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ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Biotechnology
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1573949
This article is part of the Research Topic Enhancing Plant Resilience and Productivity Through Biostimulants and Advanced Biotechnological Approaches View all 3 articles
Development and Validation of a Droplet Digital PCR Assay for Sensitive Detection and Quantification of Phytophthora nicotianae
Provisionally accepted- 1 College of Life Sciences, Shanxi University, Taiyuan, Shanxi Province, China
- 2 School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, China
- 3 College of Biotechnology, Tianjin University of Science and Technology, Tianjin, China
- 4 Key Laboratory of Tobacco Pest Monitoring Controlling & Integrated Management, Tobacco Research Institute (CAAS), Qingdao, Shandong Province, China
- 5 National Institute of Metrology, Beijing, Beijing Municipality, China
Tobacco black shank (TBS) disease, caused by Phytophthora nicotianae (P. nicotianae), poses a significant threat to global agriculture and results in substantial economic losses. Traditional methods, like culture-based techniques and quantitative polymerase chain reaction (qPCR), aid pathogen identification but can be less sensitive for complex samples with low pathogen loads. Here, we developed and validated a droplet digital PCR (ddPCR) assay with high sensitivity and specificity for detecting P. nicotianae. ddPCR and quantitative polymerase chain reaction (qPCR) revealed comparable analytical performance including limit of blank (LoB), limit of detection (LoD), and limit of quantitation (LoQ). For the 68 infectious tobacco root samples and 145 surrounding soil samples, ddPCR demonstrated greater sensitivity, with a higher positive rate of 96.4% vs 83.9%. Receiver operating characteristic (ROC) analysis showed an area under the curve (AUC) of ddPCR was 0.913, compared to 0.885 for qPCR. Moreover, ddPCR provided better quantification accuracy for low pathogen concentrations in soil, suggesting better tolerance to potential PCR inhibitors in soil. These results highlight ddPCR as a robust and reliable tool for early diagnosis in complex samples, offering a valuable tool for improving disease management strategies.
Keywords: Phytophthora nicotianae, Droplet digital PCR, quantitative PCR, Pathogen Detection, plant disease management
Received: 10 Feb 2025; Accepted: 27 Mar 2025.
Copyright: © 2025 Liu, Li, Guo, Feng, Gao, Liu and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Danmei Liu, College of Life Sciences, Shanxi University, Taiyuan, 030006, Shanxi Province, China
Di Wang, National Institute of Metrology, Beijing, 100029, Beijing Municipality, China
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