A versatile computational pipeline for bacterial genome annotation improvement and comparative analysis, with Brucella as a use case.

We present a bacterial genome computational analysis pipeline, called GenVar. The pipeline, based on the program GeneWise, is designed to analyze an annotated genome and automatically identify missed gene calls and sequence variants such as genes with disrupted reading frames (split genes) and those with insertions and deletions (indels). For a given genome to be analyzed, GenVar relies on a database containing closely related genomes (such as other species or strains) as well as a few additional reference genomes. GenVar also helps identify gene disruptions probably caused by sequencing errors. We exemplify GenVar's capabilities by presenting results from the analysis of four Brucella genomes. Brucella is an important human pathogen and zoonotic agent. The analysis revealed hundreds of missed gene calls, new split genes and indels, several of which are species specific and hence provide valuable clues to the understanding of the genome basis of Brucella pathogenicity and host specificity.

PATRIC: the VBI PathoSystems Resource Integration Center.

The PathoSystems Resource Integration Center (PATRIC) is one of eight Bioinformatics Resource Centers (BRCs) funded by the National Institute of Allergy and Infection Diseases (NIAID) to create a data and analysis resource for selected NIAID priority pathogens, specifically proteobacteria of the genera Brucella, Rickettsia and Coxiella, and corona-, calici- and lyssaviruses and viruses associated with hepatitis A and E. The goal of the project is to provide a comprehensive bioinformatics resource for these pathogens, including consistently annotated genome, proteome and metabolic pathway data to facilitate research into counter-measures, including drugs, vaccines and diagnostics. The project's curation strategy has three prongs: 'breadth first' beginning with whole-genome and proteome curation using standardized protocols, a 'targeted' approach addressing the specific needs of researchers and an integrative strategy to leverage high-throughput experimental data (e.g. microarrays, proteomics) and literature. The PATRIC infrastructure consists of a relational database, analytical pipelines and a website which supports browsing, querying, data visualization and the ability to download raw and curated data in standard formats. At present, the site warehouses complete sequences for 17 bacterial and 332 viral genomes. The PATRIC website (https://patric.vbi.vt.edu) will continually grow with the addition of data, analysis and functionality over the course of the project.

Reproducibility, bioinformatic analysis and power of the SAGE method to evaluate changes in transcriptome.

The serial analysis of gene expression (SAGE) method is used to study global gene expression in cells or tissues in various experimental conditions. However, its reproducibility has not yet been definitively assessed. In this study, we have evaluated the reproducibility of the SAGE method and identified the factors that affect it. The determination coefficient (R2 ) for the reproducibility of SAGE is 0.96. However, there are some factors that can affect the reproducibility of SAGE, such as the replication of concatemers and ditags, the number of sequenced tags and double PCR amplification of ditags. Thus, corrections for these factors must be made to ensure the reproducibility and accuracy of SAGE results. A bioinformatic analysis of SAGE data is also presented in order to eliminate these artifacts. Finally, the current study shows that increasing the number of sequenced tags improves the power of the method to detect transcripts and their regulation by experimental conditions.

Mutations in the preproghrelin/ghrelin gene associated with obesity in humans.

Ghrelin and preproghrelin sequences were determined in 96 unrelated female subjects with severe obesity (mean body mass index (BMI) 42.3 +/- 3.4 kg/m(2)) and in 96 non-obese female controls (mean BMI 23.0 +/- 1.4 (kg/m2) of the Swedish Obese Subjects cohort. A mutation at amino acid position 51 (Arg51Gln) of the preproghrelin sequence that corresponds to the last amino acid in mature ghrelin product was identified in six (all heterozygotes) obese subjects (6.3%) but not among controls (p < 0.05). The self-reported weight at 20, 30, and 40 years of age tended to be 7.5, 4.7 and 6.4 kg lower, respectively, among obese Gln allele carriers versus obese non-carriers. In addition, a mutation at codon 72 of the preproghrelin gene (Leu72Met) was detected in 15 obese (12 hetero- and 3 homozygotes) and 12 control (all heterozygotes) subjects. This mutation outside the coding region of the mature ghrelin product tended to be associated with lower age of self-reported onset of obesity (15.6 +/- 7.9 vs. 20.5 +/- 10.5 years; p = 0.09). In addition to these two mutations in coding regions, a G274A base change in a non-coding region between exons one and two was found only in two obese individuals. The Arg51Gln amino acid substitution may alter the cleavage site of endoproteases and the length of the mature ghrelin product. The functional significance of the Leu72Met mutation and a G274A base change remains to be determined. In conclusion, the data provide evidence that a low frequency sequence variation in the ghrelin gene could play a role in the etiology of obesity.

Identification of protein coding regions in genomic DNA.

We have developed a computer program, GeneParser, which identifies and determines the fine structure of protein genes in genomic DNA sequences. The program scores all subintervals in a sequence for content statistics indicative of introns and exons, and for sites that identify their boundaries. This information is weighted by a neural network to approximate the log-likelihood that each subinterval exactly represents an intron or exon (first, internal or last). A dynamic programming algorithm is then applied to this data to find the combination of introns and exons that maximizes the likelihood function. Using this method, we can rapidly generate ranked suboptimal solutions, each of which is the optimum solution containing a given intron-exon junction. We have tested the system on a large collection of human genes. On sequences not used in training, we achieved a correlation coefficient for exon nucleotide prediction of 0.89. For a subset of G + C-rich genes, a correlation coefficient of 0.94 was achieved. We have also quantified the robustness of the method to substitution and frame-shift errors and show how the system can be optimized for performance on sequences with known levels of sequencing errors.

High-affinity RNA ligands to Escherichia coli ribosomes and ribosomal protein S1: comparison of natural and unnatural binding sites.

High-affinity RNA ligands were generated against intact 30S ribosomes, S1-depleted 30S ribosomes, and purified ribosomal protein S1. Sequence analysis indicated two classes of ligand: unstructured RNAs containing a Shine-Dalgarno sequence and structured RNAs containing a pseudoknot. The Shine-Dalgarno-containing ligands were generated against S1-depleted 30S ribosomes but, surprisingly, not against intact 30S ribosomes or ribosomal protein S1. In contrast, pseudoknot-containing ligands were generated against intact ribosomes as well as purified S1 protein. The two classes of ligand exhibited specificity for their respective targets, as well as conserved sequence and secondary structure reminiscent of naturally occurring, cis-acting mRNA elements.

Identification of coding regions in genomic DNA sequences: an application of dynamic programming and neural networks.

Dynamic programming (DP) is applied to the problem of precisely identifying internal exons and introns in genomic DNA sequences. The program GeneParser first scores the sequence of interest for splice sites and for these intron- and exon-specific content measures: codon usage, local compositional complexity, 6-tuple frequency, length distribution and periodic asymmetry. This information is then organized for interpretation by DP. GeneParser employs the DP algorithm to enforce the constraints that introns and exons must be adjacent and non-overlapping and finds the highest scoring combination of introns and exons subject to these constraints. Weights for the various classification procedures are determined by training a simple feed-forward neural network to maximize the number of correct predictions. In a pilot study, the system has been trained on a set of 56 human gene fragments containing 150 internal exons in a total of 158,691 bps of genomic sequence. When tested against the training data, GeneParser precisely identifies 75% of the exons and correctly predicts 86% of coding nucleotides as coding while only 13% of non-exon bps were predicted to be coding. This corresponds to a correlation coefficient for exon prediction of 0.85. Because of the simplicity of the network weighting scheme, generalization performance is nearly as good as with the training set.

Quantitating and engineering the ion specificity of an EF-hand-like Ca2+ binding.

The Escherichia coli D-galactose and D-glucose receptor, an aqueous periplasmic receptor that triggers sugar sensing and transport, possesses a single Ca2+ binding site similar in structure and specificity to the EF-hand class of sites found in eukaryotic Ca2+ signaling proteins including calmodulin and its homologues. A universal feature of these sites is the use of a pentagonal bipyramidal array of seven oxygens to coordinate bound Ca2+. Here we investigate the mechanisms used by this coordinating array to control ion specificity. To vary the cavity size and charge of the array, we have replaced axial glutamine 142 in the prokaryotic site with asparagine, glutamate, and aspartate. The ion selectivities of the resulting engineered sites have been quantitated by measuring dissociation constants for a series of spherical metal ions, differing in increments of radius and charge, from groups Ia, IIa, and IIIa and the lanthanides. Dramatic specificity changes are observed: sites containing an engineered smaller side chain (Asn or Asp) bind the largest cations up to 50-fold more tightly than the native site; and sites containing an engineered negative side chain (Glu or Asp) exhibit preferences for trivalent over divalent cations up to 1900-fold higher than the native site. The results indicate that the cavity size and negative charge of the coordination array play key roles in selective Ca2+ binding and that the array can be engineered to preferentially bind other cations.

Calcium(II) site specificity: effect of size and charge on metal ion binding to an EF-hand-like site.

The molecular mechanisms by which protein Ca(II) sites selectively bind Ca(II) even in the presence of high concentrations of other metals, particularly Na(I), K(I), and Mg(II), have not been fully described. The single Ca(II) site of the Escherichia coli receptor for D-galactose and D-glucose (GGR) is structurally related to the eukaryotic EF-hand Ca(II) sites and is ideally suited as a model for understanding the structural and electrostatic basis of Ca(II) specificity. Metal binding to the bacterial site was monitored by a Tb(III) phosphorescence assay: Ca(II) in the site was replaced with Tb(III), which was then selectively excited by energy transfer from protein tryptophans. Photons emitted from the bound Tb(III) enabled specific detection of this substrate; for other metals binding was detected by competitive displacement of Tb(III). Representative spherical metal ions from groups IA, IIA, and IIIA and the lanthanides were chosen to study the effects of metal ion size and charge on the affinity of metal binding. A dissociation constant was measured for each metal, yielding a range of KD's spanning over 6 orders of magnitude. Monovalent metal ions of group IA exhibited very low affinities. Divalent group IIA metal ions exhibited affinities related to their size, with optimal binding at an effective ionic radius between those of Mg(II) (0.81 A) and Ca(II) (1.06 A). Trivalent metal ions of group IIIA and the lanthanides also exhibited size-dependent affinities, with an optimal effective ionic radius between those of Sc(III) (0.81 A) and Yb(III) (0.925 A). The results indicate that the GGR site selects metal ions on the basis of both charge and size.(ABSTRACT TRUNCATED AT 250 WORDS)

Atttitudes of the aged toward nontraditional sexual behavior.

Age as a correlate of attitudes toward nontraditional sexual behavior is explored. The data were drawn from a United State national probability sample. Subgroup comparisons were made between two age cohorts--respondents over and under 65. Sexual attitudes were measured toward premarital sexual relations, extramartial sexual relations, and homosexuality. Older respondents held the most conservative sexual attitudes. However, the background variables of sex, social status, church attendance, marital status, and parenthood were predictors of sexual attitudes for both age strata. The findings indicate individual variations among the aged with the likelihood of a greater range of differences in the future.