Matthew D. Whiteside

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

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.

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

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.

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

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.

The Burkholderia Genome Database

Summary: 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. Contact: brinkman@sfu.ca.

The brighter side of soils: quantum dots track organic nitrogen through fungi and plants.

Soil microorganisms mediate many nutrient transformations that are central in terrestrial cycling of carbon and nitrogen. However, uptake of organic nutrients by microorganisms is difficult to study in natural systems. We assessed quantum dots (fluorescent nanoscale semiconductors) as a new tool to observe uptake and translocation of organic nitrogen by fungi and plants. We conjugated quantum dots to the amino groups of glycine, arginine, and chitosan and incubated them with Penicillium fungi (a saprotroph) and annual bluegrass (Poa annua) inoculated with arbuscular mycorrhizal fungi. As experimental controls, we incubated fungi and bluegrass samples with substrate-free quantum dots as well as unbound quantum dot substrate mixtures. Penicillium fungi, annual bluegrass, and arbuscular mycorrhizal fungi all showed uptake and translocation of quantum dot-labeled organic nitrogen, but no uptake of quantum dot controls. Additionally, we observed quantum dot-labeled organic nitrogen within soil hyphae, plant roots, and plant shoots using field imaging techniques. This experiment is one of the first to demonstrate direct uptake of organic nitrogen by arbuscular mycorrhizal fungi.

Organic nitrogen uptake by arbuscular mycorrhizal fungi in a boreal forest

The breakdown of organic nitrogen in soil is a potential rate-limiting step in nitrogen cycling. Arbuscular mycorrhizal (AM) fungi are root symbionts that might improve the ability of plants to compete for organic nitrogen products against other decomposer microbes. However, AM uptake of organic nitrogen, especially in natural systems, has traditionally been difficult to test. We developed a novel quantitative nanotechnological technique to determine in situ that organic nitrogen uptake by AM fungi can occur to a greater extent than has previously been assumed. Specifically, we found that AM fungi acquired recalcitrant and labile forms of organic nitrogen. Moreover, N enrichment of soil reduced plot-scale uptake of these compounds. Since most plants host AM fungi, AM use of organic nitrogen could widely influence plant productivity, especially where N availability is relatively low.

Identification of the Regulatory Logic Controlling Salmonella Pathoadaptation by the SsrA-SsrB Two-Component System

Sequence data from the past decade has laid bare the significance of horizontal gene transfer in creating genetic diversity in the bacterial world. Regulatory evolution, in which non-coding DNA is mutated to create new regulatory nodes, also contributes to this diversity to allow niche adaptation and the evolution of pathogenesis. To survive in the host environment, Salmonella enterica uses a type III secretion system and effector proteins, which are activated by the SsrA-SsrB two-component system in response to the host environment. To better understand the phenomenon of regulatory evolution in S. enterica, we defined the SsrB regulon and asked how this transcription factor interacts with the cis-regulatory region of target genes. Using ChIP-on-chip, cDNA hybridization, and comparative genomics analyses, we describe the SsrB-dependent regulon of ancestral and horizontally acquired genes. Further, we used a genetic screen and computational analyses integrating experimental data from S. enterica and sequence data from an orthologous regulatory system in the insect endosymbiont, Sodalis glossinidius, to identify the conserved yet flexible palindrome sequence that defines DNA recognition by SsrB. Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB. These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host.

Amino Acid Uptake in Arbuscular Mycorrhizal Plants

We examined the extent to which arbuscular mycorrhizal (AM) fungi root improved the acquisition of simple organic nitrogen (ON) compounds by their host plants. In a greenhouse-based study, we used quantum dots (fluorescent nanoparticles) to assess uptake of each of the 20 proteinaceous amino acids by AM-colonized versus uncolonized plants. We found that AM colonization increased uptake of phenylalanine, lysine, asparagine, arginine, histidine, methionine, tryptophan, and cysteine; and reduced uptake of aspartic acid. Arbuscular mycorrhizal colonization had the greatest effect on uptake of amino acids that are relatively rare in proteins. In addition, AM fungi facilitated uptake of neutral and positively-charged amino acids more than negatively-charged amino acids. Overall, the AM fungi used in this study appeared to improve access by plants to a number of amino acids, but not necessarily those that are common or negatively-charged.

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

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.

B Cells With High Side Scatter Parameter by Flow Cytometry Correlate With Inferior Survival in Diffuse Large B-Cell Lymphoma

Despite advances in the understanding of diffuse large B-cell lymphoma (DLBCL) biology, only the clinically based International Prognostic Index (IPI) is used routinely for risk stratification at diagnosis. To find novel prognostic markers, we analyzed flow cytometric data from 229 diagnostic DLBCL samples using an automated multiparameter data analysis approach developed in our laboratory. By using the developed automated data analysis pipeline, we identified 71 of 229 cases as having more than 35% B cells with a high side scatter (SSC) profile, a parameter reflecting internal cellular complexity. This high SSC B-cell feature was associated with inferior overall and progression-free survival (P = .001 and P = .01, respectively) and remained a significant predictor of overall survival in multivariate Cox regression analysis (IPI, P = .001; high SSC, P = .004; rituximab, P = .53). This study suggests that high SSC among B cells may serve as a useful biomarker to identify patients with DLBCL at high risk for relapse. This is of particular interest because this biomarker is readily available in most clinical laboratories without significant alteration to existing routine diagnostic strategies or incurring additional costs.