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J-GLOBAL ID：202202221316149120   整理番号：22A1023337

共通病原体の同定と可視化のための偽標的化メタボロミクスフィンガープリントと深層学習【JST・京大機械翻訳】

Pseudotargeted Metabolomic Fingerprinting and Deep Learning for Identification and Visualization of Common Pathogens

著者 (19件)： Feng Ying (Guangzhou Institute of Chemistry, Chinese Academy of Sciences, Guangzhou, China) ,  Feng Ying (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Feng Ying (University of Chinese Academy of Sciences, Beijing, China) ,  Chen Moutong (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Wei Xianhu (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Zhu Honghui (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Zhang Jumei (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Zhang Youxiong (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Xue Liang (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Huang Lanyan (Guangzhou Institute of Chemistry, Chinese Academy of Sciences, Guangzhou, China) ,  Huang Lanyan (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Huang Lanyan (University of Chinese Academy of Sciences, Beijing, China) ,  Chen Guoyang (Guangzhou Institute of Chemistry, Chinese Academy of Sciences, Guangzhou, China) ,  Chen Guoyang (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Chen Guoyang (University of Chinese Academy of Sciences, Beijing, China) ,  Chen Minling (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Ding Yu (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...) ,  Ding Yu (Department of Food Science and Technology, Institute of Food Safety and Nutrition, Jinan University, Guangzhou, China) ,  Wu Qingping (Guangdong Provincial Key Laboratory of Microbial Safety and Health, Ministry of Agricultural and Rural Affairs, Key Laboratory of Agricultural Microbiomics and Precision Application, State Key Laboratory of Applied Microbiology Southern China, Guangdong Institute of Microbiology, Guangdon...)
資料名： Frontiers in Microbiology (Web)  (Frontiers in Microbiology (Web))
巻： 13  ページ： 830832  発行年： 2022年 
JST資料番号： U7080A  ISSN： 1664-302X  資料種別： 逐次刊行物 (A)
記事区分： 原著論文  発行国： スイス (CHE)  言語： 英語 (EN)

抄録/ポイント： マトリックス支援レーザ脱離/イオン化飛行時間質量(MALDI-TOF)分光法フィンガープリンティングは,様々な研究室における従来の手順として,ターンアラウンド時間,コスト,および労働を削減した。しかし,高い遺伝的相関を有するいくつかの種株は,従来の標準手順を用いて直接識別されていない。メタボロームは,表現型に直接関係するので,マイナーな違いを増幅することにより,これらの株を同定できる。擬似標的メタボロミクス法は非標的および標的メタボロミクスの両方の利点を有する。それは,高い被覆率で新しい半定量的フィンガープリントを提供できる。病原体の同定と可視化のために,この擬似標的メタボロームフィンガープリントを深層学習技術と組み合わせた。病原性細菌を同定し,分類するために変分オートエンコーダフレームワークを実行し,99%を超える予測精度でそれらの可視化を達成した。したがって,この技術は病原体を迅速に正確に同定するための強力なツールになるであろう。Copyright 2022 The Author(s) All rights reserved. Translated from English into Japanese by JST.【JST・京大機械翻訳】

シソーラス用語： イオン化 ,  脱着 ,  変分法 ,  *解析 ,  遺伝 ,  代謝産物 ,  表現型 ,  *可視化 ,  ターンアラウンド時間 ,  *病原体 ,  *指紋 ,  フィンガープリント法 ,  *ターゲティング
準シソーラス用語： *メタボロミクス ,  予測精度 ,  メタボローム ,  *深層学習 , 【Automatic Indexing@JST】

著者キーワード (5件)： 擬似標的メタボロミクス ,  深層学習 ,  LC-QQQ-MS ,  変分オートエンコーダ(VAE) ,  畳込みニューラルネットワーク(CNN)

分類 (2件)： 細菌による植物病害  (FC04053P) ,  微生物形態学・分類学  (EG03030Y)

引用文献 (20件)：

• Chen S., Kong H., Lu X., Li Y., Yin P., Zeng Z., et al (2013). Pseudotargeted metabolomics method and its application in serum biomarker discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry. Anal. Chem. 85 8326-8333. doi: 10.1021/ac4016787
• Dingle T. C., Butler-Wu S. M., Abbott A. N. (2014). Accidental exposure to Burkholderia pseudomallei in the laboratory in the era of matrix-assisted laser desorption ionization-time of flight mass spectrometry. J. Clin. Microbiol. 52 3490-3491. doi: 10.1128/JCM.01238-14
• Dong S., Yang X., Zhao L., Zhang F., Hou Z., Xue P. (2020). Antibacterial activity and mechanism of action saponins from Chenopodium quinoa Willd. husks against foodborne pathogenic bacteria. Industrial Crops Prod. 149:112350. doi: 10.1016/j.indcrop.2020.112350
• Ferone M., Gowen A., Fanning S., Scannell A. G. M. (2020). Microbial detection and identification methods: bench top assays to omics approaches. Compr. Rev. Food Sci. Food Saf. 19 3106-3129. doi: 10.1111/1541-4337.12618
• Fiehn O. (2002). “"“Metabolomics - the link between genotypes and phenotypes,”,"” in Functional Genomics, ed. Town C. (Netherlands: Springer), 155-171. doi: 10.1111/1541-4337.12618

タイトルに関連する用語 (5件)： 病原体 ,  同定 ,  可視化 ,  標的化 ,  深層学習