Matrix Effects on Water Analysis for Alkylphenols Using Solid Phase Extraction Gas Chromatography-Mass Spectrometry

Gas chromatography with mass spectrometry is frequently used for the quantification of many classes of substances, including alkylphenols. Alkylphenol polyethoxylates are nonionic surfactants used in a wide variety of industrial and consumer applications. Alkylphenol polyethoxylates can degrade to alkylphenols, which are endocrine disruptors. In analytical validation procedures, the most common parameters studied are the detection and quantification limits, linearity, and recovery; however, the matrix effects are sometimes neglected. Although some investigators have evaluated matrix effects, there is no consensus on how to evaluate them during method validation. In this study, the matrix effects of alkylphenol polyethoxylates (nonylphenol monoethoxylate, nonylphenol diethoxylate, octylphenol monoethoxylate, octylphenol diethoxylate) and alkylphenols (nonylphenol and octylphenol) were studied using solid phase extraction and gas chromatography-mass spectrometry analysis. For alkylphenol polyethoxylates, the matrix effects ranged from 16 to 4692%, whereas for alkylphenols (nonylphenol and octylphenol), the effects were insignificant. Therefore, constructing an analytical curve in the matrix for alkylphenol polyethoxylates is essential. © 2013 Copyright Taylor and Francis Group, LLC.

Unravelling the Neospora caninum secretome through the secreted fraction (ESA) and quantification of the discharged tachyzoite using high-resolution mass spectrometry-based proteomics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Structural and functional characterization of the chaperone Hsp70 from sugarcane. Insights into conformational changes during cycling from cross-linking/mass spectrometry assays

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

RAMSY: Ratio Analysis of Mass Spectrometry to Improve Compound Identification

The complexity of biological samples poses a major challenge for reliable compound identification in mass spectrometry (MS). The presence of interfering compounds that cause additional peaks in the spectrum can make interpretation and assignment difficult. To overcome this issue, new approaches are needed to reduce complexity and simplify spectral interpretation. Recently, focused on unknown metabolite identification, we presented a new approach, RANSY (ratio analysis of nuclear magnetic resonance spectroscopy; Anal. Chem. 2011, 83, 7616-7623), which extracts the signals related to the same metabolite based on peak intensity ratios. On the basis of this concept, we present the ratio analysis of mass spectrometry (RAMSY) method, which facilitates improved compound identification in complex MS spectra. RAMSY works on the principle that, under a given set of experimental conditions, the abundance/intensity ratios between the mass fragments from the same metabolite are relatively constant. Therefore, the quotients of average peak ratios and their standard deviations, generated using a small set of MS spectra from the same ion chromatogram, efficiently allow the statistical recovery of the metabolite peaks and facilitate reliable identification. RAMSY was applied to both gas chromatography/MS and liquid chromatography tandem MS (LC-MS/MS) data to demonstrate its utility. The performance of RAMSY is typically better than the results from correlation methods. RAMSY promises to improve unknown metabolite identification for MS users in metabolomics or other fields.

Identification of species of the Euterpe genus by rare earth elements using inductively coupled plasma mass spectrometry and linear discriminant analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analysis of rocuronium in human plasma by liquid chromatography-tandem mass spectrometry with application in clinical pharmacokinetics

Rocuronium (ROC) is a neuromuscular blocking agent used in surgical procedures which is eliminated primarily by biliary excretion. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for analysis of ROC in human plasma. Separation of ROC and IS (verapamil) was performed using an endcapped C-18 column and a mixture of water:acetonitrile:trifluoracetic acid (50:50:0.1, v/v) as mobile phase. Aliquots of 100 mu L of human plasma were extracted at pH 3, using dichloromethane. The lower limit of quantification of 5 ng/mL shows the high sensitivity of this method. Intra- and inter-assay precision (as relative standard deviation) was all <= 14.2% and accuracy (as relative standard error) did not exceed 10.1%. The validated method was successfully applied to quantify ROC concentrations in patients under surgical procedures up to 6 h after the administration of the 0.4-0.9 mg/kg ROC. The pharmacokinetic parameter estimations of ROC showed AUC/dose of 563 mu g min/mL, total clearance of 2.5 mL/min/kg, volume of distribution at steady state of 190 mL/kg and mean residence time of 83 min. (C) 2013 Elsevier B.V. All rights reserved.

Metabolic profiling by ultra-performance liquid chromatography-mass spectrometry and parallel factor analysis for the determination of disease biomarkers in Eucalyptus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analysis of Steroids using Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry-Mass Spectrometry (SPME-GC-MS-MS)

Direct immersion SPME-GC-MS-MS was used for the analysis of steroids in water at part-per-trillion(ppt) and lower concentrations. The method was validated and extended to real sample analysis. The method were linear from 0.01 to 5 ng/ml with precision less than 10% relative standard deviation for a steroid mixture at 1 ng/ml. Limit of quantitation and limit of detection was found to be 200- 1200 pg/L and 30-200 pg/L respectively and recoveries ranged from 88-103 %. To understand the extraction efficiency of the fiber, a depletion study was performed. The fiber/ sample partition coefficients for the steroids were determined to be 1.0 x 104 to 1.5 x 104 . The extraction was performed without derivatization or the use of an internal standard. SPMEGC-MS-MS effectively demonstrated ultra-trace level detection of steroids in water.

Rapid determination of 12 antibiotics and caffeine in sewage and bioreactor effluent by online column-switching liquid chromatography/tandem mass spectrometry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Characterization of Glycation Sites on Human Serum Albumin using Mass Spectrometry

The modification of proteins by reducing sugars is a process that occurs naturally in the body. This process, which is known as glycation, has been linked to many of the chronic complications encountered during diabetes. Glycation has also been linked to changes in the binding of human serum albumin (HSA) to several drugs and small solutes in the body. While these effects are known, there is little information that explains why these changes in binding occur. The goal of this project was to obtain qualitative and quantitative information about glycation that occurs on HSA. The first section of this dissertation examined methods that could be used to quantify and identify glycation that occurs on HSA. The extent of glycation that occurred on HSA was quantified using oxygen-18 labeling mass spectrometry and the glycation sites were identified by observing the mass-to-charge (m/z) shifts that occurred in glycated HSA. This initial investigation revealed that oxygen-18 labeling based quantitation can be improved over previous methods if a relative comparison is done with oxygen-18 labeled peptides in a control HSA sample. Similarly, the process of making m/z shift-based assignments could be improved if only the peptides that were unique to the glycated HSA samples were used with internal calibration. These techniques were used in subsequent chapters for the assignment of early and late-stage glycation products on HSA. The regions of HSA that contained the highest amount of modification were identified, quantified, and ranked in order of their relative abundance. Of the commonly reported glycation sites, the N-terminus was found to have the highest extent of modification, followed by lysines 525, 199, and 439. The relative amount of modification on lysine 281, with respect to the aforementioned residues, varied with different degrees of glycation. The oxygen-18 labeling approach used for this analysis was novel because it allowed for the simultaneous quantification of all glycation-related modifications that were occurring on HSA. As such, several arginine residues were also found to have high amounts of modification on glycated HSA.

A novel HS-SBSE system coupled with gas chromatography and mass spectrometry for the analysis of organochlorine pesticides in water samples

A methodology to analyze organochlorine pesticides (OCPs) in water samples has been accomplished by using headspace stir bar sorptive extraction (HS-SBSE). The bars were in house coated with a thick film of PDMS in order to properly work in the headspace mode. Sampling was done by a novel HS-SBSE system whereas the analysis was performed by capillary GC coupled mass spectrometric detection (HS-SBSE-GC-MS). The extraction optimization, using different experimental parameters has been established by a standard equilibrium time of 120 min at 85 degrees C. A mixture of ACN/toluene as back extraction solvent promoted a good performance to remove the OCPs sorbed in the bar. Reproducibility between 2.1 and 14.8% and linearity between 0.96 and 1.0 were obtained for pesticides spiked in a linear range between 5 and 17 ng/g in water samples during the bar evaluation.

Evaluation of comprehensive two-dimensional gas chromatography coupled to rapid scanning quadrupole mass spectrometry for quantitative analysis

Comprehensive two-dimensional gas chromatography (GC x GC) is a powerful technique that provides excellent separation and identification of analytes in highly complex samples with considerable increase in GC peak capacities. However, since second dimension analyses are very fast, detectors with a rapid acquisition rate are required. Over the last years, quite a number of studies have discussed the potential and limitations of the combination GC x GC with a variety of quadrupole mass spectrometers. The present research focuses on the evaluation of qMS effectiveness at a 10,000-amu/s scan speed and 20-Hz scan frequency for the identification (full scan mode acquisition-TIC) and quantification (extracted ion chromatogram) of target pesticide residues in tomato samples. The following MS parameters have been evaluated: number of data points per peak, mass spectrum quality, peak skewing, and sensitivity. The validated proposed GC x GC/qMS method presented satisfactory results in terms of repeatability (coefficient of variation lower than 15%), accuracy (84-117%), and linearity (ranging from 25 to 500 ng/g), while significant enhancement in sensitivity was observed (a factor of around 10) under scan conditions. (C) 2012 Elsevier B.V. All rights reserved.

CE-ESI-MS metabolic fingerprinting of Leishmania resistance to antimony treatment

Metabolomics has become an invaluable tool to unveil biology of pathogens, with immediate application to chemotherapy. It is currently accepted that there is not one single technique capable of obtaining the whole metabolic fingerprint of a biological system either due to their different physical-chemical properties or concentrations. In this work, we have explored the capability of capillary electrophoresis mass spectrometry with a sheathless interface with electrospray ionization (CE-ESI-TOF-MS) to separate metabolites in order to be used as a complementary technique to LC. As proof of concept, we have compared the metabolome of Leishmania infantum promastigotes BCN 150 (Sb (III) IC50 = 20.9 mu M) and its variation when treated with 120 mu M of Sb(III) potassium tartrate for 12 h, as well as with its Sb(III) resistant counterpart obtained by growth of the parasites under increasing Sb(III) in a step-wise manner up to 180 mu M. The number of metabolites compared were of 264 for BCN150 Sb(III) treated versus nontreated and of 195 for Sb(III) resistant versus susceptible parasites. After successive data filtering, differences in seven metabolites identified in databases for Leishmania pathways, showed the highest significant differences, corresponding mainly to amino acids or their metabolite surrogates. Most of them were assigned to sulfur containing amino acids and polyamine biosynthetic pathways, of special relevance considering the deterioration of the thiol-dependent redox metabolism in Leishmania by Sb(III). Given the low concentrations typical for most of these metabolites, the assay can be considered a success that should be explored for new biological questions.

Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class

The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8.