Modulation of cell surface sialic acid expression in Neisseria meningitidis via a transposable genetic element.

Hammerschmidt, Sven; Hilse, R.; Putten, J. P. M. Van; Gerardy‐Schahn, Rita; Unkmeir, Alexandra; Frosch, Matthias

doi:10.1002/j.1460-2075.1996.tb00347.x

Cited by 196 publications

(192 citation statements)

References 31 publications

(39 reference statements)

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“…Phase variation between capsular and acapsular states is postulated as a necessary step in meningococcal persistence and virulence (59). One mechanism controlling this phase variation is transposition of an insertion element into the genes for PSA expression (58). However, a more common mechanism appears to be slipped-strand mispairing in a poly(dC) tract of the capsule polymerase gene, siaD, causing premature translational arrest coupled with Rho-dependent termination (78).…”

Section: Meningococcal Psa Phase Variation and Los Sialylationmentioning

confidence: 99%

Diversity of Microbial Sialic Acid Metabolism

Vimr

Kalivoda

Deszo

et al. 2004

Microbiol Mol Biol Rev

505

663

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Sialic acids are structurally unique nine-carbon keto sugars occupying the interface between the host and commensal or pathogenic microorganisms. An important function of host sialic acid is to regulate innate immunity, and microbes have evolved various strategies for subverting this process by decorating their surfaces with sialylated oligosaccharides that mimic those of the host. These subversive strategies include a de novo synthetic pathway and at least two truncated pathways that depend on scavenging host-derived intermediates. A fourth strategy involves modification of sialidases so that instead of transferring sialic acid to water (hydrolysis), a second active site is created for binding alternative acceptors. Sialic acids also are excellent sources of carbon, nitrogen, energy, and precursors of cell wall biosynthesis. The catabolic strategies for exploiting host sialic acids as nutritional sources are as diverse as the biosynthetic mechanisms, including examples of horizontal gene transfer and multiple transport systems. Finally, as compounds coating the surfaces of virtually every vertebrate cell, sialic acids provide information about the host environment that, at least in Escherichia coli, is interpreted by the global regulator encoded by nanR. In addition to regulating the catabolism of sialic acids through the nan operon, NanR controls at least two other operons of unknown function and appears to participate in the regulation of type 1 fimbrial phase variation. Sialic acid is, therefore, a host molecule to be copied (molecular mimicry), eaten (nutrition), and interpreted (cell signaling) by diverse metabolic machinery in all major groups of mammalian pathogens and commensals

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Section: Meningococcal Psa Phase Variation and Los Sialylationmentioning

confidence: 99%

Diversity of Microbial Sialic Acid Metabolism

Vimr

Kalivoda

Deszo

et al. 2004

Microbiol Mol Biol Rev

505

663

View full text Add to dashboard Cite

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“…The meningococcal capsule is another major surface structure that could hinder intimate contact between Nm and target cells (Virji et al, 1992;de Vries et al, 1996;Hammerschmidt et al, 1996;Hardy et al, 2000). We have previously reported that capsule levels decrease upon cell contact (Deghmane et al, 2000).…”

Section: Modulation Of Capsule and Pili During Adhesion Of Meningococmentioning

confidence: 99%

“…crgA encodes a transcriptional regulator of the LysR family and seems to be involved in the adhesion of Nm to target cells because insertional inactivation of this gene strongly decreases meningococcal adhesion to epithelial cells, particularly during the phase of Nm-cell intimate adhesion (Deghmane et al, 2000). CrgA may be involved in the switch from initial adhesion to intimate adhesion by downregulating bacterial surface structures that hinder intimate adhesion, such as the pili and capsule (Virji et al, 1992;Hammerschmidt et al, 1996;de Vries et al, 1996;Hardy et al, 2000). The aim of this work was to investigate this hypothesis by analysing the effects of CrgA on the production of pili and capsule during interaction between bacteria and cells.…”

Section: Introductionmentioning

confidence: 99%

Down‐regulation of pili and capsule of Neisseria meningitidis upon contact with epithelial cells is mediated by CrgA regulatory protein

Deghmane¹,

Giorgini²,

Larribe³

et al. 2002

Molecular Microbiology

131

146

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SummaryThe initial attachment of Neisseria meningitidis to the target cell surface appears to be largely pilus dependent in capsulated bacteria. Intimate adhesion subsequently occurs to permit colonization. We recently reported that insertional inactivation of the crgA gene, which encodes a transcriptional regulator belonging to the LysR family, decreased meningococcal adhesion to epithelial cells and abolished intimate adhesion. In this report, we analyse expression of the pilE and sia genes, which are involved in the biosynthesis of pili and capsule respectively, during bacteria-host cell interactions. Western blotting, transcriptional fusion and reverse transcriptase polymerase chain reaction (RT-PCR) analysis showed that the expression of these genes was downregulated during intimate adhesion. DNA-binding assays, footprinting and RT-PCR analysis indicated that this downregulation was directly mediated by the CrgA protein. The pilE and sia promoters were found to have a CrgA binding motif in common. These results strongly suggest that N. meningitidis displays an adaptive response upon cell contact. CrgA may play a central regulatory role in meningococcal adhesion, particularly in switching from initial to intimate adhesion by downregulating the bacterial surface structures that hinder this adhesion.

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“…Other papers, even ones cited for their methods of rate determination (e.g. Hammerschmidt et al, 1996, cited by Bucci et al, 1999), are not explicit about essential steps in the estimation process. These examples serve to illustrate common problems with this type of study.…”

Section: Introductionmentioning

confidence: 99%

Mutation rates: estimating phase variation rates when fitness differences are present and their impact on population structure

2003

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Phase variation is a mechanism of ON-OFF switching that is widely utilized by bacterial pathogens. There is currently no standardization to how the rate of phase variation is determined experimentally, and traditional methods of mutation rate estimation may not be appropriate to this process. Here, the history of mutation rate estimation is reviewed, describing the existing methods available. A new mathematical model that can be applied to this problem is also presented. This model specifically includes the confounding factors of back-mutation and the influence of fitness differences between the alternate phenotypes. These are central features of phase variation but are rarely addressed, with the result that some previously estimated phase variation rates may have been significantly overestimated. It is shown that, conversely, the model can also be used to investigate fitness differences if mutation rates are approximately known. In addition, stochastic simulations of the model are used to explore the impact of 'jackpot cultures' on the mutation rate estimation. Using the model, the impact of realistic rates and selection on population structure is investigated. In the absence of fitness differences it is predicted that there will be phenotypic stability over many generations. The rate of phenotypic change within a population is likely, therefore, to be principally determined by selection. A greater insight into the population dynamics of mutation rate processes can be gained if populations are monitored over successive time points. INTRODUCTIONPhase variation describes a process of reversible, highfrequency phenotypic switching that is mediated by DNA mutations, reorganization or modification. Phase variation is used by several bacterial species to generate population diversity that increases bacterial fitness and is important in niche adaptation including immune evasion (Saunders, 2003; Salaün et al., 2003). Being able to determine the rate at which these processes occur and the nature of any factors that influence them is integral to understanding the impact of these processes on the evolution and dynamics of the population as a whole and on the host-bacterium interaction. To do this, tools with which to reliably determine and compare phase variation rates within and between experiments and bacterial populations are needed. The estimation of mutation rates in bacteria has a long history. The methods in use, however, are not general across all systems and it is important that the assumptions behind the methods are recognized. Here, we present a new mathematical model that can be used to estimate phase variation rates in the presence of fitness differences, and explore the impact of proposed rates on population structure over time. It is also timely to compare and contrast some of the many different methods and terminology in this field. To put our approach in context, we begin with a brief review of the previous work in this field.

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Modulation of cell surface sialic acid expression in Neisseria meningitidis via a transposable genetic element.

Cited by 196 publications

References 31 publications

Diversity of Microbial Sialic Acid Metabolism

Diversity of Microbial Sialic Acid Metabolism

Down‐regulation of pili and capsule of Neisseria meningitidis upon contact with epithelial cells is mediated by CrgA regulatory protein

Mutation rates: estimating phase variation rates when fitness differences are present and their impact on population structure

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