首页> 外文期刊>International Journal of Medicinal Mushrooms >Identification of Chinese Caterpillar Medicinal Mushroom, Ophiocordyceps sinensis (Ascomycetes), from Counterfeit Species
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Identification of Chinese Caterpillar Medicinal Mushroom, Ophiocordyceps sinensis (Ascomycetes), from Counterfeit Species

机译:鉴别伪造物种中药毛虫药用蘑菇,Ophiocordyceps Sinensis(Ascometes)

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摘要

Ophiocordyceps sinensis is a valuable traditional Chinese medicine with a high market price. In this study, a polymerase chain reaction-restriction fragment-length polymorphism (PCR-RFLP) method based on 2 enzymes was developed to distinguish O. sinensis from 6 common counterfeit species. To verify the applicability of this method, we experimentally tested O. sinensis organisms, tablet preparations made from O. sinensis, and cultured mycelia isolated from O. sinensis. To validate the results from this PCR-RFLP method, all real samples were identified by internal transcribed spacer sequencing. This is, to our knowledge, the first time the PCR-RFLP method has been applied to identify O. sinensis. The selection of 2 restrictive enzymes for identification dramatically improved the accuracy and efficiency of this method. It is the great advantage of this method that sampling from either of 2 parts of O. sinensis-the fruiting body or the caterpillar body-would not cause any difference in the final experimental results. Therefore, this method is not only feasible for testing crude drugs of O. sinensis but it is also useful when the crude drugs are broken down into powder or made into tablets, demonstrating the promising prospect of application in quality control.
机译:Ophiocordyceps Sinensis是一个有价值的中药,市场价格高。在该研究中,开发了一种基于2个酶的聚合酶链反应限制片段长度多态性(PCR-RFLP)方法,以区分O. Sinensis从6种常见的假冒物种。为了验证这种方法的适用性,我们经过实验测试了O. Sinensis生物,由O. Sinensis制成的片剂制剂,以及从O. Sinensis中分离的培养菌丝体。为了通过该PCR-RFLP方法验证结果,通过内部转录的间隔序列测序识别所有真实样品。这是我们的知识,首次应用PCR-RFLP方法以鉴定O. Sinensis。选择2个限制性酶用于识别显着提高了该方法的准确性和效率。这种方法的巨大优点是从o. sinensis的2个部分中的两部分份 - 结果或毛虫身体取样 - 不会导致最终实验结果的任何差异。因此,该方法不仅可以测试O. Sinensis的粗药物,而且当粗药物分解成粉末或制成片剂时,它也很有用,证明了在质量控制中的应用前景。

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