Comprehensive steroid profiling by liquid chromatography coupled to high resolution mass spectrometry

类固醇 色谱法 化学 葡萄糖醛酸 串联质谱法 质谱法 激素 尿 生物化学
作者
Zied Kaabia,Jérôme Laparre,Nora Cesbron,Bruno Le Bizec,Gaud Dervilly
出处
期刊:The Journal of Steroid Biochemistry and Molecular Biology [Elsevier]
卷期号:183: 106-115 被引量:28
标识
DOI:10.1016/j.jsbmb.2018.06.003
摘要

A steroidomics workflow has been developed in the objective of monitoring a wide range (n >150) of steroids in urine. The proposed workflow relies on the optimization of an adequate SPE extraction step followed by an UHPLC-HRMS/MS simultaneous analysis of both free and conjugated forms of C18, C19 and C21 steroid hormones. On the basis of 44 selected steroids, representative of main classes of steroids constituting the steroidome, the performances of the developed workflow were evaluated in terms of selectivity, repeatability (< 13%) and linearity (R2> 0.985 in the concentration range [0.01–10 ng/mL]). As metabolites identification and characterization constitute the bottleneck of such profiling approaches, a homemade database was created encompassing a large number of characterized free and conjugated steroids (n> 150) for putative steroid-like biomarkers identification purposes. The efficiency of the workflow in highlighting fine modifications within the urinary steroidome was assessed in the frame of an anabolic treatment involving an intra-muscular administration of boldenone undecylenate (2 mg/kg) to veals (n=6) and the investigation of potential steroid biomarkers. Besides monitoring known phase II metabolites of boldenone in the bovine specie, namely, boldenone glucuronide and sulfate, the applied strategy also permitted to observe, upon boldenone administration, a modified profile of epiboldenone glucuronide. Furthermore, 31 signals corresponding to non-identified steroid species could also be highlighted as impacted upon the exogenous steroid treatment. This study is the first to simultaneously investigate both free and conjugated C18, C19 and C21 steroid hormones in their native form using UHPLC-HRMS/MS and allowing their comprehensive profiling. This strategy was probed in-vivo.
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