Non-genetic mechanisms communicating antibiotic resistance:rethinking strategies for antimicrobial drug design

Introduction: Infections by multidrug-resistant bacteria are of great concern worldwide. In many cases, resistance is not due to the presence of specific antibiotic-modifying enzymes, but rather associated with a general impermeability of the bacterial cell envelope. The molecular bases of this intrinsic resistance are not completely understood. Moreover, horizontal gene transfers cannot solely explain the spread of intrinsic resistance among bacterial strains. Areas covered: This review focuses on the increased intrinsic antibiotic resistance mediated by small molecules. These small molecules can either be secreted from bacterial cells of the same or different species (e.g., indole, polyamines, ammonia, and the Pseudomonas quinolone signal) or be present in the bacterial cell milieu, whether in the environment, such as indole acetic acid and other plant hormones, or in human tissues and body fluids, such as polyamines. These molecules are metabolic byproducts that act as infochemicals and modulate bacterial responses toward antibiotics leading to increasing or decreasing resistance levels. Expert opinion: The non-genetic mechanisms of antibiotic response modulation and communication discussed in this review should reorient our thinking of the mechanisms of intrinsic resistance to antibiotics and its spread across bacterial cell populations. The identification of chemical signals mediating increased intrinsic antibiotic resistance will expose novel critical targets for the development of new antimicrobial strategies.

A new analytical approach for the detection of palm oil in vegetable oil blends

The new Food Information Regulation (1169/2011), dictates that in a refined vegetable oil blend, the type of oil must be clearly identified in the package in contract with current practice where is labelled under the generic and often misleading term “vegetable oil”. With increase consumer awareness in food authenticity, as shown in the recent food scandal with horsemeat in beef products, the identification of the origin of species in food products becomes increasingly relevant. Palm oil is used extensively in food manufacturing and as global demand increases, producing countries suffer from the aftermath of intensive agriculture. Even if only a small portion of global production, sustainable palm oil comes in great demand from consumers and industry. It is therefore of interest to detect the presence of palm oil in food products as consumers have the right to know if it is present in the product or not, mainly from an ethical point of view. Apart from palm oil and its derivatives, rapeseed oil and sunflower oil are also included. With DNA-based methods, the gold standard for the detection of food authenticity and species recognition deemed not suitable in this analytical problem, the focus is inevitably drawn to the chromatographic and spectroscopic methods. Both chromatographic (such as GC-FID and LC-MS) and spectroscopic methods (FT-IR, Raman, NIR) are relevant. Previous attempts have not shown promising results due to oils’ natural variation in composition and complex chemical signals but the suggested two-step analytical procedure is a promising approach with very good initial results.

Using Process Algebra to Model Radiation Induced Bystander Effects

Radiation induced bystander effects are secondary effects caused by the production of chemical signals by cells in response to radiation. We present a Bio-PEPA model which builds on previous modelling work in this field to predict: the surviving fraction of cells in response to radiation, the relative proportion of cell death caused by bystander signalling, the risk of non-lethal damage and the probability of observing bystander signalling for a given dose. This work provides the foundation for modelling bystander effects caused by biologically realistic dose distributions, with implications for cancer therapies.

Metal Oxide Nanoparticle Mediated Enhanced Raman Scattering and Its Use in Direct Monitoring of Interfacial Chemical Reactions

Metal oxide nanoparticles (MONPs) have widespread usage across many disciplines, but monitoring molecular processes at their surfaces in situ has not been possible. Here we demonstrate that MONPs give highly enhanced (X10(4)) Raman scattering signals from molecules at the interface permitting direct monitoring of their reactions, when placed on top of flat metallic surfaces. Experiments with different metal oxide materials and molecules indicate that the enhancement is generic and operates at the single nanoparticle level. Simulations confirm that the amplification is principally electromagnetic and is a result of optical modulation of the underlying plasmonic metallic surface by MONPs, which act as scattering antennae and couple light into the confined region sandwiched by the underlying surface. Because of additional functionalities of metal oxides as magnetic, photoelectrochemical and catalytic materials, enhanced Raman scattering mediated by MONPs opens up significant opportunities in fundamental science, allowing direct tracking and understanding of application-specific transformations at such interfaces. We show a first example by monitoring the MONP-assisted photocatalytic decomposition reaction of an organic dye by individual nanoparticles.