Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Identification of the Pangenome and Its Components in 14 Distinct Aggregatibacter actinomycetemcomitans Strains by Comparative Genomic Analysis

  • Weerayuth Kittichotirat,

    Affiliation Department of Microbiology, University of Washington, Seattle, Washington, United States of America

  • Roger E. Bumgarner,

    Affiliation Department of Microbiology, University of Washington, Seattle, Washington, United States of America

  • Sirkka Asikainen,

    Affiliation Department of Surgical Sciences, Periodontology, Kuwait University, Kuwait City, Kuwait

  • Casey Chen

    ccchen@hsc.usc.edu

    Affiliation Division of Periodontology, Diagnostic Sciences and Dental Hygiene, Herman Ostrow School of Dentistry of the University of Southern California, Los Angeles, California, United States of America

Identification of the Pangenome and Its Components in 14 Distinct Aggregatibacter actinomycetemcomitans Strains by Comparative Genomic Analysis

  • Weerayuth Kittichotirat, 
  • Roger E. Bumgarner, 
  • Sirkka Asikainen, 
  • Casey Chen
PLOS
x

Abstract

Background

Aggregatibacter actinomycetemcomitans is genetically heterogeneous and comprises distinct clonal lineages that may have different virulence potentials. However, limited information of the strain-to-strain genomic variations is available.

Methodology/Principal Findings

The genome sequences of 11 A. actinomycetemcomitans strains (serotypes a-f) were generated de novo, annotated and combined with three previously sequenced genomes (serotypes a-c) for comparative genomic analysis. Two major groups were identified; serotypes a, d, e, and f, and serotypes b and c. A serotype e strain was found to be distinct from both groups. The size of the pangenome was 3,301 genes, which included 2,034 core genes and 1,267 flexible genes. The number of core genes is estimated to stabilize at 2,060, while the size of the pangenome is estimated to increase by 16 genes with every additional strain sequenced in the future. Within each strain 16.7–29.4% of the genome belonged to the flexible gene pool. Between any two strains 0.4–19.5% of the genomes were different. The genomic differences were occasionally greater for strains of the same serotypes than strains of different serotypes. Furthermore, 171 genomic islands were identified. Cumulatively, 777 strain-specific genes were found on these islands and represented 61% of the flexible gene pool.

Conclusions/Significance

Substantial genomic differences were detected among A. actinomycetemcomitans strains. Genomic islands account for more than half of the flexible genes. The phenotype and virulence of A. actinomycetemcomitans may not be defined by any single strain. Moreover, the genomic variation within each clonal lineage of A. actinomycetemcomitans (as defined by serotype grouping) may be greater than between clonal lineages. The large genomic data set in this study will be useful to further examine the molecular basis of variable virulence among A. actinomycetemcomitans strains.

Introduction

Gram-negative Aggregatibacter actinomycetemcomitans is assumed to be the primary etiologic agent of localized aggressive periodontitis [1] and has also been implicated in chronic periodontitis and severe non-oral infections [2]. The bacterium has a complex lifecycle. It is acquired through transmission from infected individuals [3], [4], and may initially colonize oral mucosa possibly as a facultative intracellular pathogen [5], [6]. The bacterium moves from the initial oral colonization site to subgingival crevices and competes with other bacteria in the niche. Successful establishment of persistent colonization in subgingival crevices by A. actinomycetemcomitans may lead to periodontal destruction and development of periodontitis in susceptible individuals [7], [8]. To initiate a new cycle, the bacterium is transmitted by saliva to a new host [4].

The virulence potential of A. actinomycetemcomitans appears to vary among strains. Specific serotypes/clonal types of A. actinomycetemcomitans have been reported to be over-represented in periodontitis [9], [10]. Subjects infected by strains of serotype b JP2 clone (defined by a 530-bp deletion in the promoter region of the leukotoxin operon) were shown to be at a higher risk of exhibiting progressing periodontal disease or developing aggressive periodontitis than by strains of “non-JP2 clones” [7], [11]. The within-species variable virulence may be attributed to strain-to-strain variation in genome content and regulation of virulence gene expressions [12], [13]. Comparative genomics of A. actinomycetemcomitans strains may yield insight to the molecular basis of such variation.

The complete genome sequence of A. actinomycetemcomitans serotype b strain HK1651 has been available since 2002 (http://www.genome.ou.edu/act.html). The genome sequences of a serotype a strain D7S-1 and serotype c strain D11S-1 were recently published by our laboratory [14], [15]. In the present study, the genome sequences of an additional 11 A. actinomycetemcomitans strains were generated de novo, and combined with the three available genome sequences for comparative genomic analysis. The protein-coding genes of the genomes were compared among strains to determine the size of the core and flexible gene pools, the pangenome, the gain/loss of putative virulence determinants, and to identify genomic islands within each strain. The results demonstrated substantial differences in genomic content that included functionally undefined genes, well-established virulence determinants and newly identified genomic islands among the 14 A. actinomycetemcomitans strains.

Results and Discussion

Genome sequencing, gene finding and annotation

Table 1 provides a summary of the 11 strains sequenced in this study as well as the three previously sequenced strains of A. actinomycetemcomitans. These strains were recovered from the subgingival plaque of non-cohabiting individuals with different periodontal disease diagnoses (periodontally healthy, gingivitis, chronic periodontitis, and aggressive periodontitis), and included a strain of JP2 clone (HK1651).

The % G+C of the genomes is in the range of 43.9–44.9 as expected for the species. Individual genomes varied in size from 2.02 to 2.38 Mb (mean±S.D: 2.17±0.12 Mb). Excluding RNA genes, individual genomes contained 2,442–2,880 protein-coding genes. The numbers of protein-coding genes represent an upper limit since they were identified by a combination of different approaches and included genes that were relatively short (100–200 bp). Also, the results included genes that may belong to plasmids or phages. Overall, the genomic variations in size or the numbers of protein-coding genes were <20% between any two strains.

The sequence quality of the 11 A. actinomycetemcomitans genomes was high (see Table S1 for detail of sequence quality). The depths of the genome sequencing were 16× to 43×. The percentage of Q39 (ie, the percentage of bases with a quality score of less than or equal to 39 which is equivalent to an error rate of approximately 1 in 10,000 bases) was less than 1% in 11 of the 12 genomes, and only 1.6% in the remaining genome.

A total of 33,626 predicted genes were found in the genomes of 14 A. actinomycetemcomitans strains and grouped into 3,338 homologous gene clusters. Gene members within each homologous gene cluster showed at least 75% DNA sequence similarity to the cluster representative sequence (the longest member) suggesting meaningful homologous gene grouping result (see Figure S1). The homologous gene clusters data used in this study can be accessed by using our online tool, which can be found at http://expression.washington.edu/genetable/script/gene_table_viewer. A more detailed description of our homologous gene grouping method as well as our web tool for browsing through the homologous gene cluster data will be presented in a separate paper.

Two approaches were employed in this study to overcome possible sequencing errors, missed sequences and fragmented genes expected in the draft genomes. First, the gene clusters were analyzed instead of the individual genes. By using this approach the split genes were recognized and assigned to the same gene clusters. Second, the representative gene sequences of each gene cluster were used to search for homologs in the genomes. To validate our approaches, we analyzed the gene prediction results using the complete genomes of strains D7S-1 and D11S-1 and the unfinished genomes (ie, contigs derived from 454 sequencing) of the strains. Using the unfinished genomes would have missed a total of three out of 5,237 genes between these strains (Table 2). Our approaches also avoided common sequencing errors involving polynucleotides. As an example we identified a sequencing error in ltxC of strain D7S-1, which missed a “T” at the end of a poly-T track at the nucleotide coordinates 601,187–601,190 (sequencing data not shown). Importantly, the gene was correctly identified in spite of the sequencing error.

thumbnail
Table 2. Comparison of gene identification in complete and draft genomes of A. actinomycetemcomitans strains D7S-1 and D11S-1.

https://doi.org/10.1371/journal.pone.0022420.t002

Phylogenetic analysis of A. actinomycetemcomitans and closely related species

The sequences of 25 housekeeping genes (a total length of 17,840 bp) (Table S2) common to Aggregatibacter actinomycetemcomitans and related species (Aggregatibacter aphrophilus, Haemophilus influenzae, Haemophilus somnus, Haemophilus ducreyi 35000HP, and Mannheimia haemolytica) were used for phylogenetic analysis. The results are shown in Figure 1. Strains of serotypes a, d, e and f (except serotype e strain SC1083) formed a group, while serotypes b and c strains formed a separate group. The serotype e strain SC1083 appeared to be equally distinct from the two major A. actinomycetemcomitans groups. To the best of our knowledge, this is the first study that used the sequences of a large number of housekeeping genes for phylogenetic analysis of major serotypes of A. actinomycetemcomitans. The results are in agreement with previous studies that used limited numbers of genetic markers or genome alignment for phylogenetic analysis of A. actinomycetemcomitans [16], [17], [18], [19]. The data suggest a major evolutionary division between the group of serotypes a, d, e and f strains and the group of serotypes b and c strains.

thumbnail
Figure 1. Phylogenetic tree of A. actinomycetemcomitans and related species based on housekeeping genes.

The phylogenetic relationships of A. actinomycetemcomitans, A. aphrophilus, Haemophilus spp. and M. haemolytica strains were examined with 25 housekeeping gene (a total length of 17,840 bp) sequences. Bootstrap values (100 replicates) are given at branch points. Bar represents substitutions per site. M. haemolytica strain PHL213 was used to root the tree. Serotype information is given for all A. actinomycetemcomitans strains. The phylogenetic tree was constructed and drawn using PHYLIP version 3.6.

https://doi.org/10.1371/journal.pone.0022420.g001

The heterogeneity within the serotype e strains of A. actinomycetemcomitans found in our study has been suggested previously. Dogan et al. [20] distinguished three groups of serotype e strains by AP-PCR typing and by sugar fermentation profiling or two genotypes based on the restriction analysis of the apaH amplification product. Also, two groups of serotype e strains of A. actinomycetemcomitans were identified (e and e′) based on 16S rRNA gene sequence similarity and amplified fragment length polymorphism typing [21]. In this study, strain SC1083 could be assigned to the serotype e′ and the strain SCC393 to the conventional serotype e group based on the signature sequences of the 16S rRNA genes described by Reijden et al. [21]. It is tempting to speculate that each subtype of serotype e strains may represent a distinct clonal lineage. Additional serotype e strains of both subtypes should be examined to verify this possibility.

Size of the core genome, flexible gene pool, and pangenome

Counting protein-coding genes only, the size of the pangenome (the total unique genes of the 14 strains) was 3,301 genes, which included 2,034 core genes (genes found in all strains) and 1,267 flexible genes (present in some but not all 14 strains). The data was used to further assess the size of the core gene pool and the pangenome by mathematical modeling (Figure 2). The core gene pool approached 2,060 genes and the addition of new strains for analysis beyond the 14 examined strains was not expected to significantly affect its size (Figure 2A). The pangenome of A. actinomycetemcomitans was found to be open-ended (Figure 2C). Sixteen new genes are estimated to be added to the pangenome for each additional strain sequenced (Figure 2B).

thumbnail
Figure 2. Analysis of pangenome and its components in A. actinomycetemcomitans.

Analysis of the size of the core genome (A) and whether the pangenome is open or closed (B and C). The number of common genes (A), new genes (B) and size of pangenome (C) are plotted as a function of the number of n of strains sequentially added. Circles show all different strain combinations for each n. Squares are the averages for each n. The continuous curve in A and B represents the least-squares fit of an exponential decay function. The extrapolated A. actinomycetemcomitans core genome size and average number of new genes are shown as dashed lines in top and middle plots respectively. Based on the curve, the core genome size is estimated to be about 2,060 genes. For every additional strain up to 16 new genes can be added to the open pangenome.

https://doi.org/10.1371/journal.pone.0022420.g002

The distribution patterns of the flexible genes (subgrouped based on the numbers of strains sharing the genes) in individual strains are illustrated in Figure S2. Within each strain 16.7–29.4% of the genome belonged to the flexible gene pool. Figure 3 shows the functional classification of core and flexible genes by COG super-functional (Figure 3A) or functional category (Figure 3B). As expected, the vast majority of genes making up the core genome belonged to the groups of housekeeping functions. As is common in most bacteria, about one-fourth of the shared genes were assigned to the category of poorly characterized proteins, suggesting that many aspects of basic A. actinomycetemcomitans biology still need to be explored. Genes associated with housekeeping functions were also found within the flexible gene pool but less well-represented there, whereas poorly characterized genes comprised the majority of the flexible pool; 951 out of 1,267 (75%) flexible genes were classified as poorly characterized (Figure 3A). One hundred and sixty-seven of the remaining 316 flexible genes (53%) are associated with mobile and extrachromosomal elements.

thumbnail
Figure 3. Classification of core and flexible genes in A. actinomycetemcomitans.

Genes were classified by the COG super-functional category (A) and the COG functional category (B). As expected, the core genome is better represented by genes that provide the essential cell function for the bacterium whereas the vast majority of the variable genome is made up of poorly characterized genes. Poorly characterized genes also represented about one third of the core genome. This suggests that more studies are still needed to understand the basic biology of this bacterial species.

https://doi.org/10.1371/journal.pone.0022420.g003

In this study the core genome of A. actinomycetemcomitans accounts for 70.6% to 83.3% of any single genome. The sizes of the core genome or the flexible gene pool of A. actinomycetemcomitans are not unusual in comparison to other bacterial species. Welch et al. [22] examined three strains of Escherichia coli and showed that less than 40% of the genomes were shared. Presumably the size of the core genome will be even smaller with additional E. coli strains included for comparison. In a study of 12 Procholorococcus isolates, the size of the core genome approached 1,250 genes, or from 40% to 67% of the genomes of individual isolates. Among Streptococcus agalactiae strains 80% of the genome of any strain was shared [23].

Genome comparison among A. actinomycetemcomitans strains

Figure 4 provides a summary of strain-to-strain comparisons of protein-coding genes of the genomes. Depending on the pair of strains compared and the direction of the comparison, the percentage of genes present in one genome but not in another ranged from 0.4% to 19.5%. Two groups of strains were recognized based on the similarity matrix. One group was formed by the strains of serotypes a, d, e (except strain SC1083) and f. The other group was formed by the strains of serotypes b and c. The serotype e strain SC1083 did not seem to follow the pattern. Two-way hierarchical clustering analysis of the flexible genes also illustrated the same patterns of two major groups and the distinctiveness of strain SC1083 (Figure 5). The segregation in the pattern of genomic variation among strains mirrored that found in phylogenetic analysis using housekeeping genes (Figure 1).

thumbnail
Figure 4. Pair-wise genomic comparisons among A. actinomycetemcomitans strains.

A heat map of the genome variation among 14 A. actinomycetemcomitans strains is shown. The numbers in the box show the % of protein-coding genes found in one genome (left) but not another. The data are organized by serotypes; a (D17P3, D7S-1, and H5P-1), d (I63B), e (SC1083), e (SCC393), f (D18P1), b (HK1651, ANH9381, SCC1398, I23C), c (D11S-1, D17P2, SCC2302). The patterns of genome similarity mirror those found in phylogenetic analysis by 16S rRNA gene sequences or 25 housekeeping genes shown in Figures 1 and 2. The numbers in parenthesis on the left of the map indicate the numbers of protein-coding genes.

https://doi.org/10.1371/journal.pone.0022420.g004

thumbnail
Figure 5. Two-way hierarchical clustering of the variable gene profiles of A. actinomycetemcomitans strains.

Columns represent A. actinomycetemcomitans genomes. Rows represent genes. Red and black color cells represent presence or absence of genes in a particular genome respectively. Clustering result shows a similar grouping of A. actinomycetemcomitans strains as phylogenetic analysis where strains from serotype a, d, e and f (excluding strain SC1083) form a group and strains from serotype b and c form another group. Image truncated for brevity.

https://doi.org/10.1371/journal.pone.0022420.g005

The natural population of A. actinomycetemcomitans is clonal, with each serotype representing a distinct clone lineage [18]. However, the extent of the genomic variation within individual clonal lineages has not previously been known. In this study multiple strains of each of the serotypes a, b, c and e were available for comparison. The strain-to-strain variations in genome content were 0.4–11.9% for serotype a strains, 10.5–16% for serotype e strains, 1.8–6.3% for serotype b strains, and 1.6–9.5% for serotype c strains (Figure 4). The variations between serotypes a and e were 1.2–19.5%, and between serotypes b and c were 3.0–12.3%. Therefore, the genomic variation within each serotype in some instances may be as great as that between serotypes, suggesting that phenotypic variation (including virulence potentials) of A. actinomycetemcomitans strains cannot be expected to comply with the serotype group.

Strain HK1651 belongs to the JP2 clone, which comprises strains marked by the 530-bp deletion of the leukotoxin promoter and are clonally identical based on multilocus enzyme analysis [24], [25], [26], [27]. The term “non-JP2 clones” has been loosely applied to all serotypes of A. actinomycetemcomitans strains that do not have the characteristic 530-bp deletion [7]. The present study has clearly demonstrated significant variation of the genome content among strains of different serotypes. Comparison of genetically restricted JP2 clone to genetically diverse “non-JP2 clones” is not informative. Here we propose that the terms “JP2” and “non-JP2” should apply only to serotype b strains for a meaningful comparison of the closely related group of bacteria with or without the particular genetic marker.

Identification of genomic islands among A. actinomycetemcomitans strains

A total of 171 genomic islands were found among the 14 A. actinomycetemcomitans strains (Table 1). Some of these islands resembled phage or plasmid sequences. Cumulatively 777 strain-specific genes were found on these islands and represented 61% of the flexible gene pool and showed similar COG distribution pattern with the flexible gene pool.

On average 26.7% of the variable genes found on the genomic islands in each genome (in comparison to 8.5% of the core genes) displayed atypical nucleotide composition of at least two standard deviations from the mean values in one of three base composition values (%G+C, genome signature and codon bias) [28] (see Table S3 for the list of genomic islands, genes and base composition analysis). Evidently nearly all genomic islands identified in this study were novel. The functions of these islands remain to be elucidated.

The occurrence of each genomic island among the 14 strains is provided in Table S4. On average each of the 171 islands was found in 3.1 strains. Only one island was found to occur in more than 10 strains. While the presence of the “strain-specific regions” in the genomes can be interpreted as genomic islands, or alternatively as deletions (in the strains that do not have the “strain-specific regions”), the latter could be ruled out based on the distribution patterns of these islands among strains. It is less likely that a majority of the A. actinomycetemcomitans strains would have independently suffered a deletion in identical genomic regions.

Genomic islands may be identified by base composition analysis as well as by phylogenetic approaches [29]. No single method is considered optimal or universally accepted as the best approach for identification of genomic islands. For example, base composition analysis may not identify ancient genomic islands due to amelioration of the horizontally acquired genes over time [30]. In this study, comparative genomics has the advantage of directly identifying strain-specific DNA regions as putative genomic islands. Prior to this study, there was limited information about the genomic islands of A. actinomycetemcomitans. Eight genomic islands have been identified in strain HK1651 (http://www.oralgen.lanl.gov/_index.html), including four islands also identified independently in this study. Among the remaining four islands three were species-specific genomic islands (ie, present in all examined strains; the islands of tight adherence gene cluster, leukotoxin gene cluster and LOS biosynthesis enzyme) and one was too small (cytolethal distending toxin gene cluster, <5 kb) to be categorized as a genomic island in this study. Finally, this study also identified 32 DNA regions that have many features of genomic islands (Table S5). For example, each has one or more flexible genes with atypical base compositions characterized by 1 standard deviation from the mean values, and carries mobile elements and genes encoding phage proteins.

Variable presence of virulence determinants in A. actinomycetemcomitans strains

It is known that the ∼2.4 kb cdtABC operon of A. actinomycetemcomitans resides on a genomic island [31]. In this study a homologous ∼14 kb cdtABC-carrying genomic island (here designated as cdt-island) was identified in five A. actinomycetemcomitans strains based on its presence in a finished genome or its clear delineation within single contigs of the unfinished genomes. These strains were serotype a strains D7S-1 and D17P3, serotype d strain I63B, serotype e strain SCC393, and serotype f strain D18P1. The presence of the cdt-island in serotype a strain H5P1 was undefined because it was distributed in three different contigs. While the cdtABC operon was also found in the serotype b and c strains in this study, no apparent genomic island was associated with the operon. Instead, a ∼5 kb homologous region that carried the ∼2.4 kb cdt operon was found among the serotype b and serotype c strains.

The ∼14 kb cdt-islands identified in this study were different from a previously reported genomic island (designated GIY4-1) of cdtABC operon [31] in a serotype b strain Y4. Sequence analyses of these two types of genomic islands showed a ∼4 kb region of sequence homology that included the ∼2.5 kb cdtABC and its upstream 1.3 kb region.

Interestingly, the ∼14 kb cdt-island (and the cdtABC) was either not acquired by strain SC1083 or was deleted from the strain during its evolution. The evidence is shown in the comparison of the locus between SC1083 and D7S-1 (Figure 6) (see Figure S3 for sequence confirmation). The flanking regions of the cdt-island in D7S-1 were found as a single contiguous DNA region in SC1083 without the island. Notably a Gly-tRNA gene was identified in both strains. Genomic islands are often associated with tRNA genes, which may serve as a preferred integration sites [32], [33]. The results also suggest that the cdt-island was acquired en bloc in some A. actinomycetemcomitans strains.

thumbnail
Figure 6. Genetic comparison between A. actinomycetemcomitans strains with or without the cdt-island.

Comparison of the genetic locus of the cdt-island in strain D7S-1 and the comparable locus in strain SC1083. The homologous sulfatase and Gly-rRNA between strains are colored in dark blue and red, respectively. Several genes encoding hypothetical proteins and other proteins in the cdt-island of strain D7S-1 are not indicated in the map (see Table S3 for a full list of genes on the island). The comparison shows that strain SC1083 is missing the ∼14 kb cdt-island.

https://doi.org/10.1371/journal.pone.0022420.g006

A putative virulence factor CagE [34], [35] (designated as p-cluster 03282 in this study) was found only in two serotype b strains HK1651 (JP2 clone) and SCC2302. The significance of the presence or absence of CagE to the virulence of A. actinomycetemcomitans strains remains to be examined.

A. actinomycetemcomitans strains are known to exhibit variation in natural competence for DNA uptake. Naturally competent A. actinomycetemcomitans strains were identified in serotypes a, d and e but not in serotypes b or c [36]. One possible reason for the lack of detectable natural competence is a common insertional inactivation of a comM gene in strains of serotypes b and c [37]. In this study we found that all serotype a strains (D7S-1, D17P3, and H5P1) and the serotype e strain SCC393 had an intact full-length comM gene. In contrast, the comM of serotype b and c strains (HK1651, ANH9381, SCC1398, SCC2302, D11S-1, D17P-2), and the serotype e strain SC1083 and serotype f strain D18P-1, were apparently inactivated by the insertion of a genomic island (∼14–25 kb) that showed significant homology among strains. The results again suggest that the insertional inactivation of comM gene occurred in some clonal lineages of A. actinomycetemcomitans. The significance of such insertional event in the evolution of A. actinomycetemcomitans remains to be investigated.

Genome comparison between A. actinomycetemcomitans and Aggregatibacter aphrophilus

A. aphrophilus is closely related to A. actinomycetemcomitans. While both species belong to the HACEK group that is often associated with nonoral infections, the former is not considered a periodontal pathogen. A preliminary comparative genomic analysis was performed to examine the presence of known virulence determinants of A. actinomycetemcomitans in the genomes of A. aphrophilus. The homologs of fimbrial gene cluster [38], [39], aae [40] and emaA [41] were found in both A. aphrophilus and A. actinomycetemcomitans. However, leukotoxin operon, cdtABC operon or kat (for catalase) [42] were found in A. actinomycetemcomitans (except in strain SC1083 which does not have cdtABC) but not A. aphrophilus. It is premature to conclude that the presence or absence of these virulence determinants accounts for the distinctions in their periodontal virulence potentials. Nevertheless, comparative genomics of closely related oral haemophili may be a valid approach to examine the etiopathogenesis of A. actinomycetemcomitans-associated periodontal disease.

Finally, the strain-dependent genomic differences have implications in applications such as microarray design for A. actinomycetemcomitans. With such genomic variation, a microarray created based on the genome content of a single strain will not provide comprehensive information if applied to a strain, or strains with significant differences in genome content. We have applied the information obtained in this study and designed a pangenome microarray for A. actinomycetemcomitans (accessible through https://earray.chem.agilent.com/earray/ under “Published Designs” by species “Na”. or alternatively, https://earray.chem.agilent.com/earray/showPublishPageForLogin.do?action=showPublishResultsForLoginPage&species=Na under “aa_array.100315”), and successfully tested on clinical isolates for genome content analysis and for transcriptome analysis (manuscripts in preparation).

Materials and Methods

Bacteria and genome sequences

Eleven clinical strains of A. actinomycetemcomitans (2, 3, 2, 1, 2, 1 strains of serotypes a, b, c, d, e, and f, respectively) were selected for whole genome sequencing. These strains were cultivated from subgingival plaque of 11 noncohabiting individuals with different periodontal disease diagnoses. All strains were verified as A. actinomycetemcomitans by a 16S rDNA-based PCR assay and their serotypes were determined as described previously [36], [43], [44], [45]. A. aphrophilus ATCC 33389 (purchased from ATCC) was also sequenced. The genome sequencing was performed using 454 pyrosequencing technology [46] and run on a Genome Sequencer FLX Instrument (Software 1.0.53) following the manufacturer's instruction (Hoffmann-La Roche Ltd). The raw data were assembled using the Newbler Assembler Software (Genome Sequencer 20, Version 1.0.53), with default parameters. The Newbler Metrics of 454 sequencing and Genbank accession numbers are provided in Table S1. The Genbank accession numbers are; ADOA00000000 (D17P-3), AEJK00000000 (H5P1), ADOC00000000 (ANH9381), AEJQ00000000 (i23C), AEJP00000000 (SCC1398), AEJR00000000 (SCC2302), ADOB00000000 (D17P-2), AEJL00000000 (I63B), AEJN00000000 (SCC393), AEJM00000000 (SC1083), AEJO00000000 (D18P-1) and AEWB00000000 (A. aphrophilus ATCC 33389).

Gene prediction and annotation

In addition to the 11 A. actinomycetemcomitans strains sequenced in this study, the genome sequences of three previously sequenced A. actinomycetemcomitans strains [14], [15] (http://www.genome.ou.edu/act.html), A. aphrophilus strain NJ 8700 [47] and ATCC 33389 were included in the analysis. The sequences were processed by our in-house pipeline for gene prediction and annotation as described previously [14], [15]. Briefly, Glimmer3 [48], Exonerate [49], and tRNAscan SE tools [50] were used to predict protein-, rRNA- and tRNA-coding genes, respectively. All protein-coding genes were annotated by BLAST searching against Genbank non-redundant protein sequence database (Blastp with E-Value cutoff of 1e-6). The description of the best BLAST hit was then used as an annotation for that gene. Each protein sequence was also BLAST searched against the Clusters of Orthologous Groups of proteins (COGs) database [51] and a COG identification number was assigned to each gene if the best BlastP hit exhibits at least 80% sequence coverage in both query and hit sequences and at least 30% protein sequence identity. Because our genome sequence data were produced using the 454 pyrosequencing technology, which tends to produce insertion/deletion (indel) nucleotide polymorphism in homopolymer stretches, protein-coding genes were further analyzed to identify putative frameshift mutations using BLAST Extend-Repraze (http://ber.sourceforge.net/). Additionally, BLAST hits of each protein-coding gene were analyzed to identify cases where indels in homopolymer stretch have caused a potentially correct stop codon to be out of frame and created a predicted gene that was a fusion between two genes, which was then corrected manually.

Identification and grouping of homologous genes

In order to analyze genes across multiple genomes, we created a method to identify and group genes that were homologous to one another. Initially, each gene from all genomes was treated as an independent gene cluster (defined as a collection of homologous genes) of one gene. The number of gene clusters at this initial step was therefore equal to the total number of predicted genes from all genomes. A representative gene sequence of each cluster, which we defined as the longest member, was then used to search all genomes to identify other homologous genes. Four different modes of sequence comparison were employed for identification of homologous genes (ie, belonging to the same gene clusters): (i) comparison of a representative gene DNA sequence to all gene DNA sequences database using BlastN, (ii) comparison of a representative gene DNA sequence to all genome sequences database using BlastN, (iii) comparison of a representative Protein sequence to all gene Protein sequences database using BlastP, (iv) comparison of a representative Protein sequence to all translated genome Protein sequences database using TBlastN.

For i) and iii), significant BLAST hits that had e-values of less than 1e-6 and exhibited at least 50% sequence identity and 50% sequence coverage between query and hit sequences were considered homologous to the query representative sequence. Similarly, for ii) and iv), significant BLAST hits that showed at least 50% sequence identity and 50% sequence coverage between the query representative sequence and the sequence in the genome were considered homologous. Any genes found within these homologous genomic regions were automatically considered as homologs to the query representative sequence. This representative gene versus genome sequence comparisons allowed us to identify and group genes that may have been predicted inconsistently in different genomes due to factors such as differences in sequence quality (especially near the ends of a contig), frameshift mutations, and the incomplete nature of genome sequences. Specifically, these factors could cause a gene prediction program to call fragmented genes instead of a full length version or a significantly shorter gene relative to homologs found in other genomes. Genes that showed homology to the representative sequence by any of the four comparison modes were then removed from their clusters and added to the cluster that was the origin of the representative sequence. For ii) and iv), if a homologous genomic region was found but no gene was predicted in that region, a note for that particular genome was added to the cluster. This allowed us to differentiate a true missing gene from an artifact in gene prediction result. This homologous gene grouping process was iterated for all non-empty clusters until no change was found in the gene cluster membership after a whole round of comparison had been carried out. Finally, manual inspection was performed to further group genes that are obviously homologous but were not grouped together by our criteria.

Phylogenetic analysis

Twenty-five housekeeping genes, most of which coded for 30S and 50S ribosomal subunit proteins (see Table S2), common to 14 A. actinomycetemcomitans strains, two A. aphrophilus strains, and Haemophilus influenzae 028NP, H. influenzae Rd, H. influenzae PittGG, H. influenzae PittEE, Haemophilus somnus 129PT, H. somnus 2336, Haemophilus ducreyi 35000HP, and Mannheimia haemolytica PHL213, were selected for analysis. The nucleotide sequences of individual genes were aligned using ClustalW version 2 with default parameters [52]. Gaps were removed from all alignment results, which in turn were concatenated to produce a single alignment (a total length of 17,840 bp) in PHYLIP format. PHYLIP program version 3.6 was used to construct the tree using the maximum likelihood method (dnaml) (http://evolution.genetics.washington.edu/phylip/getme.html) [53]. A bootstrap analysis was carried out to test the reliability of the tree. Finally the DRAWGRAM software (part of the PHYLIP package) was used to draw the tree.

Identification of genomic islands

Initially, three different base composition analyses: namely, G+C content, dinucleotide bias (also known as genomic signature), and codon bias were performed for predicted genes in each genome. The methods established by Karlin [47] were used to calculate the dinucleotide and codon bias values for each coding sequence. The mean and standard deviation for each of these base composition values were calculated. Genomic islands of at least 5 kb in length were then identified by a step-wise process. First, regions of at least 1 kb containing a gene not shared by all strains were identified. The variable regions were then merged if they were within 5 kb of each other. Finally, the resulting regions of at least 5 kb that contain at least one gene that displays atypical base composition (as characterized by at least 2 standard deviations in any of the three base composition values) were considered as genomic islands.

Estimation of the size of the core genome and the pangenome of 14 A. actinomycetemcomitans strains

The core genome and the pangenome were estimated based on a method described by Tettelin et al. [23]. In brief, all possible combinations of sequential inclusion of up to 14 strains were simulated and a regression analysis was used to fit an exponential decaying function to the amount of conserved genes and of strain-specific genes. This allowed us to estimate and extrapolate the size of the core genome and the pangenome if additional A. actinomycetemcomitans strains were available for genome sequencing and analysis.

Supporting Information

Figure S1.

DNA sequence similarity within gene clusters. Histogram shows the distribution of percent DNA sequence similarity between genes and their corresponding gene cluster representatives. Seventy-six percent of the genes showed 95–100% sequence similarity to their cluster representative sequences. No genes showed less than 75% DNA sequence similarity to their cluster representatives.

https://doi.org/10.1371/journal.pone.0022420.s001

(DOCX)

Figure S2.

Distribution patterns of core and flexible genes in A. actinomycetemcomitans strains. This figure shows cumulative percentage of genes (y-axis) that are found in different number of the 14 A. actinomycetemcomitans genomes studied. The genes are color coded based on the numbers of genomes that share the genes (see right side of the figure for the color coding). This analysis shows that about 20% or less of the genes in each A. actinomycetemcomitans genome constitute a variable gene pool.

https://doi.org/10.1371/journal.pone.0022420.s002

(DOCX)

Figure S3.

Sequence confirmation of the deletion of cdt-island in strain SC1083. See Figure 6 for the genetic map. Two primers (underlined) annealing to sulfatase and Gly-tRNA were used to amplify a 660 bp DNA fragment for sequencing. The result is identical to the sequencing information of SC1083 from pyrosequencing. The intergenic region is indicated with lower case letters, and the ends of the flanking genes indicated by the upper case letters.

https://doi.org/10.1371/journal.pone.0022420.s003

(DOCX)

Table S1.

Newbler Metrics of 454 sequencing of 11 A. actinomycetemcomitans strains and the A. aphrophilus strain ATCC 33389.

https://doi.org/10.1371/journal.pone.0022420.s004

(DOCX)

Table S2.

List of genes of A. actinomycetemcomitans for phylogenetic analysis.

https://doi.org/10.1371/journal.pone.0022420.s005

(DOCX)

Table S3.

List of genomic islands and their gene content in A. actinomycetemcomitans strains.

https://doi.org/10.1371/journal.pone.0022420.s006

(XLSX)

Table S4.

The distribution of individual genomic islands among A. actinomycetemcomitans strains.

https://doi.org/10.1371/journal.pone.0022420.s007

(XLSX)

Table S5.

Additional DNA regions with atypical base composition among A. actinomycetemcomitans strains.

https://doi.org/10.1371/journal.pone.0022420.s008

(XLSX)

Author Contributions

Conceived and designed the experiments: RB SA CC. Performed the experiments: WK RB CC. Analyzed the data: WK RB CC. Contributed reagents/materials/analysis tools: WK RB SA CC. Wrote the paper: WK CC.

References

  1. 1. Slots J, Ting M (1999) Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis in human periodontal disease: occurrence and treatment. Periodontol 2000 20: 82–121.J. SlotsM. Ting1999Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis in human periodontal disease: occurrence and treatment.Periodontol 20002082121
  2. 2. van Winkelhoff AJ, Slots J (1999) Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis in nonoral infections. Periodontol 2000 20: 122–135.AJ van WinkelhoffJ. Slots1999Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis in nonoral infections.Periodontol 200020122135
  3. 3. Asikainen S, Chen C, Slots J (1996) Likelihood of transmitting Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis in families with periodontitis. Oral Microbiol Immunol 11: 387–394.S. AsikainenC. ChenJ. Slots1996Likelihood of transmitting Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis in families with periodontitis.Oral Microbiol Immunol11387394
  4. 4. Asikainen S, Chen C (1999) Oral ecology and person-to-person transmission of Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis. Periodontol 2000 20: 65–81.S. AsikainenC. Chen1999Oral ecology and person-to-person transmission of Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis.Periodontol 2000206581
  5. 5. Yue G, Kaplan JB, Furgang D, Mansfield KG, Fine DH (2007) A second Aggregatibacter actinomycetemcomitans autotransporter adhesin exhibits specificity for buccal epithelial cells in humans and Old World primates. Infect Immun 75: 4440–4448.G. YueJB KaplanD. FurgangKG MansfieldDH Fine2007A second Aggregatibacter actinomycetemcomitans autotransporter adhesin exhibits specificity for buccal epithelial cells in humans and Old World primates.Infect Immun7544404448
  6. 6. Rudney JD, Chen R, Sedgewick GJ (2005) Actinobacillus actinomycetemcomitans, Porphyromonas gingivalis, and Tannerella forsythensis are components of a polymicrobial intracellular flora within human buccal cells. J Dent Res 84: 59–63.JD RudneyR. ChenGJ Sedgewick2005Actinobacillus actinomycetemcomitans, Porphyromonas gingivalis, and Tannerella forsythensis are components of a polymicrobial intracellular flora within human buccal cells.J Dent Res845963
  7. 7. Haubek D, Ennibi OK, Poulsen K, Vaeth M, Poulsen S, et al. (2008) Risk of aggressive periodontitis in adolescent carriers of the JP2 clone of Aggregatibacter (Actinobacillus) actinomycetemcomitans in Morocco: a prospective longitudinal cohort study. Lancet 371: 237–242.D. HaubekOK EnnibiK. PoulsenM. VaethS. Poulsen2008Risk of aggressive periodontitis in adolescent carriers of the JP2 clone of Aggregatibacter (Actinobacillus) actinomycetemcomitans in Morocco: a prospective longitudinal cohort study.Lancet371237242
  8. 8. Fine DH, Markowitz K, Furgang D, Fairlie K, Ferrandiz J, et al. (2007) Aggregatibacter actinomycetemcomitans and its relationship to initiation of localized aggressive periodontitis: longitudinal cohort study of initially healthy adolescents. J Clin Microbiol 45: 3859–3869.DH FineK. MarkowitzD. FurgangK. FairlieJ. Ferrandiz2007Aggregatibacter actinomycetemcomitans and its relationship to initiation of localized aggressive periodontitis: longitudinal cohort study of initially healthy adolescents.J Clin Microbiol4538593869
  9. 9. Asikainen S, Chen C, Saarela M, Saxen L, Slots J (1997) Clonal specificity of Actinobacillus actinomycetemcomitans in destructive periodontal disease. Clin Infect Dis 25: Suppl 2S227–229.S. AsikainenC. ChenM. SaarelaL. SaxenJ. Slots1997Clonal specificity of Actinobacillus actinomycetemcomitans in destructive periodontal disease.Clin Infect Dis25Suppl 2S227229
  10. 10. Asikainen S, Chen C, Slots J (1995) Actinobacillus actinomycetemcomitans genotypes in relation to serotypes and periodontal status. Oral Microbiol Immunol 10: 65–68.S. AsikainenC. ChenJ. Slots1995Actinobacillus actinomycetemcomitans genotypes in relation to serotypes and periodontal status.Oral Microbiol Immunol106568
  11. 11. DiRienzo JM, Slots J, Sixou M, Sol MA, Harmon R, et al. (1994) Specific genetic variants of Actinobacillus actinomycetemcomitans correlate with disease and health in a regional population of families with localized juvenile periodontitis. Infect Immun 62: 3058–3065.JM DiRienzoJ. SlotsM. SixouMA SolR. Harmon1994Specific genetic variants of Actinobacillus actinomycetemcomitans correlate with disease and health in a regional population of families with localized juvenile periodontitis.Infect Immun6230583065
  12. 12. Hacker J, Hentschel U, Dobrindt U (2003) Prokaryotic chromosomes and disease. Science 301: 790–793.J. HackerU. HentschelU. Dobrindt2003Prokaryotic chromosomes and disease.Science301790793
  13. 13. Maurelli AT, Fernandez RE, Bloch CA, Rode CK, Fasano A (1998) “Black holes” and bacterial pathogenicity: A large genomic deletion that enhances the virulence of Shigella spp. and enteroinvasive Escherichia coli. Proc Natl Acad Sci U S A 95: 3943–3948.AT MaurelliRE FernandezCA BlochCK RodeA. Fasano1998“Black holes” and bacterial pathogenicity: A large genomic deletion that enhances the virulence of Shigella spp. and enteroinvasive Escherichia coli.Proc Natl Acad Sci U S A9539433948
  14. 14. Chen C, Kittichotirat W, Chen W, Downey JS, Si Y, et al. (2010) Genome sequence of a naturally competent Aggregatibacter actinomycetemcomitans serotype a strain D7S-1. J Bacteriol 192: 2643–2644.C. ChenW. KittichotiratW. ChenJS DowneyY. Si2010Genome sequence of a naturally competent Aggregatibacter actinomycetemcomitans serotype a strain D7S-1.J Bacteriol19226432644
  15. 15. Chen C, Kittichotirat W, Si Y, Bumgarner R (2009) Genome sequence of Aggregatibacter actinomycetemcomitans serotype c strain D11S-1. J Bacteriol 191: 7378–7379.C. ChenW. KittichotiratY. SiR. Bumgarner2009Genome sequence of Aggregatibacter actinomycetemcomitans serotype c strain D11S-1.J Bacteriol19173787379
  16. 16. Poulsen K, Theilade E, Lally ET, Demuth DR, Kilian M (1994) Population structure of Actinobacillus actinomycetemcomitans: a framework for studies of disease-associated properties. Microbiology 140: 2049–2060.K. PoulsenE. TheiladeET LallyDR DemuthM. Kilian1994Population structure of Actinobacillus actinomycetemcomitans: a framework for studies of disease-associated properties.Microbiology14020492060
  17. 17. Kaplan JB, Schreiner HC, Furgang D, Fine DH (2002) Population structure and genetic diversity of Actinobacillus actinomycetemcomitans strains isolated from localized juvenile periodontitis patients. J Clin Microbiol 40: 1181–1187.JB KaplanHC SchreinerD. FurgangDH Fine2002Population structure and genetic diversity of Actinobacillus actinomycetemcomitans strains isolated from localized juvenile periodontitis patients.J Clin Microbiol4011811187
  18. 18. Kilian M, Frandsen EV, Haubek D, Poulsen K (2006) The etiology of periodontal disease revisited by population genetic analysis. Periodontol 2000 42: 158–179.M. KilianEV FrandsenD. HaubekK. Poulsen2006The etiology of periodontal disease revisited by population genetic analysis.Periodontol 200042158179
  19. 19. Kittichotirat W, Bumgarner R, Chen C (2010) Markedly different genome arrangements between serotype a strains and serotypes b or c strains of Aggregatibacter actinomycetemcomitans. BMC Genomics 11: 489.W. KittichotiratR. BumgarnerC. Chen2010Markedly different genome arrangements between serotype a strains and serotypes b or c strains of Aggregatibacter actinomycetemcomitans.BMC Genomics11489
  20. 20. Dogan B, Saarela MH, Jousimies-Somer H, Alaluusua S, Asikainen S (1999) Actinobacillus actinomycetemcomitans serotype e–biotypes, genetic diversity and distribution in relation to periodontal status. Oral Microbiol Immunol 14: 98–103.B. DoganMH SaarelaH. Jousimies-SomerS. AlaluusuaS. Asikainen1999Actinobacillus actinomycetemcomitans serotype e–biotypes, genetic diversity and distribution in relation to periodontal status.Oral Microbiol Immunol1498103
  21. 21. van der Reijden WA, Brunner J, Bosch-Tijhof CJ, van Trappen S, Rijnsburger MC, et al. (2010) Phylogenetic variation of Aggregatibacter actinomycetemcomitans serotype e reveals an aberrant distinct evolutionary stable lineage. Infect Genet Evol 10: 1124–1131.WA van der ReijdenJ. BrunnerCJ Bosch-TijhofS. van TrappenMC Rijnsburger2010Phylogenetic variation of Aggregatibacter actinomycetemcomitans serotype e reveals an aberrant distinct evolutionary stable lineage.Infect Genet Evol1011241131
  22. 22. Welch RA, Burland V, Plunkett G 3rd, Redford P, Roesch P, et al. (2002) Extensive mosaic structure revealed by the complete genome sequence of uropathogenic Escherichia coli. Proc Natl Acad Sci U S A 99: 17020–17024.RA WelchV. BurlandG. Plunkett 3rdP. RedfordP. Roesch2002Extensive mosaic structure revealed by the complete genome sequence of uropathogenic Escherichia coli.Proc Natl Acad Sci U S A991702017024
  23. 23. Tettelin H, Masignani V, Cieslewicz MJ, Donati C, Medini D, et al. (2005) Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial “pan-genome”. Proc Natl Acad Sci U S A 102: 13950–13955.H. TettelinV. MasignaniMJ CieslewiczC. DonatiD. Medini2005Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial “pan-genome”.Proc Natl Acad Sci U S A1021395013955
  24. 24. Haubek D, Dirienzo JM, Tinoco EM, Westergaard J, Lopez NJ, et al. (1997) Racial tropism of a highly toxic clone of Actinobacillus actinomycetemcomitans associated with juvenile periodontitis. J Clin Microbiol 35: 3037–3042.D. HaubekJM DirienzoEM TinocoJ. WestergaardNJ Lopez1997Racial tropism of a highly toxic clone of Actinobacillus actinomycetemcomitans associated with juvenile periodontitis.J Clin Microbiol3530373042
  25. 25. Brogan JM, Lally ET, Poulsen K, Kilian M, Demuth DR (1994) Regulation of Actinobacillus actinomycetemcomitans leukotoxin expression: analysis of the promoter regions of leukotoxic and minimally leukotoxic strains. Infect Immun 62: 501–508.JM BroganET LallyK. PoulsenM. KilianDR Demuth1994Regulation of Actinobacillus actinomycetemcomitans leukotoxin expression: analysis of the promoter regions of leukotoxic and minimally leukotoxic strains.Infect Immun62501508
  26. 26. Haubek D, Poulsen K, Westergaard J, Dahlen G, Kilian M (1996) Highly toxic clone of Actinobacillus actinomycetemcomitans in geographically widespread cases of juvenile periodontitis in adolescents of African origin. J Clinic Microbiol 34: 1576–1578.D. HaubekK. PoulsenJ. WestergaardG. DahlenM. Kilian1996Highly toxic clone of Actinobacillus actinomycetemcomitans in geographically widespread cases of juvenile periodontitis in adolescents of African origin.J Clinic Microbiol3415761578
  27. 27. Haubek D, Poulsen K, Kilian M (2007) Microevolution and patterns of dissemination of the JP2 clone of Aggregatibacter (Actinobacillus) actinomycetemcomitans. Infect Immun 75: 3080–3088.D. HaubekK. PoulsenM. Kilian2007Microevolution and patterns of dissemination of the JP2 clone of Aggregatibacter (Actinobacillus) actinomycetemcomitans.Infect Immun7530803088
  28. 28. Karlin S (2001) Detecting anomalous gene clusters and pathogenicity islands in diverse bacterial genomes. Trends Microbiol 9: 335–343.S. Karlin2001Detecting anomalous gene clusters and pathogenicity islands in diverse bacterial genomes.Trends Microbiol9335343
  29. 29. Eisen JA (2000) Horizontal gene transfer among microbial genomes: new insights from complete genome analysis. Curr Opin Genet Dev 10: 606–611.JA Eisen2000Horizontal gene transfer among microbial genomes: new insights from complete genome analysis.Curr Opin Genet Dev10606611
  30. 30. Lawrence JG, Ochman H (1997) Amelioration of bacterial genomes: rates of change and exchange. J Mol Evol 44: 383–397.JG LawrenceH. Ochman1997Amelioration of bacterial genomes: rates of change and exchange.J Mol Evol44383397
  31. 31. Doungudomdacha S, Volgina A, DiRienzo JM (2007) Evidence that the cytolethal distending toxin locus was once part of a genomic island in the periodontal pathogen Aggregatibacter (Actinobacillus) actinomycetemcomitans strain Y4. J Med Microbiol 56: 1519–1527.S. DoungudomdachaA. VolginaJM DiRienzo2007Evidence that the cytolethal distending toxin locus was once part of a genomic island in the periodontal pathogen Aggregatibacter (Actinobacillus) actinomycetemcomitans strain Y4.J Med Microbiol5615191527
  32. 32. Hacker J, Blum-Oehler G, Muhldorfer I, Tschape H (1997) Pathogenicity islands of virulent bacteria: structure, function and impact on microbial evolution. Mol Microbiol 23: 1089–1097.J. HackerG. Blum-OehlerI. MuhldorferH. Tschape1997Pathogenicity islands of virulent bacteria: structure, function and impact on microbial evolution.Mol Microbiol2310891097
  33. 33. Hacker J, Carniel E (2001) Ecological fitness, genomic islands and bacterial pathogenicity. A Darwinian view of the evolution of microbes. EMBO Rep 2: 376–381.J. HackerE. Carniel2001Ecological fitness, genomic islands and bacterial pathogenicity. A Darwinian view of the evolution of microbes.EMBO Rep2376381
  34. 34. Teng YT, Zhang X (2005) Apoptotic activity and sub-cellular localization of a T4SS-associated CagE-homologue in Actinobacillus actinomycetemcomitans. Microb Pathog 38: 125–132.YT TengX. Zhang2005Apoptotic activity and sub-cellular localization of a T4SS-associated CagE-homologue in Actinobacillus actinomycetemcomitans.Microb Pathog38125132
  35. 35. Teng YT, Hu W (2003) Expression cloning of a periodontitis-associated apoptotic effector, cagE homologue, in Actinobacillus actinomycetemcomitans. Biochem Biophys Res Commun 303: 1086–1094.YT TengW. Hu2003Expression cloning of a periodontitis-associated apoptotic effector, cagE homologue, in Actinobacillus actinomycetemcomitans.Biochem Biophys Res Commun30310861094
  36. 36. Fujise O, Lakio L, Wang Y, Asikainen S, Chen C (2004) Clonal distribution of natural competence in Actinobacillus actinomycetemcomitans. Oral Microbiol Immunol 19: 340–342.O. FujiseL. LakioY. WangS. AsikainenC. Chen2004Clonal distribution of natural competence in Actinobacillus actinomycetemcomitans.Oral Microbiol Immunol19340342
  37. 37. Mena J, Chen C (2007) Identification of strain-specific DNA of Actinobacillus actinomycetemcomitans by representational difference analysis. Oral Microbiol Immunol 22: 429–432.J. MenaC. Chen2007Identification of strain-specific DNA of Actinobacillus actinomycetemcomitans by representational difference analysis.Oral Microbiol Immunol22429432
  38. 38. Planet PJ, Kachlany SC, Fine DH, DeSalle R, Figurski DH (2003) The Widespread Colonization Island of Actinobacillus actinomycetemcomitans. Nat Genet 34: 193–198.PJ PlanetSC KachlanyDH FineR. DeSalleDH Figurski2003The Widespread Colonization Island of Actinobacillus actinomycetemcomitans.Nat Genet34193198
  39. 39. Kachlany SC, Planet PJ, Bhattacharjee MK, Kollia E, DeSalle R, et al. (2000) Nonspecific adherence by Actinobacillus actinomycetemcomitans requires genes widespread in Bacteria and Archaea. J Bacteriol 182: 6169–6176.SC KachlanyPJ PlanetMK BhattacharjeeE. KolliaR. DeSalle2000Nonspecific adherence by Actinobacillus actinomycetemcomitans requires genes widespread in Bacteria and Archaea.J Bacteriol18261696176
  40. 40. Fine DH, Velliyagounder K, Furgang D, Kaplan JB (2005) The Actinobacillus actinomycetemcomitans autotransporter adhesin Aae exhibits specificity for buccal epithelial cells from humans and old world primates. Infect Immun 73: 1947–1953.DH FineK. VelliyagounderD. FurgangJB Kaplan2005The Actinobacillus actinomycetemcomitans autotransporter adhesin Aae exhibits specificity for buccal epithelial cells from humans and old world primates.Infect Immun7319471953
  41. 41. Mintz KP (2004) Identification of an extracellular matrix protein adhesin, EmaA, which mediates the adhesion of Actinobacillus actinomycetemcomitans to collagen. Microbiology 150: 2677–2688.KP Mintz2004Identification of an extracellular matrix protein adhesin, EmaA, which mediates the adhesion of Actinobacillus actinomycetemcomitans to collagen.Microbiology15026772688
  42. 42. Thomson VJ, Bhattacharjee MK, Fine DH, Derbyshire KM, Figurski DH (1999) Direct selection of IS903 transposon insertions by use of a broad-host-range vector: isolation of catalase-deficient mutants of Actinobacillus actinomycetemcomitans. J Bacteriol 181: 7298–7307.VJ ThomsonMK BhattacharjeeDH FineKM DerbyshireDH Figurski1999Direct selection of IS903 transposon insertions by use of a broad-host-range vector: isolation of catalase-deficient mutants of Actinobacillus actinomycetemcomitans.J Bacteriol18172987307
  43. 43. Chen C, Wang T, Chen W (2010) Occurrence of Aggregatibacter actinomycetemcomitans serotypes in subgingival plaque from United States subjects. Mol Oral Microbiol 25: 207–214.C. ChenT. WangW. Chen2010Occurrence of Aggregatibacter actinomycetemcomitans serotypes in subgingival plaque from United States subjects.Mol Oral Microbiol25207214
  44. 44. Suzuki N, Nakano Y, Yoshida Y, Ikeda D, Koga T (2001) Identification of Actinobacillus actinomycetemcomitans serotypes by multiplex PCR. J Clin Microbiol 39: 2002–2005.N. SuzukiY. NakanoY. YoshidaD. IkedaT. Koga2001Identification of Actinobacillus actinomycetemcomitans serotypes by multiplex PCR.J Clin Microbiol3920022005
  45. 45. Kaplan JB, Perry MB, MacLean LL, Furgang D, Wilson ME, et al. (2001) Structural and genetic analyses of O polysaccharide from Actinobacillus actinomycetemcomitans serotype f. Infect Immun 69: 5375–5384.JB KaplanMB PerryLL MacLeanD. FurgangME Wilson2001Structural and genetic analyses of O polysaccharide from Actinobacillus actinomycetemcomitans serotype f.Infect Immun6953755384
  46. 46. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, et al. (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437: 376–380.M. MarguliesM. EgholmWE AltmanS. AttiyaJS Bader2005Genome sequencing in microfabricated high-density picolitre reactors.Nature437376380
  47. 47. Di Bonaventura MP, DeSalle R, Pop M, Nagarajan N, Figurski DH, et al. (2009) Complete genome sequence of Aggregatibacter (Haemophilus) aphrophilus NJ8700. J Bacteriol 191: 4693–4694.MP Di BonaventuraR. DeSalleM. PopN. NagarajanDH Figurski2009Complete genome sequence of Aggregatibacter (Haemophilus) aphrophilus NJ8700.J Bacteriol19146934694
  48. 48. Delcher AL, Bratke KA, Powers EC, Salzberg SL (2007) Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics 23: 673–679.AL DelcherKA BratkeEC PowersSL Salzberg2007Identifying bacterial genes and endosymbiont DNA with Glimmer.Bioinformatics23673679
  49. 49. Slater GS, Birney E (2005) Automated generation of heuristics for biological sequence comparison. BMC Bioinformatics 6: 31.GS SlaterE. Birney2005Automated generation of heuristics for biological sequence comparison.BMC Bioinformatics631
  50. 50. Lowe TM, Eddy SR (1997) tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 25: 955–964.TM LoweSR Eddy1997tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence.Nucleic Acids Res25955964
  51. 51. Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B, et al. (2003) The COG database: an updated version includes eukaryotes. BMC Bioinformatics 4: 41.RL TatusovND FedorovaJD JacksonAR JacobsB. Kiryutin2003The COG database: an updated version includes eukaryotes.BMC Bioinformatics441
  52. 52. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, et al. (2007) Clustal W and Clustal X version 2.0. Bioinformatics 23: 2947–2948.MA LarkinG. BlackshieldsNP BrownR. ChennaPA McGettigan2007Clustal W and Clustal X version 2.0.Bioinformatics2329472948
  53. 53. Felsenstein J (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 17: 368–376.J. Felsenstein1981Evolutionary trees from DNA sequences: a maximum likelihood approach.J Mol Evol17368376