Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Robust Markers Reflecting Phylogeny and Taxonomy of Rhizobia

  • Yan Ming Zhang,

    Affiliations State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China, Key Laboratory of Soil Microbiology, Ministry of Agriculture, China Agricultural University, Beijing, China, Rhizobium Research Center, China Agricultural University, Beijing, China

  • Chang Fu Tian ,

    Affiliations State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China, Key Laboratory of Soil Microbiology, Ministry of Agriculture, China Agricultural University, Beijing, China, Rhizobium Research Center, China Agricultural University, Beijing, China

  • Xin Hua Sui,

    Affiliations State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China, Key Laboratory of Soil Microbiology, Ministry of Agriculture, China Agricultural University, Beijing, China, Rhizobium Research Center, China Agricultural University, Beijing, China

  • Wen Feng Chen,

    Affiliations State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China, Key Laboratory of Soil Microbiology, Ministry of Agriculture, China Agricultural University, Beijing, China, Rhizobium Research Center, China Agricultural University, Beijing, China

  • Wen Xin Chen

    Affiliations State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China, Key Laboratory of Soil Microbiology, Ministry of Agriculture, China Agricultural University, Beijing, China, Rhizobium Research Center, China Agricultural University, Beijing, China

Robust Markers Reflecting Phylogeny and Taxonomy of Rhizobia

  • Yan Ming Zhang, 
  • Chang Fu Tian, 
  • Xin Hua Sui, 
  • Wen Feng Chen, 
  • Wen Xin Chen


Genomic ANI (Average Nucleotide Identity) has been found to be able to replace DNA-DNA hybridization in prokaryote taxonomy. The ANI of each of the core genes that has a phylogeny congruent with the reference species tree of rhizobia was compared to the genomic ANI. This allowed us to identify three housekeeping genes (SMc00019-truA-thrA) whose ANI reflected the intraspecies and interspecies genomic ANI among rhizobial strains, revealing an ANI gap (≥2%) between the inter- and intra-species comparisons. The intraspecies (96%) and interspecies (94%) ANI boundaries calculated from three genes (SMc00019-truA-thrA) provided a criterion for bacterial species definition and confirmed 621/629 of known interspecies relationships within Bradyrhizobium, Mesorhizobium, Sinorhizobium and Rhizobium. Some widely studied strains should be renamed. The SMc00019-truA-thrA ANI also correlates well with the genomic ANI of strains in Agrobacterium, Methylobacterium, Ralstonia, Rhodopseudomonas, Cupriavidus and Burkholderia, suggesting their wide applicability in other bacteria.


Theory-based concepts of prokaryotic species have been debated in the community [1] but, pragmatically, prokaryotic species have been defined by polyphasic approaches including phenotypic and genetic methods. Among these, the 70% DDH (DNA-DNA hybridization) value has been widely used as a gold standard, especially where 16S rRNA gene sequence similarity values are more than 97% [2]. However, DDH has serious limitations: it is time-consuming, ill-suited for rapid identification, and unavailable for non-culturable prokaryotes. Moreover the 70% DDH criterion does not correspond to an ecological/evolutionary theory-based concept of what properties a species should have [3]. The advance of sequencing technology has allowed us to use comparative genomics and multi-locus sequence analysis (MLSA) to provide a closer marriage between the definition and concept of species [3]. Recently, 95–96% ANI (Average Nucleotide Identity) of pairwise genomes has been demonstrated to correlate with the current boundary of the 70% DDH value [4][6]. In a phylogenetic and/or taxonomic survey, however, it is unnecessary to sequence genomes for all the prokaryotes under study and genome assembly may not even be possible, as in metagenomics. Thus, efforts have been made either to reduce the sequencing coverage of genomes or to screen fewer loci while reflecting the average signatures of whole genomes [4], [7]. Up to now, MLSA has been widely used to infer the taxonomy, phylogeny and microevolution of prokaryotes [2], [3], but a universal set of genes for all prokaryotes might be unattainable because those ubiquitous genes conserved enough to be amplified by general primers might not evolve quickly enough to distinguish closely related taxa [3]. Moreover, the species- and subspecies- level analyses dominated the topics of most studies and are increasingly important in microbiome survey [8], [9].

Rhizobia are defined as symbiotic bacteria forming nitrogen-fixing nodules with diverse legumes, and they play an important role in sustainable agriculture. More than 90 species belonging to 13 genera of α- and β- proteobacteria have been described as rhizobia. Due to the limited number of rhizobial genomes in databases, target genes (atpD, dnaK, gap, glnA, glnII, gltA, gyrB, pnp, recA, rpoB and thrC) for MLSA of rhizobia have been selected largely in the belief that they were housekeeping genes [10][12]. No comparisons between the phylogenies of these genes and phylogenies derived from whole genome data were made before using them. Although different subsets of these possible housekeeping genes were carefully chosen for further analyses in each genus, incongruent phylogenetic signals among these loci have been reported [10][12]. Moreover, for these possible housekeeping loci, a universal clear-cut gap between intra- and inter-specific sequences was not found [10][12]. A recent comparative genomic study of 22 rhizobial genomes identified 33 core genes with phylogenies congruent with the reference tree based on 295 core genes [13]. In the present study, we first tested whether the ANI of each of these 33 genes reflected the ANI of the corresponding pair of genomes. The best performing markers were then used to evaluate the current taxonomy of type strains in Bradyrhizobium, Mesorhizobium, Sinorhizobium (later synonym Ensifer; due to more extensive use of Sinorhizobium in the community, Sinorhizobium was used throughout the text), and Rhizobium. The correlation between the ANI of selected markers and the genomic ANI of published genomes in Agrobacterium, Methylobacterium, Ralstonia, Rhodopseudomonas, Cupriavidus and Burkholderia was also studied.

Materials and Methods

Genomes and housekeeping genes

The 85 genomes used in this study are listed in Table S1. Thirty-three core genes with phylogenies congruent with the reference species tree of 22 rhizobial genomes were found earlier [13], but five of these genes are absent in other rhizobial genomes. Therefore, 28 out of 33 genes were analyzed herein (Table 1).

Average nucleotide identity (ANI) analysis

ANI between genomes (ANIm) was calculated by using the NUCmer algorithm [14] integrated in Jspecies [4].The “No. of differences” model integrated in MEGA 5 [15] was used for calculating the pairwise distance between sequences of a single gene, from which ANI values (ANIg) were obtained using Excel. Pearson and Spearman correlation coefficients between ANIg and ANIm values were calculated using SPSS. Curve estimation integrated in SPSS was used to find the curve that gives the best fit to the data of ANIm-ANIg pairs.

Phylogenetic and recombination analysis

All of the 28 test genes passed the Permutation Tail Probability test (PTP) integrated in PAUP* 4.0b10 [16]. Single gene alignments were aligned by using MEGA 5 [15]. Modeltest [17] was used to produce the best nucleotide substitution model for each alignment. Maximum likelihood (ML) trees with 100 bootstrap replicates were constructed by PhyML 3.0 [18], or by PAUP* 4.0b10 [16] with PHYLIP [19] for bootstrapping. The Shimodaira-Hasegawa (SH) test [20] integrated in PAUP* 4.0b10 was performed to test the level of topological congruence between ML trees (P = 0.05). The PHI test [21] was used to detect potential recombination signal in single or concatenated genes.

Primers and PCR conditions

Degenerate primers (Table 2) were designed for the amplification of thrA, SMc00019 and truA in 67 type strains of Bradyrhizobium, Sinorhizobium, Mesorhizobium and Rhizobium (Table S2). Fragment amplifications were carried out by PCR with primer pairs as follows: thrAB-F/R (Bradyrhizobium), thrAMRS-F/R (Mesorhizobium, Rhizobium and Sinorhizobium), SMc00019B-F/R (Bradyrhizobium), SMc00019MRS-F/R (Mesorhizobium, Rhizobium and Sinorhizobium), truAB-F/R (Bradyrhizobium), truAR-F/R (Rhizobium) and truAMS-F/R (Mesorhizobium and Sinorhizobium). Corresponding PCR conditions were listed in Table 2. The resulting 201 sequences were deposited in GenBank under the accession numbers JX064199-JX064265 (SMc00019), JX064271-JX064337 (truA) and JX064343- JX064409 (thrA).

Results and Discussion

Novel phylogenetic and taxonomic markers and re-evaluation of current classification of Rhizobiaceae

Consistent with the genomic ANIm 95%–96% boundary for the species definition of other prokaryotes, it was recently shown that genomic ANIm >95% could be used to identify strains of the same rhizobial species [4], [13]. Among the 295 core genes of rhizobial genomes, single-gene trees (ML) of 33 core genes have been found to have phylogenies congruent with the reference species tree based on concatenation of 295 core genes or with the strict consensus tree of 295 single-gene trees [13]. In this study, 28/33 of these core genes (Table 1) were further analyzed. An ML tree based on the concatenated sequences of these 28 genes (Figure 1A) was found to have a topology highly congruent (SH-test, P = 1.0) with the rhizobial species tree described earlier [13], and was used as the reference species tree herein. In order to find potential taxonomic markers among these 28 genes, we calculated their ANIg values among rhizobial strains for which genome sequences are available (Table S1). Twelve genes satisfied the criterion that ANIg 95% or 96% serves as the boundary of rhizobial species corresponding to the species assignments based on genomic ANIm values (with 95% as the boundary, see below). Among these genes, SMc00019, truA and thrA were selected for further analyses, considering their shorter gene length (<1.5 kb) and more similar topology to the reference tree.

Figure 1. The maximum likelihood (ML) phylogenetic trees.

The tree was constructed by PhyML based on concatenated sequences of 28 core genes (A), SMc00019-truA-thrA concatenate (B) or recA-glnII-atpD concatenate (C). Bootstrap confidence levels ≥50% are indicated at the internodes. Bar = 10% nucleotide divergence.

The ML phylogenetic tree of concatenated SMc00019-truA-thrA (Figure 1B) had higher bootstrap values than the individual gene trees of SMc00019, truA, and thrA, and showed significant congruent topology (SH-test, P = 0.348) to the reference species tree (Figure 1A). Consequently, the SMc00019-truA-thrA concatenation could be used for the construction of a robust phylogenetic tree of rhizobia.

Genomic ANIm and the ANIg of the SMc00019-truA-thrA concatenation (ANIstt was used below) were calculated for 294 pairwise comparisons between strains in Bradyrhizobium, Mesorhizobium, Sinorhizobium and Rhizobium (Tables S3, S4, S5, and S6). Pearson and Spearman correlation coefficient values between these two data sets were 0.938 (P<0.0001) and 0.954 (P<0.0001), respectively. Although the linear curve produces a reasonable fit to these data (R2 = 0.881, F (1, 292) = 2155.01, P<0.0001), the quadratic function explains substantially more of the variance (R2 = 0.966, F (2, 291) = 4195.907, P<0.0001). Model comparison by using extra sum-of-squares suggests that the quadratic model is better than the linear (F (1, 291) = 745.117, P<0.0001). The highest value of interspecies ANIstt was 94% and the lowest value of intraspecies ANIstt was 96%, and these values corresponded to 93% and 95% ANIm of genome sequences (Figure 2 and Tables S3, S4, S5, and S6). Therefore, there seems to be an ANI gap (≥2%) between the boundaries of inter- and intra-species comparisons for rhizobia. One exception was, however, found when comparing R. leguminosarum bv. viciae 3841 and R. leguminosarum bv. trifolii WSM1325, for which ANIm = 94.15% and ANIstt = 95.5%. These are unexpectedly low values for an intraspecific comparison. Both ANIm and ANIstt values between CIAT652 and the type strain CFN42 were lower than 92% indicating that CIAT652 should belong to a species other than Rhizobium etli. This is consistent with the recent finding that CIAT652 may belong to R. phaseoli rather than R. etli [22]. Species assignments of several widely studied rhizobial strains USDA110, NGR234, BTAi1, ORS278, 3841 etc. should be further examined by comparing ANI values between each strain and the type strains in the corresponding genus (Table S2).

Figure 2. Plotted results of ANIstt (average nucleotide identity of SMc00019-truA-thrA) versus ANIm (genomic ANI).

460 intra-genus pairwise comparisons in Bradyrhizobium (190), Mesorhizobium (3), Sinorhizobium (91), Rhizobium (10), Agrobacterium (6), Cupriavidus (10), Methylobacterium (28), Ralstonia (10), Rhodopseudomonas (21) and Burkholderia (91). 7/460 points lie between the interspecies region (ANIm <93% and ANIstt <94%) and the intraspecies region (ANIm >95% and ANIstt >96%). The thick and fine solid line(s) depicted the quadratic curve (the best curve to fit the data) and the individual confidence intervals (95%). The quadratic equation and R square are shown.

Unfortunately, most rhizobial genome sequences available in the public database were not obtained from the type strains of the species. On the other hand, as described above, ANIstt (ANIg of SMc00019-truA-thrA) is a good surrogate for ANIm. Since these genes could potentially serve as excellent taxonomic markers, they were amplified from 67 type strains (Table S2) of species in four major rhizobial genera (Bradyrhizobium, Sinorhizobium, Mesorhizobium and Rhizobium) which account for around 80% of the species pool of rhizobia. Among 12 species of Bradyrhizobium (Table S7), 64/66 interspecies ANIstt values were below 94%; the exceptions were the B. lablabi/B. jicamae pair (ANIstt = 94.89%) and the B. elkanii/B. pachyrhizi pair (ANIstt = 96.59%). In Sinorhizobium (Table S8), 27/28 interspecies ANIstt values were below 94% and S. kummerowiae should be a later synonym of S. meliloti due to the high ANIstt (99.51%) between their type strains. In Mesorhizobium (Table S9), 204/210 interspecies ANIstt values were below 94%, exceptions were found in M. tianshanense/M. tarimense (97.72%), M. temperatum/M. mediterraneum (94.86%), M. amorphae/M. septentrionale (94.71%), M. tianshanense/M. temperatum (94.34%), M. temperatum/M. tarimense (94.34%) and M. tarimense/M. mediterraneum(94.12%). In Rhizobium (Table S10), 320/325 interspecies ANIstt values were below 94%, R. yanglingense, R. loessense and R. gallicum may belong to the same species due to their high ANIstt values (96.43%–97.79%), R. indigoferae and R. leguminosarum had ANIstt of 98.71%, ANIstt between R. pisi and R. fabae was 97.93%. Notably, considering the lowest boundary of intraspecies ANIstt 96% as described above, 621/629 currently known interspecies relationships were supported by this study and the remaining few species with interspecies ANIstt >96% (96.43%–99.51%) should be combined. Interestingly, these findings were perfectly supported by earlier MLSA and MALDI-TOF studies on Rhizobium and Ensifer (Sinorhizobium) [22][25]. Species assignments for those strains with whole genome sequences (Table S1) were also evaluated by calculating their ANIstt with type strains of related genera. Bradyrhizobium japonicum USDA 110 (ANIstt = 92.26%), Sinorhizobium fredii NGR234 (ANIstt = 93.86%), Sinorhizobium medicae WSM419 (ANIstt = 88.84%), Mesorhizobium loti MAFF303099 (ANIstt = 89.64%) and Rhizobium leguminosarum bv. trifolii WSM2304 (ANIstt = 93.20%) should represent species other than the names currently used. Moreover, Bradyrhizobium sp. BTAi1, Bradyrhizobium sp. ORS278, Bradyrhizobium sp. II CCBAU 43298, Bradyrhizobium sp. I (CCBAU 15615, CCBAU 15635 and CCBAU 15544), and Sinorhizobium sp. CCBAU 05631 did not belong to any known species (the highest ANIstt value between each strain and various type strains ranged from 81.04%–92.72%). R. leguminosarum bv. trifolii WSM1325 and R. leguminosarum bv. viciae 3841 had ANIstt of 95.1% and 95.5% with R. leguminosarum bv. viciae USDA 2370T, and these values lie between the inter- and intraspecies boundary of 94%–96%, implying a genetic continuum among these strains or an ongoing speciation process.

Traditional rhizobial molecular markers for rhizobial taxonomy or phylogeny

MLSA has been widely used in rhizobial taxonomy and phylogeny. Martens et al [26] compared phylogenies of dnaK, gltA, glnA, recA, thrC and 16S rRNA genes within the genus Ensifer (Sinorhizobium). Rivas et al [10] and Nzoué et al [11] assessed partial sequence analysis for atpD, recA, gyrB, rpoB, dnaK, glnA, glnII, gltA and thrC in the genus Bradyrhizobium. Although the concatenation of certain housekeeping genes sometimes produced reasonable taxonomic resolution, incongruent phylogenies were reported among these genes in the same studies [10][11], [26]. dnaK, glnA, gyrB, thrC, recA, atpD and rpoB are among the 295 core genes of rhizobial genomes [13] (Table 1). Moreover, the ML gene trees for dnaK and rpoB were not significantly different from the reference species tree, according to the SH test. An intraspecific rpoB sequence similarity of 98.2% and an interspecific value of 97.7% were earlier suggested for bacterial species definition [27]. Nevertheless, according to the species assignments of rhizobia based on ANIm, intraspecies ANIg values of rpoB were 97.36%–100% whereas the highest value of interspecies ANIg was 97.7%. In the case of dnaK, intraspecies ANIg values were 97.32%–100% whereas the highest interspecies ANIg was 97.95%. Thus neither rpoB nor dnaK had a clear gap between inter- and intra-species ANIg values for rhizobia. Among the housekeeping genes, recA, glnII and atpD have been widely used as molecular markers to study rhizobial taxonomy, phylogeny, biogeography and population genetics [12], [23], [28][31]. In this study, with SH-test, significant incongruence (P = 0.017) was found between the ML tree of concatenated recA-glnII-atpD (Figure 1C) and that of SMc00019-truA-thrA (Figure 1B), whereas, as mentioned above, the latter tree was congruent with the reference species tree of rhizobia (Figure 1A). A notable number of incongruent branches within Bradyrhizobium and Sinorhizobium were found in Figure 1C as compared to Figure 1A and 1B. In line with these observations, significant recombination signal was found in the concatenated recA-glnII-atpD sequence (PHI test, P<0.0001) but not in SMc00019-truA-thrA (PHI test, P = 0.332).

The application of SMc00019-truA-thrA in other prokaryotes

Interestingly, ANIstt also correlates well (Spearman correlation coefficient 0.835, P<0.0001) with the ANIm of strains in Agrobacterium, Methylobacterium, Ralstonia, Rhodopseudomonas, Cupriavidus and Burkholderia. In these genera, 160/166 intragenus comparisons belong to either the intraspecies ANI region (ANIm >95% and ANIstt >96%) or the interspecies region (ANIm <93% and ANIstt <94%). ANIstt could be used to evaluate current species assignments of related strains. For example, JMP134 [32] should not be referred to as Cupriavidus necator because it has low ANIm/ANIstt values (86.39%/81.74%) with the type strain N-1 [33], whereas H16 has been correctly named as C. necator (ANIm/ANIstt values are 95.59%/97.84% with N-1). Most strains, with published genomes, currently referred to as Rhodopseudomonas palustris should be subject to taxonomic re-evaluation, considering that 20/21 interstrain ANIm/ANIstt values are below 91%/94%. Likewise, among the completely sequenced genomes of Ralstonia solanacearum, CFBP2957, GMI1000 and PSI07 may not be considered as the same species due to their low values of ANIm (91.97%–92.73%) and ANIstt (85.96%–93.99%). ANIm/ANIstt also confirmed the interspecies relationships among Burkholderia cenocepacia, B. mallei, B. glumae, B. gladioli etc. Notably, Burkholderia ambifaria strains MC40_6 and AMMD have high intraspecies ANIm/ANIstt values (96.88%/98.55%), but 3 out of 4 ANIm values between MC40_6 and B. cenocepacia strains are above 94% and 1 out of 4 ANIm values between AMMD and B. cenocepacia is above 93%. In fact, among the seven points that are intermediate between the interspecific (ANIm <93% and ANIstt <94%) and intraspecific (ANIm >93% and ANIstt >94%) ANI regions (Figure 2), six points were found in these comparisons between B. cenocepacia and B. ambifaria strains. These findings are consistent with the view that B. cepacia complex bacteria (including B. cenocepacia, B. ambifaria etc.) may constitute a genetic continuum in which species have only relatively recently developed [34]. It is noteworthy that, as shown in Figure 2, a cluster of outliers are found around ANIstt = 85% and these data points all come from the comparisons between Burkholderia sp. CCGE1001/CCGE1002/CCGE1003 and other abovementioned Burkholderia species. The underlying mechanisms remained elusive, but it could be related to the distinct phylogenetic position of CCGE1001/CCGE1002/CCGE1003 in Burkholderia [34].


Comparing the genomic ANIm with the ANIg of core genes that have a phylogeny congruent with the reference species tree of rhizobia allowed us identifying three housekeeping genes (SMc00019-truA-thrA) whose ANIg could also reflect the intraspecies and interspecies genomic ANIm among rhizobial strains. The limits of intraspecies ANIg (96%) and interspecies ANIg (94%) of SMc00019-truA-thrA provided a criterion for rhizobial species definition that confirmed the majority of known interspecies relationships of rhizobia and called for amalgamation of certain species and name corrections for some widely studied strains. Reconsidering species assignments of related strains is particular important, if any evolutionary conclusions are to be made at the species or sub-species level. Indeed, the micro-evolutionary mechanisms of rhizobia and pathogenic bacteria have recently received a great deal of attention by microbiologists. Therefore, SMc00019-truA-thrA could be utilized in taxonomy, phylogeny, population genetics and biogeography of related bacteria and in metagenomics surveys. The same type of approach could also be carried out on any prokaryote.

Supporting Information

Table S3.

Genomic ANI (low-left) versus ANI of SMc00019-truA-thrA (up-right) in Bradyrhizobium .


Table S4.

Genomic ANI (low-left) versus ANI of SMc00019-truA-thrA (up-right) in Sinorhizobium .


Table S5.

Genomic ANI (low-left) versus ANI of SMc00019-truA-thrA (up-right) in Rhizobium .


Table S6.

Genomic ANI (low-left) versus ANI of SMc00019-truA-thrA (up-right) in Mesorhizobium .


Table S7.

ANIstt values between type stains of Bradyrhizobium .


Table S8.

ANIstt values between type stains of Sinorhizobium .


Table S9.

ANIstt values between type stains of Mesorhizobium .


Table S10.

ANIstt values between type stains of Rhizobium .



We thank Miss Yan Li for preparing the cultures of rhizobial type strains used in this study and J. Peter W. Young for language revision and comments. We also thank two anonymous reviewers for their comments on the manuscript.

Author Contributions

Conceived and designed the experiments: CFT. Performed the experiments: YMZ. Analyzed the data: YMZ CFT. Contributed reagents/materials/analysis tools: XHS WFC WXC CFT YMZ. Wrote the paper: CFT YMZ.


  1. 1. Fraser C, Alm EJ, Polz MF, Spratt BG, Hanage WP (2009) The bacterial species challenge: making sense of genetic and ecological diversity. Science 323 (5915) 741–746. (doi:10.1126/science.1159388).
  2. 2. Tindall BJ, Rossello-Mora R, Busse HJ, Ludwig W, Kampfer P (2010) Notes on the characterization of prokaryote strains for taxonomic purposes. Int J Syst Evol Microbiol 60 (Pt 1) 249–266. (doi:10.1099/ijs.0.016949-0).
  3. 3. Gevers D, Cohan FM, Lawrence JG, Spratt BG, Coenye T, et al. (2005) Opinion: Re-evaluating prokaryotic species. Nat Rev Microbiol 3 (9) 733–739. (doi:10.1038/nrmicro1236).
  4. 4. Richter M, Rossello-Mora R (2009) Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci U S A 106 (45) 19126–19131. (doi:10.1073/pnas.0906412106).
  5. 5. Konstantinidis KT, Tiedje JM (2005) Genomic insights that advance the species definition for prokaryotes. Proc Natl Acad Sci U S A 102 (7) 2567–2572. (doi:10.1073/pnas.0409727102).
  6. 6. Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P, et al. (2007) DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol 57 (1) 81–91. (doi:10.1099/ijs.0.64483-0).
  7. 7. Konstantinidis KT, Ramette A, Tiedje JM (2006) Toward a more robust assessment of intraspecies diversity, using fewer genetic markers. Appl Environ Microbiol 72 (11) 7286–7293. (doi:10.1128/AEM.01398-06).
  8. 8. Kuczynski J, Lauber CL, Walters WA, Parfrey LW, Clemente JC, et al. (2011) Experimental and analytical tools for studying the human microbiome. Nature Reviews Genetics 13: 47–58. (doi:10.1038/nrg3129).
  9. 9. Cho I, Blaser MJ (2012) The human microbiome: at the interface of health and disease. Nature Reviews Genetics 13: 260–270. (doi:10.1038/nrg3182).
  10. 10. Rivas R, Martens M, de Lajudie P, Willems A (2009) Multilocus sequence analysis of the genus Bradyrhizobium. Syst Appl Microbiol 32 (2) 101–110. (doi:10.1016/j.syapm.2008.12.005).
  11. 11. Nzoué A, Miché L, Klonowska A, Laguerre G, de Lajudie P, et al. (2009) Multilocus sequence analysis of bradyrhizobia isolated from Aeschynomene species in Senegal. Systematic and Applied Microbiology 32: 400–412. (doi:10.1016/j.syapm.2009.06.002).
  12. 12. Martens M, Dawyndt P, Coopman R, Gillis M, De Vos P, et al. (2008) Advantages of multilocus sequence analysis for taxonomic studies: a case study using 10 housekeeping genes in the genus Ensifer (including former Sinorhizobium). Int J Syst Evol Microbiol 58: 200–214. (doi:10.1099/ijs.0.65392-0).
  13. 13. Tian CF, Zhou YJ, Zhang YM, Li QQ, Zhang YZ, et al. (2012) Comparative genomics of rhizobia nodulating soybean suggests extensive recruitment of lineage-specific genes in adaptations. Proc Natl Acad Sci U S A. (doi:10.1073/pnas.1120436109).
  14. 14. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, et al. (2004) Versatile and open software for comparing large genomes. Genome Biol 5 (2) R12. (doi:10.1186/gb-2004-5-2-r12).
  15. 15. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, et al. (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28 (10) 2731–2739. (doi:10.1093/molbev/msr121).
  16. 16. Swofford DL (1998) PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4. Sunderland, Massachusetts, Sinauer Associates.
  17. 17. Posada D, Crandall KA (1998) MODELTEST: testing the model of DNA substitution. Bioinformatics 14 (9) 817–818. (doi:10.1093/bioinformatics/14.9.817).
  18. 18. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, et al. (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 59 (3) 307–321. (doi:10.1093/sysbio/syq010).
  19. 19. Retief JD (2000) Phylogenetic analysis using PHYLIP. Methods Mol Biol 132: 243–258. (doi:10.1385/1-59259-192-2:243).
  20. 20. Shimodaira H, Hasegawa M (1999) Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Mol Biol Evol 16 (8) 1114–1116.
  21. 21. Bruen TC, Philippe H, Bryant D (2006) A simple and robust statistical test for detecting the presence of recombination. Genetics 172 (4) 2665–2681. (doi:10.1534/genetics.105.048975).
  22. 22. Aserse AA, Rasanen LA, Assefa F, Hailemariam A, Lindstrom K (2012) Phylogeny and genetic diversity of native rhizobia nodulating common bean (Phaseolus vulgaris L.) in Ethiopia. Syst Appl Microbiol 35: 120–131. (doi:10.1016/j.syapm.2011.11.005).
  23. 23. Tian CF, Young JPW, Wang ET, Tamimi SM, Chen WX (2010) Population mixing of Rhizobium leguminosarum bv. viciae nodulating Vicia faba: the role of recombination and lateral gene transfer. FEMS Microbiol Ecol 73 (3) 563–576. (doi:10.1111/j.1574-6941.2010.00909.x).
  24. 24. Adler B, Ferreira L, Sánchez-Juanes F, García-Fraile P, Rivas R, et al. (2011) MALDI-TOF mass spectrometry is a fast and reliable platform for identification and ecological studies of species from family Rhizobiaceae. PLoS ONE 6 (5) e20223. (doi:10.1371/journal.pone.0020223).
  25. 25. Silva C, Vinuesa P, Eguiarte LE, Souza V, Martinez-Romero E (2005) Evolutionary genetics and biogeographic structure of Rhizobium gallicum sensu lato, a widely distributed bacterial symbiont of diverse legumes. Mol Ecol 14 (13) 4033–4050. (doi:10.1111/j.1365-294X.2005.02721.x).
  26. 26. Martens M, Delaere M, Coopman R, De Vos P, Gillis M, et al. (2007) Multilocus sequence analysis of Ensifer and related taxa. Int J Syst Evol Microbiol 57 (3) 489–503. (doi:10.1099/ijs.0.64344-0).
  27. 27. Adekambi T, Shinnick TM, Raoult D, Drancourt M (2008) Complete rpoB gene sequencing as a suitable supplement to DNA-DNA hybridization for bacterial species and genus delineation. Int J Syst Evol Microbiol 58 (8) 1807–1814. (doi:10.1099/ijs.0.65440-0).
  28. 28. Gaunt MW, Turner SL, Rigottier-Gois L, Lloyd-Macgilp SA, Young JPW (2001) Phylogenies of atpD and recA support the small subunit rRNA-based classification of rhizobia. Int J Syst Evol Microbiol 51 (Pt 6) 2037–2048.
  29. 29. Vinuesa P, Rojas-Jimenez K, Contreras-Moreira B, Mahna SK, Prasad BN, et al. (2008) Multilocus sequence analysis for assessment of the biogeography and evolutionary genetics of four Bradyrhizobium species that nodulate soybeans on the asiatic continent. Appl Environ Microbiol 74 (22) 6987–6996. (doi:10.1128/aem.00875-08).
  30. 30. Vinuesa P, Silva C, Werner D, Martinez-Romero E (2005) Population genetics and phylogenetic inference in bacterial molecular systematics: the roles of migration and recombination in Bradyrhizobium species cohesion and delineation. Mol Phylogenet Evol 34 (1) 29–54. (doi:10.1016/j.ympev.2004.08.020).
  31. 31. Zhang YM, Li Y, Chen WF, Wang ET, Tian CF, et al. (2011) Biodiversity and biogeography of rhizobia associated with soybean plants grown in the north china plain. Appl Environ Microbiol 77 (18) 6331–6342. (doi:10.1128/AEM.00542-11).
  32. 32. Lykidis A, Perez-Pantoja D, Ledger T, Mavromatis K, Anderson IJ, et al. (2010) The complete multipartite genome sequence of Cupriavidus necator JMP134, a versatile pollutant degrader. PLoS ONE 5 (3) e9729. (doi:10.1371/journal.pone.0009729).
  33. 33. Poehlein A, Kusian B, Friedrich B, Daniel R, Bowien B (2011) Complete genome sequence of the type strain Cupriavidus necator N-1. J Bacteriol 193 (18) 5017. (doi:10.1128/JB.05660-11).
  34. 34. Vandamme P, Dawyndt P (2011) Classification and identification of the Burkholderia cepacia complex: Past, present and future. Syst Appl Microbiol 34 (2) 87–95. (doi:10.1016/j.syapm.2010.10.002).