Improved resolution on the phylogenetic relationships amongPseudomonas by the combined analysis of atpD, carA, recA and 16S rDNA

Elena Hilario1,2, Thomas R. Buckley1 and John M. Young1,*1Landcare Research, Private Bag 92-170, Auckland, New Zealand; 2Current address: Horticulture and FoodResearch Institute of New Zealand, Private Bag 92-169, Auckland, New Zealand; *Author for correspondence(e-mail: youngj@LandcareResearch.co.nz; phone: 64-9-574-4200 x 7359; fax:64-9-574-4101)

Received 24 June 2003; accepted in revised form 12 November 2003

Key words: Phylogenies

Abstract

A study of representatives of the bacterial genus Pseudomonas, analysing a combined data set of four molecularsequences with completely different properties and evolutionary constraints, is reported. The best evolutionarymodel was obtained with a hierarchical hypothesis testing program to describe each data set and the combineddata set is presented and analysed under the likelihood criterion. The resolution among Pseudomonas taxa basedon the combined data set analysis of the different lineages increased due to a synergistic effect of the individualdata sets. The unresolved fluorescens lineage, as well as other weakly supported lineages in the single data settrees, should be revised in detail at the biochemical and molecular level. The taxonomic status of biovars of P.putida is discussed.

Introduction

In recent studies, revisions of the taxonomy of theProteobacteria have commonly been determined byreference to polyphasic classifications underpinnedby phylogenetic interpretations based only on com-parisons of 16S rDNA sequences using the neigh-bour-joining method �De Lajudie et al. 1994; Mooreet al. 1996; Vandamme et al. 1996; Hauben et al.1998�. In such analyses, the resolution of branches ofinferred phylogenetic trees was poor. In this study, thedata from several gene sequences from Pseudomonasspp. were combined to test whether such combina-tions would improve the resolution of the inferredphylogeny.

Until recently, the genus Pseudomonas was cir-cumscribed as a heterogeneous taxon represented byaerobic, Gram-negative, polar-flagellate, rod-shapedbacteria that do not produce spores and display a widevariety of physiological traits �Stanier et al. 1966;Palleroni 1984, 1993�. Pseudomonas �sensu stricto)

includes mainly fluorescent species belonging to thegamma-Proteobacteria �Kersters et al. 1996�. Revi-sions of the genus based on DNA-rRNA reassociationdata �Palleroni et al. 1973; De Vos et al. 1985�, aswell as progress on the phylogenetic analyses of 16SrDNA sequence data, have transferred species fromPseudomonas to new genera in the alpha-, beta- andgamma-Proteobacteria. Relocation of taxa withinPseudomonas �sensu stricto� has also been proposedbased on the inferred phylogenetic analyses of 16SrDNA �Moore et al. 1996; Anzai et al. 2000� and arecent report using combined data of gyrase B and therho factor �Yamamoto et al. 2000�. However, discrep-ancies have arisen due to different phylogeneticmethodologies and the nature of the molecularsequence under study.

The gene encoding 16S rRNA has been widelypreferred as a molecular sequence to reconstruct in-ferred phylogenies �Woese 1987� because it was as-sumed that the intraspecific variation and horizontaltransfer of this gene between organisms was low.

51© 2004 Kluwer Academic Publishers. Printed in the Netherlands.Antonie van Leeuwenhoek 86: 51–64, 2004.

These assumptions have been challenged �Clayton etal. 1995; Cilia et al. 1996; Gest 2003�. Moreover, inthe case of the genus Pseudomonas, the inferred phy-logenies based on 16S rDNA lack resolution at theintrageneric level due its slow rate of evolution�Yamamoto et al. 2000, Moore et al. 1996, Anzai etal. 2000�. Other molecular sequences, as well as otherstrategies to analyse the evolution of Pseudomonas,could clarify such discrepancies.

This study aimed to provide a robust systematicanalysis of several molecular sequences to resolvesome of the differences found in the inferred phylog-eny of the genus Pseudomonas, as well as to consideralternative explanations �e.g., recombination or hori-zontal gene transfer�. Four molecular sequences thatact in unrelated ways in bacterial metabolic processeswere selected for this study: atpD, carA, recA and16S rDNA. The gene atpD encodes the catalytic sub-unit of the F0F1-ATP synthase complex. The catalyticsubunit is part of the hexamer knob of the hydrophilicsector of the enzyme complex. The gene carA �car-

bamoyl phosphate synthase, subunit A� providesglutamine amidotransferase activity �GATase� neces-sary for removal of the ammonia group fromglutamine in the biosynthesis of pyrimidines and pu-rines. The gene recA �recombinase A� is a multi-functional protein involved in the S.O.S. mechanismof DNA repair. The small subunit of the ribosomalRNA �16S� allows the ribosome to select the properinitiation codon during translation. The internalregions of atpD, carA, recA and 16S rDNA by PCRwere obtained amplification using selected primers, orwere cloned where necessary, and sequenced.

Materials and methods

Bacterial cultures

Bacterial strains used in this study are listed in Table1. Strains were cultivated in liquid King’s medium B�modified�: K3�PO4� 3H2O 1.8 g/l, MgSO4 7H2O 1.5

Table 1. GenBank accession numbers for atpD, carA, recA and 16S rDNA of the Pseudomonas species used in this study

GenBank Accesion Numbers

Organism Strain used Other designations atpD carA recA 16S rDNA

P. aeruginosa ICMP 8647T ATCC 10145; NCIMB 9295 AJ414232 AJ414208 AJ316143 AJ308297P. aeruginosa PAO1 AE004967 AE004889 AE004782 AE004844P. agarici ICMP 2656T ATCC 29541; NCPPB 2289 AJ414233 AJ414209 AJ316144 AJ308298P. aurantiaca ICMP 6003T ATCC 33663; NCIMB 10068 AJ414234 AJ414210 AJ316145 AJ308299P. aureofaciens ICMP 13610T ATCC 13985; NRRL B-1576 AJ414235 AJ414211 AJ316146 AJ308300P. chlororaphis ICMP 13613T ATCC 9446; NCIMB 9392; NRRL B-560 AJ414236 AJ414212 AJ316147 AJ308301P. cichorii ICMP 5707T ATCC 10857; NRRL B-832 AJ414237 AJ414213 AJ316148 AJ308302P. flavescens ICMP 13539T ATCC 51555 AJ414238 AJ414214 AJ316149 AJ308320P. fluorescens ICMP 3512T ATCC 10844; NCIMB 9046 AJ414244 AJ414220 AJ316155 AJ308308P. fluorescens biotype A ICMP 13622 ATCC 17555; NCPPB 263 AJ414239 AJ414215 AJ316150 AJ308303P. fluorescens biotype B ICMP 13619 ATCC 17482; IFO 15832 AJ414240 AJ414216 AJ316151 AJ308304P. fluorescens biotype C ICMP 13624 ATCC 17559; IFO 15834 AJ414241 AJ414217 AJ316152 AJ308305P. fluorescens biotype F ICMP 13616 ATCC 12983; IFO 15837; NRRL B-1864 AJ414242 AJ414218 AJ316153 AJ308306P. fluorescens biotype G ICMP 13621 ATCC 17518; IFO 15838 AJ414243 AJ414219 AJ316154 AJ308307P. marginalis ICMP 3553T ATCC 10844; NCPPB 667 AJ414245 AJ414221 AJ316156 AJ308309P. mendocina ICMP 13540T ATCC 25411 AJ414246 AJ414222 AJ316157 AJ308310P. putida ICMP 2758T ATCC 12633; NCIMB 9494 ND AJ414225 AJ316160 AJ308313P. putida biotype A ICMP 13629 ATCC 17392 ND AJ414223 AJ316158 AJ308311P. putida biotype B ICMP 13630 ATCC 17472; NCIMB 11772 AJ414247 AJ414224 AJ316159 AJ308312P. resinovorans ICMP 13541T ATCC 14325 AJ414248 AJ414226 AJ316161 AJ308314P. stutzeri ICMP 12561T ATCC 17588; NCIMB 11358 ND AJ414227 AJ316162 AJ308315P. syringae ICMP 3023T ATCC 19310; NCPPB 281 AJ414249 AJ414228 AJ316163 AJ308316P. tolaasii ICMP 12833T ATCC 33618; NCPPB 2192 AJ414250 AJ414229 AJ316164 AJ308317

TType strain; ND: Not determined; ATCC: American Type Culture Collection, Manassas, Virginia, USA; ICMP: International Collection ofMicro-organisms from Plants, Landcare Research, Auckland, New Zealand; IFO: Institute for Fermentation, Osaka, Japan;NCIMB: NationalCollection of Industrial and Marine Bacteria, Aberdeen, Scotland; NCPPB: National Collection of Plant Pathogenic Bacteria, Ministry ofAgriculture, Fisheries and Food, Sand Hutton, York, England; NRRL: Agricultural Research Service Culture Collection, Peoria, Illinois,USA.

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g/l, glycerol 10 g/l, proteose peptone No. 3 �DifcoLaboratories� 20 g/l, pH 7.2. Single colonies werepicked from King’s medium B �modified� plates in-cubated at 30 °C for 2 or 3 days. Twenty-five ml ofliquid medium were inoculated with one single col-ony and grown overnight at 30 °C, 250 rpm. Cellswere harvested at 3783 g, 20 min, at 4 °C. The bac-terial pellet was washed with an equal volume ofsterile TE buffer �10 mM Tris-HCl, 1 mM EDTA, pH8.0�. The bacterial cells were used immediately toextract genomic DNA, or stored at � 20 °C for overa year without any evident DNA degradation.

Genomic DNA extractions

The extraction method, based on the protocol devel-oped by López-Gómez and Gómez-Lin �1992�, con-sisted of a selective precipitation of carbohydrates inthe presence of 20% ethanol and 0.5 M of potassiumions. The pH of the lysis buffer was adjusted withboric acid, which forms H-bonded complexes withpolyphenols �Su and Gibor 1988�. The bacterial pel-let �0.25-0.5 g wet weight� was resuspended in 14 mlof lysis buffer �0.5% SDS, 5 mM EDTA, 150 mMTris borate pH 7.4� and incubated for 10 min at 37 °C,inverting the tube 3 or 4 times during the incubation.1.4 ml of 5 M potassium acetate �pH 7.0� were added,and mixed gently by inversion, followed by 3.5 ml of100% ethanol. The mixture was vortexed at maxi-mum speed for 30 s, and extracted with equal volumeof chloroform:isoamyl alcohol �24:1�. The mixturewas then mixed in a rotary shaker �~70 rev/min� for5 min. The liquid phases were separated by centri-fugation at 12716 g, 10 min at 4 °C. The supernatantwas precipitated with equal volume of ice-cold iso-propanol, and incubated 30 min at � 20 °C. Nucleicacids were collected by centrifugation as before andwashed twice with half volume of 70% ethanol. Thepellet was air dried and resuspended in 2 ml TEbuffer. A standard RNase A extraction was followedby two phenol:chloroform extractions, one chloro-

form:isoamyl alcoholextraction, and sodium ace-tate:ethanol precipitation as described by Ausubel etal. �1994�. The final pellet was dissolved in 500 �lTE buffer by heating at 65 °C for 5 min. GenomicDNA was quantified visually on agarose gels �0.7%�against lambda bacteriophage DNA standards. Thegenomic DNA stocks were stored at � 20°C withoutdegradation for up to 3 years.

PCR amplification of the molecular sequences

The nucleotide sequences of the redundant primersdesigned for amplifying most of the internal regionof the atpD, carA, recA and 16S rDNA genes areshown in Table 2 �specific motifs of the amplified re-gions are described below�. The amplification cock-tail contained 1x PCR buffer �10 mM Tris-HCl, 1.5mM MgCl2, 50 mM KCl, pH 8.3, �Roche Diagnos-tics��, 0.2 mM of each deoxynucleotide, 12.5 pmol ofeach primer, 50 ng of genomic DNA, in a final vol-ume of 25 �l. Manual Hot Start was performed byadding 2 units of Taq DNA polymerase �Roche Diag-nostics� after the first 3 minutes of initial denatur-ation. The amplification of carA and recA wasperformed in a Cyclogene DriBlock® Cycler �Techne,Cambridge UK�, while the atpD and 16S rDNA geneswere amplified in a PC960G Microplate GradientThermal Cycler �Corbett Research, NSW, Australia�.The amplification profiles for carA and recA were asfollows: initial denaturation at 94 °C, 4 min, onecycle; denaturation at 94 °C, 30 s, annealing at 55 °C,20 s, polymerisation at 72 °C, 40 s, 25 cycles; finalextension at 72 °C, 10 min; overnight at 4 °C. Theamplification of atpD and 16S rDNA consisted of oneinitial denaturation step at 94 °C, 4 min; denaturationat 94 °C, 30 s, annealing by touchdown from 63 to53 °C, 2 cycles per degree, 30 s, polymerisation at72 °C, 1 min; 8 cycles of 30 s at 94 °C, 30 s at 53 °C,1 min at 72 °C; final extension at 72 °C 10 min;overnight at 25 °C. Five microliters were used for vi-sual quantification on agarose gels. The rest of the

Table 2. Nucleotide sequence of the primers for amplifying atpD, carA, recA and 16S rDNA

GENE Foward primer Reverse primer expected amplified product

atpD CTGGGCCGSATCATGGACG GTCCATGCCCAGGATSGCG 900 bpcarA TTCAACACCGCCATGACCGG TGATGRCCSAGGCAGATRCC 700 bprecA TCSGGYAARACCACSCTGAC RTACCAGGCRCCGGACTTCT 600 bp16S rDNA AGCGGCGGACGGGTGAGTAATG AAGGAGGGGATCCAGCCGCA 1300 bp

CAGCAGCCGCGGTAA GGGTTGCGCTCGTTG internal 16S rDNA sequencing primers

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PCR reaction was purified with Concert™ RapidPCR Purification System �Life Technologies, Gaith-ersburg, MD, USA�. The PCR products were se-quenced using the same primers used for theamplification, in both directions. Sequencing wasperformed using 310 ABI Prism™ BigDye™ Termi-nator Cycle Sequencing Ready Reaction Kit �AppliedBiosystems, Foster City, CA, USA�, 3.1 pmol ofprimer, 5 �l purified PCR product, in a final volumeof 10 �l. The sequencing reaction and its purificationwere performed according to the vendor’s recommen-dation. The sequencing reaction products wereresolved in a ABI Prism™ 377 Sequencer or ABIPrism™ 310 Genetic Analyzer. Sequences wereassembled and edited with Sequencher 3.1.1 �GeneCodes Corp., Ann Arbor, MI USA�. All nucleotidesequences are stored in GenBank �accession numbersshown in Table 1�.

Sequence and phylogenetic analysis

Nucleotide and amino acid multiple sequence align-ments were constructed with ClustalW version 1.7�Thompson et al. 1994� under the following param-eters: gap opening penalty: 10; gap extension penalty:0.05; delay divergent sequences; 40 %; DNA transi-tions weight; 0.50; protein weight matrix; BLOSUMseries; or DNA weight matrix; IUB. Visualization andmanual editing of the multiple sequence alignmentswas performed using GeneDoc �Nicholas et al. 1997�.The location of gaps in the nucleotide sequence werecompared against the amino acid multiple sequencealignment, taking into account the secondary struc-tural signatures located with PROSITE �Hofmann etal. 1999� or BLOCKS �Henikoff and Henikoff 1994�.Both ends of each multiple sequence alignment weretrimmed to the following final sizes: atpD 776 posi-tions, carA 625 positions, recA 597 positions, 16SrDNA 1373 positions. The combined data set was as-sembled by joining the four multiple sequence align-ments consecutively �3371 positions�.

All the phylogenetic analyses were performed withPAUP* version 4.0b4a �Swofford 2001�. The best fitmodels for the individual and combined data setswere selected using hierarchical likelihood ratio testsas implemented in ModelTest 3.06 �Posada and Cran-dall 1998�. The assumption of constant nucleotidefrequencies among taxa was tested with a �2 good-ness-of-fit test. Heuristic search settings were as fol-lows: gaps were treated as ‘missing’, starting treeswere obtained via stepwise random addition, 100

replicates, 1 tree held at each step during stepwiseaddition, branch-swapping performed with the tree-bisection-reconnection �TBR� algorithm, steepest de-scent not in effect, maximum number of trees set to100 with 100 tree increments, branches collapsed ifmaximum branch length is zero, and the trees wereunrooted. Bootstrap analysis was performed with aneighbour-joining start tree followed by 1000 TBRarrangements. This computational approximation wasimplemented due to the slowness of the likelihoodanalysis. The heterogeneity in phylogenetic signalamong the different genes was examined by imple-menting the Shimodaira-Hasegawa �Shimodaira-Ha-segawa 1999� test of topology. For each gene, the treeobtained from the combined analysis was comparedwith the optimal tree for that data sets. SH tests wereperformed with the RELL approximation and 10,000bootstrap replicates.

To search for evidence of horizontal gene transferwithin and between sequences, a recombination siteanalysis was performed with the combined multiplesequence alignment using the software package Phyl-Pro �Weiller 1998�.

Results

The partial sequences were aligned individually andverified according to structural motifs. A combinedmultiple sequence alignment was produced by join-ing the previously aligned single data sets. The par-tial amplified sequence of atpD encodes residuesinvolved in the catalytic site �PDOC00137� and theP-loop �PDOC00017�. Carbamoyl phosphate syn-thase �CPS� is formed of two subunits: the smallchain �carA� provides the glutamine amidotransferaseactivity �GATase�, and the large chain �carB� providesthe CPSase activity. The first two GATase domainsignatures were identified with BLOCKS �PR00099�.The signature pattern of recA �PDOC00131� islocated in the middle of the sequence and is part ofthe monomer-monomer interface. The secondarystructure prediction of the 16S rDNA of Escherichiacoli was used to verify the multiple sequence align-ment of this gene �Gutell et al. 2000, www.rna.icm-b.utexas.edu�.

The properties of the four molecular data sets arepresented in Table 3. Except for the atpD data set, theother three sets contain 23 taxa. The average GCcontent is 60%, which is close to the average GCcontent of Pseudomonas �61-70%, Comprehensive

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Microbial Resource, The Institute of Genomic Re-search�. No nucleotide bias was detected in any of thedata sets �P�0.96�. The best-fit models for the like-lihood analysis were selected with ModelTest 3.06.The major difference between the models selected forthe single and combined data sets was that for thecarA and 16S rDNA data sets, the null hypothesis ‘1or 2 transversion rates’ was accepted, leading to theTamura and Nei model �TrN�, whereas for atpD, recAand the combined data sets the hypothesis wasrejected and the transitional model �TIM� or the gen-eral time reversible model �GTR� were selected. Thenull hypotheses of ‘equal rates among sites’ and ‘noinvariable sites’ were rejected in all cases, and thecorresponding parameters for each data set are shownin Table 3.

Inferred phylogenetic trees based on maximumlikelihood and constructed with parameters estimatedby ModelTest 3.06 �Table 3� are shown in Figure 2,using the combined data �Figure 2a�, atpD �Figure2b�, carA �Figure 2c�, recA �Figure2d� and 16S rDNA�Figure 2e�.

The combined data set was scanned with the pro-gram PhylPro �Weiller 1998� to search for recombi-nation events that could indicate horizontal transfer ofgenes among pseudomonads. No significant recombi-nation sites were detected under different parametersimplemented in the program �data not shown�.

Discussion

The genus Pseudomonas is an unusually diversegroup, but there are few reports of detailed studies atthe molecular level. Apart from early DNA-rDNA re-association studies �Palleroni et al. 1972; 1973; DeVos et al. 1985� and recent 16S rDNA sequence data,there have been few attempts to model the phylogenyof the genus using other sequence data. Figure 1shows a condensed version of the inferred phyloge-nies described for the evolution of Pseudomonas pro-posed by Moore et al. �1996� and Anzai et al. �2000�,based on comparative analyses of 16S rDNA se-quence data, and by Yamamoto et al. �2000�, basedon gyrase B and the rho factor �Yamamoto et al.2000�. The trees only show the species common tothese studies. The three inferred phylogenies agree inrecognizing two major intrageneric clusters: thePseudomonas aeruginosa and the Pseudomonas fluo-rescens intrageneric clusters also called intragenericcluster I �IG 1� and intrageneric cluster II �IG II� re-spectively, that encompass several Pseudomonas lin-eages. In most cases the location of each lineagewithin the intrageneric clusters is a matter of contro-versy.

Within Pseudomonas sensu stricto, Moore et al.�1996� identified two intrageneric clusters by neigh-bour-joining. The P. aeruginosa intrageneric cluster

Table 3. Properties of the four molecular sequences

atpD carA recA 16S rDNA Combined

Number of taxa 20 23 23 23 23Number of positions 776 625 597 1373 3371Nucleotide frequenciesA 0.2064 0.1776 0.2025 0.2576 0.2196C 0.3134 0.3538 0.3268 0.2169 0.2918G 0.2841 0.2958 0.3144 0.3106 0.3042T 0.1961 0.1728 0.1563 0.2149 0.1844Base frequency test �p-value�a 25.15 �0.99� 46.31 �0.96� 22.42 �0.99� 2.21 �1.00� 47.30 �0.96�Best fit modelb TIM�I�G TrN�I�G GTR�I�G TrN�I�G GTR�I�GProportion of invariable sites 0.5901 0.3884 0.6045 0.797 0.6196Gamma distribution shape parameter 0.7667 0.8096 0.7692 0.7407 0.5959Rate matrixrAC 1.0000 1.0000 0.1504 1.0000 0.6188rAG 3.1253 2.9103 2.7569 2.1685 2.3539rAT 1.8095 1.0000 1.1612 1.0000 1.3020rCG 1.8095 1.0000 0.7492 1.0000 0.9889rCT 6.4077 7.0367 8.9093 3.2742 5.8151

a Base frequency values were calculated with PAUP*, df = 66for all data sets, except atpD, df = 56. b Best fit model parameters were cal-culated with the hierarchical hypothesis testing implemented in ModelTest 3.06: TIM, transitional model �Rodríguez et al. 1990�; TrN,Tamura-Nei �Tamura and Nei 1993�; GTR, general time reversible �Rodríguez et al. 1990�; I, proportion of invariable sites; G, shape pa-rameter of the gamma distribution.

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comprised the following lineages: aeruginosa, resino-vorans, mendocina and flavescens �IG I�, whereas theP. fluorescens intrageneric cluster comprised chloro-raphis, fluorescens, syringae and putida lineages �IGII�. In a comprehensive study, Anzai et al. �2000�identified two main clusters based on maximum like-lihood methods. The first cluster included aeruginosaand related species. Within the second cluster theydistinguished five subclusters: chlororaphis, fluore-scens, putida, stutzeri and syringae with P. agarici asdistinct species. Yamamoto et al. �2000� proposed amodel of the phylogenetic relationships based on thecombined data from gyrase B gene �gyrB� and the rhofactor gene �rpoD� analysed by neighbour-joining.They recognized the same two intrageneric clustersand a more complex pattern of internal relationships.The P. aeruginosa intrageneric cluster was dividedinto two complexes: aeruginosa and stutzeri; the P.fluorescens intrageneric cluster comprised three com-plexes: putida, fluorescens and syringae. Although the

three inferred phylogenies recognized defined clustersand species lineages, some of these were poorly sup-ported at the statistical level, as indicated with ques-tion marks and unresolved branches in Figure 1.

The two intrageneric clusters were well supportedby chemotaxonomic analyses using whole-cell fattyacid methyl ester �FAME� and phospholipid fatty acidprofiling �Vancanneyt et al. 1996� and were clearlyidentified in this study �Figure 2� and in previous re-ports �Moore et al. 1996; Anzai et al. 2000; Yama-moto et al. 2000�. However, attempts to correlate anyother phenotypic trait to the defined lineages haveencountered many complications �Moore et al. 2000�.The extraordinary phenotypic and genetic diversityamong Pseudomonas �Spiers et al. 2000� showed nodefinitive pattern of distribution that could defineprecisely any of the lineages. For this reason, ameaningful account of the evolutionary history of thegenus Pseudomonas needs to be well supported byrobust inferred phylogenies based on molecular data.

Figure 1. Hypotheses on the phylogeny of Pseudomonas; Summarized versions of the trees proposed by a� Anzai et al. �2000�, maximumlikelihood tree estimated with HKY85 substitution model; b� Moore et al. �1996�, neighbor-joining tree using the JC69 substitution model,and c� Yamamoto et al. �2000�, neighbor-joining tree using K80 substitution model. Only the species considered in the present study aredepicted. Nodes supported by bootstrap values � 50% are depicted; however, nodes with lower support values considered by the authors arealso included and marked with double question marks �??�. Conflict among the three hypotheses are denoted with one question mark. Thenodes leading to the intrageneric clusters are denoted by numbers 1 and 2. The branch comprising the chlororaphis, fluorescens, and syringaelineages is marked by number 3.

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In this study combined data sets as well as singledata sets were used to reconstruct the inferred phylo-genetic relationships of selected Pseudomonas spe-cies. Combined molecular data sets have been widelyused to study the phylogenetic relationships ofdiverse organisms �Barkman et al. 2000; Colgan et al.2000; Cryan et al. 2000; O’Donnell et al. 1998;Remigio and Herbert 2000; Savolainen et al. 2000;Soltis et al. 1998; Thao et al. 2000; Yamamoto et al.2000�. This approach is not immune to criticism. For

example, arguments against combining data sets arebased on the observation that different molecular datasets have evolved in different ways and are informa-tive at different taxonomic levels. To test the compat-ibility among different data sets, statistical tests toexamine the heterogeneity in the phylogenetic signalshave been developed. Based on the parsimony crite-rion, the Templeton test �1983�, and the IncongruenceLength Difference test �ILD; Farris et al. 1994� havebeen developed, as well as likelihood approaches

Figure 2a. Phylogenetic relationships in Pseudomonas; Maximum likelihood phylogenetic trees constructed with parameters estimated byModelTest 3.06 �Table 3� using the combined data. Branches with less than 50% bootstrap support were collapsed. Scale bar denotes numberof substitutions per site. Separation between the intrageneric clusters is denoted with a black triangle.

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such as the Kishino-Hasegawa �K-H; Kishino andHasegawa 1989� and the Shimodaira-Hasegawa �S-H;Shimodaira and Hasegawa 1999� tests. The ILD testwith the 23 taxa plus 8 outgroup taxa chosen amongthe proteobacteria showed that in most instances thedata sets were incongruent and one possible interpre-tation of this result is that they should not be com-bined �data not shown�. Preliminary phylogenetictrees in which several outgroups �Campylobacter, Es-cherichia, Haemophilus, Helicobacter, Neisseria,Vibrio and Xyllela, all from the Proteobacteria� were

considered, showed that the Pseudomonas strainsgroup closely together and the internal structure couldnot be readily interpreted from the tree. The data setscontaining only the Pseudomonas strains did notshow any nucleotide bias �Table 2�. A second reasonfor not including these outgroups �Figure 2� was be-cause their inclusion caused extremely long branchesthat produced anomalous branching orders within theingroup by long branch attraction �Hendy and Penny1989�.

Figure 2b. Phylogenetic relationships in Pseudomonas; Maximum likelihood phylogenetic trees constructed with parameters estimated byModelTest 3.06 �Table 3� using atpD. Branches with less than 50% bootstrap support were collapsed. Scale bar denotes number of substi-tutions per site. Separation between the intrageneric clusters is denoted with a black triangle.

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As parsimony may not be the best criterion toanalyse the data presented in this work, as suggestedby the heterogeneous data set characteristics, resultsfrom the ILD test were set aside and the S-H test wasimplemented. The results from these tests also indi-cated substantial heterogeneity in phylogenetic signalamong the partitions. However, the combined datashowed increased resolution, probably due to a syn-ergistic effect among the data sets that are able to re-solve different clades �Eernisse and Kluge 1993; Wolf

et al. 2002�. This effect was also observed by distanceanalysis under the Tamura-Nei model for the com-bined data set phylogeny �data not shown�, and it wasalso observed by Yamamoto et al. �2000� for someclades of their proposed phylogeny built with thecombined data set gyrB-rpoD. Only bootstrap valuesare presented for supports for the inferred phyloge-nies constructed with the most suitable evolutionarymodel analysed under the likelihood criterion. Thisapproach presents a hypothesis on the evolution of the

Figure 2c. Phylogenetic relationships in Pseudomonas; Maximum likelihood phylogenetic trees constructed with parameters estimated byModelTest 3.06 �Table 3� using carA. Branches with less than 50% bootstrap support were collapsed. Scale bar denotes number of substi-tutions per site. Separation between the intrageneric clusters is denoted with a black triangle.

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Pseudomonas that clearly supports the intragenericsplit and provides support for previous lineageassignments but rejects other weakly supportedbranches. The phylogenetic information contained inthe single and combined data sets was not able to re-solve branches among the fluorescens lineage. Per-haps more variable molecular sequences should beincluded, e.g. the ITS region of the ribosomal genes,or other intergenic regions. In the era of whole-genome phylogenetic comparisons, combined data

analysis will certainly gain more support and contrib-ute to the development of new assessment tests.

The effect of recombination and horizontal genetransfer on phylogenetic inference could not beassessed in this study. All data presented here wereobtained from PCR products of the 4 genes directlysequenced from the 23 taxa. Because the genes werenot cloned and individual clones sequenced for eachstrain, it is not possible to determine the role of re-combination in the evolution of these genes fromthese data. Although there is evidence of only one

Figure 2d. Phylogenetic relationships in Pseudomonas; Maximum likelihood phylogenetic trees constructed with parameters estimated byModelTest 3.06 �Table 3� using recA. Branches with less than 50% bootstrap support were collapsed. Scale bar denotes number of substi-tutions per site.

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copy of atpD, carA, and recA from the fullysequenced genomes of P. aeruginosa PaO1,Pseudomonas putida KT2440 and Pseudomonas sy-ringae DC3000, there are 4, 7 and 5 copies of the 16SrDNA gene, respectively �Comprehensive MicrobialResource, The Institute of Genomic Research�. Thenumber of copies of the 16S rDNA gene couldincrease the likelihood of recombination events inthese sequences, as has been studied in Escherichiacoli �Cilia et al. 1996�. The inferred phylogenies re-ported by Moore et al. �1996�, Anzai et al. �2000� and

Yamamoto et al. �2000� are also based on directly se-quenced PCR products and not individually isolatedPCR clones, which leaves the question unanswered asto the extent to which recombination events have af-fected the phylogeny of the genus Pseudomonas.

Horizontal gene transfer as an explanation for con-flicting inferred phylogenies was evaluated. Althoughthe trees presented in this study have no outgroup�e.g., other gamma-proteobacteria�, there is no radi-cal misplacement of any taxa across the intragenericcluster boundary in the combined data or the single

Figure 2e. Phylogenetic relationships in Pseudomonas; Maximum likelihood phylogenetic trees constructed with parameters estimated byModelTest 3.06 �Table 3� using 16S rDNA. Branches with less than 50% bootstrap support were collapsed. Scale bar denotes number ofsubstitutions per site. Separation between the intrageneric clusters is denoted with a black triangle.

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data set trees �Figure 2�. Unresolved lineages �e.g.chlororaphis lineage in the 16S rDNA tree, Figure 2e�are not candidates for horizontal gene transfer butthey did show the power of resolution of each dataset and the combined data set in support of eachclade.

The likelihood phylogenetic trees calculated for thecombined and single data sets under the parametersselected by ModelTest 3.06 are shown in Figure 2a-e.The node that connects Pseudomonas flavescens,Pseudomonas mendocina, Pseudomonas stutzeri,Pseudomonas resinovorans and P. aeruginosa is wellsupported in all likelihood trees �91-100% bootstrapsupport� except in the recA tree �Figure 2d�. Thisnode corresponds to the major divisions detected byother authors: the ‘Pseudomonas aeruginosa intrage-neric cluster’ �IG I� described by Moore et al. �1996�,‘Cluster I’ of Yamamoto et al. �2000� and the‘Pseudomonas aeruginosa group’ of Anzai et al.�2000�, except that in the later work, P. stutzeri formsan independent group.

The fluorescens lineage is clearly identified by thecombined data and carA likelihood trees, andmarginally supported by the 16S rDNA and recA datasets. P. agarici groups among the fluorescens lineagein almost all trees �Fig 2�, and fails to conform to anindependent lineage as previously reported by Mooreet al. �1996� and Anzai et al. �2000�, except in the 16SrDNA phylogeny where P. agarici is the seconddeepest branch in the P. fluorescens intrageneric clus-ter �IG II�, although weakly supported by the boot-strap analysis. All the P. fluorescens biotypes A, B, C,F, and G group together with the P. fluorescens typestrain in all the phylogenies but none of the molecu-lar sequences used in this study was able to resolvethe branching order among them. The grouping ofbiotype F, or G or B with P. putida B, or P. agarici orthe syringae lineage is inconsistent and not well sup-ported. The same observations hold true forPseudomonas marginalis and Pseudomonas tolaasiiwhich only group among the fluorescens lineage.

There are three lineages that could be consideredmonophyletic according to the results reported hereand by other authors �Moore et al. 1996; Anzai et al.2000; Yamamoto et al. 2000�: the chlororaphislineage, the syringae lineage and the putida lineage.The chlororaphis lineage is consistently locatedwithin the P. fluorescens intrageneric cluster �IG II�.This lineage is fully resolved and well supported bythe combined data set and the atpD phylogenies. Thetrees obtained with recA and carA showed a trifurca-

tion among the three species, whereas the 16S rDNAtree is only able to group together P. aurantiaca andP. aureofaciens, and leaves P. chlororaphis unre-solved within the fluorescens lineage. The syringaeand putida lineages are the deepest branches withinthe P. fluorescens intrageneric group, as clearlyshown by the combined data and carA phylogenies�both lineages�, and the 16S rDNA and rec A �for theputida lineage only�. The atpD phylogeny is incon-clusive regarding the putida lineage, since the PCRamplification of this gene from the P. putida typestrain and P. putida biotype A was unsuccessful.

The deepest branches of the P. aeruginosa intrage-neric group are P. flavescens and P. mendocina asshown in the phylogenies constructed with the com-bined data set, atpD, carA and 16S rDNA. The recAtree shows a multifurcating branch leading to theaeruginosa intrageneric group and fails to resolve thetaxa contained in the P. aeruginosa intragenericgroup. The only two species that consistently grouptogether are P. aeruginosa �type strain and PaO1strain� and P. resinovorans, as previously reported byAnzai et al. �2000�.

The synonymy of P. aureofaciens and P. chlorora-phis, with P. chlororaphis taking priority �Johnsonand Palleroni 1989�, and the close relationship of P.aurantiaca to this species has been indicated �Palle-roni 1984�. These species were included for detailedsequence analyses to consider possible recombinationevents between them. The individual sequencesrepresent a greater diversity than is demonstrated be-tween the biovars of P. fluorescens and unless there isa clear phenotypic differentiation between them thenboth P. aureofaciens and P. aurantiaca can be con-sidered synonyms of P. chlororaphis. There was noevidence for recombination events within the se-quences considered.

P. putida B consistently groups among the fluore-scens lineage, although not fully resolved, but nevergroups with P. putida type strain or P. putida biotypeA. P. putida was distinguished in determinative testsfrom P. fluorescens by its lack of proteolytic activity�Palleroni 1984�. The species was divided into twobiovars. However, from the sequence analysis re-corded here, P. putida biovar A and the sequence rep-resenting the type strain of the species are distantlyrelated to P. fluorescens in terms of inferred phylog-enies. By contrast, P. putida biovar B is closely re-lated to P. fluorescens biovar F, which is equivalentto biovar 5 in the nomenclature of Palleroni �1984�.Further studies are needed to determine if the P. fluo-

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rescens biovars merit species rank by reason of phe-noypic differences or if P. putida biovar B should berecognised as an additional biovar of P. fluorescens.

Acknowledgements

The Marsden Fund of the Royal Society of NewZealand under contract 97-LAN-LFS-0011; Dr D. R.Musgrave, University of the Waikato, Hamilton, NewZealand, as associate investigator; M. J. Fletcher, DrDianne Gleeson and Dr Richard Leschen from Land-care Research, New Zealand, for assistance with thebacterial cultures; Dr P.K. Buchanan and G. Putt; Dr.G. Weiller, Australian National University, Canberra,Australia, for assistance in the analysis of putative re-combination sites using his software package �Phyl-Pro �Beta Version 0.9��; Dr A. Rodrigo, University ofAuckland, Auckland, New Zealand, for constructivecomments.

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