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Database and primer selections affect nematode community composition under different vegetations of Changbai Mountain

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Soil Ecology Letters 2023年第1期5卷 142-150页

作者： Yixin Sun Xiaofang Du Yingbin Li Xu Han Shuai Fang stefan geisen Qi Li CAS Key Laboratory of Forest Ecology Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China University of Chinese Academy of Sciences Beijing 100049China Laboratory of Nematology Wageningen UniversityWageningenThe Netherlands

High-throughput sequencing technology is increasingly used in the study of nematode biodiversity.However,the annotation difference of commonly used primers and reference databases on nematode community is still unclear.We compared two pairs of primers(3NDf/C_1132rmod,NF1F/18Sr2bR)and three databases(NT_V20200604,SILVA138/18s Eukaryota and PR2_v4.5 databases)on the determination of nematode community from four different vegetation types in Changbai Mountain,including mixed broadleaf-conifer forest,dark coniferous forest,betula ermanii Cham and alpine tundra.Our results showed that the selection of different primers and databases influenced the annotation of nematode taxa,but the diversity of nematode community showed consistent pattern among different vegetation types.Our findings emphasize that it is necessary to select appropriate primer and database according to the target taxonomic level.The difference in primers will affect the result of nematode taxa at different classification levels,so sequencing analysis cannot be used for comparison with studies using different primers.In terms of annotation effect in this study,3NDf/C_1132rmod primers with NT_v20200604 database could provide more information than other combinations at the genus or species levels.

关键词： Soil nematodes Primer Database High-throughput sequencing Community composition

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Rhizosphere immunity: targeting the underground for sustainable plant health management

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Frontiers of Agricultural Science and Engineering 2020年第3期7卷 317-328页

作者： Zhong WEI Vill-Petri FRIMAN Thomas POMMIER stefan geisen Alexandre JOUSSET Qirong SHEN Key Laboratory of Plant Immunity Jiangsu Key Laboratory for Organic Solid Waste UtilizationNational Engineering Research Center for Organic-Based FertilizersNanjing Agricultural UniversityNanjing 210095China Department of Biology University of YorkYorkYO105DDUK Ecologie Microbienne UMR1418French National Institute for Agricultural Research(INRA)University Lyon IF-69622 VilleurbanneFrance Laboratory of Nematology Wageningen University and Research6700ES Wageningenthe Netherlands Institute of Environmental Biology Ecology and BiodiversityUtrecht University3584CH Utrechtthe Netherlands

Managing plant health is a great challenge formodern food production and is further complicated by thelack of common ground between the many disciplinesinvolved in disease control. Here we present the concept ofrhizosphere immunity, in which plant health is consideredas an ecosystem level property emerging from networks ofinteractions between plants, microbiota and the surround-ing soil matrix. These interactions can potentially extendthe innate plant immune system to a point where therhizosphere immunity can fulfil all four core functions ofafull immune system: pathogen prevention, recognition,response and homeostasis. We suggest that consideringplant health from a meta-organism perspective will help indeveloping multidisciplinary pathogen management stra-tegies that focus on steering the whole plant-microbe-soilnetworks instead of individual components. This might beachieved by bringing together the latest discoveries inphytopathology, microbiome research, soil science andagronomy to pave the way toward more sustainable andproductive agriculture.

关键词： rthizosphere soil microbiome plant immunity microbial ecology plant health soilborme pathogens

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The relative importance of soil moisture in predicting bacterial wilt disease occurrence

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Soil Ecology Letters 2021年第4期3卷 356-366页

作者： Gaofei Jiang Ningqi Wang Yaoyu Zhang Zhen Wang Yuling Zhang Jiabao Yu Yong Zhang Zhong Wei Yangchun Xu stefan geisen Ville-Petri Friman Qirong Shen Key Laboratory of Plant immunity Jiangsu Provincial Key Laboratory for Organic Solid Waste UtilizationJiangsu Collaborative Innovation Center for Solid Organic Waste Resource UtilizationNational Engineering Research Center for Organic-based FertilizersNanjing Agricultural UniversityNanjing 210095China College of Resources and Environment Key Laboratory of Efficient Utilization of Soil and Fertilizer ResourcesSouthwest UniversityChongqing 400715China Laboratory of Nematology Wageningen University&ResearchWageningenThe Netherlands Department of Biology University of YorkYO105DDUK

Soil-borne plant diseases cause major economic losses globally.This is partly because their epidemiology is difficult to predict in agricultural fields,where multiple environmental factors could determine disease outcomes.Here we used a combination of field sampling and direct experimentation to identify key abiotic and biotic soil properties that can predict the occurrence of bacterial wilt caused by pathogenic Ralstonia solanacearum.By analyzing 139 tomato rhizosphere soils samples isolated from six provinces in China,we first show a clear link between soil properties,pathogen density and plant health.Specifically,disease outcomes were positively associated with soil moisture,bacterial abundance and bacterial community composition.Based on soil properties alone,random forest machine learning algorithm could predict disease outcomes correctly in 75%of cases with soil moisture being the most significant predictor.The importance of soil moisture was validated causally in a controlled greenhouse experiment,where the highest disease incidence was observed at 60%of maximum water holding capacity.Together,our results show that local soil properties can predict disease occurrence across a wider agricultural landscape,and that management of soil moisture could potentially offer a straightforward method for reducing crop losses to R.solanacearum.

关键词： Bacterial wilt disease Soil moisture Soil physicochemical properties Rhizosphere bacterial communities Ralstonia solanacearum Random forest algorithm

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联合接种原生动物和木霉对黄瓜生长及土壤微生物区系的影响

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南京农业大学学报 2023年第2期46卷 297-305页

作者：莫雅旎郭赛欧燕楠焦子轩黄若菱李荣沈宗专 geisen stefan 沈其荣南京农业大学资源与环境科学学院/江苏省固体有机废弃物资源化研究重点实验室/江苏省有机固体废弃物协同创新中心/教育部资源节约型肥料工程技术研究中心江苏南京210095 瓦赫宁根大学荷兰瓦赫宁根6708PB

[目的]本文旨在探究吞噬性原生动物、真菌及两者联合对黄瓜生长和土壤微生物群落组成的影响。[方法]供试黄瓜品种为‘露丰黄瓜’,采用盆栽试验,设计不接种对照(CK)、单独接种贵州木霉(Trichoderma guizhouense NJAU 4742)(T处理)、单独... 详细信息

[目的]本文旨在探究吞噬性原生动物、真菌及两者联合对黄瓜生长和土壤微生物群落组成的影响。[方法]供试黄瓜品种为‘露丰黄瓜’,采用盆栽试验,设计不接种对照(CK)、单独接种贵州木霉(Trichoderma guizhouense NJAU 4742)(T处理)、单独接种丝竹虫(Cercomomnas lenta)(C处理)、组合接种丝竹虫和贵州木霉(T+C处理)4个处理,处理2周后采集植株及土壤样品,评估各处理对黄瓜性状及土壤细菌和真菌群落的影响。[结果]相较于CK,T、C和T+C 3个处理黄瓜株高分别增加6.0%、12.5%和21.5%,生物量分别提高5.6%、12.9%和24.0%,即贵州木霉和丝竹虫均能促进黄瓜生长且两者组合能够进一步增强促生效应。基于主坐标分析发现,3个处理均显著改变了土壤细菌和真菌群落组成,随机森林模型进一步发现细菌和真菌群落组成是影响黄瓜生物量的主要因素。线性判别分析发现,与CK相比,3个处理分别激发22、51和82个关键细菌操作分类单元(OTU),2、6和16个关键真菌OTU;T+C处理激发了更多的与黄瓜促生相关的OTU,其中,有21个关键细菌OTU仅在T+C处理中被激发,对黄瓜促生贡献最大的分别归属于Parasediminibacterium、Fluviicola和Roseimaritima;有11个关键真菌OTU仅在T+C处理中被激发,对黄瓜促生贡献最大的分别归属于隔指孢属、Melanoleuca和毛壳菌属。[结论]相比于单一接种,丝竹虫和木霉组合接种后能更显著促进黄瓜生长,两者协同调控土著细菌和真菌群落,激发并富集潜在的土著功能微生物以塑造更有利于黄瓜生长的土壤微生物群落。

关键词：黄瓜原生动物木霉接种土壤微生物群落促生

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