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MINI REVIEW article
Front. Microbiomes
Sec. Environmental Microbiomes
Volume 4 - 2025 | doi: 10.3389/frmbi.2025.1544070
This article is part of the Research Topic Harnessing Plant Microbiomes: Developing Resilient Microbial Formulations for Crop Growth View all 3 articles
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Effective management of plant diseases and the reduction of agricultural losses hinges on the timely detection and accurate identification of plant pathogens. Traditional methods have largely relied on protein and nucleic acid analyses, with enzyme-linked immunosorbent assays (ELISA) standing out for their high throughput and cost-effectiveness. However, ELISA's sensitivity often falls short in the early stages of infection, limiting its utility for preemptive disease control. Nucleic acid-based technologies have brought significant improvements in pathogen identification, particularly for those that resist conventional culturing. Portable diagnostic tools, such as polymerase chain reaction (PCR) assays and lateral flow systems, have enabled rapid field detection. Despite their promise, these methods still face challenges related to sensitivity and specificity. The increasing impact of plant pathogens on global crop yields underscores the critical need for precise and robust diagnostic solutions. Recent breakthroughs in genomic technologies specifically shotgun metagenomics, amplicon-based metagenomics, and meta transcriptomics offer transformative potential. These techniques not only enable the accurate identification of diverse pathogens but also facilitate the analysis of their metabolic pathways, providing valuable insights into pathogen ecology and evolution. This review delves into the emerging role of metagenomic sequencing in plant pathogen detection, highlighting its advantages over traditional approaches and discussing its future implications for sustainable disease management in agriculture.
Keywords: plant pathogens, Early detection, metagenomic sequencing, Shotgun metagenomics, Amplicon-based metagenomics, Meta transcriptomics, Disease Management, Nucleic acid-based diagnostics
Received: 12 Dec 2024; Accepted: 11 Feb 2025.
Copyright: © 2025 Virk, Giri and Srivastava. 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:
Verinder Virk, Faculty of Sciences, Gurukul Kangri University, Haridwar, India
Sadhana Giri, Gurukul Kangri University, Haridwar, 249404, Uttarakhand, India
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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