Novel Analytical Workflow for Comprehensive Non-targeted Phytochemical Metabolic Profiling: FH-HES

The understanding and interpretation of pharmacological properties on a molecular level is of great importance for many different fields of research. Our study provides a novel model work-flow for comprehensive metabolic profiling by structural identification of relevant metabolites not limited to phytochemistry applications. High resolution liquid chromatography mass spectrometry LC-MS/MS data can be directly correlated with pharmacological test results on a molecular level. Thus the understanding and interpretation of pharmacological properties is supported by structural and chemical information

RNA-DNA hybrid (R-loop) immunoprecipitation mapping: an analytical workflow to evaluate inherent biases

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New Approach in Analytical Workflow to Accurately Characterize Heterogeneous Carbonates Using Non-Destructive Tracers

The main goal of this research is to compare and understand the efficiency of the numerical methods by comparing them with experimental data obtained from coreflood non-destructive tracer experiments on 6 different carbonate cores. Commercial simulation software is used to compare the numerical and experimental tracer concentration profiles and identifying the influencing parameters for history matching. Six different types of carbonate cores 6 in.-length and 1.5 in. - diameter were obtained from different outcrop cores, with varying pore scale heterogeneity. 8 wt% potassium chloride (KCl) will be used as the non-destructive tracer in all the experiments. After characterizing the carbonates and tracer used in the experiments using standard coreflood procedures, concentration profiles were plotted against time (pore volume tracer injected). Computed tomography (CT) scan was performed on the core samples and single porosity based on the scans was used in the simulation studies. Detailed history matching and sensitivity studies have been carried out thoroughly via commercial simulator, to validate the experimental data and create an accurate model for further analysis. The ultimate goal of this proposed research is to devise a new analytical workflow to analyze and interpret the effect of heterogeneity in the carbonates using non-destructive tracers and a numerical simulator

Untargeted Lipidomic Analysis to Broadly Characterize the Effects of Pathogenic and Non-Pathogenic Staphylococci on Mammalian Lipids

Modification of the host lipidome via secreted enzymes is an integral, but often overlooked aspect of bacterial pathogenesis. In the current era of prevalent antibiotic resistance, knowledge regarding critical host pathogen lipid interactions has the potential for use in developing novel antibacterial agents. While most studies to date on this matter have focused on specific lipids, or select lipid classes, this provides an incomplete picture. Modern methods of untargeted lipidomics have the capacity to overcome these gaps in knowledge and provide a comprehensive understanding of the role of lipid metabolism in the pathogenesis of infections. In an attempt to determine the role of lipid modifying enzymes produced by staphylococci, we exposed bovine heart lipids, a standardized model for the mammalian lipidome, to spent medium from staphylococcal cultures, and analyzed lipid molecular changes by MS/MSALLshotgun lipidomics. We elucidate distinct effects of different staphylococcal isolates, including 4 clinical isolates of the pathogenic species Staphylococcus aureus, a clinical isolate of the normally commensal species S. epidermidis, and the non-pathogenic species S. carnosus. Two highly virulent strains of S. aureus had a more profound effect on mammalian lipids and modified more lipid classes than the other staphylococcal strains. Our studies demonstrate the utility of the applied untargeted lipidomics methodology to profile lipid changes induced by different bacterial secretomes. Finally, we demonstrate the promise of this lipidomics approach in assessing the specificity of bacterial enzymes for mammalian lipid classes. Our data suggests that there may be a correlation between the bacterial expression of lipid-modifying enzymes and virulence, and could facilitate the guided discovery of lipid pathways required for bacterial infections caused by S. aureus and thereby provide insights into the generation of novel antibacterial agents