Abstract: Purpose. Ocular surface (OS) microbiota contributes to infectious and autoimmune diseases of the eye. Comprehensive analysis of microbial diversity at the OS has been impossible because of the limitations of conventional cultivation techniques. This pilot study aimed to explore true diversity of human OS microbiota using DNA sequencing-based detection and identification of bacteria. Methods. Composition of the bacterial community was characterized using deep sequencing of the 16S rRNA gene amplicon libraries generated from total conjunctival swab DNA. The DNA sequences were classified and the diversity parameters measured using bioinformatics software ESPRIT and MOTHUR and tools available through the Ribosomal Database Project-II (RDP-II). Results. Deep sequencing of conjunctival rDNA from four subjects yielded a total of 115,003 quality DNA reads, corresponding to 221 species-level phylotypes per subject. The combined bacterial community classified into 5 phyla and 59 distinct genera. However, 31% of all DNA reads belonged to unclassified or novel bacteria. The intersubject variability of individual OS microbiomes was very significant. Regardless, 12 genera-Pseudomonas, Propionibacterium, Bradyrhizobium, Corynebacterium, Acinetobacter, Brevundimonas, Staphylococci, Aquabacterium, Sphingomonas, Streptococcus, Streptophyta, and Methylobacterium-were ubiquitous among the analyzed cohort and represented the putative "core" of conjunctival microbiota. The other 47 genera accounted for <4% of the classified portion of this microbiome. Unexpectedly, healthy conjunctiva contained many genera that are commonly identified as ocular surface pathogens. Conclusions. The first DNA sequencing-based survey of bacterial population at the conjunctiva have revealed an unexpectedly diverse microbial community. All analyzed samples contained ubiquitous (core) genera that included commensal, environmental, and opportunistic pathogenic bacteria.
Abstract: ABSTRACT: BACKGROUND: The analysis of genome synteny is a common practice in comparative genomics. With the advent of DNA sequencing technologies, individual biologists can rapidly produce their genomic sequences of interest. Although web-based synteny visualization tools are convenient for biologists to use, none of the existing ones allow biologists to upload their own data for analysis. RESULTS: We have developed the web-based Genome Synteny Viewer (GSV) that allows users to upload two data files for synteny visualization, the mandatory synteny file for specifying genomic positions of conserved regions and the optional genome annotation file. GSV presents two selected genomes in a single integrated view while still retaining the browsing flexibility necessary for exploring individual genomes. Users can browse and filter for genomic regions of interest, change the color or shape of each annotation track as well as re-order, hide or show the tracks dynamically. Additional features include downloadable images, immediate email notification and tracking of usage history. The entire GSV package is also light-weighted which enables easy local installation. CONCLUSIONS: GSV provides a unique option for biologists to analyze genome synteny by uploading their own data set to a web-based comparative genome browser. A web server hosting GSV is provided at http://cas-bioinfo.cas.unt.edu/gsv, and the software is also freely available for local installations.
Abstract: SUMMARY: Ergatis is a flexible workflow management system for designing and executing complex bioinformatics pipelines. However, its complexity restricts its usage to only highly skilled bioinformaticians. We have developed a web-based prokaryotic genome annotation server, Integrative Services for Genomics Analysis (ISGA), which builds upon the Ergatis workflow system, integrates other dynamic analysis tools and provides intuitive web interfaces for biologists to customize and execute their own annotation pipelines. ISGA is designed to be installed at genomics core facilities and be used directly by biologists. AVAILABILITY: ISGA is accessible at http://isga.cgb.indiana.edu/ and the system is also freely available for local installation.
Abstract: The microbiome of the male urogenital tract is poorly described but it has been suggested that bacterial colonization of the male urethra might impact risk of sexually transmitted infection (STI). Previous cultivation-dependent studies showed that a variety of non-pathogenic bacteria colonize the urethra but did not thoroughly characterize these microbiomes or establish links between the compositions of urethral microbiomes and STI.
Abstract: SUMMARY: Investigating the conservation of gene clusters across multiple genomes has become a standard practice in the era of comparative genomics. However, all existing software and databases rely heavily on pre-computation to identify homologous genes by genome-wide comparisons. Such pre-computing strategies lack accuracy and updating the data is computationally intensive. Since most molecular biologists are often interested only in a small cluster of genes, catering to this need, we have developed a web-based software system that allows users to upload a list of genes, perform dynamic search against the genomes of their choices and interactively visualize the gene cluster conservation using a novel multi-genome browser. Our approach avoids expensive genome-wide pre-computing and allows users to dynamically change the search criteria to fit their genes of interest. Our system can be customized for any genome sequences. We have applied it to both prokaryotic and eukaryotic genomes to illustrate its usability. AVAILABILITY: Our software is freely available at http://cgcv.cgb.indiana.edu/cgi-bin/index.cgi.
Abstract: The BLAST program is one of the most widely used sequence similarity search tools for genomic research, even by those biologists lacking extensive bioinformatics training. As the availability of sequence data increases, more researchers are downloading the BLAST program for local installation and performing larger and more complex tasks, including batch queries. In order to manage and interpret the results of batch queries, a host of software packages have been developed to assist with data management and post-processing. Among these programs, there is almost a complete lack of visualization tools to provide graphic representation of complex BLAST pair-wise alignments. We have developed a web-based program, BLAST Output Visualization Tool (BOV), that allows users to interactively visualize the matching regions of query and database hit sequences, thereby allowing the user to quickly and easily dissect complex matching patterns.
