Identificação e caracterização de minicírculos de Trypanosoma vivax (Zieman, 1905) através de geração e análise de GSS (Genome Sequence Survey)

Submitted by Repositório Arca ([email protected]) on 2019-07-02T18:34:37Z No. of bitstreams: 2 license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) luana_guerreiro_ioc_mest_2005.pdf: 1613307 bytes, checksum: 44e55191310e9fa64706ac71781fb8fd (MD5)Approved for entry into archive by Raquel Dinelis ([email protected]) on 2019-10-02T13:39:05Z (GMT) No. of bitstreams: 2 luana_guerreiro_ioc_mest_2005.pdf: 1613307 bytes, checksum: 44e55191310e9fa64706ac71781fb8fd (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5)Made available in DSpace on 2019-10-02T13:39:05Z (GMT). No. of bitstreams: 2 luana_guerreiro_ioc_mest_2005.pdf: 1613307 bytes, checksum: 44e55191310e9fa64706ac71781fb8fd (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2005Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Trypanosoma vivax é um hemoparasita causador de doença em ruminantes, amplamente distribuído na África, principalmente nas áreas tropicais onde a mosca tsé-tsé é encontrada. Também encontrado em vários países da América do Sul, principalmente no Pantanal do Brasil e na Bolívia, o T. vivax é um parasita patogênico considerado de grande importância para grandes regiões agropecuárias da África e América do Sul. Estimam-se possíveis perdas econômicas de 160 milhões de dólares no Pantanal brasileiro e áreas inundáveis da Bolívia. Apesar da grande relevância econômica da doença causada por T. vivax, poucas pesquisas sobre sua caracterização foram realizadas até agora, comparado com tripanosomas que afetam a saúde humana como o T. brucei e T. cruzi, por exemplo, uma pesquisa no portal Entrez do NCBI (24/05/05) usando \201CTrypanosoma vivax\201D como palavra chave apresentou apenas 447, 27, 23 e 5 entradas disponíveis nas secções de PubMed, proteína, nucleotídeo e estrutura, respectivamente, mostrando o limitado conhecimento desta espécie O diagnóstico das infecções por T. vivax continua sendo um desafio em função da baixa parasitemia observada na maioria das infecções, reforçando a importância da descoberta de novos marcadores para o desenvolvimento de ensaios mais sensíveis e espécie-específicos para o diagnóstico da infecção pelo T. vivax. Com o objetivo de gerar novos dados do genoma de T. vivax alçamos mão da geração e análise de GSS como estratégia de descobertas de genes, focando especificamente na identificação de minicírculos. A partir de uma biblioteca semi-normalizada, foram obtidas 455 GSS de alta qualidade, equivalentes a 0,5% do genoma do parasita, que foi estimado ser em torno de 25 MB. Destas, foram obtidas 331 GSS-nr, das quais 108 seqüências tiveram uma similaridade significante com seqüências depositadas nos bancos de dados públicos, sendo classificadas em três categorias funcionais do GO: processo biológico, componente celular e função molecular, e 18 seqüências não apresentaram nenhuma similaridade com os bancos de dados utilizados neste estudo, sendo consideradas genes órfãos No presente estudo, iniciadores foram desenhados para obtenção das seqüências de minicírculo de diferentes cepas de T. vivax, e testados quanto a sua sensibilidade. Durante todo o trabalho foram identificados 36 minicírculos, cada um apresentando apenas uma região conservada e os blocos de seqüência conservada (CSB), estimando-se o tamanho do minicírculo em torno de 480 pb.Trypanosoma vivax is a hemoparasite which causes sickness in ruminants. In Africa it is found wide-spread, mainly in tropical areas where tsetse is found, and in several South America countries, mainly in the Pantanal of Brazil and in Bolivia. T. vivax is a pathogenic parasite considered of great importance for cattle-industry of Africa and South America. Possible economic losses of 160 million dollar in the Brazilian Pantanal and lowlands of Bolivia are estimated. Despite the high economic relevance of the disease caused by T. vivax, few researches on its molecular characterization have been done up to this moment compared with human trypanosomes as T. brucei and T. cruzi, for example, a search in the NCBI-Entrez portal (24/05/05) using “Trypanosoma vivax” as a keyword showed only 439, 27, 23 and 5 entries available in the PubMed, Protein, Nucleotide and Structure sections, respectively, showing the limited knowledge about this species. The diagnosis of the infections for T. vivax remains a challenge, since parasitemias are usually very low in the majority of the infections, reinforcing the necessity to discover new markers for the development of more sensitive and species-specific assays. The technique for gene discovery used in this study was the GSS, with the objective to generate new data from the T. vivax genome, to make a preliminary innotation of these sequences and identification of minicircles. From a genomic library, 455 high quality GSS were obtained, equivalent to 0.5% of the parasite genome, that was estimated to be around 25 MB. From those 455 GSS, 331 GSS-nr were obtained, of which 108 sequences had a significant similarity with sequences deposited in the public databases and were classified in the three functional categories of GO: biological process, cellular component and molecular function. Eighteen sequences did not show any similarity with the databases used in this study, being considered orphan genes. In the present study, primers were designed to obtain minicircle sequences of different T. vivax strains, and their sensitivity was tested. Thirty-six minicircles were identified, each one showing only one conserved region and conserved sequence blocks (CSB). The estimated size of the minicircle was of 480 bp

Gene Expression Profiling Specifies Chemokine, Mitochondrial and Lipid Metabolism Signatures in Leprosy

<div><p>Herein, we performed microarray experiments in Schwann cells infected with live <i>M. leprae</i> and identified novel differentially expressed genes (DEG) in <i>M. leprae</i> infected cells. Also, we selected candidate genes associated or implicated with leprosy in genetic studies and biological experiments. Forty-seven genes were selected for validation in two independent types of samples by multiplex qPCR. First, an <i>in vitro</i> model using THP-1 cells was infected with live <i>Mycobacterium leprae</i> and <i>M. bovis</i> bacillus Calmette-Guérin (BCG). In a second situation, mRNA obtained from nerve biopsies from patients with leprosy or other peripheral neuropathies was tested. We detected DEGs that discriminate <i>M. bovis</i> BCG from <i>M. leprae</i> infection. Specific signatures of susceptible responses after <i>M. leprae</i> infection when compared to BCG lead to repression of genes, including <i>CCL2</i>, <i>CCL3</i>, <i>IL8</i> and <i>SOD2</i>. The same 47-gene set was screened in nerve biopsies, which corroborated the down-regulation of <i>CCL2</i> and <i>CCL3</i> in leprosy, but also evidenced the down-regulation of genes involved in mitochondrial metabolism, and the up-regulation of genes involved in lipid metabolism and ubiquitination. Finally, a gene expression signature from DEG was identified in patients confirmed of having leprosy. A classification tree was able to ascertain 80% of the cases as leprosy or non-leprous peripheral neuropathy based on the expression of only <i>LDLR</i> and <i>CCL4</i>. A general immune and mitochondrial hypo-responsive state occurs in response to <i>M. leprae</i> infection. Also, the most important genes and pathways have been highlighted providing new tools for early diagnosis and treatment of leprosy.</p></div

Toll-like receptor 1 N248S single-nucleotide polymorphism is associated with leprosy risk and regulates immune activation during mycobacterial infection

Conflicting findings about the association between leprosy and TLR1 variants N248S and I602S have been reported. Here, we performed case-control and family based studies, followed by replication in 2 case-control populations from Brazil, involving 3162 individuals. Results indicated an association between TLR1 248S and leprosy in the case-control study (SS genotype odds ratio [OR], 1.81; P = .004) and the family based study (z = 2.02; P = .05). This association was consistently replicated in other populations (combined OR, 1.51; P < .001), corroborating the finding that 248S is a susceptibility factor for leprosy. Additionally, we demonstrated that peripheral blood mononuclear cells (PBMCs) carrying 248S produce a lower tumor necrosis factor/interleukin-10 ratio when stimulated with Mycobacterium leprae but not with lipopolysaccharide or PAM3cysK4. The same effect was observed after infection of PBMCs with the Moreau strain of bacillus Calmette-Guerin but not after infection with other strains. Finally, molecular dynamics simulations indicated that the Toll-like receptor 1 structure containing 248S amino acid is different from the structure containing 248N. Our results suggest that TLR1 248S is associated with an increased risk for leprosy, consistent with its hypoimmune regulatory function.Fundação Oswaldo Cruz/Programa Estratégico de Apoio à Pesquisa em SaúdeFundação Oswaldo Cruz/Programa Estratégico de Apoio à Pesquisa em SaúdeInstituto Oswaldo Cruz/FIOCRUZ (internal funds)Instituto Oswaldo Cruz/FIOCRUZ (internal funds)Fundação de Amparo a Pesquisa do Estado do Rio de JaneiroFundacao do Amparo a Pesquisa do Estado do Rio de JaneiroFundacao de Amparo a Pesquisa do Estado de Sao PauloFundação de Amparo a Pesquisa do Estado de São PauloConselho Nacional de Pesquisa e Desenvolvimento TecnológicoConselho Nacional de Pesquisa e Desenvolvimento Tecnológic

Toll-like receptor 1 (TLR1) N248S single nucleotide polymorphism is associated with leprosy risk and regulates immune activation during mycobacterial infection

Submitted by sandra infurna ([email protected]) on 2016-01-21T12:52:44Z No. of bitstreams: 1 carolinnes_marques_etal_IOC_2013.pdf: 681352 bytes, checksum: 93595bbcfadc6e1fc928835a67a3c3e2 (MD5)Approved for entry into archive by sandra infurna ([email protected]) on 2016-01-21T13:14:09Z (GMT) No. of bitstreams: 1 carolinnes_marques_etal_IOC_2013.pdf: 681352 bytes, checksum: 93595bbcfadc6e1fc928835a67a3c3e2 (MD5)Made available in DSpace on 2016-01-21T13:14:09Z (GMT). No. of bitstreams: 1 carolinnes_marques_etal_IOC_2013.pdf: 681352 bytes, checksum: 93595bbcfadc6e1fc928835a67a3c3e2 (MD5) Previous issue date: 2013Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brasil.Instituto Lauro de Souza Lima. Bauru, SP, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Programa de Computação Científica (PROCC). Rio de Janeiro, RJ, Brasil.Universidade Federal de Minas Gerais. Departamento de Enfermagem Materno-Infantil e Saúde Pública. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brasil / Universidade Federal do Rio de Janeiro. Departamento de Genética. Laboratório de Virologia Molecular. Rio de Janeiro, RJ, Brasil.Instituto Lauro de Souza Lima. Bauru, SP, Brasil.Instituto Lauro de Souza Lima. Bauru, SP, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brasil.Instituto Lauro de Souza Lima. Bauru, SP, Brasil.Instituto Lauro de Souza Lima. Bauru, SP, Brasil.Universidade de São Paulo. Escola de Odontologia de Bauru. Departamento de Ciências Biológicas. Bauru, SP, Brasil.Instituto Lauro de Souza Lima. Bauru, SP, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brasil.Universidade Católica do Paraná. Escola de Medicina. Programa de Pós-Graduação em Ciências da Saúde. Curitiba, PR, Brasil.Universidade Federal de Minas Gerais. Departamento de Enfermagem Materno-Infantil e Saúde Pública. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Programa de Computação Científica (PROCC). Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Programa de Computação Científica (PROCC). Rio de Janeiro, RJ, Brasil.Instituto Lauro de Souza Lima. Bauru, SP, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Hanseníase. Rio de Janeiro, RJ, Brasil.TLR1 variants N248S and I602S have been described associated with leprosy, but different results were found. Here, we performed both a case-control and family-based studies followed by replication in two case-control samples from Brazil, enrolling 3,162 individuals. Results indicated risk association between TLR1 248S and leprosy in case-control (OR SS genotype= 1.81, p=0.004) and familial study (z=2.02, p=0.05). This association was consistently replicated in other populations (ORCombined=1.51, p-value<0.001), corroborating 248S as a susceptibility factor for leprosy. Additionally, we demonstrated that PBMCs carrying 248S produce lower log(TNF/IL-10) when stimulated with M. leprae, but not with LPS or PAM3cysK4. The same effect was observed after infection of PBMCs with BCG Moreau, but not other strains. Finally, molecular dynamics simulations indicated that 248S-TLR1 structure is different than 248N-TLR1. Our results suggest that TLR1 248S is associated with leprosy risk, consistent with its hypo-immune regulatory function

Clustering of differentially expressed genes in nerve biopsies of leprosy and non-leprous patients peripheral neuropathy.

<p>The left graph displays a dendrogram representing the 1D clusterization of genes and the 2D map corresponding to the levels of standardized gene expression profiles (z-score), while the graph on the right displays the three significant clusters (pink, blue and yellow). Red dotted lines in the dendrogram (up-left) indicate weak unions, discouraged by the Bayesian clustering analysis. Values represented in the dendrogram branches correspond to log-odds of the union of corresponding branches. Gray lines in the graphs on the right indicate gene z-scores on leprosy and non-leprous samples, while black solid and dotted lines represent the mean and CI95% of the mean for all genes belonging to each cluster, respectively. Solid pink, blue and yellow lines indicate the mean of all genes in all samples belonging to the leprosy and non-leprous groups.</p

Discrimination between leprosy and non-leprous patients with peripheral neuropathy by combination of LDLR and CCL4 expression.

<p>Graph of a trained classification tree, where rounded rectangles represent internal nodes and hexagons represent terminal nodes. Percentages in each node represent the proportion of specified observations in each group.</p

Gene expression from nerve biopsies from leprosy and non-leprous patients with peripheral neuropathy.

<p>Among the 47-gene set only genes that showed at least a suggestive result (n = 15) are presented. Two-tailed levels of significance less than or equal to 0.01 (**), 0.05 (*) and 0.1 (^.) were considered as “highly significant”, “significant”, and “suggestive”, respectively. A total of 50 samples non-leprous patients (white columns) and 35 samples from leprosy samples (black columns).</p