Target highlights in CASP13: Experimental target structures through the eyes of their authors

The functional and biological significance of selected CASP13 targets are described by the authors of the structures. The structural biologists discuss the most interesting structural features of the target proteins and assess whether these features were correctly reproduced in the predictions submitted to the CASP13 experiment.     

Multiblock PLS analysis of an industrial pharmaceutical process

The performance of an industrial pharmaceutical process (production of an active pharmaceutical ingredient by fermentation, API) was modeled by multiblock partial least squares (MBPLS). The most important process stages are inoculum production and API production fermentation. Thirty batches (runs) were produced according to an experimental planning. Rather than merging all these data into a single block of independent variables (as in ordinary PLS), four data blocks were used separately (manipulated and quality variables for each process stage). With the multiblock approach it was possible to calculate weights and scores for each independent block. It was found that the inoculum quality variables were highly correlated with API production for nominal fermentations. For the nonnominal fermentations, the manipulations of the fermentation stage explained the amount of API obtained (especially the pH and biomass concentration). Based on the above process analysis it was possible to select a smaller set of variables with which a new model was built. The amount of variance predicted of the final API concentration (cross-validation) for this model was 82.4%. The advantage of the multiblock model over the standard PLS model is that the contributions of the two main process stages to the API volumetric productivity were determined.     

Expression of Lex antigen in Schistosoma japonicum and S.haematobium and immune responses to Lex in infected animals: lack of Lex expression in other trematodes and nematodes

Adults of the human parasitic trematode Schistosoma mansoni, which causes hepatosplenic/intestinal complications in humans, synthesize glycoconjugates containing the Lewis x (Lex) Galbeta1-->4(Fucalpha1-- >3)GlcNAcbeta1-->R, but not sialyl Lewis x (sLex), antigen. We now report on our analyses of Lexand sLexexpression in S.haematobium and S.japonicum, which are two other major species of human schistosomes that cause disease, and the possible autoimmunity to these antigens in infected individuals. Antigen expression was evaluated by both ELISA and Western blot analyses of detergent extracts of parasites using monoclonal antibodies. Several high molecular weight glycoproteins in both S. haematobium and S. japonicum contain the Lexantigen, but no sialyl Lexantigen was detected. In addition, sera from humans and rodents infected with S.haematobium and S.japonicum contain antibodies reactive with Lex. These results led us to investigate whether Lexantigens are expressed in other helminths, including the parasitic trematode Fasciola hepatica , the parasitic nematode Dirofilaria immitis (dog heartworm), the ruminant nematode Haemonchus contortus , and the free-living nematode Caenorhabditis elegans . Neither Lexnor sialyl-Lexis detectable in these other helminths. Furthermore, none of the helminths, including schistosomes, express Lea, Leb, Ley, or the H- type 1 antigen. However, several glycoproteins from all helminths analyzed are bound by Lotus tetragonolobus agglutinin , which binds Fucalpha1-->3GlcNAc, and Wisteria floribunda agglutinin, which binds GalNAcbeta1-->4GlcNAc (lacdiNAc or LDN). Thus, schistosomes may be unique among helminths in expressing the Lexantigen, whereas many different helminths may express alpha1,3-fucosylated glycans and the LDN motif.      

Analysis of longitudinal metabolomics data

MOTIVATION: Metabolomics datasets are generally large and complex. Using principal component analysis (PCA), a simplified view of the variation in the data is obtained. The PCA model can be interpreted and the processes underlying the variation in the data can be analysed. In metabolomics, often a priori information is present about the data. Various forms of this information can be used in an unsupervised data analysis with weighted PCA (WPCA). A WPCA model will give a view on the data that is different from the view obtained using PCA, and it will add to the interpretation of the information in a metabolomics dataset. RESULTS: A method is presented to translate spectra of repeated measurements into weights describing the experimental error. These weights are used in the data analysis with WPCA. The WPCA model will give a view on the data where the non-uniform experimental error is accounted for. Therefore, the WPCA model will focus more on the natural variation in the data. AVAILABILITY: M-files for MATLAB for the algorithm used in this research are available at http://www-its.chem.uva.nl/research/pac/Software/pcaw.zip.