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优化集成生物监测工具箱,以研究空气中真菌群的空间分布和动态变化,重点关注加拿大西部的谷物锈菌。

Optimizing an integrated biovigilance toolbox to study the spatial distribution and dynamic changes of airborne mycobiota, with a focus on cereal rust fungi in western Canada.

机构信息

Ottawa Research and Development Centre, Agriculture and Agri-Food Canada (AAFC), Ottawa, Ontario, Canada.

Department of Biology, University of Ottawa, Marie-Curie Private, Ottawa, Ontario, Canada.

出版信息

Mol Ecol Resour. 2024 Aug;24(6):e13983. doi: 10.1111/1755-0998.13983. Epub 2024 Jun 6.

DOI:10.1111/1755-0998.13983
PMID:38840549
Abstract

In the face of evolving agricultural practices and climate change, tools towards an integrated biovigilance platform to combat crop diseases, spore sampling, DNA diagnostics and predictive trajectory modelling were optimized. These tools revealed microbial dynamics and were validated by monitoring cereal rust fungal pathogens affecting wheat, oats, barley and rye across four growing seasons (2015-2018) in British Columbia and during the 2018 season in southern Alberta. ITS2 metabarcoding revealed disparity in aeromycobiota diversity and compositional structure across the Canadian Rocky Mountains, suggesting a barrier effect on air flow and pathogen dispersal. A novel bioinformatics classifier and curated cereal rust fungal ITS2 database, corroborated by real-time PCR, enhanced the precision of cereal rust fungal species identification. Random Forest modelling identified crop and land-use diversification as well as atmospheric pressure and moisture as key factors in rust distribution. As a valuable addition to explain observed differences and patterns in rust fungus distribution, trajectory HYSPLIT modelling tracked rust fungal urediniospores' northeastward dispersal from the Pacific Northwest towards southern British Columbia and Alberta, indicating multiple potential origins. Our Canadian case study exemplifies the power of an advanced biovigilance toolbox towards developing an early-warning system for farmers to detect and mitigate impending disease outbreaks.

摘要

面对不断发展的农业实践和气候变化,我们优化了用于综合生物监测平台的工具,以对抗作物疾病、孢子采样、DNA 诊断和预测轨迹建模。这些工具揭示了微生物动态,并通过监测不列颠哥伦比亚省四个生长季节(2015-2018 年)和 2018 年艾伯塔省南部影响小麦、燕麦、大麦和黑麦的谷物锈病真菌病原体得到了验证。ITS2 宏条形码揭示了加拿大落基山脉地区空气微生物群落多样性和组成结构的差异,表明空气流动和病原体传播存在屏障效应。一种新颖的生物信息学分类器和经过精心整理的谷物锈菌 ITS2 数据库,通过实时 PCR 得到了验证,提高了谷物锈菌物种鉴定的精度。随机森林模型确定了作物和土地利用多样化以及气压和湿度是锈病分布的关键因素。轨迹 HYSPLIT 模型追踪锈菌冬孢子从太平洋西北向不列颠哥伦比亚省南部和艾伯塔省的东北方向扩散,为解释锈菌分布的差异和模式提供了有价值的补充,表明存在多个潜在起源。我们的加拿大案例研究展示了先进的生物监测工具箱的强大功能,可为农民开发早期预警系统,以检测和减轻即将发生的疾病爆发。

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