Inhibiting α-Synuclein Oligomerization by Stable Cell-Penetrating β-Synuclein Fragments Recovers Phenotype of Parkinson's Disease Model Flies

The intracellular oligomerization of α-synuclein is associated with Parkinson's disease and appears to be an important target for disease-modifying treatment. Yet, to date, there is no specific inhibitor for this aggregation process. Using unbiased systematic peptide array analysis, we indentified molecular interaction domains within the β-synuclein polypeptide that specifically binds α-synuclein. Adding such peptide fragments to α-synuclein significantly reduced both amyloid fibrils and soluble oligomer formation in vitro. A retro-inverso analogue of the best peptide inhibitor was designed to develop the identified molecular recognition module into a drug candidate. While this peptide shows indistinguishable activity as compared to the native peptide, it is stable in mouse serum and penetrates α-synuclein over-expressing cells. The interaction interface between the D-amino acid peptide and α-synuclein was mapped by Nuclear Magnetic Resonance spectroscopy. Finally, administering the retro-inverso peptide to a Drosophila model expressing mutant A53T α-synuclein in the nervous system, resulted in a significant recovery of the behavioral abnormalities of the treated flies and in a significant reduction in α-synuclein accumulation in the brains of the flies. The engineered retro-inverso peptide can serve as a lead for developing a novel class of therapeutic agents to treat Parkinson's disease

Drosophila melanogaster as an Animal Model for the Study of Pseudomonas aeruginosa Biofilm Infections In Vivo

Pseudomonas aeruginosa is an opportunistic pathogen capable of causing both acute and chronic infections in susceptible hosts. Chronic P. aeruginosa infections are thought to be caused by bacterial biofilms. Biofilms are highly structured, multicellular, microbial communities encased in an extracellular matrix that enable long-term survival in the host. The aim of this research was to develop an animal model that would allow an in vivo study of P. aeruginosa biofilm infections in a Drosophila melanogaster host. At 24 h post oral infection of Drosophila, P. aeruginosa biofilms localized to and were visualized in dissected Drosophila crops. These biofilms had a characteristic aggregate structure and an extracellular matrix composed of DNA and exopolysaccharide. P. aeruginosa cells recovered from in vivo grown biofilms had increased antibiotic resistance relative to planktonically grown cells. In vivo, biofilm formation was dependent on expression of the pel exopolysaccharide genes, as a pelB::lux mutant failed to form biofilms. The pelB::lux mutant was significantly more virulent than PAO1, while a hyperbiofilm strain (PAZHI3) demonstrated significantly less virulence than PAO1, as indicated by survival of infected flies at day 14 postinfection. Biofilm formation, by strains PAO1 and PAZHI3, in the crop was associated with induction of diptericin, cecropin A1 and drosomycin antimicrobial peptide gene expression 24 h postinfection. In contrast, infection with the non-biofilm forming strain pelB::lux resulted in decreased AMP gene expression in the fly. In summary, these results provide novel insights into host-pathogen interactions during P. aeruginosa oral infection of Drosophila and highlight the use of Drosophila as an infection model that permits the study of P. aeruginosa biofilms in vivo

Business Ethics: The Promise of Neuroscience

Recent advances in cognitive neuroscience research portend well for furthering understanding of many of the fundamental questions in the field of business ethics, both normative and empirical. This article provides an overview of neuroscience methodology and brain structures, and explores the areas in which neuroscience research has contributed findings of value to business ethics, as well as suggesting areas for future research. Neuroscience research is especially capable of providing insight into individual reactions to ethical issues, while also raising challenging normative questions about the nature of moral responsibility, autonomy, intent, and free will. This article also provides a brief summary of the papers included in this special issue, attesting to the richness of scholarly inquiry linking neuroscience and business ethics. We conclude that neuroscience offers considerable promise to the field of business ethics, but we caution against overpromise

Recent advances of metabolomics in plant biotechnology

Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants

Ultrafast multidimensional Laplace NMR for a rapid and sensitive chemical analysis

Traditional nuclear magnetic resonance (NMR) spectroscopy relies on the versatile chemical information conveyed by spectra. To complement conventional NMR, Laplace NMR explores diffusion and relaxation phenomena to reveal details on molecular motions. Under a broad concept of ultrafast multidimensional Laplace NMR, here we introduce an ultrafast diffusion-relaxation correlation experiment enhancing the resolution and information content of corresponding 1D experiments as well as reducing the experiment time by one to two orders of magnitude or more as compared with its conventional 2D counterpart. We demonstrate that the method allows one to distinguish identical molecules in different physical environments and provides chemical resolution missing in NMR spectra. Although the sensitivity of the new method is reduced due to spatial encoding, the single-scan approach enables one to use hyperpolarized substances to boost the sensitivity by several orders of magnitude, significantly enhancing the overall sensitivity of multidimensional Laplace NMR