Article(id=1192149550044430444, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1192149543010582589, articleNumber=null, orderNo=null, doi=10.13343/j.cnki.wsxb.20250250, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1743091200000, receivedDateStr=2025-03-28, revisedDate=null, revisedDateStr=null, acceptedDate=1750348800000, acceptedDateStr=2025-06-20, onlineDate=1762160201797, onlineDateStr=2025-11-03, pubDate=1756915200000, pubDateStr=2025-09-04, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1762160201797, onlineIssueDateStr=2025-11-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1762160201797, creator=13701087609, updateTime=1762160201797, updator=13701087609, issue=Issue{id=1192149543010582589, tenantId=1146029695717560320, journalId=1192105938417971205, year='2025', volume='65', issue='10', pageStart='4241', pageEnd='4713', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1762160200113, creator=13701087609, updateTime=1762160638682, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1192151382586175735, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1192149543010582589, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1192151382586175736, tenantId=1146029695717560320, journalId=1192105938417971205, issueId=1192149543010582589, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4684, endPage=4699, ext={EN=ArticleExt(id=1192149550220591213, articleId=1192149550044430444, tenantId=1146029695717560320, journalId=1192105938417971205, language=EN, title=Effects of organic-inorganic fertilization regime alterations on microbial community structures in paddy soils, columnId=1192149543992045670, journalTitle=Acta Microbiologica Sinica, columnName=Research Article, runingTitle=null, highlight=null, articleAbstract=

[Objective] To investigate the effects of fertilization regime alterations on microbial communities in paddy soils. [Methods] We conducted a long-term field experiment with three treatments: chemical fertilizer (H) and H converted to a conventional amount of organic fertilizer (HC), a conventional amount of organic fertilizer (C) and C converted to chemical fertilizer (CH), and a high amount of organic fertilizer (G) and G converted to chemical fertilizer (GH). Metagenomic sequencing was combined with bioinformatics analysis to assess the structures, diversity, and co-occurrence networks of microbial communities in paddy soils. [Results] Compared with the H treatment, the HC treatment increased the soil organic carbon, dissolved organic carbon, total nitrogen, and alkali-hydrolyzable nitrogen (P<0.05). The CH and GH treatments exhibited lower soil carbon and nitrogen levels than C and G treatments, respectively. The HC treatment markedly altered the relative abundance of Acidobacteriota, Nitrospirota, Candidatus Rokubacteria, Mucoromycota, and Thaumarchaeota. The CH treatment showed no significant changes in microbial composition at the phylum level, whereas the GH treatment significantly modified the relative abundance of Nitrospirota and the archaeal community structure. Although fertilization regime alterations showed no significant effect on microbial alpha diversity (P>0.05), the beta diversity differed across treatments (P<0.05). Co-occurrence network analysis demonstrated that the HC treatment enhanced the network complexity relative to the H treatment, with increased nodes (181), edges (2 935), average degree (16.215), modularity (0.757), and clustering coefficient (0.495). The CH treatment showed more edges (3 894) and higher average degree (21.514) but lower modularity (0.599) than the C treatment (0.751). Conversely, the GH treatment diminished all network topology parameters relative to G. Redundancy analysis identified dissolved organic carbon (22.1%), soil pH (16.8%), total nitrogen (15.6%), ammonium nitrogen (14.6%), available potassium (11.8%), and available phosphorus (10.6%) as the primary drivers of microbial community variations. [Conclusion] The findings indicate that fertilization regime alterations influence the microbial community structure and network characteristics in paddy soils by modifying soil physicochemical properties. Transitioning from chemical to organic fertilization enhances microbial community stability and soil ecological functions, while replacing organic with chemical fertilization reduces soil carbon and nitrogen availability, potentially compromising microbial network complexity and resilience.

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【目的】 探究变更施肥对水稻土微生物群落的影响。 【方法】 在长期定位试验田中设置3组变更施肥模式处理:化肥与化肥改常量有机肥;常量有机肥与常量有机肥改化肥;高量有机肥与高量有机肥改化肥。通过宏基因组测序结合生物信息学分析研究施肥模式变更对土壤微生物群落结构、多样性及互作网络的影响。 【结果】 与化肥处理相比,化肥改常量有机肥处理显著提高了土壤有机碳、溶解性有机碳、全氮和碱解氮的含量(P<0.05)。常量有机肥改化肥处理和高量有机肥改化肥处理的土壤碳、氮水平分别低于常量有机肥处理和高量有机肥处理。化肥改常量有机肥处理显著改变了酸杆菌、硝化螺菌、Candidatus Rokubacteria、毛霉菌和奇古菌的丰度;常量有机肥改化肥处理未显著改变水稻土微生物群落的相对丰度(门水平);高量有机肥改化肥处理显著改变了硝化螺菌的相对丰度和古菌群落的组成。改变施肥模式对土壤微生物α多样性无显著影响(P>0.05),但不同施肥处理之间微生物群落的β多样性存在显著差异(P<0.05)。网络分析显示,与化肥处理相比,化肥改常量有机肥处理的节点数(181)、边数(2 935)、平均度(16.215)、模块化(0.757)及平均聚类系数(0.495)均更高;常量有机肥改化肥处理的边数(3 894)和平均度(21.514)高于常量有机肥处理,而模块化(0.599)低于常量有机肥处理(0.751);高量有机肥改化肥处理的网络拓扑参数均低于高量有机肥处理。冗余分析表明,溶解性有机碳(22.1%)、土壤pH (16.8%)、全氮(15.6%)、铵态氮(14.6%)、速效钾(11.8%)和有效磷(10.6%)是驱动微生物群落变化的主要因子。 【结论】 变更施肥模式通过改变土壤理化因子影响了水稻土微生物群落结构和网络特征。无机肥变更为有机肥可优化微生物群落结构,增强土壤生态功能;而有机肥变更为无机肥施入可能降低土壤碳、氮供应水平,对土壤微生物群落的稳定性和复杂性产生负面影响。

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作者贡献声明

王宇欣:全面参与试验设计、采样、数据处理、图表制作及论文撰写、修改;高清虹:样本采集、图表制作、论文构思与修改;樊婕:研究方案设计与论文撰写;孙耿:负责数据核查、理化性质分析;尹力初:提供试验基地、构思与论文审阅;聂三安:提供研究经费、研究构思、方案设计与论文修改。

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A: Composition of microbial communities in paddy soils; B-D: Compositional differences of bacterial, fungal, and archaeal communities at the phylum level. Mean±SE (n=3). 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Application rates of straw and fertilizer for different treatments in positioning experimental plots

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TreatmentMaize straw (kg/ha)Urea fertilizer (kg/ha)CaH2PO4(kg/ha)KCl (kg/ha)
H-321.53322.92193.75
C4 861.11213.89200.69149.31
G9 722.22106.9478.47104.17
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定位试验小区各处理秸秆及肥料用量

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TreatmentMaize straw (kg/ha)Urea fertilizer (kg/ha)CaH2PO4(kg/ha)KCl (kg/ha)
H-321.53322.92193.75
C4 861.11213.89200.69149.31
G9 722.22106.9478.47104.17
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Physicochemical properties of paddy soils under different fertilization regimes

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TreatmentpHSOC (g/kg)DOC (mg/kg)TN (g/kg)AN (mg/kg)NH4+-N (mg/kg)AP (mg/kg)AK (mg/kg)
H5.06±0.09a12.43±0.48b78.32±2.97b1.36±0.09b157.00±4.04b10.74±1.38a26.77±3.27a169.67±10.11b
HC5.13±0.05a15.47±0.61a106.56±6.09a1.78±0.07a202.67±15.34a14.70±2.81a18.23±3.46a242.67±23.02a
C5.12±0.01a15.60±0.89a100.60±4.87a1.63±0.06a186.67±5.70a12.18±1.70a14.10±2.47b234.33±26.14a
CH5.10±0.04a13.70±0.85a81.80±1.89b1.55±0.03a179.00±2.08a12.06±0.98a26.20±2.26a150.00±12.58b
G5.22±0.02a19.37±1.07a121.09±2.09a2.02±0.11a250.33±11.84a21.57±2.15a6.70±0.90b359.33±22.10a
GH5.19±0.06a14.53±0.35b103.22±3.09b1.64±0.06b213.00±3.79b20.07±3.56a18.33±2.87a207.67±18.02b
), ArticleFig(id=1192161295983063693, tenantId=1146029695717560320, journalId=1192105938417971205, articleId=1192149550044430444, language=CN, label=表2, caption=

不同施肥模式下水稻土理化性质

, figureFileSmall=null, figureFileBig=null, tableContent=
TreatmentpHSOC (g/kg)DOC (mg/kg)TN (g/kg)AN (mg/kg)NH4+-N (mg/kg)AP (mg/kg)AK (mg/kg)
H5.06±0.09a12.43±0.48b78.32±2.97b1.36±0.09b157.00±4.04b10.74±1.38a26.77±3.27a169.67±10.11b
HC5.13±0.05a15.47±0.61a106.56±6.09a1.78±0.07a202.67±15.34a14.70±2.81a18.23±3.46a242.67±23.02a
C5.12±0.01a15.60±0.89a100.60±4.87a1.63±0.06a186.67±5.70a12.18±1.70a14.10±2.47b234.33±26.14a
CH5.10±0.04a13.70±0.85a81.80±1.89b1.55±0.03a179.00±2.08a12.06±0.98a26.20±2.26a150.00±12.58b
G5.22±0.02a19.37±1.07a121.09±2.09a2.02±0.11a250.33±11.84a21.57±2.15a6.70±0.90b359.33±22.10a
GH5.19±0.06a14.53±0.35b103.22±3.09b1.64±0.06b213.00±3.79b20.07±3.56a18.33±2.87a207.67±18.02b
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有机-无机肥变更对水稻土微生物群落结构的影响
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王宇欣 1 , 高清虹 1 , 樊婕 1 , 孙耿 2 , 尹力初 1 , 聂三安 1
微生物学报 | 研究报告 2025,65(10): 4684-4699
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微生物学报 | 研究报告 2025, 65(10): 4684-4699
有机-无机肥变更对水稻土微生物群落结构的影响
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王宇欣1, 高清虹1, 樊婕1, 孙耿2, 尹力初1, 聂三安1
作者信息
  • 1湖南农业大学 资源学院,湖南 长沙
  • 2湖南省耕地与农业环境生态研究所,湖南 长沙
Effects of organic-inorganic fertilization regime alterations on microbial community structures in paddy soils
Yuxin WANG1, Qinghong GAO1, Jie FAN1, Geng SUN2, Lichu YIN1, San’an NIE1
Affiliations
  • 1College of Resources, Hunan Agricultural University, Changsha, Hunan, China
  • 2Hunan Cultivated Land and Agricultural Eco-environment Institute, Changsha, Hunan, China
出版时间: 2025-09-04 doi: 10.13343/j.cnki.wsxb.20250250
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【目的】 探究变更施肥对水稻土微生物群落的影响。 【方法】 在长期定位试验田中设置3组变更施肥模式处理:化肥与化肥改常量有机肥;常量有机肥与常量有机肥改化肥;高量有机肥与高量有机肥改化肥。通过宏基因组测序结合生物信息学分析研究施肥模式变更对土壤微生物群落结构、多样性及互作网络的影响。 【结果】 与化肥处理相比,化肥改常量有机肥处理显著提高了土壤有机碳、溶解性有机碳、全氮和碱解氮的含量(P<0.05)。常量有机肥改化肥处理和高量有机肥改化肥处理的土壤碳、氮水平分别低于常量有机肥处理和高量有机肥处理。化肥改常量有机肥处理显著改变了酸杆菌、硝化螺菌、Candidatus Rokubacteria、毛霉菌和奇古菌的丰度;常量有机肥改化肥处理未显著改变水稻土微生物群落的相对丰度(门水平);高量有机肥改化肥处理显著改变了硝化螺菌的相对丰度和古菌群落的组成。改变施肥模式对土壤微生物α多样性无显著影响(P>0.05),但不同施肥处理之间微生物群落的β多样性存在显著差异(P<0.05)。网络分析显示,与化肥处理相比,化肥改常量有机肥处理的节点数(181)、边数(2 935)、平均度(16.215)、模块化(0.757)及平均聚类系数(0.495)均更高;常量有机肥改化肥处理的边数(3 894)和平均度(21.514)高于常量有机肥处理,而模块化(0.599)低于常量有机肥处理(0.751);高量有机肥改化肥处理的网络拓扑参数均低于高量有机肥处理。冗余分析表明,溶解性有机碳(22.1%)、土壤pH (16.8%)、全氮(15.6%)、铵态氮(14.6%)、速效钾(11.8%)和有效磷(10.6%)是驱动微生物群落变化的主要因子。 【结论】 变更施肥模式通过改变土壤理化因子影响了水稻土微生物群落结构和网络特征。无机肥变更为有机肥可优化微生物群落结构,增强土壤生态功能;而有机肥变更为无机肥施入可能降低土壤碳、氮供应水平,对土壤微生物群落的稳定性和复杂性产生负面影响。

变更施肥  /  水稻土  /  宏基因组  /  有机-无机肥

[Objective] To investigate the effects of fertilization regime alterations on microbial communities in paddy soils. [Methods] We conducted a long-term field experiment with three treatments: chemical fertilizer (H) and H converted to a conventional amount of organic fertilizer (HC), a conventional amount of organic fertilizer (C) and C converted to chemical fertilizer (CH), and a high amount of organic fertilizer (G) and G converted to chemical fertilizer (GH). Metagenomic sequencing was combined with bioinformatics analysis to assess the structures, diversity, and co-occurrence networks of microbial communities in paddy soils. [Results] Compared with the H treatment, the HC treatment increased the soil organic carbon, dissolved organic carbon, total nitrogen, and alkali-hydrolyzable nitrogen (P<0.05). The CH and GH treatments exhibited lower soil carbon and nitrogen levels than C and G treatments, respectively. The HC treatment markedly altered the relative abundance of Acidobacteriota, Nitrospirota, Candidatus Rokubacteria, Mucoromycota, and Thaumarchaeota. The CH treatment showed no significant changes in microbial composition at the phylum level, whereas the GH treatment significantly modified the relative abundance of Nitrospirota and the archaeal community structure. Although fertilization regime alterations showed no significant effect on microbial alpha diversity (P>0.05), the beta diversity differed across treatments (P<0.05). Co-occurrence network analysis demonstrated that the HC treatment enhanced the network complexity relative to the H treatment, with increased nodes (181), edges (2 935), average degree (16.215), modularity (0.757), and clustering coefficient (0.495). The CH treatment showed more edges (3 894) and higher average degree (21.514) but lower modularity (0.599) than the C treatment (0.751). Conversely, the GH treatment diminished all network topology parameters relative to G. Redundancy analysis identified dissolved organic carbon (22.1%), soil pH (16.8%), total nitrogen (15.6%), ammonium nitrogen (14.6%), available potassium (11.8%), and available phosphorus (10.6%) as the primary drivers of microbial community variations. [Conclusion] The findings indicate that fertilization regime alterations influence the microbial community structure and network characteristics in paddy soils by modifying soil physicochemical properties. Transitioning from chemical to organic fertilization enhances microbial community stability and soil ecological functions, while replacing organic with chemical fertilization reduces soil carbon and nitrogen availability, potentially compromising microbial network complexity and resilience.

fertilization regime alteration  /  paddy soil  /  metagenome  /  organic-inorganic fertilizer
王宇欣, 高清虹, 樊婕, 孙耿, 尹力初, 聂三安. 有机-无机肥变更对水稻土微生物群落结构的影响. 微生物学报, 2025 , 65 (10) : 4684 -4699 . DOI: 10.13343/j.cnki.wsxb.20250250
Yuxin WANG, Qinghong GAO, Jie FAN, Geng SUN, Lichu YIN, San’an NIE. Effects of organic-inorganic fertilization regime alterations on microbial community structures in paddy soils[J]. Acta Microbiologica Sinica, 2025 , 65 (10) : 4684 -4699 . DOI: 10.13343/j.cnki.wsxb.20250250
水稻土作为重要的农业土壤资源直接关系到水稻的产量和品质,是支撑全球粮食安全的核心土壤类型[1]。水稻土受人为活动强烈影响,周期性淹水和落干使其具有独特的氧化还原交替特性[2],这一特性深刻影响着微生物驱动的生物化学过程[3]。施肥是提高水稻产量的重要农业措施[4],深入探究水稻土对不同施肥模式的响应机制,尤其是微生物群落的响应,对于维持稻田生态系统生产力和土壤健康具有重要意义[5]
土壤微生物是驱动稻田生态系统功能的核心生物群体[6],其组成、多样性及互作网络直接反映土壤健康状况[7-8]。细菌、真菌和古菌作为水稻土中的核心功能微生物类群,在养分循环、有机物分解及土壤结构改良等方面发挥着关键作用[9]。例如,部分细菌类群,如假单胞菌门、硝化螺菌门和酸杆菌门,通过参与土壤中碳、氮等元素的循环维持土壤生态系统的平衡和功能稳定性;在真菌方面,子囊菌门和担子菌门能够有效分解复杂有机质,促进土壤中营养元素的循环和转化[10];古菌中的广古菌门和奇古菌门通过参与甲烷循环、氮循环等多种生态过程共同驱动元素循环和能量流动[11]。研究表明施肥能显著改变水稻土微生物的群落结构,长期单施化肥会破坏水稻土微团聚结构,降低土壤微生物活性[3]。施用有机肥能保持土壤微生物活性,且提高土壤微生物多样性[12]。有机无机肥配合施用能优化红壤性水稻土微生物群落结构,显著提高土壤微生物活性[13-14]。此外,微生物生态网络可以提供土壤生物之间潜在关联的关键信息[15],土壤微生物群落的稳定性与生态网络复杂度密切相关[16]。有研究指出,土壤有机质等环境因子是影响土壤微生物丰度变化的重要因素,施肥模式通过改变环境因子间接调控微生物的生态功能[17]。因此,研究不同施肥模式下微生物群落在水稻土中的响应机制有助于进一步认识土壤生态系统的健康状况。
化肥和有机肥是水稻土最常用的施肥方式。施用化肥虽能在短期内提高作物产量,但可能导致土壤酸化、养分失衡以及微生物多样性下降;有机肥通过增加土壤有机碳和速效养分改善土壤理化性质,促进有益微生物的增殖,从而增强土壤生态系统的稳定性[18-19]。当前研究土壤微生物对不同施肥的响应主要聚焦于长期不同施肥模式下微生物的响应与机理探索。然而,在实际生产中通常需要结合2种肥料的优点,采用优化配比或轮替使用的“变更施肥”方式[20-22],如化学肥料与有机肥料的配比与变更、有机肥施用量的变更。对于有机-无机2种施肥模式之间相互变更所导致的土壤关键养分的变化、微生物群落的适应性调整及二者之间的关系,以及土壤微生物对有机肥与化肥、有机肥用量等施肥模式变更的响应有待深入研究。
本研究以湖南农业大学长期定位试验水稻田为研究对象,采用宏基因组测序技术结合生物信息学分析探究施肥模式变更对土壤理化性质的影响,关注核心微生物群落的响应,进一步明确微生物群落变化与土壤理化因子的关联性,以期为优化施肥策略和水稻土可持续管理提供理论依据。
试验在湖南农业大学(28°10′58″N,113°4′37″E)校园内的稻田肥力长期定位试验点开展。试验点水稻田采用小区设计,以随机区组排列,各小区供试面积为1.44 m2,池深1.5 m,底层铺设15 cm厚的卵石与粗砂。每组小区中间设有水位控制槽,各小区之间互不渗漏,可独立灌溉。1982年试验启动时,设置了化肥(H)、常量有机肥(C)、高量有机肥(G) 3个处理,每个处理设6个重复。稻作制度为稻-稻-冬闲,土壤类型为第四纪红色黏土发育的水稻土。自2012年起,在保留原有试验处理不变的前提下,从“化肥处理”中随机选取3个小区变更为“常量有机肥处理”,得到化肥改常量有机肥处理(HC);从“常量有机肥处理”和“高量有机肥处理”中各随机选取3个小区变更为“化肥处理”,得到常量有机肥改化肥处理(CH)和高量有机肥改化肥处理(GH)。
试验过程中无机氮、磷、钾肥分别以尿素、过磷酸钙、氯化钾的形态施入,有机肥源为粉碎后的玉米秸秆。各处理采用等氮施肥量,每季水稻的施氮量为150 kg/ha,N:P2O5:K2O施用比例为1:0.5:1。各处理具体施肥情况见表1。其中,常量有机肥处理中施入的有机氮为总氮量的1/3,高量有机肥处理中的有机氮为总氮量的2/3。为保持各处理间施肥水平一致,有机肥处理小区氮、磷、钾含量不足部分用化肥补足。肥料均在水稻移栽前一次性施入土壤。
本研究共设置6个处理,分别为化肥(H)、化肥改常量有机肥(HC)、常量有机肥(C)、常量有机肥改化肥(CH)、高量有机肥(G)和高量有机肥改化肥(GH),每个处理设3个重复。在水稻成熟期(2024年7月),采用五点取样法在小区内采集耕层(0-20 cm)土壤,土壤样品用无菌自封袋密封保存,一部分储存于干冰中,用于宏基因组测序分析;另一部分运回实验室自然风干后,分别过60目和100目尼龙筛,用于理化性质指标的测定。
土壤理化指标分析参照《土壤农业化学分析方法》[23]。土壤pH采用电位法测定,水土比为2.5:1;土壤有机碳(soil organic carbon, SOC)采用重铬酸钾氧化-外加热法测定;土壤溶解性有机碳(dissolved organic carbon, DOC)用去离子水浸提,过滤后用总有机碳分析仪测定;土壤全氮(soil total nitrogen, TN)采用凯氏定氮消煮法测定;土壤碱解氮(soil alkaline hydrolysis nitrogen, AN)采用碱解扩散法测定;土壤铵态氮(soil ammonium nitrogen, NH4+-N)用氯化钾浸提后,用连续流动分析仪测定;土壤有效磷(available phosphorus, AΡ)采用钼锑抗比色法测定;土壤速效钾(available potassium, AK)用乙酸铵浸提,用火焰光度计测定[23]
土壤样本总DNA提取严格参照E.Z.N.A.® Soil DNA Kit (Omega Bio-Tek公司)说明书进行。采用1%琼脂糖凝胶电泳分析DNA的纯度和完整性,经Qubit荧光定量系统测定浓度后,于-20 ℃低温保存待用。检测合格的DNA样品送往北京奥维森基因科技有限公司,经Covaris超声波破碎仪打断处理,获得长度约300 bp的片段。通过末端修复、加A尾、加测序接头、纯化、PCR扩增等步骤完成整个文库构建。构建完成后,初步定量使用Qubit 2.0将文库稀释至2 ng/μL,随后使用Agilent 2100检测文库的插入片段,最后使用qPCR技术对文库的有效浓度进行准确定量,以保证文库质量。质检合格后,根据不同文库的有效浓度及目标下机数据量的需求进行混合,基于Illumina NovaSeq进行双末端PE150测序[24]。本研究的原始测序数据已提交至NCBI数据库(https://www.ncbi.nlm.nih.gov/),暂存编号为SUB15201378,包含18个样本的元数据(BioSample)及原始测序文件(sequence read archive, SRA)。数据将在论文正式发表后公开,公开后可通过生物项目编号PRJNA1242716访问完整数据集。
测序数据经双末端序列质控处理,获取高质量读段。随后应用MEGAHIT组装平台,基于succinct de Bruijn graphs算法原理对优化序列进行拼接组装。在拼接结果中筛选≥800 bp的高置信度连续序列作为最终的组装结果。构建非冗余基因集后,采用Bowtie 2软件严格比对每个样品,统计基因在对应样品中的丰度信息[25]。从比对上的reads数目及基因长度出发,计算得到各基因在各样品中的丰度信息,如公式(1)所示。
TPMi=(Ri/Li)×1061n(Rj/Lj)
式中:TPM为每百万转录本中的转录本数;RiLi 分别为目标基因i的比对reads数目与基因长度;求和项中的RjLj 代表所有基因j (j=1, 2, ...... , n; n为基因总数)的相应值。
物种注释使用Diamond软件将非冗余基因集与NCBI-NR数据库进行比对(BLASTP,E-value≤1.0×10-5),并通过最低共同祖先算法(lowest common ancestor, LCA)进行物种分类注释,QIIME 2用于后续多样性分析。
使用Microsoft Excel 2019软件对数据进行统计分析;采用R (v4.4.1)进行数据分析和可视化,绘制微生物多样性箱线图及散点图;使用SPSS 26.0软件进行显著性分析(Duncan或t-test,P<0.05);使用Origin 2021绘制微生物群落物种丰度柱状图;使用Gephi (v0.9.2)进行微生物共现网络分析;使用Canoco 5.0进行土壤微生物群落变化与土壤理化性状的冗余分析。
由于施肥模式变更,土壤理化性质发生了明显变化(表2)。施肥模式变更前后对比,化肥改常量有机肥处理显著提高了水稻土有机碳、溶解性有机碳、全氮、碱解氮和速效钾含量(P<0.05);常量有机肥改化肥处理显著降低了水稻土溶解性有机碳和速效钾含量,显著提高了有效磷含量;高量有机肥改化肥处理下,水稻土有机碳、溶解性有机碳、全氮、碱解氮和速效钾含量显著低于高量有机肥处理,有效磷含量显著提高。整体上,化肥处理(H、CH和GH)的有机碳、溶解性有机碳、全氮、碱解氮、铵态氮和速效钾含量低于有机肥处理(HC、C和G),有效磷含量高于有机肥处理。各处理间土壤pH无显著差异(P>0.05)。
对土壤微生物进行物种注释,分别对细菌、真菌和古菌进行群落组成分析,发现微生物对施肥模式变更产生了响应。整体上,各处理微生物以细菌为主,其相对丰度超过94.00%,真菌约占0.01%-0.02%,古菌占2.31%-5.10% (图1A)。施肥模式变更前后对比,化肥改常量有机肥和高量有机肥改化肥处理使细菌和真菌相对丰度提高,古菌相对丰度降低;常量有机肥改化肥处理降低了细菌和真菌相对丰度,提高了古菌相对丰度。
选择相对丰度大于1.00%的微生物在门水平进行分析。各处理细菌群落(图1B)优势物种为假单胞菌门(Pseudomonadota,48.88%-51.32%)、绿屈挠菌门(Chloroflexota,8.31%-14.68%)、酸杆菌门(Acidobacteriota,12.17%-15.07%)、放线菌门(Actinomycetota,4.08%-5.98%)、硝化螺菌门(Nitrospirota,2.60%-3.88%)和出芽单胞菌门(Gemmatimonadota,2.61%-4.19%)等。整体上,化肥处理的绿屈挠菌、硝化螺菌相对丰度高于有机肥处理,有机肥处理的放线菌相对丰度高于化肥处理(P>0.05)。变更施肥模式前后对比,化肥改常量有机肥处理提高了酸杆菌、放线菌、Candidatus Rokubacteria和出芽单胞菌的相对丰度,降低了变形菌、绿屈挠菌和硝化螺菌的相对丰度,其中酸杆菌、Candidatus Rokubacteria和硝化螺菌具有显著性差异(P<0.05);而常量有机肥改化肥处理提高了绿屈挠菌和硝化螺菌的相对丰度,降低了变形菌、酸杆菌、放线菌和出芽单胞菌的相对丰度(P>0.05);高量有机肥改化肥处理提高了绿屈挠菌、酸杆菌、硝化螺菌和出芽单胞菌的相对丰度,降低了变形菌和放线菌的相对丰度,其中硝化螺菌发生了显著性变化(P<0.05)。
各处理真菌群落(图1C)优势物种为子囊菌门(Ascomycota,54.74%-68.44%)、担子菌门(Basidiomycota,15.14%-20.94%)、壶菌门(Chytridiomycota,3.69%-9.36%)、毛霉菌门(Mucoromycota,3.42%-16.14%)和捕虫菌门(Zoopagomycota,0.57%-1.55%)等。与化肥处理相比,化肥改常量有机肥处理提高了群落中毛霉菌和捕虫菌的相对丰度,降低了子囊菌、担子菌和壶菌相对丰度,其中毛霉菌的变化具有显著性(P<0.05);常量有机肥改化肥处理与常量有机肥处理相比,壶菌和毛霉菌的相对丰度提高,子囊菌、担子菌和捕虫菌相对丰度降低;高量有机肥改化肥处理中,子囊菌和毛霉菌相对丰度提高,担子菌、壶菌和捕虫菌相对丰度低于化肥处理(P>0.05)。
各处理土壤古菌群落组成如图1D所示,优势菌为广古菌门(Euryarchaeota,65.49%-92.69%)、奇古菌门(Thaumarchaeota,2.14%-6.41%)、Candidatus Bathyarchaeota(1.72%-22.93%)和Candidatus Thermoplasmatota(0.90%-3.62%)等。变更施肥模式前后对比,化肥改常量有机肥处理较化肥处理显著提高了群落中奇古菌丰度;常量有机肥改化肥处理中古菌相对丰度无显著变化;高量有机肥改化肥处理中广古菌相对丰度显著低于高量有机肥处理,Candidatus Thermoplasmatota相对丰度显著高于高量有机肥处理(P<0.05)。
通过Shannon、Simpson和Richness指数反映土壤微生物群落结构的α多样性(图2)[25]。整体上,有机-无机肥变更影响了微生物群落的α多样性,但未达到显著水平(P>0.05)。其中,常量有机肥处理(HC、C)下的微生物群落多样性和丰富度均低于化肥处理(H、CH);高量有机肥处理(G)下的微生物群落多样性高于化肥处理(GH),但丰富度低于高量有机肥改化肥处理(GH)。对比施肥模式变更前后,化肥改常量有机肥处理降低了微生物群落结构的α多样性;常量有机肥改化肥处理增加了水稻土微生物的α多样性;高量有机肥改化肥处理降低了多样性指数,增加了丰富度指数。
通过计算Bray-Curtis距离进行ANOSIM相似性分析并绘制PCoA主坐标分析图,分析处理间微生物β多样性指数以反映处理间微生物群落结构差异。如图3所示,细菌和古菌的轴1和轴2累计贡献量之和均大于70.00%,真菌累计贡献量之和为30.23%。相似性分析结果表明,细菌(R=0.312,P=0.001)、真菌(R=0.192,P=0.032)和古菌(R=0.381,P=0.003)组间差异达到显著性水平,各处理之间组间差异大于组内差异(R>0)。
通过不同处理土壤微生物共现网络分析水稻土中细菌、真菌和古菌的稳定性与复杂性。如图4所示,每个点代表网络中的一个节点,点的大小代表节点的丰富度;边的颜色表示节点之间的影响类型,红色表示正向影响,绿色表示负向影响。整体来看,细菌是主要的微生物类型,在所有处理组中占主导地位,在每个网络中占比均超过80%;真菌数量相对较少,但不同处理之间存在一定差异;古菌的数量也较为稳定,占比11%-13%。正向影响和负向影响的比例在不同处理组中有较明显差异,尤其是常量有机肥改化肥组的正向比例明显高于其他组。对比施肥模式变更前后,与化肥处理相比,化肥改常量有机肥处理表现出较高的节点数、边数、平均度、模块化以及平均聚类系数;常量有机肥改化肥处理中,边数和平均度高于常量有机肥处理,模块化程度低于常量有机肥处理;高量有机肥改化肥处理与高量有机肥处理相比,节点数、边数、平均度、模块化以及平均聚类系数均有所降低。综上所述,化肥改常量有机肥处理提高了微生物群落结构的稳定性、连通性和复杂性;常量有机肥处理改化肥处理降低了微生物群落抗干扰能力;高量有机肥改化肥处理使得土壤微生物群落的整体连通性下降,互作关系变得更加松散。有机肥处理(HC、C和G)较化肥处理(H、CH和GH)微生物网络结构更具稳定性,且群落之间的相互作用增强。
选择变更施肥后相对丰度发生显著变化的细菌、真菌和古菌群落,采用冗余分析(redundancy analysis, RDA)研究其与土壤理化性质的关系(图5)。轴1和轴2分别解释微生物群落结构变异的17.63%和10.24%。溶解性有机碳、土壤pH、全氮、铵态氮、速效钾和有效磷是影响土壤微生物群落结构的主要因素,分别解释微生物结构变异的22.1%、16.8%、15.6%、14.6%、11.8%和10.6%。酸杆菌和广古菌与pH、溶解性有机碳、速效钾、全氮呈正相关,与铵态氮和有效磷呈负相关;Candidatus Rokubacteria与pH和溶解性有机碳呈正相关,与全氮、铵态氮和有效磷呈负相关;硝化螺菌、毛霉菌和Candidatus Thermoplasmatota与有效磷和铵态氮呈正相关,与pH、溶解性有机碳、速效钾、全氮呈负相关;奇古菌与pH和溶解性有机碳呈正相关,与速效钾、全氮、铵态氮和有效磷呈负相关。
施肥模式变更影响了水稻土中微生物群落的组成(图1)。本研究结果显示,细菌是土壤微生物群落的主要组成部分(>94.00%),真菌相对丰度偏低(0.01%-0.02%),这可能与水稻土独特的生态环境和微生物互作特征密切相关。本研究采样时期为水稻成熟期,土壤中的真菌比例偏低,且多数真菌对缺氧环境高度敏感,水稻土长期处于淹水少氧状态,抑制了真菌的生长,同时促进了厌氧微生物(如某些细菌和古菌)的繁殖[26-27];细菌在富营养环境(如高氮)中能快速占据优势,并通过代谢产物抑制真菌生长,例如假单胞菌门与真菌呈负相关,其丰度升高可能压缩真菌生态位[28]。此外,宏基因组测序对不同微生物类群的DNA提取效率存在差异,真菌细胞壁结构复杂,尤其是一些厚壁真菌(如子囊菌门和担子菌门),其DNA提取效率通常低于细菌和古菌[29]
本研究中不同施肥模式下的水稻土假单胞菌门相对丰度最高(48.88%-51.32%),表明其在红壤性水稻土中分布广泛[30]。变更施肥措施后其丰度均有所降低(P>0.05,图1B),可能是因为假单胞菌门包含大量与氮素转化相关的功能性微生物(如硝化细菌和反硝化细菌)[31],当施肥方式改变,土壤中氮素形态发生变化,并对功能菌的活性产生负面影响[32]。无机肥改为常量有机肥处理后显著提高了酸杆菌门和Candidatus Rokubacteria的相对丰度(P<0.05),可能原因是这2种微生物对碳源具有高度敏感性[33-34],有机肥更符合酸杆菌门和Candidatus Rokubacteria的生理代谢需求。酸杆菌门作为典型的寡营养型细菌,对施肥方式的变化,尤其是土壤中可利用营养物质的变化较为敏感,能有效利用土壤中的有机物质[35];同时,酸杆菌是参与有机物和腐殖质分解的重要种群,能够促进土壤中木质素与纤维素的分解,增强土壤生态功能,其丰度的增殖也反映土壤有机碳的有效供应[36]Candidatus Rokubacteria依赖其他微生物或外源碳生存,并参与复杂的有机质分解。本研究中当玉米秸秆作为有机肥源施入土壤后分解缓慢,不仅能够为酸杆菌门提供长期稳定的碳源,同时为Candidatus Rokubacteria提供更适宜的生态位,使Candidatus Rokubacteria在分解有机质和参与土壤养分循环过程中表现出更强的竞争力,进而提高其相对丰度。冗余分析结果表明,酸杆菌和Candidatus Rokubacteria丰度均与溶解性有机碳含量呈正相关(图5),且变更施肥模式前后溶解性有机碳浓度发生了显著变化(表2),进一步证明了该结论。化肥改常量有机肥处理显著降低了硝化螺菌门的相对丰度,高量有机肥改化肥处理显著提高了硝化螺菌门的相对丰度(P<0.05,图1B),可能与氮素供应水平有关。硝化螺菌参与土壤中亚硝酸盐氧化为硝酸盐的过程[37],能够有效利用无机氮源,对无机肥更为敏感。本研究中化肥(尿素)施入土壤,水解释放铵态氮并被氧化为亚硝酸盐,为硝化螺菌提供底物[38],促进其增殖,因此在短时间内化肥能够快速提供氮素营养,有利于作物生长。有机肥处理(HC、G)中高碳氮比有机肥源施入土壤,缓释氮源并提供有机碳,微生物优先利用土壤中的有效氮导致短期内有效氮浓度下降,硝化螺菌因底物不足生长受到抑制而丰度降低[39]。冗余分析显示,硝化螺菌门丰度与铵态氮及有效磷含量正相关,与溶解性有机碳负相关(图5)。变更施肥模式后水稻土细菌群落组成发生显著变化,这与底物,尤其是碳、氮、磷的供应水平密切相关。
变更施肥模式后真菌群落组成变化不明显,但毛霉菌门相对丰度显著增加(P<0.05,图1C),可能是由于毛霉菌通常具有较强的环境适应能力,能够在土壤条件发生变化时迅速占据新的生态位[40]。另一方面,毛霉菌可与植物共生,变更施肥措施后水稻与土壤微生物互作关系可能发生调整,毛霉菌门可通过与水稻的共生关系增强其竞争力,从而提高其相对丰度[33]。本研究表明,化肥改施常量有机肥后奇古菌门丰度显著提高(P<0.05),可能与底物供应水平有关。某些奇古菌通过将氨氧化为亚硝酸盐获取能量,对低浓度NH4⁺环境具有高亲和力[41-42],本研究中的有机肥源(玉米秸秆)碳氮比较高,土壤中游离NH4⁺浓度降低,有利于这些奇古菌在水稻土中的生长。此外,奇古菌参与3-羟基丙酸/4-羟基丁酸循环固定CO[43],因而有机碳输入增加的土壤可能更适合奇古菌这类慢生长型微生物,使其在竞争中占据优势[44]。冗余分析结果也表明奇古菌与溶解性有机碳呈正相关(图5)。高量有机肥改化肥显著降低广古菌门相对丰度(P<0.05),可能与广古菌的生理特性有关。高量有机肥改施化肥后土壤有机质降低,化肥释放的无机氮经氨氧化形成的硝酸盐可能作为电子受体促进反硝化作用,加速有机质矿化,减少产甲烷底物的积累,导致某些广古菌如产甲烷古菌丰度下降[45-46]。在水稻土中,真菌和古菌的群落组成主要受其生理特点的影响。
施肥模式变更对土壤微生物α多样性有一定影响但不显著(图2)。本研究表明,化肥改常量有机肥降低了微生物群落结构多样性和物种丰富度;常量有机肥改化肥处理增加了微生物α多样性指数;高量有机肥改化肥处理中群落多样性指数降低,但物种丰富度提高,这种变化反映了不同施肥模式之间的动态平衡。施肥模式的变更可能打破了原有群落的稳态,引发适应性的多样性波动[47]。例如,化肥改常量有机肥处理虽然提高了某些有益菌群的丰度,但也可能导致竞争性排斥,由于功能冗余减少和优势菌群扩张使得群落整体多样性和物种丰富度降低[47];而常量有机肥改化肥处理缓解了有机肥单一条件下某些微生物的竞争压力,或激活了部分寡营养菌群,增加了生态位分化[48-49],从而提升了群落多样性,但长期来看,这种变化可能伴随功能冗余的降低[50],进而影响土壤生态系统的稳定性;高量有机肥改化肥使得土壤中的养分来源从复杂的有机物转变为单一的矿质养分,施肥模式的改变增加了土壤中微生物物种数,但由于减少了微生物可利用的碳源种类和复杂性,许多依赖分解复杂有机物生存的微生物可能因缺乏适宜的碳源而减少[51]。β多样性分析进一步揭示了不同施肥处理间土壤微生物群落的差异(图3)。无论是细菌、真菌还是古菌,各处理组间的群落结构差异均大于组内差异,且具有统计学意义(P<0.05)。施肥模式的变更对微生物群落结构产生了深刻影响,并可能导致生态系统功能的改变[52]。有机-无机变更施肥对淹水水稻土处理内微生物物种多样性无显著性改变,但可能对处理间微生物群落结构及功能产生重要影响。
微生物共现网络分析表明,施肥模式的变更影响了水稻土中微生物群落的互作模式(图4)。本研究中化肥改常量有机肥处理各项网络复杂性指标(节点数、边数、平均度、模块化和平均聚类系数)均有提高,可能原因是有机肥的施入提供了丰富的有机质,为土壤微生物提供充足的底物,促进了微生物的生长繁殖和新的合作关系[53],提高了微生物网络结构的稳定性和复杂性[54]。常量有机肥改化肥处理中边数及平均度高于常量有机肥处理,模块化低于常量有机肥处理(图4),可能是因为微生物群落在重组过程中存在功能整合风险[55-56]。一方面,化肥提供的无机养分促进了一些快速生长型微生物的增殖,这些微生物具有较高的代谢活性,能迅速利用可溶性养分,并可能在短期内形成高度互联的小团体,从而增加了微生物之间的互作关系和平均相互作用强度[57];另一方面,化肥提供的简单无机养分也可能促使微生物依赖相对单一的代谢途径,从而减少了不同功能类群之间的分化,限制微生物的生存空间和多样性,导致微生物群落的功能分区减少,生态位压缩,模块化程度降低[58]。本研究中常量有机肥改化肥处理中正向互作比例较其他处理明显提高(图4),这可能与化肥施入后诱导的竞争压力有关,部分微生物通过互利共生增强资源利用效率[59]。高量有机肥改施化肥后网络参数的全面降低,说明从高量有机肥转为化肥对微生物互作的负面影响较大,可能原因是原有机肥处理土壤有机质水平较高,改为化肥模式后导致功能微生物关键生态功能(如碳、氮循环)的衰退[60]。此外,各施肥处理中有机肥处理均体现出较高的网络模块化程度和平均聚类系数,表明其群落内部分工明确、互作紧密,生态系统稳定性更强;与之相比,化肥处理的节点数、平均度和模块数较低,反映其微生物互作简单化,可能对环境扰动更为敏感[33,61]。本研究结果表明,有机肥的施用有助于构建复杂且稳定的微生物互作网络,提高微生物群落的适应性调节能力,对外部干扰更具抵抗力或弹性,而化肥的施用可能削弱微生物群落的恢复能力[62]。水稻土变更施肥模式后肥料选择及施肥水平很大程度上决定了微生物互作网络的复杂性和稳定性。
本研究通过宏基因组测序和生物信息学分析揭示了有机-无机肥变更施肥对红壤性水稻土基本理化性质的影响及微生物群落的响应特征。有机-无机肥变更显著影响了水稻土中碳、氮、磷和钾相关理化因子的变化,其中溶解性有机碳、土壤pH、全氮、铵态氮、速效钾和有效磷是驱动微生物群落变化的主要因素。施肥措施的变更显著影响了细菌酸杆菌、硝化螺菌和Candidatus Rokubacteria;真菌毛霉菌;古菌奇古菌、广古菌和Candidatus Thermoplasmatota的相对丰度。有机-无机肥变更后微生物群落α多样性指数未发生显著变化,不同施肥处理微生物β多样性有显著差异。有机-无机肥变更施肥影响了水稻土中微生物群落的互作模式,变更施肥前后,有机肥较化肥均体现出较高的适应性调节能力和对外部干扰的抵抗力。肥料选择及施肥水平很大程度上决定了微生物互作网络的复杂性和稳定性。
  • 湖南省教育厅重点项目(23A0185)
  • 湖南省自然科学基金(2023JJ30307)
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2025年第65卷第10期
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doi: 10.13343/j.cnki.wsxb.20250250
  • 接收时间:2025-03-28
  • 首发时间:2025-11-03
  • 出版时间:2025-09-04
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  • 收稿日期:2025-03-28
  • 录用日期:2025-06-20
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the Scientific Research Fund of Hunan Provincial Education Department(23A0185)
湖南省教育厅重点项目(23A0185)
the Natural Science Foundation of Hunan Province(2023JJ30307)
湖南省自然科学基金(2023JJ30307)
作者信息
    1湖南农业大学 资源学院,湖南 长沙
    2湖南省耕地与农业环境生态研究所,湖南 长沙
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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