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对植物土壤进行初步分析,以寻找与幼苗病害相关病原体的证据。

Initial Analysis of Plant Soil for Evidence of Pathogens Associated with a Disease of Seedling .

作者信息

Eaton William D, Hamilton Debra A, Lemenze Alexander, Soteropoulos Patricia

机构信息

Biology Department, Dyson College, Pace University, New York, NY 10038, USA.

Department of Environment and Development, University for Peace, El Rodeo de Mora, San José 10701, Costa Rica.

出版信息

Microorganisms. 2025 Jul 17;13(7):1682. doi: 10.3390/microorganisms13071682.

Abstract

Seedlings of the ecologically important, critically endangered tree experience high mortality in the Monteverde, Costa Rica, cloud forests at the onset of the wet season, yet there are no studies suggesting the disease etiology. Here, healthy and diseased plant root and bulk soils were analyzed for various carbon and nitrogen (N) metrics and respiration levels, and DNA sequence-based bacterial and fungal community compositions. All nitrogen metric levels were greater in diseased vs. healthy plant root soils, which could enhance pathogen growth and pathogenic mechanisms. Greater DNA percentages from several potential pathogens were found in diseased vs. healthy plant root soils, suggesting this disease may be associated with a root pathogen. The DNA of the fungus was at greater levels in diseased vs. healthy plant root soils than other potential pathogens. causes similar diseases in other plants, including coffee, after onset of the wet season. The disease also occurs in seedlings planted within or near former coffee plantations at wet season onset. Distance-based linear model analyses indicated that NO levels best predicted the pattern of fungal pathogens in the soils, and and best predicted the patterns of the different N metrics in the soils, supporting their possible roles in this disease.

摘要

这种具有重要生态意义的极度濒危树种的幼苗,在雨季开始时于哥斯达黎加蒙特维多云雾森林中死亡率很高,但尚无研究表明其病因。在此,对健康和患病植物的根系及大量土壤进行了各种碳和氮(N)指标以及呼吸水平的分析,以及基于DNA序列的细菌和真菌群落组成分析。患病植物根系土壤中的所有氮指标水平均高于健康植物根系土壤,这可能会促进病原体生长和致病机制。在患病植物根系土壤中发现的几种潜在病原体的DNA百分比高于健康植物根系土壤,表明这种疾病可能与一种根系病原体有关。与其他潜在病原体相比,患病植物根系土壤中该真菌的DNA水平更高。在雨季开始后,该真菌会在包括咖啡在内的其他植物中引发类似疾病。在雨季开始时,种植在以前咖啡种植园内部或附近的幼苗也会出现这种疾病。基于距离的线性模型分析表明,一氧化氮(NO)水平最能预测土壤中真菌病原体的模式,而铵态氮(NH₄⁺)和硝态氮(NO₃⁻)最能预测土壤中不同氮指标的模式,这支持了它们在这种疾病中可能发挥的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/53e6/12300691/5741a6027ae2/microorganisms-13-01682-g001a.jpg

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