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      Distinct effects on diversifying selection by two mechanisms of immunity against Streptococcus pneumoniae.

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          Abstract

          Antigenic variation to evade host immunity has long been assumed to be a driving force of diversifying selection in pathogens. Colonization by Streptococcus pneumoniae, which is central to the organism's transmission and therefore evolution, is limited by two arms of the immune system: antibody- and T cell- mediated immunity. In particular, the effector activity of CD4(+) T(H)17 cell mediated immunity has been shown to act in trans, clearing co-colonizing pneumococci that do not bear the relevant antigen. It is thus unclear whether T(H)17 cell immunity allows benefit of antigenic variation and contributes to diversifying selection. Here we show that antigen-specific CD4(+) T(H)17 cell immunity almost equally reduces colonization by both an antigen-positive strain and a co-colonized, antigen-negative strain in a mouse model of pneumococcal carriage, thus potentially minimizing the advantage of escape from this type of immunity. Using a proteomic screening approach, we identified a list of candidate human CD4(+) T(H)17 cell antigens. Using this list and a previously published list of pneumococcal Antibody antigens, we bioinformatically assessed the signals of diversifying selection among the identified antigens compared to non-antigens. We found that Antibody antigen genes were significantly more likely to be under diversifying selection than the T(H)17 cell antigen genes, which were indistinguishable from non-antigens. Within the Antibody antigens, epitopes recognized by human antibodies showed stronger evidence of diversifying selection. Taken together, the data suggest that T(H)17 cell-mediated immunity, one form of T cell immunity that is important to limit carriage of antigen-positive pneumococcus, favors little diversifying selection in the targeted antigen. The results could provide new insight into pneumococcal vaccine design.

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          Most cited references37

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          Longitudinal data analysis for discrete and continuous outcomes.

          Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.
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            An algorithm for progressive multiple alignment of sequences with insertions.

            Dynamic programming algorithms guarantee to find the optimal alignment between two sequences. For more than a few sequences, exact algorithms become computationally impractical, and progressive algorithms iterating pairwise alignments are widely used. These heuristic methods have a serious drawback because pairwise algorithms do not differentiate insertions from deletions and end up penalizing single insertion events multiple times. Such an unrealistically high penalty for insertions typically results in overmatching of sequences and an underestimation of the number of insertion events. We describe a modification of the traditional alignment algorithm that can distinguish insertion from deletion and avoid repeated penalization of insertions and illustrate this method with a pair hidden Markov model that uses an evolutionary scoring function. In comparison with a traditional progressive alignment method, our algorithm infers a greater number of insertion events and creates gaps that are phylogenetically consistent but spatially less concentrated. Our results suggest that some insertion/deletion "hot spots" may actually be artifacts of traditional alignment algorithms.
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              Antigenic variation in Plasmodium falciparum.

              The persistence of the human malaria parasite Plasmodium falciparum during blood stage proliferation in its host depends on the successive expression of variant molecules at the surface of infected erythrocytes. This variation is mediated by the differential control of a family of surface molecules termed PfEMP1 encoded by approximately 60 var genes. Each individual parasite expresses a single var gene at a time, maintaining all other members of the family in a transcriptionally silent state. PfEMP1/var enables parasitized erythrocytes to adhere within the microvasculature, resulting in severe disease. This review highlights key regulatory mechanisms thought to be critical for monoallelic expression of var genes. Antigenic variation is orchestrated by epigenetic factors including monoallelic var transcription at separate spatial domains at the nuclear periphery, differential histone marks on otherwise identical var genes, and var silencing mediated by telomeric heterochromatin. In addition, controversies surrounding var genetic elements in antigenic variation are discussed.
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                Author and article information

                Journal
                PLoS Pathog.
                PLoS pathogens
                Public Library of Science (PLoS)
                1553-7374
                1553-7366
                2012
                : 8
                : 11
                Affiliations
                [1 ] Department of Epidemiology and Department of Immunology & Infectious Diseases, Harvard School of Public Health, Boston, Massachusetts, United States of America. liyuan@hsph.harvard.edu
                Article
                PPATHOGENS-D-12-00854
                10.1371/journal.ppat.1002989
                3493470
                23144610
                659ea6f4-a08f-4956-be70-2b08e178506c
                History

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