The comprehended knowledge of the metabolic profile of the fecal matter has been recognized as an important point for understanding metabolic changes in the human systemic metabolism and it can provide precious information about host-gut microbiota interactions. However, few analytical strategies have been addressed for a broad analysis of metabolites with different chemical properties to better understand the chemical space of fecal samples. Here we report a systematic pipeline to achieve comprehensive coverage of the fecal metabolome, from high polar to nonpolar metabolites, using dog fecal samples as a proof-of-concept. This pipeline comprises a monophasic (ACN/H2O) and a biphasic extraction (methyl tert-butyl ether (MTBE)/MeOH/H2O) of the sample, followed by three liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS) methods using HILIC-amide, RP-C18 and CSH-C18 columns, and a switch polarity acquisition mode in the electrospray ion source. This approach allowed the annotation of 376 metabolites from 70 different chemical classes. The chemical space analysis by molecular networking and the pathway analysis revealed the complexity of the fecal sample and the importance of combined methods to better understand biochemical pathways. This pipeline can be used as a valuable tool to comprehend the relationship between host-gut microbiota metabolites and the influence of diet, medication, or environmental changes.
Petroleum exploration in presalt reservoirs is reaching increasingly deeper carbonate reservoirs, more and more distant from coastline. Therefore, optimization of investments for a safe and profitable production is critical. Each possible concern on geological conditions that would govern fluid composition and that can bring impact in development cost of an accumulation must be taken into account. In some petroleum accumulations, within presalt reservoirs, along southeastern offshore Brazilian basins, H 2 S was found. Although H 2 S concentrations were significantly lower than most of carbonates worldwide, they are enough to be considered in economical evaluations. Therefore, it is important to identify the process that generated H 2 S and to constraint the main variables that govern its occurrence for a more precise evaluation of the "H 2 S risk", take into consideration possible pit falls during well intervention. In this way, H 2 S is precipitated on site as a salt (Ag 2 S) from the gas produced during the long lasting producing tests, shipped to laboratory and the 34 S/ 32 S ratio is measured. The corresponding δ 34 S value is the main tool for identifying H 2 S origin: if it was formed due to organic (BSR, δ 34 S < −10 ‰) or inorganic (TSR, δ 34 S > +10 ‰) sulfate reduction. Results of δ 34 S CDT obtained in H 2 S from presalt reservoirs of the Santos Basin spread between +10 ‰ and +20 ‰ typical of TSR. However, temperatures of the reservoirs are lower than that inferred for development of TSR (T > ≈120 °C) suggesting that H 2 S was generated in deeper intervals with significantly higher temperatures. More accuracy in the interpretation about the origin, and clues on migration pathways and accumulation are obtained integrating geochemical, geological and well data production. This integrated approach gives to the explorationist the best understanding about the "H 2 S risk" in a specific exploratory target. In this work it will be presented a discussion on the methodology for sampling and measuring δ 34 S for identification of H 2 S origin.
Metabolic profiling of complex biological matrices based on liquid chromatography-mass spectrometry (LC-MS) allows detecting a wide range of metabolites with distinct concentrations and physicochemical properties. Given the complexity of samples and the necessity of a comprehensive approach in untargeted metabolomics, quality control strategies are mandatory to obtain high-quality data. The LC-MS performance must be monitored and evaluated to guarantee data reliability. In this study, a test mixture (TM) was developed, systematically evaluated, and applied to untargeted metabolomics of urine samples from individuals suspected of inborn errors of metabolism. The TM was composed of fifteen analytes that eluted across the entire gradient in reversed-phase columns and ionized in positive/negative electrospray modes. It helped set the LC-MS conditions for urine analysis, from sample reconstitution solvent to selecting the MS ion source parameters. The TM quickly indicated column stationary phase degradation during the batch analysis when employed to monitor and evaluate the LC-MS system in an untargeted metabolomic analysis. Thus, in addition to pooled QC samples, a TM can be employed in untargeted metabolomics to rapidly assess the system performance avoiding unnecessary efforts for further data treatment and multivariate analysis of poor-quality data
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