描述发酵食品中真菌群落的元条形码分类标记比较

Olivier Rué, Monika Coton, Eric Dugat-Bony, Kate Howell, Françoise Irlinger, Jean-Luc Legras, Valentin Loux, Elisa Michel, Jérôme Mounier, Cécile Neuvéglise, Delphine Sicard
{"title":"描述发酵食品中真菌群落的元条形码分类标记比较","authors":"Olivier Rué, Monika Coton, Eric Dugat-Bony, Kate Howell, Françoise Irlinger, Jean-Luc Legras, Valentin Loux, Elisa Michel, Jérôme Mounier, Cécile Neuvéglise, Delphine Sicard","doi":"10.24072/pcjournal.321","DOIUrl":null,"url":null,"abstract":"Next generation sequencing offers several ways to study microbial communities. For agri-food sciences, identifying species in diverse food ecosystems is key for both food sustainability and food security. The aim of this study was to compare metabarcoding pipelines and markers to determine fungal diversity in food ecosystems, from Illumina short reads. We built mock communities combining the most representative fungal species in fermented meat, cheese, wine and bread. Four barcodes (ITS1, ITS2, D1/D2 and RPB2) were tested for each mock and on real fermented products. We created a database, including all mock species sequences for each barcode to compensate for the lack of curated data in available databases. Four bioinformatics tools (DADA2, QIIME, FROGS and a combination of DADA2 and FROGS) were compared. Our results clearly showed that the combined DADA2 and FROGS tool gave the most accurate results. Most mock community species were not identified by the RPB2 barcode due to unsuccessful barcode amplification. When comparing the three rDNA markers, ITS markers performed better than D1/D2, as they are better represented in public databases and have better specificity to distinguish species. Between ITS1 and ITS2, differences in the best marker were observed according to the studied ecosystem. While ITS2 is best suited to characterize cheese, wine and fermented meat communities, ITS1 performs better for sourdough bread communities. Our results also emphasized the need for a dedicated database and enriched fungal-specific public databases with novel barcode sequences for 118 major species in food ecosystems.","PeriodicalId":74413,"journal":{"name":"Peer community journal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Comparison of metabarcoding taxonomic markers to describe fungal communities in fermented foods\",\"authors\":\"Olivier Rué, Monika Coton, Eric Dugat-Bony, Kate Howell, Françoise Irlinger, Jean-Luc Legras, Valentin Loux, Elisa Michel, Jérôme Mounier, Cécile Neuvéglise, Delphine Sicard\",\"doi\":\"10.24072/pcjournal.321\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Next generation sequencing offers several ways to study microbial communities. For agri-food sciences, identifying species in diverse food ecosystems is key for both food sustainability and food security. The aim of this study was to compare metabarcoding pipelines and markers to determine fungal diversity in food ecosystems, from Illumina short reads. We built mock communities combining the most representative fungal species in fermented meat, cheese, wine and bread. Four barcodes (ITS1, ITS2, D1/D2 and RPB2) were tested for each mock and on real fermented products. We created a database, including all mock species sequences for each barcode to compensate for the lack of curated data in available databases. Four bioinformatics tools (DADA2, QIIME, FROGS and a combination of DADA2 and FROGS) were compared. Our results clearly showed that the combined DADA2 and FROGS tool gave the most accurate results. Most mock community species were not identified by the RPB2 barcode due to unsuccessful barcode amplification. When comparing the three rDNA markers, ITS markers performed better than D1/D2, as they are better represented in public databases and have better specificity to distinguish species. Between ITS1 and ITS2, differences in the best marker were observed according to the studied ecosystem. While ITS2 is best suited to characterize cheese, wine and fermented meat communities, ITS1 performs better for sourdough bread communities. Our results also emphasized the need for a dedicated database and enriched fungal-specific public databases with novel barcode sequences for 118 major species in food ecosystems.\",\"PeriodicalId\":74413,\"journal\":{\"name\":\"Peer community journal\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Peer community journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24072/pcjournal.321\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Peer community journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24072/pcjournal.321","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

下一代测序提供了几种研究微生物群落的方法。对于农业食品科学来说,确定不同粮食生态系统中的物种是粮食可持续性和粮食安全的关键。本研究的目的是比较元条形码管道和标记,以确定食物生态系统中真菌的多样性,从Illumina短读。我们将发酵肉类、奶酪、葡萄酒和面包中最具代表性的真菌物种结合起来,建立了模拟群落。4种条形码(ITS1、ITS2、D1/D2和RPB2)分别对每个模拟发酵产品和真实发酵产品进行检测。我们创建了一个数据库,包括每个条形码的所有模拟物种序列,以弥补可用数据库中管理数据的不足。比较4种生物信息学工具(DADA2、QIIME、FROGS以及DADA2和FROGS的组合)。我们的结果清楚地表明,DADA2和FROGS工具的组合给出了最准确的结果。由于RPB2条形码扩增不成功,大多数模拟群落物种无法被识别。在比较三种rDNA标记时,ITS标记优于D1/D2标记,因为ITS标记在公共数据库中具有更好的代表性,并且具有更好的区分物种的特异性。在ITS1和ITS2之间,根据所研究的生态系统,观察到最佳标记的差异。ITS2最适合描述奶酪、葡萄酒和发酵肉类群落,而ITS1对酵母面包群落的表现更好。我们的研究结果还强调需要建立一个专门的数据库和丰富的真菌特异性公共数据库,其中包含118种食物生态系统中主要物种的新型条形码序列。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of metabarcoding taxonomic markers to describe fungal communities in fermented foods
Next generation sequencing offers several ways to study microbial communities. For agri-food sciences, identifying species in diverse food ecosystems is key for both food sustainability and food security. The aim of this study was to compare metabarcoding pipelines and markers to determine fungal diversity in food ecosystems, from Illumina short reads. We built mock communities combining the most representative fungal species in fermented meat, cheese, wine and bread. Four barcodes (ITS1, ITS2, D1/D2 and RPB2) were tested for each mock and on real fermented products. We created a database, including all mock species sequences for each barcode to compensate for the lack of curated data in available databases. Four bioinformatics tools (DADA2, QIIME, FROGS and a combination of DADA2 and FROGS) were compared. Our results clearly showed that the combined DADA2 and FROGS tool gave the most accurate results. Most mock community species were not identified by the RPB2 barcode due to unsuccessful barcode amplification. When comparing the three rDNA markers, ITS markers performed better than D1/D2, as they are better represented in public databases and have better specificity to distinguish species. Between ITS1 and ITS2, differences in the best marker were observed according to the studied ecosystem. While ITS2 is best suited to characterize cheese, wine and fermented meat communities, ITS1 performs better for sourdough bread communities. Our results also emphasized the need for a dedicated database and enriched fungal-specific public databases with novel barcode sequences for 118 major species in food ecosystems.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信