A novel approach identified the FOLR1 gene, a putative regulator of milk protein synthesis

This study has utilised comparative functional genomics to exploit animal models with extreme adaptation to lactation to identify candidate genes that specifically regulate protein synthesis in the cow mammary gland. Increasing milk protein production is valuable to the dairy industry. The lactation strategies of both the Cape fur seal (Artocephalus pusillus pusillus) and the tammar wallaby (Macropus eugenii) include periods of high rates of milk protein synthesis during an established lactation and therefore offer unique models to target genes that specifically regulate milk protein synthesis. Global changes in mammary gene expression in the Cape fur seal, tammar wallaby, and the cow (Bos taurus) were assessed using microarray analysis. The folate receptor α (FOLR1) showed the greatest change in gene expression in all three species [cow 12.7-fold (n = 3), fur seal 15.4-fold (n = 1), tammar 2.4-fold (n = 4)] at periods of increased milk protein production. This compliments previous reports that folate is important for milk protein synthesis and suggests FOLR1 may be a key regulatory point of folate metabolism for milk protein synthesis within mammary epithelial cells (lactocytes). These data may have important implications for the dairy industry to develop strategies to increase milk protein production in cows. This study illustrates the potential of comparative genomics to target genes of interest to the scientific community.

A genômica funcional no âmbito da produção animal: estado da arte e perspectivas

Os últimos vinte anos caracterizaram-se pela proliferação de tecnologias que tornaram possível decifrar o genoma das espécies, localizar e identificar particularidades na sua seqüência, elucidar as suas funções dentro dos sistemas biológicos e, sobretudo, começar a entender os mecanismos que controlam as interações entre os genótipos e os estímulos ambientais, que são responsáveis pela diversidade fenotípica. Estes estudos sobre as bases moleculares da variabilidade fenotípica abriram uma nova abordagem científica, caracterizada pela multiplicidade das questões envolvidas, que resultou no surgimento de novas áreas de pesquisa, cujos conhecimentos estão sendo aplicados em diversos campos da biologia, inclusive na zootecnia. Tendo em vista o grande impacto que tais conhecimentos estão tendo sobre a compreensão dos fenômenos biológicos, parece ser oportuno fazer uma avaliação das potencialidades de aplicação das abordagens de Genômica Funcional em pesquisas de nutrição e alimentação de ruminantes. Nesse contexto, este artigo está focado na descrição das principais ferramentas genômicas disponíveis e na discussão sobre a viabilidade de se utilizar as informações por elas geradas em benefício da produção animal.

Molecular models of NS3 protease variants of the Hepatitis C virus

Background: Hepatitis C virus (HCV) currently infects approximately three percent of the world population. In view of the lack of vaccines against HCV, there is an urgent need for an efficient treatment of the disease by an effective antiviral drug. Rational drug design has not been the primary way for discovering major therapeutics. Nevertheless, there are reports of success in the development of inhibitor using a structure-based approach. One of the possible targets for drug development against HCV is the NS3 protease variants. Based on the three-dimensional structure of these variants we expect to identify new NS3 protease inhibitors. In order to speed up the modeling process all NS3 protease variant models were generated in a Beowulf cluster. The potential of the structural bioinformatics for development of new antiviral drugs is discussed.Results: the atomic coordinates of crystallographic structure 1CU1 and 1DY9 were used as starting model for modeling of the NS3 protease variant structures. The NS3 protease variant structures are composed of six subdomains, which occur in sequence along the polypeptide chain. The protease domain exhibits the dual beta-barrel fold that is common among members of the chymotrypsin serine protease family. The helicase domain contains two structurally related beta-alpha-beta subdomains and a third subdomain of seven helices and three short beta strands. The latter domain is usually referred to as the helicase alpha-helical subdomain. The rmsd value of bond lengths and bond angles, the average G-factor and Verify 3D values are presented for NS3 protease variant structures.Conclusions: This project increases the certainty that homology modeling is an useful tool in structural biology and that it can be very valuable in annotating genome sequence information and contributing to structural and functional genomics from virus. The structural models will be used to guide future efforts in the structure-based drug design of a new generation of NS3 protease variants inhibitors. All models in the database are publicly accessible via our interactive website, providing us with large amount of structural models for use in protein-ligand docking analysis.

Sequenciamento de DNA de nova geração e suas aplicações na genômica de plantas

As plataformas de sequenciamento de nova geração são uma alternativa poderosa para estudos de genômica estrutural e funcional. Na genômica de plantas, os trabalhos com as novas plataformas têm sido destinados ao sequenciamento de transcritos, ressequenciamento ou sequenciamento de novo de genomas plastidiais. Neste trabalho, são detalhadas as tecnologias das plataformas mais utilizadas atualmente, bem como é revisada a aplicação dessas tecnologias na genômica estrutural e funcional de plantas.

Estudos de expressão gênica utilizando-se microarrays: delineamento, análise, e aplicações na pesquisa zootécnica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

DBMODELING - A database applied to the study of protein targets from genome projects

Genome sequencing efforts are providing us with complete genetic blueprints for hundreds of organisms. We are now faced with assigning, understanding, and modifying the functions of proteins encoded by these genomes. DBMODELING is a relational database of annotated comparative protein structure models and their metabolic pathway characterization, when identified. This procedure was applied to complete genomes such as Mycobacteritum tuberculosis and Xylella fastidiosa. The main interest in the study of metabolic pathways is that some of these pathways are not present in humans, which makes them selective targets for drug design, decreasing the impact of drugs in humans. In the database, there are currently 1116 proteins from two genomes. It can be accessed by any researcher at http://www.biocristalografia.df.ibilce.unesp.br/tools/. This project confirms that homology modeling is a useful tool in structural bioinformatics and that it can be very valuable in annotating genome sequence information, contributing to structural and functional genomics, and analyzing protein-ligand docking.

Bacillus Thuringiensis mutant increase activity against Apodoptera Frugiperda larvae

Bacillus thuringiensis is a Gram-positive bacterium which main characteristic is the production of Cry proteins, that is toxic to some insects. These proteins, when ingested by susceptible insects, become active causing their death. In nature, it is possible to found B. thuringiensis strains which produce these proteins, but they differ in productivity (some of these isolates are more productive then others), and as to the toxicity levels of the produced proteins. Two B. thuringiensis strains that were highly effective against Spodoptera frugiperda larvae were chosen to verifying genetic mutation implication on Cry proteins productivity. One strain with a prolific spores production, while the other one only produced small amounts of spores. A genomic mutant library of these two isolates was, separately, constructed by genome Tn-5 transposon random insertion. Data analysis showed that mutation had a direct effect on the spores production, inducing an increase as well as a decrease in the production, according to the different strain observed. These results indicate, for the first time, that it is possible to use the described technique with B. thuringiensis, as well as the possibility to genetically breeding this bacteria. Another possibility introduced here is the possibility to do functional genetic studies mediated by mutagenesis in this bacterium.

Effects of BST and high energy diet on gene expression in mammary parenchyma of dairy heifers

The objective of this study was to determine the effects of dietary energy and recombinant bovine somatotropin (bST) injection to identify genes that might control mammogenesis. Total RNA was extracted from the parenchymal tissue of 32 heifers randomly assigned to one of four treatments: two diets (a standard diet and a high energy, high protein diet), each with or without bST. To perform microarray experiments, RNA samples were pooled (2 animals/pool) before reverse transcription and labeling with Cy3 or Cy5. A 4-node loop design was used to examine the differential gene expression among treatments using a bovine-specific cDNA micro array (National Bovine Functional Genomics Consortium Library, NBFGC) containing 18,263 unique expressed sequence tags (EST). Significance levels of differential gene expression among treatments were assessed using a mixed model approach. Injection of bST altered the expression of 12 % of the genes on NBFGC slide related to tissue development, whereas 6% were altered by diet. Administration of bST increases the expression of genes positively related to cell proliferation and mammary parenchyma to a greater extent than a high energy diet. © 2013 Sociedade Brasileira de Zootecnia.

Modelagem molecular da Chiquimato quinase de Mycobacterium leprae

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização fenotípica e funcional de mutantes da bactéria fitopatogênica Xanthomonas citri subsp. citri

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Bioinformática estrutural aplicada ao estudo de proteínas alvo do genoma do Mycobacterium tuberculosis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Chemotactic signal transduction and phosphate metabolism as adaptive strategies during citrus canker induction by Xanthomonas citri

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparative Genome Analysis of Trichophyton rubrum and Related Dermatophytes Reveals Candidate Genes Involved in Infection

The major cause of athlete's foot is Trichophyton rubrum, a dermatophyte or fungal pathogen of human skin. To facilitate molecular analyses of the dermatophytes, we sequenced T. rubrum and four related species, Trichophyton tonsurans, Trichophyton equinum, Microsporum canis, and Microsporum gypseum. These species differ in host range, mating, and disease progression. The dermatophyte genomes are highly colinear yet contain gene family expansions not found in other human-associated fungi. Dermatophyte genomes are enriched for gene families containing the LysM domain, which binds chitin and potentially related carbohydrates. These LysM domains differ in sequence from those in other species in regions of the peptide that could affect substrate binding. The dermatophytes also encode novel sets of fungus-specific kinases with unknown specificity, including nonfunctional pseudokinases, which may inhibit phosphorylation by competing for kinase sites within substrates, acting as allosteric effectors, or acting as scaffolds for signaling. The dermatophytes are also enriched for a large number of enzymes that synthesize secondary metabolites, including dermatophyte-specific genes that could synthesize novel compounds. Finally, dermatophytes are enriched in several classes of proteases that are necessary for fungal growth and nutrient acquisition on keratinized tissues. Despite differences in mating ability, genes involved in mating and meiosis are conserved across species, suggesting the possibility of cryptic mating in species where it has not been previously detected. These genome analyses identify gene families that are important to our understanding of how dermatophytes cause chronic infections, how they interact with epithelial cells, and how they respond to the host immune response. IMPORTANCE Athlete's foot, jock itch, ringworm, and nail infections are common fungal infections, all caused by fungi known as dermatophytes (fungi that infect skin). This report presents the genome sequences of Trichophyton rubrum, the most frequent cause of athlete's foot, as well as four other common dermatophytes. Dermatophyte genomes are enriched for four gene classes that may contribute to the ability of these fungi to cause disease. These include (i) proteases secreted to degrade skin; (ii) kinases, including pseudokinases, that are involved in signaling necessary for adapting to skin; (iii) secondary metabolites, compounds that act as toxins or signals in the interactions between fungus and host; and (iv) a class of proteins (LysM) that appear to bind and mask cell wall components and carbohydrates, thus avoiding the host's immune response to the fungi. These genome sequences provide a strong foundation for future work in understanding how dermatophytes cause disease.

Transcriptional profiling of Saccharomyces cerevisiae exposed to propolis

Abstract Background Propolis is a natural product of plant resins collected by honeybees (Apis mellifera) from various plant sources. Our previous studies indicated that propolis sensitivity is dependent on the mitochondrial function and that vacuolar acidification and autophagy are important for yeast cell death caused by propolis. Here, we extended our understanding of propolis-mediated cell death in the yeast Saccharomyces cerevisiae by applying systems biology tools to analyze the transcriptional profiling of cells exposed to propolis. Methods We have used transcriptional profiling of S. cerevisiae exposed to propolis. We validated our findings by using real-time PCR of selected genes. Systems biology tools (physical protein-protein interaction [PPPI] network) were applied to analyse the propolis-induced transcriptional bevavior, aiming to identify which pathways are modulated by propolis in S. cerevisiae and potentially influencing cell death. Results We were able to observe 1,339 genes modulated in at least one time point when compared to the reference time (propolis untreated samples) (t-test, p-value 0.01). Enrichment analysis performed by Gene Ontology (GO) Term finder tool showed enrichment for several biological categories among the genes up-regulated in the microarray hybridization such as transport and transmembrane transport and response to stress. Real-time RT-PCR analysis of selected genes showed by our microarray hybridization approach was capable of providing information about S. cerevisiae gene expression modulation with a considerably high level of confidence. Finally, a physical protein-protein (PPPI) network design and global topological analysis stressed the importance of these pathways in response of S. cerevisiae to propolis and were correlated with the transcriptional data obtained thorough the microarray analysis. Conclusions In summary, our data indicate that propolis is largely affecting several pathways in the eukaryotic cell. However, the most prominent pathways are related to oxidative stress, mitochondrial electron transport chain, vacuolar acidification, regulation of macroautophagy associated with protein target to vacuole, cellular response to starvation, and negative regulation of transcription from RNA polymerase II promoter. Our work emphasizes again the importance of S. cerevisiae as a model system to understand at molecular level the mechanism whereby propolis causes cell death in this organism at the concentration herein tested. Our study is the first one that investigates systematically by using functional genomics how propolis influences and modulates the mRNA abundance of an organism and may stimulate further work on the propolis-mediated cell death mechanisms in fungi.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.