Precise quantification of Phytophthora nicotianae in tobacco using digital PCR

文献类型： 外文期刊

第一作者： Liu, Yuanyuan

作者： Liu, Yuanyuan;Li, Jiali;Guo, Zining;Shen, Tianci;Lu, Song;Chen, Xian;Gao, Yunhua;Wang, Di;Liu, Yuanyuan;Liu, Danmei;Li, Jiali;Guo, Zining;Wang, Wei;Feng, Chao

作者机构：

关键词： Phytophthora nicotianae; ddPCR; qPCR; Tobacco black shin; Predictive modeling

期刊名称：MICROCHEMICAL JOURNAL （ 影响因子：5.1； 五年影响因子：4.7 ）

ISSN： 0026-265X

年卷期： 2025 年 213 卷

页码：

收录情况： SCI

摘要： Phytophthora nicotianae (P. nicotianae) is a destructive soil-borne pathogen responsible for tobacco black shank disease. Early and accurate pathogen detection is essential for effective disease management. In this study, we developed a species-specific droplet digital PCR (ddPCR) assay for sensitive detection and quantification of P. nicotianae in field samples. The ddPCR assay exhibited excellent quantification inearity, with detection and quantification limits of 3.9 and 11.6 copies, respectively. Compared to quantitative real-time PCR (qPCR), ddPCR demonstrated superior sensitivity, especially in low pathogen load samples, with ddPCR results 2.63-fold higher. Inhibition analysis confirmed ddPCR's resilience to matrix effects. Additionally, finite element simulation of fungal proliferation patterns validated ddPCR results and illustrated pathogen transmission from soils to roots and stems. Regression models incorporating environmental variables predicted fungal loads with high accuracy (R2 > 0.88). These findings highlight ddPCR's capability for precise quantification and its adaptability for modeling-based analytical applications in complex sample matrices.

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