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黄土高原雨养区不同种植年限紫花苜蓿土壤细菌群落特征与生态功能预测
引用本文:马欣,罗珠珠,张耀全,刘家鹤,牛伊宁,蔡立群.黄土高原雨养区不同种植年限紫花苜蓿土壤细菌群落特征与生态功能预测[J].草业学报,2021,30(3):54-67.
作者姓名:马欣  罗珠珠  张耀全  刘家鹤  牛伊宁  蔡立群
作者单位:甘肃农业大学资源与环境学院,甘肃 兰州 730070;延安市农业科学研究所,陕西 延安 716000;甘肃农业大学资源与环境学院,甘肃 兰州 730070;甘肃省干旱生境作物学重点实验室,甘肃 兰州 730070;甘肃农业大学资源与环境学院,甘肃 兰州 730070;甘肃农业大学资源与环境学院,甘肃 兰州 730070;甘肃省干旱生境作物学重点实验室,甘肃 兰州 730070;甘肃农业大学资源与环境学院,甘肃 兰州 730070;甘肃省干旱生境作物学重点实验室,甘肃 兰州 730070
基金项目:国家自然科学基金项目;甘肃省科技计划项目;甘肃省国际科技合作基地
摘    要:依托布设在黄土高原雨养农业区的长期田间定位试验,以农田土壤为对照,不同种植年限紫花苜蓿地(L2003,L2005,L2012)土壤为研究对象,采用细菌16S rRNA高通量测序技术探究以上3种土壤细菌群落分布格局与演替特征,并借助冗余分析等方法探讨土壤理化性质与细菌群落结构和多样性的关系,最后利用PICRUSt方法预测了土壤细菌群落生态功能。结果表明,黄绵土区门水平优势菌群为放线菌门(20.34%~32.40%)、变形菌门(18.99%~23.14%)、酸杆菌门(12.50%~13.39%)和绿弯菌门(11.41%~12.55%)。放线菌门、变形菌门和绿弯菌门相对丰度表现为农田土壤高于苜蓿土壤,且放线菌门相对丰度随苜蓿种植时间延长呈降低趋势,变形菌门和绿弯菌门相对丰度随苜蓿种植时间的延长先增加后降低;酸杆菌门相对丰度在农田和苜蓿地无明显差异。黄绵土属水平优势类群包括Gaiella属(1.65%~3.33%)、硝化螺菌属(1.52%~2.34%)、假节杆菌属(1.36%~2.61%)和Solirubrobac?ter属(1.03%~2.24%)。与农田相比,苜蓿土壤Solirubrobacter属相对丰度显著增加(P<0.05)。冗余分析(RDA)表明,土壤全磷(P=0.002)是影响细菌群落结构变化的主要因子。PICRUSt功能预测表明,黄绵土细菌菌群共有46个子功能,其中代谢为最主要的功能,占比为69.20%~70.22%;苜蓿土壤代谢、生物体系统功能基因丰度均显著高于农田土壤,具体表现在碳水化合物代谢、外源物质降解及代谢、萜类和酮类化合物代谢、内分泌系统、神经系统和物质依赖功能基因中。苜蓿种植年限可影响黄绵土细菌群落结构和代谢功能,该结果可为西部黄土高原紫花苜蓿人工草地的可持续利用和黄绵土细菌代谢潜力及功能预测提供参考。

关 键 词:紫花苜蓿  高通量测序  细菌群落结构  PICRUSt功能预测

Distribution characteristics and ecological function predictions of soil bacterial communities in rainfed alfalfa fields on the Loess Plateau
MA Xin,LUO Zhu-zhu,ZHANG Yao-quan,LIU Jia-he,NIU Yi-ning,CAI Li-qun.Distribution characteristics and ecological function predictions of soil bacterial communities in rainfed alfalfa fields on the Loess Plateau[J].Acta Prataculturae Sinica,2021,30(3):54-67.
Authors:MA Xin  LUO Zhu-zhu  ZHANG Yao-quan  LIU Jia-he  NIU Yi-ning  CAI Li-qun
Institution:(College of Resources and Environmental Sciences,Gansu Agricultural University,Lanzhou 730070,China;Gansu Provincial Key Laboratory of Arid Land Crop Science,Lanzhou 730070,China;Yan’an Institute of Agricultural Sciences,Yan’an 716000,China)
Abstract:A field study was conducted to investigate crop land and alfalfa land established for different lenghths of time ment years(L2003,L2005 and L2012)on soil bacterial communities and ecological function prediction.Soil bacterial communities were identified by high-throughput sequencing 16S rRNA gene amplicons.The Illumina MiSeq high-throughput sequencing technology was used to explore the structure and diversity of bacterial communities under three treatments,and statistical methods(such as redundancy analysis)were used to explore the relationship between soil physical and chemical properties and bacterial community structure and diversity.PICRUSt software was applied to predict the ecological function of soil bacterial communities present in different treatments.The results indicated that the predominant taxa at the phylum level are Actinobacteria,Proteobacteria,Acidobacteria and Chloroflexi of bacteria in loess soil,comprising 20.34%-32.40%,18.99%-23.14%,12.50%-13.39%,and 11.41%-12.55%of the microbial population,respectively.The relative abundance of Actinobacteria,Proteobacteria and Chloroflexi was higher in farmland soil than in alfalfa soil.The relative abundance of Actinobacteria showed a decreasing trend with increase in the stand age,and the relative abundance of Proteobacteria and Chlorophyta initially increased and then decreased with increasing stand age.The relative abundance of Acidobacteria did not differ significantly between farmland and alfalfa soil.The dominant bacterial genera of this loess soil were Gaiella,Nitrospira,Pseudarthrobacter and Solirubrobacter,which comprised 0.65%-3.33%,1.52%-2.34%,1.36%-2.61%and 1.03%-2.24%,respectively,of the microbial population.Compared with farmland,the relative abundance of the Solirubrobacter genus was significantly increased in alfalfa land.Redundancy analysis showed that soil total phosphorus is the main factor affecting the soil bacterial community structure.PICRUSt function prediction analysis indicates that the bacterial microbiota of the loessial soil has a total of 46 sub-functions,of which metabolism is the most important function,accounting for 69.20%to 70.22%of activity.Soil metabolism,genetic information processing,and biological system functional gene abundance of alfalfa soils were significantly higher than those in farmland soil,and these characteristics were specifically reflected in carbohydrate metabolism,exogenous substance degradation and metabolism,terpenoid and ketone metabolism,endocrine system,nervous system and substance dependent functional genes.This study emphasizes the bacterial community structure and metabolic function in loessial soil and the findings provide a strategy to enhance the sustainability of alfalfa fields through soil microbial community management.
Keywords:Medicago sativa  high-throughput sequencing  bacterial community structure  function prediction with PICRUSt
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