Microbial Ecology

, Volume 61, Issue 4, pp 917–931 | Cite as

Diversity and Biogeography of Rhizobia Isolated from Root Nodules of Glycine max Grown in Hebei Province, China

  • Qin Qin Li
  • En Tao Wang
  • Yun Zeng Zhang
  • Yan Ming Zhang
  • Chang Fu Tian
  • Xin Hua Sui
  • Wen Feng Chen
  • Wen Xin Chen
Soil Microbiology

Abstract

A total of 215 rhizobial strains were isolated and analyzed with 16S rRNA gene, 16S–23S intergenic spacer, housekeeping genes atpD, recA, and glnII, and symbiotic genes nifH and nodC to understand the genetic diversity of soybean rhizobia in Hebei province, China. All the strains except one were symbiotic bacteria classified into nine genospecies in the genera of Bradyrhizobium and Sinorhizobium. Surveys on the distribution of these rhizobia in different regions showed that Bradyrhizobium japonicum and Bradyrhizobium elkanii strains were found only in neutral to slightly alkaline soils whereas Bradyrhizobium yuanmingense, Bradyrhizobium liaoningense-related strains and strains of five Sinorhizobium genospecies were found in alkaline–saline soils. Correspondence and canonical correspondence analyses on the relationship of rhizobial distribution and their soil characteristics reveal that high soil pH, electrical conductivity, and potassium content favor distribution of the B. yuanmingense and the five Sinorhizobium species but inhibit B. japonicum and B. elkanii. High contents of available phosphorus and organic matters benefit Sinorhizobium fredii and B. liaoningense-related strains and inhibit the others groups mentioned above. The symbiotic gene (nifH and nodC) lineages among B. elkanii, B. japonicum, B. yuanmingense, and Sinorhizobium spp. were observed in the strains, signifying that vertical gene transfer was the main mechanism to maintain these genes in the soybean rhizobia. However, lateral transfer of symbiotic genes commonly in Sinorhizobium spp. and rarely in Bradyrhizobium spp. was also detected. These results showed the genetic diversity, the biogeography, and the soil determinant factors of soybean rhizobia in Hebei province of China.

Supplementary material

248_2011_9820_MOESM1_ESM.doc (48 kb)
Table ASequence similarities for 16S rRNA, atpD, recA, glnII genes, and DNA–DNA relatedness (%) among strains of the ungrouped species and related Sinorhizobium (Ensifer) species. (DOC 48 kb)
248_2011_9820_MOESM2_ESM.doc (108 kb)
Table BAccession number of housekeeping genes deposited in GenBank. (DOC 107 kb)
248_2011_9820_MOESM3_ESM.ppt (638 kb)
FigureA Dendrogram based on the cluster analysis of 16S rDNA-RFLP. The correlation coefficient was calculated and the UPGMA dendrogram was constructed by the unweighted average pair grouping method (UPGMA). Vertical dashed line indicates the level of similarity at which groups were delineated. B Phylogenetic relationships of 16S rDNA sequences inferred using the neighbor-joining method. The evolutionary distances were computed using the Kimura’s two-parameter method. The scale bar presents 1% of nucleotide substitution. Only bootstrap values above 50 are shown. C Phylogenies of housekeeping genes atpD (a), recA (b), and glnII (c), showing the relationships among isolates and reference strains. Trees were constructed by using the neighbor-joining method with a Kimura’s two-parameter distance matrix. Bootstrap probability values ≥50% are indicated at branch points. Bars, 2% nucleotide substitutions. D Phylogenetic relationships of nodC (a) and nifH (b) sequences inferred using the neighbor-joining method. The scale bar presents 2% of nucleotide substitution. Bootstrap values greater than 50% were indicated. The evolutionary distances were computed using the Kimura’s two-parameter method. E Correlation analysis between sample sites and CACAI groups of soybean rhizobia in Hebei province was instructed with the Correspondence 1.0 program in SPSS 17.0 package. The dimensions 1 and 2 were the linear combination of the two variables and may have no real meaning. Inertia value was 0.983 and 0.841, respectively, for dimensions 1 and 2, indicating that both the dimensions were closely related to the two variables. Pearson’s coefficient was 0.686 (p = 0.01), indicating that the sample sites (1, Changli; 2, Cangxian; 3, Huanghua; 4, Hejian; 5, Luanxian; 6, Baoding; 7, Tianjin) and CACAI groups of soybean were significantly correlated. (PPT 638 kb)

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Qin Qin Li
    • 1
  • En Tao Wang
    • 1
    • 2
  • Yun Zeng Zhang
    • 1
  • Yan Ming Zhang
    • 1
  • Chang Fu Tian
    • 1
  • Xin Hua Sui
    • 1
  • Wen Feng Chen
    • 1
  • Wen Xin Chen
    • 1
  1. 1.State Key Laboratory of Agrobiotechnology/College of Biological SciencesChina Agricultural UniversityBeijingChina
  2. 2.Departamento de Microbiología, Escuela Nacional de Ciencias BiológicasInstituto Politécnico NacionalMéxico D.F.Mexico

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