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大豆籽粒溯源和检疫鉴定中的元数据应用。

Applying meta-data of soybean grain in origin trace and quarantine inspection.

机构信息

State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, PR China; College of Life Science, University of Chinese Academy of Sciences, Beijing 100049, PR China.

Ningbo Academy of Inspection and Quarantine, Ningbo, Zhejiang 315012, PR China; Ningbo Customs District, Ningbo, Zhejiang 315012, PR China.

出版信息

Food Res Int. 2022 Dec;162(Pt A):111998. doi: 10.1016/j.foodres.2022.111998. Epub 2022 Sep 30.

Abstract

Soybean and derived products are among the most important food for both humans and animals. China is the world's largest importer of soybeans, with more than 100 million tons of annual imports, mainly from the United States of America (US), Brazil, and Argentina. However, there have been limited studies on the microbiota associated with imported soybean grains. Here, we reveal the soybean microbiota using amplicon sequencing based on samples from four countries on three continents of North America (US), South America (Argentina, Brazil), and Asia (China). Our results showed that the soybean-associated microbiota from different continents significantly separated, presenting strong geographic variations. The core microbial taxa and geographically specified taxa were defined, with Alternaria, Enterobacter, Plectosphaerella, Stenotrophomanas, and Xeromyces defined as the core microbiota for soybean from Asia; Amanita, Aspergillus, Fusarium, Nigrospora, Herbiconiux, Pseudomonas, Saccharopolyspora, and Schumannella from North America; and Bradyrhizobium, Colletotrichum, Filobasidium, Phialosimplex, Mycosphaerella, Septoria, Sphingomonas, and Weissalla, from South America. In addition, we build the Random Forest (RF) model to predict the source of imported soybean grains. We could accurately predict the original countries of imported soybean grains within the RF prediction models, with accuracies greater than 95 %. We constructed a database of soybean-related quarantine pathogens using full-length sequences of fungal ITS region and bacterial 16S rDNA region. Two phytopathogenic fungi, Diaporthe caulivora and Cladosporium cucumerinum, listed in the Chinese quarantine catalog, were intercepted through metabarcoding sequencing. The former was further confirmed using an available national standard protocol of qPCR diagnosis. In summary, our NGS-based approach revealed the microbiota associated with soybeans. It could provide comprehensive information and valuable method on the trace the origin of soybean and detection of quarantine pathogens at Customs and departments of inspection and quarantine.

摘要

大豆及其制品是人类和动物最重要的食物之一。中国是世界上最大的大豆进口国,年进口量超过 1 亿吨,主要来自美国、巴西和阿根廷。然而,关于进口大豆颗粒相关微生物群的研究有限。在这里,我们使用基于来自四大洲(北美洲的美国、南美洲的阿根廷、巴西和亚洲的中国)的样本的基于扩增子测序的方法来揭示大豆微生物群。我们的结果表明,来自不同大洲的大豆相关微生物群显著分离,呈现出强烈的地理变化。定义了核心微生物类群和具有地理特异性的类群,将链格孢属、肠杆菌属、盾壳霉属、寡养单胞菌属和毕赤酵母属定义为亚洲大豆的核心微生物群;北美大豆的核心微生物群为鹅膏属、曲霉属、镰刀菌属、黑孢霉属、食线虫菌属、假单胞菌属、糖多孢菌属和施马氏菌属;而南美的核心微生物群为慢生根瘤菌属、炭疽菌属、Filobasidium 属、拟青霉属、球腔菌属、叶点霉属、鞘氨醇单胞菌属和魏斯氏菌属。此外,我们构建了随机森林(RF)模型来预测进口大豆的来源。我们可以在 RF 预测模型中准确预测进口大豆的原始国家,准确率大于 95%。我们使用真菌 ITS 区和细菌 16S rDNA 区全长序列构建了大豆相关检疫病原体数据库。通过 metabarcoding 测序截获了中国检疫目录中列出的两种植物病原菌,腐皮镰刀菌和瓜枝孢霉。前者通过现有的国家标准 qPCR 诊断协议进一步确认。总之,我们基于 NGS 的方法揭示了与大豆相关的微生物群。它可以为海关和检验检疫部门提供关于大豆来源追踪和检疫性病原菌检测的全面信息和有价值的方法。

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