Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Multiple inert gas elimination technique by micropore membrane inlet mass spectrometry--a comparison with reference gas chromatography.

The mismatching of alveolar ventilation and perfusion (VA/Q) is the major determinant of impaired gas exchange. The gold standard for measuring VA/Q distributions is based on measurements of the elimination and retention of infused inert gases. Conventional multiple inert gas elimination technique (MIGET) uses gas chromatography (GC) to measure the inert gas partial pressures, which requires tonometry of blood samples with a gas that can then be injected into the chromatograph. The method is laborious and requires meticulous care. A new technique based on micropore membrane inlet mass spectrometry (MMIMS) facilitates the handling of blood and gas samples and provides nearly real-time analysis. In this study we compared MIGET by GC and MMIMS in 10 piglets: 1) 3 with healthy lungs; 2) 4 with oleic acid injury; and 3) 3 with isolated left lower lobe ventilation. The different protocols ensured a large range of normal and abnormal VA/Q distributions. Eight inert gases (SF6, krypton, ethane, cyclopropane, desflurane, enflurane, diethyl ether, and acetone) were infused; six of these gases were measured with MMIMS, and six were measured with GC. We found close agreement of retention and excretion of the gases and the constructed VA/Q distributions between GC and MMIMS, and predicted PaO2 from both methods compared well with measured PaO2. VA/Q by GC produced more widely dispersed modes than MMIMS, explained in part by differences in the algorithms used to calculate VA/Q distributions. In conclusion, MMIMS enables faster measurement of VA/Q, is less demanding than GC, and produces comparable results.

Determination of ajulemic acid and its glucuronide in human plasma by gas chromatography-mass spectrometry

A method using gas chromatography-mass spectrometry (GC-MS) and solid-phase extraction (SPE) was developed for the determination of ajulemic acid (AJA), a non-psychoactive synthetic cannabinoid with interesting therapeutic potential, in human plasma. When using two calibration graphs, the assay linearity ranged from 10 to 750 ng/ml, and 750 to 3000 ng/ml AJA. The intra- and inter-day precision (R.S.D., %), assessed across the linear ranges of the assay, was between 1.5 and 7.0, and 3.6 and 7.9, respectively. The limit of quantitation (LOQ) was 10 ng/ml. The amount of AJA glucuronide was determined by calculating the difference in the AJA concentration before ("free AJA") and after enzymatic hydrolysis ("total AJA"). The present method was used within a clinical study on 21 patients suffering from neuropathic pain with hyperalgesia and allodynia. For example, plasma levels of 599.4+/-37.2 ng/ml (mean+/-R.S.D., n=9) AJA were obtained for samples taken 2 h after the administration of an oral dose of 20 mg AJA. The mean AJA glucuronide concentration at 2h was 63.8+/-127.9 ng/ml.

A plasma global metabolic profiling approach applied to an exercise study monitoring the effects of glucose, galactose and fructose drinks during post-exercise recovery

A global metabolic profiling methodology based on gas chromatography coupled to time-of-flight mass spectrometry (GC-TOFMS) for human plasma was applied to a human exercise study focused on the effects of beverages containing glucose, galactose, or fructose taken after exercise and throughout a recovery period of 6 h and 45 min. One group of 10 well trained male cyclists performed 3 experimental sessions on separate days (randomized, single center). After performing a standardized depletion protocol on a bicycle, subjects consumed one of three different beverages: maltodextrin (MD)+glucose (2:1 ratio), MD+galactose (2:1), and MD+fructose (2:1), consumed at an average of 1.25 g of carbohydrate (CHO) ingested per minute. Blood was taken straight after exercise and every 45 min within the recovery phase. With the resulting blood plasma, insulin, free fatty acid (FFA) profile, glucose, and GC-TOFMS global metabolic profiling measurements were performed. The resulting profiling data was able to match the results obtained from the other clinical measurements with the addition of being able to follow many different metabolites throughout the recovery period. The data quality was assessed, with all the labelled internal standards yielding values of <15% CV for all samples (n=335), apart from the labelled sucrose which gave a value of 15.19%. Differences between recovery treatments including the appearance of galactonic acid from the galactose based beverage were also highlighted.

Radiation metabolomics. 4. UPLC-ESI-QTOFMS-Based metabolomics for urinary biomarker discovery in gamma-irradiated rats

Radiation metabolomics has aided in the identification of a number of biomarkers in cells and mice by ultra-performance liquid chromatography-coupled time-of-flight mass spectrometry (UPLC-ESI-QTOFMS) and in rats by gas chromatography-coupled mass spectrometry (GCMS). These markers have been shown to be both dose- and time-dependent. Here UPLC-ESI-QTOFMS was used to analyze rat urine samples taken from 12 rats over 7 days; they were either sham-irradiated or γ-irradiated with 3 Gy after 4 days of metabolic cage acclimatization. Using multivariate data analysis, nine urinary biomarkers of γ radiation in rats were identified, including a novel mammalian metabolite, N-acetyltaurine. These upregulated urinary biomarkers were confirmed through tandem mass spectrometry and comparisons with authentic standards. They include thymidine, 2'-deoxyuridine, 2'deoxyxanthosine, N(1)-acetylspermidine, N-acetylglucosamine/galactosamine-6-sulfate, N-acetyltaurine, N-hexanoylglycine, taurine and, tentatively, isethionic acid. Of these metabolites, 2'-deoxyuridine and thymidine were previously identified in the rat by GCMS (observed as uridine and thymine) and in the mouse by UPLC-ESI-QTOFMS. 2'Deoxyxanthosine, taurine and N-hexanoylglycine were also seen in the mouse by UPLC-ESI-QTOFMS. These are now unequivocal cross-species biomarkers for ionizing radiation exposure. Downregulated biomarkers were shown to be related to food deprivation and starvation mechanisms. The UPLC-ESI-QTOFMS approach has aided in the advance for finding common biomarkers of ionizing radiation exposure.

Search for a heavy particle decaying into an electron and a muon with the ATLAS detector in sqrt[s] = 7 TeV pp collisions at the LHC

This Letter presents the first search for a heavy particle decaying into an e ± μ(-/+) final state in sqrt[s] = 7 TeV pp collisions at the LHC. The data were recorded by the ATLAS detector during 2010 and correspond to a total integrated luminosity of 35 pb(-1). No excess above the standard model background expectation is observed. Exclusions at 95% confidence level are placed on two representative models. In an R-parity violating supersymmetric model, tau sneutrinos with a mass below 0.75 TeV are excluded, assuming all R-parity violating couplings are zero except λ(311)' = 0.11 and λ312 = 0.07. In a lepton flavor violating model, a Z'-like vector boson with masses of 0.70-1.00 TeV and corresponding cross sections times branching ratios of 0.175-0.183 pb is excluded. These results extend to higher mass R-parity violating sneutrinos and lepton flavor violating Z's than previous constraints from the Tevatron.