AUTHOR=Kumar Dinesh , Azad Ramiz M. R. , Oulkar Dasharath , Oberoi Harinder Singh , Jacob Sanu , Koner B. C. , Sonkar S. C. 

TITLE=A quantification method for trace level of oxytocin in food matrices using LC-MS/MS

JOURNAL=Frontiers in Analytical Science

VOLUME=2

YEAR=2022

URL=https://www.frontiersin.org/journals/analytical-science/articles/10.3389/frans.2022.1039606

DOI=10.3389/frans.2022.1039606

ISSN=2673-9283

ABSTRACT=<p><bold>Backgrounds:</bold> Oxytocin is nowadays used to increase the agricultural products besides its use during the milking of cattle leading to the contamination of agricultural produce and milk with oxytocin. Monitoring of accurate oxytocin contaminations from foodstuffs is sometimes required to maintain the quality standard. The commonly used oxytocin assays in this study were interfered with by the food matrix. There is a need to develop an accurate and confirmed method for monitoring oxytocin contaminations in foodstuffs.</p><p><bold>Objective:</bold> An attempt is made to develop an accurate assay method of oxytocin from milk and agricultural produces.</p><p><bold>Methods:</bold> The acidified methanol was used for the extraction of oxytocin from target food stuff/matrices (agricultural produce and Milk). LC-MS/MS was used for its detection and quantification. In the chromatographic separation, Oxytocin concentration was optimized using selective reaction monitoring (SRM) with heated electrospray ionization (HESI) in positive polarity. The chromatographic separation was performed using a reversed-phase C<sub>18</sub> column with gradient elution at a flow rate of 0.4 ml/min. The acidified methanol was used for the extraction of oxytocin in all target food matrices. The method performance was verified as per the SANTE 2021 guideline. After method validation, the method was applied in real food samples analysis for assessing the presence/absence of oxytocin.</p><p><bold>Results:</bold> The calibration curve offered excellent linearity (<italic>R</italic><sup>2</sup> = 0.999) with less than 15% residuals. The matrix effect was &lt;20% observed for all target matrices. The mean recoveries were within 70%–115% with &lt;11% RSD at four different levels in milk and 0.01 mg/kg in fruits and vegetables. The optimized method was applied to 50 random samples of milk, fruits, and vegetables from the market for the purposes of an established quality control approach. Based on the results, we did observe a signal of oxytocin in the random samples Therefore, this method has shown its practical suitability for the detection of oxytocin in milk, fruits, and vegetables.</p><p><bold>Conclusion:</bold> Extraction of oxytocin using acidified methanol followed by assays using LC-MS/MS is a simple, sensitive, accurate, reproducible, and practically suitable method for detection and quantification of oxytocin from milk, fruits, and vegetables.</p>