An improved DNA extraction method in okra for rapid PCR detection of Okra enation leaf curl virus from diverse Indian regions

IF 2.3 3区 生物学 Q3 MICROBIOLOGY
Ankit Kumar, Jyoti Singh, Deepak Panwar, Anupma Singh, Ravi Singh Thapa, Rakesh Kumar, Dharmendra Pratap
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引用次数: 0

Abstract

The extraction of DNA from okra (Abelmoschus esculentus) is challenging due to its high mucilage and polysaccharide content, which can hinder both the yield and quality of DNA. In this study, an improved DNA isolation method is described incorporating a key modification being the use of solution I (1 M NaCl and 2% Sarcosyl) as a pre-treatment before applying the CTAB buffer, resulting in high-purity genomic DNA in just 1 h and 45 min., making it suitable for handling large sample sizes due to its rapid processing capabilities. This enhanced DNA extraction method was crucial for the accurate and rapid molecular detection of Okra enation leaf curl virus (OELCuV), a monopartite begomovirus that has spread across various regions of India. Transmitted by the whitefly (Bemisia tabaci), OELCuV causes leaf curling, enations, and stunted growth in okra, leading to significant yield losses. The surveys conducted during the 2020–21 and 2021–22 sowing seasons revealed disease incidence ranging from 14.03 to 67.57%. The extracted DNA via the improved DNA extraction method enhanced the speed of PCR based molecular identification of OELCuV, using virus-specific coat protein primers. The amplified CP genes were cloned and sequenced to study the CP gene based diversity among OELCuV isolates from different states of India. The CP gene nucleotide identity among the studied OELCuV isolates ranged from 95.57 to 99.27%, while comparison with previously reported Indian OELCuV CP sequences, the nucleotide identity ranged from 89.35 to 98.83%. The successful application of this optimized DNA extraction method sped up the detection process but also holds promise for broader use in the molecular study of okra and other mucilaginous crops, particularly in the rapid and reliable identification of begomoviruses. The optimized DNA extraction method significantly accelerated the detection of OELCuV, demonstrating its efficiency and reliability. This method shows strong potential for broader applications in the molecular study of okra and other mucilaginous crops, making it a valuable tool for future research and disease management.

Abstract Image

一种改进的秋葵 DNA 提取方法,用于快速 PCR 检测印度不同地区的秋葵卷叶病毒。
从黄秋葵(Abelmoschus esculentus)中提取DNA是一项挑战,因为黄秋葵的粘液和多糖含量很高,会影响DNA的产量和质量。本研究介绍了一种改进的 DNA 分离方法,其主要改进是在使用 CTAB 缓冲液之前使用溶液 I(1 M NaCl 和 2% Sarcosyl)作为预处理,从而在 1 小时 45 分钟内获得高纯度基因组 DNA,由于其快速处理能力,适合处理大量样本。这种增强型 DNA 提取方法对于准确、快速地分子检测秋葵卷叶病毒(OELCuV)至关重要。OELCuV 由粉虱(Bemisia tabaci)传播,会导致秋葵卷叶、茎瘤和生长受阻,造成严重的产量损失。在 2020-21 年和 2021-22 年播种季节进行的调查显示,病害发生率从 14.03% 到 67.57%不等。通过改进的 DNA 提取方法提取的 DNA 提高了利用病毒特异性衣壳蛋白引物对 OELCuV 进行基于 PCR 的分子鉴定的速度。对扩增的 CP 基因进行了克隆和测序,以研究来自印度不同邦的 OELCuV 分离物中基于 CP 基因的多样性。所研究的 OELCuV 分离物的 CP 基因核苷酸同一性在 95.57% 到 99.27% 之间,而与之前报道的印度 OELCuV CP 序列相比,核苷酸同一性在 89.35% 到 98.83% 之间。这种优化的 DNA 提取方法的成功应用不仅加快了检测过程,而且有望在秋葵和其他黏液作物的分子研究中得到更广泛的应用,特别是在快速可靠地鉴定乞猴病毒方面。优化的 DNA 提取方法大大加快了 OELCuV 的检测速度,证明了其高效性和可靠性。该方法在黄秋葵和其他黏液作物的分子研究中显示出更广泛的应用潜力,是未来研究和疾病管理的重要工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Archives of Microbiology
Archives of Microbiology 生物-微生物学
CiteScore
4.90
自引率
3.60%
发文量
601
审稿时长
3 months
期刊介绍: Research papers must make a significant and original contribution to microbiology and be of interest to a broad readership. The results of any experimental approach that meets these objectives are welcome, particularly biochemical, molecular genetic, physiological, and/or physical investigations into microbial cells and their interactions with their environments, including their eukaryotic hosts. Mini-reviews in areas of special topical interest and papers on medical microbiology, ecology and systematics, including description of novel taxa, are also published. Theoretical papers and those that report on the analysis or ''mining'' of data are acceptable in principle if new information, interpretations, or hypotheses emerge.
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