中文(简体)
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
FEMS Microbiology Letters 2013-Oct

DNA barcoding the commercial Chinese caterpillar fungus.

只有注册用户可以翻译文章
登陆注册
链接已保存到剪贴板
Li Xiang
Jingyuan Song
Tianyi Xin
Yingjie Zhu
Linchun Shi
Xiaolan Xu
Xiaohui Pang
Hui Yao
Wenjia Li
Shilin Chen

关键词

抽象

Chinese caterpillar fungus (Ophiocordyceps sinensis) has been widely used as tonic in Asian medicine. Considering its curative effect and high cost, various counterfeit versions of O. sinensis have been introduced and are commercially available. These counterfeits have morphological characteristics that are difficult to distinguish based on morphology alone, thereby causing confusion and threatening its safe use. In this study, internal transcribed spacer (ITS) sequences as a DNA barcode were analyzed and assessed for rapid and accurate identification of 131 O. sinensis samples and 12 common counterfeits and closely related species. Results showed that sufficient ITS sequence differences, also known as 'barcode gaps', existed to distinguish between O. sinensis and counterfeit species. ITS sequence correctly identified 100% of the samples at the species and genus level using the Basic Local Alignment Search Tool 1 and the nearest distance method. Furthermore, O. sinensis, counterfeits, and closely related species can be successfully identified using tree-based methods including maximum parsimony, neighbor-joining, and maximum likelihood analysis. These results indicated that DNA barcoding could be used as a fast and accurate identification method to distinguish O. sinensis from counterfeits and closely related species to ensure its safe use.

加入我们的脸书专页

科学支持的最完整的草药数据库

  • 支持55种语言
  • 科学支持的草药疗法
  • 通过图像识别草药
  • 交互式GPS地图-在位置标记草药(即将推出)
  • 阅读与您的搜索相关的科学出版物
  • 通过药效搜索药草
  • 组织您的兴趣并及时了解新闻研究,临床试验和专利

输入症状或疾病,并阅读可能有用的草药,输入草药并查看所使用的疾病和症状。
*所有信息均基于已发表的科学研究

Google Play badgeApp Store badge