Searching for the QCD Axion with Gravitational Microlensing

The phase transition responsible for axion dark matter production can create large amplitude isocurvature perturbations which collapse into dense objects known as axion miniclusters. We use microlensing data from the EROS survey, and from recent observations with the Subaru Hyper Suprime Cam to place constraints on the minicluster scenario. We compute the microlensing event rate for miniclusters treating them as spatially extended objects with an extended mass function. Using the published bounds on the number of microlensing events we bound the fraction of DM collapsed into miniclusters, $f_{\rm MC}$. For an axion with temperature dependent mass consistent with the QCD axion we find $f_{\rm MC}<0.22(m_a/100\,\mu\text{eV})^{-0.57}$, which represents the first observational constraint on the minicluster fraction. We forecast that a high-efficiency observation of ten nights with Subaru would be sufficient to constrain $f_{\rm MC}\lesssim 0.1$ over the entire QCD axion mass range. We make various approximations to derive these constraints and dedicated analyses by the observing teams of EROS and Subaru are necessary to confirm our results. If accurate theoretical predictions for $f_{\rm MC}$ can be made in future then microlensing can be used to exclude, or discover, the QCD axion. Further details of our computations are presented in a companion paper.Comment: 5 pages, 4 figures, v2 contains an improved description of our modeling of miniclusters and lensing with revised limits, matches version accepted in PR

InterProScan: protein domains identifier

InterProScan [E. M. Zdobnov and R. Apweiler (2001) Bioinformatics, 17, 847–848] is a tool that combines different protein signature recognition methods from the InterPro [N. J. Mulder, R. Apweiler, T. K. Attwood, A. Bairoch, A. Bateman, D. Binns, P. Bradley, P. Bork, P. Bucher, L. Cerutti et al. (2005) Nucleic Acids Res., 33, D201–D205] consortium member databases into one resource. At the time of writing there are 10 distinct publicly available databases in the application. Protein as well as DNA sequences can be analysed. A web-based version is accessible for academic and commercial organizations from the EBI (). In addition, a standalone Perl version and a SOAP Web Service [J. Snell, D. Tidwell and P. Kulchenko (2001) Programming Web Services with SOAP, 1st edn. O'Reilly Publishers, Sebastopol, CA, ] are also available to the users. Various output formats are supported and include text tables, XML documents, as well as various graphs to help interpret the results

AutoPSI: a database for automatic structural classification of protein sequences and structures

In protein research, structural classifications of protein domains provided by databases such as SCOP play an important role. However, as such databases have to be curated and prepared carefully, they update only up to a few times per year, and in between newly entered PDB structures cannot be used in cases where a structural classification is required. The Automated Protein Structure Identification (AutoPSI) database delivers predicted SCOP classifications for several thousand yet unclassified PDB entries as well as millions of UniProt sequences in an automated fashion. In order to obtain predictions, we make use of two recently published methods, namely AutoSCOP (sequence-based) and Vorolign (structure-based) and the consensus of both. With our predictions, we bridge the gap between SCOP versions for proteins with known structures in the PDB and additionally make structure predictions for a very large number of UniProt proteins. AutoPSI is freely accessible at http://www.bio.ifi.lmu.de/AutoPSIDB

Java GUI for InterProScan (JIPS): A tool to help process multiple InterProScans and perform ortholog analysis

BACKGROUND: Recent, rapid growth in the quantity of available genomic data has generated many protein sequences that are not yet biochemically classified. Thus, the prediction of biochemical function based on structural motifs is an important task in post-genomic analysis. The InterPro databases are a major resource for protein function information. For optimal results, these databases should be searched at regular intervals, since they are frequently updated. RESULTS: We describe here a new program JIPS (Java GUI for InterProScan), a tool for tracking and viewing results obtained from repeated InterProScan searches. JIPS stores matches (in a local database) obtained from InterProScan searches performed with multiple versions of the InterPro database and highlights hits that have been added since the last search of the InterPro database. Results are displayed in an easy-to-use tabular format. JIPS also contains tools to assist with ortholog-based comparative studies of protein signatures. CONCLUSION: JIPS is an efficient tool for performing repeated InterProScans on large batches of protein sequences, tracking and viewing search results, and mining the collected data

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

Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation

InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models

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

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

Potential conservation of circadian clock proteins in the phylum Nematoda as revealed by bioinformatic searches

Although several circadian rhythms have been described in C. elegans, its molecular clock remains elusive. In this work we employed a novel bioinformatic approach, applying probabilistic methodologies, to search for circadian clock proteins of several of the best studied circadian model organisms of different taxa (Mus musculus, Drosophila melanogaster, Neurospora crassa, Arabidopsis thaliana and Synechoccocus elongatus) in the proteomes of C. elegans and other members of the phylum Nematoda. With this approach we found that the Nematoda contain proteins most related to the core and accessory proteins of the insect and mammalian clocks, which provide new insights into the nematode clock and the evolution of the circadian system.Fil: Romanowski, Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; ArgentinaFil: Garavaglia, Matías Javier. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Ing.genética y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Goya, María Eugenia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ghiringhelli, Pablo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Ing.genética y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Golombek, Diego Andres. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin