Characterization of Clinically-Attenuated Burkholderia mallei by Whole Genome Sequencing: Candidate Strain for Exclusion from Select Agent Lists

is an understudied biothreat agent responsible for glanders which can be lethal in humans and animals. Research with this pathogen has been hampered in part by constraints of Select Agent regulations for safety reasons. Whole genomic sequencing (WGS) is an apt approach to characterize newly discovered or poorly understood microbial pathogens. genome. Therefore, the strain by itself is unlikely to revert naturally to its virulent phenotype. There were other genes present in one strain and not the other and vice-versa. was both avirulent in the natural host ponies, and did not possess T3SS associated genes may be fortuitous to advance biodefense research. The deleted virulence-essential T3SS is not likely to be re-acquired naturally. These findings may provide a basis for exclusion of SAVP1 from the Select Agent regulation or at least discussion of what else would be required for exclusion. This exclusion could accelerate research by investigators not possessing BSL-3 facilities and facilitate the production of reagents such as antibodies without the restraints of Select Agent regulation

Ctr2 Links Copper Homeostasis to Polysaccharide Capsule Formation and Phagocytosis Inhibition in the Human Fungal Pathogen Cryptococcus neoformans

Cryptococcus neoformans is a human opportunistic fungal pathogen responsible for ∼1/3 of HIV/AIDS deaths worldwide. This budding yeast expresses a polysaccharide capsule necessary for virulence. Capsule production inhibits phagocytosis by macrophages. Here we describe results that link copper homeostasis to capsule production and the inhibition of phagocytosis. Specifically, using Agrobacterium-mediated insertional mutagenesis, we identified an insertion in the promoter region of the putative copper transporter-encoding gene CTR2 that results in reduced expression of CTR2 and increased phagocytosis by murine RAW264.7 macrophages. The mutant also displayed sensitivity to copper starvation and defects in polysaccharide capsule production and melanization. These defects were all reversed by genetic correction of the promoter insertion by homologous targeting. Several melanization-defective mutants identified previously, those in the RIM20, RIM101, and VPS25 genes, also display sensitivity to copper starvation, reduced capsule production and increased phagocytosis. Together these results indicate a previously undescribed link between copper homeostasis to polysaccharide capsule production and phagocytosis inhibition in Cryptococcus neoformans

Spirituality as an Essential Determinant for the Good Life, its Importance Relative to Self-Determinant Psychological Needs

This study focuses on the relevance of spirituality as an essential element for the Good Life. Despite spirituality’s prominence in people’s lives and cultures, it has been mostly neglected in psychological needs theories. This paper investigates the value of spirituality compared to that of the three basic psychological needs of self-determination theory: relatedness, competence and autonomy. In a scenario study design, participants in two samples (students and train passengers) were asked to judge a survey on the personal well-being of an imaginary person. The results show that spirituality positively contributes to the qualification of a good life, in terms of desirability and moral goodness. In addition, the crucial role of relatedness was confirmed

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (λ) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty (“Forward” scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores (“Viterbi” scores) are Gumbel-distributed with constant λ = log 2, and the high scoring tail of Forward scores is exponential with the same constant λ. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments

Triad pattern algorithm for predicting strong promoter candidates in bacterial genomes

Abstract Background Bacterial promoters, which increase the efficiency of gene expression, differ from other promoters by several characteristics. This difference, not yet widely exploited in bioinformatics, looks promising for the development of relevant computational tools to search for strong promoters in bacterial genomes. Results We describe a new triad pattern algorithm that predicts strong promoter candidates in annotated bacterial genomes by matching specific patterns for the group I σ70 factors of Escherichia coli RNA polymerase. It detects promoter-specific motifs by consecutively matching three patterns, consisting of an UP-element, required for interaction with the α subunit, and then optimally-separated patterns of -35 and -10 boxes, required for interaction with the σ70 subunit of RNA polymerase. Analysis of 43 bacterial genomes revealed that the frequency of candidate sequences depends on the A+T content of the DNA under examination. The accuracy of in silico prediction was experimentally validated for the genome of a hyperthermophilic bacterium, Thermotoga maritima, by applying a cell-free expression assay using the predicted strong promoters. In this organism, the strong promoters govern genes for translation, energy metabolism, transport, cell movement, and other as-yet unidentified functions. Conclusion The triad pattern algorithm developed for predicting strong bacterial promoters is well suited for analyzing bacterial genomes with an A+T content of less than 62%. This computational tool opens new prospects for investigating global gene expression, and individual strong promoters in bacteria of medical and/or economic significance.</p

Gata3 Acts Downstream of β-Catenin Signaling to Prevent Ectopic Metanephric Kidney Induction

Metanephric kidney induction critically depends on mesenchymal–epithelial interactions in the caudal region of the nephric (or Wolffian) duct. Central to this process, GDNF secreted from the metanephric mesenchyme induces ureter budding by activating the Ret receptor expressed in the nephric duct epithelium. A failure to regulate this pathway is believed to be responsible for a large proportion of the developmental anomalies affecting the urogenital system. Here, we show that the nephric duct-specific inactivation of the transcription factor gene Gata3 leads to massive ectopic ureter budding. This results in a spectrum of urogenital malformations including kidney adysplasia, duplex systems, and hydroureter, as well as vas deferens hyperplasia and uterine agenesis. The variability of developmental defects is reminiscent of the congenital anomalies of the kidney and urinary tract (CAKUT) observed in human. We show that Gata3 inactivation causes premature nephric duct cell differentiation and loss of Ret receptor gene expression. These changes ultimately affect nephric duct epithelium homeostasis, leading to ectopic budding of interspersed cells still expressing the Ret receptor. Importantly, the formation of these ectopic buds requires both GDNF/Ret and Fgf signaling activities. We further identify Gata3 as a central mediator of β-catenin function in the nephric duct and demonstrate that the β-catenin/Gata3 pathway prevents premature cell differentiation independently of its role in regulating Ret expression. Together, these results establish a genetic cascade in which Gata3 acts downstream of β-catenin, but upstream of Ret, to prevent ectopic ureter budding and premature cell differentiation in the nephric duct

Host Genes Related to Paneth Cells and Xenobiotic Metabolism Are Associated with Shifts in Human Ileum-Associated Microbial Composition

The aim of this study was to integrate human clinical, genotype, mRNA microarray and 16 S rRNA sequence data collected on 84 subjects with ileal Crohn’s disease, ulcerative colitis or control patients without inflammatory bowel diseases in order to interrogate how host-microbial interactions are perturbed in inflammatory bowel diseases (IBD). Ex-vivo ileal mucosal biopsies were collected from the disease unaffected proximal margin of the ileum resected from patients who were undergoing initial intestinal surgery. Both RNA and DNA were extracted from the mucosal biopsy samples. Patients were genotyped for the three major NOD2 variants (Leufs1007, R702W, and G908R) and the ATG16L1T300A variant. Whole human genome mRNA expression profiles were generated using Agilent microarrays. Microbial composition profiles were determined by 454 pyrosequencing of the V3–V5 hypervariable region of the bacterial 16 S rRNA gene. The results of permutation based multivariate analysis of variance and covariance (MANCOVA) support the hypothesis that host mucosal Paneth cell and xenobiotic metabolism genes play an important role in host microbial interactions

NAViGaTing the Micronome – Using Multiple MicroRNA Prediction Databases to Identify Signalling Pathway-Associated MicroRNAs

MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (http://ophid.utoronto.ca/mirDIP).mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs.Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level