Giusti Alice, Ricci Enrica, Gasperetti Laura, Galgani Marta, Polidori Luca, Verdigi Francesco, Narducci Roberto, Armani Andrea
FishLab, Department of Veterinary Sciences, University of Pisa, Viale delle Piagge 2, 56124 Pisa, Italy.
Experimental Zooprophylactic Institute of Lazio and Tuscany M. Aleandri, UOT Toscana Nord, SS Abetone e Brennero 4, 56124 Pisa, Italy.
Foods. 2021 May 25;10(6):1193. doi: 10.3390/foods10061193.
This study aims at building an ITS gene dataset to support the Italian Health Service in mushroom identification. The target species were selected among those mostly involved in regional (Tuscany) poisoning cases. For each target species, all the ITS sequences already deposited in GenBank and BOLD databases were retrieved and accurately assessed for quality and reliability by a systematic filtering process. Wild specimens of target species were also collected to produce reference ITS sequences. These were used partly to set up and partly to validate the dataset by BLAST analysis. Overall, 7270 sequences were found in the two databases. After filtering, 1293 sequences (17.8%) were discarded, with a final retrieval of 5977 sequences. Ninety-seven ITS reference sequences were obtained from 76 collected mushroom specimens: 15 of them, obtained from 10 species with no sequences available after the filtering, were used to build the dataset, with a final taxonomic coverage of 96.7%. The other 82 sequences (66 species) were used for the dataset validation. In most of the cases (n = 71; 86.6%) they matched with identity values ≥ 97-100% with the corresponding species. The dataset was able to identify the species involved in regional poisoning incidents. As some of these species are also involved in poisonings at the national level, the dataset may be used for supporting the National Health Service throughout the Italian territory. Moreover, it can support the official control activities aimed at detecting frauds in commercial mushroom-based products and safeguarding consumers.
本研究旨在构建一个内转录间隔区（ITS）基因数据集，以支持意大利卫生服务部门进行蘑菇鉴定。目标物种是从那些在区域（托斯卡纳）中毒事件中最常涉及的物种中挑选出来的。对于每个目标物种，检索了已存入GenBank和BOLD数据库的所有ITS序列，并通过系统的筛选过程对其质量和可靠性进行了准确评估。还收集了目标物种的野生标本以产生参考ITS序列。这些序列部分用于建立数据集，部分用于通过BLAST分析验证数据集。总体而言，在两个数据库中发现了7270个序列。经过筛选，1293个序列（17.8%）被丢弃，最终检索到5977个序列。从76个采集的蘑菇标本中获得了97个ITS参考序列：其中15个序列来自10个在筛选后没有可用序列的物种，用于构建数据集，最终分类覆盖率为96.7%。其他82个序列（66个物种）用于数据集验证。在大多数情况下（n = 71；86.6%），它们与相应物种的同一性值≥97-100%相匹配。该数据集能够识别涉及区域中毒事件的物种。由于其中一些物种也涉及全国范围内的中毒事件，该数据集可用于支持意大利全国领土内的国家卫生服务。此外，它可以支持旨在检测基于蘑菇的商业产品欺诈行为并保护消费者的官方监管活动。
