eNose) technology has shown potential for diagnosing invasive aspergillosis.
Purpose of the Study:
- To evaluate the capability of an eNose to discriminate between molds and other microorganisms (bacteria/yeasts).
- To assess the eNose's ability to differentiate between two specific mold species: Aspergillus fumigatus and Rhizopus oryzae.
- To determine the diagnostic accuracy of eNose technology for mold identification in vitro.
Main Methods:
- Culturing of microbial strains including Streptococcus pneumoniae, Escherichia coli, Pseudomonas aeruginosa, Candida albicans, Aspergillus fumigatus, and Rhizopus oryzae in separate airtight bottles.
- Analysis of microbial headspace volatile organic compounds (VOCs) using an electronic nose (Cyranose 320).
- Development of diagnostic algorithms using canonical discriminant analysis and principal component analysis for classification and accuracy validation.
Main Results:
- The eNose achieved a cross-validated accuracy of 92.9% in discriminating Aspergillus fumigatus from bacteria/yeasts (sensitivity 95.2%, specificity 91.9%).
- The eNose demonstrated 100% accuracy in discriminating between Aspergillus fumigatus and Rhizopus oryzae using split-half validation.
- In vitro analysis confirmed the eNose's capability to identify and classify different mold species.
Conclusions:
- Electronic nose technology can effectively identify and differentiate between various mold species in vitro.
- These findings support the potential of eNose-based exhaled breath analysis for the early detection and classification of invasive pulmonary mold disease.
- Further in vivo studies are warranted to validate these promising results for clinical application in diagnosing IPMD.
