Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors

We investigate the application of hierarchical classification schemes to the annotation of gene function based on several characteristics of protein sequences including phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL) model, a hierarchical model based on a set of nested MNL models, and a MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs) from the E. coli genome. The results from all three models show substantial improvement over previous methods, which were based on the C5 algorithm. The MNL model using a prior based on the hierarchy outperforms both the non-hierarchical MNL model and the nested MNL model. In contrast to previous attempts at combining these sources of information, our approach results in a higher accuracy rate when compared to models that use each data source alone. Together, these results show that gene function can be predicted with higher accuracy than previously achieved, using Bayesian models that incorporate suitable prior information

Virtual screening for inhibitors of the human TSLP:TSLPR interaction

The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Ra), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an in silico characterization of the TSLP: TSLPR complex to investigate the drugability of this complex. Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP: alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP: TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-ofprinciple for use of fragments in the inhibition of TSLP: TSLPR complexation

Scoring Protein Relationships in Functional Interaction Networks Predicted from Sequence Data

The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins

The Personal Sequence Database: a suite of tools to create and maintain web-accessible sequence databases

Background: Large molecular sequence databases are fundamental resources for modern\ud bioscientists. Whether for project-specific purposes or sharing data with colleagues, it is often\ud advantageous to maintain smaller sequence databases. However, this is usually not an easy task for\ud the average bench scientist.\ud \ud Results: We present the Personal Sequence Database (PSD), a suite of tools to create and\ud maintain small- to medium-sized web-accessible sequence databases. All interactions with PSD\ud tools occur via the internet with a web browser. Users may define sequence groups within their\ud database that can be maintained privately or published to the web for public use. A sequence group\ud can be downloaded, browsed, searched by keyword or searched for sequence similarities using\ud BLAST. Publishing a sequence group extends these capabilities to colleagues and collaborators. In\ud addition to being able to manage their own sequence databases, users can enroll sequences in\ud BLASTAgent, a BLAST hit tracking system, to monitor NCBI databases for new entries displaying\ud a specified level of nucleotide or amino acid similarity.\ud \ud Conclusion: The PSD offers a valuable set of resources unavailable elsewhere. In addition to\ud managing sequence data and BLAST search results, it facilitates data sharing with colleagues,\ud collaborators and public users. The PSD is hosted by the authors and is available at http://\ud bioinfo.cgrb.oregonstate.edu/psd/

Copy Number Variation in CNP267 Region May Be Associated with Hip Bone Size

Osteoporotic hip fracture (HF) is a serious global public health problem associated with high morbidity and mortality. Hip bone size (BS) has been identified as one of key measurable risk factors for HF, independent of bone mineral density (BMD). Hip BS is highly genetically determined, but genetic factors underlying BS variation are still poorly defined. Here, we performed an initial genome-wide copy number variation (CNV) association analysis for hip BS in 1,627 Chinese Han subjects using Affymetrix GeneChip Human Mapping SNP 6.0 Array and a follow-up replicate study in 2,286 unrelated US Caucasians sample. We found that a copy number polymorphism (CNP267) located at chromosome 2q12.2 was significantly associated with hip BS in both initial Chinese and replicate Caucasian samples with p values of 4.73E-03 and 5.66E-03, respectively. An important candidate gene, four and a half LIM domains 2 (FHL2), was detected at the downstream of CNP267, which plays important roles in bone metabolism by binding to several bone formation regulator, such as insulin-like growth factor-binding protein 5 (IGFBP-5) and androgen receptor (AR). Our findings suggest that CNP267 region may be associated with hip BS which might influence the FHL2 gene downstream

Therapeutic effects of pyrrolidine dithiocarbamate on acute lung injury in rabbits

<p>Abstract</p> <p>Background</p> <p>Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) is an early characteristic of multiple organ dysfunction, responsible for high mortality and poor prognosis in patients. The present study aims to evaluate therapeutic effects and mechanisms of pyrrolidine dithiocarbamate (PDTC) on ALI.</p> <p>Methods</p> <p>Alveolar-arterial oxygen difference, lung tissue edema and compromise, NF-κB activation in polymorphonuclear neutrophil (PMN), and systemic levels of tumor necrosis factor-alpha (TNFa) and intercellular adhesion molecule-1 (ICAM-1) in rabbits induced by the intravenous administration of lipopolysaccharide (LPS) and treated with PDTC. Production of TNFa and IL-8, activation of Cathepsin G, and PMNs adhesion were also measured.</p> <p>Results</p> <p>The intravenous administration of PDTC had partial therapeutic effects on endotoxemia-induced lung tissue edema and damage, neutrophil influx to the lung, alveolar-capillary barrier dysfunction, and high systemic levels of TNFa and ICAM-1 as well as over-activation of NF-κB. PDTC could directly and partially inhibit LPS-induced TNFa hyper-production and over-activities of Cathepsin G. Such inhibitory effects of PDTC were related to the various stimuli and enhanced through combination with PI3K inhibitor.</p> <p>Conclusion</p> <p>NF-κB signal pathway could be one of targeting molecules and the combination with other signal pathway inhibitors may be an alternative of therapeutic strategies for ALI/ARDS.</p

Molecular characterization and phylogenetic analysis of betasatellite molecules associated with okra yellow vein mosaic disease in Sri Lanka

Okra production in Sri Lanka has been severely affected by okra yellow vein mosaic disease (OYVMD), which is caused by begomoviruses and associated betasatellites. These betasatellite molecules commonly determine the development and severity of the disease. Therefore, knowledge about the genetic variability of betasatellites associated with OYVMD could assist okra breeding programs in the selection of resistant varieties. The present study aimed to characterize the betasatellite DNA sequences associated with OYVMD in Sri Lanka and to determine their phylogenetic relationships. Betasatellite DNA of six virus isolates from widely separated geographical locations were sequenced and compared with already reported begomovirus betasatellites. The betasatellite molecules have features common to other betasatellite DNAs: a conserved nonanucleotide TAATATTAC, a coding sequence for the protein βC1, an adenine rich region and a satellite conserved region. Nucleotide diversity among the isolates was relatively low (π = 0.034). A recombination event was detected at a specific region in the genome of all isolates. The isolates shared >96% sequence identity with bhendi yellow vein betasatellites reported from India and phylogenetic analysis confirmed their genetic relationship

PLCL1 rs7595412 variation is not associated with hip bone size variation in postmenopausal Danish women

<p>Abstract</p> <p>Background</p> <p>Bone size (BS) variation is under strong genetic control and plays an important role in determining bone strength and fracture risk. Recently, a genome-wide association study identified polymorphisms associated with hip BS variation in the <it>PLCL1 </it>(phospholipase c-like 1) locus. Carriers of the major A allele of the most significant polymorphism, rs7595412, have around 17% larger hip BS than non-carriers. We therefore hypothesized that this polymorphism may also influence postmenopausal complications.</p> <p>Methods</p> <p>The effects of rs7595412 on hip BS, bone mineral density (BMD), vertebral fractures, serum Crosslaps and osteocalcin levels were analyzed in 1,191 postmenopausal Danish women.</p> <p>Results</p> <p>This polymorphism had no influence on hip and spine BS as well as on femur and spine BMD. Women carrying at least one copy of the A allele had lower levels of serum osteocalcin as compared with those homozygous for the G allele (p = 0.03) whereas no effect on serum Crosslaps was detected. Furthermore, women homozygous for the A allele were more affected by vertebral fractures than those carrying at least one copy of the G allele (p = 0.04).</p> <p>Conclusions</p> <p>In postmenopausal women, our results suggest that the <it>PLCL1 </it>rs7595412 polymorphism has no obvious effect on hip BS or BMD but may be nominally associated with increased proportion of vertebral fracture and increased levels of osteocalcin.</p