HelicoBase: a Helicobacter genomic resource and analysis platform
© Choo et al.; licensee BioMed Central Ltd. 2014
Received: 9 January 2014
Accepted: 9 July 2014
Published: 16 July 2014
Helicobacter is a genus of Gram-negative bacteria, possessing a characteristic helical shape that has been associated with a wide spectrum of human diseases. Although much research has been done on Helicobacter and many genomes have been sequenced, currently there is no specialized Helicobacter genomic resource and analysis platform to facilitate analysis of these genomes. With the increasing number of Helicobacter genomes being sequenced, comparative genomic analysis on members of this species will provide further insights on their taxonomy, phylogeny, pathogenicity and other information that may contribute to better management of diseases caused by Helicobacter pathogens.
To facilitate the ongoing research on Helicobacter, a specialized central repository and analysis platform for the Helicobacter research community is needed to host the fast-growing amount of genomic data and facilitate the analysis of these data, particularly comparative analysis. Here we present HelicoBase, a user-friendly Helicobacter resource platform with diverse functionality for the analysis of Helicobacter genomic data for the Helicobacter research communities. HelicoBase hosts a total of 13 species and 166 genome sequences of Helicobacter spp. Genome annotations such as gene/protein sequences, protein function and sub-cellular localisation are also included. Our web implementation supports diverse query types and seamless searching of annotations using an AJAX-based real-time searching system. JBrowse is also incorporated to allow rapid and seamless browsing of Helicobacter genomes and annotations. Advanced bioinformatics analysis tools consisting of standard BLAST for similarity search, VFDB BLAST for sequence similarity search against the Virulence Factor Database (VFDB), Pairwise Genome Comparison (PGC) tool for comparative genomic analysis, and a newly designed Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomic analysis are also included to facilitate the analysis of Helicobacter genomic data.
HelicoBase offers access to a range of genomic resources as well as tools for the analysis of Helicobacter genome data. HelicoBase can be accessed at http://helicobacter.um.edu.my.
Helicobacter is a genus of Gram-negative bacteria possessing a characteristic spiral shape . In the past, they were classified as members of the Campylobacter genus, but the Helicobacter genus has been recognized since 1989; currently with 29 known species (H. acinonychis, H. anseris, H. aurati, H. bilis, H. bizzozeronii, H. brantae, H. canadensis, H. canis, H. cetorum, H. cholecystus, H. cinaedi, H. cynogastricus, H. felis, H. fennelliae, H. ganmani, H. hepaticus, H. mesocricetorum, H. marmotae, H. muridarum, H. mustelae, H. pametensis, H. pullorum, H. pylori, H. rappini, H. rodentium, H. salomonis, H. trogontum, H. typhlonius, H. winghamensis) [2, 3]. Helicobacter species have been found living in the lining of the upper gastrointestinal tract, as well as the liver of some birds and mammals . Helicobacter bacteria can be isolated from feces, saliva and dental plaque of some infected people which is consistent with known transmission routes [5–7]. The most widely known and well-studied species of the genus is H. pylori, a human pathogen which infects up to half of the human population . In general, most patients with H. pylori infections do not have specific clinical symptoms or signs . However, acute infection may appear as acute gastritis which may further develop into chronic gastritis if no treatment is given . H. pylori is also strongly associated with peptic ulcers, duodenitis and stomach cancer . H. pylori is a genetically diverse species that has co-evolved with the human race since their migration out of Africa 60,000 years ago , and subsequent geographic separation plus founder effects have resulted in distinct populations of bacterial strains that are specific for various geographical regions. In all, 7 populations and 3 subpopulations have been described: hpEurope (isolated from Europe, the Middle East, India and Iran), hpNEAfrica (isolated in Northeast Africa), hpAfrica1 (isolated from countries in Western Africa and South Africa), hpAfrica2 (so far only isolated from South Africa), hpAsia2 (isolated from Northern India and among isolates from Bangladesh, Thailand and Malaysia), hpSahul (from Australian Aboriginals and Papua New Guineans) and hpEastAsia with the subpopulations hspEAsia (from East Asians), hspMaori (from Taiwanese Aboriginals, Melanesians and Polynesians) and hspAmerind (Native Americans) [13–17].
With advances in next-generation sequencing technologies, many genomes of Helicobacter isolates have been sequenced by many laboratories [18–22]. The availability of these genome sequences from different sources has made it possible to get a deeper understanding of Helicobacter at the genomic level, for example through genome-wide comparative analyses. Such comparative analysis will have a profound impact on understanding the evolution, biology, diversity, evolution and pathogenicity of the Helicobacter spp. which may be useful in successfully managing Helicobacter-caused diseases.
Many specialized genomic databases or resources have been developed and published for well-studied human pathogens such as Pseudomonas Genome database [23, 24], Burkholderia Genome Database , Cyanobacteria Gene Annotation Database (CYORF)  and Mycobacterium abscessus Genome and Annotation Database (MabsBase) . But no such specialized genomic database is available for Helicobacter spp. despite the wealth of available data. Microbial Genome Database for Comparative Analysis (MBGD)  and the Integrated Microbial Genomes (IMG) system  do provide a wide array of microbial genomes including some Helicobacter strains for comparative genomics, but lack the virulence factor perspective for comparative pathogenomics. Another concern regarding most of the existing biological databases is their lack of user-friendly web interfaces, for example, allowing real-time and fast querying and browsing of genomic data.
To facilitate Helicobacter research, we have developed a specialized Helicobacter resource and analysis platform for the storage of the rapidly increasing genomic data of Helicobacter, which presents the data in a useful manner that is easy to access, and enables the analysis of these genomic data, particularly in the field of comparative genomics. The aims of HelicoBase are to provide a comprehensive set of genomic data and a set of useful analysis tools with diverse functionality for data analysis. For instance, HelicoBase is powered by two newly designed tools: PGC for pairwise genome comparison and PathoProT for comparative pathogenomics analysis. The AJAX-based real-time search feature and JBrowse  have also been integrated into HelicoBase to allow rapid and seamless searching and browsing of the Helicobacter genomic data and annotations. Here we provide an overview and describe some key features of HelicoBase.
Construction and content
List of Helicobacter species and genomes in HelicoBase
Number of draft genomes
Number of complete genomes
HelicoBase currently accumulates a total of 166 genome sequences from 13 Helicobacter species, which were downloaded and compiled from the National Center for Biotechnology Information (NCBI) [31, 32]. To have consistent annotations for comparative analyses, we re-annotate all genomes with the Rapid Annotation using Subsystem Technology (RAST) pipeline . RAST has been successfully tested in annotating both complete and draft genomes of archaea and bacteria in the recent review by Liu et al. . Using this well-established pipeline, functional elements like protein-encoding genes, rRNAs, tRNAs and pseudogenes can be predicted in each Helicobacter genome. All genome annotations were stored in our MySQL database. Currently HelicoBase has stored 280,550 coding sequences (CDSs), 6,683 rRNAs and 5,965 tRNA genes predicted in all 166 genomes of the 13 Helicobacter species. Among annotations generated by RAST include ORF type, functional classification, chromosomal position, nucleotide length, amino acid length and strand. Other annotations like subcellular localisation, hydrophobicity and molecular weight of the RAST-predicted proteins are also provided. For subcellular localization prediction, we used PSORTb version 3.0, a well-established software to determine the subcellular localization of putative proteins for prokaryotes . In HelicoBase, the 280,550 RAST-predicted CDSs were categorised by PSORTb into 5 different categories such as cytoplasmic, cytoplasmic membrane, extracellular, outer membrane and periplasmic (Additional file 1: Figure S1).
Real-time data searching feature
Pairwise genome comparison (PGC) tool: information aesthetic for comparative genomics
HelicoBase is not just designed as a genomic data repository, but also aims to be an analysis platform, particularly to facilitate comparative analysis of multiple Helicobacter genomes. The PGC tool is a newly designed in-house comparative analysis tool allowing users to compare two selected Helicobacter genomes and display the results in a circular layout on the fly. Through the provided web interface of PGC, users can choose two genomes of interest in HelicoBase for comparison. Alternatively, users can use an online custom web form to upload their own Helicobacter genome sequence for comparison with a Helicobacter genome in HelicoBase.
Although a similar tool, called Circoletto  is available, PGC has some advantages over this online tool. Firstly, while Circoletto aligns sequences using BLAST (local alignment) the alignment algorithm used in PGC is based on the NUCmer (global alignment) package in MUMmer, which is suitable for large-scale and rapid genome alignment. Secondly, PGC provides many useful options for users. For instance, a user can adjust settings such as minimum percent genome identity (%), merging of links/ribbons according to MT, and the removal of links according to the user-defined LT through the provided online form. Thirdly, in the circular layout generated by PGC, a histogram track showing the percentage of mapped regions along the genome is provided. This track is very useful and helps users to identify putative indels and repetitive regions in the Helicobacter genomes. Additional file 2: Figure S2B shows how the data in the histogram track is calculated. Besides the Circoletto, RCircos is another tool with a similar function to PGC, which was developed by Zhang et al. . RCircos was developed using R packages that come with R base installation. The package supports Circos 2D data track plots such as scatter, line, histogram, heat map, tile, connectors, links, and text labels . However, unlike PGC which has a user-friendly interface and is easy to use without knowledge in programming, users need to have knowledge in the R programming language in order to run the RCircos and no user-friendly interface is provided.
A newly designed pathogenomics profiling tool (PathoProT) for comparative pathogenomics analysis
Virulence factors are molecules present in bacteria, which are responsible for causing disease in the host or converting non-pathogenic bacteria into pathogens [41, 42]. The availability of sequenced genomes of different Helicobacter species makes the comparative analyses of virulence factors in the Helicobacter pathogen genomes feasible and may provide new insights into pathogen evolution and the diverse virulence strategies employed. Understanding the pathogenic mechanisms of these pathogens would aid in the treatment and prevention of Helicobacter-caused diseases.
Figure 6, gives a bird eye’s view of the virulence genes that are present and widely distributed across all Helicobacter species. In general, it is clearly shows that H. pylori strains have more virulence genes compared to other species, which may explain their high virulence [46, 47].
Interestingly, H. hepaticus ATCC51449 harbours three unique virulence genes, which are cdtA, cdtB and cdtC. The cytolethal distending toxins (CDTs) constitute the most recently discovered family of bacterial protein toxins. CDTs are unique among bacterial toxins as they have the ability to induce DNA double strand breaks in both proliferating and non-proliferating cells, thereby causing irreversible cell cycle arrest or death of the target cells . It has been shown that CDTs encoded by the three genes, cdtA, cdtB, and cdtC are required for cytotoxicity . When cdtA, cdtB, and cdtC are present together, the CDTs interact with one another to form an active tripartite holotoxin. The presence of these three genes in H. hepaticus ATCC51449 is supported by a recent study by Vincent et al., who identified these virulence genes in H. hepaticus species .
In summary, we have demonstrated that PathoProT can be used to identify virulence genes in Helicobacter strains by sequence homology. Moreover, comparative pathogenomics analysis can be easily performed to compare strains/groups of strains e.g. non-pathogenic strains versus pathogenic strains, which can give better insights into the biology, evolution and virulence of the Helicobacter strains of interest. In other words, PathoProT can be used to answer interesting biological questions including what are the conserved virulence genes in a group of Helicobacter strains and enables strain-specific/group-specific virulence genes to be easily viewed in the generated heat map.
BLAST is included in HelicoBase to allow for easy similarity searching for sequences of interest . The built-in BLAST in HelicoBase provides two main functions: (1) standard BLAST which will search the provided query sequence against genome or ORF sequences (either nucleotide or protein) in HelicoBase; (2) VFDB BLAST which searches the provided query sequence against the Virulence Factor Database (VFDB) [43, 44, 52]. Users can use VFDB BLAST if they want to determine whether their sequence of interest is a virulence gene based on sequence homology.
HelicoBase development and implementation
HelicoBase rests on MySQL version 14.12 (http://www.mysql.com) and was hosted using Ubuntu Lucid 10.04 Web server application (http://www.ubuntu.com). Development used a combination of PHP 5.3 and Perl 5 languages, with Codelgniter 2.1.3 framework for web tier and Twitter Bootstrap front-end framework for the presentation layer.
The web server architecture was designed to be scalable and combined with a flexible PHP coding interface enables users with different devices to connect to HelicoBase in a fast and readable manner. For tools such as BLAST, VFDB BLAST, PathoProT, and PGC users can submit their analysis jobs through the provided interfaces and these jobs will be submitted to the cluster server in a firewall-enabled secure process. The job scheduler in turn makes it possible for the application server to process the submitted jobs in a fair and parallel manner with fast processing speed. Our cluster computer (5 nodes, 12 CPUs for each node and 625GB of RAM in total) prompts the database server to run in a fast fibre-optic internal network to retrieve necessary information needed to process the submitted jobs. Meanwhile, our MySQL data structures were formed in a manner that supports fast and localized searching which makes the user-website interactions fast and also user-friendly. To construct HelicoBase, we used the several software components: RAST , BLAST , MUMmer , PSORTb , Circos  and JBrowse .
Discussion and conclusion
With advances in high-throughput sequencing technologies, it is imperative that the abundant data generated can be easily accessible for analysis. With HelicoBase we aim to provide a one-stop resource platform that will make it easy to access and analyse whole-genome genomic data and information for Helicobacter spp. through an organised and user-friendly interface. PGC and PathoProT are some of the bioinformatics tools for comparative analysis implemented in HelicoBase which allow researchers to conveniently assimilate and explore the data in an intuitive manner.
HelicoBase will be updated from time to time as more genome sequences of Helicobacter spp. become available. To accelerate the development of HelicoBase, we encourage researchers to email us at email@example.com if they would like to share their annotations and related data with us. Suggestions on improving HelicoBase are most welcome.
Availability and requirements
HelicoBase is available online at http://helicobacter.um.edu.my. All sequences and annotations described in this paper can be downloaded from that site.
We would like to thank Professor Dr Robert White (Department of Physiology, Development and Neuroscience, University of Cambridge) for his assistance in proofreading the manuscript. We also thank Amir Hessam Yazdi for providing IT support in this project. Special thanks to Aini Mohamed Yusoff for helping us to compile the genome sequences.
This project was funded by University of Malaya and Ministry of Education (MOHE), Malaysia under the High Impact Research (HIR) grant UM.C/HIR/MOHE/08.
- Sycuro LK, Pincus Z, Gutierrez KD, Biboy J, Stern CA, Vollmer W, Salama NR: Peptidoglycan crosslinking relaxation promotes< i> Helicobacter pylori </i>’s helical shape and stomach colonization. Cell. 2010, 141: 822-833.PubMed CentralPubMedView ArticleGoogle Scholar
- Dick JD: Helicobacter (Campylobacter) pylori: a new twist to an old disease. Annu Rev Microbiol. 1990, 44: 249-269.PubMedView ArticleGoogle Scholar
- Owen R: Helicobacter-species classification and identification. Br Med Bull. 1998, 54: 17-30.PubMedView ArticleGoogle Scholar
- Fox JG, Lee A: The role of Helicobacter species in newly recognized gastrointestinal tract diseases of animals. Lab Anim Sci. 1997, 47: 222-255.PubMedGoogle Scholar
- Goodman KJ, Correa P: The transmission of Helicobacter pylori. A critical review of the evidence. Int J Epidemiol. 1995, 24: 875-887.PubMedView ArticleGoogle Scholar
- Axon A: Review article is Helicobacter pylori transmitted by the gastro‒oral route?. Aliment Pharmacol Ther. 1995, 9: 585-588.PubMedView ArticleGoogle Scholar
- Dowsett S, Kowolik M: Oral Helicobacter pylori: can we stomach it?. Crit Rev Oral Biol Med. 2003, 14: 226-233.PubMedView ArticleGoogle Scholar
- Brown LM: Helicobacter pylori: epidemiology and routes of transmission. Epidemiol Rev. 2000, 22: 283-PubMedView ArticleGoogle Scholar
- Kuipers E, Nelis G, Klinkenberg-Knol E, Snel P, Goldfain D, Kolkman J, Festen H, Dent J, Zeitoun P, Havu N: Cure of Helicobacter pylori infection in patients with reflux oesophagitis treated with long term omeprazole reverses gastritis without exacerbation of reflux disease: results of a randomised controlled trial. Gut. 2004, 53: 12-20.PubMed CentralPubMedView ArticleGoogle Scholar
- Sipponen P, Hyvärinen H: Role of Helicobacter pylori in the pathogenesis of gastritis, peptic ulcer and gastric cancer. Scand J Gastroenterol. 1993, 28: 3-6.View ArticleGoogle Scholar
- Kuipers E: Helicobacter pylori and the risk and management of associated diseases: gastritis, ulcer disease, atrophic gastritis and gastric cancer. Aliment Pharmacol Ther. 1997, 11: 71-88.PubMedView ArticleGoogle Scholar
- Linz B, Balloux F, Moodley Y, Manica A, Liu H, Roumagnac P, Falush D, Stamer C, Prugnolle F, van der Merwe SW: An African origin for the intimate association between humans and Helicobacter pylori. Nature. 2007, 445: 915-918.PubMed CentralPubMedView ArticleGoogle Scholar
- Falush D, Wirth T, Linz B, Pritchard JK, Stephens M, Kidd M, Blaser MJ, Graham DY, Vacher S, Perez-Perez GI: Traces of human migrations in Helicobacter pylori populations. Science. 2003, 299: 1582-1585.PubMedView ArticleGoogle Scholar
- Achtman M, Azuma T, Berg DE, Ito Y, Morelli G, Pan ZJ, Suerbaum S, Thompson SA, Van Der Ende A, Van Doorn LJ: Recombination and clonal groupings within Helicobacter pylori from different geographical regions. Mol Microbiol. 1999, 32: 459-470.PubMedView ArticleGoogle Scholar
- Moodley Y, Linz B, Yamaoka Y, Windsor HM, Breurec S, Wu J-Y, Maady A, Bernhöft S, Thiberge J-M, Phuanukoonnon S: The peopling of the Pacific from a bacterial perspective. Science. 2009, 323: 527-530.PubMed CentralPubMedView ArticleGoogle Scholar
- Devi SM, Ahmed I, Francalacci P, Hussain MA, Akhter Y, Alvi A, Sechi LA, Mégraud F, Ahmed N: Ancestral European roots of Helicobacter pylori in India. BMC Genomics. 2007, 8: 184-PubMed CentralPubMedView ArticleGoogle Scholar
- Tay CY, Mitchell H, Dong Q, Goh K-L, Dawes IW, Lan R: Population structure of Helicobacter pylori among ethnic groups in Malaysia: recent acquisition of the bacterium by the Malay population. BMC Microbiol. 2009, 9: 126-PubMed CentralPubMedView ArticleGoogle Scholar
- Duncan SS, Bertoli MT, Kersulyte D, Valk PL, Tamma S, Segal I, McClain MS, Cover TL, Berg DE: Genome sequences of three hpAfrica2 strains of Helicobacter pylori. Genome Announc. 2013, 1: e00729-00713-View ArticleGoogle Scholar
- Behrens W, Bönig T, Suerbaum S, Josenhans C: Genome sequence of Helicobacter pylori hpEurope strain N6. J Bacteriol. 2012, 194: 3725-3726.PubMed CentralPubMedView ArticleGoogle Scholar
- Uchiyama J, Takeuchi H, Kato S-i, Takemura-Uchiyama I, Ujihara T, Daibata M, Matsuzaki S: Complete genome sequences of two Helicobacter pylori bacteriophages isolated from Japanese patients. J Virol. 2012, 86: 11400-11401.PubMed CentralPubMedView ArticleGoogle Scholar
- Clancy CD, Forde BM, Moore SA, O’Toole PW: Draft genome sequences of Helicobacter pylori strains 17874 and P79. J Bacteriol. 2012, 194: 2402-2402.PubMed CentralPubMedView ArticleGoogle Scholar
- Goto T, Ogura Y, Hirakawa H, Tomida J, Morita Y, Akaike T, Hayashi T, Kawamura Y: Complete genome sequence of Helicobacter cinaedi strain PAGU611, isolated in a case of human bacteremia. J Bacteriol. 2012, 194: 3744-3745.PubMed CentralPubMedView ArticleGoogle Scholar
- Winsor GL, Van Rossum T, Lo R, Khaira B, Whiteside MD, Hancock RE, Brinkman FS: Pseudomonas genome database: facilitating user-friendly, comprehensive comparisons of microbial genomes. Nucleic Acids Res. 2009, 37: D483-D488.PubMed CentralPubMedView ArticleGoogle Scholar
- Winsor GL, Lam DK, Fleming L, Lo R, Whiteside MD, Nancy YY, Hancock RE, Brinkman FS: Pseudomonas genome database: improved comparative analysis and population genomics capability for Pseudomonas genomes. Nucleic Acids Res. 2011, 39: D596-D600.PubMed CentralPubMedView ArticleGoogle Scholar
- Winsor GL, Khaira B, Van Rossum T, Lo R, Whiteside MD, Brinkman FS: The Burkholderia genome database: facilitating flexible queries and comparative analyses. Bioinformatics. 2008, 24: 2803-2804.PubMed CentralPubMedView ArticleGoogle Scholar
- Furumichi M, Sato Y, Omata T, Ikeuchi M, Kanehisa M: CYORF: community annotation of cyanobacteria genes. Genome Inform Ser. 2002, 13: 402-403.Google Scholar
- Heydari H, Wee WY, Lokanathan N, Hari R, Yusoff AM, Beh CY, Yazdi AH, Wong GJ, Ngeow YF, Choo SW: MabsBase: a mycobacterium abscessus genome and annotation database. PLoS ONE. 2013, 8: e62443-PubMed CentralPubMedView ArticleGoogle Scholar
- Uchiyama I: MBGD: microbial genome database for comparative analysis. Nucleic Acids Res. 2003, 31: 58-62.PubMed CentralPubMedView ArticleGoogle Scholar
- Markowitz VM, Chen I-MA, Palaniappan K, Chu K, Szeto E, Grechkin Y, Ratner A, Jacob B, Huang J, Williams P: IMG: the integrated microbial genomes database and comparative analysis system. Nucleic Acids Res. 2012, 40: D115-D122.PubMed CentralPubMedView ArticleGoogle Scholar
- Skinner ME, Uzilov AV, Stein LD, Mungall CJ, Holmes IH: JBrowse: a next-generation genome browser. Genome Res. 2009, 19: 1630-1638.PubMed CentralPubMedView ArticleGoogle Scholar
- Pruitt KD, Tatusova T, Maglott DR: NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2007, 35: D61-D65.PubMed CentralPubMedView ArticleGoogle Scholar
- Pruitt KD, Tatusova T, Maglott DR: NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2005, 33: D501-D504.PubMed CentralPubMedView ArticleGoogle Scholar
- Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, Formsma K, Gerdes S, Glass EM, Kubal M: The RAST server: rapid annotations using subsystems technology. BMC Genomics. 2008, 9: 75-PubMed CentralPubMedView ArticleGoogle Scholar
- Liu Z, Ma H, Goryanin I: A semi-automated genome annotation comparison and integration scheme. BMC Bioinformatics. 2013, 14: 172-PubMed CentralPubMedView ArticleGoogle Scholar
- Nancy YY, Wagner JR, Laird MR, Melli G, Rey S, Lo R, Dao P, Sahinalp SC, Ester M, Foster LJ: PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics. 2010, 26: 1608-1615.View ArticleGoogle Scholar
- Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, Salzberg SL: Versatile and open software for comparing large genomes. Genome Biol. 2004, 5: R12-PubMed CentralPubMedView ArticleGoogle Scholar
- Krzywinski M, Schein J, Birol İ, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra MA: Circos: an information aesthetic for comparative genomics. Genome Res. 2009, 19: 1639-1645.PubMed CentralPubMedView ArticleGoogle Scholar
- Zhou Y, Liang Y, Lynch KH, Dennis JJ, Wishart DS: PHAST: a fast phage search tool. Nucleic Acids Res. 2011, 39: W347-W352.PubMed CentralPubMedView ArticleGoogle Scholar
- Zhang H, Meltzer P, Davis S: RCircos: an R package for Circos 2D track plots. BMC Bioinformatics. 2013, 14: 1-5.View ArticleGoogle Scholar
- Zhang H, Zhang MH, Plot RCI, Point RD, Plot RGC: Package ‘RCircos’. 2013Google Scholar
- Litwin CM, Calderwood S: Role of iron in regulation of virulence genes. Clin Microbiol Rev. 1993, 6: 137-149.PubMed CentralPubMedGoogle Scholar
- Ochman H, Lawrence JG, Groisman EA: Lateral gene transfer and the nature of bacterial innovation. Nature. 2000, 405: 299-304.PubMedView ArticleGoogle Scholar
- Yang J, Chen L, Sun L, Yu J, Jin Q: VFDB 2008 release: an enhanced web-based resource for comparative pathogenomics. Nucleic Acids Res. 2008, 36: D539-D542.PubMed CentralPubMedView ArticleGoogle Scholar
- Chen L, Xiong Z, Sun L, Yang J, Jin Q: VFDB 2012 update: toward the genetic diversity and molecular evolution of bacterial virulence factors. Nucleic Acids Res. 2012, 40: D641-D645.PubMed CentralPubMedView ArticleGoogle Scholar
- Westesson O, Skinner M, Holmes I: Visualizing next-generation sequencing data with JBrowse. Brief Bioinform. 2013, 14: 172-177.PubMed CentralPubMedView ArticleGoogle Scholar
- Covacci A, Telford JL, Del Giudice G, Parsonnet J, Rappuoli R: Helicobacter pylori virulence and genetic geography. Science. 1999, 284: 1328-1333.PubMedView ArticleGoogle Scholar
- Kusters JG, van Vliet AH, Kuipers EJ: Pathogenesis of Helicobacter pylori infection. Clin Microbiol Rev. 2006, 19: 449-490.PubMed CentralPubMedView ArticleGoogle Scholar
- Thelestam M: Cytolethal distending toxins. Reviews of physiology, biochemistry and pharmacology. 2005, Springer, 111-133.View ArticleGoogle Scholar
- Lara-Tejero M, Galan JE: CdtA, CdtB, and CdtC form a tripartite complex that is required for cytolethal distending toxin activity. Infect Immun. 2001, 69: 4358-4365.PubMed CentralPubMedView ArticleGoogle Scholar
- Young VB, Knox KA, Schauer DB: Cytolethal distending toxin sequence and activity in the enterohepatic pathogen Helicobacter hepaticus. Infect Immun. 2000, 68: 184-191.PubMed CentralPubMedView ArticleGoogle Scholar
- Ye J, McGinnis S, Madden TL: BLAST: improvements for better sequence analysis. Nucleic Acids Res. 2006, 34: W6-W9.PubMed CentralPubMedView ArticleGoogle Scholar
- Chen L, Yang J, Yu J, Yao Z, Sun L, Shen Y, Jin Q: VFDB: a reference database for bacterial virulence factors. Nucleic Acids Res. 2005, 33: D325-D328.PubMed CentralPubMedView ArticleGoogle Scholar
- Delcher AL, Salzberg SL, Phillippy AM: Using MUMmer to identify similar regions in large sequence sets. Curr Protoc Bioinformatics. 2003, Chapter 10: Unit 10 13-Google Scholar
- Gardy JL, Spencer C, Wang K, Ester M, Tusnady GE, Simon I, Hua S, Lambert C, Nakai K, Brinkman FS: PSORT-B: improving protein subcellular localization prediction for Gram-negative bacteria. Nucleic Acids Res. 2003, 31: 3613-3617.PubMed CentralPubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.