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.      

Surface display of a functional single-chain Fv antibody on staphylococci.

Two different host-vector expression systems designed for cell surface display of chimeric receptors on Staphylococcus xylosus and Staphylococcus carnosus have been evaluated for surface display of a mouse immunoglobulin G1(kappa) [IgG1(kappa)] anti-human IgE single-chain Fv (scFv) antibody fragment. To achieve surface anchoring of the chimeric receptors containing the scFv, the cell surface attachment regions from Staphylococcus aureus protein A were used in both expression systems. The different chimeric receptors could be recovered from cell wall extracts of both S. xylosus and S. carnosus, and surface localization was demonstrated by taking advantage of a serum albumin-binding reporter region present within the two types of receptors. In addition, the two different recombinant staphylococci carrying hybrid receptors containing the scFv were demonstrated to react with the antigen, which was human IgE, in whole-cell enzyme-linked immunosorbent assays. This is the first report of an antibody fragment expressed in a functional form anchored to the surface of gram-positive bacteria. The potential use of recombinant gram-positive bacteria as whole-cell diagnostic devices or alternatives to filamentous phages for surface display of scFv libraries is discussed.     

Nifedipine loaded chitosan microspheres prepared by emulsification phase-separation

A high yield of nifedipine-chitosan microspheres could be obtained using an emulsification phase-separation method. A high level of entrapment of nifedipine in the microspheres was achieved. The microspheres exhibited excellent swelling properties. Differential scanning calorimetry, X-ray diffractometry, and scanning electron microscopy confirmed that at 1.84% loading, nifedipine was dispersed molecularly. The microspheres exhibited faster release at low loadings compared to high loadings. Fitting the data to the coupled Fickian/case II equation, showed that at low loadings polymer relaxation coefficients (k₂) were high. As the polymer content increased in the microspheres, the value of n (diffusional exponent characteristic of the release mechanism) approached one, which is indicative of zero order.     

Predicting breast cancer using an expression values weighted clinical classifier

Background

Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier.LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.

Results

We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies.

Conclusions

Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems.     

Dissecting Antibodies with Regards to Linear and Conformational Epitopes

An important issue for the performance and specificity of an antibody is the nature of the binding to its protein target, including if the recognition involves linear or conformational epitopes. Here, we dissect polyclonal sera by creating epitope-specific antibody fractions using a combination of epitope mapping and an affinity capture approach involving both synthesized peptides and recombinant protein fragments. This allowed us to study the relative amounts of antibodies to linear and conformational epitopes in the polyclonal sera as well as the ability of each antibody-fraction to detect its target protein in Western blot assays. The majority of the analyzed polyclonal sera were found to have most of the target-specific antibodies directed towards linear epitopes and these were in many cases giving Western blot bands of correct molecular weight. In contrast, many of the antibodies towards conformational epitopes did not bind their target proteins in the Western blot assays. The results from this work have given us insights regarding the nature of the antibody response generated by immunization with recombinant protein fragments and has demonstrated the advantage of using antibodies recognizing linear epitopes for immunoassay involving wholly or partially denatured protein targets.     

A reagent resource to identify proteins and peptides of interest for the cancer community: a workshop report

On the basis of discussions with representatives from all sectors of the cancer research community, the National Cancer Institute (NCI) recognizes the immense opportunities to apply proteomics technologies to further cancer research. Validated and well characterized affinity capture reagents (e.g. antibodies, aptamers, and affibodies) will play a key role in proteomics research platforms for the prevention, early detection, treatment, and monitoring of cancer. To discuss ways to develop new resources and optimize current opportunities in this area, the NCI convened the "Proteomic Technologies Reagents Resource Workshop" in Chicago, IL on December 12-13, 2005. The workshop brought together leading scientists in proteomics research to discuss model systems for evaluating and delivering resources for reagents to support MS and affinity capture platforms. Speakers discussed issues and identified action items related to an overall vision for and proposed models for a shared proteomics reagents resource, applications of affinity capture methods in cancer research, quality control and validation of affinity capture reagents, considerations for target selection, and construction of a reagents database. The meeting also featured presentations and discussion from leading private sector investigators on state-of-the-art technologies and capabilities to meet the user community's needs. This workshop was developed as a component of the NCI's Clinical Proteomics Technologies Initiative for Cancer, a coordinated initiative that includes the establishment of reagent resources for the scientific community. This workshop report explores various approaches to develop a framework that will most effectively fulfill the needs of the NCI and the cancer research community.