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Author

Ulrich Vogel

Other affiliations: Carlos III Health Institute
Bio: Ulrich Vogel is an academic researcher from University of Würzburg. The author has contributed to research in topics: Neisseria meningitidis & Vaccination. The author has an hindex of 43, co-authored 174 publications receiving 7800 citations. Previous affiliations of Ulrich Vogel include Carlos III Health Institute.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors used sequence typing of the spa gene repeat region to study the epidemiology of MRSA at a German university hospital during two periods of 10 and 4 months, respectively.
Abstract: The spa gene of Staphylococcus aureus encodes protein A and is used for typing of methicillin-resistant Staphylococcus aureus (MRSA) We used sequence typing of the spa gene repeat region to study the epidemiology of MRSA at a German university hospital One hundred seven and 84 strains were studied during two periods of 10 and 4 months, respectively Repeats and spa types were determined by Ridom StaphType, a novel software tool allowing rapid repeat determination, data management and retrieval, and Internet-based assignment of new spa types following automatic quality control of DNA sequence chromatograms Isolates representative of the most abundant spa types were subjected to multilocus sequence typing and pulsed-field gel electrophoresis One of two predominant spa types was replaced by a clonally related variant in the second study period Ten unique spa types, which were equally distributed in both study periods, were recovered The data show a rapid dynamics of clone circulation in a university hospital setting spa typing was valuable for tracking of epidemic isolates The data show that disproval of epidemiologically suggested transmissions of MRSA is one of the main objectives of spa typing in departments with a high incidence of MRSA

1,544 citations

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TL;DR: The hypothesis that inhibiting the binding of a complement down-regulator protein to the neisserial surface by specific Ab may enhance intrinsic bactericidal activity of the Ab is supported, resulting in two distinct mechanisms of Ab-mediated vaccine efficacy.
Abstract: Neisseria meningitidis binds factor H (fH), a key regulator of the alternative complement pathway. A approximately 29 kD fH-binding protein expressed in the meningococcal outer membrane was identified by mass spectrometry as GNA1870, a lipoprotein currently under evaluation as a broad-spectrum meningococcal vaccine candidate. GNA1870 was confirmed as the fH ligand on intact bacteria by 1) abrogation of fH binding upon deleting GNA1870, and 2) blocking fH binding by anti-GNA1870 mAbs. fH bound to whole bacteria and purified rGNA1870 representing each of the three variant GNA1870 families. We showed that the amount of fH binding correlated with the level of bacterial GNA1870 expression. High levels of variant 1 GNA1870 expression (either by allelic replacement of gna1870 or by plasmid-driven high-level expression) in strains that otherwise were low-level GNA1870 expressers (and bound low amounts of fH by flow cytometry) restored high levels of fH binding. Diminished fH binding to the GNA1870 deletion mutants was accompanied by enhanced C3 binding and increased killing of the mutants. Conversely, high levels of GNA1870 expression and fH binding enhanced serum resistance. Our findings support the hypothesis that inhibiting the binding of a complement down-regulator protein to the neisserial surface by specific Ab may enhance intrinsic bactericidal activity of the Ab, resulting in two distinct mechanisms of Ab-mediated vaccine efficacy. These data provide further support for inclusion of this molecule in a meningococcal vaccine. To reflect the critical function of this molecule, we suggest calling it fH-binding protein.

412 citations

Journal ArticleDOI
TL;DR: MATS analysis showed that a multicomponent vaccine could protect against a substantial proportion of invasive MenB strains isolated in Europe, however, monitoring of antigen expression will be needed in the future.
Abstract: Summary Background A novel multicomponent vaccine against meningococcal capsular group B (MenB) disease contains four major components: factor-H-binding protein, neisserial heparin binding antigen, neisserial adhesin A, and outer-membrane vesicles derived from the strain NZ98/254. Because the public health effect of the vaccine, 4CMenB (Novartis Vaccines and Diagnostics, Siena, Italy), is unclear, we assessed the predicted strain coverage in Europe. Methods We assessed invasive MenB strains isolated mainly in the most recent full epidemiological year in England and Wales, France, Germany, Italy, and Norway. Meningococcal antigen typing system (MATS) results were linked to multilocus sequence typing and antigen sequence data. To investigate whether generalisation of coverage applied to the rest of Europe, we also assessed isolates from the Czech Republic and Spain. Findings 1052 strains collected from July, 2007, to June, 2008, were assessed from England and Wales, France, Germany, Italy, and Norway. All MenB strains contained at least one gene encoding a major antigen in the vaccine. MATS predicted that 78% of all MenB strains would be killed by postvaccination sera (95% CI 63–90, range of point estimates 73–87% in individual country panels). Half of all strains and 64% of covered strains could be targeted by bactericidal antibodies against more than one vaccine antigen. Results for the 108 isolates from the Czech Republic and 300 from Spain were consistent with those for the other countries. Interpretation MATS analysis showed that a multicomponent vaccine could protect against a substantial proportion of invasive MenB strains isolated in Europe. Monitoring of antigen expression, however, will be needed in the future. Funding Novartis Vaccines and Diagnostics.

281 citations

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TL;DR: A comprehensive description of all N. meningitidis serogroups is provided, along with a proposed nomenclature, which was presented at the 2012 XVIIIth International Pathogenic Neisseria Conference.
Abstract: Pathogenic Neisseria meningitidis isolates contain a polysaccharide capsule that is the main virulence determinant for this bacterium. Thirteen capsular polysaccharides have been described, and nuclear magnetic resonance spectroscopy has enabled determination of the structure of capsular polysaccharides responsible for serogroup specificity. Molecular mechanisms involved in N. meningitidis capsule biosynthesis have also been identified, and genes involved in this process and in cell surface translocation are clustered at a single chromosomal locus termed cps. The use of multiple names for some of the genes involved in capsule synthesis, combined with the need for rapid diagnosis of serogroups commonly associated with invasive meningococcal disease, prompted a requirement for a consistent approach to the nomenclature of capsule genes. In this report, a comprehensive description of all N. meningitidis serogroups is provided, along with a proposed nomenclature, which was presented at the 2012 XVIIIth International Pathogenic Neisseria Conference.

255 citations

Journal ArticleDOI
TL;DR: DNA sequence-based typing of the Staphylococcus aureus protein A gene showed 100% intra- and interlaboratory reproducibility without extensive harmonization of protocols for 30 blind-coded S. aureUS DNA samples sent to 10 laboratories.
Abstract: Current DNA amplification-based typing methods for bacterial pathogens often lack interlaboratory reproducibility. In this international study, DNA sequence-based typing of the Staphylococcus aureus protein A gene (spa, 110 to 422 bp) showed 100% intra- and interlaboratory reproducibility without extensive harmonization of protocols for 30 blind-coded S. aureus DNA samples sent to 10 laboratories. Specialized software for automated sequence analysis ensured a common typing nomenclature.

213 citations


Cited by
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Journal Article
Fumio Tajima1
30 Oct 1989-Genomics
TL;DR: It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.

11,521 citations

Journal ArticleDOI
TL;DR: The Bacterial Isolate Genome Sequence Database (BIGSDB) represents a freely available resource that will assist the broader community in the elucidation of the structure and function of bacteria by means of a population genomics approach.
Abstract: The opportunities for bacterial population genomics that are being realised by the application of parallel nucleotide sequencing require novel bioinformatics platforms These must be capable of the storage, retrieval, and analysis of linked phenotypic and genotypic information in an accessible, scalable and computationally efficient manner The Bacterial Isolate Genome Sequence Database (BIGSDB) is a scalable, open source, web-accessible database system that meets these needs, enabling phenotype and sequence data, which can range from a single sequence read to whole genome data, to be efficiently linked for a limitless number of bacterial specimens The system builds on the widely used mlstdbNet software, developed for the storage and distribution of multilocus sequence typing (MLST) data, and incorporates the capacity to define and identify any number of loci and genetic variants at those loci within the stored nucleotide sequences These loci can be further organised into 'schemes' for isolate characterisation or for evolutionary or functional analyses Isolates and loci can be indexed by multiple names and any number of alternative schemes can be accommodated, enabling cross-referencing of different studies and approaches LIMS functionality of the software enables linkage to and organisation of laboratory samples The data are easily linked to external databases and fine-grained authentication of access permits multiple users to participate in community annotation by setting up or contributing to different schemes within the database Some of the applications of BIGSDB are illustrated with the genera Neisseria and Streptococcus The BIGSDB source code and documentation are available at http://pubmlstorg/software/database/bigsdb/ Genomic data can be used to characterise bacterial isolates in many different ways but it can also be efficiently exploited for evolutionary or functional studies BIGSDB represents a freely available resource that will assist the broader community in the elucidation of the structure and function of bacteria by means of a population genomics approach

1,943 citations

Journal ArticleDOI
TL;DR: This Review highlights the most important antiviral mechanisms of bacteria as well as the counter-attacks used by phages to evade these systems.
Abstract: Phages are now acknowledged as the most abundant microorganisms on the planet and are also possibly the most diversified. This diversity is mostly driven by their dynamic adaptation when facing selective pressure such as phage resistance mechanisms, which are widespread in bacterial hosts. When infecting bacterial cells, phages face a range of antiviral mechanisms, and they have evolved multiple tactics to avoid, circumvent or subvert these mechanisms in order to thrive in most environments. In this Review, we highlight the most important antiviral mechanisms of bacteria as well as the counter-attacks used by phages to evade these systems.

1,894 citations

Journal ArticleDOI
TL;DR: A new implementation of eBURST is presented, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment.
Abstract: The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain(23F)-1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.

1,800 citations