Investigating Pseudomonas aeruginosa population structure and frequency of cross-infection in UK cystic fibrosis clinics - a reference laboratory perspective.

BACKGROUND: We aimed to describe the UK Pseudomonas aeruginosa population structure amongst people with cystic fibrosis (PWCF), and to examine evidence for cross-infection. METHODS: Variable Number Tandem Repeat (VNTR) typing was performed on 4640 isolates from 2619 PWCF received from 55 hospital laboratories between 2017 and 2019. A combination of whole genome sequence (WGS)-based analysis of four clusters from one hospital, and epidemiological analysis of shared strains in twelve hospitals evaluated cross-infection. RESULTS: Of 2619 PWCF, 1324 (51%) harboured common clusters or known transmissible strains, while 1295 carried unique strains/those shared among small numbers of patients. Of the former, 9.5% (250 patients) harboured the Liverpool epidemic strain (LES), followed in prevalence by clone C (7.8%; 205 patients), cluster A (5%;130 patients), and cluster D (3.6%; 94 patients). WGS analysis of 10 LES isolates, 9 of cluster D and 6 isolates each of cluster A and clone C from one hospital revealed LES formed the tightest cluster (between 7 and 205 SNPs), and cluster D the loosest (between 53 and 1531 SNPs). Hospital-specific shared strains were found in some centres, although cross-infection was largely historical, with few new acquisitions. Fifty-nine PWCF (2.3%) harboured "high-risk" clones; one ST235 isolate carried a blaIMP-1 allele. CONCLUSION: Of 2619 PWCF who had P. aeruginosa isolates submitted for VNTR, 51% harboured either common clusters or known transmissible strains, of which LES was the most common. Limited evidence of recent patient-to-patient strain transmission was found, suggesting cross-infection prevention measures and surveillance effectively reduce transmission.

Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission.

Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16-20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement.

Risk of symptomatic COVID-19 due to aircraft transmission: a retrospective cohort study of contact-traced flights during England's containment phase.

BACKGROUND: Knowledge gaps remain regarding SARS-CoV-2 transmission on flights. We conducted a retrospective cohort study to estimate risk of acquiring symptomatic SARS-CoV-2 on aircraft, to inform contact tracing and infection control efforts. METHODS: We identified co-passengers of infectious passengers on 18 England-bound flights from European cities up to 12/03/2020, using manifests received for contact tracing. Infectious passengers were laboratory-confirmed cases with symptom onset from 7 days before to 2 days after the flight. Possible aircraft-acquired cases were laboratory-confirmed with onset 3-14 days post-flight with no known non-flight exposure. Manifests was merged with the national case management dataset (identifying cases, onset dates, contact tracing status) and the national COVID-19 linelist. Contact tracing notes were reviewed to identify non-flight exposures. We calculated attack rates (ARs) among all co-passengers and within subgroups, including by distance from infectious cases and number of infectious cases on-board. RESULTS: There were 55 infectious passengers and 2313 co-passengers, including 2221 flight-only contacts. Five possible aircraft-acquired cases were identified; ARs of 0.2% (95%CI 0.1-0.5) among all flight-only contacts and 3.8% (95%CI 1.3-10.6) among contact-traced flight-only contacts sat within a two-seat radius. The AR among 92 co-travellers with known non-flight exposure to infectious cases was 13.0% (95%CI 7.6%-21.4%). There were insufficient numbers to assess differences between subgroups. CONCLUSION: We conclude that risk of symptomatic COVID-19 due to transmission on short to medium-haul flights is low, and recommend prioritising contact-tracing of close contacts and co-travellers where resources are limited. Further research on risk on aircraft is encouraged.

Investigation of a Pandoraea apista cluster common to adult and paediatric cystic fibrosis patients attending two hospitals in the same city.

PURPOSE: We examined evidence for transmission of Pandorea apista among cystic fibrosis (CF) patients attending paediatric and adult services in one city who had previously been found to harbour related isolates by pulsed-field gel electrophoresis (PFGE). METHODOLOGY: The whole-genome sequences of 18 isolates from this cluster from 15 CF patients were examined, along with 2 cluster isolates from 2 other centres. The annotated sequence of one of these, Pa14367, was examined for virulence factors and antibiotic resistance-associated genes in comparison with data from a 'non-cluster' isolate, Pa16226. RESULTS: Single-nucleotide polymorphism (SNP) analysis suggested that cluster isolates from the same city differed from one another by a minimum of 1 and a maximum of 383 SNPs (an average of 213 SNPs; standard deviation: 18.5), while isolates from the 2 other hospitals differed from these by a minimum of 34 and 61 SNPs, respectively. Pa16226 differed from all cluster isolates by a minimum of 22 706 SNPs. Evidence for patient-to-patient transmission among isolates from the same city was relatively limited, although transmission from a common source could not be excluded. The annotated genomes of Pa14367 and Pa16226 carried putative integrative and conjugative elements (ICEs), coding for type IV secretion systems, and genes associated with heavy metal degradation and carbon dioxide fixation, and a wide selection of genes coding for efflux pumps, beta-lactamases and penicillin-binding proteins. CONCLUSION: Epidemiological analysis suggested that this cluster could not always be attributed to patient-to-patient transmission. The acquisition of ICE-related virulence factors may have had an impact on its prevalence.

Identification and typing of Yersinia enterocolitica and Yersinia pseudotuberculosis isolated from human clinical specimens in England between 2004 and 2018.

PurposeandMethodology. Epidemiological and microbiological data on Yersinia enterocolitica (n=699) and Yersinia pseudotuberculosis (n=35) isolated from human clinical specimens in England between April 2004 and March 2018 were reviewed. Traditional biochemical species identification and serological typing results were compared with species identifications and serotypes derived from whole-genome sequencing (WGS) data for a sub-set of these isolates (n=179).Results. Most Y. enterocolitica isolates were from faecal specimens (74.4%) from adults (80.7%) and 50.7  % of isolates were from male patients. Most Y. pseudotuberculosis isolates were from blood cultures (68.6%) from adults (91%) and 60.0  % of isolates were from male patients. All sequenced isolates of Y. enterocolitica (n=158) and Y. pseudotuberculosis (n=21), as well as isolates belonging to other Yersinia species (n=21), were correctly identified from genomic data using a kmer-based identification approach. Traditional phenotypic serotyping typed 82/158 and 12/21 isolates of Y. enterocolitica and Y. pseudotuberculosis, respectively, while 118/158 and 21/21 isolates of Y. enterocolitica and Y. pseudotuberculosis, respectively, were typed by the genome-derived serotyping method. In addition, WGS data provided a multi-locus sequence type profile and virulence gene profile for all isolates.Conclusion. The use of WGS for typing Y. enterocolitica and Y. pseudotuberculosis at Public Health England will facilitate the monitoring of animal-to-human transmission of these important foodborne pathogens in the UK and improve public health surveillance of the pathogenic lineages.

Evaluation of Whole-Genome Sequencing for Identification and Typing of Vibrio cholerae.

Epidemiological and microbiological data on Vibrio cholerae strains isolated between April 2004 and March 2018 (n = 836) and held at the Public Health England culture archive were reviewed. The traditional biochemical species identification and serological typing results were compared with the genome-derived species identification and serotype for a subset of isolates (n = 152). Of the 836 isolates, 750 (89.7%) were from a fecal specimen, 206 (24.6%) belonged to serogroup O1, and 7 (0.8%) were serogroup O139; 792 (94.7%) isolates were from patients reporting recent travel abroad, most commonly to India (n = 209) and Pakistan (n = 104). Of the 152 V. cholerae isolates identified by use of kmer, 149 (98.1%) were concordant with those identified using the traditional biochemical approach. Traditional serotyping results were 100% concordant with those of the whole-genome sequencing (WGS) analysis for the identification of serogroups O1 and O139 and classical and El Tor biotypes. ctxA was detected in all isolates of V. cholerae O1 El Tor and O139 belonging to sequence type 69 (ST69) and in V. cholerae O1 classical variants belonging to ST73. A phylogeny of isolates belonging to ST69 from U.K. travelers clustered geographically, with isolates from India and Pakistan located on separate branches. Moving forward, WGS data from U.K. travelers will contribute to global surveillance programs and the monitoring of emerging threats to public health and the global dissemination of pathogenic lineages. At the national level, these WGS data will inform the timely reinforcement of direct public health messaging to travelers and mitigate the impact of imported infections and the associated risks to public health.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

Sustained transmission of high-level azithromycin-resistant Neisseria gonorrhoeae in England: an observational study.

BACKGROUND: Between Nov 3, 2014, and Feb 24, 2017, 70 cases of high-level azithromycin-resistant (HL-AziR; minimum inhibitory concentration [MIC] ≥256 mg/L) Neisseria gonorrhoeae were reported from across England. Whole-genome sequencing was done to investigate this outbreak to determine whether the ongoing outbreak represented clonal spread of an HL-AziR N gonorrhoeae strain identified in Leeds. We also wanted to elucidate the molecular mechanisms of azithromycin resistance in N gonorrhoeae in the UK. METHODS: In this observational study, whole-genome sequencing was done on the HL-AziR N gonorrhoeae isolates from England. As comparators, 110 isolates from the UK and Ireland with a range of azithromycin MICs were also sequenced, including eight isolates from Scotland with azithromycin MICs ranging from 0·12 mg/L to 1·00 mg/L that were N gonorrhoeae multi-antigen sequence type 9768 (ST9768), which was the sequence type initially responsible for the outbreak. The presence of mutations or genes associated with azithromycin resistance was also investigated. FINDINGS: 37 of the 60 HL-AziR isolates from England belonged to ST9768, and were genetically similar (mean 4·3 single-nucleotide polymorphisms). A 2059A→G mutation was detected in three or all four alleles of the 23S rRNA gene. Five susceptible ST9768 isolates had one mutated 23S rRNA allele and one low-level resistant ST9768 isolate had two mutated alleles. INTERPRETATION: Sustained transmission of a successful HL-AziR clone was seen across England. Mutation 2059A→G was found in isolates with lower azithromycin MICs. Azithromycin exposure might have provided the selection pressure for one or two mutated copies of the 23S rRNA gene to recombine with wild-type copies, leading to three or four mutated copies and the HL-AziR phenotype. HL-AziR could emerge in isolates with low azithromycin MICs and eliminate the effectiveness of azithromycin as part of dual therapy for the treatment of gonorrhoea. FUNDING: Public Health England.

Clinical streptococcal isolates, distinct from Streptococcus pneumoniae, but containing the ß-glucosyltransferase tts gene and expressing serotype 37 capsular polysaccharide.

The major virulence factor of the pneumococcus, and target for conjugate vaccines, is the polysaccharide capsule, which is usually encoded by the highly variable cps locus. Serotype 37 is an unusual pneumococcal type in which the single ß-glucosyltransferase gene responsible for serotype capsule production (tts) is located outside of the capsular operon region. Using a previously described automated whole genome sequence (WGS)-based serotyping bioinformatics tool, PneumoCaT, we identified and investigated seven clinical isolates (three from blood cultures) of non-pneumococcal streptococci containing a highly homologous tts and included them in a study panel of 20 isolates which included a 11 further clinical isolates of S. pneumoniae serotype 37, a reference strain of serotype 37 and the S. pseudopneumoniae type strain BAA 960T. The seven non-pneumococcal isolates generated novel alleles at all pneumococcal MLST loci and gave low percentage similarity (<45%) to S. pneumoniae or S. pseudopneumoniae species by comparison of short sequence patterns in genomic data (k-mer analysis). The S. pseudopneumoniae BAA-960T isolate generated two novel alleles in the MLST and gave a high similarity (>99%) to the reference sequence for BAA-960T. Twelve isolates gave high similarity (>77%) to the Streptococcus pneumoniae 5652-06 serotype 19A reference genome sequence and had previously reported MLST alleles. Each of the seven clinical non-pneumococcal strains and all of the 12 S. pneumoniae possessed a ß-glycosyltransferase gene (tts) with >95% similarity to the pneumococcal tts reference DNA sequence with 20-22 non-synonymous SNPs. All but two strains in which the tts gene was detected gave positive reactions for serotype 37 in slide agglutination tests with serotype 37 typing sera. Phylogenetic analysis using both SNP and MLST data showed distinct clades corresponding to strains identified as pneumococcus or non-pneumococcus by kmer WGS analysis. Extended k-mer database analysis and ribosomal MLST placed the non-pneumococcal isolates within the S. mitis group. Biochemical and bile solubility assays showed differences between the unusual isolates and S. pneumoniae. All isolates had detectable pneumolysin (ply) genes, but only those that identified as pneumococcus contained the genes for autolysin (lytA) or the ABC transporter lipoprotein A (piaA) with >80% coverage and >95% similarity. Here we report the existence of a novel group of strains distinct from S. pneumoniae, but which can express a pneumococcal serotype 37 capsular polysaccharide which can be associated with clinical disease.

Identification of Escherichia coli and Shigella Species from Whole-Genome Sequences.

Escherichia coli and Shigella species are closely related and genetically constitute the same species. Differentiating between these two pathogens and accurately identifying the four species of Shigella are therefore challenging. The organism-specific bioinformatics whole-genome sequencing (WGS) typing pipelines at Public Health England are dependent on the initial identification of the bacterial species by use of a kmer-based approach. Of the 1,982 Escherichia coli and Shigella sp. isolates analyzed in this study, 1,957 (98.4%) had concordant results by both traditional biochemistry and serology (TB&S) and the kmer identification (ID) derived from the WGS data. Of the 25 mismatches identified, 10 were enteroinvasive E. coli isolates that were misidentified as Shigella flexneri or S. boydii by the kmer ID, and 8 were S. flexneri isolates misidentified by TB&S as S. boydii due to nonfunctional S. flexneri O antigen biosynthesis genes. Analysis of the population structure based on multilocus sequence typing (MLST) data derived from the WGS data showed that the remaining discrepant results belonged to clonal complex 288 (CC288), comprising both S. boydii and S. dysenteriae strains. Mismatches between the TB&S and kmer ID results were explained by the close phylogenetic relationship between the two species and were resolved with reference to the MLST data. Shigella can be differentiated from E. coli and accurately identified to the species level by use of kmer comparisons and MLST. Analysis of the WGS data provided explanations for the discordant results between TB&S and WGS data, revealed the true phylogenetic relationships between different species of Shigella, and identified emerging pathoadapted lineages.

MOST: a modified MLST typing tool based on short read sequencing.

Multilocus sequence typing (MLST) is an effective method to describe bacterial populations. Conventionally, MLST involves Polymerase Chain Reaction (PCR) amplification of housekeeping genes followed by Sanger DNA sequencing. Public Health England (PHE) is in the process of replacing the conventional MLST methodology with a method based on short read sequence data derived from Whole Genome Sequencing (WGS). This paper reports the comparison of the reliability of MLST results derived from WGS data, comparing mapping and assembly-based approaches to conventional methods using 323 bacterial genomes of diverse species. The sensitivity of the two WGS based methods were further investigated with 26 mixed and 29 low coverage genomic data sets from Salmonella enteridis and Streptococcus pneumoniae. Of the 323 samples, 92.9% (n = 300), 97.5% (n = 315) and 99.7% (n = 322) full MLST profiles were derived by the conventional method, assembly- and mapping-based approaches, respectively. The concordance between samples that were typed by conventional (92.9%) and both WGS methods was 100%. From the 55 mixed and low coverage genomes, 89.1% (n = 49) and 67.3% (n = 37) full MLST profiles were derived from the mapping and assembly based approaches, respectively. In conclusion, deriving MLST from WGS data is more sensitive than the conventional method. When comparing WGS based methods, the mapping based approach was the most sensitive. In addition, the mapping based approach described here derives quality metrics, which are difficult to determine quantitatively using conventional and WGS-assembly based approaches.

Identification of Salmonella for public health surveillance using whole genome sequencing.

In April 2015, Public Health England implemented whole genome sequencing (WGS) as a routine typing tool for public health surveillance of Salmonella, adopting a multilocus sequence typing (MLST) approach as a replacement for traditional serotyping. The WGS derived sequence type (ST) was compared to the phenotypic serotype for 6,887 isolates of S. enterica subspecies I, and of these, 6,616 (96%) were concordant. Of the 4% (n = 271) of isolates of subspecies I exhibiting a mismatch, 119 were due to a process error in the laboratory, 26 were likely caused by the serotype designation in the MLST database being incorrect and 126 occurred when two different serovars belonged to the same ST. The population structure of S. enterica subspecies II-IV differs markedly from that of subspecies I and, based on current data, defining the serovar from the clonal complex may be less appropriate for the classification of this group. Novel sequence types that were not present in the MLST database were identified in 8.6% of the total number of samples tested (including S. enterica subspecies I-IV and S. bongori) and these 654 isolates belonged to 326 novel STs. For S. enterica subspecies I, WGS MLST derived serotyping is a high throughput, accurate, robust, reliable typing method, well suited to routine public health surveillance. The combined output of ST and serovar supports the maintenance of traditional serovar nomenclature while providing additional insight on the true phylogenetic relationship between isolates.

An outbreak of high-level azithromycin resistant Neisseria gonorrhoeae in England.

OBJECTIVES: To investigate a potential outbreak of high-level azithromycin resistant (HL-AziR) gonococcal infections diagnosed in eight patients attending a sexual health clinic in Leeds, North England, between November 2014 and March 2015. METHODS: Eight cases of infection with gonococci exhibiting azithromycin minimum inhibitory concentrations (MICs) ≥256 mg/L were identified from patients in Leeds as part of the routine service provided by the Sexually Transmitted Bacteria Reference Unit. All patient records were reviewed to collate epidemiological and clinical information including evaluation of patient management. Whole-genome sequencing (WGS) was performed on seven gonococcal isolates to determine Neisseria gonorrhoeae multiantigen sequence type (NG-MAST), WGS comparison and mutations in the 23S rRNA genes. RESULTS: All patients were heterosexual (five male, three female) from a range of ethnic backgrounds and from the Leeds area. Three patients were linked by partner notification. All patients were infected at genital sites and two women had pharyngeal infection also. Six patients received the recommended first-line therapy for uncomplicated gonorrhoea, one was treated for pelvic inflammatory disease and one received spectinomycin followed later by ciprofloxacin. Test of cure was achieved in seven patients and confirmed successful eradication. All seven isolates sequenced were identical by NG-MAST and WGS comparison, and contained an A2143G mutation in all four 23S rRNA alleles. CONCLUSIONS: Epidemiological and microbiological investigations confirm that an outbreak of a gonococcal strain showing HL-AziR is ongoing in the North of England. Every effort should be made to identify and curtail dissemination of this strain as it presents a significant threat to the current recommended front-line dual therapy.

A promoter-level mammalian expression atlas.

Regulated transcription controls the diversity, developmental pathways and spatial organization of the hundreds of cell types that make up a mammal. Using single-molecule cDNA sequencing, we mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body. We find that few genes are truly 'housekeeping', whereas many mammalian promoters are composite entities composed of several closely separated TSSs, with independent cell-type-specific expression profiles. TSSs specific to different cell types evolve at different rates, whereas promoters of broadly expressed genes are the most conserved. Promoter-based expression analysis reveals key transcription factors defining cell states and links them to binding-site motifs. The functions of identified novel transcripts can be predicted by coexpression and sample ontology enrichment analyses. The functional annotation of the mammalian genome 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type-specific transcriptomes with wide applications in biomedical research.

HOCOMOCO: a comprehensive collection of human transcription factor binding sites models.

Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source.

Mutations and binding sites of human transcription factors.

Mutations in any genome may lead to phenotype characteristics that determine ability of an individual to cope with adaptation to environmental challenges. In studies of human biology, among the most interesting ones are phenotype characteristics that determine responses to drug treatments, response to infections, or predisposition to specific inherited diseases. Most of the research in this field has been focused on the studies of mutation effects on the final gene products, peptides, and their alterations. Considerably less attention was given to the mutations that may affect regulatory mechanism(s) of gene expression, although these may also affect the phenotype characteristics. In this study we make a pilot analysis of mutations observed in the regulatory regions of 24,667 human RefSeq genes. Our study reveals that out of eight studied mutation types, "insertions" are the only one that in a statistically significant manner alters predicted transcription factor binding sites (TFBSs). We also find that 25 families of TFBSs have been altered by mutations in a statistically significant manner in the promoter regions we considered. Moreover, we find that the related transcription factors are, for example, prominent in processes related to intracellular signaling; cell fate; morphogenesis of organs and epithelium; development of urogenital system, epithelium, and tube; neuron fate commitment. Our study highlights the significance of studying mutations within the genes regulatory regions and opens way for further detailed investigations on this topic, particularly on the downstream affected pathways.

DESTAF: a database of text-mined associations for reproductive toxins potentially affecting human fertility.

The Dragon Exploration System for Toxicants and Fertility (DESTAF) is a publicly available resource which enables researchers to efficiently explore both known and potentially novel information and associations in the field of reproductive toxicology. To create DESTAF we used data from the literature (including over 10500 PubMed abstracts), several publicly available biomedical repositories, and specialized, curated dictionaries. DESTAF has an interface designed to facilitate rapid assessment of the key associations between relevant concepts, allowing for a more in-depth exploration of information based on different gene/protein-, enzyme/metabolite-, toxin/chemical-, disease- or anatomically centric perspectives. As a special feature, DESTAF allows for the creation and initial testing of potentially new association hypotheses that suggest links between biological entities identified through the database. DESTAF, along with a PDF manual, can be found at http://cbrc.kaust.edu.sa/destaf. It is free to academic and non-commercial users and will be updated quarterly.

Network analysis of microRNAs and their regulation in human ovarian cancer.

BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNA molecules that repress the translation of messenger RNAs (mRNAs) or degrade mRNAs. These functions of miRNAs allow them to control key cellular processes such as development, differentiation and apoptosis, and they have also been implicated in several cancers such as leukaemia, lung, pancreatic and ovarian cancer (OC). Unfortunately, the specific machinery of miRNA regulation, involving transcription factors (TFs) and transcription co-factors (TcoFs), is not well understood. In the present study we focus on computationally deciphering the underlying network of miRNAs, their targets, and their control mechanisms that have an influence on OC development. RESULTS: We analysed experimentally verified data from multiple sources that describe miRNA influence on diseases, miRNA targeting of mRNAs, and on protein-protein interactions, and combined this data with ab initio transcription factor binding site predictions within miRNA promoter regions. From these analyses, we derived a network that describes the influence of miRNAs and their regulation in human OC. We developed a methodology to analyse the network in order to find the nodes that have the largest potential of influencing the network's behaviour (network hubs). We further show the potentially most influential miRNAs, TFs and TcoFs, showing subnetworks illustrating the involved mechanisms as well as regulatory miRNA network motifs in OC. We find an enrichment of miRNA targeted OC genes in the highly relevant pathways cell cycle regulation and apoptosis. CONCLUSIONS: We combined several sources of interaction and association data to analyse and place miRNAs within regulatory pathways that influence human OC. These results represent the first comprehensive miRNA regulatory network analysis for human OC. This suggests that miRNAs and their regulation may play a major role in OC and that further directed research in this area is of utmost importance to enhance our understanding of the molecular mechanisms underlying human cancer development and OC in particular.

HCVpro: hepatitis C virus protein interaction database.

It is essential to catalog characterized hepatitis C virus (HCV) protein-protein interaction (PPI) data and the associated plethora of vital functional information to augment the search for therapies, vaccines and diagnostic biomarkers. In furtherance of these goals, we have developed the hepatitis C virus protein interaction database (HCVpro) by integrating manually verified hepatitis C virus-virus and virus-human protein interactions curated from literature and databases. HCVpro is a comprehensive and integrated HCV-specific knowledgebase housing consolidated information on PPIs, functional genomics and molecular data obtained from a variety of virus databases (VirHostNet, VirusMint, HCVdb and euHCVdb), and from BIND and other relevant biology repositories. HCVpro is further populated with information on hepatocellular carcinoma (HCC) related genes that are mapped onto their encoded cellular proteins. Incorporated proteins have been mapped onto Gene Ontologies, canonical pathways, Online Mendelian Inheritance in Man (OMIM) and extensively cross-referenced to other essential annotations. The database is enriched with exhaustive reviews on structure and functions of HCV proteins, current state of drug and vaccine development and links to recommended journal articles. Users can query the database using specific protein identifiers (IDs), chromosomal locations of a gene, interaction detection methods, indexed PubMed sources as well as HCVpro, BIND and VirusMint IDs. The use of HCVpro is free and the resource can be accessed via http://apps.sanbi.ac.za/hcvpro/ or http://cbrc.kaust.edu.sa/hcvpro/.