Abstract
Truffles of the Tuber species are known as expensive foods, mainly for their distinct aroma and taste. This high price makes them a profitable target of food fraud, e.g., the misdeclaration of cheaper truffle species as expensive ones. While many studies investigated truffles on the metabolomic level or the volatile organic compounds extruded by them, research at the proteome level as a phenotype determining basis is limited. In this study, a bottom-up proteomic approach based on LC-MS/MS measurements in data-independent acquisition mode was performed to analyze the truffle species Tuber aestivum, Tuber albidum pico, Tuber indicum, Tuber magnatum, and Tuber melanosporum, and a protein atlas of the investigated species was obtained. The yielded proteomic fingerprints are unique for each of the of the five truffle species and can now be used in case of suspected food fraud. First, a comprehensive spectral library containing 9000 proteins and 50,000 peptides was generated by two-dimensional liquid chromatography coupled to tandem mass spectrometry (2D-LC-MS/MS). Then, samples of the truffle species were analyzed in data-independent acquisition (DIA) proteomics mode yielding 2715 quantified proteins present in all truffle samples. Individual species were clearly distinguishable by principal component analysis (PCA). Quantitative proteome fingerprints were generated from 2066 ANOVA significant proteins, and side-by-side comparisons of truffles were done by T-tests. A further aim of this study was the annotation of functions for the identified proteins. For Tuber magnatum and Tuber melanosporum conclusive links to their superior aroma were found by enrichment of proteins responsible for sulfur-metabolic processes in comparison with other truffles. The obtained data in this study may serve as a reference library for food analysis laboratories in the future to tackle food fraud by misdeclaration of truffles. Further identified proteins with their corresponding abundance values in the different truffle species may serve as potential protein markers in the establishment of targeted analysis methods. Lastly, the obtained data may serve in the future as a basis for deciphering the biochemistry of truffles more deeply as well, when protein databases of the different truffle species will be more complete.
Highlights
Truffles are ascomycete fungi in the genus Tuber that form subterranean fruiting bodies
To determine which methods recovered the most proteins for ground truffle powder, three different established sample preparation protocols for bottom-up proteomics by LC-MS/MS were tested to prepare ground truffle powder from one sample of T. indicum
The data-independent acquisition (DIA) approach included the generation of a comprehensive spectral library consisting of 9170 proteins from T. magnatum, T. melanosporum, and T. aestivum
Summary
Truffles are ascomycete fungi in the genus Tuber that form subterranean fruiting bodies They often grow in symbiotic relationships with the roots of trees and have a pronounced taste and, more important, smell to attract animals for spreading their spores while being dug up and eaten [1]. In 2013, Islam et al were the first to do a combined deep proteomics and bioinformatics approach for taking a comprehensive look on a whole global truffle proteome, using the black Perigord truffle (Tuber melanosporum, strain Mel28) as an example. They functionally annotated the proteome and used sequential BLAST search strategies to match proteins to fungal homologues. Spectral libraries are usually generated by running a pooled part of the samples of interest in data-dependent acquisition (DDA) mode
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
