Improved Thyreostatic Drug Detection in Animal Tissues Using Liquid Chromatography-High-Field Asymmetric Waveform Ion Mobility Spectrometry-Mass Spectrometry

Thyreostatic drugs (thyreostats) interfere with thyroid function and have been used illegally in animals slaughtered for food. Thyreostat use leads to poorer quality meat, and the drug residues can cause adverse effects in humans. These drugs, with the exception of thiouracil, do not occur naturally and require sensitive methodologies for their detection in animal tissues. Because thyreostats are low-molecular-weight polar analytes, liquid chromatography-mass spectrometry (LC-MS) is typically used for detection and, in particular, triple quadrupole mass spectrometry with selective reaction monitoring (i.e., LC-SRM). However, LCSRM thyreostat methods suffer from chemical background noise and endogenous interferences arising from the complex tissue matrix. An improved high-field asymmetric waveform ion mobility spectrometry interface (FAIMS Pro), which separates ions based on differential ion mobility, was combined with LC-SRM to minimize these interferences. Using the same samples and conditions, LC-FAIMS-SRM showed improvements in the signal-to-noise ratio (S/N) of up to 50 times compared with our validated LCSRM method. In addition, wider linear ranges, including substantial improvements in the lower limit of quantification (approximately an order of magnitude for tapazole and methylthiouracil), were observed with LC-FAIMS-SRM.

Automated summary

Thyreostatic drugs are illegally used in animals for food production, leading to lower quality meat and potential adverse effects on humans. Detecting these drugs in animal tissues can be challenging due to their low-molecular-weight properties. The study proposes an improved LC-FAIMS-SRM method, which combines liquid chromatography with high-field asymmetric waveform ion mobility spectrometry and selective reaction monitoring. This method demonstrates significant improvements in signal-to-noise ratio and lower limit of quantification compared to the traditional LC-SRM method.