Morgan G. I. Langille

IslandViewer: an integrated interface for computational identification and visualization of genomic islands

Summary: Genomic islands (clusters of genes of probable horizontal origin; GIs) play a critical role in medically important adaptations of bacteria. Recently, several computational methods have been developed to predict GIs that utilize either sequence composition bias or comparative genomics approaches. IslandViewer is a web accessible application that provides the first user-friendly interface for obtaining precomputed GI predictions, or predictions from user-inputted sequence, using the most accurate methods for genomic island prediction: IslandPick, IslandPath-DIMOB and SIGI-HMM. The graphical interface allows easy viewing and downloading of island data in multiple formats, at both the chromosome and gene level, for method-specific, or overlapping, GI predictions. Availability: The IslandViewer web service is available at http://www.pathogenomics.sfu.ca/islandviewer and the source code is freely available under the GNU GPL license. Contact: brinkman@sfu.ca

Newly introduced genomic prophage islands are critical determinants of in vivo competitiveness in the Liverpool Epidemic Strain of Pseudomonas aeruginosa

Pseudomonas aeruginosa isolates have a highly conserved core genome representing up to 90% of the total genomic sequence with additional variable accessory genes, many of which are found in genomic islands or islets. The identification of the Liverpool Epidemic Strain (LES) in a childrens cystic fibrosis (CF) unit in 1996 and its subsequent observation in several centers in the United Kingdom challenged the previous widespread assumption that CF patients acquire only unique strains of P. aeruginosa from the environment. To learn about the forces that shaped the development of this important epidemic strain, the genome of the earliest archived LES isolate, LESB58, was sequenced. The sequence revealed the presence of many large genomic islands, including five prophage clusters, one defective (pyocin) prophage cluster, and five non-phage islands. To determine the role of these clusters, an unbiased signature tagged mutagenesis study was performed, followed by selection in the chronic rat lung infection model. Forty-seven mutants were identified by sequencing, including mutants in several genes known to be involved in Pseudomonas infection. Furthermore, genes from four prophage clusters and one genomic island were identified and in direct competition studies with the parent isolate; four were demonstrated to strongly impact on competitiveness in the chronic rat lung infection model. This strongly indicates that enhanced in vivo competitiveness is a major driver for maintenance and diversifying selection of these genomic prophage genes.

Evaluation of genomic island predictors using a comparative genomics approach.

BackgroundGenomic islands (GIs) are clusters of genes in prokaryotic genomes of probable horizontal origin. GIs are disproportionately associated with microbial adaptations of medical or environmental interest. Recently, multiple programs for automated detection of GIs have been developed that utilize sequence composition characteristics, such as G+C ratio and dinucleotide bias. To robustly evaluate the accuracy of such methods, we propose that a dataset of GIs be constructed using criteria that are independent of sequence composition-based analysis approaches.ResultsWe developed a comparative genomics approach (IslandPick) that identifies both very probable islands and non-island regions. The approach involves 1) flexible, automated selection of comparative genomes for each query genome, using a distance function that picks appropriate genomes for identification of GIs, 2) identification of regions unique to the query genome, compared with the chosen genomes (positive dataset) and 3) identification of regions conserved across all genomes (negative dataset). Using our constructed datasets, we investigated the accuracy of several sequence composition-based GI prediction tools.ConclusionOur results indicate that AlienHunter has the highest recall, but the lowest measured precision, while SIGI-HMM is the most precise method. SIGI-HMM and IslandPath/DIMOB have comparable overall highest accuracy. Our comparative genomics approach, IslandPick, was the most accurate, compared with a curated list of GIs, indicating that we have constructed suitable datasets. This represents the first evaluation, using diverse and, independent datasets that were not artificially constructed, of the accuracy of several sequence composition-based GI predictors. The caveats associated with this analysis and proposals for optimal island prediction are discussed.

The Association of Virulence Factors with Genomic Islands

Background It has been noted that many bacterial virulence factor genes are located within genomic islands (GIs; clusters of genes in a prokaryotic genome of probable horizontal origin). However, such studies have been limited to single genera or isolated observations. We have performed the first large-scale analysis of multiple diverse pathogens to examine this association. We additionally identified genes found predominantly in pathogens, but not non-pathogens, across multiple genera using 631 complete bacterial genomes, and we identified common trends in virulence for genes in GIs. Furthermore, we examined the relationship between GIs and clustered regularly interspaced palindromic repeats (CRISPRs) proposed to confer resistance to phage. Methodology/Principal Findings We show quantitatively that GIs disproportionately contain more virulence factors than the rest of a given genome (p<1E-40 using three GI datasets) and that CRISPRs are also over-represented in GIs. Virulence factors in GIs and pathogen-associated virulence factors are enriched for proteins having more “offensive” functions, e.g. active invasion of the host, and are disproportionately components of type III/IV secretion systems or toxins. Numerous hypothetical pathogen-associated genes were identified, meriting further study. Conclusions/Significance This is the first systematic analysis across diverse genera indicating that virulence factors are disproportionately associated with GIs. “Offensive” virulence factors, as opposed to host-interaction factors, may more often be a recently acquired trait (on an evolutionary time scale detected by GI analysis). Newly identified pathogen-associated genes warrant further study. We discuss the implications of these results, which cement the significant role of GIs in the evolution of many pathogens.

3D live-wire-based semi-automatic segmentation of medical images

Segmenting anatomical structures from medical images is usually one of the most important initial steps in many applications, including visualization, computer-aided diagnosis, and morphometric analysis. Manual 2D segmentation suffers from operator variability and is tedious and time-consuming. These disadvantages are accentuated in 3D applications and, the additional requirement of producing intuitive displays to integrate 3D information for the user, makes manual segmentation even less approachable in 3D. Robust, automatic medical image segmentation in 2D to 3D remains an open problem caused particularly by sensitivity to low-level parameters of segmentation algorithms. Semi-automatic techniques present possible balanced solution where automation focuses on low-level computing-intensive tasks that can be hidden from the user, while manual inter- vention captures high-level expert knowledge nontrivial to capture algorithmically. In this paper we present a 3D extension to the 2D semi-automatic live-wire technique. Live-wire based contours generated semi-automatically on a selected set of slices are used as seed points on new unseen slices in different orientations. The seed points are calculated from intersections of user-based live-wire techniques with new slices. Our algorithm includes a step for ordering the live-wire seed points in the new slices, which is essential for subsequent multi-stage optimal path calculation. We present results of automatically detecting contours in new slices in 3D volumes from a variety of medical images.

Color Lesion Boundary Detection Using Live Wire

The boundaries of oral lesions in color images were detected using a live-wire method and compared to expert delineations. Multiple cost terms were analyzed for their inclusion in the final total cost function including color gradient magnitude, color gradient direction, Canny edge detection, and Laplacian zero crossing. The gradient magnitude and direction cost terms were implemented so that they acted directly on the three components of the color image, instead of using a single derived color band. The live-wire program was shown to be considerably more accurate and faster compared to manual segmentations by untrained users.

Bioinformatic detection of horizontally transferred DNA in bacterial genomes

We highlight a selection of recent research on computational methods and associated challenges surrounding the prediction of bacterial horizontal gene transfer. This research area continues to face controversy, but is becoming more critical as the importance of horizontal gene transfer in medically and ecologically important prokaryotic evolution is further appreciated.

Differences in adiposity and diet quality among individuals with inflammatory bowel disease in Eastern Canada

The objective of the current study was to characterize the relationship between diet quality and body composition in participants living with IBD, specifically Crohn’s disease (CD) or ulcerative colitis (UC), in Atlantic Canada. Participants from the Atlantic Partnership for Tomorrow’s Health (PATH) study are residents of one of the four Atlantic Canada provinces. Participants who completed the dietary questionnaire and had body composition measured were included in the study (n = 12,462 without IBD, n = 111 CD, n = 119 UC). A greater number of participants with IBD reported having multiple chronic conditions compared to those without IBD. Those with UC had statistically higher body weight and body mass index (BMI) compared to those without IBD. Overall, significant positive correlations were observed between adiposity and servings of refined grains, and meats and alternatives such as eggs and fish, whereas negative correlations were observed with servings of vegetables, fruit, whole grains, and alternatives such as tofu, and nuts/seeds. Participants with IBD (both CD and UC) consumed more refined grains than those without IBD. Using logistic regression analysis, participants consuming more servings of vegetables and whole grains were less likely to have CD where as those consuming more serving of fruit and bean/legumes were less likely to have UC. In the Atlantic PATH cohort, which includes a region of the world with a high incidence of IBD, distinct differences in adiposity and diet quality were observed in individuals with specific types of IBD compared to those without. There is a need for collaborative efforts to address weight management and diet quality issues in those living with IBD in the Atlantic Canadian region.

Taxonomic differences of gut microbiomes drive cellulolytic enzymatic potential within hind-gut fermenting mammals

Host diet influences the diversity and metabolic activities of the gut microbiome. Previous studies have shown that the gut microbiome provides a wide array of enzymes that enable processing of diverse dietary components. Because the primary diet of the porcupine, Erethizon dorsatum, is lignified plant material, we reasoned that the porcupine microbiome would be replete with enzymes required to degrade lignocellulose. Here, we report on the bacterial composition in the porcupine microbiome using 16S rRNA sequencing and bioinformatics analysis. We extended this analysis to the microbiomes of 20 additional mammals located in Shubenacadie Wildlife Park (Nova Scotia, Canada), enabling the comparison of bacterial diversity amongst three mammalian taxonomic orders (Rodentia, Carnivora, and Artiodactyla). 16S rRNA sequencing was validated using metagenomic shotgun sequencing on selected herbivores (porcupine, beaver) and carnivores (coyote, Arctic wolf). In the microbiome, functionality is more conserved than bacterial composition, thus we mined microbiome data sets to identify conserved microbial functions across species in each order. We measured the relative gene abundances for cellobiose phosphorylase, endoglucanase, and beta-glucosidase to evaluate the cellulose-degrading potential of select mammals. The porcupine and beaver had higher proportions of genes encoding cellulose-degrading enzymes than the Artic wolf and coyote. These findings provide further evidence that gut microbiome diversity and metabolic capacity are influenced by host diet.