Aspergillicins A-E: five novel depsipeptides from the marine-derived fungus Aspergillus carneus

A search for new antiparasitic agents from a strain of the fungus Aspergillus carneus isolated from an estuarine sediment collected in Tasmania, Australia, yielded the known terrestrial fungal metabolite marcfortine A ( 1) as an exceptionally potent antiparasitic agent. This study also yielded a series of new depsipeptides, aspergillicins A - E ( 2 - 6) and the known terrestrial fungal metabolite acyl aszonalenin ( 7). Marcfortine A ( 1) and acyl aszonalenin ( 7) were identified by spectroscopic analysis, with comparison to literature data. Complete stereostructures were assigned to aspergillicins A - E ( 2 - 6) on the basis of detailed spectroscopic analysis, together with ESIMS analysis of the free amino acids generated by acid hydrolysis, and HPLC analysis of Marfey derivatives prepared from the acid hydrolysate. The peptide amino acid sequence for all aspergillicins was unambiguously assigned by MSn ion-trap ESI mass spectrometry.

Comparison of an ELISA and an LC/MS/MS method for measuring tacrolimus concentrations and making dosage decisions in transplant recipients

This study compared an enzyme-linked immunosorbent assay (ELISA) to a liquid chromatography-tandem mass spectrometry (LC/MS/MS) technique for measurement of tacrolimus concentrations in adult kidney and liver transplant recipients, and investigated how assay choice influenced pharmacokinetic parameter estimates and drug dosage decisions. Tacrolimus concentrations measured by both ELISA and LC/MS/MS from 29 kidney (n = 98 samples) and 27 liver (n = 97 samples) transplant recipients were used to evaluate the performance of these methods in the clinical setting. Tacrolimus concentrations measured by the two techniques were compared via regression analysis. Population pharmacokinetic models were developed independently using ELISA and LC/MS/MS data from 76 kidney recipients. Derived kinetic parameters were used to formulate typical dosing regimens for concentration targeting. Dosage recommendations for the two assays were compared. The relation between LC/MS/MS and ELISA measurements was best described by the regression equation ELISA = 1.02 . (LC/MS/MS) + 0.14 in kidney recipients, and ELISA = 1.12 . (LC/MS/MS) - 0.87 in liver recipients. ELISA displayed less accuracy than LC/MS/MS at lower tacrolimus concentrations. Population pharmacokinetic models based on ELISA and LC/MS/MS data were similar with residual random errors of 4.1 ng/mL and 3.7 ng/mL, respectively. Assay choice gave rise to dosage prediction differences ranging from 0% to 30%. ELISA measurements of tacrolimus are not automatically interchangeable with LC/MS/MS values. Assay differences were greatest in adult liver recipients, probably reflecting periods of liver dysfunction and impaired biliary secretion of metabolites. While the majority of data collected in this study suggested assay differences in adult kidney recipients were minimal, findings of ELISA dosage underpredictions of up to 25% in the long term must be investigated further.

Enhancing the ratio of molecular ions to non-covalent compounds in the electrospray interface of LC-MS in quantitative analysis

A common problem encountered during the development of MS methods for the quantitation of small organic molecules by LGMS is the formation of non-covalently bound species or adducts in the electrospray interface. Often the population of the molecular ion is insignificant compared to those of all other forms of the analyte produced in the electrospray, making it difficult to obtain the sensitivity required for accurate quantitation. We have investigated the effects of the following variables: orifice potential, nebulizer gas flow, temperature, solvent composition and the sample pH on the relative distributions of ions of the types MH+, MNa+, MNH+, and 2MNa(+), where M represents a 4 small organic molecule: BAY 11-7082 ((E)-3-[4-methylphenylsulfonyl]-2-propenenitrile). Orifice potential, solvent composition and the sample pH had the greatest influence on the relative distributions of these ions, making these parameters the most useful for optimizing methods for the quantitation of small molecules.

Matrix effects: The Achilles heel of quantitative high-performance liquid chromatography-electrospray-tandem mass spectrometry

High-performance liquid chromatography coupled by an electrospray ion source to a tandem mass spectrometer (HPLC-EST-MS/ MS) is the current analytical method of choice for quantitation of analytes in biological matrices. With HPLC-ESI-MS/MS having the characteristics of high selectivity, sensitivity, and throughput, this technology is being increasingly used in the clinical laboratory. An important issue to be addressed in method development, validation, and routine use of HPLC-ESI-MS/MS is matrix effects. Matrix effects are the alteration of ionization efficiency by the presence of coeluting substances. These effects are unseen in the chromatograrn but have deleterious impact on methods accuracy and sensitivity. The two common ways to assess matrix effects are either by the postextraction addition method or the postcolumn infusion method. To remove or minimize matrix effects, modification to the sample extraction methodology and improved chromatographic separation must be performed. These two parameters are linked together and form the basis of developing a successful and robust quantitative HPLC-EST-MS/MS method. Due to the heterogenous nature of the population being studied, the variability of a method must be assessed in samples taken from a variety of subjects. In this paper, the major aspects of matrix effects are discussed with an approach to address matrix effects during method validation proposed. (c) 2004 The Canadian Society of Clinical Chemists. All rights reserved.

Taxonomy of Australian Funnel-web spiders using rp-HPLC/ESI-MS profiling techniques

The complex nature of venom from spider species offers a unique natural source of potential pharmacological tools and therapeutic leads. The increased interest in spider venom molecules requires reproducible and precise identification methods. The current taxonomy of the Australian Funnel-web spiders is incomplete, and therefore, accurate identification of these spiders is difficult. Here, we present a study of venom from numerous morphologically similar specimens of the Hadronyche infensa species group collected from a variety of geographic locations in southeast Queensland. Analysis of the crude venoms using online reversed-phase high performance liquid chromatography/electrospray ionisation mass spectrometry (rp-HPLC/ESI-MS) revealed that the venom profiles provide a useful means of specimen identification, from the species level to species variants. Tables defining the descriptor molecules for each group of specimens were constructed and provided a quick reference of the relationship between one specimen and another. The study revealed that the morphologically similar specimens from the southeast Queensland region are a number of different species/species variants. Furthermore, the study supports aspects of the current taxonomy with respect to the H. infensa species group. Analysis of Australian Funnel-web spider venom by rp-HPLC/ESI-MS provides a rapid and accurate method of species/species variant identification. (c) 2006 Elsevier Ltd. All rights reserved.

Strategies for identifying and predicting islet autoantigen T-cell epitopes in insulin-dependent diabetes mellitus

T cells recognize peptide epitopes bound to major histocompatibility complex molecules. Human T-cell epitopes have diagnostic and therapeutic applications in autoimmune diseases. However, their accurate definition within an autoantigen by T-cell bioassay, usually proliferation, involves many costly peptides and a large amount of blood, We have therefore developed a strategy to predict T-cell epitopes and applied it to tyrosine phosphatase IA-2, an autoantigen in IDDM, and HLA-DR4(*0401). First, the binding of synthetic overlapping peptides encompassing IA-2 was measured directly to purified DR4. Secondly, a large amount of HLA-DR4 binding data were analysed by alignment using a genetic algorithm and were used to train an artificial neural network to predict the affinity of binding. This bioinformatic prediction method was then validated experimentally and used to predict DR4 binding peptides in IA-2. The binding set encompassed 85% of experimentally determined T-cell epitopes. Both the experimental and bioinformatic methods had high negative predictive values, 92% and 95%, indicating that this strategy of combining experimental results with computer modelling should lead to a significant reduction in the amount of blood and the number of peptides required to define T-cell epitopes in humans.