Molecular targets for rapid identification of Brucella spp

BACKGROUND: Brucella 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. RESULTS: We 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. CONCLUSION: Although 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

Equifinality and preservation potential of complex eskers

Eskers are useful for reconstructing meltwater drainage systems of glaciers and ice sheets. However, our process understanding of eskers suffers from a disconnect between sporadic detailed morpho‐sedimentary investigations of abundant large‐scale ancient esker systems, and a small number of modern analogues where esker formation has been observed. This paper presents the results of detailed field and high‐resolution remote sensing studies into two esker systems that have recently emerged at Hørbyebreen, Svalbard, and one at Breiðamerkurjökull, Iceland. Despite the different glaciological settings (polythermal valley glacier vs. active temperate piedmont lobe), in all cases a distinctive planform morphology has developed, where ridges are orientated in two dominant directions corresponding to the direction of ice flow and the shape of the ice margin. These two orientations in combination form a cross‐cutting and locally rectilinear pattern. One set of ridges at Hørbyebreen is a hybrid of eskers and geometric ridges formed during a surge and/or jökulhlaup event. The other sets of ridges are eskers formed time‐transgressively at a retreating ice margin. The similar morphology of esker complexes formed in different ways on both glacier forelands implies equifinality, meaning that care should be taken when interpreting Quaternary esker patterns. The eskers at Hørbyebreen contain substantial ice‐cores with a high ice:sediment ratio, suggesting that they would be unlikely to survive after ice melt. The Breiðamerkurjökull eskers emerged from terrain characterized by buried ice that has melted out. Our observations lead us to conclude that eskers may reflect a wide range of processes at dynamic ice margins, including significant paraglacial adjustments. This work, as well as previous studies, confirms that constraints on esker morphology include: topographic setting (e.g. confined valley or broad plain); sediment and meltwater availability (including surges and jökulhlaups); position of formation (supraglacial, englacial or subglacial); and ice‐marginal dynamics such as channel abandonment, the formation of outwash heads or the burial and/or exhumation of dead ice

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

Sequencing by Hybridization of Long Targets

Sequencing by Hybridization (SBH) reconstructs an n-long target DNA sequence from its biochemically determined l-long subsequences. In the standard approach, the length of a uniformly random sequence that can be unambiguously reconstructed is limited to due to repetitive subsequences causing reconstruction degeneracies. We present a modified sequencing method that overcomes this limitation without the need for different types of biochemical assays and is robust to error

Coupling Constant pH Molecular Dynamics with Accelerated Molecular Dynamics

An extension of the constant pH method originally implemented by Mongan et al. (J. Comput. Chem.2004, 25, 2038−2048) is proposed in this study. This adapted version of the method couples the constant pH methodology with the enhanced sampling technique of accelerated molecular dynamics, in an attempt to overcome the sampling issues encountered with current standard constant pH molecular dynamics methods. Although good results were reported by Mongan et al. on application of the standard method to the hen egg-white lysozyme (HEWL) system, residues which possess strong interactions with neighboring groups tend to converge slowly, resulting in the reported inconsistencies for predicted pKa values, as highlighted by the authors. The application of the coupled method described in this study to the HEWL system displays improvements over the standard version of the method, with the improved sampling leading to faster convergence and producing pKa values in closer agreement to those obtained experimentally for the more slowly converging residues

A Novel Statistical Algorithm for Gene Expression Analysis Helps Differentiate Pregnane X Receptor-Dependent and Independent Mechanisms of Toxicity

Genome-wide gene expression profiling has become standard for assessing potential liabilities as well as for elucidating mechanisms of toxicity of drug candidates under development. Analysis of microarray data is often challenging due to the lack of a statistical model that is amenable to biological variation in a small number of samples. Here we present a novel non-parametric algorithm that requires minimal assumptions about the data distribution. Our method for determining differential expression consists of two steps: 1) We apply a nominal threshold on fold change and platform p-value to designate whether a gene is differentially expressed in each treated and control sample relative to the averaged control pool, and 2) We compared the number of samples satisfying criteria in step 1 between the treated and control groups to estimate the statistical significance based on a null distribution established by sample permutations. The method captures group effect without being too sensitive to anomalies as it allows tolerance for potential non-responders in the treatment group and outliers in the control group. Performance and results of this method were compared with the Significant Analysis of Microarrays (SAM) method. These two methods were applied to investigate hepatic transcriptional responses of wild-type (PXR+/+) and pregnane X receptor-knockout (PXR−/−) mice after 96 h exposure to CMP013, an inhibitor of β-secretase (β-site of amyloid precursor protein cleaving enzyme 1 or BACE1). Our results showed that CMP013 led to transcriptional changes in hallmark PXR-regulated genes and induced a cascade of gene expression changes that explained the hepatomegaly observed only in PXR+/+ animals. Comparison of concordant expression changes between PXR+/+ and PXR−/− mice also suggested a PXR-independent association between CMP013 and perturbations to cellular stress, lipid metabolism, and biliary transport

HMMSplicer: A Tool for Efficient and Sensitive Discovery of Known and Novel Splice Junctions in RNA-Seq Data

Background: High-throughput sequencing of an organism’s transcriptome, or RNA-Seq, is a valuable and versatile new strategy for capturing snapshots of gene expression. However, transcriptome sequencing creates a new class of alignment problem: mapping short reads that span exon-exon junctions back to the reference genome, especially in the case where a splice junction is previously unknown. Methodology/Principal Findings: Here we introduce HMMSplicer, an accurate and efficient algorithm for discovering canonical and non-canonical splice junctions in short read datasets. HMMSplicer identifies more splice junctions than currently available algorithms when tested on publicly available A. thaliana, P. falciparum, and H. sapiens datasets without a reduction in specificity. Conclusions/Significance: HMMSplicer was found to perform especially well in compact genomes and on genes with low expression levels, alternative splice isoforms, or non-canonical splice junctions. Because HHMSplicer does not rely on prebuilt gene models, the products of inexact splicing are also detected. For H. sapiens, we find 3.6 % of 39 splice sites and 1.4% of 59 splice sites are inexact, typically differing by 3 bases in either direction. In addition, HMMSplicer provides a score for every predicted junction allowing the user to set a threshold to tune false positive rates depending on the needs of the experiment. HMMSplicer is implemented in Python. Code and documentation are freely available a

Targeted p120-Catenin Ablation Disrupts Dental Enamel Development

Dental enamel development occurs in stages. The ameloblast cell layer is adjacent to, and is responsible for, enamel formation. When rodent pre-ameloblasts become tall columnar secretory-stage ameloblasts, they secrete enamel matrix proteins, and the ameloblasts start moving in rows that slide by one another. This movement is necessary to form the characteristic decussating enamel prism pattern. Thus, a dynamic system of intercellular interactions is required for proper enamel development. Cadherins are components of the adherens junction (AJ), and they span the cell membrane to mediate attachment to adjacent cells. p120 stabilizes cadherins by preventing their internalization and degradation. So, we asked if p120-mediated cadherin stability is important for dental enamel formation. Targeted p120 ablation in the mouse enamel organ had a striking effect. Secretory stage ameloblasts detached from surrounding tissues, lost polarity, flattened, and ameloblast E- and N-cadherin expression became undetectable by immunostaining. The enamel itself was poorly mineralized and appeared to be composed of a thin layer of merged spheres that abraded from the tooth. Significantly, p120 mosaic mouse teeth were capable of forming normal enamel demonstrating that the enamel defects were not a secondary effect of p120 ablation. Surprisingly, blood-filled sinusoids developed in random locations around the developing teeth. This has not been observed in other p120-ablated tissues and may be due to altered p120-mediated cell signaling. These data reveal a critical role for p120 in tooth and dental enamel development and are consistent with p120 directing the attachment and detachment of the secretory stage ameloblasts as they move in rows

Accurate Estimates of Microarray Target Concentration from a Simple Sequence-Independent Langmuir Model

Background: Microarray technology is a commonly used tool for assessing global gene expression. Many models for estimation of target concentration based on observed microarray signal have been proposed, but, in general, these models have been complex and platform-dependent. Principal Findings: We introduce a universal Langmuir model for estimation of absolute target concentration from microarray experiments. We find that this sequence-independent model, characterized by only three free parameters, yields excellent predictions for four microarray platforms, including Affymetrix, Agilent, Illumina and a custom-printed microarray. The model also accurately predicts concentration for the MAQC data sets. This approach significantly reduces the computational complexity of quantitative target concentration estimates. Conclusions: Using a simple form of the Langmuir isotherm model, with a minimum of parameters and assumptions, and without explicit modeling of individual probe properties, we were able to recover absolute transcript concentrations with high R 2 on four different array platforms. The results obtained here suggest that with a ‘‘spiked-in’ ’ concentration serie

Measures of Association for Identifying MicroRNA-mRNA Pairs of Biological Interest

MicroRNAs are a class of small non-protein coding RNAs that play an important role in the regulation of gene expression. Most studies on the identification of microRNA-mRNA pairs utilize the correlation coefficient as a measure of association. The use of correlation coefficient is appropriate if the expression data are available for several conditions and, for a given condition, both microRNA and mRNA expression profiles are obtained from the same set of individuals. However, there are many instances where one of the requirements is not satisfied. Therefore, there is a need for new measures of association to identify the microRNA-mRNA pairs of interest and we present two such measures. The first measure requires expression data for multiple conditions but, for a given condition, the microRNA and mRNA expression may be obtained from different individuals. The new measure, unlike the correlation coefficient, is suitable for analyzing large data sets which are obtained by combining several independent studies on microRNAs and mRNAs. Our second measure is able to handle expression data that correspond to just two conditions but, for a given condition, the microRNA and mRNA expression must be obtained from the same set of individuals. This measure, unlike the correlation coefficient, is appropriate for analyzing data sets with a small number of conditions. We apply our new measures of association to multiple myeloma data sets, which cannot be analyzed using the correlation coefficient, and identify several microRNA-mRNA pairs involved in apoptosis and cell proliferation