International Journal of Evolutionary BiologyVolume 2012 (2012), Article ID 205274, 6 pagesdoi:10.1155/2012/205274

Research Article

Genome Signature Difference between Deinococcus radiodurans and Thermus thermophilus

Hiromi Nishida,¹ Reina Abe,² Taishi Nagayama,² and Kentaro Yano²

¹Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan²Bioinformatics Laboratory, Department of Life Sciences, School of Agriculture, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan

Received 7 November 2011; Accepted 8 December 2011

Academic Editor: Kenro Oshima

Copyright © 2012 Hiromi Nishida et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The extremely radioresistant bacteria of the genus Deinococcus and the extremely thermophilic bacteria of the genus Thermus belong to a common taxonomic group. Considering the distinct living environments of Deinococcus and Thermus, different genes would have been acquired through horizontal gene transfer after their divergence from a common ancestor. Their guanine-cytosine (GC) contents are similar; however, we hypothesized that their genomic signatures would be different. Our findings indicated that the genomes of Deinococcus radiodurans and Thermus thermophilus have different tetranucleotide frequencies. This analysis showed that the genome signature of D. radiodurans is most similar to that of Pseudomonas aeruginosa, whereas the genome signature of T. thermophilus is most similar to that of Thermanaerovibrio acidaminovorans. This difference in genome signatures may be related to the different evolutionary backgrounds of the 2 genera after their divergence from a common ancestor.

1. Introduction

In the present bacterial taxonomic system, the extremely radioresistant bacteria of the genus Deinococcus and the extremely thermophilic bacteria of the genus Thermus belong to a common lineage with remarkably different characteristics [1, 2]. Comparative genomic analyses have shown that after their divergence from a common ancestor, Deinococcus species seem to have acquired numerous genes from various other bacteria to survive different kinds of environmental stresses, whereas Thermus species have acquired genes from thermophilic archaea and bacteria to adapt to high-temperature environments [3]. For example, the aspartate kinase gene of Deinococcus radiodurans has a different evolutionary history from that of Thermus thermophilus [4]. In addition, D. radiodurans has several unique protein families [5] and genomic characters [6], and there is no genome-wide synteny between D. radiodurans and T. thermophilus [7]. However, phylogenetic analyses based on both orthologous protein sequence comparison and gene content comparison have shown that the genomes of Deinococcus and Thermus are most closely related with each other [3, 8]. The trinucleotide usage correlations have been used to predict the functional similarity between two RecA orthologs of bacteria including D. radiodurans and T. thermophilus [9].

If the genes acquired through horizontal gene transfers are different between Deinococcus and Thermus, then the genomic base composition (GC content) and/or genome signature can be hypothesized to also be different between these 2 genera. However, the GC content of D. radiodurans (67%) is similar to that of T. thermophilus (69.4%). The genome signature, on the other hand, is a powerful basis for comparing different bacterial genomes [11–19].

Phylogenetic analyses based on genome signature comparison have been developed, and these analyses are useful for metagenomics studies [20]. It was reported that comparative study using the frequency of tetranucleotides is a powerful tool for the bacterial genome comparison [21]. In this study, we compared the relative frequencies of tetranucleotides in 89 bacterial genome sequences and determined the phylogenetic positions of D. radiodurans and T. thermophilus.

2. Methods

2.1. Construction of Phylogenetic Relationships Based on the Relative Frequencies of Tetranucleotides in 89 Genome Sequences

We compared the relative frequencies of tetranucleotides in the genome sequences. The frequencies of the 89 bacteria were obtained from OligoWeb (oligonucleotide frequency search, http://insilico.ehu.es/oligoweb/). The 89 bacterial species are part of a list that which covers a wide range of bacterial species published in a previous report [8]. Each frequency vector consisted of 256 elements. The Euclidean distance between 2 vectors was calculated using the software package R (language and environment for statistical computing, http://www.R-project.org). On the basis of the distance matrix, a neighbor-joining tree was constructed using the MEGA software [10].

2.2. Ranking Based on Similarities between the Relative Frequencies of Tetranucleotides according to Correspondence Analysis

Correspondence analysis [22], which is a multivariate analysis method for profile data, was performed against the relative frequencies of tetranucleotides in 89 genomes. Correspondence analysis summarizes an originally high-dimensional data matrix (rows (tetranucleotides) and columns (genomes)) into a low-dimensional projection (space) [23, 24]. Scores (coordinates) in the low-dimensional space are given to each genome. The distance between plots (genomes) in a low-dimensional space theoretically depends on the degree of similarity in the relative frequencies of tetranucleotides: a short distance means similar relative frequencies of tetranucleotides between genomes, whereas a long distance means different relative frequencies. Thus, distance can be used as an index for similarity among genomes in the relative frequencies of tetranucleotides. Distances between all genome pairs were calculated, and then a ranking for distances was obtained.

3. Results and Discussion

In the neighbor-joining tree (Figure 1), D. radiodurans is located in the high-GC-content cluster, whereas T. thermophilus is grouped with Thermanaerovibrio acidaminovorans and their group is located away from the high-GC-content cluster. The neighbor-joining tree (Figure 1) was greatly influenced by the genomic GC content bias; most of the well-defined major taxonomic groups did not form a monophyletic lineage. This result indicates that each constituent of the well-defined major group has diversified by changing its genome signature during evolution. It is consistent with a previous paper indicating that microorganisms with a similar GC content have similar genome signature patterns [25].

Figure 1: Neighbor-joining tree based on tetranucleotide sequence frequencies in 89 genomes. The frequencies for 89 bacteria were obtained from OligoWeb (oligonucleotide frequency search, http://insilico.ehu.es/oligoweb/). Each frequency vector consisted of 256 elements. The Euclidean distance between 2 vectors was calculated using the software package R (language and environment for statistical computing, http://www.R-project.org). On the basis of the distance matrix, a neighbor-joining tree was constructed using the MEGA software [10]. Numbers in parentheses indicate the GC content (percentage) of each genome sequence. Arrows indicate the positions of Thermus thermophilus and Deinococcus radiodurans.

Phylogenetic analysis according to genome signature comparison is not based on multiple alignment data. Thus, bootstrap analysis cannot be performed. In this paper, we estimated the similarity between 2 different tetranucleotide frequencies by using correspondence analysis. The correspondence analysis showed that the genome signature of D. radiodurans is most similar to that of Pseudomonas aeruginosa (Table 1), whereas the genome signature of T. thermophilus is most similar to that of Th. acidaminovorans (Table 2). Although the D. radiodurans genome signature has similarity to 18 bacterial species within the distance 0.5, the T. thermophilus genome signature has similarity only to Th. acidaminovorans within the same distance (Table 2). These results indicate that T. thermophilus has a different genome signature from those of bacteria included in the high-GC-content cluster (Figure 1).

Table 1: Distance between Deinococcus radiodurans and each bacterium using correspondence analysis.

Bacterial species
Distance

Pseudomonas aeruginosa PO1
0.297932379

Myxococcus xanthus
0.305390764

Azorhizobium caulinodans
0.308895493

Ralstonia solanacearum
0.309212661

Gloeobacter violaceus
0.317496648

Symbiobacterium thermophilum
0.324422553

Thermomonospora curvata
0.347077134

Opitutus terrae
0.376683191

Acidobacterium capsulatum
0.378916616

Gemmatimonas aurantiaca
0.383939504

Rhodobacter sphaeroides 2.4.1
0.386383492

Rhodospirillum rubrum
0.392789705

Streptomyces griseus
0.415746597

Geobacter sulfurreducens
0.425877427

Agrobacterium tumefaciens
0.457788385

Thermomicrobium roseum
0.460897799

Syntrophobacter fumaroxidans
0.470005872

Sphingomonas wittichii
0.478630032

Desulfohalobium retbaense
0.50752939

Heliobacterium modesticaldum
0.512911658

Chloroflexus aurantiacus
0.53688488

Pirellula staleyi
0.540489386

Desulfatibacillum alkenivorans
0.618176651

Pelotomaculum thermopropionicum
0.636637282

Moorella thermoacetica
0.637983756

Xylella fastidiosa 9a5c
0.655118109

Escherichia coli K-12 MG1655
0.671407958

Neisseria meningitidis MC58
0.679417806

Thermanaerovibrio acidaminovorans
0.707497366

Nitrosomonas europaea ATCC 19718
0.718956013

Fibrobacter succinogenes
0.773393097

Dehalococcoides ethenogenes
0.793600646

Vibrio cholerae N16961
0.794460696

Desulfitobacterium hafniense DCB-2
0.823845007

Thermus thermophilus
0.831109438

Shewanella oneidensis
0.84848937

Alteromonas macleodii
0.881823764

Aminobacterium colombiense
0.889238858

Thermobaculum terrenum
0.899243716

Syntrophomonas wolfei
0.90576094

Bacillus subtilis
0.913613719

Coprothermobacter proteolyticus
0.923779953

Chlorobium chlorochromatii
0.926043337

Coxiella burnetii RSA 493
0.929681834

Thermotoga maritima
0.952651677

Bacteroides thetaiotaomicron
0.958944885

Denitrovibrio acetiphilus
0.966489936

Kosmotoga olearia
0.998958025

Carboxydothermus hydrogenoformans
1.012583789

Nostoc sp. PCC 7120
1.014447775

Aquifex aeolicus
1.03027576

Chlamydia trachomatis D/UW-3/CX
1.041383827

Elusimicrobium minutum
1.06077929

Haemophilus influenzae Rd KW20
1.084974973

Veillonella parvula
1.10092918

Helicobacter pylori 26695
1.124775019

Cyanothece sp. ATCC 51142
1.126779861

Thermoanaerobacter tengcongensis
1.139238445

Halothermothrix orenii
1.149150516

Eubacterium eligens
1.164829099

Natranaerobius thermophilus
1.167863816

Prochlorococcus marinus CCMP1375
1.174664974

Fervidobacterium nodosum
1.195233916

Caldicellulosiruptor saccharolyticus
1.19880562

Caldicellulosiruptor bescii
1.199097055

Persephonella marina
1.209862481

Leptospira interrogans serovar lai 56601
1.221066506

Anaerococcus prevotii
1.224535688

Petrotoga mobilis
1.231307366

Thermodesulfovibrio yellowstonii
1.242134666

Trichodesmium erythraeum
1.246593564

Sebaldella termitidis
1.270114395

Dictyoglomus turgidum
1.29240584

Dictyoglomus thermophilum
1.297069077

Thermosipho melanesiensis
1.324630145

Deferribacter desulfuricans
1.331638037

Clostridium acetobutylicum
1.357082068

Mycoplasma genitalium
1.360597739

Campylobacter jejuni NCTC 11168
1.374681774

Leptotrichia buccalis
1.383345312

Rickettsia prowazekii
1.426681449

Borrelia burgdorferi B31
1.431569209

Candidatus Phytoplasma asteris
1.471567529

Mesoplasma florum
1.477622916

Fusobacterium nucleatum
1.487576702

Brachyspira hyodysenteriae
1.517447262

Streptobacillus moniliformis
1.535004291

Ureaplasma parvum ATCC 700970
1.559892696

Table 2: Distance between Thermus thermophilus and each bacterium using correspondence analysis.

Bacterial species
Distance

Thermanaerovibrio acidaminovorans
0.468763255

Symbiobacterium thermophilum
0.686400076

Geobacter sulfurreducens
0.756754453

Myxococcus xanthus
0.772836176

Streptomyces griseus
0.786527308

Thermomonospora curvata
0.791039191

Moorella thermoacetica
0.806329416

Syntrophobacter fumaroxidans
0.825184063

Deinococcus radiodurans
0.831109438

Desulfohalobium retbaense
0.835469081

Rhodospirillum rubrum
0.836862939

Azorhizobium caulinodans
0.837497899

Gloeobacter violaceus
0.847382695

Rhodobacter sphaeroides 2.4.1
0.857474011

Desulfatibacillum alkenivorans
0.876877944

Heliobacterium modesticaldum
0.886943785

Pseudomonas aeruginosa PO1
0.902403886

Pelotomaculum thermopropionicum
0.910464775

Acidobacterium capsulatum
0.940977424

Thermomicrobium roseum
0.958396462

Agrobacterium tumefaciens
0.993864461

Gemmatimonas aurantiaca
0.993867563

Ralstonia solanacearum
0.99540692

Opitutus terrae
1.014357577

Sphingomonas wittichii
1.018425039

Chloroflexus aurantiacus
1.027585883

Pirellula staleyi
1.047176443

Desulfitobacterium hafniense DCB-2
1.051272244

Dehalococcoides ethenogenes
1.071801398

Xylella fastidiosa 9a5c
1.080146527

Thermobaculum terrenum
1.103102039

Aminobacterium colombiense
1.103447745

Syntrophomonas wolfei
1.119525557

Nitrosomonas europaea ATCC 19718
1.125942985

Escherichia coli K-12 MG1655
1.136087269

Neisseria meningitidis MC58
1.137392967

Fibrobacter succinogenes
1.147727362

Aquifex aeolicus
1.154770307

Thermotoga maritima
1.163190235

Coprothermobacter proteolyticus
1.187035315

Vibrio cholerae N16961
1.194131544

Carboxydothermus hydrogenoformans
1.202997317

Shewanella oneidensis
1.207081448

Bacillus subtilis
1.236980427

Coxiella burnetii RSA 493
1.237627206

Kosmotoga olearia
1.240198963

Alteromonas macleodii
1.241401986

Bacteroides thetaiotaomicron
1.250498401

Chlamydia trachomatis D/UW-3/CX
1.259097769

Chlorobium chlorochromatii
1.264256111

Denitrovibrio acetiphilus
1.264320363

Nostoc sp. PCC 7120
1.283892849

Halothermothrix orenii
1.307140057

Thermoanaerobacter tengcongensis
1.321852789

Elusimicrobium minutum
1.327006319

Cyanothece sp. ATCC 51142
1.338924672

Helicobacter pylori 26695
1.353623157

Veillonella parvula
1.366604516

Natranaerobius thermophilus
1.374016605

Persephonella marina
1.384851067

Prochlorococcus marinus CCMP1375
1.392425502

Haemophilus influenzae Rd KW20
1.392980033

Anaerococcus prevotii
1.394012634

Eubacterium eligens
1.420199298

Dictyoglomus turgidum
1.42068199

Caldicellulosiruptor saccharolyticus
1.428805275

Caldicellulosiruptor bescii
1.430940559

Dictyoglomus thermophilum
1.432160811

Petrotoga mobilis
1.43247619

Fervidobacterium nodosum
1.436232766

Leptospira interrogans serovar lai 56601
1.445508054

Thermodesulfovibrio yellowstonii
1.445636432

Trichodesmium erythraeum
1.459523665

Sebaldella termitidis
1.491593819

Thermosipho melanesiensis
1.522817305

Deferribacter desulfuricans
1.541728701

Clostridium acetobutylicum
1.553667164

Mycoplasma genitalium
1.586376378

Campylobacter jejuni NCTC 11168
1.590027263

Leptotrichia buccalis
1.598390503

Borrelia burgdorferi B31
1.626448618

Rickettsia prowazekii
1.653875547

Candidatus Phytoplasma asteris
1.673704846

Fusobacterium nucleatum
1.674099107

Mesoplasma florum
1.701326765

Streptobacillus moniliformis
1.715886446

Brachyspira hyodysenteriae
1.717967185

Ureaplasma parvum ATCC 700970
1.784252531

Although Pearson’s correlation coefficient between the tetranucleotide frequencies of genomes of D. radiodurans and T. thermophilus is 0.630 (Figure 2), that between the tetranucleotide frequencies of genomes of D. radiodurans and Pseudomonas aeruginosa is 0.935 (Figure 3) and that between the tetranucleotide frequencies of genomes of Th. acidaminovorans and T. thermophilus is 0.914 (Figure 4). These results support the results of the neighbor-joining and correspondence analyses.

Figure 2: Scatter plot between the tetranucleotide frequencies of the genomes of Deinococcus radiodurans and Thermus thermophilus.

Figure 3: Scatter plot between the tetranucleotide frequencies of the genomes of Deinococcus radiodurans and Pseudomonas aeruginosa.

Figure 4: Scatter plot between the tetranucleotide frequencies of the genomes of Thermanaerovibrio acidaminovorans and Thermus thermophilus.

The frequency of horizontal gene transfer between different bacteria may be associated with genome signature similarity. However, the tree topology based on genome signature (Figure 1) is different from that based on gene content [8]. This is caused by, among others, an amelioration of the horizontally transferred genes [26]. Our findings strongly support the previous report that Deinococcus has acquired genes from various other bacteria to survive different kinds of environmental stresses, whereas Thermus has acquired genes from thermophilic bacteria to adapt to high-temperature environments [3].

Acknowledgment

The authors thank Professor Teruhiko Beppu for his valuable comments and encouragement.

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