Application of MALDI TOF and DART mass spectrometry as novel tools for classification of anaerobic gut fungi strains

Anaerobic gut fungi (AGF) have emerged as promising candidates for optimized biogas and biofuel production due to their unique repertoire of potent lignocellulose-degrading enzymes. However, identifying AGF strains through standard fungal DNA barcodes still poses challenges due to their distinct genomic features. This study explored the applicability of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI) and direct analysis in real-time (DART) mass spectrometry (MS) as alternative methods for AGF identification. Further, the capability of the methods to differentiate strains from different growth phases was investigated. The study found that both MALDI and DART were viable methods for AGF strain identification. MALDI proved to be a precise and robust technique for strain discrimination with prediction accuracies of 94% for unknown standard samples. Even at longer growth times (>3 weeks) MALDI achieved good prediction accuracies with 84%; however, younger cultures (72 h) were only predicted with 63% accuracy. The fast on-target lysis with minimal chemical demand yielded suitable spectra for strain differentiation. DART MS, while effective with prediction accuracies of samples with the same age of up to 93%, exhibited lower prediction accuracies for cultures of different ages, with 14% for young (72 h) and 71% for old (>3 weeks) samples. Further research could enhance the capabilities of these mass spectrometry methods for AGF identification and broaden their application to species-level discrimination and a wider range of AGF genera.

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Publication Details

Journal
Analytical and Bioanalytical Chemistry
Published
2025-03-25
DOI
https://doi.org/10.1007/s00216-025-05846-8
Citations
2
Primary Topic
Bacterial Identification and Susceptibility Testing
Type
article
Field-Weighted Citation Impact
2.64

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article

Application of MALDI TOF and DART mass spectrometry as novel tools for classification of anaerobic gut fungi strains

Christoph Kappacher, Jovan Badzoka, Tobias Schlappack, Christian Wolfgang Huck et al.
2 citations
Analytical and Bioanalytical Chemistry
Bacterial Identification and Susceptibility Testing
2.64
article

Application of MALDI TOF and DART mass spectrometry as novel tools for classification of anaerobic gut fungi strains

Christoph Kappacher, Jovan Badzoka, Tobias Schlappack, Christian Wolfgang Huck, Markus Neurauter, Julia Vinzelj, Sabine Marie Podmirseg, Matthias Rainer, S. Strobl
article en
2 citations

Abstract

Anaerobic gut fungi (AGF) have emerged as promising candidates for optimized biogas and biofuel production due to their unique repertoire of potent lignocellulose-degrading enzymes. However, identifying AGF strains through standard fungal DNA barcodes still poses challenges due to their distinct genomic features. This study explored the applicability of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI) and direct analysis in real-time (DART) mass spectrometry (MS) as alternative methods for AGF identification. Further, the capability of the methods to differentiate strains from different growth phases was investigated. The study found that both MALDI and DART were viable methods for AGF strain identification. MALDI proved to be a precise and robust technique for strain discrimination with prediction accuracies of 94% for unknown standard samples. Even at longer growth times (>3 weeks) MALDI achieved good prediction accuracies with 84%; however, younger cultures (72 h) were only predicted with 63% accuracy. The fast on-target lysis with minimal chemical demand yielded suitable spectra for strain differentiation. DART MS, while effective with prediction accuracies of samples with the same age of up to 93%, exhibited lower prediction accuracies for cultures of different ages, with 14% for young (72 h) and 71% for old (>3 weeks) samples. Further research could enhance the capabilities of these mass spectrometry methods for AGF identification and broaden their application to species-level discrimination and a wider range of AGF genera.

Analytical and Bioanalytical ChemistryVol. 417(15)
Universität Innsbruck (AT)
Austrian Science Fund, Medizinische Universität Innsbruck, Universität Innsbruck
Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Bacterial Identification and Susceptibility Testing
2.64
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