63 research outputs found

    A module-based analytical strategy to identify novel disease-associated genes shows an inhibitory role for interleukin 7 Receptor in allergic inflammation

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    <p>Abstract</p> <p>Background</p> <p>The identification of novel genes by high-throughput studies of complex diseases is complicated by the large number of potential genes. However, since disease-associated genes tend to interact, one solution is to arrange them in modules based on co-expression data and known gene interactions. The hypothesis of this study was that such a module could be a) found and validated in allergic disease and b) used to find and validate one ore more novel disease-associated genes.</p> <p>Results</p> <p>To test these hypotheses integrated analysis of a large number of gene expression microarray experiments from different forms of allergy was performed. This led to the identification of an experimentally validated reference gene that was used to construct a module of co-expressed and interacting genes. This module was validated in an independent material, by replicating the expression changes in allergen-challenged CD4<sup>+ </sup>cells. Moreover, the changes were reversed following treatment with corticosteroids. The module contained several novel disease-associated genes, of which the one with the highest number of interactions with known disease genes, <it>IL7R</it>, was selected for further validation. The expression levels of <it>IL7R </it>in allergen challenged CD4<sup>+ </sup>cells decreased following challenge but increased after treatment. This suggested an inhibitory role, which was confirmed by functional studies.</p> <p>Conclusion</p> <p>We propose that a module-based analytical strategy is generally applicable to find novel genes in complex diseases.</p

    Marked variation in MSP-119 antibody responses to malaria in western Kenyan highlands

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    <p>Abstract</p> <p>Background</p> <p>Assessment of malaria endemicity at different altitudes and transmission intensities, in the era of dwindling vector densities in the highlands, will provide valuable information for malaria control and surveillance. Measurement of serum anti-malarial antibodies is a useful marker of malaria exposure that indicates long-term transmission potential. We studied the serologic evidence of malaria endemicity at two highland sites along a transmission intensity cline. An improved understanding of the micro-geographic variation in malaria exposure in the highland ecosystems will be relevant in planning effective malaria control.</p> <p>Methods</p> <p>Total IgG levels to <it>Plasmodium falciparum </it>MSP-1<sub>19 </sub>were measured in an age-stratified cohort (< 5, 5-14 and ≥ 15 years) in 795 participants from an uphill and valley bottom residents during low and high malaria transmission seasons. Antibody prevalence and level was compared between different localities. Regression analysis was performed to examine the association between antibody prevalence and parasite prevalence. Age-specific MSP-1<sub>19 </sub>seroprevalence data was fitted to a simple reversible catalytic model to investigate the relationship between parasite exposure and age.</p> <p>Results</p> <p>Higher MSP-1<sub>19 </sub>seroprevalence and density were observed in the valley residents than in the uphill dwellers. Adults (> 15 years) recorded high and stable immune response in spite of changing seasons. Lower responses were observed in children (≤ 15 years), which, fluctuated with changing seasons particularly in the valley residents. In the uphill population, annual seroconversion rate (SCR) was 8.3% and reversion rate was 3.0%, with seroprevalence reaching a plateau of 73.3% by age of 20. Contrary, in the valley bottom population, the annual SCR was 35.8% and the annual seroreversion rate was 3.5%, and seroprevalence in the population had reached 91.2% by age 10.</p> <p>Conclusion</p> <p>The study reveals the micro-geographic variation in malaria endemicity in the highland eco-system; this validates the usefulness of sero-epidemiological tools in assessing malaria endemicity in the era of decreasing sensitivity of conventional tools.</p

    Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

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    <p>Abstract</p> <p>Background</p> <p>Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function.</p> <p>Results</p> <p>We experimentally annotated the bacterial pathogen <it>Salmonella </it>Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in <it>Salmonella </it>and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in <it>Salmonella </it>pathogenesis. We also characterized post-translational features in the <it>Salmonella </it>genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our <it>in vivo </it>proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.</p> <p>Conclusion</p> <p>This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of <it>Salmonella </it>as a resource for systems analysis.</p
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