149I. de Filippis and M.L. McKee (eds.), Molecular Typing in Bacterial Infections, Infectious Disease, DOI 10.1007/978-1-62703-185-1_10, © Springer Science+Business Media New York 2013

10.1 Introduction

Adult periodontitis is a chronic in fl ammatory gum disease that results from the complex actions of a small subset of periodontal pathogens. Although the central cause of periodontitis is loss of healthy balance between microbial virulent agents and host immunity in host-parasite interactions, there are marked differences in the progression rate and severity of this infectious disorder, as well as response to ther-apy among patients. Thus, periodontitis is not considered to be a homogeneous disease, but rather intricately in fl uenced by host susceptibility differences as well as diversities in virulence among the harbored organisms. Indeed, Porphyromonas gingivalis, a bona fi de periodontal pathogen associated with various forms of mar-ginal periodontitis, can be present in periodontal pockets undergoing destruction as well as in healthy gingival margins. Clonal heterogeneity of subpopulations with both high and low levels of pathogenicity has been suggested to exist among peri-odontal pathogens harbored by individuals with negligible, slight, or even severe periodontal destruction. Therefore, speci fi c virulent clones of the pathogens may be the cause of advanced and/or aggressive periodontitis.

Such aspects are not pathognomonic for only periodontitis, as they are also com-monly observed features of various infectious diseases caused by a wide variety of pathogens in humans. Recent technical innovations have provided various genomic

M. Kuboniwa , D.D.S., Ph.D. • A. Amano , D.D.S., Ph.D. (*) Department of Preventive Dentistry , Osaka University Graduate School of Dentistry , 1-8 Yamadaoka , Suita, Osaka 565-0871 , Japan e-mail: kuboniwa@dent.osaka-u.ac.jp; amanoa@dent.osaka-u.ac.jp

Chapter 10 Genotyping of Periodontal Anaerobic Bacteria in Relationship to Pathogenesis

Masae Kuboniwa and Atsuo Amano

150 M. Kuboniwa and A. Amano

tools for identi fi cation of microorganisms, as well as evaluation of the presence of virulence factors and antibiotic resistance determinants. Genotyping assays of peri-odontal pathogens are expected to become useful methods for periodontal examina-tions and diagnosis. However, those will require additional re fi nements to elucidate how the degree of clonality of particular periodontal pathogens in fl uences outcome and results interpretation. This chapter describes currently available assay methods, including those for the most advanced microbiome analyses, which are used to investigate disease-causing bacterial fl ora and genotypic variations of periodontal pathogens, as well as fi ndings from past studies that enable the estimation of speci fi c virulent phenotypes and genotypes related to periodontitis.

10.2 Classi fi cation of Bacteria in Pre-Genomic and Post-Genomic Eras

Screening for the existence of particular species recognized as periodontal patho-gens is the fi rst step of diagnosis and usually performed prior to evaluation of viru-lent subspecies. Despite its eminent practical signi fi cance for identi fi cation, diagnosis, and diversity surveys, bacterial species de fi nition remains a very dif fi cult issue for researchers. In 1987, it was proposed that bacterial strains showing >70% DNA-DNA hybridization and sharing characteristic phenotypic traits should be considered as the same species, which is still the most recent de fi nition of bacterial species of fi cially utilized. On the other hand, advances in sequencing techniques have introduced other markers for bacterial classi fi cation, such as 16S ribosomal RNA (rRNA), a molecule that is ubiquitous in bacterial genomes. Sequence simi-larities of 16S rRNA genes have been found to be highly correlated with DNA hybridization, with a roughly 97% 16S rRNA sequence identity considered to cor-respond to the 70% cutoff level in DNA-DNA reassociation, and widely used for estimation of evolutionary history and taxonomic assignment of individual organ-isms. For this purpose, sequence identity ranging from 90 to 95% is sometimes used to de fi ne genera, and a range of 97–98.7% generally used to de fi ne a species or phylotype. However, this phylogenetic de fi nition has some disadvantages. First, the 16S rRNA typing method lacks resolution below the species level, though strains may be distinguished at the level of 99% pair wise sequence identity. Second, a phylogenetic de fi nition has some exceptions that include the Bacillus genus, for which the 16S rRNA sequences from phenotypically distinct species differ at only a few bases. In contrast, considerable intragenomic variations of 16S rRNA genes were found in 24 species according to the current GenBank database and, when compared with the 16S rRNA-based threshold for operational de fi nition of species, the diversity was borderline (between 1 and 1.3%) in 10 species and >1.3% in 14 species [ 1 ] . Thus, taxonomic classi fi cation using the 16S rRNA-based operational threshold might misclassify a number of species, leading to under- or overestima-tion of the diversity of a complex microbiome.

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10.3 Metagenomic Analysis of Oral Microbiome

10.3.1 Microbiome Study Using 16S Ribosomal RNA Gene Clone Library

Despite the taxonomic dilemma described in the former section, a ribosomal RNA approach remains the principal tool to study microbial diversity. During the last decade, microbiome studies of clinical specimens, including saliva, supragingival plaque, subgingival plaque, and tongue coating, were performed by constructing 16S rRNA gene clone libraries. However, they may have considerable biases related to the polymerase chain reaction (PCR) primers used and the relative inef fi ciency of DNA extraction techniques. So-called “universal” PCR primers can introduce bias into analysis of a species composition of clone libraries, because of mismatches between the primer and target organism sequences. Thus, a combined use of mul-tiple universal primer sets, multiple DNA extraction techniques, and deep commu-nity sequencing is recommended for minimizing such biases and recovering substantially more species than reported in prior studies.

10.3.2 Microbiome Study Using 16S Ribosomal RNA Gene Hypervariable Tag Sequence

Presently, metagenomic studies rely on the utilization and analysis of reads obtained using next-generation sequencing (NGS), such as 454 pyrosequencing, and Illumina and SOLiD sequencing, to replace conventional Sanger sequencing. NGS has mark-edly accelerated multiple areas of genomics research, enabling experiments that previously were not technically feasible or affordable. However, the sequences are much shorter, thus new methods are necessary to identify microbes from short DNA tags.

The 16S rRNA gene in bacteria consists of conserved sequences interspersed with variable sequences that include nine hypervariable regions (V1–V9), whose lengths range from approximately 5 to 100 bases. Individual reference databases for the speci fi c hypervariable regions 3, 6, and 9 of 16S rRNA genes (RefHVR_v3, RefHVR _v6, and RefHVR _v9, respectively) were created by excising in silico the appropriate sections of full-length sequences from the SILVA database ( http://www.arb-silva.de/ ), and are available at the Visualization and Analysis of Microbial Population Structures (VAMPS) Web site ( http://vamps.mbl.edu/resources/data-bases.php ). The taxonomies assigned to hypervariable regions three and six were compared with those assigned to the full-length 16S rRNA sequences, and the hypervariable region tags and full-length ribosomal RNA sequences were found to provide equivalent taxonomy and measures of relative abundance of microbial communities. In addition, the numbers of different phylotypes and their relative

152 M. Kuboniwa and A. Amano

abundance in saliva and supragingival plaque samples from healthy adult populations were determined using V6 hypervariable region pyrosequencing analysis, with an estimated 19,000 phylotypes identi fi ed, a number considerably higher than previ-ously estimated [ 2 ] . Very recently, the ~82 base segment in V5 has been shown to be a short region which provided reliable identi fi cation of oral bacteria by Illumina technology. However, phylum Bacteroidetes was detected at a lower rate by this method [ 3 ] .

10.3.3 Terminal Restriction Fragment Length Polymorphism

Terminal restriction fragment length polymorphism analysis, a quantitative molecu-lar PCR technique, was developed for rapid analysis of microbial community diver-sity in various environments. With this method, one of the two primers is fl uorescently labeled at the 5 ¢ end and used to amplify a selected region of bacterial genes encod-ing 16S ribosomal RNA from the total community of DNA. The PCR product is digested with restriction enzymes and the fl uorescently labeled terminal restriction fragment precisely measured using an automated DNA sequencer. This analysis has been applied to assess oral microbial communities in subgingival specimens for monitoring changes after clinical treatment [ 4 ] , as well as those in saliva obtained from oral malodor patients [ 5 ] .

10.3.4 Microbiome Study Using Whole-Genome Shotgun Sequencing

As described in the former section, 16S rRNA gene-based sequencing can detect predominant members of a microbial community, though it may not detect rare members of a community with divergent target sequences. Primer bias and the low depth of sampling cause some of these limitations. To overcome the limitations of single gene-based amplicon sequencing, whole-genome shotgun sequencing has emerged as an attractive strategy for assessing complex microbial diversity in mixed populations.

One key issue of whole-genome sequencing strategies is the requirement for suf fi cient amounts of input genomic DNA for comprehensive studies based on metagenomics. Whole-genome ampli fi cation represents an effective technology for enabling whole-genome shotgun sequencing of limited amounts of total DNA in the precious samples. However, the potential of whole-genome ampli fi cation to co- amplify contaminating host (human) DNA poses a signi fi cant problem, while such host DNA co-ampli fi cation may also overwhelm the bacterial DNA sequence data in the sample. Different subtraction strategies for human DNA sequences are needed to minimize this possible blockade.

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10.3.5 Third-Generation Sequencing—Single-Molecule Sequencing Technologies

Third-generation sequencing technologies, including real-time single-molecule DNA sequencing and nanopore-based sequencing, may drastically decrease sequencing time, reduce costs, and streamline sample preparation. Real-time sin-gle-molecule sequencing developed by VisiGen uses DNA polymerase modi fi ed with a fl uorescent donor molecule. Paci fi c Biosciences performs another type of single-molecule sequencing, which uses phospholinked fl uorescently labeled dNTPs. Nanopore-based sequencing monitors the passage of DNA molecules through nanopores 2–5 nm or greater in diameter, by which kilobase length poly-mers (single-strand genomic DNA or RNA) can be identi fi ed and characterized without ampli fi cation bias. Third generation instruments can sequence a mam-malian genome for ~$1,000 in ~24 h, however, the large amounts of sequence data outputted will cause a bioinformatics challenge for the clinical laboratory per-forming the test. In addition to data processing, the interpretation of sequencing results will require further characterization of the genomic variation, as described in the Sect. 10.4.6

10.3.6 Pan-Genome Analysis

The development of ef fi cient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens. However, the sequence of a single genome does not re fl ect how genetic variability drives pathogenesis within a bacterial species. Tettelin et al. analyzed eight genomes considered to be representative of the serotype diversity among Streptococcus agalactiae strains to answer the question of how many genomes are needed to fully describe a bacterial species [ 6 ] . Analysis of these genomes and those in available databases showed that S. agalactiae species can be described by a pan-genome consisting of a “core genome” shared by all isolates, accounting for approximately 80% of any single genome, plus a “dispensable genome” consisting of partially shared and strain-speci fi c genes.

Recently, the pan-genome concept has been extended to higher taxonomic units. The size of the bacterial pan-genome was estimated based on the frequency of occurrences of genes among 573 sequenced genomes, with three distinct pools of gene families; core, character and accessory gene families, characterized (Fig. 10.1 ). The results indicate that the pan-genome of the bacterial domain is of in fi nite size and that approximately 250 genes per genome belong to the extended bacterial core genome [ 7 ] .

154 M. Kuboniwa and A. Amano

Fig. 10.1 The bacterial pan-genome. ( a ) A total of 15,000 genes were sampled to determine their frequencies of occurrence among 293 genomes (Lapierre Trends in Genetics). A Bitscore >50 obtained using a basic local alignment search tool (BLAST) was used to classify a gene as present in the target genome and a member of the same gene family. Each bar corresponds to the normal-ized number of genes [ n genes at Fq( x )/15,000] having the indicated frequency (Fq) of occurrence (present in n other genomes/total number of genomes − 1). Genes without any homologs (Fq = 0) represent accessory genes, whereas genes present in 292 other genomes (Fq = 1) represent strict core genes. Parts of the histogram that mainly contribute to the extended core genes, as well as character and accessory genes are indicated. ( b ) Each gene found in the bacterial genome repre-sents one of three pools. Genes found in all but a few bacterial genomes comprise the extended core of essential genes that encode proteins involved in translation, replication, and energy homeo-stasis; character genes represent genes essential for colonization and survival in particular environ-mental niches; and the accessory gene family, comprising a pool of apparently in fi nite size, contains genes that can be used to distinguish strains and serotypes, though the function of most genes in this category is unknown

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10.3.7 “Human Microbiome Project” and “Genomic Encyclopedia of Bacteria and Archaea”

The human microbiome refers to the community of microorganisms that populate the human body. The National Institutes of Health launched an initiative that focuses on describing the diversity of microbial species associated with health and disease, and the results from an initial reference genome sequencing of 178 microbial genomes, including those of oral microorganisms, are presented at The Human Microbiome Project Web site ( http://www.hmpdacc.org/ ) [ 8 ] . On the other hand, The Genomes Online Database (GOLD; http://www.genomesonline.org/ ) released 1,291 completed bacterial and archaeal genome sequences, most of which were chosen for sequencing on the basis of their physiology. As a consequence, the per-spective provided by the currently available genomes is limited by a highly biased phylogenetic distribution. Very recently, genomes of 56 culturable species of bacte-ria and archaea have been selected and sequenced to maximize the phylogenetic coverage. Analysis of these genomes demonstrated pronounced bene fi ts in diverse areas, including the reconstruction of phylogenetic history, the discovery of new protein families and biological properties, and the prediction of functions for known genes from other organisms. To utilize a phylogeny-driven “Genomic Encyclopedia of Bacteria and Archaea” would be advantageous to derive maximum knowledge from genome sequences yet to be revealed [ 9 ] .

10.4 Genotyping Methods to Distinguish Clonality of Periodontal Pathogens

Studies of pathogens require uniform and reproducible nomenclature schemes, and molecular typing systems are able to distinguish among epidemiologically unre-lated isolates by characterizing the genetic variations in the chromosomal DNA of bacterial species. Several of the DNA-based typing methods described below have been used for characterizing periodontal pathogens during the previous 10 years. Among these methods, multi-locus sequence typing (MLST) and PCR analysis for detection of target genotypes have been the most commonly utilized to discriminate isolates below the species level (Fig. 10.2 ).

10.4.1 Mobility Shift Assays

Electrophoretic mobility shift assays (EMSA), including denaturing gradient gel electrophoresis (DGGE), temperature gradient gel electrophoresis (TGGE), tem-perature sweep gel electrophoresis (TSGE), and heteroduplex analysis (HA), were

156 M. Kuboniwa and A. Amano

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originally developed as tools for detection of genetic mutations in cancer genomes. However, they have also been found suitable for screening of virulent phylotypes in oral bio fi lm as well. In EMSA, DNA fragments of the same length, but with differ-ent base-pair sequences, can be separated. Even a single-base change in a sequence can be resolved, which provides PCR-EMSA with great potential to identify closely related species based on 16S rRNA sequence divergence. In addition to being applied to the broad-range analysis of complex microbial communities [ 10, 11 ] , the method can also be used to detect speci fi c bacterial groups by altering the primer targets or by using a nested PCR approach. Moreover, denaturing high performance liquid chromatography (DHPLC), an electrophoresis-independent mobility shift assay, has been applied to the monitoring of micro fl ora [ 12 ] .

10.4.2 Multi-Locus Sequence Typing

The ability to accurately characterize species is reliant on strain typing methods used to distinguish among isolates of the same species, and is usually accomplished using one or more DNA-based methods. Multiple locus sequence typing (MLST), a phylo-genetic approach designed to infer the relatedness among strains of various bacterial pathogens, has been used in several etiologic studies of periodontal diseases. With this method, 7–10 housekeeping genes are generally chosen, depending on the spe-cies of interest, which are then sequenced and the resultant individual gene sequences linked in tandem, or concatenated, prior to phylogenetic analysis. The resulting data is storable in a digital format so that worldwide coverage of pathogen diversity can eventually be achieved ( http://pubmlst.org/ ). MLST has been performed in studies of P. gingivalis, A. actinomycetemcomitans , and T. denticola . However, this method seems to be incapable of linking strains to pathogenesis, thus direct genotyping of virulence related genes is still necessary for clustering of virulent strains [ 13 ] .

MLST involves sequencing portions of 7–10 housekeeping genes, thus the sam-ples comprise only about 0.1–0.2% of a microbial genome (Fig. 10.3 , Table 10.1 ). As a result, it is not surprising that a large number of isolates appear to be identical when using such small fractions of their genomes. The question remains whether all or many of those isolates are actually different from each other. It seems likely that higher resolution methods could usefully distinguish them and whole-genome information may provide such a desired increase in resolution, as described in the “Pan-genome analysis as a strain typing solution” section.

10.4.3 Multi-Virulence-Locus Sequence Typing

The multi-virulence-locus sequence typing (MVLST) scheme was originally devel-oped for subtyping Listeria monocytogenes [ 14 ] . Internal fragments (ca. 418–469 bp) of three virulence genes and three virulence-associated genes were sequenced, and then multiple DNA sequence alignment identi fi ed a total of 28

158 M. Kuboniwa and A. Amano

Fig. 10.3 Genomic coverage of genetic typing methods. The core genome includes genes that encode proteins involved in essential functions, such as replication, transcription, and translation. The dispensable genome includes genes that encode proteins that facilitate organismal adaptation. Coverage by 16S ribosomal RNA (rRNA), housekeeping genes for multilocus sequence typing (MLST), pathogenic genes for multi-virulence-locus sequence typing (MVLST), tandem repeat sequences for multilocus variable number of tandem repeats analysis (MLVA), and single-nucle-otide polymorphisms (SNPs) is also depicted

15910 Genotyping of Periodontal Anaerobic Bacteria in Relationship to Pathogenesis

Table 10.1 Genomic coverage of genetic typing methods

Typing method Genetic loci

Genomic coverage rate (%) Classi fi cation level

16S rRNA 1 locus (various copy number)

0.062 a Domain, phylum, class, order, family, genus, (species)

MLST ~10 loci 0.26 b Clonal complex (subspecies) SNPs ~100 loci ~2 c Haplotype Pan-genome Whole genome 100 All non-clonal genetic variations

a Calculated based on genome size (2,354,886 bp) and 16S rRNA size (1,474 bp) in Porphyromonas gingivalis ATCC33277 b Calculated based on genome size (2,354,886 bp) and sum of MLST target region size [ ef-tu (650 bp), ftsQ (566 bp), hagB (560 bp), gpdxJ (501 bp), pepO (642 bp), mcmA (562 bp), dnaK (659 bp), recA (642 bp), pga (693 bp), nah (683 bp)] in P. gingivalis ATCC33277 [ 28 ] c Calculated based on genome size (~4.8 Mb) and SNP gene fragment size (~89 Kb) in Salmonella enterica serovar Typhi [ 29 ]

unique sequence types. Comparison of MVLST results with those of automated EcoRI- ribotyping (RT) and pulsed- fi eld gel electrophoresis (PFGE) with Apa I enzymatic digestion showed that MVLST was able to differentiate strains that were indistinguishable by RT or PFGE. Furthermore, a comparison of MVLST with housekeeping gene-based MLST analysis showed that MVLST provided higher discriminatory power for some strains than MLST, while cluster analysis based on the intragenic sequences of the selected virulence genes indicated a strain phylog-eny closely related to serotypes and genetic lineages. Thus, MVLST may improve the discriminatory power of MLST and become a convenient tool for studying the molecular epidemiology of periodontal pathogens.

10.4.4 Single Nucleotide Polymorphisms

Single nucleotide polymorphisms (SNPs) were originally developed for use in humans and then applied to bacteria. SNPs have recently been utilized to differenti-ate Bacillus anthracis clinical samples that were collected from a disease outbreak and to propose a Mycobacterium tuberculosis typing scheme. Furthermore, a set of 16 SNPs was reported able to differentiate all epidemic clones and outbreak strains of L. monocytogenes [ 15 ] . SNPs can be a powerful tool owing to their provision of greater genomic coverage as compared with other classi fi cation methods (Fig. 10.3 , Table 10.1 ). However, their use is limited and their potential for more general use in bacterial population genetics remains unproven.

10.4.5 Multiple-Loci Variable Number of Tandem Repeats Analysis

A large number of bacterial genes or intergenic regions contain loci of repetitive DNA, which may vary among strains with respect to their individual primary struc-ture or the number of repeat units present [ 16 ] . This has implications for both the

160 M. Kuboniwa and A. Amano

techniques used to determine the number of repeats and the level of variability. In addition, tandem repeats can be part of coding regions or intergenic, and may play a direct role in adaptation to the environment, thus the observed evolution rates may differ. For these reasons, the choice of a variable number of tandem repeats is important for this type of analysis. Although reasonable discrimination can be achieved with the typing of 6–8 markers, particularly with species with high genomic diversity, it may be necessary to type 20–40 markers in order to cluster pathogenic strains in monomorphic species. A variable number of tandem repeat data sets for the P. gingivalis strains ATCC33277 and W83 are currently available online ( http://minisatellites.u-psud.fr/ASPSamp/base_ms/bact.php ).

10.4.6 Pan-Genome Analysis as Strain Typing Solution

Comparative genomics analyses between multiple genomes of individual species have revealed extensive genomic intraspecies diversity [ 17 ] . Some intraspecies molecular evolutionary mechanisms, including point mutation, gene duplication, gene loss, and recombination, have been reported to contribute to bacterial genome diversity. Interspecies mechanisms, such as phage infection and plasmid acquisition, as well as population dynamic mechanisms including bottleneck and selective sweep are also known as forces that shape bacterial genomes. For these reasons, one genome sequence is inadequate to describe the complexity of spe-cies, genera, and their interrelationships. The term “pan-genome” denotes the set of all genes present in the genomes of a group of organisms, usually a species. As described in the former section, a pan-genome includes genes that exist in only a single organism (accessory genes), in the genomes of a few members of the group (character genes), or in all genomes of the group (core genes). A group of accessory genes and character genes is described as distributed genes or dis-pensable genes. Very recently, Hall et al. [ 18 ] have developed a novel strain typ-ing method termed neighbor grouping (NG), which is based on core gene distances and the presence or absence of distributed genes. NG de fi nes a pair of genomes as valid neighbors if they are signi fi cantly more closely related than an average pair of genomes. According to their report, the results of NG analyses are entirely consistent with those of MLST, while NG provides additional dis-criminatory power.

10.4.7 Microarray-Based Comparative Genomic Hybridization

Microarray-based comparative genomic hybridization (M-CGH) techniques have been used to characterize the extensive intraspecies genetic diversity found among bacteria at the whole genome level. Very recently, M-CGH has been performed to estimate the whole genomic diversity of representative P. gingivalis strains [ 19 ] .

16110 Genotyping of Periodontal Anaerobic Bacteria in Relationship to Pathogenesis

In that study, the relatedness of the strains to one another shown by this analysis was reported to be highly similar to their relatedness based on ribosomal operon inter-genic spacer region sequence analysis, while a correlation was also observed between the genome contents and disease-associated phenotypes of the strains.

10.4.8 In Situ Oligonucleotide Probes

Prokaryotic cells can be identi fi ed without cultivation by applying fl uorescence in situ hybridization (FISH) with ribosomal RNA targeted oligonucleotide probes. Generally, these probes are 15–25 nucleotides in length and labeled covalently at the 5 ¢ end with a fl uorescent dye. Speci fi cally stained cells are detected via epi fl uorescence microscopy or fl ow cytometry. This technique has become the method of choice for reliable and rapid identi fi cation of microorganisms in environ-mental and medical samples, such as dental plaque. The large online database “Probebase” provides an encompassing overview of published probes ( http://www.microbial-ecology.net/probebase/ ).

Flow cytometry is a routine method used for cellular biology studies, though its application to prokaryotic cells up to this point has been rather limited, mainly because of the dif fi culty in interpreting signals from very small objects. However, studies that use fl ow cytometry techniques for application to environmental micro-biology have been increasing in recent years. Although bacteria are relatively dif fi cult to analyze and differentiate by fl ow cytometry, owing to their small cell size (so-called diminutiveness) and mostly similar morphologies, fl ow cytometry tech-niques are especially promising due to their high-throughput capacity and ability for interrogation at the single-cell level. Recent technical advances have simpli fi ed fl ow cytometry instrument handling, improved cell sorting capabilities, and introduced multi-parametric measurements, and it is now possible to interrogate microbial communities using two or three different fl uorescent dyes that target speci fi c biomolecules and physiological processes.

10.4.9 Pattern-Based Technologies

Pattern-based technologies, such as restriction fragment length polymorphism (RFLP), multi-locus enzyme electrophoresis (MLEE), arbitrarily primed PCR (AP-PCR) for randomly ampli fi ed polymorphic DNA analysis (RAPD), pulse- fi eld gel electrophoresis (PFGE), and ampli fi ed fragment length polymorphism (AFLP), have been used for characterizing periodontal pathogens including P. gingivalis , A. actinomycetemcomitans , and T. denticola . However, it should be noted that pat-terns produced in different laboratories can only be compared if very strict quality standards are followed.

162 M. Kuboniwa and A. Amano

10.4.10 PCR Analysis for Detection of Target Genes

The identi fi cation of bacterial species or detection of particular virulence related genes using molecular techniques, such as conventional polymerase chain reaction (PCR), provide binary presence or absence data, while other methods, such as check-erboard DNA–DNA hybridization or real-time polymerase chain reaction (RT-PCR), provide quantitative data [ 20, 21 ] . In addition, PCR analysis has also been used for genotyping of virulence-related genes in P. gingivalis and A. actinomycetemcomitans , as described in the next section.

10.5 Clonal Variations of Bacterial Molecules Related to Bacterial Virulence Diversity

10.5.1 Variations of P. gingivalis Fimbriae

Fimbriae are thin, fi lamentous, proteinaceous surface appendages (hair-like organ-elles) that protrude from the surface of a number of different bacterial species, and are especially prominent on Gram-negative bacteria where they are anchored within the outer membrane [ 22 ] . P. gingivalis expresses two distinct fi mbriae types on its cell surface; one of which is composed of a subunit protein (named FimA or fi mbrillin) encoded by the fi mA gene and termed long, or major fi mbriae, while the other con-sists of a subunit Mfa protein encoded by the mfa1 gene and termed short, minor, or Mfa fi mbriae (henceforth referred to as simply long and short fi mbriae, respectively). Long fi mbriae are a critical factor for colonization of P. gingivalis in subgingival regions, as they promote both bacterial adhesion to and invasion of targeted sites. The fi mA gene is monocistronic and exists as a single copy in the chromosome of P. gingivalis . P. gingivalis fi mA genes have been classi fi ed into six variants (types I to V and Ib) on the basis of their different nucleotide sequences [ 22 ] .

We developed a conventional PCR assay method using fi mA type-speci fi c primer sets to differentiate the fi mA genotypes of the organisms present in saliva and dental plaque samples [ 22 ] . With this method, various researchers have investigated the prev-alence and distribution of fi mA genotypes in subjects with different periodontal condi-tions in various geographical locations, including Japan, China, Germany, Norway, the Netherlands, Switzerland, Brazil, and Mexico. From those epidemiological and clinical studies, it can be derived that the type II fi mA genotype is most prevalent in periodontitis patients, while the second most prevalent has been variably found to be type IV or Ib, depending on the ethnic population studied. Conversely, types I and III fi mA are more prevalent in non-periodontitis subjects. As for clinical signi fi cance, type II clones are most frequently associated with advanced chronic periodontitis with deep probing pocket depth, and severe forms such as aggressive periodontitis and refractory periodontitis. In addition, type II clones seem to be related to marginal periodontitis in Down’s syndrome and mentally disabled populations.

P. gingivalis has been reported to contribute to such systemic conditions as cardiovascular diseases and diabetes mellitus by direct oral-hematogenous spreading of

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bacteria. Types II and IV clones were detected in atheromatous plaque specimens collected from patients undergoing cardiovascular surgery more frequently than the other types [ 23 ] , while type II clones were also shown to be a participation factor in marginal periodontitis associated with type II diabetes mellitus. On the other hand, dia-betes glycemic level may be affected by the persistence of P. gingivalis , especially type II clones, in periodontal pockets after professional periodontal treatment [ 24 ] . Furthermore, type II fi mbriae were shown to most ef fi ciently mediate bacterial adhesion to and invasion of host cells, as compared to those of the other types. Following invasion of cells, intracellular P. gingivalis organisms with type II fi mbriae were found to clearly degrade integrin-related signaling molecules such as paxillin and focal adhesion kinase, thus disabling cellular migration and proliferation. These events are considered to be an integral part of the bacterial strategy for persistence in periodontal tissues. Together, these fi ndings strongly suggest that clonal variations of long fi mbriae are related to bac-terial infectious traits that in fl uence disease development and deterioration.

10.5.2 Variations of A. actinomycetemcomitans Leukotoxin

Leukotoxin (Ltx) is one of the virulence factors of A. actinomycetemcomitans and likely linked to aggressive periodontitis. Ltx is assumed to contribute to the severity of periodontal disease by disrupting local defense mechanisms, and has also been corre-lated to disease onset and progression. All isolates of A. actinomycetemcomitans exhibit the ltx operon, which has been classi fi ed into three genotypes based on differences in Ltx expression in the representative strains ATCC33384, Y4, and JP2 [ 25 ] . Those gen-otypes were also shown to be related with the expression ef fi ciency of Ltx, i.e., lower (ATCC33384), moderate (Y4), and high (JP2) levels of expression with apparent toxic diversity shown in chromium release assays using monocytes. The Ltx operon of iso-lates with high titers of leukotoxin production (JP2-like) presents a deletion of 530 bp, resulting in 10–20 times greater levels of Ltx expression than low leukotoxic strains. In addition, the truncated structure of the promoter was shown to drive Ltx expression, while the levels of toxin expressed by 15 strains of A. actinomycetemcomitans were found to be correlated with the truncated structure of the ltx promoter.

10.5.3 Variations of A. actinomycetemcomitans Cytolethal Distending Toxin

Cytolethal distending toxin (Cdt) is a newly described virulence factor produced by A. actinomycetemcomitans that disturbs the cell cycle (G2 arrest) and is involved in cellular proliferation. The cdt gene is encoded by three genes, designated as cdtA , cdtB , and cdtC , which are organized in an apparent operon. The cdt operon has been classi fi ed into four genotypes using a PCR method, which are correlated with various serotypes, with cdt genotype 1 found only in serotype b strains, cdt genotype 2 only in serotype a and b strains, cdt genotype 3 only in serotype c and f strains, and cdt

164 M. Kuboniwa and A. Amano

genotype 4 only in serotype c strains [ 26 ] . In addition, the cdt operon was classi fi ed into six restriction fragment length polymorphism (RFLP) types based on Hind III-digested genomic DNA [ 27 ] . However, there was no strict correlation shown between RFLP type and the cyto-distending activity of each strain. Groups with RFLP types I, II, and IV showed medium cyto-distending activities, while the activities of those with types III, V, and VI varied widely among each type, though types V and VI seemed to have greater cyto-distending activities than the others. These fi ndings suggest that cdt genotype may have a relationship with aggressive periodontitis, though the correlation between cdt alleles and aggressive periodontitis remains to be de fi ned.

10.6 Conclusion

Development of a useful genotyping testing tool for periodontal pathogens is neces-sary for therapeutic use. Future dentistry-related research will certainly produce such bacterial testing tools for periodontal diagnosis, as well as medication and treatment for affected individuals. However, additional efforts are required to inves-tigate the exact relationship between genotypic variation and bacterial pathogenic-ity in periodontitis. Genomic variations of the long fi mbria structures of P. gingivalis seem to be related to periodontitis initiation and progression. Recently, in addition to the whole genome sequence of P. gingivalis strain W83, that of ATCC 33277 has also been determined. Furthermore, the whole genome sequence of P. gingivalis with type II fi mA will soon be revealed. Pan-genome analysis of P. gingivalis would be expected to clarify the differences of virulence among strains, and M-CGH could be utilized for analysis of the relationship between expression levels of microbial genes and periodontal situation. These future developments will be vital to identify the virulence/pathogenicity-related genes of P. gingivalis , while they will also be necessary for advancements in periodontal therapy and assessment of prognosis, by elucidating disease contributing clones of periodontal bacteria.

References

1. Pei AY, Oberdorf WE, Nossa CW et al (2010) Diversity of 16S rRNA genes within individual prokaryotic genomes. Appl Environ Microbiol 76:3886–3897

2. Keijser BJ, Zaura E, Huse SM et al (2008) Pyrosequencing analysis of the oral micro fl ora of healthy adults. J Dent Res 87:1016–1020

3. Lazarevic V, Whiteson K, Huse S et al (2009) Metagenomic study of the oral microbiota by Illumina high-throughput sequencing. J Microbiol Methods 79:266–271

4. Sakamoto M, Huang Y, Ohnishi M, Umeda M, Ishikawa I, Benno Y (2004) Changes in oral microbial pro fi les after periodontal treatment as determined by molecular analysis of 16S rRNA genes. J Med Microbiol 53:563–571

5. Takeshita T, Suzuki N, Nakano Y et al (2010) Relationship between oral malodor and the global composition of indigenous bacterial populations in saliva. Appl Environ Microbiol 76:2806–2814

6. Tettelin H, Masignani V, Cieslewicz MJ et al (2005) Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae : implications for the microbial “pan-genome”. Proc Natl Acad Sci USA 102:13950–13955

16510 Genotyping of Periodontal Anaerobic Bacteria in Relationship to Pathogenesis

7. Lapierre P, Gogarten JP (2009) Estimating the size of the bacterial pan-genome. Trends Genet 25:107–110

8. Nelson KE, Weinstock GM, Highlander SK et al (2010) A catalog of reference genomes from the human microbiome. Science 328:994–999

9. Wu D, Hugenholtz P, Mavromatis K et al (2009) A phylogeny-driven genomic encyclopaedia of bacteria and archaea. Nature 462:1056–1060

10. Rasiah IA, Wong L, Anderson SA, Sissons CH (2005) Variation in bacterial DGGE patterns from human saliva: over time, between individuals and in corresponding dental plaque micro-cosms. Arch Oral Biol 50:779–787

11. Zijnge V, Welling GW, Degener JE, van Winkelhoff AJ, Abbas F, Harmsen HJ (2006) Denaturing gradient gel electrophoresis as a diagnostic tool in periodontal microbiology. J Clin Microbiol 44:3628–3633

12. Schaudinn C, Gorur A, Keller D, Sedghizadeh PP, Costerton JW (2009) Periodontitis: an archetypical bio fi lm disease. J Am Dent Assoc 140:978–986

13. Enersen M, Olsen I, Kvalheim O, Caugant DA (2008) fi mA genotypes and multilocus sequence types of Porphyromonas gingivalis from patients with periodontitis. J Clin Microbiol 46:31–42

14. Zhang W, Jayarao BM, Knabel SJ (2004) Multi-virulence-locus sequence typing of Listeria monocytogenes . Appl Environ Microbiol 70:913–920

15. Chen Y, Zhang W, Knabel SJ (2007) Multi-virulence-locus sequence typing identi fi es single nucleotide polymorphisms which differentiate epidemic clones and outbreak strains of Listeria monocytogenes . J Clin Microbiol 45:835–846

16. Vergnaud G, Pourcel C (2009) Multiple locus variable number of tandem repeats analysis. Methods Mol Biol 551:141–158

17. Pallen MJ, Wren BW (2007) Bacterial pathogenomics. Nature 449:835–842 18. Hall BG, Ehrlich GD, Hu FZ (2010) Pan-genome analysis provides much higher strain typing

resolution than multi-locus sequence typing. Microbiology 156:1060–1068 19. Igboin CO, Griffen AL, Leys EJ (2009) Porphyromonas gingivalis strain diversity. J Clin

Microbiol 47:3073–3081 20. Socransky SS, Haffajee AD, Smith C et al (2004) Use of checkerboard DNA-DNA hybridiza-

tion to study complex microbial ecosystems. Oral Microbiol Immunol 19:352–362 21. Kuboniwa M, Amano A, Kimura KR et al (2004) Quantitative detection of periodontal patho-

gens using real-time polymerase chain reaction with TaqMan probes. Oral Microbiol Immunol 19:168–176

22. Amano A (2000) Bacterial adhesins to host components in periodontitis. Periodontol 2000 52:12–37

23. Nakano K, Inaba H, Nomura R et al (2008) Distribution of Porphyromonas gingivalis fi mA genotypes in cardiovascular specimens from Japanese patients. Oral Microbiol Immunol 23:170–172

24. Makiura N, Ojima M, Kou Y et al (2008) Relationship of Porphyromonas gingivalis with glycemic level in patients with type 2 diabetes following periodontal treatment. Oral Microbiol Immunol 23:348–351

25. Huber JA, Morrison HG, Huse SM, Neal PR, Sogin ML, Mark Welch DB (2009) Effect of PCR amplicon size on assessments of clone library microbial diversity and community struc-ture. Environ Microbiol 11:1292–1302

26. Kolodrubetz D, Spitznagel J Jr, Wang B, Phillips LH, Jacobs C, Kraig E (1996) cis Elements and trans factors are both important in strain-speci fi c regulation of the leukotoxin gene in Actinobacillus actinomycetemcomitans . Infect Immun 64:3451–3460

27. Kaplan JB, Schreiner HC, Furgang D, Fine DH (2002) Population structure and genetic diver-sity of Actinobacillus actinomycetemcomitans strains isolated from localized juvenile perio-dontitis patients. J Clin Microbiol 40:1181–1187

28. Koehler A, Karch H, Beikler T, Flemmig TF, Suerbaum S, Schmidt H (2003) Multilocus sequence analysis of Porphyromonas gingivalis indicates frequent recombination. Microbiology 149:2407–2415

29. Roumagnac P, Weill FX, Dolecek C et al (2006) Evolutionary history of Salmonella typhi . Science 314:1301–1304