Spectral Counting Approach to Measure Selectivity of High-Resolution LC-MS Methods for Environmental Analysis

Advances in high-resolution mass spectrometers have allowed for the development of nontargeted screening methods, where data sets can be archived and retrospectively mined as new environmental contaminants are identified. We have developed a spectral counting approach to calculate the selectivities of LC-MS acquisition modes taking mass accuracy, sample matrix, and the analyte properties into account. The selectivities of high-resolution MS (HRMS) alone or in combination with all-ion-fragmentation (AIF), data-independent-acquisition (DIA), and data-dependent-acquisition (DDA) modes, performed on a Q-Exactive Orbitrap were compared by retrospectively screening surface water samples for 95 pharmaceuticals. Samples were reanalyzed using targeted LC-MS/MS to confirm the accuracy of each acquisition method and to quantitate the 29 putatively detected drugs. LC-HRMS provided the lowest calculated selectivities and accordingly produced the highest number of false positives (6). In contrast, DDA provided the highest selectivities, yielding only one false positive; however, it was bias toward the most intense signals resulting in the detection of only 10 compounds. AIF had lower selectivities than traditional LC-MS/MS, produced one false positive and did not detect 6 confirmed compounds. Because of the high-quality archived data, DIA selectivities were better than traditional LC-MS/MS, showed no bias toward the most intense signals, achieved low limits of detection, and confidently detected the greatest number of pharmaceuticals (22) with only one false positive. This spectral counting method can be used across different instrument platforms or samples and provides a robust and empirical estimation of selectivities to give more confident detection of trace analytes.