Project description:<p><strong>BACKGROUND:</strong> The protozoan parasite Toxoplasma gondii infects and alters the neurotransmission in cerebral cortex and other brain regions, leading to neurobehavioral and neuropathologic changes in humans and animals. However, the molecules that contribute to these changes remain largely unknown.</p><p><strong>METHODS:</strong> We have investigated the impact of T. gondii infection on the overall metabolism of mouse cerebral cortex. Mass-spectrometry-based metabolomics and multivariate statistical analysis were employed to discover metabolomic signatures that discriminate between cerebral cortex of T. gondii-infected and uninfected control mice.</p><p><strong>RESULTS:</strong> Our results identified 73, 67 and 276 differentially abundant metabolites, which were involved in 25, 37 and 64 pathways at 7, 14 and 21 days post-infection (dpi), respectively. Metabolites in the unsaturated fatty acid biosynthesis pathway were upregulated as the infection progressed, indicating that T. gondii induces the biosynthesis of unsaturated fatty acids to promote its own growth and survival. Some of the downregulated metabolites were related to pathways, such as steroid hormone biosynthesis and arachidonic acid metabolism. Nine metabolites were identified as T. gondii responsive metabolites, namely galactosylsphingosine, arachidonic acid, LysoSM(d18:1), L-palmitoylcarnitine, calcitetrol, 27-Deoxy-5b-cyprinol, L-homophenylalanine, oleic acid and ceramide (d18:1/16:0).</p><p><strong>CONCLUSIONS:</strong> Our data provide novel insight into the dysregulation of the metabolism of the mouse cerebral cortex during T. gondii infection and have important implications for studies of T. gondii pathogenesis.</p>
Project description:Epitope mapping studies aim to identify the binding sites of antibody-antigen interactions to enhance the development of vaccines, diagnostics and immunotherapeutic compounds. However, mapping is a laborious process employing time- and resource-consuming M-bM-^@M-^Xwet benchM-bM-^@M-^Y techniques or epitope prediction software that are still in their infancy. For polymorphic antigens, another challenge is characterizing cross-reactivity between epitopes, teasing out distinctions between broadly cross-reactive responses, limited cross-reactions among variants and the truly type-specific responses. A refined understanding of cross-reactive antibody binding could guide the selection of the most informative subsets of variants for diagnostics and multivalent subunit vaccines. We explored the antibody binding reactivity of sera from human patients and Peromyscus leucopus rodents infected with Borrelia burgdorferi to the polymorphic outer surface protein C (OspC), an attractive candidate antigen for vaccine and improved diagnostics for Lyme disease. We constructed a protein microarray displaying 23 natural variants of OspC and quantified the degree of cross-reactive antibody binding between all pairs of variants, using Pearson correlation calculated on the reactivity values using three independent transforms of the raw data: (1) logarithmic, (2) rank, and (3) binary indicators. We observed that the global amino acid sequence identity between OspC pairs was a poor predictor of cross-reactive antibody binding. Then we asked if specific regions of the protein would better explain the observed cross-reactive binding and performed in silico screening of the linear sequence and 3-dimensional structure of OspC. This analysis pointed to the C-terminal helix of the structure as a major determinant of type-specific cross-reactive antibody binding. We developed bioinformatics methods to systematically analyze the relationship between local sequence/structure variation and cross-reactive antibody binding patterns among variants of a polymorphic antigen, and this method can be applied to other polymorphic antigens for which immune response data is available for multiple variants. Antibody profiling was performed on sera from Borrelia burgdorferi infected and non-infected humans and Peromyscus leucopus rodents against 23 variants of the surface protein OspC . For infected human serum samples, the OspC type of the infecting B. burgdorferi strain is unknown; for experimentally-infected P. leucopus serum samples, it is known. Of human serum samples, 55 were from infected individuals and 25 from naive controls. Of P. leucopus serum samples, 23 were from infected individuals and 7 were from naive controls.
Project description:This article describes a suite of global climate model output files that provide continental climatic conditions (monthly temperatures, precipitation, evaporation, precipitation minus evaporation balance, runoff) together with the calculated Köppen-Geiger climate classes and topography, for 28 evenly spaced time slices through the Phanerozoic (Cambrian to Quaternary, 540 Ma to 0 Ma). Climatic variables were simulated with the Fast Ocean Atmosphere Model (FOAM), using a recent set of open-access continental reconstructions with paleotopography and recent atmospheric CO2 and solar luminosity estimates. FOAM is a general circulation model frequently used in paleoclimate studies, especially in the Palaeozoic. Köppen-Geiger climate classes were calculated based on simulated temperature and precipitation fields using Wong Hearing et al.'s [1] implementation of Peel et al.'s [2] updated classification. This dataset provides a unique window onto changing continental climate throughout the Phanerozoic that accounts for the simultaneous evolution of paleogeography (continental configuration and topography), atmospheric composition and greenhouse gas forcing, and solar luminosity.
Project description:We analyzed proteome of the anammox bacterium Kuenenia stuttgartiensis strain CSTR1 after separation by size exclusion chromatography. Each fraction has a volume of 0.1 mL. Elution volume is between 11.5 and 13.9 mL