使用Proofman-LMTIA扩增试验的植物基因组DNA提取试剂盒的比较。

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Phytochemical Analysis Pub Date : 2024-12-28 DOI:10.1002/pca.3497
Wei Yao, Yajie Wang, Dan Zhou, Jinxin Liu, Chunmei Song, Xiaohua Zhang, Deguo Wang, Yao Wang
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引用次数: 0

摘要

DNA的提取是分子生物学研究的基础。提取DNA的质量是分子生物学实验成功与否的关键因素之一。目的:选择合适的中药材及其种子DNA提取方法。方法:本实验采用4种商用DNA提取试剂盒提取半夏(Pinellia ternata, Thunb)的基因组DNA (gDNA)。布莱特。粉;格言。甘氨酸(L.)的粉末和种子稳定。一方面比较了这四种试剂盒提取的DNA的浓度和纯度。另一方面,采用新型核酸等温扩增技术Proofman-LMTIA方法,对4种试剂盒各提取的3个样品进行核酸扩增实验。通过不同试剂盒提取DNA的浓度和纯度,确定适合中药材干粉和种子干粉提取的方法。扩增曲线的效率显示提取的DNA是否可以用于核酸扩增实验。结果:结果表明,Proofman-LMTIA方法特异性高,最佳反应温度分别为63℃、59℃和59℃。牧野;A.格言;G. max (L.)稳定。,分别。所有试剂盒提取的dna浓度和纯度均在可接受范围内;同时,Kit II提取的gDNA扩增效率最高。结论:本实验比较了四种试剂盒提取DNA的原理、浓度、纯度和所需时间。磁法自动提取试剂盒适用于中药材和种子DNA的提取。提取的DNA适合核酸扩增检测。
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Comparison of Plant Genomic DNA Extraction Kits Using the Proofman-LMTIA Amplification Assay.

Introduction: The extraction of DNA is the basis of molecular biology research. The quality of the extracted DNA is one of the key factors for the success of molecular biology experiments.

Objective: To select a suitable DNA extraction method for Chinese medicinal herbs and seeds.

Methods: In this experiment, four commercial DNA extraction kits were used to extract the genomic DNA (gDNA) from the Pinellia ternata (Thunb.) Breit. powder; Arisaema amurense Maxim. powder as well as the seeds of Glycine max (L.) Merr. On the one hand, the concentration and purity of DNA extracted by these four kits were compared. On the other hand, nucleic acid amplification experiments were performed on three samples extracted by each of the four kits by Proofman-LMTIA methods, which is a novel nucleic acid isothermal amplification technique. The concentration and purity of DNA extracted by different kits were used to determine which methods were suitable for the dry powder of Chinese herbal medicines and seeds. The efficiency of the amplification curve to show whether the extracted DNA can be used in nucleic acid amplification experiments.

Results: The results showed that the Proofman-LMTIA methods were of high specificity and the optimal reaction temperatures were 63, 59, and 59°C for P. ternata (Thunb.) Makino; A. amurense Maxim. and G. max (L.) Merr., respectively. The concentration and purity of the gDNAs extracted with all kits were within the acceptable ranges; meanwhile, the amplification of the gDNA extracted by Kit II was of the highest efficiency.

Conclusion: In this experiment, the principle, concentration, purity, and time taken for extracting DNA with four kits were compared. The automated extraction kit based on the magnetic method is suitable for extracting DNA from Chinese medicinal herbs and seeds. The extracted DNA is suitable for nucleic acid amplification detection.

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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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