Plant-antivenom: Database of anti-venom medicinal plants

Plant-antivenom is a computational Websystem about medicinal plants with anti-venom properties. The system consists of a database of these plants, including scientific publications on this subject and amino acid sequences of active principles from venomous animals. The system relates these data allowing their integration through different search applications. For the development of the system, the first surveys were conducted in scientific literature, allowing the creation of a publication database in a library for reading and user interaction. Then, classes of categories were created, allowing the use of tags and the organization of content. This database on medicinal plants has information such as family, species, isolated compounds, activity, inhibited animal venoms, among others. Provision is made for submission of new information by registered users, by the use of wiki tools. Content submitted is released in accordance to permission rules defined by the system. The database on biological venom protein amino acid sequences was structured from the essential information from National Center for Biotechnology Information (NCBI). Plant-antivenom's interface is simple, contributing to a fast and functional access to the system and the integration of different data registered on it. Plant-antivenom system is available on the Internet at http://gbi.fmrp.usp.br/plantantivenom

Poly (A)+ Transcriptome Assessment of ERBB2-Induced Alterations in Breast Cell Lines

We report the first quantitative and qualitative analysis of the poly (A)+ transcriptome of two human mammary cell lines, differentially expressing (human epidermal growth factor receptor) an oncogene over-expressed in approximately 25% of human breast tumors. Full-length cDNA populations from the two cell lines were digested enzymatically, individually tagged according to a customized method for library construction, and simultaneously sequenced by the use of the Titanium 454-Roche-platform. Comprehensive bioinformatics analysis followed by experimental validation confirmed novel genes, splicing variants, single nucleotide polymorphisms, and gene fusions indicated by RNA-seq data from both samples. Moreover, comparative analysis showed enrichment in alternative events, especially in the exon usage category, in ERBB2 over-expressing cells, data indicating regulation of alternative splicing mediated by the oncogene. Alterations in expression levels of genes, such as LOX, ATP5L, GALNT3, and MME revealed by large-scale sequencing were confirmed between cell lines as well as in tumor specimens with different ERBB2 backgrounds. This approach was shown to be suitable for structural, quantitative, and qualitative assessment of complex transcriptomes and revealed new events mediated by ERBB2 overexpression, in addition to potential molecular targets for breast cancer that are driven by this oncogene

In silico Connection between Medicinal Plants and Animals Venom

Na grande diversidade de plantas encontrada em todo o mundo, encontram-se as plantas medicinais com propriedades antivenenos. O estudo da relação dessas plantas com venenos de animais contribui muito para o desenvolvimento de novos medicamentos. A quantidade de dados a ser armazenada e a relação dessas informações é um processo que deve ser administrado por um sistema computacional. O desenvolvimento de sistemas de computadores tem se destacado nos últimos anos na Bioinformática e são muito úteis para organizar diferentes tipos de dados e, juntamente, com o uso de gerenciadores de conteúdo, eles contribuem, significantemente, no processo de desenvolvimento de softwares. O presente projeto teve como objetivo o desenvolvimento de um sistema computacional para Web, o qual relaciona dados de plantas medicinais com propriedades antivenenos e de animais venenosos, permitindo a integração dos mesmos, através de diferentes aplicativos de busca. O sistema foi denominado de Venom e está disponível no site http://gbi.fmrp.usp.br/venom/. Foram criadas categorias para a classificação dos dados de plantas e de animais. Essa categorização das informações é muito importante, pois possibilita o relacionamento das mesmas nas buscas por categorias. Os dados, tanto de plantas quanto de animais, foram extraídos de artigos científicos e de bases de dados públicos. Família, espécie, composto isolado e nome popular são algumas das informações referentes às plantas. Quanto aos animais venenosos, o sistema oferece informações tais como, espécie, seqüência de aminoácidos no formato FASTA, entre outras. Até o momento, encontram-se categorizados e disponíveis no sistema 97 dados de plantas medicinais com propriedades antiveneno, distribuídos em 42 famílias e 4.623 dados de animais venenosos, distribuídos em 392 espécies entre 10 diferentes organismos. Novas informações podem ser depositadas por colaboradores cadastrados no sistema. Tais depósitos entram em uma fila de espera e, se os campos requisitados estiverem preenchidos e os dados categorizados corretamente, o conteúdo é liberado de acordo com as regras de permissão estabelecidas pelo sistema de segurança. A interface do Venom é simples, contribuindo, assim, para um acesso rápido e funcional.In the vast diversity of plants found around the world, there are medicinal plants with antivenom properties. The study that relates data from medicinal plants with poisons of animals contributes to the development of new medicines. These information and integration between them is a process that must be administered by a computer system, which helps significantly in the structure of storage. The development of computer systems has been highlighted in recent years in Bioinformatics and are very useful for organizing different types of data and, together with the use of content managers, they contribute, significantly, in the process of developing software. This project aimed to the development of a computer Web system, which related data of medicinal plants with anti-venom properties and venomous animals, allowing the integration of the data, through different search applications. The system was named Venom and is available on the web site http://gbi.fmrp.usp.br/venom/. Categories were created for the classification of the plants and animals data. This categorization is very important because it allows the use of the categories relationship in the searches. Data both of plants and animals were extracted from scientific articles and from public databases. Family, species, isolated composed and popular name are some of the information relating to the plants. About venomous animals, the system provides information such as species, amino acids sequence in FASTA format, among others. Until now, there are 97 categorized plants data available on the system, which are distributed in 42 families, and there are 4,623 data from venomous animals, distributed in 392 species of 10 different organisms. New information may be submitted by collaborators researches registered in the system. Such deposits come to a waiting queue, and whether all the requested fields are completed and corrected categorized, the content is released in accordance with the permission rules established by the system. The Venom\'s user interface is simple, contributing to a fast and functional access

Plant-antivenom: Database of anti-venom medicinal plants

Plant-antivenom is a computational Websystem about medicinal plants with anti-venom properties. The system consists of a database of these plants, including scientific publications on this subject and amino acid sequences of active principles from venomous animals. The system relates these data allowing their integration through different search applications. For the development of the system, the first surveys were conducted in scientific literature, allowing the creation of a publication database in a library for reading and user interaction. Then, classes of categories were created, allowing the use of tags and the organization of content. This database on medicinal plants has information such as family, species, isolated compounds, activity, inhibited animal venoms, among others. Provision is made for submission of new information by registered users, by the use of wiki tools. Content submitted is released in accordance to permission rules defined by the system. The database on biological venom protein amino acid sequences was structured from the essential information from National Center for Biotechnology Information (NCBI). Plant-antivenom`s interface is simple, contributing to a fast and functional access to the system and the integration of different data registered on it. Plant-antivenom system is available on the Internet at http://gbi.fmrp.usp.br/plantantivenom.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES

MicroRNAs Discriminate Familial from Sporadic Non-BRCA1/2 Breast Carcinoma Arising in Patients ≤35 Years

<div><p>The influence of genetic factors may contribute to the poor prognosis of breast cancer (BC) at a very young age. However <i>BRCA1/2</i> mutations could not explain the majority of cases arising in these patients. MicroRNAs (miRs) have been implicated in biological processes associated with BC. Therefore, we investigated differences in miRs expression between tumors from young patients (≤35 years) with sporadic or familial history and non-carriers of <i>BRCA1/2</i> mutations. Thirty-six young Brazilian patients were divided into 2 groups: sporadic (NF-BC) or familial breast cancer (F-BC). Most of the samples were classified as luminal A and B and the frequency of subtypes did not differ between familial or sporadic cases. Using real time qPCR and discriminant function analysis, we identified 9 miRs whose expression levels rather than miR identity can discriminate between both patient groups. Candidate predicted targets were determined by combining results from miRWalk algorithms with mRNA expression profiles (n = 91 differently expressed genes). MiR/mRNA integrated analysis identified 91 candidate genes showing positive or negative correlation to at least 1 of the 9 miRs. Co-expression analysis of these genes with 9 miRs indicated that 49 differentially co-expressed miR-gene interactions changes in F-BC tumors as compared to those of NF-BC tumors. Out of 49, 17 (34.6%) of predicted miR-gene interactions showed an inverse correlation suggesting that miRs act as post-transcriptional regulators, whereas 14 (28.6%) miR-gene pairs tended to be co-expressed in the same direction indicating that the effects exerted by these miRs pointed to a complex level of target regulation. The remaining 18 pairs were not predicted by our criteria suggesting involvement of other regulators. MiR–mRNA co-expression analysis allowed us to identify changes in the miR-mRNA regulation that were able to distinguish tumors from familial and sporadic young BC patients non-carriers of BRCA mutations.</p></div

Initial findings of striatum tripartite model in OCD brain samples based on transcriptome analysis.

Obsessive-compulsive disorder (OCD) is a psychiatric disorder characterized by obsessions and/or compulsions. Different striatal subregions belonging to the cortico-striato-thalamic circuitry (CSTC) play an important role in the pathophysiology of OCD. The transcriptomes of 3 separate striatal areas (putamen (PT), caudate nucleus (CN) and accumbens nucleus (NAC)) from postmortem brain tissue were compared between 6 OCD and 8 control cases. In addition to network connectivity deregulation, different biological processes are specific to each striatum region according to the tripartite model of the striatum and contribute in various ways to OCD pathophysiology. Specifically, regulation of neurotransmitter levels and presynaptic processes involved in chemical synaptic transmission were shared between NAC and PT. The Gene Ontology terms cellular response to chemical stimulus, response to external stimulus, response to organic substance, regulation of synaptic plasticity, and modulation of synaptic transmission were shared between CN and PT. Most genes harboring common and/or rare variants previously associated with OCD that were differentially expressed or part of a least preserved coexpression module in our study also suggest striatum subregion specificity. At the transcriptional level, our study supports differences in the 3 circuit CSTC model associated with OCD