AMRColab - a user-friendly antimicrobial resistance detection and visualization tool.

Antimicrobial resistance (AMR) poses a significant threat to global public health, with the potential to cause millions of deaths annually by 2050. Effective surveillance of AMR pathogens is crucial for monitoring and predicting their behaviour in response to antibiotics. However, many public health professionals lack the necessary bioinformatics skills and resources to analyse pathogen genomes effectively. To address this challenge, we developed AMRColab, an open-access bioinformatics analysis suite hosted on Google Colaboratory. AMRColab enables users with limited or no bioinformatics training to detect and visualize AMR determinants in pathogen genomes using a 'plug-and-play' approach. The platform integrates established bioinformatics tools such as AMRFinderPlus and hAMRonization, allowing users to analyse, compare and visualize trends in AMR pathogens easily. A trial run using methicillin-resistant Staphylococcus aureus (MRSA) strains demonstrated AMRColab's effectiveness in identifying AMR determinants and facilitating comparative analysis across strains. A workshop was conducted and feedback from participants indicated high confidence in using AMRColab and a willingness to incorporate it into their research. AMRColab's user-friendly interface and modular design make it accessible to a diverse audience, including medical laboratory technologists, medical doctors and public health scientists, regardless of their bioinformatics expertise. Future improvements to AMRColab will include enhanced visualization tools, multilingual support and the establishment of an online community platform. AMRColab represents a significant step towards democratizing AMR surveillance and empowering public health professionals to combat AMR effectively.

Desiccation tolerance and reduced antibiotic resistance: Key drivers in ST239-III to ST22-IV MRSA clonal replacement at a Malaysian teaching hospital.

Molecular surveillance of methicillin-resistant Staphylococcus aureus (MRSA) isolated from Hospital Canselor Tuanku Muhriz (HCTM), a Malaysian teaching hospital revealed clonal replacement events of SCCmec type III-SCCmercury to SCCmec type IV strains before the year 2017; however, the reasons behind this phenomenon are still unclear. This study aimed to identify factors associated with the clonal replacement using genomic sequencing and phenotypic investigations (antibiogram profiling, growth rate and desiccation tolerance determination, survival in vancomycin sub-minimum inhibitory concentration (MIC) determination) of representative HCTM MRSA strains isolated in four-year intervals from 2005 - 2017 (n = 16). HCTM Antimicrobial Stewardship (AMS) and Infection Prevention and Control (IPC) policies were also reviewed. Phylogenetic analyses revealed the presence of 3 major MRSA lineages: ST239-III, ST22-IV and ST6-IV; MRSAs with the same STs shared similar core and accessory genomes. Majority of the ST239-III strains isolated in earlier years of the surveillance (2005, 2009 and 2013) were resistant to many antibiotics and harboured multiple AMR and virulence genes compared to ST22-IV and ST6-IV strains (isolated in 2013 and 2017). Interestingly, ST22-IV and ST6-IV MRSAs grew significantly faster and were more resistant to desiccation than ST239-III (p < 0.05), even though the later clone survived better post-vancomycin exposure. Intriguingly, ST22-IV was outcompeted by ST239-III in broth co-cultures; though it survived better when desiccated together with ST239-III. Higher desiccation tolerance and fewer carriage of AMR genes by ST22-IV, together with reduction of antibiotic selection pressure in HCTM (due to AMS and IPC policies) during 2005 - 2017 may have provided the clone a competitive edge in replacing the previously dominant ST239-III in HCTM. This study highlights the importance of MRSA surveillance for a clearer picture of circulating clones and clonal changes. To our knowledge, this is the first genomic epidemiology study of MRSA in Malaysia, which will serve as baseline genomic data for future surveillance.

Deciphering the genetic landscape of obesity: a data-driven approach to identifying plausible causal genes and therapeutic targets.

OBJECTIVES: Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. However, identifying the causal genes, pathways, and tissues/cell types responsible for these associations remains a challenge, and standardized analysis workflows are lacking. Additionally, due to limited treatment options for obesity, there is a need for the development of new pharmacological therapies. This study aimed to address these issues by performing step-wise utilization of knowledgebase for gene prioritization and assessing the potential relevance of key obesity genes as therapeutic targets. METHODS AND RESULTS: First, we generated a list of 28,787 obesity-associated SNPs from the publicly available GWAS dataset (approximately 800,000 individuals in the GIANT meta-analysis). Then, we prioritized 1372 genes with significant in silico evidence against genomic and transcriptomic data, including transcriptionally regulated genes in the brain from transcriptome-wide association studies. In further narrowing down the gene list, we selected key genes, which we found to be useful for the discovery of potential drug seeds as demonstrated in lipid GWAS separately. We thus identified 74 key genes for obesity, which are highly interconnected and enriched in several biological processes that contribute to obesity, including energy expenditure and homeostasis. Of 74 key genes, 37 had not been reported for the pathophysiology of obesity. Finally, by drug-gene interaction analysis, we detected 23 (of 74) key genes that are potential targets for 78 approved and marketed drugs. CONCLUSIONS: Our results provide valuable insights into new treatment options for obesity through a data-driven approach that integrates multiple up-to-date knowledgebases.

Gene-regulation modules in nonalcoholic fatty liver disease revealed by single-nucleus ATAC-seq.

We investigated the progression of nonalcoholic fatty liver disease from fatty liver to steatohepatitis using single-nucleus and bulk ATAC-seq on the livers of rats fed a high-fat diet (HFD). Rats fed HFD for 4 wk developed fatty liver, and those fed HFD for 8 wk further progressed to steatohepatitis. We observed an increase in the proportion of inflammatory macrophages, consistent with the pathological progression. Utilizing machine learning, we divided global gene regulation into modules, wherein transcription factors within a module could regulate genes within the same module, reaffirming known regulatory relationships between transcription factors and biological processes. We identified core genes-central to co-expression and protein-protein interaction-for the biological processes discovered. Notably, a large part of the core genes overlapped with genes previously implicated in nonalcoholic fatty liver disease. Single-nucleus ATAC-seq, combined with data-driven statistical analysis, offers insight into in vivo global gene regulation as a combination of modules and assists in identifying core genes of relevant biological processes.

Diversity and Dissemination of Methicillin-Resistant Staphylococcus aureus (MRSA) Genotypes in Southeast Asia.

Methicillin-resistant Staphylococcus aureus (MRSA) is a successful pathogen that has achieved global dissemination, with high prevalence rates in Southeast Asia. A huge diversity of clones has been reported in this region, with MRSA ST239 being the most successful lineage. Nonetheless, description of MRSA genotypes circulating in the Southeast Asia region has, until now, remained poorly compiled. In this review, we aim to provide a better understanding of the molecular epidemiology and distribution of MRSA clones in 11 Southeast Asian countries: Singapore, Malaysia, Thailand, Vietnam, Cambodia, Lao People's Democratic Republic (PDR), Myanmar, Philippines, Indonesia, Brunei Darussalam, and Timor-Leste. Notably, while archaic multidrug-resistant hospital-associated (HA) MRSAs, such as the ST239-III and ST241-III, were prominent in the region during earlier observations, these were then largely replaced by the more antibiotic-susceptible community-acquired (CA) MRSAs, such as ST22-IV and PVL-positive ST30-IV, in recent years after the turn of the century. Nonetheless, reports of livestock-associated (LA) MRSAs remain few in the region.

Draft Genome Sequences of Four Methicillin-Resistant Staphylococcus aureus Strains (M080_2017, M106_2017, M181_2017, and M191_2017), Isolated from a Malaysian Teaching Hospital.

Draft genome sequences were obtained for four methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from various wards of the Hospital Canselor Tuanku Muhriz (HCTM), Kuala Lumpur, Malaysia, in 2017. Using different bioinformatics tools, we annotated the draft genomes and identified multiple antimicrobial resistance genes.

Transcriptomic Response in the Heart and Kidney to Different Types of Antihypertensive Drug Administration.

Certain classes of antihypertensive drug may exert specific, blood pressure (BP)-independent protective effects on end-organ damages such as left ventricular hypertrophy, although the overall evidence has not been definitive in clinical trials. To unravel antihypertensive drug-induced gene expression changes that are potentially related to the amelioration of end-organ damages, we performed in vivo phenotypic evaluation and transcriptomic analysis on the heart and the kidney, with administration of antihypertensive drugs to two inbred strains (ie, hypertensive and normotensive) of rats. We chose 6 antihypertensive classes: enalapril (angiotensin-converting enzyme inhibitor), candesartan (angiotensin receptor blocker), hydrochlorothiazide (diuretics), amlodipine (calcium-channel blocker), carvedilol (vasodilating ß-blocker), and hydralazine. In the tested rat strains, 4 of 6 drugs, including 2 renin-angiotensin system inhibitors, were effective for BP lowering, whereas the remaining 2 drugs were not. Besides BP lowering, there appeared to be some interdrug heterogeneity in phenotypic changes, such as suppressed body weight gain and body weight-adjusted heart weight reduction. For the transcriptomic response, a considerable number of genes showed prominent mRNA expression changes either in a BP-dependent or BP-independent manner with substantial diversity between the target organs. Noticeable changes of mRNA expression were induced particularly by renin-angiotensin system blockade, for example, for genes in the natriuretic peptide system (Nppb and Corin) in the heart and for those in the renin-angiotensin system/kallikrein-kinin system (Ren and rat Klk1 paralogs) and those related to calcium ion binding (Calb1 and Slc8a1) in the kidney. The research resources constructed here will help corroborate occasionally inconclusive evidence in clinical settings.

Parvimonas micra, Peptostreptococcus stomatis, Fusobacterium nucleatum and Akkermansia muciniphila as a four-bacteria biomarker panel of colorectal cancer.

Dysbiosis of the gut microbiome has been associated with the pathogenesis of colorectal cancer (CRC). We profiled the microbiome of gut mucosal tissues from 18 CRC patients and 18 non-CRC controls of the UKM Medical Centre (UKMMC), Kuala Lumpur, Malaysia. The results were then validated using a species-specific quantitative PCR in 40 CRC and 20 non-CRC tissues samples from the UMBI-UKMMC Biobank. Parvimonas micra, Fusobacterium nucleatum, Peptostreptococcus stomatis and Akkermansia muciniphila were found to be over-represented in our CRC patients compared to non-CRC controls. These four bacteria markers distinguished CRC from controls (AUROC = 0.925) in our validation cohort. We identified bacteria species significantly associated (cut-off value of > 5 fold abundance) with various CRC demographics such as ethnicity, gender and CRC staging; however, due to small sample size of the discovery cohort, these results could not be further verified in our validation cohort. In summary, Parvimonas micra, Fusobacterium nucleatum, Peptostreptococcus stomatis and Akkermansia muciniphila were enriched in our local CRC patients. Nevertheless, the roles of these bacteria in CRC initiation and progression remains to be investigated.

Proteogenomics: From next-generation sequencing (NGS) and mass spectrometry-based proteomics to precision medicine.

One of the best-established area within multi-omics is proteogenomics, whereby the underpinning technologies are next-generation sequencing (NGS) and mass spectrometry (MS). Proteogenomics has contributed significantly to genome (re)-annotation, whereby novel coding sequences (CDS) are identified and confirmed. By incorporating in-silico translated genome variants in protein database, single amino acid variants (SAAV) and splice proteoforms can be identified and quantified at peptide level. The application of proteogenomics in cancer research potentially enables the identification of patient-specific proteoforms, as well as the association of the efficacy or resistance of cancer therapy to different mutations. Here, we discuss how NGS/TGS data are analyzed and incorporated into the proteogenomic framework. These sequence data mainly originate from whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. We explain two major strategies for sequence analysis i.e., de novo assembly and reads mapping, followed by construction of customized protein databases using such data. Besides, we also elaborate on the procedures of spectrum to peptide sequence matching in proteogenomics, and the relationship between database size on the false discovery rate (FDR). Finally, we discuss the latest development in proteogenomics-assisted precision oncology and also challenges and opportunities in proteogenomics research.

Connecting Proteomics to Next-Generation Sequencing: Proteogenomics and Its Current Applications in Biology.

Understanding the relationship between genotypes and phenotypes is essential to disentangle biological mechanisms and to unravel the molecular basis of diseases. Genes and proteins are closely linked in biological systems. However, genomics and proteomics have developed separately into two distinct disciplines whereby crosstalk among scientists from the two domains is limited and this constrains the integration of both fields into a single data modality of useful information. The emerging field of proteogenomics attempts to address this by building bridges between the two disciplines. In this review, how genomics and transcriptomics data in different formats can be utilized to assist proteogenomics application is briefly discussed. Subsequently, a much larger part of this review focuses on proteogenomics research articles that are published in the last five years that answer two important questions. First, how proteogenomics can be applied to tackle biological problems is discussed, covering genome annotation and precision medicine. Second, the latest developments in analytical technologies for data acquisition and the bioinformatics tools to interpret and visualize proteogenomics data are covered.

Comparative Genome Analysis of Fusobacterium nucleatum.

Fusobacterium nucleatum is considered to be a key oral bacterium in recruiting periodontal pathogens into subgingival dental plaque. Currently F. nucleatum can be subdivided into five subspecies. Our previous genome analysis of F. nucleatum W1481 (referred to hereafter as W1481), isolated from an 8-mm periodontal pocket in a patient with chronic periodontitis, suggested the possibility of a new subspecies. To further investigate the biology and relationships of this possible subspecies with other known subspecies, we performed comparative analysis between W1481 and 35 genome sequences represented by the five known Fusobacterium subspecies. Our analyses suggest that W1481 is most likely a new F. nucleatum subspecies, supported by evidence from phylogenetic analyses and maximal unique match indices (MUMi). Interestingly, we found a horizontally transferred W1481-specific genomic island harboring the tripartite ATP-independent (TRAP)-like transporter genes, suggesting this bacterium might have a high-affinity transport system for the C4-dicarboxylates malate, succinate, and fumarate. Moreover, we found virulence genes in the W1481 genome that may provide a strong defense mechanism which might enable it to colonize and survive within the host by evading immune surveillance. This comparative study provides better understanding of F. nucleatum and the basis for future functional work on this important pathogen.

Comparative Genomic Analysis Reveals a Possible Novel Non-Tuberculous Mycobacterium Species with High Pathogenic Potential.

Mycobacteria have been reported to cause a wide range of human diseases. We present the first whole-genome study of a Non-Tuberculous Mycobacterium, Mycobacterium sp. UM_CSW (referred to hereafter as UM_CSW), isolated from a patient diagnosed with bronchiectasis. Our data suggest that this clinical isolate is likely a novel mycobacterial species, supported by clear evidence from molecular phylogenetic, comparative genomic, ANI and AAI analyses. UM_CSW is closely related to the Mycobacterium avium complex. While it has characteristic features of an environmental bacterium, it also shows a high pathogenic potential with the presence of a wide variety of putative genes related to bacterial virulence and shares very similar pathogenomic profiles with the known pathogenic mycobacterial species. Thus, we conclude that this possible novel Mycobacterium species should be tightly monitored for its possible causative role in human infections.

NeisseriaBase: a specialised Neisseria genomic resource and analysis platform.

Background. The gram-negative Neisseria is associated with two of the most potent human epidemic diseases: meningococcal meningitis and gonorrhoea. In both cases, disease is caused by bacteria colonizing human mucosal membrane surfaces. Overall, the genus shows great diversity and genetic variation mainly due to its ability to acquire and incorporate genetic material from a diverse range of sources through horizontal gene transfer. Although a number of databases exist for the Neisseria genomes, they are mostly focused on the pathogenic species. In this present study we present the freely available NeisseriaBase, a database dedicated to the genus Neisseria encompassing the complete and draft genomes of 15 pathogenic and commensal Neisseria species. Methods. The genomic data were retrieved from National Center for Biotechnology Information (NCBI) and annotated using the RAST server which were then stored into the MySQL database. The protein-coding genes were further analyzed to obtain information such as calculation of GC content (%), predicted hydrophobicity and molecular weight (Da) using in-house Perl scripts. The web application was developed following the secure four-tier web application architecture: (1) client workstation, (2) web server, (3) application server, and (4) database server. The web interface was constructed using PHP, JavaScript, jQuery, AJAX and CSS, utilizing the model-view-controller (MVC) framework. The in-house developed bioinformatics tools implemented in NeisseraBase were developed using Python, Perl, BioPerl and R languages. Results. Currently, NeisseriaBase houses 603,500 Coding Sequences (CDSs), 16,071 RNAs and 13,119 tRNA genes from 227 Neisseria genomes. The database is equipped with interactive web interfaces. Incorporation of the JBrowse genome browser in the database enables fast and smooth browsing of Neisseria genomes. NeisseriaBase includes the standard BLAST program to facilitate homology searching, and for Virulence Factor Database (VFDB) specific homology searches, the VFDB BLAST is also incorporated into the database. In addition, NeisseriaBase is equipped with in-house designed tools such as the Pairwise Genome Comparison tool (PGC) for comparative genomic analysis and the Pathogenomics Profiling Tool (PathoProT) for the comparative pathogenomics analysis of Neisseria strains. Discussion. This user-friendly database not only provides access to a host of genomic resources on Neisseria but also enables high-quality comparative genome analysis, which is crucial for the expanding scientific community interested in Neisseria research. This database is freely available at http://neisseria.um.edu.my.

MycoCAP - Mycobacterium Comparative Analysis Platform.

Mycobacterium spp. are renowned for being the causative agent of diseases like leprosy, Buruli ulcer and tuberculosis in human beings. With more and more mycobacterial genomes being sequenced, any knowledge generated from comparative genomic analysis would provide better insights into the biology, evolution, phylogeny and pathogenicity of this genus, thus helping in better management of diseases caused by Mycobacterium spp.With this motivation, we constructed MycoCAP, a new comparative analysis platform dedicated to the important genus Mycobacterium. This platform currently provides information of 2108 genome sequences of at least 55 Mycobacterium spp. A number of intuitive web-based tools have been integrated in MycoCAP particularly for comparative analysis including the PGC tool for comparison between two genomes, PathoProT for comparing the virulence genes among the Mycobacterium strains and the SuperClassification tool for the phylogenic classification of the Mycobacterium strains and a specialized classification system for strains of Mycobacterium abscessus. We hope the broad range of functions and easy-to-use tools provided in MycoCAP makes it an invaluable analysis platform to speed up the research discovery on mycobacteria for researchers. Database URL: http://mycobacterium.um.edu.my.

Development of ListeriaBase and comparative analysis of Listeria monocytogenes.

BACKGROUND: Listeria consists of both pathogenic and non-pathogenic species. Reports of similarities between the genomic content between some pathogenic and non-pathogenic species necessitates the investigation of these species at the genomic level to understand the evolution of virulence-associated genes. With Listeria genome data growing exponentially, comparative genomic analysis may give better insights into evolution, genetics and phylogeny of Listeria spp., leading to better management of the diseases caused by them. DESCRIPTION: With this motivation, we have developed ListeriaBase, a web Listeria genomic resource and analysis platform to facilitate comparative analysis of Listeria spp. ListeriaBase currently houses 850,402 protein-coding genes, 18,113 RNAs and 15,576 tRNAs from 285 genome sequences of different Listeria strains. An AJAX-based real time search system implemented in ListeriaBase facilitates searching of this huge genomic data. Our in-house designed comparative analysis tools such as Pairwise Genome Comparison (PGC) tool allowing comparison between two genomes, Pathogenomics Profiling Tool (PathoProT) for comparing the virulence genes, and ListeriaTree for phylogenic classification, were customized and incorporated in ListeriaBase facilitating comparative genomic analysis of Listeria spp. Interestingly, we identified a unique genomic feature in the L. monocytogenes genomes in our analysis. The Auto protein sequences of the serotype 4 and the non-serotype 4 strains of L. monocytogenes possessed unique sequence signatures that can differentiate the two groups. We propose that the aut gene may be a potential gene marker for differentiating the serotype 4 strains from other serotypes of L. monocytogenes. CONCLUSIONS: ListeriaBase is a useful resource and analysis platform that can facilitate comparative analysis of Listeria for the scientific communities. We have successfully demonstrated some key utilities of ListeriaBase. The knowledge that we obtained in the analyses of L. monocytogenes may be important for functional works of this human pathogen in future. ListeriaBase is currently available at http://listeria.um.edu.my .

YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia.

BACKGROUND: Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity. DESCRIPTION: To facilitate the ongoing and future research of Yersinia, especially those generally considered non-pathogenic species, a well-defined repository and analysis platform is needed to hold the Yersinia genomic data and analysis tools for the Yersinia research community. Hence, we have developed the YersiniaBase, a robust and user-friendly Yersinia resource and analysis platform for the analysis of Yersinia genomic data. YersiniaBase has a total of twelve species and 232 genome sequences, of which the majority are Yersinia pestis. In order to smooth the process of searching genomic data in a large database, we implemented an Asynchronous JavaScript and XML (AJAX)-based real-time searching system in YersiniaBase. Besides incorporating existing tools, which include JavaScript-based genome browser (JBrowse) and Basic Local Alignment Search Tool (BLAST), YersiniaBase also has in-house developed tools: (1) Pairwise Genome Comparison tool (PGC) for comparing two user-selected genomes; (2) Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomics analysis of Yersinia genomes; (3) YersiniaTree for constructing phylogenetic tree of Yersinia. We ran analyses based on the tools and genomic data in YersiniaBase and the preliminary results showed differences in virulence genes found in Yersinia pestis and Yersinia pseudotuberculosis compared to other Yersinia species, and differences between Yersinia enterocolitica subsp. enterocolitica and Yersinia enterocolitica subsp. palearctica. CONCLUSIONS: YersiniaBase offers free access to wide range of genomic data and analysis tools for the analysis of Yersinia. YersiniaBase can be accessed at http://yersinia.um.edu.my .

VibrioBase: a model for next-generation genome and annotation database development.

To facilitate the ongoing research of Vibrio spp., a dedicated platform for the Vibrio research community is needed to host the fast-growing amount of genomic data and facilitate the analysis of these data. We present VibrioBase, a useful resource platform, providing all basic features of a sequence database with the addition of unique analysis tools which could be valuable for the Vibrio research community. VibrioBase currently houses a total of 252 Vibrio genomes developed in a user-friendly manner and useful to enable the analysis of these genomic data, particularly in the field of comparative genomics. Besides general data browsing features, VibrioBase offers analysis tools such as BLAST interfaces and JBrowse genome browser. Other important features of this platform include our newly developed in-house tools, the pairwise genome comparison (PGC) tool, and pathogenomics profiling tool (PathoProT). The PGC tool is useful in the identification and comparative analysis of two genomes, whereas PathoProT is designed for comparative pathogenomics analysis of Vibrio strains. Both of these tools will enable researchers with little experience in bioinformatics to get meaningful information from Vibrio genomes with ease. We have tested the validity and suitability of these tools and features for use in the next-generation database development.

FusoBase: an online Fusobacterium comparative genomic analysis platform.

Fusobacterium are anaerobic gram-negative bacteria that have been associated with a wide spectrum of human infections and diseases. As the biology of Fusobacterium is still not well understood, 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 infections and diseases. To facilitate the ongoing genomic research on Fusobacterium, a specialized database with easy-to-use analysis tools is necessary. Here we present FusoBase, an online database providing access to genome-wide annotated sequences of Fusobacterium strains as well as bioinformatics tools, to support the expanding scientific community. Using our custom-developed Pairwise Genome Comparison tool, we demonstrate how differences between two user-defined genomes and how insertion of putative prophages can be identified. In addition, Pathogenomics Profiling Tool is capable of clustering predicted genes across Fusobacterium strains and visualizing the results in the form of a heat map with dendrogram. DATABASE URL: http://fusobacterium.um.edu.my.

HelicoBase: a Helicobacter genomic resource and analysis platform.

BACKGROUND: 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. DESCRIPTION: 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. CONCLUSIONS: 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.