LocateP: Genome-scale subcellular-location predictor for bacterial proteins

Contains fulltext : 69477.pdf ( ) (Open Access)BACKGROUND: In the past decades, various protein subcellular-location (SCL) predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase) cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. RESULTS: LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms current tools especially where the N-terminally anchored and the SPIase-cleaved secreted proteins are concerned. Overall, the accuracy of LocateP was always higher than 90%. LocateP was then used to predict the SCLs of all proteins encoded by completed Gram-positive bacterial genomes. The results are stored in the database LocateP-DB http://www.cmbi.ru.nl/locatep-db1. CONCLUSION: LocateP is by far the most accurate and detailed protein SCL predictor for Gram-positive bacteria currently available

Genetically Determined Rheumatoid Arthritis May Not Affect Heart Failure: Insights from Mendelian Randomization Study

Background: Evidence from observational epidemiological studies indicated that rheumatoid arthritis (RA) increased the risk of heart failure (HF). However, there is a possibility that the correlation is not explained as a causative role for RA in the pathogenesis of HF. A two-sample Mendelian randomization (MR) framework was designed to explore the potential etiological role of RA in HF to identify the target to improve the burden of HF disease. Methods: To assess the causal association between RA and HF, we analyzed summary statistics from genome-wide association studies (GWASs) for individuals of European descent. Genetic instruments for RA were identified at a genome-wide significance threshold (p 0.05). Conclusion: Our findings did not support the causal role of RA in the etiology of HF. As such, therapeutics targeted at the control of RA may have a lower likelihood of effectively controlling the occurrence of HF

How to Achieve Efficiency and Accuracy in Discrete Element Simulation of Asphalt Mixture: A DRF-Based Equivalent Model for Asphalt Sand Mortar

The clump-based discrete element model is one of the asphalt mixture simulation methods, which has the potential to not only predict mixture performance but also simulate particle movement during compaction, transporting, and other situations. However, modelling of asphalt sand mortar in this method remains to be a problem due to computing capacity. Larger-sized balls (generally 2.0-2.36 mm) were usually used to model the smaller particles and asphalt binder, but this replacement may result in the mixture\u27s unrealistic volumetric features. More specifically, replacing original elements with equal volume but larger size particles will increase in buck volume and then different particle contacting states. The major objective of this research is to provide a solution to the dilemma situation through an improved equivalent model of the smaller particles and asphalt binders. The key parameter of the equivalent model is the diameter reduction factor (DRF), which was proposed in this research to minimize the effects of asphalt mortar\u27s particle replacement modelling. To determine DRF, the DEM-based analysis was conducted to evaluate several mixture features, including element overlap ratio, ball-wall contact number, and the average wall stress. Through this study, it was observed that when the original glued ball diameters are ranging from 2.00 mm and 2.36 mm, the diameter reduction factor changes from 0.82 to 0.86 for AC mixtures and 0.80 to 0.84 for SMA mixtures. The modelling method presented in this research is suitable not only for asphalt mixtures but also for the other particulate mix with multisize particles

Characterization and Inference of Gene Gain/Loss Along Burkholderia Evolutionary History

A comparative analysis of 60 complete Burkholderia genomes was conducted to obtain insight in the evolutionary history behind the diversity and pathogenicity at species level. A concatenated multiprotein phyletic pattern and a dataset with Burkholderia clusters of orthologous genes (BuCOGs) were constructed. The extent of horizontal gene transfer (HGT) was assessed using a Markov based probabilistic method. A reconstruction of the gene gains and losses history shows that more than half of the Burkholderia genes families are inferred to have experienced HGT at least once during their evolution. Further analysis revealed that the number of gene gain and loss was correlated with the branch length. Genomic islands (GEIs) analysis based on evolutionary history reconstruction not only revealed that most genes in ancient GEIs were gained but also suggested that the fraction of the genome located in GEIs in the small chromosomes is higher than in the large chromosomes in Burkholderia. The mapping of coexpressed genes onto biological pathway schemes revealed that pathogenicity of Burkholderia strains is probably mainly determined by the gained genes in its ancestor. Taken together, our results strongly support that gene gain and loss especially in ancient evolutionary history play an important role in strain divergence, pathogenicity determinants of Burkholderia and GEIs formation

Complete Sequence of a F33:A-:B- Conjugative Plasmid Carrying the oqxAB, fosA3, and blaCTX-M-55 Elements from a Foodborne Escherichia coli Strain

This study reports the complete sequence of pE80, a conjugative IncFII plasmid recovered from an Escherichia coli strain isolated from chicken meat. This plasmid harbors multiple resistance determinants including oqxAB, fosA3, blaCTX-M-55, and blaTEM-1, and is a close variant of the recently reported p42-2 element, which was recovered from E. coli of veterinary source. Recovery of pE80 constitutes evidence that evolution or genetic re-arrangement of IncFII type plasmids residing in animal-borne organisms is an active event, which involves acquisition and integration of foreign resistance elements into the plasmid backbone. Dissemination of these plasmids may further compromise the effectiveness of current antimicrobial strategies.Department of Applied Biology and Chemical Technolog

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger

Background: The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains Delta xlnR, Delta araR, Delta amyR, Delta rhaR and Delta galX that were grown on their specific inducing compounds. Results: The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far. Conclusions: Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In addition, the data provides additional evidence in favor of and against the similarity-based functions assigned to uncharacterized genes.Peer reviewe