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Comparative Genomics of Helicobacter pylori Strains of China Associated with Different Clinical Outcome

  • Yuanhai You,

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

  • Lihua He,

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

  • Maojun Zhang,

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

  • Jianying Fu,

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

  • Yixin Gu,

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

  • Binghua Zhang,

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

  • Xiaoxia Tao,

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

  • Jianzhong Zhang

    zhangjianzhong@icdc.cn

    Affiliation State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China

Comparative Genomics of Helicobacter pylori Strains of China Associated with Different Clinical Outcome

  • Yuanhai You, 
  • Lihua He, 
  • Maojun Zhang, 
  • Jianying Fu, 
  • Yixin Gu, 
  • Binghua Zhang, 
  • Xiaoxia Tao, 
  • Jianzhong Zhang
PLOS
x

Abstract

In this study, a whole-genome CombiMatrix Custom oligonucleotide tiling microarray with 90000 probes covering six sequenced Helicobacter pylori (H. pylori) genomes was designed. This microarray was used to compare the genomic profiles of eight unsequenced strains isolated from patients with different gastroduodenal diseases in Heilongjiang province of China. Since significant genomic variation was found among these strains, an additional 76 H. pylori strains associated with different clinical outcomes were isolated from various provinces of China. These strains were tested by polymerase chain reaction to demonstrate this distinction. We identified several highly variable regions in strains associated with gastritis, gastric ulceration, and gastric cancer. These regions are associated with genes involved in the bacterial type I, type II, and type III R-M systems. They were also associated with the virB gene, which lies on the well-studied cag pathogenic island. While previous studies have reported on the diverse genetic characterization of this pathogenic island, in this study, we find that it is conserved in all strains tested by microarray. Moreover, a number of genes involved in the type IV secretion system, which is related to horizontal DNA transfer between H. pylori strains, were identified in the comparative analysis of the strain-specific genes. These findings may provide insight into new biomarkers for the prediction of gastric diseases.

Introduction

Helicobacter pylori (H. pylori) is a Gram-negative bacterial pathogen responsible for human gastric diseases, including gastritis and peptic ulcers. It is also a major risk factor in the development of gastric cancer [1][3]. In 1994, the World Health Organization listed H. pylori as a class I carcinogen.

Previous studies have shown that H. pylori has a high rate of homologous gene recombination. Phylogenetic analysis have subdivided H. pylori into distinct biogeographic populations and subpopulations with specific geographical distributions that reflect ancient human migrations. The studies also indicated that the East Asian type (hpEastAsia) is classified into at least three subtypes: East Asian (hspEAsia), Pacific (hspMaori) and native American (hspAmerind). The East Asia subtype (hspEAsia) may be related to the high incidence of gastric cancer in East Asia [4][7]. A more recent study demonstrate the East Asian group appear to differ greatly from the European group in electron transfer and redox reactions, which suggest a model of adaptive evolution and selection through proteome diversification and modulation of translational fidelity [8].

A number of studies have focused on the cag- pathogenicity island encoded virulence apparatus that may play a critical role in H. pylori pathogenesis [9][11]. Importantly, almost all isolates from East Asia harbor the cag-PAI island. A few studies have shown that there are specific sequence characteristics shared among these islands in the various strains, which are responsible for causing different diseases [12][14]. This suggests that genome-wide analyses in various worldwide strains, especially for strains found in East Asia, are necessary. To date, there are thirty-two completed genomes and four draft genomes available on GenBank [15]–. Genome sizes among clinical isolates of H. pylori vary considerably, with some showing differences up to 25% [28], [29]. Comparative genomic profiling, using microarrays designed to cover entire genomes, is one strategy that can be used to obtain information about the variability between strains isolated from different patients and locations as well as to indicate horizontal gene transfer. Previously available commercial chips cover only one or two H. pylori genomes [30][37]. With more H. pylori genome sequences publicly available, it is possible to design high-density microarrays covering all of these fully sequenced genomes. During this study, an additional twenty-six strains associated with different clinical outcomes of various phylogeographic lineages were completely sequenced in the last two years. Additionally, several strains from other countries are also now undergoing sequencing. Here we describe the design and use of a high-density oligonucleotide microarray covering six sequenced H. pylori genomes. The performance of this microarray is evaluated, and we illustrate its utility for the hybridization of genomic DNA in order to compare eight uncharacterized H. pylori strains to the six established strains. We use this microarray to identify variable genomic regions among H. pylori strains isolated from patients with different gastroduodenal diseases in a Chinese patient population.

Materials and Methods

H. Pylori Strains

H. pylori is a well-known pathogen with much genetic variation; both host and bacterial factors may contribute to this fact. Strains isolated from different countries, different geographies, and even different families show genomic diversity [38]. Therefore, from a genomic viewpoint, strain selection has been a critical issue for investigation of the pathogenic mechanism. In this study, we chose eight strains for microarray analysis. This included isolates from 2 patients with chronic superficial gastritis (HLJ220,HLJ215), 2 patients with atrophic gastritis (HLJ193,HLJ256), 2 patients with gastric ulcers (HLJ271,HLJ253), and 2 patients with gastric cancer (HLJ038,HLJ005). The strain numbers were encoded by our lab, Department of Diagnosis for Communicable Diseases, National Institute for Communicable Disease Control and Prevention, China CDC. They were all isolated from Heilongjiang province of China, which reports a high incidence rate of gastric cancer. We used PCR for investigating an additional 76 strains of disease specific genes, which were isolated from seven Chinese provinces. These included thirty-one gastric cancer strains (GC), six gastric ulcer strains (GU), one atrophic gastritis strain (AG), eight duodenal ulcer strains (DU), three gastroduodenal ulcer strains (GDU), six functional dyspesia strains (FD), and twenty-one non-atrophic gastritis strains (SG). Background information describing these strains is briefly listed in table 1.

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Table 2. General features of the sequenced H. pylori genomes selected for microarray probe design.

https://doi.org/10.1371/journal.pone.0038528.t002

Ethics Statement

All patients involved have given informed consent for the samples to be used in historic or future studies. The consent was written, and ethics approval was obtained from the ethics committee of the Chinese Center for Disease Control and Prevention (China CDC) and the academic committee of the National Institute for Communicable Disease Control and Prevention, China CDC.

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Figure 1. Comparison of HLJ005, HLJ038, and 26695 based on strain specific genes of the six sequenced genomes.

A. Comparison between HLJ005 and 26695. B. Comparison between HLJ038 and 26695. C. Comparison between HLJ038 and HLJ005. Green spots show inferred loss while orange dots show no changes in the original data. Red spots show inferred increase. Segment 1 on the X-axis: probes of 26695 strain specific genes. Segment 2: probes of G27 strain specific genes. Segment 3: probes of HPAG1 strain specific genes. Segment 4: probes of J99 strain specific genes. Segment 5: probes of P12 strain specific genes. Segment 6: probes of Shi470 strain specific genes.

https://doi.org/10.1371/journal.pone.0038528.g001

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Figure 2. Comparison of HLJ005, HLJ038, and 26695 based on 0–100 kb of p12 genome.

A. Comparison between HLJ005 and 26695. B. Comparison between HLJ038 and 26695. C. Comparison between HLJ038 and HLJ005. Green spots show inferred loss while orange dots show no changes in the original data. Red spots show inferred increase. The red rectangle indicates the predicted 5.2 kb absent region both in gastric cancer strain HLJ038 and HLJ005 based on the 0–100 kb of the reference P12 chromosome.

https://doi.org/10.1371/journal.pone.0038528.g002

DNA Preparation

Genomic DNA was extracted by using the DNeasy Blood & Tissue Kit (QIAGEN) according to the manufacturer’s instructions. The concentration of genomic DNA was adjusted to 120 ng/µl with nuclease-free water and to a volume of 40 µl. DNA was heated in a PCR machine (Biorad, USA) at 95°C for 10 min to obtain DNA fragments with sizes of 100 bp to 600 bp for genomic labeling. The results were visualized by 1% agarose gel electrophoresis.

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Figure 3. Genome comparison of eight H. pylori strains based on P12 reference sequence.

Large variable regions were labeled with colored rectangles. Predicted gastric cancer strain specific regions were labeled with a red rectangle. General genomic variation among all strains was labeled with a green rectangle. A blue rectangle represents diverse regions obtained from comparison of gastric cancer strains and superficial gastritis strains. Corresponding coding proteins were briefly labeled at the bottom of each rectangle. GC vs SG denotes comparison between the two strains of gastric cancer and the two strains of superficial gastritis. DR, different region.

https://doi.org/10.1371/journal.pone.0038528.g003

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Table 3. Predicted variable genomic region based on reference genome P12.

https://doi.org/10.1371/journal.pone.0038528.t003

Microarray Design, Labeling, Hybridization and Stripping

A whole-genome CombiMatrix tiling CustomArray™ 90 K (Mukilteo, WA, USA) was used in this study. Combimatrix is a highly flexible platform that allows for the synthesis of in situ oligos (35mers) through the use of an electrochemistry-based method. This innovative technology also allows us to reuse the same microarray several times. Traditional cDNA microarrays involve large amounts of primer design and PCR for preparation of amplicon probes to be used for microarray printing. This process can be cumbersome and time consuming. Compared to all other platforms, including cDNA microarray, the Combimatrix drastically reduces fabrication and analytic costs. Thus, this process is more rapid and convenient. The platform has established a complete protocol for genomic analyses from sample labeling to data extraction [39][41].The array contained 90000 in situ synthesized oligonucleotide probes. In total, six sequenced genomes were taken for analysis. Genomic information for each strain is summarized in Table 2. Genome alignments were performed by Combimatrix to obtain strain specific genes of each sequenced strain. We then took the whole genome of P12 as the reference sequence for tiling designation, which occupied about 70000 probes on the 90 k array. The sequences were first broken up into 100,000 bp blocks. We designed all possible probes for every 19 bp and selected the best one for each interval. At each position, a probe was extended until the Tm reached the desired Tm. Probes were then tested for quality, and the best probe (probe length 35∼40 mer) was chosen. Both strain-specific genes and plasmid genes were then chosen for tiling for the remaining 20000 probes based on the same criteria.

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Figure 4. Comparison of eight H. pylori strains based on strain specific genes of six sequenced strains.

Large variable regions were labeled with colored rectangles. Predicted gastric cancer strain specific regions were labeled with a red rectangle. General genomic variations among all strains were labeled with a green rectangle. A blue rectangle represents diverse regions obtained from comparison of gastric cancer strains and superficial gastritis strains. Corresponding coding proteins were briefly labeled at the bottom of each rectangle. GC vs SG denotes comparison between the two strains of gastric cancer and the two strains of superficial gastritis.

https://doi.org/10.1371/journal.pone.0038528.g004

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Table 4. Predicted variable genes based on strain specific genes of the six sequenced strains.

https://doi.org/10.1371/journal.pone.0038528.t004

Four micrograms of heated DNA from each H. pylori strain was labeled with Cy5-ULS using the Kreatech ULS array CGH Labeling kit (EA-005, Kreatech, Netherlands) according to the manufacturer’s instructions and then hybridized to the microarray. Experiments were performed according to CombiMatrix protocol. Microarrays were pre-hybridized with 6×SSPE containing 0.05% Tween-20, 5×Denhardt’s solution, and 100 ng salmon sperm DNA for 30 min at 50°C. The Cy5-ULS labeled DNA fragments were then hybridized in the hybridizing solution (6×SSPE and 0.05% SDS) by denaturing at 95°C for 3 min and then incubating for 16 h at 50°C. Post-hybridization wash steps were 6×SSPET for 5 min at 50°C, 3×SSPET for 1 min, 0.5×SSPET for 1 min, and PBST for 1 min at room temperature. After hybridization and imaging, the microarray was stripped using CustomArray™ Stripping Solution. The well known sequenced strain 26695 and an additional eight strains from Heilongjiang province were hybridized to the chips.

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Figure 5. Gene content analysis of TFS4 and TFS3 in eighty-four H. pylori isolates by PCR.

The presence of individual genes is indicated in red, and their absence in green. Non-specific amplicon is shown in black.

https://doi.org/10.1371/journal.pone.0038528.g005

Microarray Scanning and Statistical Analysis

Hybridized microarrays were covered with imaging solution and scanned with an Axon GenePix™ 4000B. All of the nine hybridizations were scanned at the same PMT value. The stripped microarray was also scanned with the same PMT gain value (475) to evaluate background noise as well as the stripping efficiency. Data was extracted by using Microarray_Imager_5.9.3 software. The foreground median of 635-nm signal intensities of each spot was used for the subsequent analysis. Genes that had at least five contiguous oligonucleotides with a minimum 635-nm intensity of 800 intensity units, and had at least one tile with 635-nm intensity >1200 intensity units were defined as positive. We defined background signal intensity as the median signal intensity of all spots locations that did not have any oligos. QC-oligoB-AS-3 spots were also included in the background. QC-oligoB-AS-3 spots were CombiMatrix quality control oligonucleotides that occur 459 times on the array. Since QC-oligoB-AS-3 does not align to the H. pylori genome, these spots could be considered for background calculation for further analysis. On each of the arrays, the background signal was <400 intensity units, indicating that our signal cutoff of 800 was sufficiently above background for identification. Based on the above described criteria for gene identification, information of probe location and corresponding hybridization signals were extracted for further analysis. For ease of analysis, all genes were separated into two independent files, one including genes located in the H. pylori P12 genome and another including strain specific genes in each of the other strains, which are named chromosome 1–6 (this also included P12 strain specific genes). Isolates of gastric cancer were represented as GC, isolates of gastric ulcers were represented as GU, isolates of chronic superficial gastritis were represented as SG, and isolates of atrophic gastritis were represented as AG. Signal comparison was performed between the two strains in GC, GU, SG, and AG. Comparison was also performed by GC vs GU, GU vs AG, GC vs SG, and AG vs SG. Signal ratios of two hybridized strains were log2 transformed and imported into a web tool ADaCGH, which was used for the analysis of microarray datasets to show gains and losses of genes between the two genomes. The data was centered and segmented in ADaCGH by employing a position-dependent segmentation algorithm CBS (circular binary segmentation) to partition data points into absent, present, and no change sequence segments [42], [43]. Chi-square was used to analyze the association of genes with disease by comparing one disease group (i.e., GC) with the other two groups (i.e., SG and GU), as well as to analyze the TFSS gene distributions among different disease groups. P value <0.05 was considered significant.

Microarray Data Deposition

MIAME compliant microarray data of this study has been deposited at the Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/) under series accession number GSE32107.

Validation of genes associated with diseases by PCR

The results for some variable genes found to be associated with diseases by microarray analysis were confirmed using gene-specific PCR. We preliminarily selected 25 such genes involved in two TFSS systems, a predicted 5.2 kb variable region, and an hrgA gene, which was reported to have a high occurrence rate in strains isolated from gastric cancer patients in East Asia. Specific primers were selected based on the sequences of these genes. To investigate the distribution of genes that were predicted as genomic distinctive regions, eighty-four strains were selected for PCR analysis of the 25 genes. A heatmap of type IV systems genes was created using Mev_4_0-2.

Results

Microarray Hybridization and Statistical Analysis

In order to test whether the established H. pylori microarray analysis system can accurately predict genomic distinction, we first analyzed strains 26695, HLJ005, and HLJ038 based on strain specific genes and 0–100 kb of the reference P12 genome sequence. As shown in Figure 1, six segments on the X-axis represent strain specific genes of the six sequenced genomes. Probes of segment one are strain specific genes of 26695. When comparing the hybridization signal of gastric cancer strain HLJ005 to 26695 with the web tool ADaCGH, almost all of these genes were predicted to be absent in HLJ005 (Figure 1 A). The same pattern was found in another gastric cancer strain HLJ038 (Figure 1 B).When comparing HLJ005 and HLJ038, only some minor variable probes were found in the six segments (Figure 1 C). These analyses indicate that this custom designed microarray platform accurately predicts gene absence or presence in different clinical H. pylori isolates. This was further validated by PCR to confirm a predicted 5.2 kb absent region both in gastric cancer strain HLJ038 and HLJ005 based on the 0–100 kb of the reference P12 chromosome (Figure 2).

Variable genes of the tested strains were first obtained based on the reference P12 genome sequence (Figure 3, Table 3). Twelve genomic regions with the most variable tiles among the eight strains are marked by a rectangle. Predicted gastric cancer strain specific regions were labeled with a red rectangle according to the comparison of GC vs SG and GC vs GU. Seven such areas were acquired, and encoded proteins were listed in Table 3 (DR1, 3, 4, 6, 8, 9, 12). The number of these variable genes present in the group of gastric cancer strains was statistically higher than those for the GU and SG strains (P<0.05). These regions mainly coded for proteins related to the type I R-M system, type II R-M system, type III R-M system, TFSS system, and hypothetical proteins. General genomic variations among all strains were labeled with a green rectangle. Seven such regions were identified (DR 1, 2, 4, 5, 7, 8, 11). No significant correlation was found for the unique absence or presence of TFS4 or TFS3. However, absence of both TFS3 and TFS4 system genes display significant variation comparing GC strains to GU, DU, or SG strains (P<0.05). Among the 25 strains that are absent for these two systems, 17 strains are GC strains (68%). No significant variation was found for the association of any gene cluster with special geography. In addition, cagPAI was also labeled with a green rectangle for its diversity among reported strains (DR5). However, cagPAI were conserved among the tested strains of this study. The blue rectangle represents diverse regions obtained from comparison of gastric cancer strain with superficial gastritis strain (DR10). Some of the corresponding coding proteins were briefly labeled at the bottom of each rectangle. GC vs SG denotes comparison among the two strains of gastric cancer and the two strains of superficial gastritis.

Comparison of eight H. pylori strains based on strain specific genes of six sequenced strains is shown in Figure 4. Twelve large variable regions are labeled with rectangles, including five red rectangles denoting predicted gastric cancer strain specific regions (DR1, 3, 4, 5, 12), three blue rectangles denoting diverse regions obtained from comparison of gastric cancer strains and superficial gastritis strains (DR 9, 10, 11), and five green rectangles denoting common variable genes among all strains (DR 1, 2, 6, 7, 8). These predicted variable genes based on strain specific genes of the six sequenced strains were listed in Table 4.

Gene Variation Confirmed by PCR

To further validate the microarray results, we performed PCR to confirm a predicted 5.2 kb absent region both in gastric cancer strain HLJ038 and HLJ005 based on the 0–100 kb of the reference P12 chromosome (Figure 2 A B). PCR results validated that the 5.2 kb region is absent in the two gastric cancer strains but present in 26695 (data not shown). As shown in Figure 2C, comparing 0–100 kb of HLJ005 and HLJ038 shows minor differences between the two GC strains. These scattered differing genes are suspected to be strain-specific genes of HLJ005 and HLJ038.

A heatmap of variable genes detected among the three H. pylori test strains was also confirmed using PCR. Green denotes absence of genes; red indicates presence of genes. The distinct regions of the three test strains were clustered with a dendrogram, which was constructed by hierarchical analysis of the presence or absence of genes. Amplification of some genes showing a weak PCR product band or a band of incorrect size are represented in black. One possible explanation for this is that sequence variation in these genes occurs in the primer binding region. The twenty variable genes of the TFSS3 and TFSS4 in the eight GC isolates observed by ADaCGH were confirmed by PCR, showing concordance with the microarray data. The prevalence of these genes in isolates from 76 additional patients was tested by PCR (Figure 5). These genes were found to be absent in 18 of 33 GC strains (55%). Other strains harbor two or more of these gene. These data support the association of the loss of these genes in isolates from GC patients.

Discussion

In the eight Chinese isolates studied by microarray, we found 14 significant variable regions when comparing GC isolates to SG or GU isolates based on the P12 reference genome (Figure 3, Table 2). These regions mainly coded for proteins related to the type I R-M system (DR3), type II R-M system (DR1), type III R-M system (DR6, DR12), TFSS system (DR4, DR11), and hypothetical proteins (DR8). These findings are consistent to those of previous reports. Previous research found a remarkable variety of restriction-modification (R-M) systems in H. pylori. Bacteria utilize R-M systems through conjugative plasmids or bacteriophages as a defense against invasion by foreign DNA. Recently, restriction–modification systems have been reported to be associated with H. pylori virulence. The best understood R-M system is the type II R-M family. Type II R-M systems include two enymes: one is a restriction endonuclease which cleaves DNA within a specific 4–8-bp sequence, while another is a methyltransferase which can specifically methylate DNA at adenine or cytosine residues. Bacteria can protect DNA from cleavage through this mechanism [44][48]. We identified a number of variable genes involved in these restriction-modification systems among the microarray tested strains. The results indicate a strong correlation between H. pylori R-M system and pathogenesis of gastric cancer. Further investigations involved in functional analysis of the R-M system are very necessary to demonstrate the potential mechanism.

A previous Chinese study, performed by Han, Y. H. et al, also analyzed the genomic variation of H. pylori isolates from patients with gastroduodenal diseases [34]. They found two diverse regions in the H. pylori genome that corresponded to plasticity zones (PZ) 1 and 2. Our results are partially consistent with one diverse region of their findings. This region comprises genes from HP0424 to HP0462. However in our study, we only identified genes in these regions from HP0440 to HP0445 and HP0456 to HP0462. For diverse region 2 from HP0984 to HP1009, we have not observed wide variation among our strains except for a minor difference of HP0993 and HP0994, which are predicted to be absent in GC strains HLJ005 and HLJ038 compared to the SG strain HLJ220. In addition to these distinctions, we found the other diverse region among strains based on 26695 strain specific genes. They are from HP1366 to HP1368 and encode type IIS restriction enzyme related proteins. For the other genes that were found by Han, Y. H. et al, such as HP0447, HP0704, and jhp0918, they claimed that certain genotypes had higher prevalence of these genes in DU or GC groups than in CG groups, but this was not inspected in our microarray that studied eight Heilongjiang province strains. These discrepancies may be due to the differences in strain selection. It is also possible that technical differences contribute to the discrepancies observed. Another previous comparative genomic study reported that genes located in the plasticity zones such as jhp0947 and jhp0949 are associated with disease [49][51]. For these genes, we also detected a small scattered variable region among the eight microarray tested strains. But we have not performed PCR tests in more strains for these genes. In the future, we will follow this work up with systematic analysis. Despite these variable genes described above, we found that the cag PAI was significantly conserved in the eight tested isolates from Heilongjiang province, which is consistent with the fact that cag PAI is geographically diverse.

The distribution of genes of type-IV secretion systems in Chinese isolates were also investigated in detail. H. pylori have at least three type-IV secretion systems (TFSS). The first type IV secretion system gene cluster is located in the cag pathogenicity island, which mediates the injection of the toxin CagA and is thought to be the most important apparatus that contributes to pathogenesis. Several studies have described and discussed the role of the cag-pathogenicity island encoded type IV secretion system in H. pylori pathogenesis [9][11]. However, the potential mechanism for cag PAI induced cancer is still under known. The second gene cluster is involved in a comB locus that confers competence for DNA transformation [52]. Recently, a third TFSS responsible for DNA conjugation has been demonstrated and discussed in various studies. This TFSS system helps H. pylori rapidly acquire new genetic features and adapt to changes in the environment [53][56]. We explored genes involving two such TFSS systems of P12 in our study. Consistent with previous studies, many genes in these systems are variably present (Figure 5). Although complete TFS3 or TFS4 type IV secretion systems were found in some strains (i.e., HLJ242), partial absence of type IV secretion system genes seem to be more common. None of the tested strains harbored the two TFSS system genes despite a possible failure to amplify virB7-1. All of our tested strains did not contain virB7-1; this is probably because the length of virB7-1 is only 117 bp. Therefore, it is difficult to design a pair of primers that efficiently amplify this gene target. Although no significant correlation was found for the unique absence or presence of TFS4 or TFS3, absence of both TFS3 and TFS4 system genes displayed significant variation comparing GC strains to GU, DU, or SG strains (P<0.05). It is intriguing that large proportions of GC strains in our study lost these two systems, which are reported to be involved in the transfer of genomic fragments and the restriction-modification system through a special mechanism. More thorough research is required to explore the potential function or mechanism for losing TFSS systems in GC isolates.

We also found one of the four genes with the 5.2 kb predicted variable segment, a gene encoding cytosine specific DNA methyltransferase, is present in 11 of 12 GC strains isolated from Shandong province (represented as YTC). This suggests that special genomic characteristics may exist in this group of strains. Based on the strain specific genes of the six sequenced genomes, several variable genes were identified including an hrgA gene (Figure 4, Table 3, DR6), which has been previously reported to be a strain-specific gene that might be associated with gastric cancer among H. pylori isolates from Asian patients [57]. For the distribution of hrgA in our 33 tested gastric cancer strains, 25 (76%) tested positive for the presence of this gene, which was higher than previously reported rates of prevalence (43%). 21 of the remaining 51 (41%) isolates of non-cancer patients were positive for the gene. There is no statistical significance for the distribution of hrgA in different diseases (Table 5). There are many additional variable genes that were screened by microarray among the tested strains. Validating each of these genes one by one by PCR would be laborious and be contrary to the goals of a microarray-based experiment, which is rapid and high throughput genomic analysis. Since the custom HP 90 k tiling microarray has been well designed, established, and evaluated in this study, a greater number of strains need to be analyzed by this tool in order to gather more detailed and reliable information about which variable genes contribute to different disease status.

We initially tried to cover all sequenced strains for probe design. At the time, only six strains had completed genome maps online. P12 was selected as a major tiling reference sequence since it is the longest. Strain specific genes of an additional five strains were also tiled to search for possible differences among the tested strains. To quickly evaluate the accuracy of this array design, we initially hybridized a well known sequenced strain 26695 and two strains isolated from two gastric cancer patients in Heilongjiang province. Paired comparison of these strains for a 0–100 kb region based on the P12 reference genome revealed several regions with genetic variation. Specific primers were designed for these genes, and PCR validation was performed in 26695, HLJ005, and HLJ038. Of the 12 genes tested, 11 were consistent with the microarray prediction(data not shown). For the strain specific genes of the six sequenced strains, our results precisely predicted that all strain specific genes of 26695 are actually present in 26695 compared to HLJ005 and HLJ038. These results indicate that the designed microarray can provide an accurate analysis for exploring genomic diversity among different HP strains.

The aim of this study was to search for genomic characteristics that may contribute to various digestive diseases. Strain selection is one of the most important aspects of this study because genomic diversity exists among strains of different geographic origin. To eliminate this interference, we selected eight strains that originated from a northeast province of China. Heilongjiang province has one of the highest incidence rates of gastric cancer. Our results show that comparison of the strains with the same diseases (HLJ005 vs HLJ038) have less variation than the strains with different diseases, which indicates that it is reasonable to further investigate more paired strains with different clinical diseases.

With the rapid development of next generation sequencing technology and reduced costs, microarrays will be completely replaced by sequencing in the future. However, no one can predict how long this change will take. We believe, that because of its low cost, microarray technology will continue to play an important role in genomic and expression level analyses of bacterial pathogens for several years. It also has easy handling and rapid time saving advantages. The established in situ synthesized high density oligo tiling microarray was successfully utilized in this study and can be used as a high throughput analytic tool for comparative genomics of H. pylori. Results of our study promote further understanding of specific disease-associated genes that can serve as novel biomarkers for identification of gastroduodenal diseases.

Author Contributions

Conceived and designed the experiments: YY JZ. Performed the experiments: YY BZ XT. Analyzed the data: YY. Contributed reagents/materials/analysis tools: YH LH MZ JF YG. Wrote the paper: YY.

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