Suppr超能文献

稻瘟病菌感染诱导的水稻叶片叶际微生物群落失调:来自宏条形码和微生物印记的证据

Dysbiosis of the rice leaf phyllomicrobiome induced by Magnaporthe oryzae infection: evidence from metabarcoding and microbiome imprinting.

作者信息

Krishnappa Charishma, Sahu Kuleshwar Prasad, Ashajyothi Mushineni, Kumar Mukesh, Reddy Bhaskar, Kumar Aundy

机构信息

Division of Plant Pathology, ICAR-Indian Agricultural Research Institute, Pusa Campus, New Delhi, 110012, India.

Forest Protection Division, ICFRE- FRI, Dehradun, 248006, India.

出版信息

Int Microbiol. 2025 Jul 23. doi: 10.1007/s10123-025-00691-2.

Abstract

Rice blast, caused by Magnaporthe oryzae, remains a major constraint to global rice production, typically presenting as necrotic lesions on infected leaves. To investigate the bacterial communities associated with these lesions, we employed a novel "Microbiome Imprinting-Metabarcoding" approach, which generated comprehensive microbial datasets (203.34 Mb) from two blast-infected rice cultivars, aromatic Pusa Basmati 1 (PB1) and non-aromatic VL Dhan 85. Metabarcoding analysis revealed the consistent presence of several dominant bacterial genera, including Pantoea, Allorhizobium-Neorhizobium-Pararhizobium-Rhizobium, Pseudomonas, and Chryseobacterium, across both cultivars. Notably, bacterial diversity was reduced in blast lesions compared to healthy phylloplane tissues. Lesion samples comprised 28 genera (Shannon Diversity Index: 1.66; Chao1 richness: 326.86), whereas healthy leaves harbored 48 genera (Shannon Diversity Index: 1.98; Chao1 richness: 361.82). Linear discriminant effect size (LEfSe) analysis identified specific genera such as Bifidobacterium, Desemzia, Acidovorax, and Mucilaginibacter that were uniquely associated with the dysbiotic microbial communities in infected tissues. Core microbiome analysis further revealed ten genera shared between both cultivars, with Pantoea and Allorhizobium emerging as the most abundant. These findings offer new insights into the composition and dynamics of lesion-associated bacterial communities in rice blast and highlight potential microbial targets for the development of improved disease management strategies.

摘要

由稻瘟病菌引起的稻瘟病仍然是全球水稻生产的主要制约因素,通常表现为受感染叶片上的坏死病斑。为了研究与这些病斑相关的细菌群落,我们采用了一种新颖的“微生物组印记-代谢条形码”方法,该方法从两个感染稻瘟病的水稻品种,即香稻品种Pusa Basmati 1(PB1)和非香稻品种VL Dhan 85中生成了全面的微生物数据集(203.34 Mb)。代谢条形码分析显示,两个品种中均一致存在几个优势细菌属,包括泛菌属、根瘤菌属-新根瘤菌属-副根瘤菌属-根瘤菌属、假单胞菌属和金黄杆菌属。值得注意的是,与健康的叶表组织相比,稻瘟病病斑中的细菌多样性降低。病斑样本包含28个属(香农多样性指数:1.66;Chao1丰富度:326.86),而健康叶片中含有48个属(香农多样性指数:1.98;Chao1丰富度:361.82)。线性判别效应大小(LEfSe)分析确定了双歧杆菌属、德氏菌属、嗜酸菌属和黏液杆菌属等特定属,这些属与受感染组织中失调的微生物群落独特相关。核心微生物组分析进一步揭示了两个品种共有的10个属,其中泛菌属和根瘤菌属最为丰富。这些发现为稻瘟病中与病斑相关的细菌群落的组成和动态提供了新的见解,并突出了开发改进的病害管理策略的潜在微生物靶点。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验