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      VAR2CSA Signatures of High Plasmodium falciparum Parasitemia in the Placenta

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          Abstract

          Plasmodium falciparum infected erythrocytes (IE) accumulate in the placenta through the interaction between Duffy-binding like (DBL) domains of parasite-encoded ligand VAR2CSA and chondroitin sulphate-A (CSA) receptor. Polymorphisms in these domains, including DBL2X and DBL3X, may affect their antigenicity or CSA-binding affinity, eventually increasing parasitemia and its adverse effects on pregnancy outcomes. A total of 373 DBL2X and 328 DBL3X sequences were obtained from transcripts of 20 placental isolates infecting Mozambican women, resulting in 176 DBL2X and 191 DBL3X unique sequences at the protein level. Sequence alignments were divided in segments containing combinations of correlated polymorphisms and the association of segment sequences with placental parasite density was tested using Bonferroni corrected regression models, taking into consideration the weight of each sequence in the infection. Three DBL2X and three DBL3X segments contained signatures of high parasite density ( P<0.003) that were highly prevalent in the parasite population (49–91%). Identified regions included a flexible loop that contributes to DBL3X-CSA interaction and two DBL3X motifs with evidence of positive natural selection. Limited antibody responses against signatures of high parasite density among malaria-exposed pregnant women could not explain the increased placental parasitemia. These results suggest that a higher binding efficiency to CSA rather than reduced antigenicity might provide a biological advantage to parasites with high parasite density signatures in VAR2CSA. Sequences contributing to high parasitemia may be critical for the functional characterization of VAR2CSA and the development of tools against placental malaria.

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          Most cited references54

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          Improved method for predicting linear B-cell epitopes

          Background B-cell epitopes are the sites of molecules that are recognized by antibodies of the immune system. Knowledge of B-cell epitopes may be used in the design of vaccines and diagnostics tests. It is therefore of interest to develop improved methods for predicting B-cell epitopes. In this paper, we describe an improved method for predicting linear B-cell epitopes. Results In order to do this, three data sets of linear B-cell epitope annotated proteins were constructed. A data set was collected from the literature, another data set was extracted from the AntiJen database and a data sets of epitopes in the proteins of HIV was collected from the Los Alamos HIV database. An unbiased validation of the methods was made by testing on data sets on which they were neither trained nor optimized on. We have measured the performance in a non-parametric way by constructing ROC-curves. Conclusion The best single method for predicting linear B-cell epitopes is the hidden Markov model. Combining the hidden Markov model with one of the best propensity scale methods, we obtained the BepiPred method. When tested on the validation data set this method performs significantly better than any of the other methods tested. The server and data sets are publicly available at .
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            Adherence of Plasmodium falciparum to chondroitin sulfate A in the human placenta.

            Women are particularly susceptible to malaria during first and second pregnancies, even though they may have developed immunity over years of residence in endemic areas. Plasmodium falciparum-infected red blood cells (IRBCs) were obtained from human placentas. These IRBCs bound to purified chondroitin sulfate A (CSA) but not to other extracellular matrix proteins or to other known IRBC receptors. IRBCs from nonpregnant donors did not bind to CSA. Placental IRBCs adhered to sections of fresh-frozen human placenta with an anatomic distribution similar to that of naturally infected placentas, and this adhesion was competitively inhibited by purified CSA. Thus, adhesion to CSA appears to select for a subpopulation of parasites that causes maternal malaria.
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              RevTrans: Multiple alignment of coding DNA from aligned amino acid sequences.

              The simple fact that proteins are built from 20 amino acids while DNA only contains four different bases, means that the 'signal-to-noise ratio' in protein sequence alignments is much better than in alignments of DNA. Besides this information-theoretical advantage, protein alignments also benefit from the information that is implicit in empirical substitution matrices such as BLOSUM-62. Taken together with the generally higher rate of synonymous mutations over non-synonymous ones, this means that the phylogenetic signal disappears much more rapidly from DNA sequences than from the encoded proteins. It is therefore preferable to align coding DNA at the amino acid level and it is for this purpose we have constructed the program RevTrans. RevTrans constructs a multiple DNA alignment by: (i) translating the DNA; (ii) aligning the resulting peptide sequences; and (iii) building a multiple DNA alignment by 'reverse translation' of the aligned protein sequences. In the resulting DNA alignment, gaps occur in groups of three corresponding to entire codons, and analogous codon positions are therefore always lined up. These features are useful when constructing multiple DNA alignments for phylogenetic analysis. RevTrans also accepts user-provided protein alignments for greater control of the alignment process. The RevTrans web server is freely available at http://www.cbs.dtu.dk/services/RevTrans/.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                25 July 2013
                : 8
                : 7
                : e69753
                Affiliations
                [1 ]Barcelona Centre for International Health Research (CRESIB, Hospital Clínic-Universitat de Barcelona), Barcelona, Spain
                [2 ]Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
                [3 ]Broad Institute, Cambridge, Massachusetts, United States of America
                [4 ]Department of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America
                [5 ]Department of Pathology, Hospital Clínic-Universitat de Barcelona, Barcelona, Spain
                Centro de Pesquisa Rene Rachou/Fundação Oswaldo Cruz (Fiocruz-Minas), Brazil
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: ERV PA CD JO CM AM. Performed the experiments: ERV IM AB ESC DQ. Analyzed the data: ERV IM AM. Contributed reagents/materials/analysis tools: DEN CV JO. Wrote the paper: ERV AM.

                Article
                PONE-D-13-11443
                10.1371/journal.pone.0069753
                3723727
                23936092
                a231650e-5610-4c46-b889-2c7bfcc6af7b
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 March 2013
                : 11 June 2013
                Page count
                Pages: 10
                Funding
                The study received financial support from the Instituto de Salud Carlos III (project PS09/01113; grant FI06/00019 to E.R.V.; salary support CP-04/00220 to A.M.) and the Ministerio de Ciencia e Innovación (salary support RYC-2008-02631 to C.D.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Molecular Genetics
                Gene Expression
                Population Genetics
                Genetic Polymorphism
                Sequence Analysis
                Genetics
                Population Genetics
                Genetic Polymorphism
                Microbiology
                Host-Pathogen Interaction
                Parasitology
                Molecular Cell Biology
                Cell Adhesion
                Medicine
                Clinical Immunology
                Immunity
                Vaccination
                Vaccines
                Global Health
                Infectious Diseases
                Parasitic Diseases
                Malaria
                Plasmodium Falciparum
                Tropical Diseases (Non-Neglected)
                Malaria
                Plasmodium Falciparum
                Obstetrics and Gynecology
                Pregnancy
                Pregnancy Complications

                Uncategorized
                Uncategorized

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