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使用基质辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)鉴定食品腐败真菌:光谱数据库的开发及其在复合菌种中的应用

Identification of Food Spoilage Fungi Using MALDI-TOF MS: Spectral Database Development and Application to Species Complex.

作者信息

Rolland Nolwenn, Girard Victoria, Monnin Valérie, Arend Sandrine, Perrin Guillaume, Ballan Damien, Beau Rachel, Collin Valérie, D'Arbaumont Maëlle, Weill Amélie, Deniel Franck, Tréguer Sylvie, Pawtowski Audrey, Jany Jean-Luc, Mounier Jérôme

机构信息

bioMérieux, R&D Microbiologie, Route de Port Michaud, F-38390 La Balme les Grottes, France.

Univ Brest, INRAE, Laboratoire Universitaire de Biodiversité et Écologie Microbienne, F-29280 Plouzané, France.

出版信息

J Fungi (Basel). 2024 Jun 28;10(7):456. doi: 10.3390/jof10070456.

Abstract

Fungi, including filamentous fungi and yeasts, are major contributors to global food losses and waste due to their ability to colonize a very large diversity of food raw materials and processed foods throughout the food chain. In addition, numerous fungal species are mycotoxin producers and can also be responsible for opportunistic infections. In recent years, MALDI-TOF MS has emerged as a valuable, rapid and reliable asset for fungal identification in order to ensure food safety and quality. In this context, this study aimed at expanding the VITEK MS database with food-relevant fungal species and evaluate its performance, with a specific emphasis on species differentiation within species complexes. To this end, a total of 380 yeast and mold strains belonging to 51 genera and 133 species were added into the spectral database including species from five species complexes corresponding to , , , complexes and series Database performances were evaluated by cross-validation and external validation using 78 fungal isolates with 96.55% and 90.48% correct identification, respectively. This study also showed the capacity of MALDI-TOF MS to differentiate closely related species within species complexes and further demonstrated the potential of this technique for the routine identification of fungi in an industrial context.

摘要

真菌,包括丝状真菌和酵母,是造成全球粮食损失和浪费的主要因素,因为它们能够在整个食物链中定殖于种类繁多的食品原料和加工食品上。此外,许多真菌物种会产生霉菌毒素,还可能导致机会性感染。近年来,基质辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)已成为一种有价值、快速且可靠的真菌鉴定工具,以确保食品安全和质量。在此背景下,本研究旨在用与食品相关的真菌物种扩展VITEK MS数据库,并评估其性能,特别强调种内复合体内的物种区分。为此,总共380株属于51个属和133个物种的酵母和霉菌菌株被添加到光谱数据库中,包括来自对应于、、、复合群和系列的五个种内复合群的物种。通过交叉验证和外部验证对数据库性能进行评估 使用78株真菌分离株,正确鉴定率分别为96.55%和90.48%。本研究还展示了MALDI-TOF MS区分种内复合体内密切相关物种的能力,并进一步证明了该技术在工业环境中对真菌进行常规鉴定的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50fd/11277938/e7d668ca340d/jof-10-00456-g001.jpg

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