Nanoelectrospray Mass Spectrometry and Precursor Ion Monitoring for Quantitative Steroid Analysis and Attomole Sensitivity

Abstract

Nanoelectrospray ionization (nanoESI) mass spectrometry was performed on naturally occurring steroid sulfates and unconjugated steroids derivatized to their sulfate esters using precursor ion monitoring. Initially, an extraction method was developed based on a combinatorial approach employed to obtain the most efficient liquid/liquid extraction protocol. The new method allowed unconjugated steroids and their sulfated analogues to be isolated separately in a two-step procedure using diethyl ether/hexane (90:10, v/v) in the first step to extract the unconjugated steroids and chloroform/2-butanol (50:50, v/v) in the second step to extract steroid sulfates. Precursor ion scanning performed with a triple-quadrupole mass spectrometer was used to examine quantitatively the extracted unconjugated and sulfated steroids, where the recovery efficiency averaged 70 and 87%, respectively. In addition, some steroids could be structurally elucidated by employing tandem mass spectrometry. The limit of detection for steroid sulfates from the biological matrix was 200 amol/microL (approximately 80 fg/microL) with only 1 microL of sample being injected. Endogenous levels of the unconjugated and sulfated steroids were detected and quantified from physiological samples including urine and blood. Internal standards, pregnenolone-d4 sulfate and dehydroepiandrosterone-d2 (DHEA), were used for quantitation. Extraction and nanoESI analyses were also performed on cerebrospinal fluid where the neurosteroid DHEA sulfate was detected. The small amount of material consumed (typically less than 20% of the injection volume) suggests that nanoESI has even greater potential for high sensitivity when combined with nanoLC approaches, especially for monitoring reproductive and adrenal steroids, as well as for the analysis of the less abundant neurosteroids.

Nanoelectrospray Mass Spectrometry and Precursor Ion Monitoring for Quantitative Steroid Analysis and Attomole Sensitivity

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Abstract

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