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Applied and Environmental Microbiology, December 2007, p. 7597-7604, Vol. 73, No. 23
0099-2240/07/$08.00+0 doi:10.1128/AEM.01046-07
Copyright © 2007, American Society for Microbiology. All Rights Reserved.

Soybean Genomics and Improvement Laboratory, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, Maryland 20705,1 Laboratoire Interactions Légumineuses Microorganismes, Centre de Biotechnologie, Technopole de Borj Cédria (CBBC), BP 901, Hammam-Lif 2050, Tunisia,2 Penn State Berks College, P.O. Box 7009, Reading, Pennsylvania 196103
Received 10 May 2007/ Accepted 26 September 2007
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The plant genus Medicago L., as currently defined, consists of about 85 species (28), including Medicago sativa (alfalfa), the world's most important cultivated forage crop. Heyn (16) reported that this genus is native to Western Asia and the Mediterranean countries, although many annual species have invaded wide areas in both the Old and New Worlds.
Among the 85 species, M. laciniata has symbiotic properties that are unusual. While most Medicago species nodulated and formed nitrogen-fixing symbioses when they were grown in Australian soils with naturalized rhizobial populations, Ballard and Charman (3) observed that there was a lower incidence of nodulation with M. laciniata. They attributed this observation to the specific rhizobial requirement of M. laciniata that had been reported previously by Brockwell and Hely (7). For nodulation of M. laciniata, Brockwell and Hely (7) suggested that its rhizobia have distinct nodule formation behavior that distinguishes them from other Medicago-nodulating rhizobia. Barran et al. (4) provided evidence from a complementation and site-directed mutagenesis analysis that the specific nodC allele carried on the pSymA plasmid of strain USDA 1170 was required for successful nodulation of M. laciniata. Subsequently, Villagas et al. (34) proposed subdivision of S. meliloti into two biovars, S. meliloti bv. meliloti and S. meliloti bv. medicaginis, to distinguish the rhizobia of M. laciniata from other Medicago-nodulating rhizobia. However, it is unclear whether these two biovars have distinctive chromosomal genotypes or whether they are members of the same Medicago-nodulating rhizobial population.
Of the techniques used to estimate the diversity among Medicago-nodulating rhizobia, DNA fingerprinting is the most popular approach (1, 5, 6, 10, 12, 23, 24, 26, 36). However, DNA fingerprinting is not sufficiently specific to estimate the genetic diversity within and among the three large replicons normally found in Medicago-nodulating rhizobia (17). Therefore, an alternative methodology is necessary to investigate the potential correspondence between chromosomal and plasmid genotypes in different rhizobial genomes.
Multilocus sequence typing (MLST) was originally developed by Maiden et al. (22) for identification of the virulent lineages of the bacterial pathogen Neisseria meningitidis. In their study Maiden et al. (22) determined the allelic variation of seven loci by direct nucleotide sequence comparison. A combination of the observed alleles for each locus was then used to derive an allelic profile or sequence type (ST) for each of their strains. This made it possible to compare large numbers of multilocus bacterial genotypes. MLST results have been reported for numerous pathogenic bacterial species (13). Because MLST has been used to determine patterns of chromosomal evolutionary descent among Medicago-nodulating rhizobia (33), this strategy also can be used to determine any potential correspondence between chromosomal background and the nodC allele carried on pSymA.
Therefore, the primary goal of this study was to identify distinct chromosomal groups of rhizobia that were isolated from M. truncatula and M. laciniata growing in a single Tunisian soil using the strategy developed by van Berkum et al. (33). The MLST results were subsequently used to link the chromosomal groups with the distribution of the nodC alleles present in the genomes of the rhizobial isolates.
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The numbers of rhizobia present in the Amra soil able to nodulate M. truncatula and M. laciniata were estimated from most probable numbers using the methodology outlined by Vincent (35).
PCR primer design and PCR amplification of chromosomal loci and nodC.
The loci chosen for MLST analysis were described previously by van Berkum et al. (33). The primers for PCR and sequence analysis of loci encoding glyceraldehyde-3-phosphate dehydrogenase (gap), protein-PII uridylyltransferase (glnD), 6-phosphogluconate dehydrogenase (gnd), and the putative oxidoreductase protein (ordL2) were the primers described previously (33). Separate PCR and sequence primers were designed for the other six loci examined (Table 1) by using the primer design software package Oligo Primer Analysis, version 6.65 (Molecular Biology Insights, Inc., Cascade, CO). Similarly, PCR and sequence primers were designed to determine the nodC alleles present in each isolate and to sequence the entire 1,281-bp nodC gene present in representative isolates (Table 1). The oligonucleotides (Table 1) were synthesized by Sigma-Genosys (The Woodlands, TX) and were received as dried preparations. Upon receipt, the primers were dissolved in 10 mM Tris buffer (pH 8.0) to obtain a final concentration of 1,000 pmol/ml and were stored at –20°C. The PCRs for each locus were then optimized by using a FailSafe PCR premix selection kit (Epicenter, Madison, WI) and the thermal cycle protocol described by van Berkum and Fuhrmann (31) with a PTC-225 Peltier thermal cycler (MJ Research Inc., Waltham, MA), using genomic DNA of USDA 1002 and A321 as templates. The reaction mixtures were analyzed by horizontal agarose gel electrophoresis to select the FailSafe PCR system (Epicenter, Madison, WI) determined to be most suitable for PCR amplification of the DNA preparations of all 148 isolates used in this investigation. The presence of a single PCR product of the expected molecular size for each primer pair using each template was verified by horizontal gel electrophoresis. Each PCR product was then purified, especially to remove the PCR primers, by using the Ampure PCR purification system (Agincourt Bioscience Corporation, Beverly, MA).
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TABLE 1. Primer sequences used in MLST and nodC analysis of 148 Medicago-nodulating rhizobia originating from a single arid Tunisian soil collected at the Amra site
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Data analysis.
A Microsoft Access database was created to compile the data collected for the 148 isolates. The sequence lengths entered for each locus were the same, and the same alleles were identified using the software Sequence Comparator (version 2.0.1; Keith Jolley). As additional alleles were identified, they were assigned different allele numbers in the database. In each case, allelic variation was verified by confirming the sequence disparity using Genedoc (version 2.6.001; K. B. Nicholas and H. B. Nicholas [http://www.nrbsc.org/gfx/genedoc/index.html]) and then checking the electropherograms produced by the sequencing analysis to substantiate differences. When there were ambiguities, the sequencing analysis was repeated.
When the database was complete, the relationship function in Microsoft Access was used to create a query for the allelic allocation for each of the 10 loci across the 148 isolates. The resulting tabulated data were then exported as a Microsoft Excel file to prepare data input files. For Fig. 1 and 2 the data input files for the 148 isolates and 231 strains of Medicago-nodulating rhizobia (33) were combined. Based on the allele frequencies among the STs, the genetic diversity of each locus was determined using a computer program by T. S. Whittam (27). Sequence Type Analysis and Recombinational Tests (START) version 2 (19) was used to determine both the allele and profile frequencies and to create a Nexus input file for SplitsTree version 4.6 (18). SplitsTree 4.6 was used to represent the genetic relationships among the Medicago-nodulating rhizobia in the form of a NeighborNet. NeighborNet is a linkage tree algorithm similar to neighbor joining or the unweighted-pair group method using average linkages (UPGMA), but the pairing and combining of nodes are different to take into consideration the fact that the phylogenetic signals may conflict or that there may be alternate evolutionary histories (8) (for example, as a result of recombination). In this case, the input file used was a treelike distance matrix resulting in a splits graph. For analysis with eBURST, STs were classified as single-locus variants (SLVs), double-locus variants, or singletons (STs differing at three or more loci) according to the convention reported by Feil et al. (14), and then the data were combined with the data published by van Berkum et al. (33). The number of groups, the clonal complex in each group, and a population snapshot of the chromosomal variation were then generated using eBURST. The null hypothesis of linkage equilibrium for the multilocus sequence data as defined by Maynard Smith et al. (22a) was evaluated for the 148 isolates from Tunisia using the program LIAN 3.0 (15). The nodC sequence alignment, created in Genedoc (http://www.nrbsc.org/gfx/genedoc/index.html), included the nodC genes of Rhizobium leguminosarum (accession number Y00548) and R. tropici (accession number X98514) as references. The alignment was used to obtain nucleotide and derived amino acid sequence similarity matrices for construction of genetic distance trees using the UPGMA algorithm (21).
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FIG. 1. Snapshot of a population of 378 Medicago-nodulating rhizobia derived from allelic variation at 10 chromosomal loci. A matrix of the STs followed by the allele labels for each ST was used in eBURST (14) to generate a diagram of the evolutionary patterns among the strains and isolates. The snapshot was produced by setting the group definition to 0/10 genes. The sizes of the circles are related to the numbers of strains and isolates in each ST. The founder and cofounder genotypes are blue and yellow, respectively. The lengths of connecting lines between STs are arbitrary.
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FIG. 2. NeighborNet for 378 Medicago-nodulating rhizobia derived from allelic variation at 10 chromosomal loci. The inset shows the NeighborNet for the 148 Tunisian isolates. Matrices of the strain or isolate identification and the ST followed by the allele designations for each taxon was used in the START program (version 1.05) (19) to generate a Nexus file for input in Splitstree (18) to generate the NeighborNet (8).
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As a result of this study, the documented number of alleles present in the chromosomes of Medicago-nodulating rhizobia (33) was increased. In addition to the 91 STs reported previously by van Berkum et al. (33), another 23 STs were discovered. Specifically, additional alleles were obtained for the following loci: asd, edd, zwf, gap, glnD, gnd, nuoE, ordL, recA, and sucA (one, five, one, one, one, two, two, one, three, and one alleles, respectively). This increased the mean number of alleles from 11.3 as reported by van Berkum et al. (33) to 13.1. However, the genetic diversity among the loci decreased with the exception of gnd and recA, for which increases were recorded (Table 2). The mean number of alleles for all the isolates from the Amra site in Tunisia was 3.7, and the mean genetic diversity across the chromosomes was 0.396. The genetic diversity and the number of alleles for the isolates originating from nodules of M. truncatula were higher than the genetic diversity and the number of alleles for the isolates from M. laciniata (Table 2).
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TABLE 2. Number of alleles and genetic diversity across chromosomes of Medicago-nodulating rhizobia
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None of the Tunisian isolates were placed in groups 2 through 6 which were previously identified in the analysis of 231 strains (33). Instead, three new groups (groups 7 through 9) were identified. The largest of these (group 7) consisted of eight STs (Fig. 1). The predicted founding type was ST-98, with a bootstrap confidence value of 100%. ST-98 was distinguished for 35 of the 148 isolates, 22 and 13 of which originated from M. truncatula and M. laciniata, respectively. Within group 7 three and two isolates were placed in the SLVs ST-97 and ST-107, respectively, while only single isolates were associated with the remaining five SLVs of group 7. Group 7 (45 isolates) was larger than group 2, which had previously been identified as the second largest group of STs, with 18 isolates (33).
The other two newly identified groups (groups 8 and 9) were much smaller than group 7. Group 8 included three STs (ST-102, ST-103, and ST-104) associated with 10 of the isolates, while group 9 included two STs (ST-111 and ST-112) associated with 19 isolates. Two singletons also were identified, increasing the total number from 19 to 21.
The NeighborNet for the entire collection of 114 STs represents a summary of multiple trees (18). The extensive cross-linking within the network indicates that it would be inappropriate to use a single, nonreticulate tree to represent the genetic relationships among the STs (Fig. 2). Some, but not necessarily all, of the ambiguity may have been caused by recombination among the different chromosomes. Regardless, it was evident from the NeighborNet analysis that groups 3 and 5 continued to be the groups most distant from group 1, as previously reported by van Berkum et al. (33), even after the 26 Tunisian STs were included in the analysis.
Among the Tunisian STs, group 9 was the group most distant from group 1 (Fig. 2, inset). However, the group 9 STs were less distant from the group 1 STs than the group 6 STs and the singleton ST-71 (Fig. 2). The 16S rRNA gene sequences of ST-12 genome strain 1021 (9) and the rhizobia placed in groups 3, 5, and 6 and the singleton ST-71 were different (33). However, both the isolates with allelic profiles of ST-111 and two isolates each from M. laciniata and M. truncatula representing ST-112 had 16S rRNA gene sequences that were identical to that of strain 1021.
The 26 STs distinguished among the 148 Tunisian isolates were further subdivided based on the trap host into 22 and 8 STs that were isolated from nodules of M. truncatula and M. laciniata, respectively (Fig. 3). The four STs found in both species include the majority of the 148 isolates (73% or 108 isolates). Two of these four STs (ST-12 with 53 isolates and ST-98 with 35 isolates) were founders of groups 1 and 7, respectively. Three and 17 of the remaining isolates were placed in ST-97 (of group 7) and ST-112 (of group 9), respectively. The majority of the remaining 40 isolates originated from M. truncatula (32 isolates) and were placed into 18 STs that were not identified in the isolates from M. laciniata. Only eight isolates obtained from M. laciniata were allocated to four STs that were not found in the isolates recovered from M. truncatula (Fig. 3). However, these four STs were closely related to the four STs found in both host plant species, since ST-93 and ST-95 were both SLVs of ST-12, while ST-96 and ST-111 were SLVs of ST-98 and ST-112, respectively.
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FIG. 3. Diagram illustrating the host origins of rhizobia that belong to each of the STs. STs in the yellow, blue, and green areas originated from M. laciniata, from M. truncatula, and from both host species, respectively.
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TABLE 3. Test of the null hypothesis of linkage equilibrium among 26 multilocus STs in a collection of 148 Tunisian Medicago isolates from a single field site
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FIG. 4. Phylogeny of nodC in rhizobia that form symbioses with the legume genus Medicago. The sequence alignment, created in Genedoc (http://www.nrbsc.org/gfx/genedoc/index.html) with the nodC genes of R. leguminosarum (accession number Y00548) and R. tropici (accession number X98514) used as outgroups, was 1,285 bp long. The msf file was converted to Mega format with Mega version 2.1 (21), which was also used to obtain nucleotide (A) and derived amino acid (B) sequence similarities for construction of trees using the UPGMA algorithm.
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This study also differed from the study of van Berkum et al. (33) in terms of the strategy used to obtain the rhizobial isolates. In the current study all 148 isolates originated from a single soil at the Amra site in Tunisia. In contrast, only 1 or 2 of the 231 strains in the study of van Berkum et al. (33) originated from the same field site. Considering the range of the diversity present in the Amra soil, it appears that an intensive sampling strategy would be necessary to obtain more realistic local estimates of rhizobial diversity.
More chromosomal diversity was identified among the 74 isolates originating from M. truncatula (22 STs) than among the 74 isolates originating from M. laciniata (8 STs). Although both Medicago species are part of the natural flora of Tunisia (16), the lower rhizobial diversity in isolates nodulating M. laciniata at the Amra site may be related to the lower numbers of these isolates in the soil. Differential estimates of the most probable numbers for rhizobia nodulating different species of Medicago growing in soil from the Amra site were reported previously. Zribi et al. (36) indicated that the most probable number of rhizobia counted with M. sativa as the trap host was 6 x 102, while no rhizobia were found when M. polymorpha was used, possibly because this species is not part of the natural flora at the Amra site. Clearly, the sizes of the native populations of rhizobia that are adapted to specific Medicago host species vary widely at this location.
The majority of the rhizobia isolated from M. laciniata were placed in four STs that were also identified among the isolates from M. truncatula. Only eight isolates from M. laciniata were assigned to the four STs that were not detected in isolates from M. truncatula. However, the Amra soil probably does harbor rhizobia with these four chromosomal STs that nodulate M. truncatula, since these STs are SLVs of STs that originated from both host plant species. One reason why these rhizobia were not identified among the 74 isolates from M. truncatula may be their low numbers in the soil and the higher chromosomal diversity among the M. truncatula rhizobia. Despite the observation that these four STs were recovered only from M. laciniata, the soil at the Amra site is colonized by the same population of rhizobia that includes members that either have the capability to specifically nodulate M. laciniata or form symbioses with M. truncatula. Since the diversity among the isolates recovered from M. laciniata was more limited, it seems that the rhizobia with specificity for M. laciniata probably represent a subpopulation of the rhizobia that form symbioses with M. truncatula.
Even though most of the rhizobia of M. truncatula and M. laciniata from the Amra site share chromosomal identity, they differed in their plasmid-encoded nodC alleles. Barran et al. (4) previously implicated the nodC allele as an allele that is important in the host specificity of USDA 1170 for nodulation of M. laciniata. Whether the variation in nodC is associated with differences in entire nodulation operons or even dissimilar pSymA plasmids in the rhizobial genomes is not clear. This hypothesis could be evaluated by complete sequence analysis of the nod operon associated with each of the nodC alleles that were revealed in this study and by development and application of MLST using loci located on pSymA.
Finally, there also is uncertainty about the manner in which rhizobia with identical chromosomes could have acquired dissimilar nodC alleles, irrespective of whether it is due to a variation in the entire operon or pSymA itself. Using a phylogenetic approach, Bailly et al. (2) obtained evidence for the spread of nod genes among nitrogen-fixing symbionts of Medicago species. Kinkle and Schmidt (20) reported transfer of the pea symbiotic plasmid in nonsterile soil. Therefore, the most plausible explanation is that pSymA or distinct regions within pSymA were shared among members of the rhizobial population by lateral transfer and recombination.
We thank K. Lee Nash for excellent technical assistance.
Published ahead of print on 5 October 2007. ![]()
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, M., S. Sikora, S. Red
epovi
, and Z.
tafa. 2003. Genetic identification and symbiotic efficiency of an indigenous Sinorhizobium meliloti field population. Food Technol. Biotechnol. 41:69-75.This article has been cited by other articles:
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