Probing Liquid Chromatography–Tandem Mass Spectrometry Response Dynamics and Nonlinear Effects for Response Level Defined Calibration Strategies with Simple Methods To Expand Linear Dynamic Ranges

Abstract

The response characteristics of liquid chromatography−tandem mass spectrometry (LC−MS/MS) serve as the basis for selecting calibration methods in quantitative analysis. LC−MS/MS inherently exhibits nonlinear detection behavior, primarily attributed to the disproportionate growth observed between peak area and peak height at elevated response levels, potentially leading to signal saturation. This disproportionate peak growth results in reduced unit response (UR), which quantifies the instrument's detection sensitivity. LC−MS/MS typically operates within a narrow near-linear response range (NLRR) due to approximately proportional peak growth, yet the NLRR width varies across different analytes or platforms. Although the inclusion of stable isotope-labeled (SIL) internal standards (IS) in LC−MS/ MS analysis can mitigate certain instrument response variations, it does not eliminate the fundamental cause of nonlinearity. Moreover, the concentration range accommodated by the NLRR can significantly fluctuate at different sensitivity levels. LC−MS/ MS also encounters various other nonlinear effects, including ion suppression during ionization, signal cross-contribution between the analyte/IS, and matrix effects (ME). Consequently, quadratic regression emerges as a more adaptable approach to LC−MS/MS nonlinear response dynamics, offering a broader calibration range. The application of linear regression, on the other hand, requires strict conditions. Although the signal saturation zone typically remains inaccessible to calibration methods, reducing responses by employing less-optimal selected reaction monitoring (SRM) transitions and/or lower detection gain can facilitate fitting a wide concentration range into the NLRR, thereby enabling accurate linear regression calibration. This report delves into examining the LC−MS/MS response profile, its dynamics, and major nonlinear effects through instrument response mapping to elucidate their influence on the selection of calibration methods.