不同类型水稻土微生物群落结构特征及其影响因素

选取基于我国土壤地理发生分类的不同类型土壤发育的四种水稻土，利用¹⁵N₂气体示踪法测定生物固氮速率，采用实时荧光定量PCR（Real-time PCR）技术测定细菌丰度，通过16S rRNA基因高通量测序分析微生物群落组成和多样性。结果表明：变形菌门（Proteobacteria）、酸杆菌门（Acidobacteria）、绿弯菌门（Chloroflexi）和蓝藻门（Cyanobacteria）是水稻土中优势微生物类群。四种类型土壤发育的水稻土细菌群落结构差异显著（Stress<0.001），群落结构分异（NMDS1）与土壤pH存在极显著正相关关系（P<0.01）。土壤有机碳和碱解氮含量显著影响水稻土中细菌丰度和群落多样性（P<0.01）。红壤发育的水稻土细菌16S rRNA基因拷贝数显著高于其他三种类型水稻土，但OTU数量、Chao1指数和PD指数均低于其他三种类型水稻土。土壤pH对水稻土生物固氮速率有显著影响（P<0.01），紫色土发育的水稻土具有最高的生物固氮速率（3.2±0.7 mg×kg^-1×d^-1），其中优势类群细鞘丝藻属（Leptolyngbya）可能是生物固氮的主要贡献者。研究结果丰富了对水稻土微生物多样性的认识，为通过调控土壤pH和微生物群落组成来提高稻田生物固氮潜力提供了理论依据。

Microbial Abundance and Community Composition in Different Types of Paddy Soils in China and Their Affecting Factors

Objective] Rice paddy soil has long been an important soil resource for farming and developed into various types under the impact of long-term anthropogenic actions. Yet, little is known about microbes in the paddy soils. To determine factors affecting soil microbial communities in the paddy soils, soil samples of four types of paddy soils (Sublayer Shajiang soil, Red soil, Black soil and Purple soil) were collected from major rice-production regions (Jiangdu of Jiangsu, Yingtan of Jiangxi, Changchun of Jilin, and Yanting of Sichun, respectively).Method] To explore abundance of the soil microbial community in the soil samples, the real-time quantitative PCR was used, and to characterize diversity and composition of the soil microbial community, the 16S rRNA genes high-throughput sequencing was performed. With the aid of the field-based ¹⁵N₂-labeling technique, biological nitrogen fixation (BNF) rates in the four types of paddy soils were assessed.Result] The number of 16S rRNA gene copies in paddy soils ranged from 1.8×10⁷ to 6.7×10⁹ copies·g^-1 dry soil. Statistical analysis shows that the number of 16S rRNA gene copies in Red soil was significantly higher than those in the other soils (P<0.05). A total of 666 738 raw sequences were obtained from 12 samples with the technique of 16S rRNA genes sequencing and were normalized to 38 715 per sample for the downstream analysis. These sequences were clustered into 13 097 OTUs. Taxonomic analysis shows that the bacterial communities in the four types of paddy soils were dominantly Proteobacteria, Actinobacteria, Chloroflexi and Cyanobacteria. Results show that observed OTU number and Chao 1 and PD indices of the soil bacteria were much lower in Red soil than in the other soils. Correlation analysis of abundance and diversity of soil bacterial communities and soil properties shows that 16S rRNA genes copies, observed OTU number, Chao 1 and PD indices of soil bacteria were significantly related to soil organic carbon and alkaline nitrogen content (P<0.01). Non-metric multidimensional scaling (NMDS) ordination shows that the bacterial community structures in the four types of paddy soils varied significantly (Stress<0.001). Among the soil properties analyzed, soil pH might play a key role in determining soil bacterial community structure (P<0.01). Biological N₂ fixation rate was significantly and positively related to soil pH (P<0.01). The highest biological N₂ fixation rate was found in Purple soil (3.2±0.7 mg·kg^-1·d^-1), and Leptolyngbya might be a major contributor to the BNF in Purple soil.Conclusion] All the finding in this study highlight the influence of soil properties on soil microbial communities in paddy soils and suggest that regulation of soil pH and microbes might be a strategy to increase the BNF in paddy soils.