Quantification Approaches in Non-Target LC/ESI/HRMS Analysis: An Interlaboratory Comparison

Abstract

Nontargeted screening (NTS) utilizing liquid chromatography electrospray ionization high-resolution mass spectrometry (LC/ESI/HRMS) is increasingly used to identify environmental contaminants. Major differences in the ionization efficiency of compounds in ESI/HRMS result in widely varying responses and complicate quantitative analysis. Despite an increasing number of methods for quantification without authentic standards in NTS, the approaches are evaluated on limited and diverse data sets with varying chemical coverage collected on different instruments, complicating an unbiased comparison. In this interlaboratory comparison, organized by the NORMAN Network, we evaluated the accuracy and performance variability of five quantification approaches across 41 NTS methods from 37 laboratories. Three approaches are based on surrogate standard quantification (parent-transformation product, structurally similar or close eluting) and two on predicted ionization efficiencies (RandFor-IE and MLR-IE). Shortly, HPLC grade water, tap water, and surface water spiked with 45 compounds at 2 concentration levels were analyzed together with 41 calibrants at 6 known concentrations by the laboratories using in-house NTS workflows. The accuracy of the approaches was evaluated by comparing the estimated and spiked concentrations across quantification approaches, instrumentation, and laboratories. The RandFor-IE approach performed best with a reported mean prediction error of 15× and over 83% of compounds quantified within 10× error. Despite different instrumentation and workflows, the performance was stable across laboratories and did not depend on the complexity of water matrices.

Figure 1

Distribution of the selected compounds spiked to the water samples: (a) range of retention times and the response factors of the compounds in a 25 min gradient (see SI 2 - DS_QDF for analysis details), and (b) distribution of the response factors of calibration and suspect compounds.

Figure 2

Prediction errors of each quantification approach across the data sets for sample s1a (high concentrated spike in HPLC water). The green area shows the 10× error and the equivalent log error. Blue boxes are from analysis on orbitrap HRMS, while orange boxes are from analysis on ToF HRMS. The fold errors, calculated according to eq 2, for reported data are displayed in (a), and corresponding log errors, calculated according to eq 3, are shown in (c). (b) and (d) show the corresponding graphs for the reprocessed data.

Figure 3

PCA (first two components) for calibrants and suspects in this study, along with the training compounds for IE-based models and the LC/ESI(+) amenable compounds from NORMAN SusDat (Prob. RPLC ≥ 0.5, Prob. + ESI ≥ 0.5. PCA based on Mordred descriptors.