Trehalose-6-phosphate-mediated phenotypic change in Acinetobacter baumannii

The stress protectant trehalose is synthesized in Acinetobacter baumannii from UPD-glucose and glucose-6-phosphase via the OtsA/OtsB pathway. Previous studies proved that deletion of otsB led to a decreased virulence, the inability to grow at 45°C and a slight reduction of growth at high salinities indicating that trehalose is the cause of these phenotypes. We have questioned this conclusion by producing ∆otsA and ∆otsBA mutants and studying their phenotypes. Only deletion of otsB, but not deletion of otsA or otsBA, led to growth impairments at high salt and high temperature. The intracellular concentrations of trehalose and trehalose-6-phosphate were measured by NMR or enzymatic assay. Interestingly, none of the mutants accumulated trehalose any more but the ∆otsB mutant with its defect in trehalose-6-phosphate phosphatase activity accumulated trehalose-6-phosphate. Moreover, expression of otsA in a ∆otsB background under conditions where trehalose synthesis is not induced led to growth inhibition and the accumulation of trehalose-6-phosphate. Our results demonstrate that trehalose-6-phosphate affects multiple physiological activities in A. baumannii ATCC 19606.     

Molecular docking analysis of beta-catenin with compounds derived from Lycopersicon esculentum

Beta-catenin is linked with colorectal cancer (CRC). Therefore, it is of interest to design and develop novel compounds to combat CRC. Hence, we document compounds (chlorogenic acid, gallic acid, protocatechuic acid, quercetin and vanillic acid) from Lycopersicon esculentum with optimal binding features for further consideration.     

Using Manifold Learning for Atlas Selection in Multi-Atlas Segmentation

Multi-atlas segmentation has been widely used to segment various anatomical structures. The success of this technique partly relies on the selection of atlases that are best mapped to a new target image after registration. Recently, manifold learning has been proposed as a method for atlas selection. Each manifold learning technique seeks to optimize a unique objective function. Therefore, different techniques produce different embeddings even when applied to the same data set. Previous studies used a single technique in their method and gave no reason for the choice of the manifold learning technique employed nor the theoretical grounds for the choice of the manifold parameters. In this study, we compare side-by-side the results given by 3 manifold learning techniques (Isomap, Laplacian Eigenmaps and Locally Linear Embedding) on the same data set. We assess the ability of those 3 different techniques to select the best atlases to combine in the framework of multi-atlas segmentation. First, a leave-one-out experiment is used to optimize our method on a set of 110 manually segmented atlases of hippocampi and find the manifold learning technique and associated manifold parameters that give the best segmentation accuracy. Then, the optimal parameters are used to automatically segment 30 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For our dataset, the selection of atlases with Locally Linear Embedding gives the best results. Our findings show that selection of atlases with manifold learning leads to segmentation accuracy close to or significantly higher than the state-of-the-art method and that accuracy can be increased by fine tuning the manifold learning process.     

Engineering of a target site-specific recombinase by a combined evolution- and structure-guided approach

Site-specific recombinases (SSRs) can perform DNA rearrangements, including deletions, inversions and translocations when their naive target sequences are placed strategically into the genome of an organism. Hence, in order to employ SSRs in heterologous hosts, their target sites have to be introduced into the genome of an organism before the enzyme can be practically employed. Engineered SSRs hold great promise for biotechnology and advanced biomedical applications, as they promise to extend the usefulness of SSRs to allow efficient and specific recombination of pre-existing, natural genomic sequences. However, the generation of enzymes with desired properties remains challenging. Here, we use substrate-linked directed evolution in combination with molecular modeling to rationally engineer an efficient and specific recombinase (sTre) that readily and specifically recombines a sequence present in the HIV-1 genome. We elucidate the role of key residues implicated in the molecular recognition mechanism and we present a rationale for sTre’s enhanced specificity. Combining evolutionary and rational approaches should help in accelerating the generation of enzymes with desired properties for use in biotechnology and biomedicine.     

Synthesis,characterization and in vitro activity of a surface-attached antimicrobial cationic peptide

Infection associated with implanted biomaterials is common and costly and such infections are extremely resistant to antibiotics and host defenses. Consequently, there is a need to develop surfaces which resist bacterial adhesion and colonization. The broad spectrum synthetic cationic peptide melimine has been covalently linked to a surface via two azide linkers, 4-azidobenzoic acid (ABA) or 4-fluoro-3-nitrophenyl azide (FNA), and the resulting surfaces characterized by X-ray photoelectron spectroscopy and contact angle measurements. The quantity of bound peptide was estimated by a modified Bradford assay. The antimicrobial efficacy of the two melimine-modified surfaces against Pseudomonas aeruginosa and Staphylococcus aureus was compared by scanning electron microscopy (SEM) and fluorescence microscopy. Attachment of melimine via ABA gave an approximately 4-fold greater quantity of melimine bound to the surface than attachment via FNA. Surfaces melimine-modified by either attachment strategy showed significantly reduced bacterial adhesion for both strains of bacteria. P. aeruginosa exposed to ABA–melimine and FNA–melimine surfaces showed marked changes in cell morphology when observed by SEM and a reduction of approximately 15-fold (p < 0.001) in the numbers of adherent bacteria compared to controls. For the ABA–melimine surface there was a 33% increase in cells showing damaged membranes (p = 0.0016) while for FNA–melimine there was no significant difference. For S. aureus there were reductions in bacterial adhesion of approximately 40-fold (p < 0.0001) and 5-fold (p = 0.008) for surfaces modified with melimine via ABA or FNA, respectively. There was an increase in cells showing damaged membranes on ABA–melimine surfaces of approximately 87% (p = 0.001) compared to controls, while for FNA–melimine there was no significant difference observed. The data presented in this study show that melimine has excellent potential for development as a broad spectrum antimicrobial coating for biomaterial surfaces. Further, it was observed that the efficacy of antimicrobial activity is related to the method of attachment.