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Biomedical subjects

Klaus-Peter Pleissner

Publications and source records attributed to Klaus-Peter Pleissner.

5 recordsLinked to original sources

Gain and loss of multiple genes during the evolution of Helicobacter pylori.

Sequence diversity and gene content distinguish most isolates of Helicobacter pylori. Even greater sequence differences differentiate distinct populations of H. pylori from different continents, but it was not clear whether these populations also differ in gene content. To address this question, we tested 56 globally representative strains of H. pylori and four strains of Helicobacter acinonychis with whole genome microarrays. Of the weighted average of 1,531 genes present in the two sequenced genomes, 25% are absent in at least one strain of H. pylori and 21% were absent or variable in H. acinonychis. We extrapolate that the core genome present in all isolates of H. pylori contains 1,111 genes. Variable genes tend to be small and possess unusual GC content; many of them have probably been imported by horizontal gene transfer. Phylogenetic trees based on the microarray data differ from those based on sequences of seven genes from the core genome. These discrepancies are due to homoplasies resulting from independent gene loss by deletion or recombination in multiple strains, which distort phylogenetic patterns. The patterns of these discrepancies versus population structure allow a reconstruction of the timing of the acquisition of variable genes within this species. Variable genes that are located within the cag pathogenicity island were apparently first acquired en bloc after speciation. In contrast, most other variable genes are of unknown function or encode restriction/modification enzymes, transposases, or outer membrane proteins. These seem to have been acquired prior to speciation of H. pylori and were subsequently lost by convergent evolution within individual strains. Thus, the use of microarrays can reveal patterns of gene gain or loss when examined within a phylogenetic context that is based on sequences of core genes.

Evolution, Molecular↗

Identification of candidate antigens for serologic detection of Helicobacter pylori-infected patients with gastric carcinoma.

Helicobacter pylori colonizes the stomach of almost half the world population and is a causative agent of gastric carcinomas and duodenal ulcers. Only a small fraction of infected people will develop these severe illnesses and a predictive test to identify people at high risk would greatly benefit disease management. Our study aimed to identify conserved bacterial antigens that may be useful for the development of such a diagnostic test. High-resolution immunoproteomics by 2-dimensional electrophoresis of H. pylori 26695 proteins was carried out with sera from infected patients with either duodenal ulcer (n=30) or gastric carcinoma (n=30), 2 clinically divergent conditions. According to their antigen recognition patterns clear groups of patients were identified. Although this classification did not correspond to the clinical status, it may be correlated to other bacterial or host factors that influence the outcome of infection. In general antigen recognition patterns were found to be highly variable, however by utilizing powerful image analysis and statistical tests the recognition of 14 antigenic protein species was found to differ significantly (p<0.01) between both diseases. Particular protein species of GroEL, HyuA, GroES and AtpA appear to be useful surrogate markers for gastric carcinoma detection and consequently should be considered for further prospective studies to assess their predictive value. For one protein species of AtpA, evidence was found that different post-translational modifications may confer different immunogenicities.

Adenocarcinoma↗

Web-accessible proteome databases for microbial research.

The analysis of proteomes of biological organisms represents a major challenge of the post-genome era. Classical proteomics combines two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) for the identification of proteins. Novel technologies such as isotope coded affinity tag (ICAT)-liquid chromatography/mass spectrometry (LC/MS) open new insights into protein alterations. The vast amount and diverse types of proteomic data require adequate web-accessible computational and database technologies for storage, integration, dissemination, analysis and visualization. A proteome database system (http://www.mpiib-berlin.mpg.de/2D-PAGE) for microbial research has been constructed which integrates 2-DE/MS, ICAT-LC/MS and functional classification data of proteins with genomic, metabolic and other biological knowledge sources. The two-dimensional polyacrylamide gel electrophoresis database delivers experimental data on microbial proteins including mass spectra for the validation of protein identification. The ICAT-LC/MS database comprises experimental data for protein alterations of mycobacterial strains BCG vs. H37Rv. By formulating complex queries within a functional protein classification database "FUNC_CLASS" for Mycobacterium tuberculosis and Helicobacter pylori the researcher can gather precise information on genes, proteins, protein classes and metabolic pathways. The use of the R language in the database architecture allows high-level data analysis and visualization to be performed "on-the-fly". The database system is centrally administrated, and investigators without specific bioinformatic competence in database construction can submit their data. The database system also serves as a template for a prototype of a European Proteome Database of Pathogenic Bacteria. Currently, the database system includes proteome information for six strains of microorganisms.

Bacterial Proteins↗

Assessment of protein spot components applying correspondence analysis for peptide mass fingerprint data.

Proteins separated by two-dimensional gel electrophoresis (2-DE) may be distributed over several spots. Otherwise, one spot may contain more than one component. The same protein occurring in several spots supposedly represents differently modified protein species that might be of biological relevance. Identification of spots with peptide mass fingerprinting and database searching leads only to the detection of the major spot components. If a spot also contains additional minor protein components, quantitation of spots with protein staining techniques or antibody detection becomes misleading. In order to find spots containing minor components we applied correspondence analysis, a multivariate data exploration method, to peptide mass fingerprint data. Correspondence analysis using peak lists revealed groups of spots containing the same protein with their characteristic mass-to-charge ratio (m/z) values. In order to detect different protein spot components an interactive threshold setting and removal of m/z values with subsequent recalculation of the correspondence analysis using our software tool CorrAn are performed. The usefulness of this methodical approach was shown by a data set of peptide mass fingerprints of 284 spots of Helicobacter pylori 26695 separated by 2-DE.

Bacterial Proteins↗

Presentation of differentially regulated proteins within a web-accessible proteome database system of microorganisms.

Web-accessible proteome databases represent indispensable tools for quantitative and comparative proteomics research. The majority of two-dimensional gel electrophoresis (2-DE) databases contains clickable 2-DE gel images and descriptive textual information such as protein name, Mr/pI values, methods of identification, cellular localization and other information on proteins. Although a great part of the work in comparative proteomics consists of the analysis of 2-DE gels using image analysis approaches, most proteome databases lack the ability to present protein abundance data and their alterations within experiments via the web. Now, differentially regulated proteins detected in microbial experiments by quantitative gel image analysis are presented in a web-accessible relational database DIFF (Differentially Regulated Proteins). The DIFF database is a part of the proteome database system for microbial research available at http://www.mpiib-berlin.mpg.de/2D-PAGE.

Bacterial Proteins↗