Cynthia J. Gibas

Pyrosequencing-Based Comparative Genome Analysis of Vibrio vulnificus Environmental Isolates

Between 1996 and 2006, the US Centers for Disease Control reported that the only category of food-borne infections increasing in frequency were those caused by members of the genus Vibrio. The gram-negative bacterium Vibrio vulnificus is a ubiquitous inhabitant of estuarine waters, and is the number one cause of seafood-related deaths in the US. Many V. vulnificus isolates have been studied, and it has been shown that two genetically distinct subtypes, distinguished by 16S rDNA and other gene polymorphisms, are associated predominantly with either environmental or clinical isolation. While local genetic differences between the subtypes have been probed, only the genomes of clinical isolates have so far been completely sequenced. In order to better understand V. vulnificus as an agent of disease and to identify the molecular components of its virulence mechanisms, we have completed whole genome shotgun sequencing of three diverse environmental genotypes using a pyrosequencing approach. V. vulnificus strain JY1305 was sequenced to a depth of 33×, and strains E64MW and JY1701 were sequenced to lesser depth, covering approximately 99.9% of each genome. We have performed a comparative analysis of these sequences against the previously published sequences of three V. vulnificus clinical isolates. We find that the genome of V. vulnificus is dynamic, with 1.27% of genes in the C-genotype genomes not found in the E- genotype genomes. We identified key genes that differentiate between the genomes of the clinical and environmental genotypes. 167 genes were found to be specifically associated with environmental genotypes and 278 genes with clinical genotypes. Genes specific to the clinical strains include components of sialic acid catabolism, mannitol fermentation, and a component of a Type IV secretory pathway VirB4, as well as several other genes with potential significance for human virulence. Genes specific to environmental strains included several that may have implications for the balance between self-preservation under stress and nutritional competence.

Physico-chemical foundations underpinning microarray and next-generation sequencing experiments

Hybridization of nucleic acids on solid surfaces is a key process involved in high-throughput technologies such as microarrays and, in some cases, next-generation sequencing (NGS). A physical understanding of the hybridization process helps to determine the accuracy of these technologies. The goal of a widespread research program is to develop reliable transformations between the raw signals reported by the technologies and individual molecular concentrations from an ensemble of nucleic acids. This research has inputs from many areas, from bioinformatics and biostatistics, to theoretical and experimental biochemistry and biophysics, to computer simulations. A group of leading researchers met in Ploen Germany in 2011 to discuss present knowledge and limitations of our physico-chemical understanding of high-throughput nucleic acid technologies. This meeting inspired us to write this summary, which provides an overview of the state-of-the-art approaches based on physico-chemical foundation to modeling of the nucleic acids hybridization process on solid surfaces. In addition, practical application of current knowledge is emphasized.

Molecular targets for rapid identification of Brucella spp

BackgroundBrucella is an intracellular pathogen capable of infecting animals and humans. There are six recognized species of Brucella that differ in their host preference. The genomes of the three Brucella species have been recently sequenced. Comparison of the three revealed over 98% sequence similarity at the protein level and enabled computational identification of common and differentiating genes. We validated these computational predictions and examined the expression patterns of the putative unique and differentiating genes, using genomic and reverse transcription PCR. We then screened a set of differentiating genes against classical Brucella biovars and showed the applicability of these regions in the design of diagnostic tests.ResultsWe have identified and tested set of molecular targets that are associated in unique patterns with each of the sequenced Brucella spp. A comprehensive comparison was made among the published genome sequences of B. abortus, B. melitensis and B. suis. The comparison confirmed published differences between the three Brucella genomes, and identified subsets of features that were predicted to be of interest in a functional comparison of B. melitensis and B. suis to B. abortus. Differentiating sequence regions from B. abortus, B. melitensis and B. suis were used to develop PCR primers to test for the existence and in vitro transcription of these genes in these species. Only B. suis is found to have a significant number of unique genes, but combinations of genes and regions that exist in only two out of three genomes and are therefore useful for diagnostics were identified and confirmed.ConclusionAlthough not all of the differentiating genes identified were transcribed under steady state conditions, a group of genes sufficient to discriminate unambiguously between B. suis, B. melitensis, and B. abortus was identified. We present an overview of these genomic differences and the use of these features to discriminate among a number of Brucella biovars.

Background correction using dinucleotide affinities improves the performance of GCRMA

BackgroundHigh-density short oligonucleotide microarrays are a primary research tool for assessing global gene expression. Background noise on microarrays comprises a significant portion of the measured raw data, which can have serious implications for the interpretation of the generated data if not estimated correctly.ResultsWe introduce an approach to calculate probe affinity based on sequence composition, incorporating nearest-neighbor (NN) information. Our model uses position-specific dinucleotide information, instead of the original single nucleotide approach, and adds up to 10% to the total variance explained (R2) when compared to the previously published model. We demonstrate that correcting for background noise using this approach enhances the performance of the GCRMA preprocessing algorithm when applied to control datasets, especially for detecting low intensity targets.ConclusionModifying the previously published position-dependent affinity model to incorporate dinucleotide information significantly improves the performance of the model. The dinucleotide affinity model enhances the detection of differentially expressed genes when implemented as a background correction procedure in GeneChip preprocessing algorithms. This is conceptually consistent with physical models of binding affinity, which depend on the nearest-neighbor stacking interactions in addition to base-pairing.

Transcriptome Sequencing Reveals the Virulence and Environmental Genetic Programs of Vibrio vulnificus Exposed to Host and Estuarine Conditions

Vibrio vulnificus is a natural inhabitant of estuarine waters worldwide and is of medical relevance due to its ability to cause grievous wound infections and/or fatal septicemia. Genetic polymorphisms within the virulence-correlated gene (vcg) serve as a primary feature to distinguish clinical (C-) genotypes from environmental (E-) genotypes. C-genotypes demonstrate superior survival in human serum relative to E-genotypes, and genome comparisons have allowed for the identification of several putative virulence factors that could potentially aid C-genotypes in disease progression. We used RNA sequencing to analyze the transcriptome of C-genotypes exposed to human serum relative to seawater, which revealed two divergent genetic programs under these two conditions. In human serum, cells displayed a distinct “virulence profile” in which a number of putative virulence factors were upregulated, including genes involved in intracellular signaling, substrate binding and transport, toxin and exoenzyme production, and the heat shock response. Conversely, the “environmental profile” exhibited by cells in seawater revealed upregulation of transcription factors such as rpoS, rpoN, and iscR, as well as genes involved in intracellular signaling, chemotaxis, adherence, and biofilm formation. This dichotomous genetic switch appears to be largely governed by cyclic-di-GMP signaling, and remarkably resembles the dual life-style of V. cholerae as it transitions from host to environment. Furthermore, we found a “general stress response” module, known as the stressosome, to be upregulated in seawater. This signaling system has been well characterized in Gram-positive bacteria, however its role in V. vulnificus is not clear. We examined temporal gene expression patterns of the stressosome and found it to be upregulated in natural estuarine waters indicating that this system plays a role in sensing and responding to the environment. This study advances our understanding of gene regulation in V. vulnificus, and brings to the forefront a number of previously overlooked genetic networks.

GenoSets: visual analytic methods for comparative genomics.

Many important questions in biology are, fundamentally, comparative, and this extends to our analysis of a growing number of sequenced genomes. Existing genomic analysis tools are often organized around literal views of genomes as linear strings. Even when information is highly condensed, these views grow cumbersome as larger numbers of genomes are added. Data aggregation and summarization methods from the field of visual analytics can provide abstracted comparative views, suitable for sifting large multi-genome datasets to identify critical similarities and differences. We introduce a software system for visual analysis of comparative genomics data. The system automates the process of data integration, and provides the analysis platform to identify and explore features of interest within these large datasets. GenoSets borrows techniques from business intelligence and visual analytics to provide a rich interface of interactive visualizations supported by a multi-dimensional data warehouse. In GenoSets, visual analytic approaches are used to enable querying based on orthology, functional assignment, and taxonomic or user-defined groupings of genomes. GenoSets links this information together with coordinated, interactive visualizations for both detailed and high-level categorical analysis of summarized data. GenoSets has been designed to simplify the exploration of multiple genome datasets and to facilitate reasoning about genomic comparisons. Case examples are included showing the use of this system in the analysis of 12 Brucella genomes. GenoSets software and the case study dataset are freely available at http://genosets.uncc.edu. We demonstrate that the integration of genomic data using a coordinated multiple view approach can simplify the exploration of large comparative genomic data sets, and facilitate reasoning about comparisons and features of interest.

Software Note: Using probe secondary structure information to enhance Affymetrix GeneChip background estimates

High-density short oligonucleotide microarrays are a primary research tool for assessing global gene expression. Background noise on microarrays comprises a significant portion of the measured raw data. A number of statistical techniques have been developed to correct for this background noise. Here, we demonstrate that probe minimum folding energy and structure can be used to enhance a previously existing model for background noise correction. We estimate that probe secondary structure accounts for up to 3% of all variation on Affymetrix microarrays.

Application of Equilibrium Models of Solution Hybridization to Microarray Design and Analysis

Background The probe percent bound value, calculated using multi-state equilibrium models of solution hybridization, is shown to be useful in understanding the hybridization behavior of microarray probes having 50 nucleotides, with and without mismatches. These longer oligonucleotides are in widespread use on microarrays, but there are few controlled studies of their interactions with mismatched targets compared to 25-mer based platforms. Principal Findings 50-mer oligonucleotides with centrally placed single, double and triple mismatches were spotted on an array. Over a range of target concentrations it was possible to discriminate binding to perfect matches and mismatches, and the type of mismatch could be predicted accurately in the concentration midrange (100 pM to 200 pM) using solution hybridization modeling methods. These results have implications for microarray design, optimization and analysis methods. Conclusions Our results highlight the importance of incorporating biophysical factors in both the design and the analysis of microarrays. Use of the probe “percent bound” value predicted by equilibrium models of hybridization is confirmed to be important for predicting and interpreting the behavior of long oligonucleotide arrays, as has been shown for short oligonucleotide arrays.

The illusion of specific capture: surface and solution studies of suboptimal oligonucleotide hybridization

BackgroundHybridization based assays and capture systems depend on the specificity of hybridization between a probe and its intended target. A common guideline in the construction of DNA microarrays, for instance, is that avoiding complementary stretches of more than 15 nucleic acids in a 50 or 60-mer probe will eliminate sequence specific cross-hybridization reactions. Here we present a study of the behavior of partially matched oligonucleotide pairs with complementary stretches starting well below this threshold complementarity length – in silico, in solution, and at the microarray surface. The modeled behavior of pairs of oligonucleotide probes and their targets suggests that even a complementary stretch of sequence 12 nt in length would give rise to specific cross-hybridization. We designed a set of binding partners to a 50-mer oligonucleotide containing complementary stretches from 6 nt to 21 nt in length.ResultsSolution melting experiments demonstrate that stable partial duplexes can form when only 12 bp of complementary sequence are present; surface hybridization experiments confirm that a signal close in magnitude to full-strength signal can be obtained from hybridization of a 12 bp duplex within a 50mer oligonucleotide.ConclusionsMicroarray and other molecular capture strategies that rely on a 15 nt lower complementarity bound for eliminating specific cross-hybridization may not be sufficiently conservative.

Gene-RiViT: A visualization tool for comparative analysis of gene neighborhoods in prokaryotes

The genomes of prokaryotes are dynamic and shuffling of gene order occurs frequently, along with horizontal transfer of genes from external sources. Local conservation of gene order tends to reflect functional constraints on the genome or on a biochemical subsystem. Comparison of the local gene neighborhoods surrounding a gene of interest gives insight into evolutionary history and functional potential of the gene. The Genomic Ring Visualization Tool (Gene-RiViT) is a high speed, intuitive visualization tool for investigating sequence environments of conserved genes among related genomes. Gene-RiViT allows the user to interact with interconnected global and local visualizations of gene neighborhoods and gene order, through a web-based interface that is easily accessible in any browser. The primary visualization is a wheel of nested rotating circles, each of which represents a single genome. This visualization is similar to common circular genome alignment views, except that the rings can be realigned with each other dynamically based on user selections within the ring view or one of the coordinated views. By allowing the user to dynamically realign genomes and focus on a locally conserved region of interest, and using or-thology connections to highlight corresponding structures among genomes, this view provides insight into gene context and preservation of neighbor relationships as genomes evolve. Visualizations are linked into a coordinated multiple view interface to provide multiple selection methods and entry points into the data. These approaches make Gene-RiViT a flexible, unique tool for examining gene neighborhoods that improves on existing methods.