This research focuses on improving the detection of trace amines, a group of naturally occurring molecules involved in brain signaling, metabolism, and cancer progression. Trace amines—such as phenylethylamine and tyramine—exist at concentrations far lower than most other biological compounds, making them difficult to measure reliably. They are also chemically unstable, which increases the risk of degradation during analysis.
To address these challenges, the researchers developed an ultrasensitive analytical strategy combining chemical labeling with advanced mass spectrometry. The key step is N-phosphorylation labeling, a chemical modification that attaches a small tag to trace amines. This tag serves two purposes: it stabilizes the molecules and dramatically increases their detectability during mass spectrometry analysis.
The labeled samples are then analyzed using chip-based two-dimensional liquid chromatography coupled with triple-quadrupole mass spectrometry (chip 2D LC-QQQ/MS). In simple terms, this system differentiates molecules more efficiently and determines them with exceptional sensitivity. Together, these improvements increased detection sensitivity by up to 5,500 times compared with conventional methods.
The researchers applied this technique to study trace amines and related metabolites in liver cancer cells treated with sorafenib, a commonly used anti-cancer drug. The analysis revealed significant changes in trace-amine levels and associated metabolic pathways, particularly those related to phenylalanine and tyrosine metabolism. These findings suggest that trace amines may play an underappreciated role in how cancer cells respond to treatment.
The impact of this research is twofold. Methodologically, it provides a powerful and reliable tool for studying trace-level metabolites that were previously difficult or impossible to quantify. Biologically, it opens new opportunities to explore how trace amines contribute to disease mechanisms, drug responses, and potential diagnostic markers. By making the invisible measurable, this approach advances both analytical science and biomedical research.
Reference
X. Bian, Y. Zhang, N. Li, M. Shi, X. Chen, H.-L. Zhang, J. Liu, and J.-L. Wu, “Ultrasensitive quantification of trace amines based on N-phosphorylation labeling chip 2D LC-QQQ/MS,” Journal of Pharmaceutical Analysis, vol. 13, pp. 315–322, 2023, doi: 10.1016/j.jpha.2023.02.003.
