Analysis of the Promoters Involved in Enterocin AS-48 Expression

The enterocin AS-48 is the best characterized antibacterial circular protein in prokaryotes. It is a hydrophobic and cationic bacteriocin, which is ribosomally synthesized by enterococcal cells and post-translationally cyclized by a head-to-tail peptide bond. The production of and immunity towards AS-48 depend upon the coordinated expression of ten genes organized in two operons, as-48ABC (where genes encoding enzymes with processing, secretion, and immunity functions are adjacent to the structural as-48A gene) and as-48C1DD1EFGH. The current study describes the identification of the promoters involved in AS-48 expression. Seven putative promoters have been here amplified, and separately inserted into the promoter-probe vector pTLR1, to create transcriptional fusions with the mCherry gene used as a reporter. The activity of these promoter regions was assessed measuring the expression of the fluorescent mCherry protein using the constitutive pneumococcal promoter PX as a reference. Our results revealed that only three promoters PA, P2(2) and PD1 were recognized in Enterococcus faecalis, Lactococcus lactis and Escherichia coli, in the conditions tested. The maximal fluorescence was obtained with PX in all the strains, followed by the P2(2) promoter, which level of fluorescence was 2-fold compared to PA and 4-fold compared to PD1. Analysis of putative factors influencing the promoter activity in single and double transformants in E. faecalis JH2-2 demonstrated that, in general, a better expression was achieved in presence of pAM401-81. In addition, the P2(2) promoter could be regulated in a negative fashion by genes existing in the native pMB-2 plasmid other than those of the as-48 cluster, while the pH seems to affect differently the as-48 promoter expression.This work was supported in part by the Ministerio de Ciencia e Innovación project BIO2008-01708, the Plan Propio from the University of Granada (Spain) and by the Research Plan Group (BIO 160)

Antibacterial activity and mode of action of selected glucosinolate hydrolysis products against bacterial pathogens

Plants contain numerous components that are important sources of new bioactive molecules with antimicrobial properties. Isothiocyanates (ITCs) are plant secondary metabolites found in cruciferous vegetables that are arising as promising antimicrobial agents in food industry. The aim of this study was to assess the antibacterial activity of two isothiocyanates (ITCs), allylisothiocyanate (AITC) and 2-phenylethylisothiocyanate (PEITC) against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Listeria monocytogenes. The antibacterial mode of action was also characterized by the assessment of different physiological indices: membrane integrity, intracellular potassium release, physicochemical surface properties and surface charge. The minimum inhibitory concentration (MIC) of AITC and PEITC was 100 g/mL for all bacteria. The minimum bactericidal concentration (MBC) of the ITCs was at least 10 times higher than the MIC. Both AITC and PEITC changed the membrane properties of the bacteria decreasing their surface charge and compromising the integrity of the cytoplasmatic membrane with consequent potassium leakage and propidium iodide uptake. The surface hydrophobicity was also non-specifically altered (E. coli and L. monocytogenes become less hydrophilic; P. aeruginosa and S. aureus become more hydrophilic). This study shows that AITC and PEITC have strong antimicrobial potential against the bacteria tested, through the disruption of the bacterial cell membranes. Moreover, phytochemicals are highlighted as a valuable sustainable source of new bioactive products.This work was supported by the Operational Programme for Competitiveness Factors - COMPETE and by the Portuguese Foundation for Science and Technology through Project Phytodisinfectants - PTDC/DTP-SAP/1078/2012 (COMPETE: FCOMP-01-0124-FEDER-028765), the PhD grant awarded to Ana Abreu (SFRH/BD/84393/2012), and the post-doctoral grants awarded to Anabela Borges (SFRH/BPD/98684/2013) and Lucia C. Simoes (SFRH/BPD/81982/2011). Also, this work was undertaken as part of the European Research Project SUSCLEAN (Contract no FP7-KBBE-2011-5, project number: 287514) and the COST Action FA1202. The authors are solely responsible for this work. It does not represent the opinion of the European Community, and the Community is not responsible for any use that might be made of data appearing herein

Advanced Machine Learning Coupled with Heart-Inter-beat derivatives for Cardiac Arrhythmia Detection

International audienceThis paper presents a novel strategy based on derivatives time series and advanced machine learning for medical decision-support especially for cardiac arrhythmia diagnosis. Most of recent technologies (smartphones, smart watches, etc.) are focusing on a unique source of information extracted from electrocardiography/photoplethysmography (i.e. heat inter-beat (RR) interval time series) coupled with classical pattern recognition methods to build efficient data-driven models. Herein, we demonstrate that the second derivative time series coupled with principal component analysis (PCA) and relevance vector machine (RVM) allow detection of abnormal rhythm. To achieve this aim, four features were extracted from one minute RR time series as well as from their derivatives and were subjected to PCA and RVM. PCA, as explanatory method, has shown that detection of AF arrhythmia became straightforward by targeting the second derivative time series. RVM was optimized through four kernel functions and the best model has reached 99.83% success rate to diagnosis AF and normal rhythm. The proposed approach outperformed several recent studies dealing with automatic AF diagnosis. Therefore, this method, which can be easily embedded in personal monitoring devices for real time cardiac arrhythmia detection, could be adapted for various medical decision-support involving time series recordings

Relevance Vector Machine as Data-Driven Method for Medical Decision Making

International audienceThe aim of this work is to develop an efficient data-driven method for automatic medical decision making, especially for cardiac arrhythmia diagnosis. To achieve this goal, we have targeted the most common arrhythmia worldwide -atrial fibrillation (AF). Most of reported studies are dealing with inter-beat interval time series analysis coupled with univariate and/or multivariate data-driven methods. The state of the art of this subject revealed that although satisfactory detection findings have been achieved for long AF durations, there is still scope for improvement which needs to be addressed for brief episodes which is highly desired by healthcare professionals. Relevance vector machine (RVM) has been developed to address this issue. Several kernel functions and parameters have been tested to optimize RVM. Five geometrical and nonlinear features were extracted from 30s inter-beat time series. The RVM classifier was trained on 3000 randomly selected samples from four publicly-accessible sets of clinical data and tested on 1000 samples. The performance of the diagnosis model was evaluated by 10-fold cross-validation method. The results showed that the RVM model performed better than do existing algorithms, with 96.58% success rate. The automatic diagnosis on another dataset of 118985 samples of AF and Normal Sinus Rhythm (NSR) has yield 96.64% of classification accuracy. This automated data-driven decision making approach can be exploited for medical diagnosis of other arrhythmias

produced by symbiotic bacteria Antimicrobial chemicals in hoopoe preen secretions are Subject collections Antimicrobial chemicals in hoopoe preen secretions are produced by symbiotic bacteria

Animals frequently use metabolites produced by symbiotic bacteria as agents against pathogens and parasites. Secretions from the preen gland of birds are used for this purpose, although its chemicals apparently are produced by the birds themselves. European hoopoes Upupa epops and green woodhoopoes Phoeniculus purpureus harbour symbiotic bacteria in the uropygial gland that might be partly responsible for the chemical composition of secretions. Here we investigate the antimicrobial activity of the volatile fraction of chemicals in hoopoe preen secretions, and, by means of experimental antibiotic injections, test whether symbiotic bacteria living within the uropygial gland are responsible for their production. Hoopoes produce two different kinds of secretions that differ drastically in their chemical composition. While the malodorous dark secretions produced by nestlings included a complex mix of volatiles, these chemicals did not appear in white secretions produced by non-nesting birds. All volatiles detected showed strong antibacterial activity, and a mixture of the chemicals at the concentrations measured in nestling glands inhibited the growth of all bacterial strains assayed. We found support for the hypothesized role of bacteria in the production of such antimicrobial chemicals because experimental clearance of bacteria from glands of nestlings with antibiotics resulted in secretions without most of the volatiles detected in control individuals. Thus, the presence of symbiotic bacteria in the uropygial gland provides hoopoes with potent antimicrobials for topical use

Microbial metabolites as biological control agents in food safety

Ensuring food safety and at the same time meeting such demands for retention of nutrition and quality attributes have resulted in increased interest in alternative preservation techniques for inactivating microorganisms and enzymes in foods. This increasing demand has opened new dimensions for the use of natural preservatives derived from plants, animals, or microflora. Extensive research has investigated the potential application of natural antimicrobial agents in food preservation. Especially the significance and use of microbes as producers of antimicrobial metabolites has increased significantly during the last decades. Reported studies have demonstrated that microbial metabolites from microorganisms exhibited a great numbers of diverse and versatile biological effects about antimicrobial activities. These microorganisms produce many compounds that are active against other microorganisms, which can be harnessed to inhibit the growth of potential spoilage or pathogenic microorganisms. These include fermentation end products (metabolites) such as organic acids, hydrogen peroxide, and diacetyl, biofilm, exopolysaccharides in addition to bacteriocins and other antagonistic compounds such as reuterin. Up to now, antimicrobial metabolites from lactic acid bacteria (such as nisin) have been mostly used in food preservation. In addition to lactic acid bacteria, some yeast, mold, and another bacteria species as well as some pathogenic bacteria can produce antimicrobial metabolites. Antimicrobial metabolites present in foods can extend the shelf life of unprocessed or processed foods by reducing the microbial growth rate or viability. This offers a new knowledge-based approach to the exploitation of bacteria for food production, from metabolic engineering of microorganisms to produce antimicrobials or nutritionals, to the molecular mining of activities as yet unknown but which could benefit food production. In addition, the availability of the genomes of many food pathogenic and spoilage bacteria may open up new possibilities for the design of novel antimicrobials which target essential functions of these problematic bacteria. In this chapter, antimicrobial metabolites from microorganism in food safety as a biocontrol agent reviewed. © 2014, Springer Science+Business Media New York