RESUMO
Arenaviridae comprises 23 recognized virus species with a bipartite ssRNA genome and an ambisense coding strategy. The virions are enveloped and include nonequimolar amounts of each genomic RNA species, designated L and S, coding for four ORFs (N, GPC, L, and Z). The arenavirus Junín (JUNV) is the etiological agent of Argentine Hemorrhagic Fever, an acute disease with high mortality rate. It has been proposed that Z is the functional counterpart of the matrix proteins found in other negative-stranded enveloped RNA viruses. Here we report the optimized expression of a synthetic gene of Z protein, using three expression systems (two bacterial and a baculoviral one). One of these recombinant proteins was used to generate antibodies. A bioinformatic analysis was made where Z was subdivided into three domains. The data presented contributes methodologies for Z recombinant production and provides the basis for the development of new experiments to test its function.
Assuntos
Vírus Junin/genética , Proteínas Recombinantes de Fusão/isolamento & purificação , Proteínas da Matriz Viral/isolamento & purificação , Sequência de Aminoácidos , Animais , Anticorpos Antivirais/metabolismo , Infecções por Arenaviridae/virologia , Western Blotting , Escherichia coli/genética , Humanos , Dados de Sequência Molecular , Estrutura Terciária de Proteína/genética , Coelhos , Proteínas Recombinantes de Fusão/química , Proteínas Recombinantes de Fusão/genética , Proteínas Recombinantes de Fusão/metabolismo , Alinhamento de Sequência , Spodoptera/genética , Proteínas da Matriz Viral/química , Proteínas da Matriz Viral/genética , Proteínas da Matriz Viral/metabolismoRESUMO
Modern biology produces data at a staggering rate. Yet, much of these biological data is still isolated in the text, figures, tables and supplementary materials of articles. As a result, biological information created at great expense is significantly underutilised. The protein motif biology field does not have sufficient resources to curate the corpus of motif-related literature and, to date, only a fraction of the available articles have been curated. In this study, we develop a set of tools and a web resource, 'articles.ELM', to rapidly identify the motif literature articles pertinent to a researcher's interest. At the core of the resource is a manually curated set of about 8000 motif-related articles. These articles are automatically annotated with a range of relevant biological data allowing in-depth search functionality. Machine-learning article classification is used to group articles based on their similarity to manually curated motif classes in the Eukaryotic Linear Motif resource. Articles can also be manually classified within the resource. The 'articles.ELM' resource permits the rapid and accurate discovery of relevant motif articles thereby improving the visibility of motif literature and simplifying the recovery of valuable biological insights sequestered within scientific articles. Consequently, this web resource removes a critical bottleneck in scientific productivity for the motif biology field. Database URL: http://slim.icr.ac.uk/articles/.