Institut für Hygiene und Mikrobiologie

    Functional Genomics and Systems Microbiology of N. meningitidis


    For N. meningitidis we could recently demonstrate by whole-transcriptome comparison that on adhesion to nasopharyngeal cells in vitro almost 8% of their shared genes were differentially expressed in two serogroup B strains from the clonal complexes ST-41/44 and ST-32, respectively. Remarkably, genes differently expressed in both strains were enriched for genes involved in energy metabolism and stress response (Figure 3).


    Figure 3. Functional classification of genes differentially expressed upon adhesion to human FaDu nasopharyngeal cell lines in the two meningococcal serogroup B strains MC58 and α710.
    Core genes regulated in both strains are depicted as black bars, core genes regulated only in MC58 as dark grey and those regulated only in α710 as light grey bars, respectively, and regulated MC58 specific genes are depicted as white bars. (A) Distribution of core and MC58 specific genes among the five different COG functional classes. The regulated core genes are not distributed equally over the five functional classes (p < 0.01, x2 test) but are enriched for metabolic genes in the respective three datasets. Likewise, the distribution of core genes that are regulated in only one strain also differs significantly between both strains (p < 10-15, x2 test) and also with the core genes regulated in both strains (p < 10-9, x2 test), respectively. In contrast, the regulated MC58 specific genes are evenly distributed over all functional classes (p = 0.77, x2 test). (B) Distribution among the different COG functional categories separated into up and down-regulated genes. For each of the four datasets the percentage of regulated genes adds up to 100% separately. Fifty-eight percent of the down-regulated MC58 specific genes fall into COG category X which therefore falls off the scale to the right side of the histogram. In all four datasets the core genes that are up-regulated in only one strain are enriched for genes coding for proteins involved in translation, ribosomal structure and biogenesis (COG J) (p < 0.05, Fisher’s exact test with BH multiple testing correction). For clarity, significance differences have not been depicted in the diagram. Abbreviations: C, Energy production and conversion; D, Cell cycle control, mitosis and meiosis; E, Amino acid transport and metabolism; F, Nucleotide transport and metabolism; G, Carbohydrate transport and metabolism; H, Coenzyme transport and metabolism; I, Lipid transport and metabolism; J, Translation; K, Transcription; L, Replication, recombination and repair; M, Cell wall/membrane biogenesis; N, Cell motility; O, Posttranslational modification, protein turnover, chaperones; P, Inorganic ion transport and metabolism; Q, Secondary metabolites biosynthesis, transport and catabolism; R, General function prediction only; S, Function unknown; T, Signal transduction mechanisms; U, Intracellular trafficking and secretion; V, Defense mechanisms; X, Not in COGs.

    In line with these transcriptomic differences, both strains also showed marked differences in their in vitro infectivity and in serum resistance. These data suggest that differences in the expression of metabolic genes might contribute to virulence differences among meningococcal strains at least in vitro.

    However, to understand how N. meningitidis adapts during interaction with the host it is necessary to study the gene expression of the bacterium under conditions that approximate the human niches it encounters in vivo. Due to the lack of appropriate animal models as mentioned above this justifies the use of an experimental system that mimics, as closely as possible, the in vivo situation seen during disease. Human whole blood, saliva and CSF have already been used as ex vivo models for the study of infection processes in a number of important bacterial pathogens including N. meningitidis.

    Recent whole-transcriptome comparisons of a carriage and an invasive strain under in vivo mimicking conditions in our group again revealed large differences in the regulation of numerous metabolic genes from the meningococcal core genome. In particular, meningococcal survival in whole blood which is crucial for causing invasive diseases seems to be linked to the bacterial metabolic status via the stringent response. Accordingly, we currently analyse the meningococcal stringent response pathway and its contribution to blood stream survival of bacterial cells, and try to characterize the regulons found to be differentially regulated under ex vivo conditions in a carriage and an invasive strain.

    The results of these analyses will allow for a better understanding of how meningococci adapt to changing environments and evade host immune responses during the transition from colonization to an invasive infection.

    Relevant recent publications:

    Joseph, B., M. Frosch, C. Schoen and A. Schubert-Unkmeir (2011) Transcriptome analyses in the interaction of Neisseria meningitidis with mammalian host cells Methods Mol Biol in press

    Joseph, B., S. Schneiker-Bekel, A. Schramm-Glück, J. Blom, H. Claus, B. Linke, R. Schwarz, A. Becker, A. Goesmann, M. Frosch and C. Schoen (2010) Comparative genome biology of a serogroup B carriage and disease strain supports a polygenic nature of meningococcal virulence. J Bacteriol 192:5363-77


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