# Genome Signature Difference betweenDeinococcus radiodurans and Thermus thermophilus

Authors: Hiromi Nishida; Reina Abe; Taishi Nagayama; Kentaro Yano
Journal: International Journal of Evolutionary Biology
 (2012)

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## Abstract

The extremely radioresistant bacteria of the genusDeinococcus 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.


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## Body

## 1. Introduction

In the present bacterial taxonomic system, the extremely radioresistant bacteria of the genusDeinococcus and the extremely thermophilic bacteria of the genusThermus 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 betweenDeinococcus 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 (=44) 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.


## 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 (=44) 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 (Figure1), D. radiodurans is located in the high-GC-content cluster, whereas T. thermophilus is grouped with Thermanaerovibrio acidaminovoransand 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 ofD. 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 betweenDeinococcus radiodurans and each bacterium using correspondence analysis.
Bacterial speciesDistancePseudomonas aeruginosaPO10.297932379Myxococcus xanthus0.305390764Azorhizobium caulinodans0.308895493Ralstonia solanacearum0.309212661Gloeobacter violaceus0.317496648Symbiobacterium thermophilum0.324422553Thermomonospora curvata0.347077134Opitutus terrae0.376683191Acidobacterium capsulatum0.378916616Gemmatimonas aurantiaca0.383939504Rhodobacter sphaeroides2.4.10.386383492Rhodospirillum rubrum0.392789705Streptomyces griseus0.415746597Geobacter sulfurreducens0.425877427Agrobacterium tumefaciens0.457788385Thermomicrobium roseum0.460897799Syntrophobacter fumaroxidans0.470005872Sphingomonas wittichii0.478630032Desulfohalobium retbaense0.50752939Heliobacterium modesticaldum0.512911658Chloroflexus aurantiacus0.53688488Pirellula staleyi0.540489386Desulfatibacillum alkenivorans0.618176651Pelotomaculum thermopropionicum0.636637282Moorella thermoacetica0.637983756Xylella fastidiosa9a5c0.655118109Escherichia coliK-12 MG16550.671407958Neisseria meningitidisMC580.679417806Thermanaerovibrio acidaminovorans0.707497366Nitrosomonas europaeaATCC 197180.718956013Fibrobacter succinogenes0.773393097Dehalococcoides ethenogenes0.793600646Vibrio choleraeN169610.794460696Desulfitobacterium hafnienseDCB-20.823845007Thermus thermophilus0.831109438Shewanella oneidensis0.84848937Alteromonas macleodii0.881823764Aminobacterium colombiense0.889238858Thermobaculum terrenum0.899243716Syntrophomonas wolfei0.90576094Bacillus subtilis0.913613719Coprothermobacter proteolyticus0.923779953Chlorobium chlorochromatii0.926043337Coxiella burnetiiRSA 4930.929681834Thermotoga maritima0.952651677Bacteroides thetaiotaomicron0.958944885Denitrovibrio acetiphilus0.966489936Kosmotoga olearia0.998958025Carboxydothermus hydrogenoformans1.012583789Nostocsp. PCC 71201.014447775Aquifex aeolicus1.03027576Chlamydia trachomatisD/UW-3/CX1.041383827Elusimicrobium minutum1.06077929Haemophilus influenzaeRd KW201.084974973Veillonella parvula1.10092918Helicobacter pylori266951.124775019Cyanothecesp. ATCC 511421.126779861Thermoanaerobacter tengcongensis1.139238445Halothermothrix orenii1.149150516Eubacterium eligens1.164829099Natranaerobius thermophilus1.167863816Prochlorococcus marinusCCMP13751.174664974Fervidobacterium nodosum1.195233916Caldicellulosiruptor saccharolyticus1.19880562Caldicellulosiruptor bescii1.199097055Persephonella marina1.209862481Leptospira interrogansserovar lai 566011.221066506Anaerococcus prevotii1.224535688Petrotoga mobilis1.231307366Thermodesulfovibrio yellowstonii1.242134666Trichodesmium erythraeum1.246593564Sebaldella termitidis1.270114395Dictyoglomus turgidum1.29240584Dictyoglomus thermophilum1.297069077Thermosipho melanesiensis1.324630145Deferribacter desulfuricans1.331638037Clostridium acetobutylicum1.357082068Mycoplasma genitalium1.360597739Campylobacter jejuniNCTC 111681.374681774Leptotrichia buccalis1.383345312Rickettsia prowazekii1.426681449Borrelia burgdorferiB311.431569209CandidatusPhytoplasma asteris1.471567529Mesoplasma florum1.477622916Fusobacterium nucleatum1.487576702Brachyspira hyodysenteriae1.517447262Streptobacillus moniliformis1.535004291Ureaplasma parvumATCC 7009701.559892696Table 2
Distance betweenThermus thermophilus and each bacterium using correspondence analysis.
Bacterial speciesDistanceThermanaerovibrio acidaminovorans0.468763255Symbiobacterium thermophilum0.686400076Geobacter sulfurreducens0.756754453Myxococcus xanthus0.772836176Streptomyces griseus0.786527308Thermomonospora curvata0.791039191Moorella thermoacetica0.806329416Syntrophobacter fumaroxidans0.825184063Deinococcus radiodurans0.831109438Desulfohalobium retbaense0.835469081Rhodospirillum rubrum0.836862939Azorhizobium caulinodans0.837497899Gloeobacter violaceus0.847382695Rhodobacter sphaeroides2.4.10.857474011Desulfatibacillum alkenivorans0.876877944Heliobacterium modesticaldum0.886943785Pseudomonas aeruginosaPO10.902403886Pelotomaculum thermopropionicum0.910464775Acidobacterium capsulatum0.940977424Thermomicrobium roseum0.958396462Agrobacterium tumefaciens0.993864461Gemmatimonas aurantiaca0.993867563Ralstonia solanacearum0.99540692Opitutus terrae1.014357577Sphingomonas wittichii1.018425039Chloroflexus aurantiacus1.027585883Pirellula staleyi1.047176443Desulfitobacterium hafnienseDCB-21.051272244Dehalococcoides ethenogenes1.071801398Xylella fastidiosa9a5c1.080146527Thermobaculum terrenum1.103102039Aminobacterium colombiense1.103447745Syntrophomonas wolfei1.119525557Nitrosomonas europaeaATCC 197181.125942985Escherichia coliK-12 MG16551.136087269Neisseria meningitidisMC581.137392967Fibrobacter succinogenes1.147727362Aquifex aeolicus1.154770307Thermotoga maritima1.163190235Coprothermobacter proteolyticus1.187035315Vibrio choleraeN169611.194131544Carboxydothermus hydrogenoformans1.202997317Shewanella oneidensis1.207081448Bacillus subtilis1.236980427Coxiella burnetiiRSA 4931.237627206Kosmotoga olearia1.240198963Alteromonas macleodii1.241401986Bacteroides thetaiotaomicron1.250498401Chlamydia trachomatisD/UW-3/CX1.259097769Chlorobium chlorochromatii1.264256111Denitrovibrio acetiphilus1.264320363Nostocsp. PCC 71201.283892849Halothermothrix orenii1.307140057Thermoanaerobacter tengcongensis1.321852789Elusimicrobium minutum1.327006319Cyanothecesp. ATCC 511421.338924672Helicobacter pylori266951.353623157Veillonella parvula1.366604516Natranaerobius thermophilus1.374016605Persephonella marina1.384851067Prochlorococcus marinusCCMP13751.392425502Haemophilus influenzaeRd KW201.392980033Anaerococcus prevotii1.394012634Eubacterium eligens1.420199298Dictyoglomus turgidum1.42068199Caldicellulosiruptor saccharolyticus1.428805275Caldicellulosiruptor bescii1.430940559Dictyoglomus thermophilum1.432160811Petrotoga mobilis1.43247619Fervidobacterium nodosum1.436232766Leptospira interrogansserovar lai 566011.445508054Thermodesulfovibrio yellowstonii1.445636432Trichodesmium erythraeum1.459523665Sebaldella termitidis1.491593819Thermosipho melanesiensis1.522817305Deferribacter desulfuricans1.541728701Clostridium acetobutylicum1.553667164Mycoplasma genitalium1.586376378Campylobacter jejuniNCTC 111681.590027263Leptotrichia buccalis1.598390503Borrelia burgdorferiB311.626448618Rickettsia prowazekii1.653875547CandidatusPhytoplasma asteris1.673704846Fusobacterium nucleatum1.674099107Mesoplasma florum1.701326765Streptobacillus moniliformis1.715886446Brachyspira hyodysenteriae1.717967185Ureaplasma parvumATCC 7009701.784252531Although Pearson’s correlation coefficient between the tetranucleotide frequencies of genomes ofD. 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 ofDeinococcus radiodurans and Thermus thermophilus.Figure 3
Scatter plot between the tetranucleotide frequencies of the genomes ofDeinococcus radiodurans and Pseudomonas aeruginosa.Figure 4
Scatter plot between the tetranucleotide frequencies of the genomes ofThermanaerovibrio 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 (Figure1) 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].



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*Source: 205274-2012-03-04.xml*