The measurement of the Higgs self-coupling at the LHC: theoretical status

Now that the Higgs boson has been observed by the ATLAS and CMS experiments at the LHC, the next important step would be to measure accurately its properties to establish the details of the electroweak symmetry breaking mechanism. Among the measurements which need to be performed, the determination of the Higgs self-coupling in processes where the Higgs boson is produced in pairs is of utmost importance. In this paper, we discuss the various processes which allow for the measurement of the trilinear Higgs coupling: double Higgs production in the gluon fusion, vector boson fusion, double Higgs-strahlung and associated production with a top quark pair. We first evaluate the production cross sections for these processes at the LHC with center-of-mass energies ranging from the present $\sqrt s=8$ TeV to $\sqrt s=100$ TeV, and discuss their sensitivity to the trilinear Higgs coupling. We include the various higher order QCD radiative corrections, at next-to-leading order for gluon and vector boson fusion and at next-to-next-to-leading order for associated double Higgs production with a gauge boson. The theoretical uncertainties on these cross sections are estimated. Finally, we discuss the various channels which could allow for the detection of the double Higgs production signal at the LHC and the accuracy on the self-coupling that could be ultimately achieved.Comment: 37 pages, 10 tables, 17 figures. Typos corrected, matches the journal versio

Badger-an accessible genome exploration environment

Summary: High-quality draft genomes are now easy to generate, as sequencing and assembly costs have dropped dramatically. However, building a user-friendly searchable Web site and database for a newly annotated genome is not straightforward. Here we present Badger, a lightweight and easy-to-install genome exploration environment designed for next generation non-model organism genomes. Availability: Badger is released under the GPL and is available at http://badger.bio.ed.ac.uk/. We show two working examples: (i) a test dataset included with the source code, and (ii) a collection of four filarial nematode genomes. Contact: [email protected]

PIG—the pathogen interaction gateway

Protein–protein interactions (PPIs) play a vital role in initiating infection in a number of pathogens. Identifying which interactions allow a pathogen to infect its host can help us to understand methods of pathogenesis and provide potential targets for therapeutics. Public resources for studying host–pathogen systems, in particular PPIs, are scarce. To facilitate the study of host–pathogen PPIs, we have collected and integrated host–pathogen PPI (HP–PPI) data from a number of public resources to create the Pathogen Interaction Gateway (PIG). PIG provides a text based search and a BLAST interface for searching the HP–PPI data. Each entry in PIG includes information such as the functional annotations and the domains present in the interacting proteins. PIG provides links to external databases to allow for easy navigation among the various websites. Additionally, PIG includes a tool for visualizing a single HP–PPI network or two HP–PPI networks. PIG can be accessed at http://pig.vbi.vt.edu

A new bioinformatics analysis tools framework at EMBL–EBI

The EMBL-EBI provides access to various mainstream sequence analysis applications. These include sequence similarity search services such as BLAST, FASTA, InterProScan and multiple sequence alignment tools such as ClustalW, T-Coffee and MUSCLE. Through the sequence similarity search services, the users can search mainstream sequence databases such as EMBL-Bank and UniProt, and more than 2000 completed genomes and proteomes. We present here a new framework aimed at both novice as well as expert users that exposes novel methods of obtaining annotations and visualizing sequence analysis results through one uniform and consistent interface. These services are available over the web and via Web Services interfaces for users who require systematic access or want to interface with customized pipe-lines and workflows using common programming languages. The framework features novel result visualizations and integration of domain and functional predictions for protein database searches. It is available at http://www.ebi.ac.uk/Tools/sss for sequence similarity searches and at http://www.ebi.ac.uk/Tools/msa for multiple sequence alignments

A predictor for toxin-like proteins exposes cell modulator candidates within viral genomes

Motivation: Animal toxins operate by binding to receptors and ion channels. These proteins are short and vary in sequence, structure and function. Sporadic discoveries have also revealed endogenous toxin-like proteins in non-venomous organisms. Viral proteins are the largest group of quickly evolving proteomes. We tested the hypothesis that toxin-like proteins exist in viruses and that they act to modulate functions of their hosts

Direct detection of Higgs-portal dark matter at the LHC

We consider the process in which a Higgs particle is produced in association with jets and show that monojet searches at the LHC already provide interesting constraints on the invisible decays of a 125 GeV Higgs boson. Using the existing monojet searches performed by CMS and ATLAS, we show the 95% confidence level limit on the invisible Higgs decay rate is of the order of the total Higgs production rate in the Standard Model. This limit could be significantly improved when more data at higher center of mass energies are collected, provided systematic errors on the Standard Model contribution to the monojet background can be reduced. We also compare these direct constraints on the invisible rate with indirect ones based on measuring the Higgs rates in visible channels. In the context of Higgs portal models of dark matter, we then discuss how the LHC limits on the invisible Higgs branching fraction impose strong constraints on the dark matter scattering cross section on nucleons probed in direct detection experiments.Comment: 6 pages, 3 figures; v2: references added; v3: monojet and Higgs data updated, version published in EPJ

The Echinococcus canadensis (G7) genome: A key knowledge of parasitic platyhelminth human diseases

Background: The parasite Echinococcus canadensis (G7) (phylum Platyhelminthes, class Cestoda) is one of the causative agents of echinococcosis. Echinococcosis is a worldwide chronic zoonosis affecting humans as well as domestic and wild mammals, which has been reported as a prioritized neglected disease by the World Health Organisation. No genomic data, comparative genomic analyses or efficient therapeutic and diagnostic tools are available for this severe disease. The information presented in this study will help to understand the peculiar biological characters and to design species-specific control tools. Results: We sequenced, assembled and annotated the 115-Mb genome of E. canadensis (G7). Comparative genomic analyses using whole genome data of three Echinococcus species not only confirmed the status of E. canadensis (G7) as a separate species but also demonstrated a high nucleotide sequences divergence in relation to E. granulosus (G1). The E. canadensis (G7) genome contains 11,449 genes with a core set of 881 orthologs shared among five cestode species. Comparative genomics revealed that there are more single nucleotide polymorphisms (SNPs) between E. canadensis (G7) and E. granulosus (G1) than between E. canadensis (G7) and E. multilocularis. This result was unexpected since E. canadensis (G7) and E. granulosus (G1) were considered to belong to the species complex E. granulosus sensu lato. We described SNPs in known drug targets and metabolism genes in the E. canadensis (G7) genome. Regarding gene regulation, we analysed three particular features: CpG island distribution along the three Echinococcus genomes, DNA methylation system and small RNA pathway. The results suggest the occurrence of yet unknown gene regulation mechanisms in Echinococcus. Conclusions: This is the first work that addresses Echinococcus comparative genomics. The resources presented here will promote the study of mechanisms of parasite development as well as new tools for drug discovery. The availability of a high-quality genome assembly is critical for fully exploring the biology of a pathogenic organism. The E. canadensis (G7) genome presented in this study provides a unique opportunity to address the genetic diversity among the genus Echinococcus and its particular developmental features. At present, there is no unequivocal taxonomic classification of Echinococcus species; however, the genome-wide SNPs analysis performed here revealed the phylogenetic distance among these three Echinococcus species. Additional cestode genomes need to be sequenced to be able to resolve their phylogeny.Fil: Maldonado, Lucas Luciano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Assis, Juliana. Fundación Oswaldo Cruz; BrasilFil: Gomes Araújo, Flávio M.. Fundación Oswaldo Cruz; BrasilFil: Salim, Anna C. M.. Fundación Oswaldo Cruz; BrasilFil: Macchiaroli, Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Cucher, Marcela Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Camicia, Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Fox, Adolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Rosenzvit, Mara Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Oliveira, Guilherme. Instituto Tecnológico Vale; Brasil. Fundación Oswaldo Cruz; BrasilFil: Kamenetzky, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentin

Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information.AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins.AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains

Purification and functional characterisation of rhiminopeptidase A, a novel aminopeptidase from the venom of Bitis gabonica rhinoceros

This study describes the discovery and characterisation of a novel aminopeptidase A from the venom of B. g. rhinoceros and highlights its potential biological importance. Similar to mammalian aminopeptidases, rhiminopeptidase A might be capable of playing roles in altering the blood pressure and brain function of victims. Furthermore, it could have additional effects on the biological functions of other host proteins by cleaving their N-terminal amino acids. This study points towards the importance of complete analysis of individual components of snake venom in order to develop effective therapies for snake bites