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Article(id=1226296955966505250, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1226296952975966478, articleNumber=null, orderNo=null, doi=10.13343/j.cnki.wsxb.20240594, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1727366400000, receivedDateStr=2024-09-27, revisedDate=null, revisedDateStr=null, acceptedDate=1731340800000, acceptedDateStr=2024-11-12, onlineDate=1770301577798, onlineDateStr=2026-02-05, pubDate=1738598400000, pubDateStr=2025-02-04, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770301577798, onlineIssueDateStr=2026-02-05, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770301577798, creator=13701087609, updateTime=1770301577798, updator=13701087609, issue=Issue{id=1226296952975966478, tenantId=1146029695717560320, journalId=1192105938417971205, year='2025', volume='65', issue='2', pageStart='421', pageEnd='861', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1770301577085, creator=13701087609, updateTime=1770353593135, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1226515124169650204, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1226296952975966478, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1226515124173844509, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1226296952975966478, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=729, endPage=744, ext={EN=ArticleExt(id=1226296956796977480, articleId=1226296955966505250, tenantId=1146029695717560320, journalId=1192105938417971205, language=EN, title=Changes of microbiome in wheat under head blight stress and its correlation with disease occurrence, columnId=1192149543992045670, journalTitle=Acta Microbiologica Sinica, columnName=Research Article, runingTitle=null, highlight=null, articleAbstract=

[Objective] To investigate the plant microbiome changes in response to wheat head blight and the correlation between the abundance of differential microorganisms and the pathogen Fusarium graminearum, and elucidate the intricate interplay between plant microbiome and disease occurrence. [Methods] We collected samples from both healthy and diseased plants in the field, combined with high-throughput sequencing to analyze the characteristics of plant microbiome changes, and the abundance of pathogen was determined by RT-qPCR to reveal the response of plant microbial community changes to wheat head blight. [Results] The alpha diversity of bacteria in wheat spikes and fungi in the rhizosphere significant increased under the disease stress, with enrichment of potentially beneficial bacteria in spikes of diseased wheat plants. Healthy plants displayed higher stability of microbial community and network than diseased plants. Plant microbial diversity can predict alterations in pathogen abundance. Notably, the microbial diversity and community stability explained the most (76.95%) variations in pathogen abundance. High fungal diversity and community stability were associated with reduced pathogen colonization. [Conclusion] Significant discrepancies of the plant microbiome were identified between healthy and diseased plants. The stable microbial community and network interactions in the spikes of healthy plants facilitate the resistance against F. graminearum infection. Additionally, the “call for help” phenomenon was observed as wheat plants recruited beneficial microflora in spikes, expanding the applicability of the “call for help” strategy. By examining the connection between plant microbiome and disease occurrence, this study presents crucial data and a theoretical framework for the targeted manipulation of plant microbiome to enhance disease prevention and control.

, correspAuthors=Yangwu DENG, authorNote=null, correspAuthorsNote=
*E-mail:
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【目的】 研究小麦赤霉病胁迫下植物微生物变化特征以及差异微生物与病原菌丰度的关系，明确植物微生物与病害发生的关系。 【方法】 本研究通过田间采集健康与患病样本，结合高通量测序分析植物相关微生物组变化特征，并通过实时荧光定量技术测定病原菌丰度，揭示植物微生物群落变化对小麦赤霉病的响应。 【结果】 小麦赤霉病胁迫下穗部细菌和根际真菌α多样性显著增加，更多的潜在有益菌群在患病小麦穗部富集。与患病植株相比，健康植株具有更强的微生物群落稳定性和网络稳定性。植物微生物多样性可以预测病原菌丰度的变化，其中穗部微生物多样性以及群落稳定性对病原菌丰度变化的解释率最高，达76.95%。较高的真菌多样性和群落稳定性不利于病原菌的定殖。 【结论】 健康植株和患病植株的微生物组存在显著差异，健康植株穗部稳定的微生物群落和网络互作模式有利于抵抗病原菌的侵染。此外，小麦穗部出现了植物对有益菌群的招募现象，即“呼救”策略，这扩展了植物“呼救”策略的适用范围。最后，本研究通过解析植物微生物组与病害发生的关系，为靶向调控植物微生物组以防治植物病害提供了重要的数据支撑和理论依据。

, correspAuthors=邓扬悟, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=MfOgMQYImpFSoXpyodKrWQ==, magXml=zpazRRW1zWKkRjgIL6NOeA==, pdfUrl=null, pdf=f/IXBjaWDLa+JTdeU8YqfQ==, pdfFileSize=6994949, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=FuAKz4OPglV5QiJo2wMqMA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=dvlEGQVc+5iyNxrhVipIcA==, mapNumber=null, authorCompany=null, fund=null, authors=

作者贡献声明

王楚涵：样品采集与实验操作、调查研究、数据分析与可视化呈现、写作初稿与修改；吴传发：实验操作、调查研究、数据管理、论文修改；羊健：调查研究、数据分析、指导；陈剑平：调查研究、提供资源、指导；葛体达：实验设计、提供资源、写作审核与编辑；邓扬悟：实验设计、论文构思、写作审核与编辑。

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Nature Climate Change, 2021, 11: 343-348., articleTitle=Climate warming enhances microbial network complexity and stability, refAbstract=null)], funds=[Fund(id=1226514040961282568, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, awardId=2022YFA1304400, language=EN, fundingSource=National Key Research and Development Program of China(2022YFA1304400), fundOrder=null, country=null), Fund(id=1226514041070334475, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, awardId=2022YFA1304400, language=CN, fundingSource=国家重点研发计划(2022YFA1304400), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1226514032090329095, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, xref=null, ext=[AuthorCompanyExt(id=1226514032102912010, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, companyId=1226514032090329095, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 College of Resources and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi, China), AuthorCompanyExt(id=1226514032111300620, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, companyId=1226514032090329095, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 江西理工大学 资源与环境工程学院，江西 赣州)]), AuthorCompany(id=1226514032207769618, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, xref=null, ext=[AuthorCompanyExt(id=1226514032216158227, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, companyId=1226514032207769618, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 Institute of Plant Virology, Ningbo University, Ningbo, Zhejiang, China), AuthorCompanyExt(id=1226514032232935446, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, companyId=1226514032207769618, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 宁波大学 植物病毒学研究所，浙江 宁波)])], figs=[ArticleFig(id=1226514038729912705, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Figure 1, caption=Experimental design and pathogen Fusarium graminearum abundance. A: Design of experiment s analysis process; B: The phenotype of healthy and diseased wheat panicle; The results (P-values) of Wilcoxon test show the difference between healthy and diseased samples in wheat panicle (C) and rhizosphere soil (D)., figureFileSmall=pqvfOUvE/wn5M4PHC+TOWw==, figureFileBig=2GsdFHqyAx2IjDWwYg0jbQ==, tableContent=null), ArticleFig(id=1226514038822187396, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=CN, label=图1, caption=实验设计与病原菌丰度检测。A：实验设计分析流程；B：健康与患病小麦穗部表型；C：Wilcoxon test配对检验了健康与患病小麦穗部禾谷镰刀菌丰度差异；D：健康与患病小麦根际土壤禾谷镰刀菌丰度差异。, figureFileSmall=pqvfOUvE/wn5M4PHC+TOWw==, figureFileBig=2GsdFHqyAx2IjDWwYg0jbQ==, tableContent=null), ArticleFig(id=1226514038985765269, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Figure 2, caption=The differences in rhizosphere soil and panicle microbial diversity between healthy and diseased wheat. A: Bacterial richness index; B: Bacterial Shannon index; C: Bacterial variation degree; D: Fungal richness index; E: Fungal Shannon index; F: Fungal average variation degree; G: Bacterial beta diversity in wheat rhizosphere soil; H: Bacterial beta diversity in wheat panicles; I: Fungal beta diversity in wheat rhizosphere soil; J: Fungal beta diversity in wheat panicles. Principal coordinate analysis and “Adonis2” function were used to test the differences of beta diversity among healthy and diseased wheat. The different colors represent wheat with different disease conditions, and the asterisk (*) represents the significant level of influence of different disease conditions (*: P<0.05; **: P<0.01; ***: P<0.001). ns stands for non-significant effect., figureFileSmall=F3ZLtxpRf36RsTW7nYJQPQ==, figureFileBig=vbGPqkMudRs0i9sLvDCkrQ==, tableContent=null), ArticleFig(id=1226514039111594393, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=CN, label=图2, caption=健康与患病小麦根际土壤和穗部微生物多样性差异。A：细菌丰富度指数；B：细菌香农指数；C：细菌群落平均变异度；D：真菌丰富度指数；E：真菌香农指数；F：真菌群落平均变异度；G：小麦根际土壤细菌β多样性；H：小麦穗部细菌β多样性；I：小麦根际土壤真菌β多样性；J：小麦穗部真菌β多样性。通过主坐标分析和Adonis2检验了β多样性在不同发病状况小麦间的差异。柱状图和点的颜色代表不同患病状况的小麦，*代表不同发病状况影响的显著水平(*：P<0.05；**：P<0.01；***：P<0.001)；ns代表无显著影响。, figureFileSmall=F3ZLtxpRf36RsTW7nYJQPQ==, figureFileBig=vbGPqkMudRs0i9sLvDCkrQ==, tableContent=null), ArticleFig(id=1226514039224840607, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Figure 3, caption=The relationship between plant pathogen abundance and wheat microbial diversity. The correlation of pathogen abundance and the richness index for bacteria (A) and fungi (E), the Shannon index for bacteria (B) and fungi (F), the PCo1 values for bacteria (C) and fungi (G) based on Principal coordinate analysis, and the average variation degree for bacteria (D) and fungi (H) were performed using linear regression analysis. * represents a significant level of correlation between the diversity index and pathogen abundance (*: P<0.05; **: P<0.01; ***: P<0.001)., figureFileSmall=92no/c7+gX25KS4462BQgw==, figureFileBig=J5RUqxacLZ4etEmCnhHuAg==, tableContent=null), ArticleFig(id=1226514039342281125, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=CN, label=图3, caption=病原菌丰度与小麦微生物多样性指数关联分析。通过线性回归分别将根际土壤和穗部细菌和真菌丰富度指数(A、E)、Shannon指数(B、F)、PCo1值(C、G)和平均变异度(D、H)与病原菌丰度进行相关性分析。*代表多样性指数与病原菌丰度相关性的显著水平(*：P<0.05；**：P<0.01；***：P<0.001)。, figureFileSmall=92no/c7+gX25KS4462BQgw==, figureFileBig=J5RUqxacLZ4etEmCnhHuAg==, tableContent=null), ArticleFig(id=1226514039447138732, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Figure 4, caption=The composition of bacterial and fungal communities between health and disease samples. Bacterial taxa (A, B) and fungal taxa (C, D) were analyzed at the phylum and class level, respectively. The phylum of rhizosphere soil and class level of panicle of healthy and diseased wheat were analyzed by t-test., figureFileSmall=wKBLGMmJkb/lo3WQ23nJzQ==, figureFileBig=6dufIu3L/N7ijncPPVveOQ==, tableContent=null), ArticleFig(id=1226514039577162163, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=CN, label=图4, caption=健康与患病样本细菌和真菌群落组成。细菌(A)和真菌(C)分别在门水平和纲水平上的群落组成。通过t-test分别分析了健康与患病小麦根际土壤(B)和穗部(D)差异的门和纲。, figureFileSmall=wKBLGMmJkb/lo3WQ23nJzQ==, figureFileBig=6dufIu3L/N7ijncPPVveOQ==, tableContent=null), ArticleFig(id=1226514039728157119, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Figure 5, caption=Key microorganisms in rhizosphere soil and panicle under different disease conditions of wheat and their relationship with pathogen abundance. A: The volcano plot performed the difference of rhizosphere bacterial ASVs; B: The volcano plot performed the difference of rhizosphere fungal ASVs; C: The volcano plot performed the difference of wheat panicle bacterial ASVs; D: The volcano plot performed the difference of wheat panicle fungal ASVs, the numbers in parentheses represent the number of microorganisms enriched in the healthy or diseased wheat rhizosphere soil and panicles; E: Correlation analysis of rhizosphere soil biomarkers and pathogen abundance, yellow and blue represent bacteria and fungi, respectively; F: Correlation analysis of panicle biomarkers and pathogen abundance, the different colors represent different genus. The edges in red and green represent positive and negative correlation pattern., figureFileSmall=KjopKkQ1szHye6vYcaMUXw==, figureFileBig=b4FewCGLvfZnDptybUCCWw==, tableContent=null), ArticleFig(id=1226514039874957767, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=CN, label=图5, caption=小麦不同患病状况根际土壤和穗部关键微生物及其与病原菌丰度的关系。A：火山图展示小麦根际土壤细菌差异物种；B：火山图展示小麦穗部细菌差异物种；C：火山图展示小麦根际土壤真菌差异物种；D：火山图展示小麦穗部真菌差异物种，括号中的数字代表健康或患病小麦根际土壤和穗部富集的微生物数目；E：根际土壤生物标志物与病原菌禾谷镰刀菌丰度相关性分析，不同颜色的点分别代表细菌和真菌；F：穗部关键物种与病原菌丰度相关性分析，不同颜色的点代表不同的微生物属，红色边代表正相关，绿色边代表负相关。, figureFileSmall=KjopKkQ1szHye6vYcaMUXw==, figureFileBig=b4FewCGLvfZnDptybUCCWw==, tableContent=null), ArticleFig(id=1226514040034341330, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Figure 6, caption=Visualized networks of microbial co-occurrence patterns in rhizosphere soil and panicle of healthy and diseased wheat. A: Visualized networks of microbial co-occurrence patterns in rhizosphere soil; B: Visualized networks of microbial co-occurrence patterns in panicle. The pink and blue dots represent bacteria and fungi, respectively, and the red and green edges indicate positive and negative correlations, respectively; C: Differences in microbial network stability in rhizosphere soil and panicle between healthy and diseased wheat; D: The relationship between plant pathogen abundance and rhizosphere soil microbial network stability; E: The relationship between plant pathogen abundance and panicle microbial network stability. * represents the significant level of influence of different disease conditions and correlation between network stability index and pathogen abundance (*: P<0.05; ***: P<0.001). ns stands for non-significant effect., figureFileSmall=gkC66cRS/Q5XQdOqYZq4BA==, figureFileBig=/S+JrT+kyvp0FzmssGLOOg==, tableContent=null), ArticleFig(id=1226514040164364760, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=CN, label=图6, caption=健康和患病小麦根际土壤及穗部的微生物共现网络差异。A：小麦根际土壤健康和患病微生物共现网络；B：小麦穗部健康与患病微生物共现网络，粉色和蓝色点分别代表细菌和真菌，红色和绿色边分别表示正相关和负相关；C：健康与患病小麦分别在根际土壤和穗部的微生物网络稳定性差异；D：根际土壤病原菌丰度与微生物网络稳定性相关性分析；F：小麦穗部病原菌丰度与微生物网络稳定性相关性分析。*代表不同发病状况影响的显著水平和网络稳定性指数与病原菌丰度相关性的显著水平(*：P<0.05；***：P<0.001)，ns代表无显著影响。, figureFileSmall=gkC66cRS/Q5XQdOqYZq4BA==, figureFileBig=/S+JrT+kyvp0FzmssGLOOg==, tableContent=null), ArticleFig(id=1226514040285999584, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Figure 7, caption=Random forest prediction of pathogen abundance by microbial diversity and network stability. A: Random forest prediction of pathogen abundance by rhizosphere soil microbial diversity and network stability; B: Random forest prediction of pathogen abundance by wheat microbial diversity and network stability. * represents the significant level of influence of different disease conditions and correlation between network stability index and pathogen abundance (*: P<0.05; **: P<0.01)., figureFileSmall=gndN2irOp7ojiIlBMfCQzw==, figureFileBig=rHE8I8LebzNh5UgyPCOa7Q==, tableContent=null), ArticleFig(id=1226514040395051495, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=CN, label=图7, caption=微生物多样性和网络稳定性对病原菌丰度的随机森林预测。A：小麦根际土壤微生物多样性和网络稳定性对病原菌丰度的随机森林预测；B：小麦穗部微生物多样性和网络稳定性对病原菌丰度的随机森林预测。*代表不同发病状况影响的显著水平和网络稳定性指数与病原菌丰度相关性的显著水平(*：P<0.05；**：P<0.01)。, figureFileSmall=gndN2irOp7ojiIlBMfCQzw==, figureFileBig=rHE8I8LebzNh5UgyPCOa7Q==, tableContent=null), ArticleFig(id=1226514040537657842, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1226296955966505250, language=EN, label=Table 1, caption=

Topological properties of microbial networks

, figureFileSmall=null, figureFileBig=null, tableContent=
NetworkWheat panicleRhizosphere soil
HealthDiseaseHealthDisease
Number of nodes3894522 4571 922
Number of edges1 1701 94022 02015 099
Positive (%)83.1388.6795.1595.51
Negative (%)16.8711.334.854.09
Bacterial ratio (%)59.6486.0681.5673.73
Fungal ratio (%)40.3613.9418.4426.27
Average degree6.028.5817.9215.71
Network diameter1814910
Network density0.020.020.010.01
Modularity1.220.930.620.63
Average clustering coefficient0.510.560.270.29
Average path length6.015.503.713.80
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微生物网络拓扑性质

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小麦赤霉病胁迫下植物微生物群落特征及其与病害发生的关系
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王楚涵 1 , 吴传发 2 , 羊健 2 , 陈剑平 2 , 葛体达 2 , 邓扬悟 1, *
微生物学报 | 研究报告 2025,65(2): 729-744
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微生物学报 | 研究报告 2025, 65(2): 729-744
小麦赤霉病胁迫下植物微生物群落特征及其与病害发生的关系
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王楚涵1, 吴传发2, 羊健2, 陈剑平2, 葛体达2, 邓扬悟1, *
作者信息
  • 1 江西理工大学 资源与环境工程学院，江西 赣州
  • 2 宁波大学 植物病毒学研究所，浙江 宁波
Changes of microbiome in wheat under head blight stress and its correlation with disease occurrence
Chuhan WANG1, Chuanfa WU2, Jian YANG2, Jianping CHEN2, Tida GE2, Yangwu DENG1, *
Affiliations
  • 1 College of Resources and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou, Jiangxi, China
  • 2 Institute of Plant Virology, Ningbo University, Ningbo, Zhejiang, China
出版时间: 2025-02-04 doi: 10.13343/j.cnki.wsxb.20240594
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摘要
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【目的】 研究小麦赤霉病胁迫下植物微生物变化特征以及差异微生物与病原菌丰度的关系，明确植物微生物与病害发生的关系。 【方法】 本研究通过田间采集健康与患病样本，结合高通量测序分析植物相关微生物组变化特征，并通过实时荧光定量技术测定病原菌丰度，揭示植物微生物群落变化对小麦赤霉病的响应。 【结果】 小麦赤霉病胁迫下穗部细菌和根际真菌α多样性显著增加，更多的潜在有益菌群在患病小麦穗部富集。与患病植株相比，健康植株具有更强的微生物群落稳定性和网络稳定性。植物微生物多样性可以预测病原菌丰度的变化，其中穗部微生物多样性以及群落稳定性对病原菌丰度变化的解释率最高，达76.95%。较高的真菌多样性和群落稳定性不利于病原菌的定殖。 【结论】 健康植株和患病植株的微生物组存在显著差异，健康植株穗部稳定的微生物群落和网络互作模式有利于抵抗病原菌的侵染。此外，小麦穗部出现了植物对有益菌群的招募现象，即“呼救”策略，这扩展了植物“呼救”策略的适用范围。最后，本研究通过解析植物微生物组与病害发生的关系，为靶向调控植物微生物组以防治植物病害提供了重要的数据支撑和理论依据。

小麦赤霉病  /  禾谷镰刀菌  /  植物微生物组  /  微生物共现性网络  /  群落稳定性

[Objective] To investigate the plant microbiome changes in response to wheat head blight and the correlation between the abundance of differential microorganisms and the pathogen Fusarium graminearum, and elucidate the intricate interplay between plant microbiome and disease occurrence. [Methods] We collected samples from both healthy and diseased plants in the field, combined with high-throughput sequencing to analyze the characteristics of plant microbiome changes, and the abundance of pathogen was determined by RT-qPCR to reveal the response of plant microbial community changes to wheat head blight. [Results] The alpha diversity of bacteria in wheat spikes and fungi in the rhizosphere significant increased under the disease stress, with enrichment of potentially beneficial bacteria in spikes of diseased wheat plants. Healthy plants displayed higher stability of microbial community and network than diseased plants. Plant microbial diversity can predict alterations in pathogen abundance. Notably, the microbial diversity and community stability explained the most (76.95%) variations in pathogen abundance. High fungal diversity and community stability were associated with reduced pathogen colonization. [Conclusion] Significant discrepancies of the plant microbiome were identified between healthy and diseased plants. The stable microbial community and network interactions in the spikes of healthy plants facilitate the resistance against F. graminearum infection. Additionally, the “call for help” phenomenon was observed as wheat plants recruited beneficial microflora in spikes, expanding the applicability of the “call for help” strategy. By examining the connection between plant microbiome and disease occurrence, this study presents crucial data and a theoretical framework for the targeted manipulation of plant microbiome to enhance disease prevention and control.

wheat head blight  /  Fusarium graminearum  /  plant microbiome  /  microbial co-occurrence network  /  community stability
王楚涵, 吴传发, 羊健, 陈剑平, 葛体达, 邓扬悟. 小麦赤霉病胁迫下植物微生物群落特征及其与病害发生的关系. 微生物学报, 2025 , 65 (2) : 729 -744 . DOI: 10.13343/j.cnki.wsxb.20240594
Chuhan WANG, Chuanfa WU, Jian YANG, Jianping CHEN, Tida GE, Yangwu DENG. Changes of microbiome in wheat under head blight stress and its correlation with disease occurrence[J]. Acta Microbiologica Sinica, 2025 , 65 (2) : 729 -744 . DOI: 10.13343/j.cnki.wsxb.20240594
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小麦赤霉病(Fusarium head blight, FHB)，又称烂麦头，是一种由真菌病原菌禾谷镰刀菌(Fusarium graminearum)侵染引起的麦类气候性病害[1]。禾谷镰刀菌以无性分生的孢子形态存在于土壤或植物病残体中，待气候条件适宜时进入植物体内侵染小麦穗部，病害主要表现为小麦穗部出现红色霉层[2]。该病害在全球范围内小麦产区均有发生，一旦发生，会导致小麦大面积减产，严重时甚至会导致小麦种植区颗粒无收[3]。此外，禾谷镰刀菌在植物宿主体内还会产生多种毒素物质，包括镰刀菌素C、金镰刀菌素、玉米赤霉烯酮和脱氧雪腐镰刀菌烯醇及其衍生物等，这些毒素的产生会极大地降低麦类作物产量和质量[4]，且会严重威胁到人类和动物的健康[5]。目前，对小麦赤霉病的防控主要依靠田间管理方式的改善(轮作和施肥等)、抗病品种的培育以及杀菌剂等农药的使用。由于禾谷镰刀菌以孢子形态在土壤中生存，具有较强的隐蔽性，轮作和施肥等田间管理措施难以根治，抗病品种培育周期较长，化学药剂对病害防控具有局限性，且其不合理施用对生态环境造成污染和破坏，目前缺乏有效的防治措施抑制病害的发生与发展。因此，在粮食安全、资源高效利用和生态健康等多目标多方向协同发展的前提下，探索绿色、高效、可持续的病害防控策略，对于推动农业现代化可持续发展显得尤为重要。
随着生物技术的高速发展，众多科研工作者开始对微生物-植物宿主-病原菌之间的互作关系进行深入的探究。其中，植物微生物中的有益菌与植物宿主经过长期的进化与互作，普遍存在共生关系，即植物宿主在其根际、茎叶和籽粒表面及其体内为微生物提供生存空间和养分，栖息于植物体上的微生物则在宿主面临养分吸收、生长发育，以及干旱、重金属、盐分等非生物胁迫，还有病虫害等生物胁迫时，协助宿主发挥相应的功能[6]。前人在研究中发现，植物微生物组可以通过多种直接或间接的互作机制促进植物对病原菌侵染的抗性，包括通过养分资源和生态位竞争的方式直接抑制病原菌或通过激活植物防御系统间接抵御病原菌侵染等方式[7]。例如，小麦穗部微生物鲑鱼假单胞菌(Pseudomonas piscium)可以通过分泌吩嗪-1-甲酰胺(phenazine-1-carboxamide)直接抑制禾谷镰刀菌毒素的生成，从而减少病原菌毒性，抑制病原菌生长[8]。此外，根际微生物菌属寡养单胞菌属(Stenotrophomonas)、根瘤菌属(Rhizobium)、苍白杆菌属(Ochrobactrum)和小陌生菌属(Advenella)组合成简易的合成菌群，也可以通过激活植物宿主系统抗性来抵御病原菌尖孢镰刀菌(Fusarium oxysporum)侵染，并抑制根腐病发生促进拟南芥生长[9]。鉴于植物微生物组的重要性，探明与病害关联的植物微生物组，有助于为植物病害生物防控提供理论和数据支撑。
此外，植物微生物组被誉为植物 “第二大基因组”，是植物基因组的延伸，当植物宿主受到病原菌侵染后，其关联的植物微生物也会出现明显的变化，进而影响植物表型[10]，因此研究病害胁迫下植物微生物组的变化特征对于揭示植物微生物抵御病原菌的机制尤为重要。Tan等研究表明，植物面临病害胁迫时可以通过释放特殊信号来招募有益菌群，协助自身抵御病原菌侵染，抑制病害扩大发展，这种现象被称为植物 “呼救” 策略[11]。例如，辣椒枯萎病胁迫下辣椒相关联的植物微生物组组成、功能及其菌群间的共现模式均发生了改变，并导致了假单胞属(Pseudomonas)、链霉菌属(Streptomyces)和芽孢杆菌(Bacillus)等有益微生物类群在宿主体内富集[10]。线虫侵染作物根系也会导致Pseudomonas富集和抑病土壤的出现，且Pseudomonas在抑病土壤中可以直接或间接地抑制病害的发生[12]。因此，通过在病害胁迫下揭示植物微生物与病原菌互作关系是挖掘植物病害生物防控核心抑病类群的重要前提。考虑到目前鲜有报道小麦赤霉病胁迫下植物微生物组与病原菌丰度的关系，本研究通过对小麦赤霉病野外调查，采集健康和发病的植物微生物组样本，对植物微生物组进行扩增子测序分析。结合植物不同状态下微生物群落变化特征和病原菌丰度，揭示植物微生物对小麦赤霉病发生的响应，以期为小麦赤霉病的生物防治策略提供理论依据和科学指导。
1 材料与方法
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1.1 实验设计和样品采集
本研究样品采集自浙江省宁波市(30°5′24″- 30°9′0″N，121°4′12″E-121°8′24″E)小麦田，该区域是小麦赤霉病多发区域，小麦生产常年受到赤霉病的危害。当地年平均气温为18.3 ℃，土壤类型为中咸土，每年执行小麦-玉米轮作。
在小麦赤霉病发生时期，分别采集健康和患病的小麦根际土壤和穗部样品(图1A、1B)。通过五点法采样，在每个小区选取5个点，并采集5株长势一致的小麦植株。通过抖落法收集附着在根系上的土壤，将5个点均匀混合作为1个根际土壤样本[13]。小麦穗部用消毒后的剪刀剪下装入自封袋中，与土壤一起放入冰盒带回实验室。采集的土壤用2 mm网筛去除植物残体和砂石后储存在-80 ℃冰箱，用于DNA提取。
1.2 DNA提取和病原菌定量分析
在提取小麦穗内微生物前，对小麦穗部进行表面灭菌处理，具体步骤如下：称取2 g穗用灭菌水冲洗干净表面，然后放置在装有75%乙醇的100 mL无菌离心管中浸泡5 min，紧接着再放入装有2.5%次氯酸钠溶液的无菌离心管中浸泡5 min，再转移到另一个装有75%乙醇的无菌离心管中浸泡30 s，最后弃去乙醇溶液，并用灭菌水反复冲洗5次。取最后洗液300 μL于LB琼脂上25 ℃培养3 d，检查灭菌效果[14-16]。
称取0.20 g已进行表面灭菌的小麦穗部组织用液氮预冷，并用研磨机研磨粉碎，土壤称取0.45 g，使用DNeasy PowerSoil Kit (Qiagen公司)提取穗部和根际土壤DNA，具体操作参照试剂盒说明书。DNA提取后利用超微量分光光度计(Implen公司)测量其浓度和质量，最后将DNA提取液放置在-80 ℃储存备用。
禾谷镰刀菌(F. graminearm)定量在LightCycler®480 II PCR仪(Roche公司)上完成。对病原菌进行实时荧光定量PCR时选用的引物对为F. graminearum-F (5′-GCGACGATTACCA GTAACGATG-3′)和F. graminearum-R (5′-GG TGAACCAGCGGAGGGAT-3′)。PCR反应体系(10 μL)：SYBR Green预混料2×Ex Taq (TaKaRa公司) 5 μL，上、下游引物(10 μmol/L)各0.5 μL，预扩增模板(5-20 ng/μL) 3 μL，无菌水1 μL。PCR反应条件：95 ℃预变性4 min；95 ℃变性30 s，60 ℃退火20 s，72 ℃延伸20 s，40个循环；72 ℃延伸5 min。取含有目的基因的质粒通过10倍稀释法构建稀释曲线，并用无菌水替代样本作为阴性对照。标准曲线扩增效率为95.7%，R2为0.991。获得的扩增数据在Excel 2023中整理并计算病原菌丰度。
1.3 植物微生物高通量测序和生物信息分析
微生物测序分析基于Illumina MiSeq PE250平台，对细菌16S rRNA基因V4区进行扩增时选用的引物对为515F (5′-GTGCCAGCM GCCGCGGTAA-3′)和806R (5′-GGACTACHV GGGTATCTAAT-3′)[17]，对真菌ITS1扩增时选用的引物对为ITS5-1737F (5′-GGAAGTAAAA GTCGTAACAAGG-3′)和ITS2-2043R (5′-GCT GCGTTCTTCATCGATGC-3′)[18]。为区分不同样品，使用在5′端携带独特的7 bp barcode序列的正向引物。PCR反应体系(25 μL)：2×Premix Taq™ (TaKaRa公司) 12.5 μL，上、下游引物(10 μmol/L)各0.5 μL，DNA提取液(5-20 ng/μL) 2 μL，无菌水9.5 μL。细菌PCR反应条件：95 ℃预变性3 min；95 ℃变性30 s，55 ℃退火30 s，75 ℃延伸45 s，35个循环；72 ℃延伸10 min。真菌PCR反应条件：95 ℃预变性5 min；94 ℃变性45 s，58 ℃退火50 s，68 ℃延伸30 s，35个循环；68 ℃延伸10 min。扩增产物用1.5%琼脂糖凝胶电泳检测，并用琼脂糖凝胶DNA回收试剂盒(Magen公司)回收。最后，将纯化的PCR产物混合并构建文库，在广州美格生物科技股份有限公司通过Illumina PE250测序平台测序。细菌和真菌原始测序数据存储在美国国家生物技术中心(National Center for Biotechnology Information, NCBI) GenBank数据库，登录号分别为PRJNA1164840 (细菌)和PRJNA1165465 (真菌)。
下机数据在QIIME 2 (v.2020.8)平台处理。首先去除barcode和引物序列，并且进行双端合并。然后使用q2-demux插件对原始数据进行拆分和质量过滤，去除平均Phred得分(Q得分)低于20、引物不匹配以及序列长度小于150 bp的原始序列。使用DADA2去噪[19]，去除嵌合体，并且采用100%相似聚类得到扩增序列变体(amplicon sequence variants, ASVs)，最后基于数据库silva132[20]和UNITE database (v88.0, 2018.08, https://unite.ut.ee/)分别对细菌和真菌进行物种注释。对得到的ASVs进行进一步质量控制，首先去除古菌、叶绿体和线粒体ASVs，然后过滤掉总序列和小于20的ASVs。最后为了后续分析，统一测序深度，抽平得到每个样本真菌64 108 reads，细菌10 610 reads，用于微生物数据统计分析。
1.4 数据统计及分析
使用R.4.0.2 (http://www.r-project.org)的“vegen”包计算各个样品微生物群落的丰富度和Shannon指数，评估微生物群落的丰富度和均匀度。利用健康与患病小麦间ASVs相对丰度正态分布均值的偏差来计算微生物群落平均变异度来评估群落稳定性[21]。基于Wilcoxon test检验确定健康与患病样本间微生物群落α多样性、群落稳定性和病原菌丰度的差异。利用主坐标分析(principal co-ordinates analysis, PCoA)计算样品间的Bray-Curtis距离指数并降维可视化，分析微生物群落的β多样性，并采用“vegan”中置换多元方差分析(permutational multivariate analysis of variance, PERMANOVA)评估病害发生对微生物群落组成的影响。最后通过线性回归分析确定微生物多样性与禾谷镰刀菌丰度的相关性。
利用在线平台(http://huttenhower.sph.harvard.edu/galaxy)进行线性判别分析(linear discriminant analysis, LDA)，判断健康和患病植株间具有显著差异的物种，然后通过R软件以火山图的形式在ASVs (平均相对丰度>0.05%)水平上展示健康和患病植株根际土壤和穗部的生物标志物[22]。将筛选出的生物标志物(ASVs)和病原菌丰度使用R语言的“psych”包获得相关性矩阵，最后利用Gephi 0.9.2进行网络可视化。
基于ASVs水平对健康和患病植株细菌和真菌群落进行跨界微生物共现网络分析。首先过滤掉相对丰度小于0.01%的物种，再使用R语言的“psych”包获得相关性矩阵，最后利用Gephi 0.9.2计算细菌和真菌交互的网络拓扑参数，并实现可视化。基于Wilcoxon test检验确定健康与患病样本间网络稳定性的差异。最后通过线性回归分析分析网络稳定性与禾谷镰刀菌丰度之间的关系。
采用R软件进行随机森林模型(random forest)分析，评估微生物多样性和网络稳定性对禾谷镰刀菌定殖的影响，计算过程使用“randomForest”包进行运算，不同因子贡献度显著性使用“rfPermute”包进行计算。
2 结果与分析
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2.1 病原菌丰度
由图1C可知，患病小麦穗部病原菌禾谷镰刀菌的丰度显著高于健康小麦穗部(P<0.01)，其中患病小麦穗部的病原菌丰度高达 5.00×1010 copies/g，与健康小麦穗部相比，增加了94.66%。然而，定量结果显示不同植物状态下根际病原菌的丰度未表现出显著性差异(图1D，P>0.05)。表明病害发生后，病原菌仅在患病部分显著富集，暗示着穗部微生物群落与病原菌存在更强烈的相互作用。
2.2 植物微生物多样性及其与病原菌丰度的关联分析
微生物多样性分析结果表明，根际微生物的α多样性(包括细菌和真菌群落)均高于小麦穗部的α多样性(图2A、2B、2D、2E)。在细菌群落中，患病植株穗部微生物丰富度指数和香农指数均显著高于健康植株，然而根际微生物表现出相反的趋势，即在健康植株根际表现出更高的微生物α多样性(图2A、2B，P<0.05)。此外，对细菌群落的变异度分析结果显示，患病植株微生物群落变异度显著高于健康植株，暗示着健康植株具有更稳定的细菌群落(图2C)。在真菌群落多样性分析中，我们发现真菌丰富度指数和香农指数在健康和患病植株之间的变化趋势与细菌群落相反(图2D、2E，P<0.05)，进一步对真菌群落变异性分析发现，仅在小麦穗部发现患病植株群落变异度显著高于健康植株(P<0.05)，不同处理间根际真菌群落变异度无显著差异(图2F，P<0.05)。
基于PERMANOVA检验分析发现，健康植株与患病植株微生物群落结构间存在显著差异(图2G-2J)。其中，健康与发病两种植物状态对小麦穗部微生物群落结构变异的解释度(细菌R2=17.84%，真菌R2=55.54%)大于根际土壤(细菌R2=2.65%，真菌R2=5.48%)，且真菌对病害发生的响应大于细菌群落。表明：真菌群落更容易受到病害胁迫的干扰。
植物关联的微生物群落与病原菌禾谷镰刀菌丰度的相关性结果显示，在根际土壤中，真菌的丰富度指数和群落变异度与病原菌的丰度显著负相关(P<0.05)，细菌群落特征与病原菌丰度不存在显著关联(图3A、3B，P>0.05)。然而，在小麦穗部，细菌α多样性指数以及细菌和真菌群落高度变异性与病原菌丰度显著正相关(P<0.05)，真菌α多样性与病原菌丰度的关系则表现出相反的趋势(图3E-3H，P<0.05)。这些结果表明，高度变异的微生物群落更有利于病原菌侵染定殖，细菌和真菌对病害胁迫的响应表现出相反的适应策略。同时，多样性与病原菌丰度的显著关联也暗示着部分微生物类群与病原菌间存在一定的互作。基于这种推测，我们进一步对根际和穗部的微生物组成进行分析。
2.3 植物微生物组成和物种差异分析
在细菌门水平上，根际细菌以变形菌门(Proteobacteria)、拟杆菌门(Bacteroidota)、酸杆菌门(Acidobacteriota)、绿弯菌门(Chloroflexi)以及放线菌门(Actinobacteriota)为主，而穗部细菌则表现出不一样的群落组成，主要以变形菌门(Proteobacteria)、拟杆菌门(Bacteroidota)、放线菌门(Actinobacteriota)和厚壁菌门(Firmicutes)为主(图4A)。值得注意的是，健康小麦穗部放线菌门的相对丰度显著高于患病植株，根际土壤中放线菌则表现出相反的趋势(图4B，P<0.05)。在真菌纲水平上，根际真菌主要以粪壳菌纲(Sordariomycetes)、座囊菌纲(Dothideomycetes)、锤舌菌纲(Leotiomycetes)、被孢霉纲(Mortierellomycetes)和伞菌纲(Agaricomycetes)以及一些未知的真菌纲；在小麦穗部，健康植株和患病植株真菌群落组成差异较大，健康植株穗部真菌主要以未知的纲类群为主，患病植株穗部真菌以粪壳菌纲(Sordariomycetes)为主(图4C)。群落组成差异分析显示，小麦穗部患病植株粪壳菌纲(Sordariomycetes)相对丰度显著高于健康植株，伞菌纲(Agaricomycetes)和微球黑粉菌纲(Microbotryomycetes)在健康植株穗部的相对丰度显著高于患病植株(图4D)。
基于ASVs水平差异分析显示，在患病植株根际和穗部分别有13个和73个ASVs富集，其次，仅在细菌中发现有7个ASVs在健康植株根际富集(图5A、5B)。在真菌群落中，患病植株根际和穗部分别有72个和6个真菌ASVs富集，健康植株根际和穗部分别有34个和7个真菌ASVs富集(图5C、5D)。这些结果表明，病害发生后更多的细菌和真菌类群在患病样本中富集，其中细菌主要在穗部富集，真菌主要在根际富集。为了进一步明确这些差异物种和病原菌丰度变化的关系，将病原菌丰度与这些ASVs的相对丰度进行相关性分析。结果显示，在根际土壤中，病原菌丰度主要与真菌ASVs呈现显著负相关关系(图5E)。在小麦穗部，病原菌丰度与差异物种间呈现显著正相关关系，这些微生物类群主要归属于潜在有益菌群Pseudomonas、马赛菌属(Massilia)、土地杆菌属(Pedobacter)、鞘氨醇单胞菌属(Sphingomonas)、杜擀氏菌属(Duganella)等细菌类群，以及真菌枝孢菌属(Cladosporium)、附球菌属(Epicoccum)和潜在植物病原菌镰刀菌(Fusarium) (图5F)。
2.4 微生物共现性网络分析
为了探究小麦赤霉病胁迫对植物微生物互作的影响，在ASVs水平上构建了细菌-真菌跨界共现网络，旨在明确小麦赤霉病对微生物潜在的相互作用的影响。总的来说，小麦穗部微生物网络与根际表现出相反的趋势。小麦穗部在病害发生后表现出更复杂的网络模式，网络节点和网络边数均高于健康植株，而根际土壤微生物网络在病害发生后变得更加简单，其节点和边的数量分别下降了21.77%和31.43% (图6A、6B和表1)。此外，病害发生后小麦穗部网络节点中细菌所占比例增加26.42%，在根际土壤中则表现出下调的趋势(表1)。微生物网络稳定性分析结果显示，健康植株在小麦穗部的网络稳定性显著高于患病植株(P<0.05)，根际未发现显著差异(图6C，P>0.05)。进一步将网络稳定性与病原菌丰度进行相关性分析发现，根际微生物网络稳定性与病原菌丰度呈现显著正相关关系(图6D，P<0.05)，而小麦穗部微生物网络稳定性与病原菌丰度呈现极显著负相关关系(图6E，P<0.001)。以上结果表明，小麦赤霉病的发生会促使发病部位微生物网络变得更加复杂，削弱根际网络复杂性。同时，网络稳定性的结果也暗示着稳定的微生物互作模式有利于抑制病原菌的侵染。
2.5 植物微生物群落变化对病原菌丰度的预测
基于以上结果分析，明确了植物微生物多样性、群落组成和微生物互作与病原菌丰度的变化存在关联。为了进一步明确和量化微生物参数对病原菌丰度的影响，通过随机森林模型分别对小麦根际和穗部病原菌丰度进行预测分析。结果表明，在根际土壤中，微生物参数对病原菌丰度变化的解释量仅有5.47%，其中细菌群落变异度和α多样性对病原菌丰度的变化具有显著影响(图7A)。与之不同的是，小麦穗部微生物参数对病原菌丰度变化的解释量高达76.95%，其中真菌群落对病原菌丰度变化的影响高于细菌和网络稳定性(图7B)。
3 讨论
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3.1 小麦赤霉病发生影响植物微生物多样性和群落稳定性
当植物受到病原菌胁迫时，会通过释放根系分泌物来招募有益的植物微生物，从而增强自身抵御病原体侵染的抗性[23-24]。在已报道的机制中，根际微生物α多样性在维持群落稳定性和协助宿主抗病害胁迫方面起着至关重要的作用[25]。我们的研究指出，小麦赤霉病的发生导致小麦穗部细菌和根际真菌多样性显著增加，结合差异物种分析显示，穗部细菌和根际真菌多样性的增加与病害发生后微生物类群的富集有关。这种现象可能归因于宿主免疫系统施加的较强选择压力，以及病原体入侵后植物释放信号型代谢产物的招募[26-27]。此外，我们的研究结果与前人研究类似[28]，在小麦赤霉病胁迫下，宿主增强了对植物微生物的招募作用，值得一提的是，这种招募作用同样可以发生在小麦穗部。其次，我们发现健康植株具有更高的群落稳定性，患病植株的群落变异度更高。这一结果符合安娜-卡列妮娜原理，即健康的植物微生物组是相似且稳定的，而患病植物的微生物组则具有更多的变数，群落稳定性较弱[29]。最后，结合微生物多样性和群落组成与病原菌丰度的相关性分析，揭示了植物微生物群落变化与病害发生的关系，并表明小麦穗部稳定的微生物群落不利于病原菌的定殖。
3.2 小麦赤霉病发生诱导植物微生物富集，降低网络稳定性
探究与病害关联的微生物类群对于指导植物病害生物防控策略至关重要。本研究继续探究了微生物类群的变化与病害的关系。在门水平上，发现放线菌门在健康的小麦穗部显著富集。放线菌通常被认为是拮抗类细菌，可以通过产生抗真菌化合物或高生态位重叠竞争养分资源抑制真菌病原菌生长[30-31]。放线菌在健康植株穗部的富集可能支撑了植物宿主对病原菌入侵的抵御。其次，发现粪壳菌纲在患病植株穗部富集，而植物病原菌禾谷镰刀菌属于粪壳菌纲，因此，粪壳菌纲在患病样本的富集可能归因于患病植株中高丰度的病原菌存在。随后，探讨了ASVs水平上微生物类群在患病植株样本上的富集与损耗。结果表明，更多的潜在有益菌群，比如Pseudomonas、Massilia、Pedobacter、Sphingomonas和Duganella在患病植株小麦穗部富集。这些菌对植物抗胁迫的作用在前人研究中被发现，例如小麦穗部微生物Pseudomonas分泌的吩嗪-1-羧酰胺可以直接操纵真菌组蛋白修饰，抑制致病性禾谷镰刀菌，增强小麦对赤霉病的抗性[8]。Massilia和Duganella则是具有抗菌活性，有利于植物健康的微生物类群，它们也可以通过调节植物根际土壤的固氮和钾的溶解作用来促进植物生长[32-33]。这些结果表明了小麦赤霉病胁迫下，植物可能通过“呼救”策略招募有益微生物类群来增强其抗胁迫能力[11]。此外，通过对小麦赤霉病胁迫下微生物网络互作的研究发现，健康与患病小麦穗部微生物网络性质存在显著差异，稳定性强的网络可能更不利于病原菌的侵染与定殖。这与前人研究结果类似，即与连通性和稳定性较低的网络相比，连通性较高且稳定的微生物网络对环境扰动的适应能力更强[34-35]。
综上所述，本研究结果表明小麦赤霉病胁迫下，植物微生物多样性增加，群落稳定性下调，更多潜在有益菌在患病部位富集，微生物网络变得更加复杂，但网络稳定性降低。相应地，健康植株之所以对病原菌侵染表现出较强的抗性，可能更多地归因于微生物群落的稳定性以及抑菌类群的富集。
4 结论
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本研究基于高通量测序和基因定量技术对健康植株和患病植株穗部与根际微生物群落比较分析，并将其与病原菌丰度进行关联分析。研究结果表明，小麦赤霉病的发生以及病原菌丰度的变化主要与小麦穗部微生物群落变化有关。植物通常可以通过调节植物微生物群落组成和平衡来维持自身健康，在本研究中发现健康植株微生物群落和网络具有更高的稳定性，且相比患病植株，健康植株穗部的潜在拮抗菌放线菌门显著富集，其他潜在有益菌Pseudomonas、Massilia、Pedobacter、Sphingomonas等在患病小麦穗部富集，这些菌群在前人的研究中被发现可以通过产生抗生素、直接抑制病原菌生长或诱导宿主抗性等途径帮助植物抵御病原菌侵染，具有作为生物防治剂的潜力。
本研究表明微生物群落的稳定性和抑菌类群的富集塑造了更加健康的植物状态。这些微生物群落的变化均与病原菌的丰度显著相关，表明穗部微生物菌群可能在植物抵御病原菌侵染过程中发挥重要作用。本研究从植物微生物对病害胁迫的响应特征入手，为挖掘潜在的生防菌群防治植物病害提供重要的数据支撑，未来的研究需要结合培养组学进一步挖掘植物对有益菌的招募机制和这些微生物类群的抑病机制。
基金
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  • 国家重点研发计划(2022YFA1304400)
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doi: 10.13343/j.cnki.wsxb.20240594
  • 接收时间：2024-09-27
  • 首发时间：2026-02-05
  • 出版时间：2025-02-04
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  • 收稿日期：2024-09-27
  • 录用日期：2024-11-12
基金
National Key Research and Development Program of China(2022YFA1304400)
国家重点研发计划(2022YFA1304400)
作者信息
    1 江西理工大学 资源与环境工程学院，江西 赣州
    2 宁波大学 植物病毒学研究所，浙江 宁波

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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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