Showing papers by "Nianbai Fang published in 2015"

Matrix effects break the LC behavior rule for analytes in LC-MS/MS analysis of biological samples:

Abstract: High-performance liquid chromatography (HPLC) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) are generally accepted as the preferred techniques for detecting and quantitating analytes of interest in biological matrices on the basis of the rule that one chemical compound yields one LC-peak with reliable retention time (Rt.). However, in the current study, we have found that under the same LC-MS conditions, the Rt. and shape of LC-peaks of bile acids in urine samples from animals fed dissimilar diets differed significantly among each other. To verify this matrix effect, 17 authentic bile acid standards were dissolved in pure methanol or in methanol containing extracts of urine from pigs consuming either breast milk or infant formula and analyzed by LC-MS/MS. The matrix components in urine from piglets fed formula significantly reduced the LC-peak Rt. and areas of bile acids. This is the first characterization of this matrix effect on Rt. in the literature. Moreover, the matrix effect resulted in an unexpected LC behavior: one single compound yielded two LC-peaks, which broke the rule of one LC-peak for one compound. The three bile acid standards which exhibited this unconventional LC behavior were chenodeoxycholic acid, deoxycholic acid, and glycocholic acid. One possible explanation for this effect is that some matrix components may have loosely bonded to analytes, which changed the time analytes were retained on a chromatography column and interfered with the ionization of analytes in the MS ion source to alter the peak area. This study indicates that a comprehensive understanding of matrix effects is needed towards improving the use of HPLC and LC-MS/MS techniques for qualitative and quantitative analyses of analytes in pharmacokinetics, proteomics/metabolomics, drug development, and sports drug testing, especially when LC-MS/MS data are analyzed by automation software where identification of an analyte is based on its exact molecular weight and Rt.