Date: 28 Sep 2010

High-Throughput Sample Preparation for the Quantitation of Acephate, Methamidophos, Omethoate, Dimethoate, Ethylenethiourea, and Propylenethiourea in Human Urine Using 96-Well–Plate Automated Extraction and High-Performance Liquid Chromatography–Tandem Mass Spectrometry

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Abstract

Acephate, methamidophos, o-methoate, and dimethoate are organophosphorus pesticides, and ethylenethiouria and propylenethiourea are two metabolites from the bisdithiocarbamate fungicide family. They are some of the most widely used pesticides and fungicides in agriculture both domestically and abroad. The existing high-performance liquid chromatography (HPLC)–tandem mass spectrometry (MS/MS) method for the measurement of these compounds in human urine was improved by using a 96-well plate format sample preparation; the use of HPLC-MS/MS was comparable with a concentration range of 0.125 to 50 ng/ml. Deuterium-labeled acephate, ethylenethiouria, and methamidophos were used as internal standards. The sample preparation procedure, in the 96-well format with a 0.8-ml urine sample size, uses lyophilization of samples, followed by extraction with dichloromethane. The analytes were chromatographed on a Zorbax SB-C3 (4.6 × 150 mm, 5.0-μm) column with gradient elution by using 0.1% formic acid in aqueous solution (solvent A) and 0.1% formic acid in methanol (solvent B) mobile phase at a flow rate of 1 ml/min. Quantitative analysis was performed by atmospheric pressure chemical ionization source in positive ion mode using multiple-reaction monitoring of the precursor-to-product ion pairs for the analytes on a TSQ Quantum Ultra HPLC-MS/MS. Repeated analyses of urine samples spiked with high (15 ng/ml), medium (5 ng/ml), and low (1 ng/ml) concentrations of the analytes gave relative SDs of <13%. The limits of detection were in the range of 0.004–0.01 ng/ml. The method also has high accuracy, high precision, and excellent extraction recovery. Furthermore, the improved sample preparation method decreased the cost and labor required while effectively doubling the analytic throughput with minimal matrix effect.