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      Population structure, epidemiology and antibiotic resistance patterns of Streptococcus pneumoniae serotype 5: prior to PCV-13 vaccine introduction in Eastern Gambia

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          Abstract

          Background

          Streptococcus pneumoniae serotype 5 is among the most common serotypes causing invasive pneumococcal disease (IPD) in The Gambia. We anticipate that introduction of the 13-valent pneumococcal conjugate vaccine (PCV-13) into routine vaccination in The Gambia will reduce serotype 5 IPD. However, the emergence of new clones that have altered their genetic repertoire through capsular switching or genetic recombination after vaccination with PCV-13 poses a threat to this public health effort. In order to monitor for potential genetic changes post-PCV-13 vaccination, we established the baseline population structure, epidemiology, and antibiotic resistance patterns of serotype 5 before the introduction of PCV-13.

          Methods

          Fifty-five invasive S. pneumoniae serotype 5 isolates were recovered from January 2009 to August 2011 in a population-based study in the Upper River Region of The Gambia. Serotyping was done by latex agglutination and confirmed by serotype-specific Polymerase Chain Reaction (PCR). Genotyping was undertaken using Multilocus Sequence Typing (MLST). Antimicrobial sensitivity was done using disc diffusion. Contingency table analyses were conducted using Pearson’s Chi 2 and Fisher’s exact test. Clustering was performed using Bionumerics version 6.5.

          Results

          MLST resolved S. pneumoniae serotype 5 isolates into 3 sequence types (ST), namely ST 289(6/55), ST 3339(19/55) and ST 3404(30/55). ST 289 was identified as the major clonal complex. ST 3339, the prevalent genotype in 2009 [84.6 % (11/13)], was replaced by ST 3404 [70.4 % (19/27)] in 2010 as the dominant ST. Interestingly, ST 3404 showed lower resistance to tetracycline and oxacillin ( P < 0.001), an empirical surrogate to penicillin in The Gambia.

          Conclusions

          There has been an emergence of ST 3404 in The Gambia prior to the introduction of PCV-13. Our findings provide important background data for future assessment of the impact of PCV-13 into routine immunization in developing countries, such as The Gambia.

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          Most cited references24

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          HLA-E binds to natural killer cell receptors CD94/NKG2A, B and C.

          The protein HLA-E is a non-classical major histocompatibility complex (MHC) molecule of limited sequence variability. Its expression on the cell surface is regulated by the binding of peptides derived from the signal sequence of some other MHC class I molecules. Here we report the identification of ligands for HLA-E. We constructed tetramers in which recombinant HLA-E and beta2-microglobulin were refolded with an MHC leader-sequence peptide, biotinylated, and conjugated to phycoerythrin-labelled Extravidin. This HLA-E tetramer bound to natural killer (NK) cells and a small subset of T cells from peripheral blood. On transfectants, the tetramer bound to the CD94/NKG2A, CD94/NKGK2B and CD94/NKG2C NK cell receptors, but did not bind to the immunoglobulin family of NK cell receptors (KIR). Surface expression of HLA-E was enough to protect target cells from lysis by CD94/NKG2A+ NK-cell clones. A subset of HLA class I alleles has been shown to inhibit killing by CD94/NKG2A+ NK-cell clones. Only the HLA alleles that possess a leader peptide capable of upregulating HLA-E surface expression confer resistance to NK-cell-mediated lysis, implying that their action is mediated by HLA-E, the predominant ligand for the NK cell inhibitory receptor CD94/NKG2A.
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            Global optimal eBURST analysis of multilocus typing data using a graphic matroid approach

            Background Multilocus Sequence Typing (MLST) is a frequently used typing method for the analysis of the clonal relationships among strains of several clinically relevant microbial species. MLST is based on the sequence of housekeeping genes that result in each strain having a distinct numerical allelic profile, which is abbreviated to a unique identifier: the sequence type (ST). The relatedness between two strains can then be inferred by the differences between allelic profiles. For a more comprehensive analysis of the possible patterns of evolutionary descent, a set of rules were proposed and implemented in the eBURST algorithm. These rules allow the division of a data set into several clusters of related strains, dubbed clonal complexes, by implementing a simple model of clonal expansion and diversification. Within each clonal complex, the rules identify which links between STs correspond to the most probable pattern of descent. However, the eBURST algorithm is not globally optimized, which can result in links, within the clonal complexes, that violate the rules proposed. Results Here, we present a globally optimized implementation of the eBURST algorithm – goeBURST. The search for a global optimal solution led to the formalization of the problem as a graphic matroid, for which greedy algorithms that provide an optimal solution exist. Several public data sets of MLST data were tested and differences between the two implementations were found and are discussed for five bacterial species: Enterococcus faecium, Streptococcus pneumoniae, Burkholderia pseudomallei, Campylobacter jejuni and Neisseria spp.. A novel feature implemented in goeBURST is the representation of the level of tiebreak rule reached before deciding if a link should be drawn, which can used to visually evaluate the reliability of the represented hypothetical pattern of descent. Conclusion goeBURST is a globally optimized implementation of the eBURST algorithm, that identifies alternative patterns of descent for several bacterial species. Furthermore, the algorithm can be applied to any multilocus typing data based on the number of differences between numeric profiles. A software implementation is available at .
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              Sequential multiplex PCR approach for determining capsular serotypes of Streptococcus pneumoniae isolates.

              Accurate serotyping is essential to monitor the changes in the seroepidemiology of Streptococcus pneumoniae. We devised a simple and schematic sequence-based system of seven multiplex PCRs, in a sequence order based upon Active Bacterial Core surveillance (ABCs) serotype distribution during 2002 to 2003, to reliably deduce specific pneumococcal serotypes. A total of 421 isolates from ABCs were randomly chosen to evaluate this system. Two hundred twenty-nine of the isolates (54.3%) were specifically assigned 1 of 17 serotypes by the multiplex PCR system, with the results in complete concordance with conventional serotyping. One hundred seventy-two additional isolates (40.9%) were assigned to 11 specific sets of 2 to 4 serotypes that with one exception (serotypes 6A and 6B) consisted of the single frequently occurring targeted serotype and 1 to 3 additional rare serotypes primarily within the same serogroup as the targeted serotype. Only 20 isolates (4.8%) could not be assigned specific serotypes or serotype sets, since they were either of rare serotypes not included in the assay design or were nonserotypeable. Overall, we found this system to be highly reliable, with the potential to greatly reduce our reliance upon conventional serotyping. Especially important is the capability of this system to give serotype-determining potential to any facility that lacks the expensive typing sera and expertise needed for conventional serotyping yet has the modest equipment necessary for DNA amplification and electrophoresis.
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                Author and article information

                Contributors
                ashuebasi@yahoo.com
                shjarju@mrc.gm
                m.dione@cgiar.org
                gmackenzie@mrc.gm
                uikumapayi@mrc.gm
                kairo1601@yahoo.co.uk
                reazuine@globalhealthprojects.org
                mantonio@mrc.gm
                Journal
                BMC Infect Dis
                BMC Infect. Dis
                BMC Infectious Diseases
                BioMed Central (London )
                1471-2334
                28 January 2016
                28 January 2016
                2015
                : 16
                : 33
                Affiliations
                [ ]Department of Biology, McMaster University, 1280 Main St. W, Hamilton, ON L8S 4 K1, Canada
                [ ]Medical Research Council Unit, P. O. Box 273, Fajara, The Gambia
                [ ]King Fahad Medical City, Central, 11525 Saudi Arabia
                [ ]Center for Global Health and Health Policy, Global Health and Education Projects, P. O. BOX 234, Riverdale, MD 20738 USA
                Article
                1370
                10.1186/s12879-016-1370-0
                4731921
                26822883
                4186fa5c-4ad4-4cd9-8b8c-a99e0d92e0a7
                © Ashu et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 11 May 2015
                : 22 January 2016
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Infectious disease & Microbiology
                s. pneumoniae,serotype 5,st 3404,population structure,the gambia,pcv-13

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