Laboratorio Multiusuario Of Bioinformatica

Campinas, Brazil

Laboratorio Multiusuario Of Bioinformatica

Campinas, Brazil
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Rojas T.C.G.,Institute of Biology | Lobo F.P.,Laboratorio Multiusuario Of Bioinformatica | Hongo J.A.,Laboratorio Multiusuario Of Bioinformatica | Vicentini R.,University of Campinas | And 3 more authors.
Foodborne Pathogens and Disease | Year: 2017

The ability to obtain bacterial genomes from the same host has allowed for comparative studies that help in the understanding of the molecular evolution of specific pathotypes. Avian pathogenic Escherichia coli (APEC) is a group of extraintestinal strains responsible for causing colibacillosis in birds. APEC is also suggested to possess a role as a zoonotic agent. Despite its importance, APEC pathogenesis still has several cryptic pathogenic processes that need to be better understood. In this work, a genome-wide survey of eight APEC strains for genes with evidence of recombination revealed that ∼14% of the homologous groups evaluated present signs of recombination. Enrichment analyses revealed that nine Gene Ontology (GO) terms were significantly more represented in recombinant genes. Among these GO terms, several were noted to be ATP-related categories. The search for positive selection in these APEC genomes revealed 32 groups of homologous genes with evidence of positive selection. Among these groups, we found several related to cell metabolism, as well as several uncharacterized genes, beyond the well-known virulence factors ompC, lamB, waaW, waaL, and fliC. A GO term enrichment test showed a prevalence of terms related to bacterial cell contact with the external environment (e.g., viral entry into host cell, detection of virus, pore complex, bacterial-Type flagellum filament C, and porin activity). Finally, the genes with evidence of positive selection were retrieved from genomes of non-APEC strains and tested as were done for APEC strains. The result revealed that none of the groups of genes presented evidence of positive selection, confirming that the analysis was effective in inferring positive selection for APEC and not for E. coli in general, which means that the study of the genes with evidence of positive selection identified in this study can contribute for the better understanding of APEC pathogenesis processes. © Copyright 2017, Mary Ann Liebert, Inc. 2017.


Silva L.L.,Institute Nacional Of Ciencia E Tecnologia Em Doencas Tropicais Fundacao Oswaldo Cruz Fiocruz | Silva L.L.,Federal University of Minas Gerais | Marcet-Houben M.,Center for Genomic Regulation | Marcet-Houben M.,University Pompeu Fabra | And 5 more authors.
BMC Genomics | Year: 2012

Background: Schistosoma mansoni is one of the causative agents of schistosomiasis, a neglected tropical disease that affects about 237 million people worldwide. Despite recent efforts, we still lack a general understanding of the relevant host-parasite interactions, and the possible treatments are limited by the emergence of resistant strains and the absence of a vaccine. The S. mansoni genome was completely sequenced and still under continuous annotation. Nevertheless, more than 45% of the encoded proteins remain without experimental characterization or even functional prediction. To improve our knowledge regarding the biology of this parasite, we conducted a proteome-wide evolutionary analysis to provide a broad view of the S. mansoni's proteome evolution and to improve its functional annotation.Results: Using a phylogenomic approach, we reconstructed the S. mansoni phylome, which comprises the evolutionary histories of all parasite proteins and their homologs across 12 other organisms. The analysis of a total of 7,964 phylogenies allowed a deeper understanding of genomic complexity and evolutionary adaptations to a parasitic lifestyle. In particular, the identification of lineage-specific gene duplications pointed to the diversification of several protein families that are relevant for host-parasite interaction, including proteases, tetraspanins, fucosyltransferases, venom allergen-like proteins, and tegumental-allergen-like proteins. In addition to the evolutionary knowledge, the phylome data enabled us to automatically re-annotate 3,451 proteins through a phylogenetic-based approach rather than solely sequence similarity searches. To allow further exploitation of this valuable data, all information has been made available at PhylomeDB (http://www.phylomedb.org).Conclusions: In this study, we used an evolutionary approach to assess S. mansoni parasite biology, improve genome/proteome functional annotation, and provide insights into host-parasite interactions. Taking advantage of a proteome-wide perspective rather than focusing on individual proteins, we identified that this parasite has experienced specific gene duplication events, particularly affecting genes that are potentially related to the parasitic lifestyle. These innovations may be related to the mechanisms that protect S. mansoni against host immune responses being important adaptations for the parasite survival in a potentially hostile environment. Continuing this work, a comparative analysis involving genomic, transcriptomic, and proteomic data from other helminth parasites, other parasites, and vectors will supply more information regarding parasite's biology as well as host-parasite interactions. © 2012 Silva et al.; licensee BioMed Central Ltd.


Lobo F.P.,Laboratorio Multiusuario Of Bioinformatica | Hilario H.O.,Federal University of Minas Gerais | Souza R.A.,Fundacao Ezequiel Dias | Tauch A.,Bielefeld University | And 2 more authors.
Nucleic Acids Research | Year: 2012

The enrichment analysis is a standard procedure to interpret 'omics' experiments that generate large gene lists as outputs, such as transcriptomics and protemics. However, despite the huge success of enrichment analysis in these classes of experiments, there is a surprising lack of application of this methodology to survey other categories of large-scale biological data available. Here, we report Kegg Orthology enrichMent-Online DetectiOn (KOMODO), a web tool to systematically investigate groups of monophyletic genomes in order to detect significantly enriched groups of homologous genes in one taxon when compared with another. The results are displayed in their proper biochemical roles in a visual, explorative way, allowing users to easily formulate and investigate biological hypotheses regarding the taxonomical distribution of genomic elements. We validated KOMODO by analyzing portions of central carbon metabolism in two taxa extensively studied regarding their carbon metabolism profile (Enterobacteriaceae family and Lactobacillales order). Most enzymatic activities significantly biased were related to known key metabolic traits in these taxa, such as the distinct fates of pyruvate (the known tendency of lactate production in Lactobacillales and its complete oxidation in Enterobacteriaceae), demonstrating that KOMODO could detect biologically meaningful differences in the frequencies of shared genomic elements among taxa. KOMODO is freely available at http://komodotool.org. © 2012 The Author(s).


Zerlotini A.,National Institute for Science and Technology in Tropical Diseases FIOCRUZ Minas | Zerlotini A.,Laboratorio Multiusuario Of Bioinformatica | Aguiar E.R.G.R.,National Institute for Science and Technology in Tropical Diseases FIOCRUZ Minas | Yu F.,Shanghai Center for Bioinformation Technology | And 10 more authors.
Nucleic Acids Research | Year: 2013

The new release of SchistoDB (http://SchistoDB.net) provides a rich resource of genomic data for key blood flukes (genus Schistosoma) which cause disease in hundreds of millions of people worldwide. SchistoDB integrates whole-genome sequence and annotation of three species of the genus and provides enhanced bioinformatics analyses and data-mining tools. A simple, yet comprehensive web interface provided through the Strategies Web Development Kit is available for the mining and visualization of the data. Genomic scale data can be queried based on BLAST searches, annotation keywords and gene ID searches, gene ontology terms, sequence motifs, protein characteristics and phylogenetic relationships. Search strategies can be saved within a user's profile for future retrieval and may also be shared with other researchers using a unique web address. © The Author(s) 2012.


Aguiar E.R.G.R.,Federal University of Minas Gerais | Aguiar E.R.G.R.,French National Center for Scientific Research | Olmo R.P.,Federal University of Minas Gerais | Olmo R.P.,French National Center for Scientific Research | And 13 more authors.
Nucleic Acids Research | Year: 2015

Virus surveillance in vector insects is potentially of great benefit to public health. Large-scale sequencing of small and long RNAs has previously been used to detect viruses, but without any formal comparison of different strategies. Furthermore, the identification of viral sequences largely depends on similarity searches against reference databases. Here, we developed a sequence-independent strategy based on virus-derived small RNAs produced by the host response, such as the RNA interference pathway. In insects, we compared sequences of small and long RNAs, demonstrating that viral sequences are enriched in the small RNA fraction. We also noted that the small RNA size profile is a unique signature for each virus and can be used to identify novel viral sequences without known relatives in reference databases. Using this strategy, we characterized six novel viruses in the viromes of laboratory fruit flies and wild populations of two insect vectors: mosquitoes and sandflies. We also show that the small RNA profile could be used to infer viral tropism for ovaries among other aspects of virus biology. Additionally, our results suggest that virus detection utilizing small RNAs can also be applied to vertebrates, although not as efficiently as to plants and insects. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.


PubMed | University of Strasbourg, Lancaster University, French National Center for Scientific Research, Federal University of Minas Gerais and Laboratorio Multiusuario Of Bioinformatica
Type: Journal Article | Journal: Nucleic acids research | Year: 2015

Virus surveillance in vector insects is potentially of great benefit to public health. Large-scale sequencing of small and long RNAs has previously been used to detect viruses, but without any formal comparison of different strategies. Furthermore, the identification of viral sequences largely depends on similarity searches against reference databases. Here, we developed a sequence-independent strategy based on virus-derived small RNAs produced by the host response, such as the RNA interference pathway. In insects, we compared sequences of small and long RNAs, demonstrating that viral sequences are enriched in the small RNA fraction. We also noted that the small RNA size profile is a unique signature for each virus and can be used to identify novel viral sequences without known relatives in reference databases. Using this strategy, we characterized six novel viruses in the viromes of laboratory fruit flies and wild populations of two insect vectors: mosquitoes and sandflies. We also show that the small RNA profile could be used to infer viral tropism for ovaries among other aspects of virus biology. Additionally, our results suggest that virus detection utilizing small RNAs can also be applied to vertebrates, although not as efficiently as to plants and insects.


Coutinho T.J.D.,Federal University of Minas Gerais | Franco G.R.,Federal University of Minas Gerais | Lobo F.P.,Laboratorio Multiusuario Of Bioinformatica
Computational and Structural Biotechnology Journal | Year: 2015

A mainstream procedure to analyze the wealth of genomic data available nowadays is the detection of homologous regions shared across genomes, followed by the extraction of biological information from the patterns of conservation and variation observed in such regions. Although of pivotal importance, comparative genomic procedures that rely on homology inference are obviously not applicable if no homologous regions are detectable. This fact excludes a considerable portion of "genomic dark matter" with no significant similarity - and, consequently, no inferred homology to any other known sequence - from several downstream comparative genomic methods. In this review we compile several sequence metrics that do not rely on homology inference and can be used to compare nucleotide sequences and extract biologically meaningful information from them. These metrics comprise several compositional parameters calculated from sequence data alone, such as GC content, dinucleotide odds ratio, and several codon bias metrics. They also share other interesting properties, such as pervasiveness (patterns persist on smaller scales) and phylogenetic signal. We also cite examples where these homology-independent metrics have been successfully applied to support several bioinformatics challenges, such as taxonomic classification of biological sequences without homology inference. They where also used to detect higher-order patterns of interactions in biological systems, ranging from detecting coevolutionary trends between the genomes of viruses and their hosts to characterization of gene pools of entire microbial communities. We argue that, if correctly understood and applied, homology-independent metrics can add important layers of biological information in comparative genomic studies without prior homology inference. © 2015 The Authors.


PubMed | Federal University of Minas Gerais and Laboratorio Multiusuario Of Bioinformatica
Type: | Journal: Computational and structural biotechnology journal | Year: 2015

A mainstream procedure to analyze the wealth of genomic data available nowadays is the detection of homologous regions shared across genomes, followed by the extraction of biological information from the patterns of conservation and variation observed in such regions. Although of pivotal importance, comparative genomic procedures that rely on homology inference are obviously not applicable if no homologous regions are detectable. This fact excludes a considerable portion of genomic dark matter with no significant similarity - and, consequently, no inferred homology to any other known sequence - from several downstream comparative genomic methods. In this review we compile several sequence metrics that do not rely on homology inference and can be used to compare nucleotide sequences and extract biologically meaningful information from them. These metrics comprise several compositional parameters calculated from sequence data alone, such as GC content, dinucleotide odds ratio, and several codon bias metrics. They also share other interesting properties, such as pervasiveness (patterns persist on smaller scales) and phylogenetic signal. We also cite examples where these homology-independent metrics have been successfully applied to support several bioinformatics challenges, such as taxonomic classification of biological sequences without homology inference. They where also used to detect higher-order patterns of interactions in biological systems, ranging from detecting coevolutionary trends between the genomes of viruses and their hosts to characterization of gene pools of entire microbial communities. We argue that, if correctly understood and applied, homology-independent metrics can add important layers of biological information in comparative genomic studies without prior homology inference.


PubMed | Federal University of Pelotas, Laboratorio Multiusuario Of Bioinformatica, Laboratorio Of Biologia Molecular Do Carrapato and Federal University of Mato Grosso do Sul
Type: Journal Article | Journal: Revista brasileira de parasitologia veterinaria = Brazilian journal of veterinary parasitology : Orgao Oficial do Colegio Brasileiro de Parasitologia Veterinaria | Year: 2016

The Rhipicephalus (Boophilus) microplus complex currently consists of five taxa, namely R. australis, R. annulatus, R. (B.) microplus clade A sensu, R. microplus clade B sensu, and R. (B.) microplus clade C sensu. Mitochondrial DNA-based methods help taxonomists when they are facing the morpho-taxonomic problem of distinguishing members of the R. (B.) microplus complex. The purpose of this study was to perform molecular characterization of ticks in all five regions of Brazil and infer their phylogenetic relationships. Molecular analysis characterized 10 haplotypes of the COX-1 gene. Molecular network analysis revealed that haplotype H-2 was the most dispersed of the studied populations (n = 11). Haplotype H-3 (n = 2) had the greatest genetic differentiation when compared to other Brazilian populations. A Bayesian phylogenetic tree of the COX-1 gene obtained strong support. In addition, it was observed that the population of R. (B.) microplus haplotype H-3 exhibited diverging branches among the other Brazilian populations in the study. The study concludes that the different regions of Brazil have R. (B.) microplus tick populations with distinct haplotypes.


PubMed | Laboratorio Multiusuario Of Bioinformatica
Type: Journal Article | Journal: Nucleic acids research | Year: 2012

The enrichment analysis is a standard procedure to interpret omics experiments that generate large gene lists as outputs, such as transcriptomics and protemics. However, despite the huge success of enrichment analysis in these classes of experiments, there is a surprising lack of application of this methodology to survey other categories of large-scale biological data available. Here, we report Kegg Orthology enrichMent-Online DetectiOn (KOMODO), a web tool to systematically investigate groups of monophyletic genomes in order to detect significantly enriched groups of homologous genes in one taxon when compared with another. The results are displayed in their proper biochemical roles in a visual, explorative way, allowing users to easily formulate and investigate biological hypotheses regarding the taxonomical distribution of genomic elements. We validated KOMODO by analyzing portions of central carbon metabolism in two taxa extensively studied regarding their carbon metabolism profile (Enterobacteriaceae family and Lactobacillales order). Most enzymatic activities significantly biased were related to known key metabolic traits in these taxa, such as the distinct fates of pyruvate (the known tendency of lactate production in Lactobacillales and its complete oxidation in Enterobacteriaceae), demonstrating that KOMODO could detect biologically meaningful differences in the frequencies of shared genomic elements among taxa. KOMODO is freely available at http://komodotool.org.

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