50 research outputs found
SUS-BAR: a database of pig proteins with statistically validated structural and functional annotation
Given the relevance of the pig proteome in different studies, including human complex maladies, a statistical validation of the annotation is required for a better understanding of the role of specific genes and proteins in the complex networks underlying biological processes in the animal. Presently, approximately 80% of the pig proteome is still poorly annotated, and the existence of protein sequences is routinely inferred automatically by sequence alignment towards preexisting sequences. In this article, we introduce SUS-BAR, a database that derives information mainly from UniProt Knowledgebase and that includes 26 206 pig protein sequences. In SUS-BAR, 16 675 of the pig protein sequences are endowed with statistically validated functional and structural annotation. Our statistical validation is determined by adopting a cluster-centric annotation procedure that allows transfer of different types of annotation, including structure and function. Each sequence in the database can be associated with a set of statistically validated Gene Ontologies (GOs) of the three main sub-ontologies (Molecular Function, Biological Process and Cellular Component), with Pfam functional domains, and when possible, with a cluster Hidden Markov Model that allows modelling the 3D structure of the protein. A database search allows some statistics demonstrating the enrichment in both GO and Pfam annotations of the pig proteins as compared with UniProt Knowledgebase annotation. Searching in SUS-BAR allows retrieval of the pig protein annotation for further analysis. The search is also possible on the basis of specific GO terms and this allows retrieval of all the pig sequences participating into a given biological process, after annotation with our system. Alternatively, the search is possible on the basis of structural information, allowing retrieval of all the pig sequences with the same structural characteristics
Cloning, expression, and antigenic characterization of recombinant protein of Mycoplasma gallisepticum expressed in Escherichia coli
Viral load, tissue distribution and histopathological lesions in goats naturally and experimentally infected with the Small Ruminant Lentivirus Genotype E (subtype E1 Roccaverano strain)
Small Ruminant Lentivirus (SRLV) subtype E1, also known as Roccaverano strain, is considered a low pathogenic virus on the basis of natural genetic deletions, in vitro properties and on-farm observations. In order to gain more knowledge on this atypical lentivirus we investigated the in vivo tropism of Roccaverano strain in both, experimentally and naturally infected goats. Antibody responses were monitored as well as tissue distribution and viral load, evaluated by real time PCR on single spliced (gag/env) and multiple spliced (rev) RNA targets respectively, that were compared to histopathological lesions. Lymph nodes, spleen, alveolar macrophages and mammary gland turned out to be the main tissue reservoirs of genotype E1-provirus. Moreover, mammary gland and/or mammary lymph nodes acted as active replication sites in dairy goats, supporting the lactogenic transmission of this virus. Notably, a direct association between viral load and concomitant infection or inflammatory processes was evident within organs such as spleen, lung and testis.
Our results validate the low pathogenicity designation of SRLV genotype E1 in vivo, and confirm the monocyte-macrophage cell lineage as the main virus reservoir of this genotype. Accordingly, SRLV genotype E displays a tropism towards all tissues characterized by an abundant presence of these cells, either for their own anatomical structure or for an occasional infectious/inflammatory status.This work was co-funded by the Italian Ministry of Instruction, University and Research PRIN 2008 (no. 20084CSFLT), by Piedmont Region, “Ricerca Sanitaria Finalizzata” 2008 and 2009, and by University of Turin, “Fondi ricerca locale (ex-60%)” 2009. The Authors acknowledge Mr. R. Maritano, CISRA for his valuable contribution in animal management, and Mr. D. Arnulfo and R. Vanni for their competent work and assistance during animal autopsies.
R. Reina was supported by Spanish Ministry of Science and Innovation ‘Ramón y Cajal’ contract (AGL2013-49137-C3-1R).Peer reviewe
Small ruminant lentivirus genotype B and E interaction: Evidences on the role of Roccaverano strain on reducing proviral load of the challenging CAEV strain.
Live attenuated vaccines provide the most consistent protective immunity in experimental models of lentivirus infections. In this study we tested the hypothesis that animals infected with a naturally attenuated small ruminant lentivirus field strain of genotype E may control a challenge infection with a virulent strain of the caprine arthritis encephalitis virus (CAEV-CO). Within genotype E, Roccaverano strain has been described as attenuated since decreased arthritic pathological indexes were recorded in Roccaverano-infected animals compared to animals of the same breed infected with genotype B strains. Moreover, under natural conditions, animals double-infected with genotypes B and E appear less prone to develop SRLV-related disease, leading to a putative protective role of Roccaverano strain. Here we present evidence that goats experimentally infected with the avirulent genotype E SRLV-Roccaverano strain control the proviral load of a pathogenic challenge virus (CAEV-CO strain) more efficiently than naïve animals and appear to limit the spread of histological lesions to the contralateral joints
Using community events to increase quality and adoption of standards: the case of Bioschemas
We present how a workshop for the local Italian ELIXIR community steered an improvement of the quality and adoption of Bioschemas, a series of semantic annotation templates for tools, data and samples developed by the ELIXIR Interoperability platform. Gathering a small number of different end-users and having them focus on applying Bioschemas specification to their tools and data resulted in recruitment of early adopters, eight annotated resources, Bioschemas examples for future users and more than ten suggestions for specification improvement. This approach could be applied to other open specifications, promoting a wider adoption and the integration of suggestions in a bottom-up fashion
ELIXIR‐IT: a growing support to national and international research in life sciences
ELIXIR-IT gathers most of the excellence centres or bioinformatics in Italy and is striving to assume pivotal role for the national and international life science communities. This is reflected by the growing number of bioinformatics services, initiatives and projects supported or participated by ELIXIR-IT, including H2020 grants and a number of training efforts delivering state of the arts courses on basic and advanced topics. In this poster we highlight some of the activities
Tools and data services registry: a community effort to document bioinformatics resources.
Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.Here we present a community-driven curation effort, supported by ELIXIR-the European infrastructure for biological information-that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
Background: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function.
Results: Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole genome mutation screening in Candida albicans and aeruginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory.
Conclusion: We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio