Abstract
Partial sequences of six core genes (fusA, gyrB, leuS, pyrG, rlpB, and rpoB) of 37 strains of Pantoea species were analyzed in order to obtain a comprehensive view regarding the phylogenetic relationships within the Pantoea genus and compare tree topologies to identify gene(s) for reliable species and subspecies differentiation. All genes used in this study were effective at species-level delineation, but the internal nodes represented conflicting common ancestors in fusA- and pyrG-based phylogenies. Concatenated gene phylogeny gave the expected DNA relatedness, underscoring the significance of a multilocus sequence analysis. Pairwise comparison of topological distances and percent similarities indicated a significant differential influence of individual genes on the concatenated tree topology. leuS- and fusA-inferred phylogenies exhibited, respectively, the lowest (4) and highest (52) topological distances to the concatenated tree. These correlated well with high (96.3%) and low (64.4%) percent similarities of leuS- and fusA-inferred tree topologies to the concatenated tree, respectively. We conclude that the concatenated tree topology is strongly influenced by the gene with the highest number of polymorphic and non-synonymous sites in the absence of significant recombination events.
Keywords: Pantoea stewartii, multilocus, phylogeny, leuS, topology
Introduction
Species of the genus Pantoea are nonencapsulated, nonspore-forming gram negative bacteria of the Enterobacteriaceae family. They are widely distributed in nature and have been isolated from plants, animals, and humans. Plant-associated pantoeas are either epiphytes or pathogens and constitute the majority of validly described species. Delétoile et al.1 reported seven validly described Pantoea species with two subspecies. Three (Pantoea citrea, Pantoea punctata, and Pantoea terrea) of the seven species have now been transferred to the genus Tatumella.2
Biochemical or nutritional characteristics used to differentiate Pantoea species/strains are inadequate and show considerable overlapping among species and subspecies. This might lead to potential errors in identification. An example is the biochemical heterogeneity of Pantoea agglomerans and related strains and species that make routine identification difficult.1 Phylogenetic inferences and identification of Pantoea species based on 16S rRNA showed that P. agglomerans, Pantoea ananatis, and Pantoea stewartii were closely related3,4 but have limitations at species- and subspecies-level identifications. An updated phylogeny using multiple loci (at least six) could provide some clarity to the DNA relatedness and the degree of uniqueness among current Pantoea species.
Multilocus sequence analysis (MLSA), with careful selection of representative sequences, provides an alternative approach to define species1,4 and improve pathogen identification. MLSA has been shown to be a powerful molecular method for microbial population genetics studies, delineation of species, and assignment of strains to defined bacterial species.5,6 The concept of MLSA involves systematic selection of several housekeeping/protein-coding genes to represent the chromosome.4 Inference of phylogeny on concatenated multiple protein-coding genes could allow for a clear delineation of species into sequence clusters that can provide valid indices for defining species1,7 even though the borders can be fuzzy in highly recombinogenic bacterial species.8 Young and Park4 used three genes (atpD, carA, and recA) to study the relationships of plant pathogenic enterobacteria, while Delétoile et al.1 used six genes (fusA, gyrB, leuS, pyrG, rplB, and rpoB) to delineate the four core Pantoea species (P. agglomerans, P. ananatis, P. stewartii, and Pantoea dispersa) with a focus on typing P. agglomerans because of its opportunistic-pathogen status in humans. Brady et al.9 used four housekeeping genes to assign new strains to the genus Pantoea. MLSA derived from few loci could be less informative, with potential impact on accurate phylogeny inference and reliable molecular identification. None of the previous studies on Pantoea species reported the discriminatory potential of each gene or compared the tree topologies obtained from the different single genes with that of concatenated tree. This is required for a better understanding of the influence of the different loci on the concatenated tree topology and to identify a reliable phylogenetic marker gene with similar topology. The objectives of this study were to define a comprehensive view regarding the phylogenetic relationships within the Pantoea genus using six core housekeeping genes, to determine percent similarities of tree topologies of each individual genes compared with that of the concatenated tree, and to identify a gene with tree topology that is highly similar (at least 95.0%) to that of the concatenated tree for reliable species and subspecies differentiation. We hypothesized that a gene with the highest number of polymorphic sites and proportion of non-synonymous sites could have a strong influence on the concatenated tree topology. The robustness of the tree topology of the selected gene(s) was compared against whole genome-based tree of 15 species of Pantoea, Erwinia, and Pectobacterium.
Materials and Methods
Bacterial strains and DNA extraction
Thirty-seven representative, reference, and/or type strains of Pantoea and Tatumella species were sequenced for multilocus phylogeny (Supplementary Table S1). Type strains of the genus Pantoea were obtained from the Belgian Coordinated Collections (BCCM/LMG; Ghent, Belgium). Strains were cultured in Luria-Bertani (LB) or nutrient broth (NB) and incubated at 28°C. Stock bacterial cultures were maintained on the same media supplemented with 25% w/v glycerol at −80 °C. Genomic DNA of the bacterial strains was purified using the Wizard SV Genomic DNA purification system Kit (Promega) following the manufacturer’s instructions.
Selection of housekeeping genes
The selected genes (leuS, rpoB, gyrB, fusA, pyrG, and rplB) were previously reported by Delétoile et al.1 in a study of P. agglomerans strains because of its opportunistic pathogen status in humans. Figure 1 shows the genomic location of the genes used in this study based on P. ananatis LMG 5342 (HE617160.1). These are single copy genes in most bacterial genera with important functional roles. leuS encodes leucyl-tRNA synthetase involved in translation. pyrG is implicated in glutamine hydrolysis through CTP synthase; rpoB encodes for the β subunit of RNA polymerase; gyrB is the structural gene for the DNA gyrase β subunit; and fusA encodes the protein synthesis elongation factor-G. The primers reported by Delétoile et al.1 were designed from conserved regions.
Figure 1.
Genomic location of core housekeeping genes used in this study based on P. ananatis LMG 5342 (Genbank genome accession number HE617160.1).
PCR amplification and nucleotide sequencing of core housekeeping genes
Partial sequences of six protein-coding genes (leuS, rpoB, gyrB, fusA, pyrG, and rplB) were generated for all the reference/type strains not available in public databases. The primer pairs and conditions applied in this study are as described by Delétoile et al.1 with the exception of rpoB. rpoBjt112 (GTTTATGGAYCAGAACAACCC)/rpoBjt748 (ATACGTGATGCRTCAACGTACT) primer pair was designed for rpoB and used in this study with an initial denaturation of 95 °C for 3 minutes, followed by 40 cycles of 95 °C for 45 seconds, 65 °C for 45 seconds, 72 °C for 90 seconds, and a final extension at 72 °C for 10 minutes. Primers were synthesized by Invitrogen Inc. (Carlsbad, CA, USA), and PCR amplifications were performed in a thermal cycler (Biometra) using 10 ng of bacterial DNA (1 μL), 1 μL of 10× PCR buffer, 0.75 μL of 2 mM deoxynucleoside triphosphates (dNTPs), 0.08 μL of each primer (20 μM), 0.1 μL of Titanium Taq DNA polymerase (5 U/μL; BD/Biosciences/Clontech), and 6.99 mL of MilliQ water. Sequencing was done as previously described10 using ABI BigDye Terminator chemistry v3.1 (Applied Biosystems) and run on an ABI 3130xl automated sequencer (Applied Biosytems/Hitachi). Sequences were edited using SeqMan (DNASTAR).
Analysis of sequence data
The sequences were imported into MEGA511 for final editing taking into account corresponding amino acids and checked for correct in-frame reading using RevTrans version1.4.12 Sequences were aligned using a Linux OS version of MUSCLE,13 and the alignments were trimmed so that sequences of each given gene were of the same length.
Summary statistics for the sequences were computed using DnaSP version 5.1.14 G + C content, number of haplotypes (h), number of polymorphic (segregating) sites (S), synonymous sites (πS), and non-synonymous sites (πN) with Jukes–Cantor correction statistics were calculated. The ratio of non-synonymous to synonymous substitutions (dN/dS) was calculated with Jukes–Cantor correction. Phi (Φw) was computed for evidence of recombination at 95% confidence interval as previously described15 and implemented in SplitsTree4 software.16 The phi test is based on the compatibility of informative sites providing a P value, which when significant (P < 0.05) would indicate that events of recombination are highly likely.
Geneious 5.6.4 (http://www.geneious.com/) was used to concatenate corresponding gene sequences. Prior to concatenation, the test for concordance was performed using the CAMD.global function.17 Distance matrices of the six core housekeeping genes were computed in MEGA511 and analyzed for congruency using Congruence Among Distance Matrices (CADM), a statistical test for estimating the level of CADM18 as implemented in R-statistics.17 The null hypothesis of the CADM test (H0) is the complete incongruence of two or more matrices, while the alternative hypothesis (H1) indicates partial or complete congruency.
The six genes were compared as previously reported19 to determine the most discriminating gene or genes. Briefly, a matrix of the phylogenetic distances between all the 37 strains was constructed for each single gene and pairwise least-square tendency lines were generated and compared. The discriminatory potential of the concatenated sequences was, also, compared with those of single genes.
Phylogenetic analyses of single gene and concatenated sequences using maximum likelihood
Aligned individual gene and concatenated sequences were used to infer maximum-likelihood (ML) phylogenies using PhyML version 3.020 and MEGA511 with the general time reversible (GTR) substitution model, selected on the basis of the Akaike information criterion implemented in jMODELTEST version 2.1.1.21 ML was executed with the Subtree pruning and regrafting (SPR) and nearest-neighbor interchange (NNI) tree improvement algorithms as implemented in PhyML20 and MEGA511 with 1000 bootstrap replicates for single gene phylogenies.
Comparison of tree topologies
Pairwise comparisons of the tree topologies derived from single gene and concatenated sequences were performed using the dist.topo (x, y, method = “PH85”) command as implemented in R-statistics.17 This function is based on Penny and Hendy (1985) rates (PH85) and describes the topological distance between two trees as twice the number of internal branches defining different bipartitions of the tips with a single numeric value as output. In addition, the Compare2Trees software22 was also used to compare phylogenies obtained from individual genes and concatenated sequences. This algorithm pairs up each branch in one phylogeny with a matching branch in the second phylogeny, and finds the optimum one-to-one map between branches in the two trees in terms of a topological score. This software identifies those parts of the trees that differ both in terms of topology and branch length.
Genome- and leuS-based phylogenies
The degree of similarity/dissimilarity of leuS phylogeny to that based on whole genome was determined using 15 publicly available genomes of Pantoea and closely related genera (Erwinia and Pectobacterium). Complete leuS gene sequences were extracted from the respective genomes and used to infer phylogenies using the composition vector (CV) approach.23 The CV approach is based on the frequency of appearance of overlapping oligonucleotides of length K in the genome or gene.23 CVTree (http://tlife.fudan.edu.cn/cvtr/) was used to construct genome- and leuS-based phylogenies with a K-value of 6 and Sulfolobus acidocaldarius Ron12/I (NC_020247) as outgroup. K = 6 was selected as the best based on our preliminary evaluation of different values. leuS- and genome-based tree topologies were compared as indicated above.
Sequence accession numbers
Two hundred and twenty-two sequences generated in this study were deposited in the Gen-Bank database with accession numbers KF482534–KF482570, KF482571–KF482607, KF482608–KF482644, KF482645–KF482681, KF482682–KF482718, and KF482719–KF482755 for fusA, gyrB, leuS, pyrG, rlpB, and rpoB, respectively.
Results
Summary statistics of sequenced genes
Table 1 summarizes the nucleotide sequence data for the six genes. Sequence length (bp) ranged from 306 (pyrG) to 722 (gyrB) with comparable G + C contents (51.5–56.9%). The number of segregating (polymorphic) sites as a percentage of sequence length was significantly highest in leuS (45.57%) followed by gyrB (36.84%) and pyrG (31.7%), while the rplB gene exhibited the lowest (18.62%). Nucleotide diversity of non-synonymous sites was highest for leuS (data not shown). All the ratios of dN/dS were <1 indicating that the six genes were subject to purifying selection. The phi test suggested that the gene fusA had significant high recombination events while pyrG and rpoB exhibited moderate recombination events (Table 1). The genes, gyrB, leuS, and rplB, did not show significant events of recombination.
Table 1.
Summary statistics for the six house-keeping gene and concatenated sequences used in this study.
| LOCUS | SEQUENCE LENGTH (bp) | GC CONTENT (%) | H | S | dN/dS | ϕω (P) |
|---|---|---|---|---|---|---|
| fusA | 588 | 51.5 | 19 | 163 | 0.12038 | 0.00002*** |
| gyrB | 722 | 52.5 | 22 | 266 | 0.03531 | 0.09800 |
| leuS | 643 | 56.9 | 21 | 293 | 0.09654 | 0.98600 |
| pyrG | 306 | 52.7 | 18 | 97 | 0.01515 | 0.03900* |
| rpoB | 409 | 52.9 | 20 | 114 | 0.05951 | 0.02600* |
| rplB | 333 | 55.7 | 17 | 62 | 0.04008 | 0.67000 |
| Concatenated | 3001 | 53.7 | 23 | 994 | 0.17937 | 0.00000*** |
Notes: ϕω phi test for evidence of recombination. P values < 0.05 (* or ***) indicate significant recombination events.
Abbreviations: h, number of haplotypes; S, number of polymorphic (segregating) sites; dN/dS, ratio of non-synonymous to synonymous substitutions.
Discriminatory potential of the different genes
The six genes were compared in order to determine the most discriminating gene or genes. A matrix of the phylogenetic distances between all the 37 strains was constructed for each single gene and the distances (3996 values) of pairs of strains were plotted.19 Plots were generated between leuS (exhibiting the highest number of polymorphic sites) or rlpB (lowest polymorphic sites) and the other five core genes. The ratio between the leuS slope and the slopes of the other genes was calculated as a measure of the discriminating potential of each gene19: leuS/rlpB (3.75 times); leuS/pyrG (1.88 times); leuS/rpoB (1.88 times); leuS/fusA (1.55 times); leuS/gyrB (1.25 times). The slopes of least square tendency lines indicate that Pantoea strains have the most distinguished genetic distance for one another in gene leuS, and to suggest that leuS is the most discriminating gene, which is followed by gyrB. Similarly, the matrix constructed for the concatenated nucleotide sequences of the six protein-coding genes (2997nt) was compared in a pairwise manner to assess the correlation and the relative discriminatory power (Fig. 2). The matrix distance of the concatenated sequence least correlated with rlpB, while maximum correlations were obtained with leuS and gyrB (Fig. 2). leuS and gyrB were 50 and 20% more discriminatory than the concatenated gene sequences, while fusA was comparable to that of the concatenated sequence. rpoB, pyrG, and rlpB were less discriminatory (Fig. 2) than the concatenated sequences.
Figure 2.
Least square tendency lines identified leuS as the most discriminating gene by correlation of phylogenetic distances between Pantoea strains as indicated by Mulet et al.19
Single gene and concatenated phylogenies
Single gene (Fig. 3A–F) and concatenated (Fig. 4) phylogenetic trees from leuS, gyrB, rpoB, fusA, pyrG, and rlpB were computed using ML to determine the phylogenetic relationships between Pantoea species. All single gene trees showed the main lineages (Fig. 3A–F) but some of the internal nodes represented conflicting common ancestors for some species in fusA- and pyrG-based phylogenies. The P. stewartii subgroup regrouped the two described subspecies (subspecies stewartii and indologenes) while the P. ananatis subgroup has all the strains of P. ananatis and Pantoea allii. The P. agglomerans subgroup included strains from P. agglomerans, Pantoea vagans, Pantoea deleyi, and Pantoea eucalypti. However, there were significant differences among genes with respect to the phylogenetic associations of P. dispersa, Pantoea septica, and Pantoea cypripedii. This discrepancy was most evident in fusA phylogeny with these three species sharing a direct ancestor with P. stewartii subgroup (Fig. 3D).
Figure 3.
Single gene phylogenetic trees inferred by maximum-likelihood (ML) of 37 strains of Pantoea and Tatumella using the general time reversible substitution model. A, leuS; B, gyrB; C, rpoB; D, fusA; E, pyrG; and F, rplB. ML trees were reconstructed for each gene sequences with 1000 bootstrap replicates. Bootstrap values higher than 50 are shown in black on nodes. Tatumella spp. were used as outgroup. Taxa and tree edges, and numbers in color denote differences, and percent edge similarity to that of the concatenated tree.
Figure 4.
The fusA–gyrB–leuS–pyrG–rlpB–rpoB concatenated tree inferred by maximum likelihood using 37 Pantoea strains, about 3000 bp. General time-reversible substitution model was used with 1000 bootstrap replicates. Tatumella spp. used as outgroup.
The expected phylogenetic associations were observed in the tree derived from concatenated gene sequences (Fig. 4). The tree inferred with concatenated sequences confirmed the phylogenetic affiliations of the core Pantoea subgroups (P. stewartii, P. ananatis, P. agglomerans, and P. dispersa) and resolved the conflicting common ancestors represented by some internal nodes especially for P. septica, P. dispersa, P. cyripedii, and P. deleyi. The P. stewartii subgroup did not include any of the newly described species while the P. ananatis subgroup now includes strains of P. allii. Strains of four new species (P. anthophila, P. eucalypti, P. vagans, and P. deleyi) could be associated with the P. agglomerans subgroup. P. cypripedii, a species recently transferred from Pectobacterium to Pantoea based on DNA relatedness, is affiliated with the P. dispersa subgroup. A new P. septica subgroup consisting of P. septica, P. calida, and P. gaviniae was identified based on genetic distance from the closest subgroups. Both strains of P. calida and P. gaviniae were isolated from powder infant milk and are highly (96.1%) similar genetically, but distantly similar to P. septica, a strain isolated from human stool. The inferred concatenated tree topology was highly congruent to leuS-derived tree.
Comparison of tree topologies
Table 2 shows the topological distances between the different phylogenetic trees generated based on PH85 rates and percent similarity of tree topologies. The highest PH85 topological distances (48 to 52) were obtained between fusA-inferred phylogeny and the other genes, an indication of high differences in tree topologies. leuS-derived tree showed the lowest PH85 topological distance of 20 with gyrB-inferred tree, suggesting high similarity. This is consistent with the high percent similarity (88.8%) computed between leuS and gyrB tree tolopogies (Table 2). leuS-derived tree topology was only 64.4% similar to that of fusA. The lowest percent similarity (59.1%) was recorded between rpoB and pyrG phylogenies (Table 2). Tree topology (Fig. 4) derived from concatenated sequences was 96.7, 89.7, or 70.8% similar to leuS, gyrB, or rpoB phylogeny, respectively. High similarity of leuS tree topology correlates well with the low topological distance based on PH85 rates (Table 2). The fusA phylogeny showed the highest topological distance of 52 when compared to tree topology derived from concatenated sequences.
Table 2.
Pairwise topological distances based on Penny and Hendy1 rate (above diagonal) and percent similarity (below diagonal) of tree topologies using Compare2Trees.
| leuS | gyrB | fusA | pyrG | rpoB | rlpB | CONCATENATED | |
|---|---|---|---|---|---|---|---|
| leuS | 0 (100%) | 20 | 52 | 44 | 32 | 40 | 4 |
| gyrB | 88.80% | 0 (100%) | 50 | 42 | 36 | 46 | 12 |
| fusA | 64.40% | 66.20% | 0 (100%) | 48 | 52 | 52 | 52 |
| pyrG | 61.90% | 65.70% | 80.10% | 0 (100%) | 44 | 42 | 42 |
| rpoB | 71.40% | 72.20% | 65.40% | 59.10% | 0 (100%) | 34 | 30 |
| rlpB | 66.10% | 66.20% | 75.00% | 69.50% | 73.20% | 0 (100%) | 36 |
| concatenated | 96.70% | 89.70% | 63.60% | 61.90% | 70.80% | 66.70% | 0 (100%) |
The tree edges within each single gene tree that differ from the corresponding edges on the concatenated tree are identified in Figure 3A–F. Three edges in leuS-derived trees differed from their corresponding tree edges on the concatenated tree with similarities of only 25, 62.5, and 75.0% (Fig. 3A), while fusA and pyrG, respectively, each showed seven differences with similarities ranging from 8.8 to 73.3% (Fig. 3D) and 33.3 to 86.7% (Fig. 3E), respectively. rpoB tree topology had six edges (Fig. 3C) while gyrB showed four edges (37.5, 55.6, 62.5, or 75.0%; Figure 3B) that differed from the corresponding edges on the concatenated tree. rlpB showed five edges (33.0, 40.0, 50.0, 50.0, and 83.0%; Figure 3F) that are not identical to those of the corresponding edges on the concatenated tree.
Genome- and leuS-based phylogenies
The tree topologies based on leuS and that derived from 15 complete genomes of Pantoea, Erwinia, and Pectobacterium showed highly similar clustering patterns (Fig. 5). Three clusters representing the different genera were apparent (Fig. 5). The leuS-derived tree topology (Fig. 5A) was 94.0% identical to that of genome-based phylogeny (Fig. 5B). In the leuS tree topology, the edge bifurcating to Pectobacterium carotovorum PC1 and P. carotovorum PCC21 seems to differ from the corresponding edge on the genome-based tree. On the genome-based tree topology, these two strains branched independently (Fig. 5B). A low similarity (73.8%) was observed between leuS-derived tree topology and that of a tree derived from the corresponding 40 complete genomes of 15 distantly related genera of the Enterobactericeae (data not shown).
Figure 5.
Similarities between leuS-infered (A) and whole genome-based (B) tree topologies of 15 publicly available Pantoea, Erwinia, and Pectobacterium genomes. Taxa and tree edges, and numbers in color denote differences, and percent edge similarity of leuS-based tree topology to that from whole genomes. Sulfolobus acidophilus Ron12 I (NC_020247) was used as outgroup.
Discussion
This study describes an in-depth analysis of a multilocus phylogeny of Pantoea species to determine the DNA relatedness of the Pantoea species using six genes and to compare single gene tree topologies of the different protein-coding genes to that from concatenated data. This allowed for the identification of leuS as a reliable phylogenetic marker for the genus Pantoea.
The MLSA approach has been used in several studies to reliably infer molecular relatedness among bacteria species.4,24–26 According to Cole et al,27 MLSA is “intermediary” of the 16S rRNA and the genome-based approach for phylogeny. It has been used to improve resolution at lower taxonomic ranks such as species and subspecies or to evaluate and eliminate phylogenetic inconsistencies due to lateral gene transfer.28–30 It is considered as a novel standard in microbial molecular systematics for species delineation.24 Several studies have proposed MLSA as an alternative to DNA–DNA hybridization24,27,28 but a consensus has not been reached due to some inherent problems.31 Whole genome-based phylogenies have potential to reveal more on similarities/dissimilarity between Pantoea species; however, at this time only six genomes (5 P. ananatis and 1 P. vagans) are available. In addition, computational and bioinformatics challenges need to be resolved before a comparative analysis can be routinely done on whole genomes of many bacteria. This indicates that MLSA will remain a useful tool in bacterial phylogeny and systematics.
It is clear that systematic biases are reduced by combining the phylogenetic signal from all loci in a concatenated dataset (multi-locus analyses). This has been the main objective of previous applications of MLSA in delineating Pantoea species, even though on a limited number of species.1,2,9 This study did not only achieve this goal but also did a comparison of single gene tree topologies to that of concatenated dataset as an indirect assessment of relative contribution of a gene to the final tree topology. In the absence of recombination events, we hypothesized that a single gene with the highest number of polymorphic sites could have a strong influence on the concatenated tree topology. This analysis allowed for the identification of leuS as a reliable phylogenetic marker for the genus Pantoea. A topological difference of only 3.3% was observed between leuS-derived and the concatenated tree topologies while those of the other genes ranged from 10.3% (gyrB) to 38.1% (pyrG). This suggests a differential influence of the loci studied on the outcome of the concatenated tree topology. High numbers of polymorphic and proportion of non-synonymous sites are among possible reasons why leuS gene strongly influenced the concatenated tree topology.
Also, leuS-based tree topologies compared favorably (94%) with whole genome-based tree of all publicly available Pantoea (5 genomes) and 10 closely related genera (Erwinia and Pectobacterium). However, relatively low similarity suggests that the robustness and reliability of the leuS phylogeny shows potential limitations with data consisting of different genera. This hypothesis was tested using 40 whole genomes of 15 enterobacterial genera and their corresponding complete leuS resulting to a lower (73.8%) topological similarity (data not shown).
Our results illustrate the importance of using multiple genes to buffer phylogenetic conflicting signals and to inform better on the validity of assigning strains to species and subspecies. Conflicting signals could be due to horizontal transfer or simply by recombination.26 Three of the six genes used in this study showed high recombination events, with fusA locus showing the highest probability. This could explain why the fusA-derived phylogeny was significantly different from the other phylogenies based on topological distances or percent similarities. The fusA phylogeny revealed a potential genetic exchange between the strains of P. stewartii, P. septica, P. dispersa and P. cypripedii. Genetic exchange between bacteria are significant and common evolutionary processes32,33 mediated by conjugation, transduction, and transformation.33,34 These processes promote the acquisition of novel genetic material and often lead to the emergence of new phenotypes/genotypes.33,34 It is not clear why leuS showed a high number of polymorphic sites (mutation) but little chance of recombination. This could be as a result of errors in single base substitutions during DNA replication or repair. Further investigation is required to elucidate the mechanisms involved.
Conclusion
An analysis was performed on a multilocus phylogeny of the genus Pantoea to determine the phylogenetic relationships of Pantoea species. It is clear that by combining the phylogenetic signal from all loci in a concatenated dataset (multi-locus analyses) systematic biases are reduced. An in-depth comparison of tree topologies derived from single individual genes suggests that the gene leuS had a strong influence on the concatenated tree topology, while pyrG and fusA had lesser effects. leuS satisfies the requirements for a suitable phylogenetic marker as previously reported.19 It is a single-copy housekeeping, protein-coding gene in Pantoea, it is widely distributed and has a high discriminative power of all the genes studied. Also, leuS has the lowest level of recombination, suggesting that it is not prone to lateral transfer. Its sequence length and high number of polymorphic sites allows sufficient phylogenetic resolution and the development of a reliable molecular diagnostic assay for genotyping strains of P. stewartii. We are currently validating leuS-based assays for reliable detection of six plant pathogenic Pantoea species in a single reaction.
Supplementary Data
Table S1.
Bacterial strains used in this studya.
| BACTERIAL SPECIES/STRAIN | SOURCE/HOST | COUNTRY |
|---|---|---|
| Pantoea stewartii subsp. stewartii: | ||
| LMG 2715T | Zea mays | USA |
| DC162 | Z. mays | USA |
| DOAB 022 | Z. mays | Canada |
| DC116 | Z. mays | USA |
| DC146 | Z. mays | USA |
| SS104 | Z. mays | USA |
| DC145 | Z. mays | USA |
| SW13 | Chaetocnema pulicaria | USA |
| DC283 | Z. mays | USA |
| DC147 | Z. mays | USA |
| SW1 | Z. mays | USA |
| Pantoea stewartii subsp. indologenes: | ||
| LMG 2632T | Setaria italica | India |
| LMG 2630 | Cyamopsis tetragonolobus | Unknown |
| LMG 2631 | Pennisetum americanum | India |
| DOAB 213 | Unknown | Unknown |
| Pantoea ananatis: | ||
| LMG 2665T | Ananas comosus | Brazil |
| LMG 2667 | Ananas comosus | Hawaii, USA |
| LMG 2668 | Ananas comosus | Hawaii, USA |
| LMG 2675 | Puccinia graminis f. sp. tritici | Hungary |
| Pantoea agglomerans: | ||
| LMG 1286T | knee laceration | Zimbabwe |
| LMG 2102 | Deer | USA |
| Pantoea anthophila: | ||
| LMG 2558T | Impatiens balsamina | India |
| LMG 2560 | Tagetes erecta | United Kingdom |
| Pantoea eucalypti: | ||
| LMG 24197T | Eucalyptus sp. | Uruguay |
| LMG 24198 | Eucalyptus sp. | Uruguay |
| Pantoea allii: | ||
| LMG24248T | Allium cepa | South Africa |
| Bacterial species/strain | Source/host | Country |
| Pantoea vagans: | ||
| LMG24199T | Eucalyptus sp. | Uganda |
| Pantoea calida: | ||
| LMG 25383T | Powdered infant formula | Switzerland |
| Pantoea gaviniae: | ||
| LMG 25382T | Powdered infant formula | Switzerland |
| Pantoea septica: | ||
| LMG 5345T | Human, stool | USA |
| Pantoea dispersa: | ||
| LMG2603T | Soil | Japan |
| Pantoea deleyi: | ||
| LMG 24200T | Eucalyptus sp. | Uganda |
| Tatumella punctata | ||
| LMG 23562T | Citrus sinensis | Japan |
Note: The type strains were obtained from BCCM/LMG bacterial collection, University of Ghent, Belgium. Strains with prefixes SW or DC were kindly provided by Dr. David Coplin.
Acknowledgments
The authors thank Shea Miller and John Bissett for reviewing the manuscript.
Footnotes
Author Contributions
JTT conceived and designed the project/experiment, analyzed data, and wrote the manuscript. RX performed all the PCR amplifications and gel electrophoresis. CAK sequenced the core housekeeping genes. JCN edited the DNA sequences. All authors reviewed and approved of the final manuscript.
ACADEMIC EDITOR: Jike Cui, Associate Editor
FUNDING: This research was funded by Agriculture and Agri-Food Canada through project #1800 and by the Defence R&D Canada-Centre for Security Science project # CRTI 09–462RD (leader, Dr. André Levesque).
COMPETING INTERESTS: Authors disclose no potential conflicts of interest.
This paper was subject to independent, expert peer review by a minimum of two blind peer reviewers. All editorial decisions were made by the independent academic editor. All authors have provided signed confirmation of their compliance with ethical and legal obligations including (but not limited to) use of any copyrighted material, compliance with ICMJE authorship and competing interests disclosure guidelines and, where applicable, compliance with legal and ethical guidelines on human and animal research participants.
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Associated Data
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Supplementary Materials
Table S1.
Bacterial strains used in this studya.
| BACTERIAL SPECIES/STRAIN | SOURCE/HOST | COUNTRY |
|---|---|---|
| Pantoea stewartii subsp. stewartii: | ||
| LMG 2715T | Zea mays | USA |
| DC162 | Z. mays | USA |
| DOAB 022 | Z. mays | Canada |
| DC116 | Z. mays | USA |
| DC146 | Z. mays | USA |
| SS104 | Z. mays | USA |
| DC145 | Z. mays | USA |
| SW13 | Chaetocnema pulicaria | USA |
| DC283 | Z. mays | USA |
| DC147 | Z. mays | USA |
| SW1 | Z. mays | USA |
| Pantoea stewartii subsp. indologenes: | ||
| LMG 2632T | Setaria italica | India |
| LMG 2630 | Cyamopsis tetragonolobus | Unknown |
| LMG 2631 | Pennisetum americanum | India |
| DOAB 213 | Unknown | Unknown |
| Pantoea ananatis: | ||
| LMG 2665T | Ananas comosus | Brazil |
| LMG 2667 | Ananas comosus | Hawaii, USA |
| LMG 2668 | Ananas comosus | Hawaii, USA |
| LMG 2675 | Puccinia graminis f. sp. tritici | Hungary |
| Pantoea agglomerans: | ||
| LMG 1286T | knee laceration | Zimbabwe |
| LMG 2102 | Deer | USA |
| Pantoea anthophila: | ||
| LMG 2558T | Impatiens balsamina | India |
| LMG 2560 | Tagetes erecta | United Kingdom |
| Pantoea eucalypti: | ||
| LMG 24197T | Eucalyptus sp. | Uruguay |
| LMG 24198 | Eucalyptus sp. | Uruguay |
| Pantoea allii: | ||
| LMG24248T | Allium cepa | South Africa |
| Bacterial species/strain | Source/host | Country |
| Pantoea vagans: | ||
| LMG24199T | Eucalyptus sp. | Uganda |
| Pantoea calida: | ||
| LMG 25383T | Powdered infant formula | Switzerland |
| Pantoea gaviniae: | ||
| LMG 25382T | Powdered infant formula | Switzerland |
| Pantoea septica: | ||
| LMG 5345T | Human, stool | USA |
| Pantoea dispersa: | ||
| LMG2603T | Soil | Japan |
| Pantoea deleyi: | ||
| LMG 24200T | Eucalyptus sp. | Uganda |
| Tatumella punctata | ||
| LMG 23562T | Citrus sinensis | Japan |
Note: The type strains were obtained from BCCM/LMG bacterial collection, University of Ghent, Belgium. Strains with prefixes SW or DC were kindly provided by Dr. David Coplin.