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.

Temperature proxies of sediment cores from the Sea of Marmara

Reconstructing ocean temperature values is a major target in paleoceanography and climate research. However, most temperature proxies are organism-based and thus suffer from an "ecological bias". Multiproxy approaches can potentially overcome this bias but typically require more investment in time and resources, while being susceptible to errors induced by sample preparation steps necessary before analysis. Three lipid-based temperature proxies are widely used: UK'37 (based on long chain alkenones from phytoplanktonic haptophytes), TEX86 [based on glycerol dialkyl glycerol tetraethers (GDGTs) from pelagic archaea] and LDI (based on long chain diols from phytoplanktonic eustigmatophytes). So far, separate analytical methods, including gas chromatography (GC) and liquid chromatography (LC), have been used to determine these proxies. Here we present a sensitive method for determining all three in a single normal phase high performance LC-atmospheric pressure chemical ionization mass spectrometry (NP-HPLC-APCI-MS) analysis. Each of the long chain alkenones and long chain diols was separated and unambiguously identified from the accurate masses and characteristic fragmentation during multiple stage MS analysis (MS2). Comparison of conventional GC and HPLC-MS methods showed similar results for UK'37 and LDI, respectively, using diverse environmental samples and an Emiliania huxleyi culture. Including the three sea surface temperature (SST) proxies; the NP-HPLC-APCI-MS method in fact allows simultaneous determination of nine paleoenvironmental proxies. The extent to which the ecology of the source organisms (ecological bias) influences lipid composition and thereby the reconstructed temperature values was demonstrated by applying the new method to a sediment core from the Sea of Marmara, covering the last 21 kyr BP. Reconstructed SST values differed considerably between the proxies for the Last Glacial Maximum (LGM) and the period of Sapropel S1 formation at ca. 10 kyr BP, whereas the trends during the late Holocene were similar. Changes in the composition of alkenone-producing species at the transition from the LGM to the Bølling/Allerød (B/A) were inferred from unreasonably high UK'37-derived SST values (ca. 20 °C) during the LGM. We ascribe discrepancies between the reconstructed temperature records during S1 deposition to habitat change, e.g. a different depth due to changes in nutrient availability.

Methanol and ethanol analysis in marine sediment pore water

Low-molecular-weight (LMW) alcohols are produced during the microbial degradation of organic matter from precursors such as lignin, pectin, and carbohydrates. The biogeochemical behavior of these alcohols in marine sediment is poorly constrained but potentially central to carbon cycling. Little is known about LMW alcohols in sediment pore waters because of their low concentrations and high water miscibility, both of which pose substantial analytical challenges. In this study, three alternative methods were adapted for the analysis of trace amounts of methanol and ethanol in small volumes of saline pore waters: direct aqueous injection (DAI), solid-phase microextraction (SPME), and purge and trap (P&T) in combination with gas chromatography (GC) coupled to either a flame ionization detector (FID) or a mass spectrometer (MS). Key modifications included the desalination of samples prior to DAI, the use of a threaded midget bubbler to purge small-volume samples under heated conditions and the addition of salt during P&T. All three methods were validated for LMW alcohol analysis, and the lowest detection limit (60 nM and 40 nM for methanol and ethanol, respectively) was achieved with the P&T technique. With these methods, ambient concentrations of volatile alcohols were determined for the first time in marine sediment pore waters of the Black Sea and the Gulf of Mexico. A strong correlation between the two compounds was observed and tentatively interpreted as being controlled by similar sources and sinks at the examined stations.