Publications by authors named "Geoffrey L Winsor"

17 Publications

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PSORTdb 4.0: expanded and redesigned bacterial and archaeal protein subcellular localization database incorporating new secondary localizations.

Nucleic Acids Res 2021 01;49(D1):D803-D808

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada.

Protein subcellular localization (SCL) is important for understanding protein function, genome annotation, and aids identification of potential cell surface diagnostic markers, drug targets, or vaccine components. PSORTdb comprises ePSORTdb, a manually curated database of experimentally verified protein SCLs, and cPSORTdb, a pre-computed database of PSORTb-predicted SCLs for NCBI's RefSeq deduced bacterial and archaeal proteomes. We now report PSORTdb 4.0 (http://db.psort.org/). It features a website refresh, in particular a more user-friendly database search. It also addresses the need to uniquely identify proteins from NCBI genomes now that GI numbers have been retired. It further expands both ePSORTdb and cPSORTdb, including additional data about novel secondary localizations, such as proteins found in bacterial outer membrane vesicles. Protein predictions in cPSORTdb have increased along with the number of available microbial genomes, from approximately 13 million when PSORTdb 3.0 was released, to over 66 million currently. Now, analyses of both complete and draft genomes are included. This expanded database will be of wide use to researchers developing SCL predictors or studying diverse microbes, including medically, agriculturally and industrially important species that have both classic or atypical cell envelope structures or vesicles.
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http://dx.doi.org/10.1093/nar/gkaa1095DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7778896PMC
January 2021

Decreasing antibiotic use, the gut microbiota, and asthma incidence in children: evidence from population-based and prospective cohort studies.

Lancet Respir Med 2020 11 24;8(11):1094-1105. Epub 2020 Mar 24.

Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada; British Columbia Children's Hospital, Vancouver, BC, Canada. Electronic address:

Background: Childhood asthma incidence is decreasing in some parts of Europe and North America. Antibiotic use in infancy has been associated with increased asthma risk. In the present study, we tested the hypothesis that decreases in asthma incidence are linked to reduced antibiotic prescribing and mediated by changes in the gut bacterial community.

Methods: This study comprised population-based and prospective cohort analyses. At the population level, we used administrative data from British Columbia, Canada (population 4·7 million), on annual rates of antibiotic prescriptions and asthma diagnoses, to assess the association between antibiotic prescribing (at age <1 year) and asthma incidence (at age 1-4 years). At the individual level, 2644 children from the Canadian Healthy Infant Longitudinal Development (CHILD) prospective birth cohort were examined for the association of systemic antibiotic use (at age <1 year) with the diagnosis of asthma (at age 5 years). In the same cohort, we did a mechanistic investigation of 917 children with available 16S rRNA gene sequencing data from faecal samples (at age ≤1 year), to assess how composition of the gut microbiota relates to antibiotic exposure and asthma incidence.

Findings: At the population level between 2000 and 2014, asthma incidence in children (aged 1-4 years) showed an absolute decrease of 7·1 new diagnoses per 1000 children, from 27·3 (26·8-28·3) per 1000 children to 20·2 (19·5-20·8) per 1000 children (a relative decrease of 26·0%). Reduction in incidence over the study period was associated with decreasing antibiotic use in infancy (age <1 year), from 1253·8 prescriptions (95% CI 1219·3-1288·9) per 1000 infants to 489·1 (467·6-511·2) per 1000 infants (Spearman's r=0·81; p<0·0001). Asthma incidence increased by 24% with each 10% increase in antibiotic prescribing (adjusted incidence rate ratio 1·24 [95% CI 1·20-1·28]; p<0·0001). In the CHILD cohort, after excluding children who received antibiotics for respiratory symptoms, asthma diagnosis in childhood was associated with infant antibiotic use (adjusted odds ratio [aOR] 2·15 [95% CI 1·37-3·39]; p=0·0009), with a significant dose-response; 114 (5·2%) of 2182 children unexposed to antibiotics had asthma by age 5 years, compared with 23 (8·1%) of 284 exposed to one course, five (10·2%) of 49 exposed to two courses, and six (17·6%) of 34 exposed to three or more courses (aOR 1·44 [1·16-1·79]; p=0·0008). Increasing α-diversity of the gut microbiota, defined as an IQR increase (25th to 75th percentile) in the Chao1 index, at age 1 year was associated with a 32% reduced risk of asthma at age 5 years (aOR for IQR increase 0·68 [0·46-0·99]; p=0·046). In a structural equation model, we found the gut microbiota at age 1 year, characterised by α-diversity, β-diversity, and amplicon sequence variants modified by antibiotic exposure, to be a significant mediator between outpatient antibiotic exposure in the first year of life and asthma diagnosis at age 5 years (β=0·08; p=0·027).

Interpretation: Our findings suggest that the reduction in the incidence of paediatric asthma observed in recent years might be an unexpected benefit of prudent antibiotic use during infancy, acting via preservation of the gut microbial community.

Funding: British Columbia Ministry of Health, Pharmaceutical Services Branch; Canadian Institutes of Health Research; Allergy, Genes and Environment (AllerGen) Network of Centres of Excellence; Genome Canada; and Genome British Columbia.
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http://dx.doi.org/10.1016/S2213-2600(20)30052-7DOI Listing
November 2020

AB569, a nontoxic chemical tandem that kills major human pathogenic bacteria.

Proc Natl Acad Sci U S A 2020 03 18;117(9):4921-4930. Epub 2020 Feb 18.

Department of Molecular Genetics, Biochemistry and Microbiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267;

Antibiotic-resistant superbug bacteria represent a global health problem with no imminent solutions. Here we demonstrate that the combination (termed AB569) of acidified nitrite (A-NO) and Na-EDTA (disodium ethylenediaminetetraacetic acid) inhibited all Gram-negative and Gram-positive bacteria tested. AB569 was also efficacious at killing the model organism in biofilms and in a murine chronic lung infection model. AB569 was not toxic to human cell lines at bactericidal concentrations using a basic viability assay. RNA-Seq analyses upon treatment of with AB569 revealed a catastrophic loss of the ability to support core pathways encompassing DNA, RNA, protein, ATP biosynthesis, and iron metabolism. Electrochemical analyses elucidated that AB569 produced more stable SNO proteins, potentially explaining one mechanism of bacterial killing. Our data implicate that AB569 is a safe and effective means to kill pathogenic bacteria, suggesting that simple strategies could be applied with highly advantageous therapeutic/toxicity index ratios to pathogens associated with a myriad of periepithelial infections and related disease scenarios.
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http://dx.doi.org/10.1073/pnas.1911927117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7060718PMC
March 2020

High-throughput detection of RNA processing in bacteria.

BMC Genomics 2018 03 27;19(1):223. Epub 2018 Mar 27.

Department of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada.

Background: Understanding the RNA processing of an organism's transcriptome is an essential but challenging step in understanding its biology. Here we investigate with unprecedented detail the transcriptome of Pseudomonas aeruginosa PAO1, a medically important and innately multi-drug resistant bacterium. We systematically mapped RNA cleavage and dephosphorylation sites that result in 5'-monophosphate terminated RNA (pRNA) using monophosphate RNA-Seq (pRNA-Seq). Transcriptional start sites (TSS) were also mapped using differential RNA-Seq (dRNA-Seq) and both datasets were compared to conventional RNA-Seq performed in a variety of growth conditions.

Results: The pRNA-Seq library revealed known tRNA, rRNA and transfer-messenger RNA (tmRNA) processing sites, together with previously uncharacterized RNA cleavage events that were found disproportionately near the 5' ends of transcripts associated with basic bacterial functions such as oxidative phosphorylation and purine metabolism. The majority (97%) of the processed mRNAs were cleaved at precise codon positions within defined sequence motifs indicative of distinct endonucleolytic activities. The most abundant of these motifs corresponded closely to an E. coli RNase E site previously established in vitro. Using the dRNA-Seq library, we performed an operon analysis and predicted 3159 potential TSS. A correlation analysis uncovered 105 antiparallel pairs of TSS that were separated by 18 bp from each other and were centered on single palindromic TAT(A/T)ATA motifs (likely - 10 promoter elements), suggesting that, consistent with previous in vitro experimentation, these sites can initiate transcription bi-directionally and may thus provide a novel form of transcriptional regulation. TSS and RNA-Seq analysis allowed us to confirm expression of small non-coding RNAs (ncRNAs), many of which are differentially expressed in swarming and biofilm formation conditions.

Conclusions: This study uses pRNA-Seq, a method that provides a genome-wide survey of RNA processing, to study the bacterium Pseudomonas aeruginosa and discover extensive transcript processing not previously appreciated. We have also gained novel insight into RNA maturation and turnover as well as a potential novel form of transcription regulation. NOTE: All sequence data has been submitted to the NCBI sequence read archive. Accession numbers are as follows: [NCBI sequence read archive: SRX156386, SRX157659, SRX157660, SRX157661, SRX157683 and SRX158075]. The sequence data is viewable using Jbrowse on www.pseudomonas.com .
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http://dx.doi.org/10.1186/s12864-018-4538-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870498PMC
March 2018

IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets.

Nucleic Acids Res 2017 07;45(W1):W30-W35

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.

IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.
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http://dx.doi.org/10.1093/nar/gkx343DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5570257PMC
July 2017

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

Nucleic Acids Res 2016 Jan 17;44(D1):D646-53. Epub 2015 Nov 17.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Greater Vancouver, BC V5A 1S6, Canada

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches.
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http://dx.doi.org/10.1093/nar/gkv1227DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702867PMC
January 2016

Clinical utilization of genomics data produced by the international Pseudomonas aeruginosa consortium.

Front Microbiol 2015 29;6:1036. Epub 2015 Sep 29.

Institute for Integrative and Systems Biology, Université Laval Quebec, QC, Canada.

The International Pseudomonas aeruginosa Consortium is sequencing over 1000 genomes and building an analysis pipeline for the study of Pseudomonas genome evolution, antibiotic resistance and virulence genes. Metadata, including genomic and phenotypic data for each isolate of the collection, are available through the International Pseudomonas Consortium Database (http://ipcd.ibis.ulaval.ca/). Here, we present our strategy and the results that emerged from the analysis of the first 389 genomes. With as yet unmatched resolution, our results confirm that P. aeruginosa strains can be divided into three major groups that are further divided into subgroups, some not previously reported in the literature. We also provide the first snapshot of P. aeruginosa strain diversity with respect to antibiotic resistance. Our approach will allow us to draw potential links between environmental strains and those implicated in human and animal infections, understand how patients become infected and how the infection evolves over time as well as identify prognostic markers for better evidence-based decisions on patient care.
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http://dx.doi.org/10.3389/fmicb.2015.01036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586430PMC
October 2015

IslandViewer 3: more flexible, interactive genomic island discovery, visualization and analysis.

Nucleic Acids Res 2015 Jul 27;43(W1):W104-8. Epub 2015 Apr 27.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada

IslandViewer (http://pathogenomics.sfu.ca/islandviewer) is a widely used web-based resource for the prediction and analysis of genomic islands (GIs) in bacterial and archaeal genomes. GIs are clusters of genes of probable horizontal origin, and are of high interest since they disproportionately encode genes involved in medically and environmentally important adaptations, including antimicrobial resistance and virulence. We now report a major new release of IslandViewer, since the last release in 2013. IslandViewer 3 incorporates a completely new genome visualization tool, IslandPlot, enabling for the first time interactive genome analysis and gene search capabilities using synchronized circular, horizontal and vertical genome views. In addition, more curated virulence factors and antimicrobial resistance genes have been incorporated, and homologs of these genes identified in closely related genomes using strict filters. Pathogen-associated genes have been re-calculated for all pre-computed complete genomes. For user-uploaded genomes to be analysed, IslandViewer 3 can also now handle incomplete genomes, with an improved queuing system on compute nodes to handle user demand. Overall, IslandViewer 3 represents a significant new version of this GI analysis software, with features that may make it more broadly useful for general microbial genome analysis and visualization.
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http://dx.doi.org/10.1093/nar/gkv401DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4489224PMC
July 2015

Mining the Pseudomonas genome.

Methods Mol Biol 2014 ;1149:417-32

Department of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, BC, Canada, V5A 1S6.

Pseudomonas species were targeted early for genomic studies since they were noted for their diverse metabolic capacity, ability to inhabit a wide range of environments and hosts, and include notable human and agriculturally relevant pathogens. As more genomes are sequenced, the power of genome-scale analyses are increasing and a wide range of analyses are now possible. The Pseudomonas Genome database has contributed to this effort by providing peer-reviewed, continually updated annotations of the Pseudomonas aeruginosa PAO1 reference strain genome plus integrated data and analyses of related Pseudomonas species. Analyses are now available via multiple resources to facilitate identification and characterization of drug targets, virulence factors, regulatory elements, genomic islands, genome rearrangements, orthologs, single nucleotide polymorphisms, and multiple other gene/protein-based analyses from gene expression to protein structure. We describe here how the Pseudomonas Genome Database and other bioinformatics resources can be leveraged to help Pseudomonas researchers "mine" Pseudomonas genomes, and associated genome-scale data, to facilitate new discovery.
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http://dx.doi.org/10.1007/978-1-4939-0473-0_33DOI Listing
March 2015

OrtholugeDB: a bacterial and archaeal orthology resource for improved comparative genomic analysis.

Nucleic Acids Res 2013 Jan 29;41(Database issue):D366-76. Epub 2012 Nov 29.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada.

Prediction of orthologs (homologous genes that diverged because of speciation) is an integral component of many comparative genomics methods. Although orthologs are more likely to have similar function versus paralogs (genes that diverged because of duplication), recent studies have shown that their degree of functional conservation is variable. Also, there are inherent problems with several large-scale ortholog prediction approaches. To address these issues, we previously developed Ortholuge, which uses phylogenetic distance ratios to provide more precise ortholog assessments for a set of predicted orthologs. However, the original version of Ortholuge required manual intervention and was not easily accessible; therefore, we now report the development of OrtholugeDB, available online at http://www.pathogenomics.sfu.ca/ortholugedb. OrtholugeDB provides ortholog predictions for completely sequenced bacterial and archaeal genomes from NCBI based on reciprocal best Basic Local Alignment Search Tool hits, supplemented with further evaluation by the more precise Ortholuge method. The OrtholugeDB web interface facilitates user-friendly and flexible ortholog analysis, from single genes to genomes, plus flexible data download options. We compare Ortholuge with similar methods, showing how it may more consistently identify orthologs with conserved features across a wide range of taxonomic distances. OrtholugeDB facilitates rapid, and more accurate, bacterial and archaeal comparative genomic analysis and large-scale ortholog predictions.
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http://dx.doi.org/10.1093/nar/gks1241DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531125PMC
January 2013

InnateDB: systems biology of innate immunity and beyond--recent updates and continuing curation.

Nucleic Acids Res 2013 Jan 24;41(Database issue):D1228-33. Epub 2012 Nov 24.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, V5A1S6, Canada.

InnateDB (http://www.innatedb.com) is an integrated analysis platform that has been specifically designed to facilitate systems-level analyses of mammalian innate immunity networks, pathways and genes. In this article, we provide details of recent updates and improvements to the database. InnateDB now contains >196 000 human, mouse and bovine experimentally validated molecular interactions and 3000 pathway annotations of relevance to all mammalian cellular systems (i.e. not just immune relevant pathways and interactions). In addition, the InnateDB team has, to date, manually curated in excess of 18 000 molecular interactions of relevance to innate immunity, providing unprecedented insight into innate immunity networks, pathways and their component molecules. More recently, InnateDB has also initiated the curation of allergy- and asthma-related interactions. Furthermore, we report a range of improvements to our integrated bioinformatics solutions including web service access to InnateDB interaction data using Proteomics Standards Initiative Common Query Interface, enhanced Gene Ontology analysis for innate immunity, and the availability of new network visualizations tools. Finally, the recent integration of bovine data makes InnateDB the first integrated network analysis platform for this agriculturally important model organism.
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http://dx.doi.org/10.1093/nar/gks1147DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531080PMC
January 2013

Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes.

Nucleic Acids Res 2011 Jan 6;39(Database issue):D596-600. Epub 2010 Oct 6.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.

Pseudomonas is a metabolically-diverse genus of bacteria known for its flexibility and leading free living to pathogenic lifestyles in a wide range of hosts. The Pseudomonas Genome Database (http://www.pseudomonas.com) integrates completely-sequenced Pseudomonas genome sequences and their annotations with genome-scale, high-precision computational predictions and manually curated annotation updates. The latest release implements an ability to view sequence polymorphisms in P. aeruginosa PAO1 versus other reference strains, incomplete genomes and single gene sequences. This aids analysis of phenotypic variation between closely related isolates and strains, as well as wider population genomics and evolutionary studies. The wide range of tools for comparing Pseudomonas annotations and sequences now includes a strain-specific access point for viewing high precision computational predictions including updated, more accurate, protein subcellular localization and genomic island predictions. Views link to genome-scale experimental data as well as comparative genomics analyses that incorporate robust genera-geared methods for predicting and clustering orthologs. These analyses can be exploited for identifying putative essential and core Pseudomonas genes or identifying large-scale evolutionary events. The Pseudomonas Genome Database aims to provide a continually updated, high quality source of genome annotations, specifically tailored for Pseudomonas researchers, but using an approach that may be implemented for other genera-level research communities.
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http://dx.doi.org/10.1093/nar/gkq869DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013766PMC
January 2011

Curating the innate immunity interactome.

BMC Syst Biol 2010 Aug 20;4:117. Epub 2010 Aug 20.

Animal & Bioscience Research Department, AGRIC, Teagasc, Grange, Dunsany, Co. Meath, Ireland.

Background: The innate immune response is the first line of defence against invading pathogens and is regulated by complex signalling and transcriptional networks. Systems biology approaches promise to shed new light on the regulation of innate immunity through the analysis and modelling of these networks. A key initial step in this process is the contextual cataloguing of the components of this system and the molecular interactions that comprise these networks. InnateDB (http://www.innatedb.com) is a molecular interaction and pathway database developed to facilitate systems-level analyses of innate immunity.

Results: Here, we describe the InnateDB curation project, which is manually annotating the human and mouse innate immunity interactome in rich contextual detail, and present our novel curation software system, which has been developed to ensure interactions are curated in a highly accurate and data-standards compliant manner. To date, over 13,000 interactions (protein, DNA and RNA) have been curated from the biomedical literature. Here, we present data, illustrating how InnateDB curation of the innate immunity interactome has greatly enhanced network and pathway annotation available for systems-level analysis and discuss the challenges that face such curation efforts. Significantly, we provide several lines of evidence that analysis of the innate immunity interactome has the potential to identify novel signalling, transcriptional and post-transcriptional regulators of innate immunity. Additionally, these analyses also provide insight into the cross-talk between innate immunity pathways and other biological processes, such as adaptive immunity, cancer and diabetes, and intriguingly, suggests links to other pathways, which as yet, have not been implicated in the innate immune response.

Conclusions: In summary, curation of the InnateDB interactome provides a wealth of information to enable systems-level analysis of innate immunity.
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http://dx.doi.org/10.1186/1752-0509-4-117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2936296PMC
August 2010

Pseudomonas Genome Database: facilitating user-friendly, comprehensive comparisons of microbial genomes.

Nucleic Acids Res 2009 Jan 31;37(Database issue):D483-8. Epub 2008 Oct 31.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.

Pseudomonas aeruginosa is a well-studied opportunistic pathogen that is particularly known for its intrinsic antimicrobial resistance, diverse metabolic capacity, and its ability to cause life threatening infections in cystic fibrosis patients. The Pseudomonas Genome Database (http://www.pseudomonas.com) was originally developed as a resource for peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome. In order to facilitate cross-strain and cross-species genome comparisons with other Pseudomonas species of importance, we have now expanded the database capabilities to include all Pseudomonas species, and have developed or incorporated methods to facilitate high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. A choice of simple and more flexible user-friendly Boolean search features allows researchers to search and compare annotations or sequences within or between genomes. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. This database aims to continue to provide a high quality, annotated genome resource for the research community and is available under an open source license.
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http://dx.doi.org/10.1093/nar/gkn861DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2686508PMC
January 2009

The Burkholderia Genome Database: facilitating flexible queries and comparative analyses.

Bioinformatics 2008 Dec 7;24(23):2803-4. Epub 2008 Oct 7.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada V5A 1S6.

Unlabelled: As the genome sequences of multiple strains of a given bacterial species are obtained, more generalized bacterial genome databases may be complemented by databases that are focused on providing more information geared for a distinct bacterial phylogenetic group and its associated research community. The Burkholderia Genome Database represents a model for such a database, providing a powerful, user-friendly search and comparative analysis interface that contains features not found in other genome databases. It contains continually updated, curated and tracked information about Burkholderia cepacia complex genome annotations, plus other Burkholderia species genomes for comparison, providing a high-quality resource for its targeted cystic fibrosis research community.

Availability: http://www.burkholderia.com. Source code: GNU GPL.
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http://dx.doi.org/10.1093/bioinformatics/btn524DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639269PMC
December 2008

InnateDB: facilitating systems-level analyses of the mammalian innate immune response.

Mol Syst Biol 2008 2;4:218. Epub 2008 Sep 2.

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada.

Although considerable progress has been made in dissecting the signaling pathways involved in the innate immune response, it is now apparent that this response can no longer be productively thought of in terms of simple linear pathways. InnateDB (www.innatedb.ca) has been developed to facilitate systems-level analyses that will provide better insight into the complex networks of pathways and interactions that govern the innate immune response. InnateDB is a publicly available, manually curated, integrative biology database of the human and mouse molecules, experimentally verified interactions and pathways involved in innate immunity, along with centralized annotation on the broader human and mouse interactomes. To date, more than 3500 innate immunity-relevant interactions have been contextually annotated through the review of 1000 plus publications. Integrated into InnateDB are novel bioinformatics resources, including network visualization software, pathway analysis, orthologous interaction network construction and the ability to overlay user-supplied gene expression data in an intuitively displayed molecular interaction network and pathway context, which will enable biologists without a computational background to explore their data in a more systems-oriented manner.
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http://dx.doi.org/10.1038/msb.2008.55DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2564732PMC
November 2008

Pseudomonas aeruginosa Genome Database and PseudoCAP: facilitating community-based, continually updated, genome annotation.

Nucleic Acids Res 2005 Jan;33(Database issue):D338-43

Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, B.C., Canada, V5A 1S6.

Using the Pseudomonas aeruginosa Genome Project as a test case, we have developed a database and submission system to facilitate a community-based approach to continually updated genome annotation (http://www.pseudomonas.com). Researchers submit proposed annotation updates through one of three web-based form options which are then subjected to review, and if accepted, entered into both the database and log file of updates with author acknowledgement. In addition, a coordinator continually reviews literature for suitable updates, as we have found such reviews to be the most efficient. Both the annotations database and updates-log database have Boolean search capability with the ability to sort results and download all data or search results as tab-delimited files. To complement this peer-reviewed genome annotation, we also provide a linked GBrowse view which displays alternate annotations. Additional tools and analyses are also integrated, including PseudoCyc, and knockout mutant information. We propose that this database system, with its focus on facilitating flexible queries of the data and providing access to both peer-reviewed annotations as well as alternate annotation information, may be a suitable model for other genome projects wishing to use a continually updated, community-based annotation approach. The source code is freely available under GNU General Public Licence.
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http://dx.doi.org/10.1093/nar/gki047DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC540001PMC
January 2005