Polymeric microneedle patches for rapid DNA extraction and molecular diagnosis of foliar pathogens of mung bean.

Authors

Asim Mushtaq, Barsha Poudel, Alina Karki, Pouria Azarikhah, Ahmed Saad, Adrian Dinsdale, Sonia Fiorito, Noel L Knight, Zahra Faraji Rad

Published in

Talanta. Volume 311. Pages 130267. Jul 10, 2026. Epub Jul 10, 2026.

Abstract

Global food security is threatened by crop losses due to plant diseases. Early detection of pathogens is essential for implementing effective management practices to mitigate the negative impacts of disease. On-site molecular diagnostic techniques have significantly advanced for rapid and accurate identification of pathogens, but DNA extraction remains a labour-intensive and time-consuming bottleneck. This study demonstrates the ability of polyvinyl alcohol/polyvinylpyrrolidone (PVA/PVP) microneedle patches to extract detectable amounts of bacterial and plant DNA from diseased leaves within 1 min. This included DNA of a gram-negative Pseudomonas savastanoi pv. phaseolicola (Psp) and a gram-positive Curtobacterium flaccumfaciens pv. flaccumfaciens (Cff) bacteria, as well as mung bean (Vigna radiata). These bacteria cause halo blight and tan spot of mung bean, respectively. The DNA extracted using microneedle patches was of adequate quality and quantity to identify pathogens using real-time quantitative and droplet digital PCR (ddPCR). For leaves expressing halo blight symptoms, Psp DNA was detected in all DNA templates from microneedle (n = 5) and conventional extractions (n = 5). Similarly, in a time course study, Psp inoculated samples at day 6 showed the same detection in templates collected with microneedles and conventionally extracted samples. Detection of Cff DNA was less frequent, suggesting an impact of the sampling or inoculation technique. This study supports ongoing development of microneedle-based extraction as a simple and cost-effective method that could be used to support diagnosis of plant diseases, facilitate rapid decision-making for disease management, enhance biosecurity responses and area-freedom datasets, and prevent crop losses.

PMID:
42456256
Bibliographic data and abstract were imported from PubMed on 16 Jul 2026.

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