Navegando por Autor "Vidigal, Pedro M. P."

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Complete genome sequence of vB_EcoM-UFV13, a new bacteriophage able to disrupt Trueperella pyogenes biofilm
(Genome Announcements, 2016-12-08) Duarte, Vinícius S.; Dias, Roberto S.; Kropinski, Andrew M.; Vidigal, Pedro M. P.; Sousa, Flávia O.; Sousa, Flávia O.; Xavier, André S.; Silva, Cynthia C.; Paula, Sergio O. de
vB_EcoM-UFV13, a member of the T4virus genus, shows lytic activity against Escherichia coli and effectiveness in controlling the biofilm formed by Trueperella pyogenes, which qualifies it as a promising component of phage cocktails for mastitis and metritis control.
Differential expression of four soybean bZIP genes during Phakopsora pachyrhizi infection
(Functional & Integrative Genomics, 2015-05-27) Alves, Murilo S.; Soares, Zamira G.; Vidigal, Pedro M. P.; Barros, Everaldo G.; Poddanosqui, Adriana M. P.; Aoyagi, Luciano N.; Abdelnoor, Ricardo V.; Marcelino-Guimarães, Francismar C.; Fietto, Luciano G.
Asian soybean rust (ASR), caused by the obligate biotrophic fungus Phakopsora pachyrhizi, is one of most important diseases in the soybean (Glycine max (L.) Merr.) agribusiness. The identification and characterization of genes related to plant defense responses to fungal infection are essential to develop ASR-resistant plants. In this work, we describe four soybean genes, GmbZIP62, GmbZIP105, GmbZIPE1, and GmbZIPE2, which encode transcription factors containing a basic leucine zipper (bZIP) domain from two divergent classes, and that are responsive to P. pachyrhizi infection. Molecular phylogenetic analyses demonstrated that these genes encode proteins similar to bZIP factors responsive to pathogens. Yeast transactivation assays showed that only GmbZIP62 has strong transactivation activity in yeast. In addition, three of the bZIP transcription factors analyzed were also differentially expressed by plant defense hormones, and all were differentially expressed by fungal attack, indicating that these proteins might participate in response to ASR infection. The results suggested that these bZIP proteins are part of the plant defense response to P. pachyrhizi infection, by regulating the gene expression related to ASR infection responses. These bZIP genes are potential targets to obtain new soybean genotypes resistant to ASR.
Geminivirus data warehouse: a database enriched with machine learning approaches
(BioMed Central Bioinformatics, 2017-05-05) Silva, Jose Cleydson F.; Carvalho, Thales F. M.; Basso, Marcos F.; Deguchi, Michihito; Pereira, Welison A.; Vidigal, Pedro M. P.; Brustolini, Otávio J. B.; Silva, Fabyano F.; Dal-Bianco, Maximiller; Fontes, Renildes L. F.; Santos, Anésia A.; Zerbini, Francisco Murilo; Cerqueira, Fabio R.; Fontes, Elizabeth P. B.; R. Sobrinho, Roberto
The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases. As a consequence, many important challenges have emerged, namely, how to classify, store, and analyze massive datasets as well as how to extract information or new knowledge. Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics. Here, we describe the development of a data warehouse enriched with ML approaches, designated geminivirus.org. We implemented search modules, bioinformatics tools, and ML methods to retrieve high precision information, demarcate species, and create classifiers for genera and open reading frames (ORFs) of geminivirus genomes. The use of data mining techniques such as ETL (Extract, Transform, Load) to feed our database, as well as algorithms based on machine learning for knowledge extraction, allowed us to obtain a database with quality data and suitable tools for bioinformatics analysis. The Geminivirus Data Warehouse (geminivirus.org) offers a simple and user-friendly environment for information retrieval and knowledge discovery related to geminiviruses.
Genomic sequence of the yeast Kluyveromyces marxianus CCT 7735 (UFV-3), a highly lactose-fermenting yeast isolated from the Brazilian dairy industry
(Genome Announcements, 2014-11-06) Silveira, Wendel B.; Diniz, Raphael H. S.; Cerdán, M. Esperanza; González-Siso, María I.; Souza, Robson de A; Vidigal, Pedro M. P.; Brustolini, Otávio J. B.; Prata, Emille R. B. de Almeida; Medeiros, Alexsandra C.; Paiva, Lílian C.; Nascimento, Moysés; Ferreira, Éder G.; Santos, Valdilene C. dos; Bragança, Caio R. S.; Fernandes, Tatiana A. R.; Colombo, Lívia T.; Passos, Flávia M. L.
Here, we present the draft genome sequence of Kluyveromyces marxianus CCT 7735 (UFV-3), including the eight chromosomes and the mitochondrial genomic sequences.
Identification of an emergent porcine circovirus-2 in vaccinated pigs from a brazilian farm during a postweaning multisystemic wasting syndrome outbreak
(Genome Announcements, 2014-03-20) Salgado, Rafael L.; Vidigal, Pedro M. P.; Souza, Luiz F. L. de; Onofre, Thiago S.; Gonzaga, Natália F.; Eller, Monique R.; Bressan, Gustavo C.; Fietto, Juliana L. R.; Almeida, Márcia R.; Silva Júnior, Abelardo
Three porcine circovirus-2 strains were isolated from pigs on a Brazilian farm during an outbreak, indicating a vaccine failure. They present identical genomic sequences, with high identities to other isolates that were also related to vaccination failures, supporting the recent theory about an antigen drift being associated with vaccine failures throughout the world.