Additional role for the ccd operon of F-plasmid as a transmissible persistence factor

Toxin-antitoxin (TA) systems are found on both bacterial plasmids and chromosomes, but in most cases their functional role is unclear. Gene knockouts often yield limited insights into functions of individual TA systems because of their redundancy. The well-characterized F-plasmid-based CcdAB TA system is important for F-plasmid maintenance. We have isolated several point mutants of the toxin CcdB that fail to bind to its cellular target, DNA gyrase, but retain binding to the antitoxin, CcdA. Expression of such mutants is shown to result in release of the WT toxin from a functional preexisting TA complex as well as derepression of the TA operon. One such inactive, active-site mutant of CcdB was used to demonstrate the contribution of CcdB to antibiotic persistence. Transient activation of WT CcdB either by coexpression of the mutant or by antibiotic/heat stress was shown to enhance the generation of drug-tolerant persisters in a process dependent on Lon protease and RecA. An F-plasmid containing a ccd locus can, therefore, function as a transmissible persistence factor.

MazF-induced Growth Inhibition and Persister Generation in Escherichia coli

Background: MazEF is a chromosomally encoded bacterial toxin-antitoxin system whose cellular role is controversial. Results: Expression of chromosomal MazF inhibits cell killing by multiple antibiotics in a Lon and ClpP dependent manner. Conclusion: MazF is involved in reversible growth inhibition and bacterial drug tolerance. Significance: Inactive, active-site toxin mutants yield functional insights by selectively activating the corresponding WT toxin in vivo. Toxin-antitoxin systems are ubiquitous in nature and present on the chromosomes of both bacteria and archaea. MazEF is a type II toxin-antitoxin system present on the chromosome of Escherichia coli and other bacteria. Whether MazEF is involved in programmed cell death or reversible growth inhibition and bacterial persistence is a matter of debate. In the present work the role of MazF in bacterial physiology was studied by using an inactive, active-site mutant of MazF, E24A, to activate WT MazF expression from its own promoter. The ectopic expression of E24A MazF in a strain containing WT mazEF resulted in reversible growth arrest. Normal growth resumed on inhibiting the expression of E24A MazF. MazF-mediated growth arrest resulted in an increase in survival of bacterial cells during antibiotic stress. This was studied by activation of mazEF either by overexpression of an inactive, active-site mutant or pre-exposure to a sublethal dose of antibiotic. The MazF-mediated persistence phenotype was found to be independent of RecA and dependent on the presence of the ClpP and Lon proteases. This study confirms the role of MazEF in reversible growth inhibition and persistence.

LiSr1.65 square 0.35B1.3B ' O-1.7(9) (B = Ti, Zr; B ' = Nb, Ta): New lithium ion conductors based on the perovskite structure

We describe the design and synthesis of new lithium ion conductors with the formula, LiSr(1.65)rectangle(0.35)B(1.3)B'O-1.7(9) (rectangle = vacancy; B = Ti, Zr; B' = Nb, Ta), on the basis of a systematic consideration of the composition-structure-property correlations in the well-known lithium-ion conductor, La-(2/3-x)Li(3x)rectangle((1/3)-2x)TiO3 (I), as well as the perovskite oxides in Li-A-B,B'-O (A = Ca, Sr, Ba; B = Ti, Zr; B' = Nb, Ta) systems. A high lithium-ion conductivity of ca. 0.12 S/cm at 360 degrees C is exhibited by LiSr(1.65)rectangle(0.35)Ti(1.3)Ta(1.7)O(9) (III) and LiSr(1.65)rectangle(0.35)Zr(1.3)Ta(1.7)O(9) (IV), of which the latter containing stable Zr(IV) and Ta(V) oxidation states is likely to be a candidate electrolyte material for all-solid-state lithium battery application. More importantly, we believe the approach described here could be extended to synthesize newer, possibly better, lithium ion conductors.

Expression of GC-C, a receptor-guanylate cyclase, and its endogenous ligands uroguanylin and guanylin along the rostrocaudal axis of the intestine

Members of the receptor-guanylate cyclase (rGC) family possess an intracellular catalytic domain that is regulated by an extracellular receptor domain. GC-C, an intestinally expressed rGC, was initially cloned by homology as an orphan receptor. The search for its Ligands has yielded three candidates: STa (a bacterial toxin that causes traveler's diarrhea) and the endogenous peptides uroguanylin and guanylin. Here, by performing Northern and Western blots, and by measuring [I-125]STa binding and STa-dependent elevation of cGMP levels, we investigate whether the distribution of GC-C matches that of its endogenous ligands in the rat intestine. We establish that 1) uroguanylin is essentially restricted to small bowel; 2) guanylin is very low in proximal small bowel, increasing to prominent levels in distal small bowel and throughout colon; 3) GC-C messenger RNA and STa-binding sites are uniformly expressed throughout the intestine; and 4) GC-C-mediated cGMP synthesis peaks at the proximal and distal extremes of the intestine (duodenum and colon), but is nearly absent in the middle (ileum). These observations suggest that GC-C's activity may be posttranslationally regulated, demonstrate that the distribution of GC-C is appropriate to mediate the actions of both uroguanylin and guanylin, and help to refine current hypotheses about the physiological role(s) of these peptides.

Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of similar to 1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (Rank Score), which correlated with the residue depth, and identify active-site residues. Using these correlations, similar to 98% of correct models of CcdB (RMSD <= 4 angstrom) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout.

Intestinal Cell Proliferation and Senescence Are Regulated by Receptor Guanylyl Cyclase C and p21

Guanylyl cyclase C (GC-C) is expressed in intestinal epithelial cells and serves as the receptor for bacterial heat-stable enterotoxin (ST) peptides and the guanylin family of gastrointestinal hormones. Activation of GC-C elevates intracellular cGMP, which modulates intestinal fluid-ion homeostasis and differentiation of enterocytes along the crypt-villus axis. GC-C activity can regulate colonic cell proliferation by inducing cell cycle arrest, and mice lacking GC-C display increased cell proliferation in colonic crypts. Activation of GC-C by administration of ST to wild type, but not Gucy2c(-/-), mice resulted in a reduction in carcinogen-induced aberrant crypt foci formation. In p53-deficient human colorectal carcinoma cells, ST led to a transcriptional up-regulation of p21, the cell cycle inhibitor, via activation of the cGMP-responsive kinase PKGII and p38 MAPK. Prolonged treatment of human colonic carcinoma cells with ST led to nuclear accumulation of p21, resulting in cellular senescence and reduced tumorigenic potential. Our results, therefore, identify downstream effectors for GC-C that contribute to regulating intestinal cell proliferation. Thus, genomic responses to a bacterial toxin can influence intestinal neoplasia and senescence.

Diffusion pattern in MSi2 and M5Si3 silicides in group VB (M = V, Nb, Ta) and VIB (M = Mo, W) refractory metal-silicon systems

Group VB and VIB M-Si systems are considered to show an interesting pattern in the diffusion of components with the change in atomic number in a particular group (M = V, Nb, Ta or M = Mo, W, respectively). Mainly two phases, MSi2 and M5Si3 are considered for this discussion. Except for Ta-silicides, the activation energy for the integrated diffusion of MSi2 is always lower than M5Si3. In both phases, the relative mobilities measured by the ratio of the tracer diffusion coefficients, , decrease with an increasing atomic number in the given group. If determined at the same homologous temperature, the interdiffusion coefficients increase with the atomic number of the refractory metal in the MSi2 phases and decrease in the M5Si3 ones. This behaviour features the basic changes in the defect concentrations on different sublattices with a change in the atomic number of the refractory components.

Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks

Background The genome of a wide variety of prokaryotes contains the luxS gene homologue, which encodes for the protein S-ribosylhomocysteinelyase (LuxS). This protein is responsible for the production of the quorum sensing molecule, AI-2 and has been implicated in a variety of functions such as flagellar motility, metabolic regulation, toxin production and even in pathogenicity. A high structural similarity is present in the LuxS structures determined from a few species. In this study, we have modelled the structures from several other species and have investigated their dimer interfaces. We have attempted to correlate the interface features of LuxS with the phenotypic nature of the organisms. Results The protein structure networks (PSN) are constructed and graph theoretical analysis is performed on the structures obtained from X-ray crystallography and on the modelled ones. The interfaces, which are known to contain the active site, are characterized from the PSNs of these homodimeric proteins. The key features presented by the protein interfaces are investigated for the classification of the proteins in relation to their function. From our analysis, structural interface motifs are identified for each class in our dataset, which showed distinctly different pattern at the interface of LuxS for the probiotics and some extremophiles. Our analysis also reveals potential sites of mutation and geometric patterns at the interface that was not evident from conventional sequence alignment studies. Conclusion The structure network approach employed in this study for the analysis of dimeric interfaces in LuxS has brought out certain structural details at the side-chain interaction level, which were elusive from the conventional structure comparison methods. The results from this study provide a better understanding of the relation between the luxS gene and its functional role in the prokaryotes. This study also makes it possible to explore the potential direction towards the design of inhibitors of LuxS and thus towards a wide range of antimicrobials.

Purification of a bacterial organophosphate-hydrolysing phosphatase by cibacron 3GA-Sepharose affinity chromatography

A phosphatase catalysing the hydrolysis of organophosphorus pesticides was purified to homogeneity using Cibacron 3GA-Sepharose CL 6B affinity chromatography. The enzyme which is localized in the periplasm of the bacterium Image NC5 was extracted by treating with 0.2M MgCl2, pH 8.4. The enzyme was adsorbed to the Cibacron-Sepharose at pH 7.0 and eluted with Tris-HCl buffer at pH 8.0, with 47 per cent recovery. The enzyme thus obtained was electrophoretically homogeneous. This simple affinity purification procedure enhances the potential for its use in large scale detoxification systems.

A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

Systems biology of tuberculosis

Systems biology seeks to study biological systems as a whole, by adopting an integrated approach to study and understand the function of biological systems, particularly, the response of such systems to various perturbations. In this article, we focus on the Indian efforts towards systems-level studies of Mycobacterium tuberculosis and its interaction with the host. Availability of a variety of genome-scale experimental data, providing first level `omics' descriptions of the pathogen, render it feasible to study it at a systems level. Various aspects of the pathogen, from metabolic pathways to protein-protein interaction networks have been modelled and simulated, while host-pathogen interactions have been studied experimentally using siRNA-based techniques. These studies have been useful in obtaining a global perspective of the pathogen and its interactions with the host in many ways. For example, significant insights have been gained about different aspects such as proteins essential for bacterial survival, proteins that are highly influential in the network, pathways that are highly connected, host factors responsible for maintaining the TB infection and key factors involved in autophagy and pathogenesis. A rational pipeline developed for drug target identification incorporating analyses of the interactome, reactome, genome, pocketome and the transcriptome is discussed. Finally, exploring host factors as drug targets and insights about the emergence of drug resistance are also discussed. (C) 2011 Elsevier Ltd. All rights reserved.

Levels of Alpha-Toxin Correlate with Distinct Phenotypic Response Profiles of Blood Mononuclear Cells and with agr Background of Community-Associated Staphylococcus aureus Isolates

Epidemiological studies of Staphylococcus aureus have shown a relation between certain clones and the presence of specific virulence genes, but how this translates into virulence-associated functional responses is not fully elucidated. Here we addressed this issue by analyses of community-acquired S. aureus strains characterized with respect to antibiotic resistance, ST types, agr types, and virulence gene profiles. Supernatants containing exotoxins were prepared from overnight bacterial cultures, and tested in proliferation assays using human peripheral blood mononuclear cells (PBMC). The strains displayed stable phenotypic response profiles, defined by either a proliferative or cytotoxic response. Although, virtually all strains elicited superantigen-mediated proliferative responses, the strains with a cytotoxic profile induced proliferation only in cultures with the most diluted supernatants. This indicated that the superantigen-response was masked by a cytotoxic effect which was also confirmed by flow cytometry analysis. The cytotoxic supernatants contained significantly higher levels of alpha-toxin than did the proliferative supernatants. Addition of alpha-toxin to supernatants characterized as proliferative switched the response into cytotoxic profiles. In contrast, no effect of Panton Valentine Leukocidin, delta-toxin or phenol soluble modulin alpha-3 was noted in the proliferative assay. Furthermore, a significant association between agr type and phenotypic profile was found, where agrII and agrIII strains had predominantly a proliferative profile whereas agrI and IV strains had a predominantly cytotoxic profile. The differential response profiles associated with specific S. aureus strains with varying toxin production could possibly have an impact on disease manifestations, and as such may reflect specific pathotypes.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.