Messing with bacterial quorum sensing.

Quorum sensing is widely recognized as an efficient mechanism to regulate expression of specific genes responsible for communal behavior in bacteria. Several bacterial phenotypes essential for the successful establishment of symbiotic, pathogenic, or commensal relationships with eukaryotic hosts, including motility, exopolysaccharide production, biofilm formation, and toxin production, are often regulated by quorum sensing. Interestingly, eukaryotes produce quorum-sensing-interfering (QSI) compounds that have a positive or negative influence on the bacterial signaling network. This eukaryotic interference could result in further fine-tuning of bacterial quorum sensing. Furthermore, recent work involving the synthesis of structural homologs to the various quorum-sensing signal molecules has resulted in the development of additional QSI compounds that could be used to control pathogenic bacteria. The creation of transgenic plants that express bacterial quorum-sensing genes is yet another strategy to interfere with bacterial behavior. Further investigation on the manipulation of quorum-sensing systems could provide us with powerful tools against harmful bacteria.     

Phenol: a complex chemoeffector in bacterial chemotaxis.

Earlier observations that phenol is a repellent for Salmonella typhimurium but an attractant for Escherichia coli were confirmed. This behavioral difference was found to correlate with a difference in the effect phenol had on receptor methylation levels; it caused net demethylation in S. typhimurium but net methylation in E. coli. On the basis of mutant behavior and measurement of phenol-stimulated methylation, the attractant response of E. coli was shown to be mediated principally by the Tar receptor. In S. typhimurium, two receptors were found to be sensitive to phenol, namely, an unidentified receptor, which mediated the repellent response and showed phenol-stimulated demethylation; and the Tar receptor, which (as with E. coli) mediated the attractant response and showed phenol-stimulated methylation. In wild-type S. typhimurium, the former receptor dominated the Tar receptor, with respect to both behavior and methylation changes. However, when the amount of Tar receptor was artificially increased by the use of Tar-encoding plasmids, S. typhimurium cells exhibited an attractant response to phenol. No protein analogous to the phenol-specific repellent receptor was evident in E. coli, explaining the different behavioral responses of the two species toward phenol.     

Plant responses to bacterial quorum sensing signals

Bacterial infection of plants often depends on the exchange of quorum sensing signals between nearby bacterial cells. It is now evident that plants, in turn, 'listen' to these bacterial signals and respond in sophisticated ways to the information. Plants also secrete compounds that mimic the bacterial signals and thereby confuse quorum sensing regulation in bacteria.     

GTPase activity of a bacterial SRP-like complex.

We have recently identified a protein (SRPM54) in Mycoplasma mycoides homologous to SRP54, a subunit of the mammalian signal recognition particle (SRP). This protein forms a complex with a mycoplasma RNA related to the RNA component of SRP. We have now demonstrated that the protein has an intrinsic GTPase activity in vitro and kinetic parameters for the enzymatic reaction have been determined. The GTPase activity was not significantly affected by the presence of the mycoplasma SRP RNA. Different regions of the SRPM54 protein were expressed as recombinant proteins in E. coli and were purified to near homogeneity. On the basis of the properties of these SRPM54 fragments two different functional domains of the protein could be distinguished. An N-terminal part was found to contain the GTPase activity and this domain had approximately the same kinetic properties as the full-length protein. Another domain corresponding to a C-terminal fragment contained the RNA binding activity as shown using an assay based on the retention of RNA-protein complexes to nitrocellulose filters.     

Response regulator output in bacterial chemotaxis.

Chemotaxis responses in Escherichia coli are mediated by the phosphorylated response-regulator protein P-CheY. Biochemical and genetic studies have established the mechanisms by which the various components of the chemotaxis system, the membrane receptors and Che proteins function to modulate levels of CheY phosphorylation. Detailed models have been formulated to explain chemotaxis sensing in quantitative terms; however, the models cannot be adequately tested without knowledge of the quantitative relationship between P-CheY and bacterial swimming behavior. A computerized image analysis system was developed to collect extensive statistics on freeswimming and individual tethered cells. P-CheY levels were systematically varied by controlled expression of CheY in an E.coli strain lacking the CheY phosphatase, CheZ, and the receptor demethylating enzyme CheB. Tumbling frequency was found to vary with P-CheY concentration in a weakly sigmoidal fashion (apparent Hill coefficient approximately 2.5). This indicates that the high sensitivity of the chemotaxis system is not derived from highly cooperative interactions between P-CheY and the flagellar motor, but rather depends on nonlinear effects within the chemotaxis signal transduction network. The complex relationship between single flagella rotation and free-swimming behavior was examined; our results indicate that there is an additional level of information processing associated with interactions between the individual flagella. An allosteric model of the motor switching process is proposed which gives a good fit to the observed switching induced by P-CheY. Thus the level of intracellular P-CheY can be estimated from behavior determinations: approximately 30% of the intracellular pool of CheY appears to be phosphorylated in fully adapted wild-type cells.     

Identification of the tip-encoded receptor in bacterial sensing.

Relaxation of titratable supercoils in bacterial nucleoids was measured following treatment of topA mutants with coumermycin or oxolinic acid, inhibitors of DNA gyrase. Relaxation occurred after treatment of the mutants with either inhibitor. We detected no significant difference in relaxation between topA- and topA+ strains treated with coumermycin. This finding, together with previous observations, supports the idea that relaxation caused by coumermycin probably arises from the relaxing activity of gyrase itself. The source of DNA relaxation caused by oxolinic acid was not identified. Nucleoid supercoiling can be increased by adding oxolinic acid to a strain that carries three topoisomerase mutations: delta topA, gyrB225, and gyrA (Nalr) (S. H. Manes, G. J. Pruss, and K. Drlica, J. Bacteriol. 155:420-423, 1983). We found that this increase in supercoiling requires partial sensitivity to the drug and at the delta topA and gyrA mutations. Full resistance to oxolinic acid in the presence of the delta topA, gyrB225, and gyrA mutations was conferred by an additional mutation that maps at or near gyrB.     

Protonmotive force and bacterial sensing

The role of the proton gradient and external pH in the motility and chemotaxis of Bacillus subtilis was investigated. Presence of a substantial proton gradient is not necessary for motility or chemotaxis, as long as the electrical potential is sufficient to maintain motility. Changes in the proton gradient do, however, lead to changes in swimming behavior, and these changes are mediated by two processes. One is sensitive to external pH and probably operates through a pH receptor. The second is sensitive to changes in the proton gradient. When the level of the protonmotive force is high enough to maintain motiligy, changes in the components of the protonmotive force are sensed by the bacteria and lead to behavioral changes, but changes in the protonmotive force are not necessary for chemotaxis.     

Identification of a bacterial sensing protein and effects of its elevated expression.

The Escherichia coli flaA gene product (also called cheC) plays a crucial role in switching flagellar rotational direction during chemotactic responses. Wild-type and mutant alleles have been cloned onto plasmid vectors, and the gene product has been identified as a 37,000-dalton protein. The flaA product appeared as a soluble protein in the cytoplasm when overproduced in minicells and maxicells. The protein could not be detected in flagellar basal structures purified from a wild-type strain. To assess the effects of altered flaA expression, the gene was fused to a synthetic tac promoter that could be regulated by the addition of an inducer. Overproduction resulted in strong counterclockwise flagellar rotational bias and partial paralysis of flagellar motors. These results suggest that the flaA protein provides the interface between the flagellar machinery and the chemotaxis signaling system in a motor structure external to the basal body.     

Quorum sensing and bacterial cross-talk in biotechnology

Only a decade ago, the secretion and perception of small signalling molecules that in turn are transduced to coordinate behaviour of a 'minimal unit' of microorganisms was termed quorum sensing by EP Greenberg and colleagues. Since then, an explosion (or exponential growth) in understanding and prevalence of quorum-sensing systems has ensued, with sightings ranging from virulence in human and plant pathogens to degradative capacity of activated sludge. Not surprisingly, regulatory mechanisms span traditional inducer/repressor motifs homologous to the lac operon to the recently discovered interfering RNAs. Further characterisation of signalling circuits, coupled with creative niche applications, suggest a wealth of opportunity for advancing commercial biotechnology.     

A mathematical model of quorum sensing in a growing bacterial biofilm

In a process called quorum sensing, bacteria monitor their population density via extracellular signaling molecules and modulate gene expression accordingly. This paper describes a one-dimensional model of a growing Pseudomonas aeruginosa biofilm. Quorum sensing has been included in the model by the addition of equations describing the production, degradation, and diffusion of acyl-homoserine lactones in the biofilm. In order for quorum sensing to initiate near the substratum, in accordance with experimental observations, model results suggest that cells in oxygen-deficient regions of the biofilm must still be synthesizing the signal compound. This result highlights the importance of careful study of the relationship between metabolic activity of the bacterium and signal synthesis. Received 11 March 2002/ Accepted in revised form 01 August 2002     

Response regulation in bacterial chemotaxis

The signal transduction system that mediates bacterial chemotaxis allows cells to moduate their swimming behavior in response to fluctuations in chemical stimuli. Receptors at the cell surface receive information from the surroundings. Signals are then passed from the receptors to cytoplasmic chemotaxis components: CheA, CheW, CheZ, CheR, and CheB. These proteins function to regulate the level of phosphorylation of a response regulator designated CheY that interacts with the flagellar motor switch complex to control swimming behavior. The structure of CheY has been determined. Magnesium ion is essential for activity. The active site contains highly conserved Asp residues that are required for divalent metal ion binding and CheY phosphorylation. Another residue-at the active site, Lys109, is important in the phosphorylation-induced conformational change that facilitates communication with the switch complex and another chemotaxis component, CheZ. CheZ facilitates the dephosphorylation of phospho-CheY. Defects in CheY and CheZ can be suppressed by mutations in the flagellar switch complex. CheZ is thought to modulate the switch bias by varying the level of phospho-CheY. © 1993 Wiley-Liss, Inc.     

A cyanide-aldehyde complex inhibits bacterial luciferase.

Cyanide at high (millimolar) concentrations inhibited in the in vitro Vibrio harveyi luciferase reaction. Cyanide reacted with free aldehyde to form an inhibitor. Inhibitor formation was accelerated by alkaline conditions and bovine serum albumin.     

细菌群体感应的蛋白质组学研究进展

细菌群体感应是指细菌能合成、释放和感应一些类激素小分子信号,从而调控群体行为并对其作出应答反应。介导细菌群体感应的信号分子有多种,它们参与调节细菌许多重要生物学功能。目前对此研究的主要手段是基因组学和转录组学。然而近年来,基因组测序技术的不断发展为另一种新兴方法——以比较和功能性为基础的蛋白质组学法奠定了基础。所不同的是,传统方法只能局限性研究某些基因或蛋白,而蛋白质组学法能检测出生物体基因表达的全部蛋白,它也因此逐渐受到人们的广泛关注。主要从研究较多的三类信号分子方面描述如何利用蛋白盾组举法解析细菌交流的“语言”。     

Early development and quorum sensing in bacterial biofilms

 We develop mathematical models to examine the formation, growth and quorum sensing activity of bacterial biofilms. The growth aspects of the model are based on the assumption of a continuum of bacterial cells whose growth generates movement, within the developing biofilm, described by a velocity field. A model proposed in Ward et al. (2001) to describe quorum sensing, a process by which bacteria monitor their own population density by the use of quorum sensing molecules (QSMs), is coupled with the growth model. The resulting system of nonlinear partial differential equations is solved numerically, revealing results which are qualitatively consistent with experimental ones. Analytical solutions derived by assuming uniform initial conditions demonstrate that, for large time, a biofilm grows algebraically with time; criteria for linear growth of the biofilm biomass, consistent with experimental data, are established. The analysis reveals, for a biologically realistic limit, the existence of a bifurcation between non-active and active quorum sensing in the biofilm. The model also predicts that travelling waves of quorum sensing behaviour can occur within a certain time frame; while the travelling wave analysis reveals a range of possible travelling wave speeds, numerical solutions suggest that the minimum wave speed, determined by linearisation, is realised for a wide class of initial conditions. Received: 10 February 2002 / Revised version: 29 October 2002 / Published online: 19 March 2003 Key words or phrases: Bacterial biofilm – Quorum sensing – Mathematical modelling – Numerical solution – Asymptotic analysis – Travelling wave analysis     

Quorum sensing and DNA release in bacterial biofilms

The multicellular behavior of bacteria has been the subject of much recent interest. This behavior includes coordinated control of virulence, luminescence, competence and biofilm formation; each of these appears to be regulated or influenced by quorum sensing. An understanding of what biofilms constitute, and how they develop, is emerging. It is clear that biofilm formation is a carefully orchestrated process that is dependent on quorum sensing. Somewhat surprisingly, several independent observations have noted an important role for DNA in the structure of biofilms. Recent studies describe a mechanism for linking DNA release to quorum sensing, providing a possible mechanism for the coordinated release of DNA, and its integration into a biofilm. A review of the literature reveals that similar observations have been made for biofilms of both Gram-positive and Gram-negative organisms. Further study will determine whether this is a general trend, however.     

Computer analysis of the binding reactions leading to a transmembrane receptor-linked multiprotein complex involved in bacterial chemotaxis.

The chemotactic response of bacteria is mediated by complexes containing two molecules each of a transmembrane receptor and the intracellular signaling proteins CheA and CheW. Mutants in which one or the other of the proteins of this complex are absent, inactive, or expressed at elevated amounts show altered chemotactic behavior and the phenotypes are difficult to interpret for some overexpression mutants. We have examined the possibility that these unexpected phenotypes might arise from the binding steps that lead to active complex formation. A limited genetic algorithm was used to search for sets of binding reactions and associated binding constants expected to give mutant phenotypes in accord with experimental data. Different sets of binding equilibria and different assumptions about the activity of particular receptor complexes were tried. Computer analysis demonstrated that it is possible to obtain sets of binding equilibria consistent with the observed phenotypes and provided a simple explanation for these phenotypes in terms of the distribution of active and inactive complexes formed under various conditions. Optimization methods of this kind offer a unique way to analyze reactions taking place inside living cells based on behavioral data.