Recent advances in the bioanalytical applications of dried matrix spotting for the analysis of drugs and their metabolites.

DBS techniques for the bioanalysis of drugs and metabolites from whole blood have been demonstrated to be a useful tool in drug development. The term dried matrix spot (DMS) has been used to indicate that the DBS technique has been applied to nonblood matrices. DMS methods often employ a color-indicating process that enhances the ability to analyze these mostly transparent fluids when spotted onto collection paper. The color-indicating dye allows the analyst to visually confirm the location of the dried sample spot. Other benefits of using a color-indicating dye include improved method accuracy and precision, because the process of adding the dye allows for the concurrent addition of the IS prior to sample addition and extraction. To date, matrices that have been analyzed using DMS include cerebrospinal fluid, synovial fluid, saliva, tears, urine and plasma.

Validation of HPLC-MS/MS methods for analysis of loxapine, amoxapine, 7-OH-loxapine, 8-OH-loxapine and loxapine N-oxide in human plasma.

BACKGROUND: Two ESI-LC-MS/MS methods were validated for the quantitative analysis of loxapine, amoxapine, 7-OH-loxapine, 8-OH-loxapine and loxapine N-oxide in human K(2)EDTA plasma. Cation-exchange solid-phase extraction (SPE) was used to extract loxapine, amoxapine and the two hydroxylated metabolites, and organic precipitation was used to quantify loxapine N-oxide. RESULTS: Both methods were shown to be accurate (±13%), intra-assay precision was less than 15%, and inter-assay precision was less than 10% in all instances across the entire dynamic range of the assays (0.0500-50.0 ng/ml for the SPE method and 0.100-25.0 ng/ml for the precipitation method). CONCLUSION: The validated methods for loxapine, amoxapine, 7-OH-loxapine, 8-OH-loxapine and loxapine N-oxide have been used to successfully support clinical trials.

Targeted protein degradation by Salmonella under phagosome-mimicking culture conditions investigated using comparative peptidomics.

The pathogen Salmonella enterica is known to cause both food poisoning and typhoid fever. Because of the emergence of antibiotic-resistant isolates and the threat of bioterrorism (e.g. contamination of the food supply), there is a growing need to study this bacterium. In this investigation, comparative peptidomics was used to study S. enterica serovar Typhimurium cultured in either a rich medium or in an acidic, low magnesium, and minimal nutrient medium designed to roughly mimic the macrophage phagosomal environment (within which Salmonella are known to survive). Native peptides from cleared cell lysates were enriched by using isopropanol extraction and analyzed by using both LC-MS/MS and LC-FTICR-MS. We identified and quantified 5,163 peptides originating from 682 proteins, and the data clearly indicated that compared with Salmonella cultured in the rich medium, cells cultured in the phagosome-mimicking medium had dramatically higher abundances of a wide variety of protein degradation products, especially from ribosomal proteins. Salmonella from the same cultures were also analyzed using traditional, bottom-up proteomic methods, and when the peptidomics and proteomics data were analyzed together, two clusters of proteins targeted for proteolysis were tentatively identified. Possible roles of targeted proteolysis by phagocytosed Salmonella are discussed.

Advances in proteomics data analysis and display using an accurate mass and time tag approach.

Proteomics has recently demonstrated utility for increasing the understanding of cellular processes on the molecular level as a component of systems biology approaches and for identifying potential biomarkers of various disease states. The large amount of data generated by utilizing high efficiency (e.g., chromatographic) separations coupled with high mass accuracy mass spectrometry for high-throughput proteomics analyses presents challenges related to data processing, analysis, and display. This review focuses on recent advances in nanoLC-FTICR-MS-based proteomics approaches and the accompanying data processing tools that have been developed to display and interpret the large volumes of data being produced.