Comparison of standard- and nano-flow liquid chromatography platforms for MRM-based quantitation of putative plasma biomarker proteins.

The analytical performance of a standard-flow ultra-high-performance liquid chromatography (UHPLC) and a nano-flow high-performance liquid chromatography (HPLC) system, interfaced to the same state-of-the-art triple-quadrupole mass spectrometer, were compared for the multiple reaction monitoring (MRM)-mass spectrometry (MS)-based quantitation of a panel of 48 high-to-moderate-abundance cardiovascular disease-related plasma proteins. After optimization of the MRM transitions for sensitivity and testing for chemical interference, the optimum sensitivity, loading capacity, gradient, and retention-time reproducibilities were determined. We previously demonstrated the increased robustness of the standard-flow platform, but we expected that the standard-flow platform would have an overall lower sensitivity. This study was designed to determine if this decreased sensitivity could be compensated for by increased sample loading. Significantly fewer interferences with the MRM transitions were found for the standard-flow platform than for the nano-flow platform (2 out of 103 transitions compared with 42 out of 103 transitions, respectively), which demonstrates the importance of interference-testing when nano-flow systems are used. Using only interference-free transitions, 36 replicate LC/MRM-MS analyses resulted in equal signal reproducibilities between the two platforms (9.3 % coefficient of variation (CV) for 88 peptide targets), with superior retention-time precision for the standard-flow platform (0.13 vs. 6.1 % CV). Surprisingly, for 41 of the 81 proteotypic peptides in the final assay, the standard-flow platform was more sensitive while for 9 of 81 the nano-flow platform was more sensitive. For these 81 peptides, there was a good correlation between the two sets of results (R(2) = 0.98, slope = 0.97). Overall, the standard-flow platform had superior performance metrics for most peptides, and is a good choice if sufficient sample is available.