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Precise quantification of Phytophthora nicotianae in tobacco using digital PCR

文献类型： 外文期刊

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

作者机构：

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

期刊名称： Microchemical Journal

ISSN： 0026-265X

年卷期： 2025 年 213 卷

页码：

收录情况： SCIE（2025版）

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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