A toxin-antitoxin module as a target for antimicrobial development.

The emergence and spread of pathogenic bacteria that have become resistant to multiple antibiotics through lateral gene transfer have created the need of novel antimicrobials. Toxin-antitoxin (TA) modules, which have been implicated in plasmid maintenance and stress management, are ubiquitous among plasmids from vancomycin or methicillin resistant bacteria. In the Streptococcus pyogenes pSM19035-encoded TA loci, the labile epsilon antitoxin binds to free zeta toxin and neutralizes it. When the zeta toxin is freed from the epsilon antitoxin, it induces a reversible state of growth arrest with a drastic reduction on the rate of replication, transcription and translation. However, upon prolonged zeta toxin action, the cells can no longer be rescued from their stasis state. A compound that disrupts the epsilon.zeta interaction can be considered as an attractive antimicrobial agent. Gene epsilon was fused to luc (Luc-epsilon antitoxin) and zeta to the gfp gene (zeta-GFP). Luc-epsilon or epsilon antitoxin neutralizes the toxic effect of the zeta or zeta-GFP toxin. In the absence of the antitoxin, free zeta or zeta-GFP triggers a reversible loss of cell proliferation, but the zetaK46A-GFP variant fails to block growth. Bioluminescence resonance energy transfer (BRET) assay was developed for high-throughput screening (HTS). To develop the proper controls, molecular dynamics studies were used to predict that the Asp18 and/or Glu22 residues might be relevant for epsilon.zeta interaction. Luc-epsilon efficiently transfers the excited energy to the fluorescent acceptor molecule (zeta-GFP or zetaK46A-GFP) and rendered high bioluminescence BRET signals. The exchange of Asp18 to Ala from zeta (D18A) affects Luc-epsilon.zetaD18A K46A-GFP interaction. In this study, we validate the hypothesis that it is possible to disrupt a TA module and offer a novel and unexploited targets to fight against antibiotic-resistant strains.

Effect of aza substitution on the photophysical and electrochemical properties of porphycenes: Characterization of the near-IR-absorbing photosensitizers 2,7,12,17-tetrakis(p-substituted phenyl)-3,6,13,16-tetraazaporphycenes.

The need for new photodynamic-therapy photosensitizers has stimulated the search of new families of compounds absorbing strongly in the 700-900 nm range, the region where tissue is most transparent to radiation capable to induce the photodynamic effect. Using computational chemistry techniques, 3,6,13,16-tetraazaporphycenes were previously identified as interesting target candidates. This work reports on the photophysical and electrochemical properties of selected members of this new family of macrocycles. Compared to porphycenes, the tetra-aza counterparts show stronger absorption in the near-infrared, lower-lying singlet and triplet excited states, and substantially larger internal conversion quantum yield (Phi(IC) = 0.93). Energy transfer to oxygen is observed, which results in the formation of the cytotoxic species singlet oxygen. The process is found to be reversible, consistent with a triplet-energy value close to that of singlet oxygen.

Simulation of local and global atrophy in Alzheimer's disease studies.

We propose a method for atrophy simulation in structural MR images based on finite-element methods, providing data for objective evaluation of atrophy measurement techniques. The modelling of diffuse global and regional atrophy is based on volumetric measurements from patients with known disease and guided by clinical knowledge of the relative pathological involvement of regions. The consequent biomechanical readjustment of structures is modelled using conventional physics-based techniques based on tissue properties and simulating plausible deformations with finite-element methods. Tissue characterization is performed by means of the meshing of a labelled brain atlas, creating a reference volumetric mesh, and a partial volume tissue model is used to reduce the impact of the mesh discretization. An example of simulated data is shown and a visual evaluation protocol used by experts has been developed to assess the degree of realism of the simulated images. First results demonstrate the potential of the proposed methodology.

Simulation of acquisition artefacts in MR scans: effects on automatic measures of brain atrophy.

Automatic algorithms in conjunction with longitudinal MR brain images can be used to measure cerebral atrophy, which is particularly pronounced in several types of dementia. An atrophy simulation technique has been devised to facilitate validation of these algorithms. To make this model of atrophy more realistic we simulate acquisition artefacts which are common problems in dementia imaging: motion (both step and periodic motion) and pulsatile flow artefact. Artefacts were simulated by combining different portions of k-space from various modified image. The original images were 7 MR scans of healthy elderly controls, each of which had two levels of simulated atrophy. We investigate the effect of the simulated acquisition artefacts in atrophy measurements provided by an automatic technique, SIENA.

An inverse problem approach to the estimation of volume change.

We present a new technique for determining structure-by-structure volume changes, using an inverse problem approach. Given a pre-labelled brain and a series of images at different time-points, we generate finite element meshes from the image data, with volume change modelled by means of an unknown coefficient of expansion on a per-structure basis. We can then determine the volume change in each structure of interest using inverse problem optimization techniques. The proposed method has been tested with simulated and clinical data. Results suggest that the presented technique can be seen as an alternative for volume change estimation.