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Identification of pathogenic fungi with an optoelectronic nose
Yinan Zhang1, Jon R Askim, Wenxuan Zhong
1Department of Chemistry, University of Illinois at Urbana-Champaign, 600 S. Mathews Av., Urbana, IL 61801, USA. ksuslick@illinois.edu.
Abstract:
Human fungal infections have gained recent notoriety following contamination of pharmaceuticals in the compounding process. Such invasive infections are a more serious global problem, especially for immunocompromised patients. While superficial fungal infections are common and generally curable, invasive fungal infections are often life-threatening and much harder to diagnose and treat. Despite the increasing awareness of the situation's severity, currently available fungal diagnostic methods cannot always meet diagnostic needs, especially for invasive fungal infections. Volatile organic compounds produced by fungi provide an alternative diagnostic approach for identification of fungal strains. We report here an optoelectronic nose based on a disposable colorimetric sensor array capable of rapid differentiation and identification of pathogenic fungi based on their metabolic profiles of emitted volatiles. The sensor arrays were tested with 12 human pathogenic fungal strains grown on standard agar medium. Array responses were monitored with an ordinary flatbed scanner. All fungal strains gave unique composite responses within 3 hours and were correctly clustered using hierarchical cluster analysis. A standard jackknifed linear discriminant analysis gave a classification accuracy of 94% for 155 trials. Tensor discriminant analysis, which takes better advantage of the high dimensionality of the sensor array data, gave a classification accuracy of 98.1%. The sensor array is also able to observe metabolic changes in growth patterns upon the addition of fungicides, and this provides a facile screening tool for determining fungicide efficacy for various fungal strains in real time.
Insights
An optoelectronic nose using colorimetric sensors can rapidly identify pathogenic fungi by detecting their volatile organic compounds. This technology achieved 98.1% accuracy, offering a new tool for diagnosing fungal infections.
Area of Science:
- Mycology
- Analytical Chemistry
- Biotechnology
Background:
- Invasive fungal infections pose a significant global health threat, particularly to immunocompromised individuals.
- Current diagnostic methods for invasive fungal infections are often insufficient, necessitating novel approaches.
- Fungal volatile organic compounds (VOCs) offer a promising avenue for rapid fungal identification.
Purpose of the Study:
- To develop and validate an optoelectronic nose system for the rapid differentiation and identification of pathogenic fungi.
- To assess the diagnostic accuracy of the system using a colorimetric sensor array and advanced data analysis.
- To evaluate the system's potential for real-time screening of fungicide efficacy.
Main Methods:
- Utilized a disposable colorimetric sensor array integrated into an optoelectronic nose.
- Exposed sensor arrays to 12 human pathogenic fungal strains grown on agar medium.
- Monitored array responses using a flatbed scanner and analyzed data with hierarchical cluster analysis, jackknifed linear discriminant analysis, and tensor discriminant analysis.
- Assessed metabolic changes in response to fungicide addition.
Main Results:
- All tested fungal strains produced unique volatile profiles detectable by the sensor array within 3 hours.
- Hierarchical cluster analysis successfully grouped fungal strains based on their volatile emissions.
- Jackknifed linear discriminant analysis achieved 94% classification accuracy, while tensor discriminant analysis reached 98.1% accuracy.
- The system demonstrated the ability to monitor fungal metabolic responses to fungicides in real time.
Conclusions:
- The developed optoelectronic nose system provides a rapid, accurate, and non-invasive method for identifying pathogenic fungi.
- This technology holds significant potential for improving the diagnosis of invasive fungal infections.
- The system serves as a valuable tool for real-time fungicide efficacy screening, aiding in the development of new antifungal treatments.
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