Dataset Information

Improving the Screening Analysis of Pesticide Metabolites in Human Biomonitoring by Combining High-Throughput In Vitro Incubation and Automated LC-HRMS Data Processing

ABSTRACT: There is a current need to monitor human exposure to a large number of pesticides and other chemicals of emerging concern (CECs). This requires screening analysis with high confidence for these compounds and their metabolites in complex matrices, which is hampered by the fact that no reference standards are available for most metabolites. We address this challenge by a high-throughput workflow based on incubation of pesticides (or other CECs) with human liver S9, followed by solid-phase extraction, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) analysis, and automated data processing to generate a database (retention time, precursor m/z, and MS² spectral library) for the annotation in human samples. The metabolite prioritization consists of statistical comparisons and mass defect and m/z range filtering to obtain a subset of probable phase I metabolites, for which molecular formulas and likely metabolic transformation are retrieved. We tested the workflow on 22 pesticides, for which we could determine 91 metabolite molecular formulas which are only partly covered by the literature and/or predicted by in silico metabolization. Our workflow allows for an efficient generation of metabolite reference information, which can be used directly for annotating LC-HRMS data from human samples. A full structure elucidation of individual metabolites can be limited to those being actually present in human samples.

INSTRUMENT(S): Liquid Chromatography MS - negative - reverse phase, Liquid Chromatography MS - positive - reverse phase

SUBMITTER: Carolin Huber

PROVIDER: MTBLS2402 | MetaboLights | 2022-01-17

REPOSITORIES: MetaboLights

ACCESS DATA

Publications

Improving the Screening Analysis of Pesticide Metabolites in Human Biomonitoring by Combining High-Throughput <i>In Vitro</i> Incubation and Automated LC-HRMS Data Processing.

Huber Carolin C Müller Erik E Schulze Tobias T Brack Werner W Krauss Martin M

Analytical chemistry 20210623 26

There is a current need to monitor human exposure to a large number of pesticides and other chemicals of emerging concern (CECs). This requires screening analysis with high confidence for these compounds and their metabolites in complex matrices, which is hampered by the fact that no reference standards are available for most metabolites. We address this challenge by a high-throughput workflow based on incubation of pesticides (or other CECs) with human liver S9, followed by solid-phase extracti ...[more]

PMID: 34161736

Similar Datasets

Project description:Photosynthetic diatoms are exposed to rapid and unpredictable changes in irradiance and spectral quality, and must be able to adapt their light harvesting systems to varying light conditions. Molecular mechanisms behind light acclimation in diatoms are largely unknown. We set out to investigate the mechanisms of high light acclimation in Phaeodactylum tricornutum using an integrated approach involving global transcriptional profiling, metabolite profiling and variable fluorescence technique. Algae cultures were acclimated to low light (LL), after which the cultures were transferred to high light (HL). Molecular, metabolic and physiological responses were studied at time points 0.5 h, 3 h, 6 h, 12 h, 24 h and 48 h after transfer to HL conditions. The integrated results indicate that the acclimation mechanisms in diatoms can be divided into an initial response phase (0.5 h), an intermediate acclimation phase (3-12 h) and a late acclimation phase (12-48 h). The initial phase is recognized by strong and rapid regulation of genes encoding proteins involved in photosynthesis, pigment metabolism and reactive oxygen species (ROS) scavenging systems. A significant increase in light protecting metabolites occur together with the induction of transcriptional processes involved in protection of cellular structures at this early phase. During the following phases, the metabolite profiling display a pronounced decrease in light harvesting pigments, whereas the variable fluorescence measurements show that the photosynthetic capacity increases strongly during the late acclimation phase. We show that P. tricornutum is capable of swift and efficient execution of photoprotective mechanisms, followed by changes in the composition of the photosynthetic machinery that enable the diatoms to utilize the excess energy available in HL. Central molecular players in light protection and acclimation to high irradiances have been identified. The experiment was designed as a time series, with diatom cultures were harvested at time points 0.5 h, 3 h, 6 h, 12 h, 24 h and 48 h after transfer to high light conditions. The reference samples were kept at low light and harvested in parallel with the treated samples. Three biological replicates were harvested for all samples.

Project description:CoMet, a fully automated Computational Metabolomics method to predict changes in metabolite levels in cancer cells compared to normal references has been developed and applied to Jurkat T leukemia cells with the goal of testing the following hypothesis: up or down regulation in cancer cells of the expression of genes encoding for metabolic enzymes leads to changes in intracellular metabolite concentrations that contribute to disease progression. Nine metabolites predicted to be lowered in Jurkat cells with respect to normal lymphoblasts were examined: riboflavin, tryptamine, 3-sulfino-L-alanine, menaquinone, dehydroepiandrosterone, Î±-hydroxystearic acid, hydroxyacetone, seleno-L-methionine and 5,6-dimethylbenzimidazole. All, alone or in combination, exhibited antiproliferative activity. Of eleven metabolites predicted to be increased or unchanged in Jurkat cells, only two (bilirubin and androsterone) exhibited significant antiproliferative activity. These results suggest that cancer cell metabolism may be regulated to reduce the intracellular concentration of certain antiproliferative metabolites, resulting in uninhibited cellular growth and have the implication that many other endogenous metabolites with important roles in carcinogenesis are awaiting discovery. Experiment Overall Design: The first step of the CoMet approach consists of the classification of each enzyme-coding human gene into four possible groups: G1) upregulated in cancer cells, G2) downregulated in cancer cells, G3) expressed in both, normal and cancer cells, at levels that are statistically indistinguishable, and G4) not expressed in both, normal and cancer cells. We used two types of data for the classification: the log base 2 signal intensities and the presence calls of the corresponding probe sets, as reported by the Affymetrix Microarray Suite Software 5.0 (MAS 5.0). First, an â??offâ?? status is provisionally assigned to each gene in each of the two studied conditions (normal and cancer) if the mean fraction of presence calls labeled as â??marginalâ?? or â??absentâ?? in the corresponding probe sets is at least 80%; otherwise, an â??onâ?? status is assigned. Then, each gene is temporarily classified into the G1, G2, G3 or G4 group, according to its on/off status in normal and cancer conditions. Finally, genes in the temporary G3 or G4 groups are transferred to the G1 or G2 groups if they fulfill the following criterion for differential expression: the signal intensities in normal and cancer samples exhibit a statistically significant difference in at least 40% of the corresponding probe sets, as evaluated by an ANOVA two-tailed test with P < 0.005. Experiment Overall Design: RNA extraction, amplification and microarray data processing. Total RNA was extracted from cell lines using Trizol (Invitrogen) and processed using the RiboAmp OA or HS kit (Arcturus) in conjunction with the IVT Labeling Kit from Affymetrix, to produce an amplified, biotin-labeled mRNA suitable for hybridizing to GeneChip Probe Arrays (Affymetrix). Labeled mRNA was hybridized to GeneChip Human Genome U133 Plus 2.0 Arrays in the GeneChip Hybridization oven 640, further processed with the GeneChip Fluidics Station 450 and scanned with the GeneChip Scanner. Affymetrix .CEL files were processed using the Affymetrix Expression Console (EC) Software Version 1.1. Files were processed using the default MAS5 3â?? expression workflow which includes scaling all probes to a target intensity (TGT) of 500. Spiked in report controls used were AFFX-BioB, AFFX-BioC, AFFX-BioDn, and AFFX-CreX. Affymetrix .CEL files for three normal lymphoblast samples used as a normal reference to compare Jurkat cells expression data were directly retrieved from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/, samples GSM113678, GSM113802 and GSM113803 of untreated GM15851 cells from the Series GSE5040).

Dataset Information

Improving the Screening Analysis of Pesticide Metabolites in Human Biomonitoring by Combining High-Throughput In Vitro Incubation and Automated LC-HRMS Data Processing

Publications

Improving the Screening Analysis of Pesticide Metabolites in Human Biomonitoring by Combining High-Throughput <i>In Vitro</i> Incubation and Automated LC-HRMS Data Processing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure