N,O-bis(trimethylsily)trifluoroacetamide (BSTFA) and N-methyl-N(trimethylsily) trifluoroacetamide (MSTFA) are common derivatization reagents used in the GC-MS analysis of estrogen steroids such as estrone (El) and 17alpha-ethinylestradiol (EE2). In this study, three trimethylsilyl (TMS) steroid derivatives, mono- and di-trimethylsilyl EE2 and mono-trimethylsilyl E1, were observed during the derivatization of EE2 with BSTFA or MSTFA and/or GC separation. Factors influencing the production of multiple TMS derivatives and their relative abundance were examined. It was found that both methanol and bisphenol A competed with estrogenic esteroids when reacting with silylation reagents, and thus affected the formation of TMS derivatives and their relative abundance in the derivatization products. Methanol was found to be more reactive than bisphenol A with the BSTFA reagent. None of the three solvents tested in this study could prevent the generation of multiple TMS derivatives during the derivatization of EE2 with BSTFA, followed by GC analysis. A similar result was observed using MSTFA as the derivative reagent followed by GC analysis. Thus, the suitability of BSTFA or MSTFA as the derivatization reagent for the determination of E1 and EE2 by GC-MS, under the conditions reported here, is questionable. This problem can be solved by adding trimethylsilylimidaz (TMSI) in the BSTFA reagent as recommended, and the performance of the method has been proved in this study.
"Prior GC/MS analysis is necessary to carry out steroid derivatization to increase the volatility and thermal stability of the molecules and to improve chromatographic separation and detection. For GC, the preferable derivatization technique remains silylation [Zhou et al., 2007] and most frequently used reagents include N,O-bis(trimethylsilyl), trifluoroacetamide, and N-methyl-N-trimethylsilyltrifluoroacetamide, trimethyliodosilane , trimethylsilylimidazole, and trimethylchlorosilane . Derivatization is aimed at the formation of alkylsilyl derivatives through displacement of active protons in –OH or -NH groups. "
[Show abstract][Hide abstract] ABSTRACT: Metabolomics is a discipline that concentrates on the global assessment of endogenous metabolites present in a biological system. Metabolic profiling has been applied to cells, tissues, and/or biofluids in order to evaluate disease progress, broaden the understanding of the disorder, and to select potential biomarkers. Steroid hormones play an important role in the regulation of routine functions in the human body, and their measurement in biological samples is essential for the diagnosis of various endocrine disorders. The present overview describes various strategies and analytical techniques applied in metabolomic studies, particularly with reference to the steroid metabolic profiling useful for the search of novel biomarkers. Drug Dev Res 73 : 381–389, 2012.
Drug Development Research 11/2012; 381–389(7):381–389. DOI:10.1002/ddr.21028 · 0.77 Impact Factor
"The eluate was concentrated, derived with BSTFA/TCMS/TMSI (99:1:0.5, v/v/v). The separation and detection of the target compounds were achieved by GCeMS using selected-ion mode based on the method from Zhou et al. (2007) "
[Show abstract][Hide abstract] ABSTRACT: Assignment of ecological impacts of contamination to specific classes of contaminants is a prerequisite for risk assessment and remediation. In this study, the combination of polarity-based fractionation, two-hybrid yeast bioassay, and chemical analysis were used to evaluate and identify estrogen receptor agonists (ER-agonists) in sediments from Wenyu River, Beijing, China. By bioassay, organic raw sediment extracts could induce significant estrogenicity and the bioassay-derived 17β-estradiol equivalents (EEQs) of raw extracts (EEQ(raw)s) ranged from 0.8 to 19.8 ng/g dry weight. By polarity-based fractionation, the raw extracts were separated into three fractions, i.e. non-polar, moderately polar, and polar fractions, which were subjected to bioassay and chemical analysis. The highest estrogenicity was observed in the polar fraction, which accounted for more than 78% of the total. The medium polar fraction contains PAHs and OCPs, and the estrogenic activities in this fraction contributed 3%-12% of the total in raw extract. An estrogenic activity of non-polarity fraction was negligible in compare to other two fractions. By chemical analysis and toxic equivalent calculation, major part of the estrogenicity in polar fraction could be attributed to six natural/synthetic estrogens (16%-63%), i.e. 17β-estradiol, estrone, estriol, 17α-ethynylestradiol, diethylstilbestrol, and β-estradiol-17-valerate, and to nonylphenols (26%-55%). The proposed approach has been successfully used for characterization of ER-agonists in this case study.
Water Research 07/2011; 45(13):3908-14. DOI:10.1016/j.watres.2011.04.045 · 5.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The occurrence of estrogens in the aquatic environment attracts increasing attention because of their strong endocrine disrupting potency. In the present work, concentrations of six estrogens including diethylstilbestrol (DES), estrone (E1), beta-estradiol (E2), estriol (E3), 17alpha-ethynylestradiol (EE2) and beta-estradiol 17-valerate (EV) in surface water and sediment sampled from three rivers in Tianjin area, northern China, were determined by gas chromatography-mass spectrometry (GC-MS). The concentrations of all six estrogens (Sigma6ES) ranged from 0.64 to 174 ng L(-1) in waters and from 0.98 to 51.6 ng g(-1) dry weight (dw) in sediments, and varied for each river. Among these estrogens, E1 was the most abundant and could be detected in all samples. DES and EV could be detected either in river water or in sediment, but in the concentration below 10 ng L(-1) and 10 ng g(-1) for water and sediment, respectively. The relationships between concentration of estrogens and organic carbon content in sediments and the relationships between sediment-water partition coefficient (logK(oc)) and octanol-water partition coefficient (logK(ow)) were examined. The results showed that the contents of the Sigma6ES correlated significantly with the contents of organic carbon (OC%). It indicated that sediments with high organic carbon were more likely to retain estrogens than those with lower organic carbon levels in the natural aquatic environment. Furthermore, the linear correlations between logK(ow) and logK(oc) were obtained for each river, which indicated that sediment-water partitioning of estrogens in three rivers could be predicted by their hydrophobic properties.
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