Back to Search
Start Over
Rapid MALDI-TOF MS identification of commercial truffles.
- Source :
-
Scientific reports [Sci Rep] 2019 Nov 27; Vol. 9 (1), pp. 17686. Date of Electronic Publication: 2019 Nov 27. - Publication Year :
- 2019
-
Abstract
- Truffles are edible mushrooms with similar morphological characteristics, that make it difficult to distinguish between highly prized truffles (such as the Périgord black T. melanosporum) and inexpensive truffles (such as the Asian Black T. indicum). These biological and economic features have led to several misidentifications and/or fraudulent profit in the truffle markets. In this paper, we investigate Matrix-assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) biotyping to identify 34 commercial fresh truffles from Europe and Asia. The MALDI-TOF MS clustering rapidly distinguished seven Tuber species identified by ITS phylogenetic analysis. The tasty T. melanosporum was clearly differentiated from the Chinese and less expensive truffles. These cheaper mushrooms were marketed as T. indicum but corresponded to a mix of three species. In total, the method confirmed misidentifications in 26% of commercial specimens. Several unknown blind-coded truffles were rapidly identified, with scores >= 2, using the Bruker Biotyper algorithm against MS databases. This study demonstrates that MALDI-TOF MS is a reliable, rapid and cheaper new tool compared with molecular methods for the identification of truffle species and could be used to control frauds in the truffle markets. It could also be useful for the certification of truffle-inoculated seedlings and/or diversity in forest ecosystems.
- Subjects :
- Agaricales genetics
Algorithms
Ascomycota genetics
Asia
Cluster Analysis
DNA, Fungal genetics
Europe
Fungal Proteins chemistry
Phylogeny
Polymerase Chain Reaction
Reproducibility of Results
Agaricales chemistry
Ascomycota chemistry
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization methods
Subjects
Details
- Language :
- English
- ISSN :
- 2045-2322
- Volume :
- 9
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Scientific reports
- Publication Type :
- Academic Journal
- Accession number :
- 31776417
- Full Text :
- https://doi.org/10.1038/s41598-019-54214-x