Development of a new HPLC-based method for 3-nitrotyrosine quantification in different biological matrices

- Increased protein nitration is associated with physiological conditions.
- 3-NT has been proposed for therapeutic monitoring of pathologies with nitrosative stress.
- The method was successfully applied to 3-NT quantification in all biological matrices tested.

BackgroundThe nitration of tyrosine residues in proteins is associated with nitrosative stress, resulting in the formation of 3-nitrotyrosine (3-NT).1 3-NT levels in biological samples have been associated with numerous physiological and pathological conditions. Hence several attempts have been made in order to develop methods that accurately quantify 3-NT in these matrices. The aim of this study was to develop a simple, rapid, low-cost and sensitive high-performance liquid chromatography (HPLC)-based 3-NT quantification method.MethodsAll experiments were performed on an Hitachi LaChrom Elite® HPLC system. The method was validated according to International Conference on Harmonisation (ICH) guidelines for serum samples. Additionally, other biological matrices were tested, namely whole blood, urine, B16 F-10 melanoma cell line, growth medium conditioned with the same cell line, bacterial and yeast suspensions.ResultsFrom all the protocols tested, the best results were obtained using 0.5% CH3COOH:MeOH:H2O (15:15:70) as mobile phase, with detection at wavelengths 215, 276 and 356 nm, at 25 °C, and using a flow rate of 1 mL min−1. By using this protocol, it was possible to obtain a linear calibration curve, limits of detection and quantification in the order of μg L−1, and a short analysis time (<15 min per sample). The developed protocol allowed the successful detection and quantification of 3-NT in all biological matrices tested, with detection at 356 nm.ConclusionThis method, successfully developed and validated for 3-NT quantification, is simple, cheap and fast. These features render this method a suitable option for analysis of a wide range of biological matrices, being a promising useful tool for both research and diagnosis activities.