Rapid nitrogen loss from ectomycorrhizal pine germinants signaled by their fungal symbiont.

Ectomycorrhizal fungi supply their plant partners with nitrogen but can also retain substantial amounts. The concentration of nitrogen in the soil and the amount of carbon supplied from the host seem to influence the proportion of N retained by the fungus. In an experiment designed to determine whether differential supply of nitrogen to two plants influenced nitrogen transfer from fungus to plant within a mycorrhizal network, we observed rapid, substantial loss of nitrogen from pine seedlings. The loss occurred when the mycorrhizal fungus experienced a sudden increase in nitrogen supply. We grew Pinus contorta seedlings in association with Suillus tomentosus in low-nitrogen microcosms where some nitrogen was accessible only by hyphae. After 70 days, foliage of some seedlings was treated with nitrogen. Three days later, hyphal nutrient media were replaced with water or a solution containing nitrogen. Foliar treatment did not affect nitrogen transfer by the fungus to shoots, but by day 75, seedling nitrogen contents had dropped by 60% in microcosms where nitrogen had been added to the hyphal compartments. Those seedlings retained only 55% of the nitrogen originally present in the seed. Loss of nitrogen did not occur if water was added or the hyphae were severed. Because of the severing effect, we concluded that S. tomentosus triggered the loss of seedling nitrogen. Nitrogen may have been lost through increased root exudation or transfer to the fungus. Access to nitrogen from nutrient-rich germinants would benefit rhizosphere microorganisms, including ectomycorrhizal fungi colonizing pine from spores after wildfire.

Mycorrhizal Fungi Respond to Resource Inequality by Moving Phosphorus from Rich to Poor Patches across Networks.

The world's ecosystems are characterized by an unequal distribution of resources [1]. Trade partnerships between organisms of different species-mutualisms-can help individuals cope with such resource inequality [2-4]. Trade allows individuals to exchange commodities they can provide at low cost for resources that are otherwise impossible or more difficult to access [5, 6]. However, as resources become increasingly patchy in time or space, it is unknown how organisms alter their trading strategies [7, 8]. Here, we show how a symbiotic fungus mediates trade with a host root in response to different levels of resource inequality across its network. We developed a quantum-dot-tracking technique to quantify phosphorus-trading strategies of arbuscular mycorrhizal fungi simultaneously exposed to rich and poor resource patches. By following fluorescent nanoparticles of different colors across fungal networks, we determined where phosphorus was hoarded, relocated, and transferred to plant hosts. We found that increasing exposure to inequality stimulated trade. Fungi responded to high resource variation by (1) increasing the total amount of phosphorus distributed to host roots, (2) decreasing allocation to storage, and (3) differentially moving resources within the network from rich to poor patches. Using single-particle tracking and high-resolution video, we show how dynamic resource movement may help the fungus capitalize on value differences across the trade network, physically moving resources to areas of high demand to gain better returns. Such translocation strategies can help symbiotic organisms cope with exposure to resource inequality.

Spfy: an integrated graph database for real-time prediction of bacterial phenotypes and downstream comparative analyses.

Public health laboratories are currently moving to whole-genome sequence (WGS)-based analyses, and require the rapid prediction of standard reference laboratory methods based solely on genomic data. Currently, these predictive genomics tasks rely on workflows that chain together multiple programs for the requisite analyses. While useful, these systems do not store the analyses in a genome-centric way, meaning the same analyses are often re-computed for the same genomes. To solve this problem, we created Spfy, a platform that rapidly performs the common reference laboratory tests, uses a graph database to store and retrieve the results from the computational workflows and links data to individual genomes using standardized ontologies. The Spfy platform facilitates rapid phenotype identification, as well as the efficient storage and downstream comparative analysis of tens of thousands of genome sequences. Though generally applicable to bacterial genome sequences, Spfy currently contains 10 243 Escherichia coli genomes, for which in-silico serotype and Shiga-toxin subtype, as well as the presence of known virulence factors and antimicrobial resistance determinants have been computed. Additionally, the presence/absence of the entire E. coli pan-genome was computed and linked to each genome. Owing to its database of diverse pre-computed results, and the ability to easily incorporate user data, Spfy facilitates hypothesis testing in fields ranging from population genomics to epidemiology, while mitigating the re-computation of analyses. The graph approach of Spfy is flexible, and can accommodate new analysis software modules as they are developed, easily linking new results to those already stored. Spfy provides a database and analyses approach for E. coli that is able to match the rapid accumulation of WGS data in public databases.

The OxyR-regulated phnW gene encoding 2-aminoethylphosphonate:pyruvate aminotransferase helps protect Pseudomonas aeruginosa from tert-butyl hydroperoxide.

The LysR member of bacterial transactivators, OxyR, governs transcription of genes involved in the response to H2O2 and organic (alkyl) hydroperoxides (AHP) in the Gram-negative pathogen, Pseudomonas aeruginosa. We have previously shown that organisms lacking OxyR are rapidly killed by <2 or 500 mM H2O2 in planktonic and biofilm bacteria, respectively. In this study, we first employed a bioinformatic approach to elucidate the potential regulatory breadth of OxyR by scanning the entire P. aeruginosa PAO1 genome for canonical OxyR promoter recognition sequences (ATAG-N7-CTAT-N7-ATAG-N7-CTAT). Of >100 potential OxyR-controlled genes, 40 were strategically selected that were not predicted to be involved in the direct response to oxidative stress (e.g., catalase, peroxidase, etc.) and screened such genes by RT-PCR analysis for potentially positive or negative control by OxyR. Differences were found in 7 of 40 genes when comparing an oxyR mutant vs. PAO1 expression that was confirmed by ß-galactosidase reporter assays. Among these, phnW, encoding 2-aminoethylphosphonate:pyruvate aminotransferase, exhibited reduced expression in the oxyR mutant compared to wild-type bacteria. Electrophoretic mobility shift assays indicated binding of OxyR to the phnW promoter and DNase I footprinting analysis also revealed the sequences to which OxyR bound. Interestingly, a phnW mutant was more susceptible to t-butyl-hydroperoxide (t-BOOH) treatment than wild-type bacteria. Although we were unable to define the direct mechanism underlying this phenomenon, we believe that this may be due to a reduced efficiency for this strain to degrade t-BOOH relative to wild-type organisms because of modulation of AHP gene transcription in the phnW mutant.

Phylotyper: in silico predictor of gene subtypes.

SUMMARY: Whole genome sequencing (WGS) is being adopted in public health for improved surveillance and outbreak analysis. In public health, subtyping has been used to infer phenotypes and distinguish bacterial strain groups. In silico tools that predict subtypes from sequences data are needed to transition historical data to WGS-based protocols. Phylotyper is a novel solution for in silico subtype prediction from gene sequences. Designed for incorporation into WGS pipelines, it is a general prediction tool that can be applied to different subtype schemes. Phylotyper uses phylogeny to model the evolution of the subtype and infer subtypes for unannotated sequences. The phylogenic framework in Phylotyper improves accuracy over approaches based solely on sequence similarity and provides useful contextual feedback. AVAILABILITY AND IMPLEMENTATION: Phylotyper is a python and R package. It is available from: https://github.com/superphy/insilico-subtyping. CONTACT: matthew.whiteside@phac-aspc.gc.ca. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Pan-genome Analyses of the Species Salmonella enterica, and Identification of Genomic Markers Predictive for Species, Subspecies, and Serovar.

Food safety is a global concern, with upward of 2.2 million deaths due to enteric disease every year. Current whole-genome sequencing platforms allow routine sequencing of enteric pathogens for surveillance, and during outbreaks; however, a remaining challenge is the identification of genomic markers that are predictive of strain groups that pose the most significant health threats to humans, or that can persist in specific environments. We have previously developed the software program Panseq, which identifies the pan-genome among a group of sequences, and the SuperPhy platform, which utilizes this pan-genome information to identify biomarkers that are predictive of groups of bacterial strains. In this study, we examined the pan-genome of 4893 genomes of Salmonella enterica, an enteric pathogen responsible for the loss of more disability adjusted life years than any other enteric pathogen. We identified a pan-genome of 25.3 Mbp, a strict core of 1.5 Mbp present in all genomes, and a conserved core of 3.2 Mbp found in at least 96% of these genomes. We also identified 404 genomic regions of 1000 bp that were specific to the species S. enterica. These species-specific regions were found to encode mostly hypothetical proteins, effectors, and other proteins related to virulence. For each of the six S. enterica subspecies, markers unique to each were identified. No serovar had pan-genome regions that were present in all of its genomes and absent in all other serovars; however, each serovar did have genomic regions that were universally present among all constituent members, and statistically predictive of the serovar. The phylogeny based on SNPs within the conserved core genome was found to be highly concordant to that produced by a phylogeny using the presence/absence of 1000 bp regions of the entire pan-genome. Future studies could use these predictive regions as components of a vaccine to prevent salmonellosis, as well as in simple and rapid diagnostic tests for both in silico and wet-lab applications, with uses ranging from food safety to public health. Lastly, the tools and methods described in this study could be applied as a pan-genomics framework to other population genomic studies seeking to identify markers for other bacterial species and their sub-groups.

Signals and cues in the evolution of plant-microbe communication.

Communication has played a key role in organismal evolution. If sender and receiver have a shared interest in propagating reliable information, such as when they are kin relatives, then effective communication can bring large fitness benefits. However, interspecific communication (among different species) is more prone to dishonesty. Over the last decade, plants and their microbial root symbionts have become a model system for studying interspecific molecular crosstalk. However, less is known about the evolutionary stability of plant-microbe communication. What prevents partners from hijacking or manipulating information to their own benefit? Here, we focus on communication between arbuscular mycorrhizal fungi and their host plants. We ask how partners use directed signals to convey specific information, and highlight research on the problem of dishonest signaling.

SuperPhy: predictive genomics for the bacterial pathogen Escherichia coli.

BACKGROUND: Predictive genomics is the translation of raw genome sequence data into a phenotypic assessment of the organism. For bacterial pathogens, these phenotypes can range from environmental survivability, to the severity of human disease. Significant progress has been made in the development of generic tools for genomic analyses that are broadly applicable to all microorganisms; however, a fundamental missing component is the ability to analyze genomic data in the context of organism-specific phenotypic knowledge, which has been accumulated from decades of research and can provide a meaningful interpretation of genome sequence data. RESULTS: In this study, we present SuperPhy, an online predictive genomics platform ( http://lfz.corefacility.ca/superphy/ ) for Escherichia coli. The platform integrates the analytical tools and genome sequence data for all publicly available E. coli genomes and facilitates the upload of new genome sequences from users under public or private settings. SuperPhy provides real-time analyses of thousands of genome sequences with results that are understandable and useful to a wide community, including those in the fields of clinical medicine, epidemiology, ecology, and evolution. SuperPhy includes identification of: 1) virulence and antimicrobial resistance determinants 2) statistical associations between genotypes, biomarkers, geospatial distribution, host, source, and phylogenetic clade; 3) the identification of biomarkers for groups of genomes on the based presence/absence of specific genomic regions and single-nucleotide polymorphisms and 4) in silico Shiga-toxin subtype. CONCLUSIONS: SuperPhy is a predictive genomics platform that attempts to provide an essential link between the vast amounts of genome information currently being generated and phenotypic knowledge in an organism-specific context.

Development and use of a quantum dot probe to track multiple yeast strains in mixed culture.

Saccharomyces cerevisiae strains vary in their ability to develop and enhance sensory attributes of alcoholic beverages and are often found growing in mixed strain fermentations; however, quantifying individual strains is challenging due to quantification inaccuracies, low marker longevity, and compromised kinetics. We developed a fluorescent probe, consisting of glutathione molecules conjugated to a quantum dot (QD). Two S. cerevisiae strains were incubated with different coloured probes (QD attached to glutathione molecules, QD-GSH), fermented at multiple ratios, and quantified using confocal microscopy. The QD method was compared with a culture method using microsatellite DNA analysis (MS method). Probes were taken up by an ADP1 encoded transporter, transferred from mother cell to daughter cell, detectable in strains throughout fermentation, and were non-toxic. This resulted in a new quantification method that was more accurate and efficient than the MS method.

Novel symbiotic protoplasts formed by endophytic fungi explain their hidden existence, lifestyle switching, and diversity within the plant kingdom.

Diverse fungi live all or part of their life cycle inside plants as asymptomatic endophytes. While endophytic fungi are increasingly recognized as significant components of plant fitness, it is unclear how they interact with plant cells; why they occur throughout the fungal kingdom; and why they are associated with most fungal lifestyles. Here we evaluate the diversity of endophytic fungi that are able to form novel protoplasts called mycosomes. We found that mycosomes cultured from plants and phylogenetically diverse endophytic fungi have common morphological characteristics, express similar developmental patterns, and can revert back to the free-living walled state. Observed with electron microscopy, mycosome ontogeny within Aureobasidium pullulans may involve two organelles: double membrane-bounded promycosome organelles (PMOs) that form mycosomes, and multivesicular bodies that may form plastid-infecting vesicles. Cultured mycosomes also contain a double membrane-bounded organelle, which may be homologous to the A. pullulans PMO. The mycosome PMO is often expressed as a vacuole-like organelle, which alternatively may contain a lipoid body or a starch grain. Mycosome reversion to walled cells occurs within the PMO, and by budding from lipid or starch-containing mycosomes. Mycosomes discovered in chicken egg yolk provided a plant-independent source for analysis: they formed typical protoplast stages, contained fungal ITS sequences and reverted to walled cells, suggesting mycosome symbiosis with animals as well as plants. Our results suggest that diverse endophytic fungi express a novel protoplast phase that can explain their hidden existence, lifestyle switching, and diversity within the plant kingdom. Importantly, our findings outline "what, where, when and how", opening the way for cell and organelle-specific tests using in situ DNA hybridization and fluorescent labels. We discuss developmental, ecological and evolutionary contexts that provide a robust framework for continued tests of the mycosome phase hypothesis.

Identification of 526 conserved metazoan genetic innovations exposes a new role for cofactor E-like in neuronal microtubule homeostasis.

The evolution of metazoans from their choanoflagellate-like unicellular ancestor coincided with the acquisition of novel biological functions to support a multicellular lifestyle, and eventually, the unique cellular and physiological demands of differentiated cell types such as those forming the nervous, muscle and immune systems. In an effort to understand the molecular underpinnings of such metazoan innovations, we carried out a comparative genomics analysis for genes found exclusively in, and widely conserved across, metazoans. Using this approach, we identified a set of 526 core metazoan-specific genes (the 'metazoanome'), approximately 10% of which are largely uncharacterized, 16% of which are associated with known human disease, and 66% of which are conserved in Trichoplax adhaerens, a basal metazoan lacking neurons and other specialized cell types. Global analyses of previously-characterized core metazoan genes suggest a prevalent property, namely that they act as partially redundant modifiers of ancient eukaryotic pathways. Our data also highlights the importance of exaptation of pre-existing genetic tools during metazoan evolution. Expression studies in C. elegans revealed that many metazoan-specific genes, including tubulin folding cofactor E-like (TBCEL/coel-1), are expressed in neurons. We used C. elegans COEL-1 as a representative to experimentally validate the metazoan-specific character of our dataset. We show that coel-1 disruption results in developmental hypersensitivity to the microtubule drug paclitaxel/taxol, and that overexpression of coel-1 has broad effects during embryonic development and perturbs specialized microtubules in the touch receptor neurons (TRNs). In addition, coel-1 influences the migration, neurite outgrowth and mechanosensory function of the TRNs, and functionally interacts with components of the tubulin acetylation/deacetylation pathway. Together, our findings unveil a conserved molecular toolbox fundamental to metazoan biology that contains a number of neuronally expressed and disease-related genes, and reveal a key role for TBCEL/coel-1 in regulating microtubule function during metazoan development and neuronal differentiation.

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.

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.

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.

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.

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.

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.

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.

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: facilitating flexible queries and comparative analyses.

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.