UNLABELLED: End-to-end next-generation sequencing microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult owing to a lack of interoperability, reproducibility and transparency. To overcome these limitations we present Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for next-generation sequencing microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics. AVAILABILITY AND IMPLEMENTATION: Orione is available online at http://orione.crs4.it.

MOTIVATION: Analysis of the human genome revealed that the amount of transcribed sequence is an order of magnitude greater than the number of predicted and well-characterized genes. A sizeable fraction of these transcripts is related to alternatively spliced forms of known protein coding genes. Inspection of the alternatively spliced transcripts identified in the pilot phase of the ENCODE project has clearly shown that often their structure might substantially differ from that of other isoforms of the same gene, and therefore that they might perform unrelated functions, or that they might even not correspond to a functional protein. Identifying these cases is obviously relevant for the functional assignment of gene products and for the interpretation of the effect of variations in the corresponding proteins. RESULTS: Here we describe a publicly available tool that, given a gene or a protein, retrieves and analyses all its annotated isoforms, provides users with three-dimensional models of the isoform(s) of his/her interest whenever possible and automatically assesses whether homology derived structural models correspond to plausible structures. This information is clearly relevant. When the homology model of some isoforms of a gene does not seem structurally plausible, the implications are that either they assume a structure unrelated to that of the other isoforms of the same gene with presumably significant functional differences, or do not correspond to functional products. We provide indications that the second hypothesis is likely to be true for a substantial fraction of the cases. AVAILABILITY: http://maistas.bioinformatica.crs4.it/.

BACKGROUND: Bacterial infections represent a global health challenge. The identification of novel antibacterial targets for both therapy and vaccination is needed on a constant basis because resistance continues to spread worldwide at an alarming rate. Even infections that were once easy to treat are becoming difficult or, in some cases, impossible to cure. Ideal targets for both therapy and vaccination are bacterial proteins exposed on the surface of the organism, which are often involved in host-pathogen interaction. Their identification can greatly benefit from technologies such as bioinformatics, proteomics and DNA microarrays. RESULTS: Here we describe a pipeline named SLEP (Surface Localization Extracellular Proteins), based on an automated optimal combination and sequence of usage of reliable available tools for the computational identification of the surfome, i.e. of the subset of proteins exposed on the surface of a bacterial cell. CONCLUSIONS: The tool not only simplifies the usage of these methods, but it also improves the results by selecting the specifying order and combination of the instruments. The tool is freely available at http://www.caspur.it/slep.

BACKGROUND: One of the most interesting problems in molecular immunology is epitope mapping, i.e. the identification of the regions of interaction between an antigen and an antibody. The solution to this problem, even if approximate, would help in designing experiments to precisely map the residues involved in the interaction and could be instrumental both in designing peptides able to mimic the interacting surface of the antigen and in understanding where immunologically important regions are located in its three-dimensional structure. From an experimental point of view, both genetically encoded and chemically synthesised peptide libraries can be used to identify sequences recognized by a given antibody. The problem then arises of which region of a folded protein the selected peptides correspond to. RESULTS: We have developed a method able to find the surface region of a protein that can be effectively mimicked by a peptide, given the structure of the protein and the maximum number of side chains deemed to be required for recognition. The method is implemented as a publicly available server. It can also find and report all peptide sequences of a specified length that can mimic the surface of a given protein and store them in a database. The immediate application of the server is the mapping of antibody epitopes, however the system is sufficiently flexible for allowing other questions to be asked, for example one can compare the peptides representing the surface of two proteins known to interact with the same macromolecule to find which is the most likely interacting region. CONCLUSION: We believe that the MEPS server, available at http://www.caspur.it/meps, will be a useful tool for immunologists and structural and computational biologists. We plan to use it ourselves to implement a database of "surface mimicking peptides" for all proteins of known structure and proteins that can be reliably modelled by comparative modelling.