Exploration advantages of data combination and partition: First chemometric analysis of liquid chromatography–mass spectrometry data in full scan mode with quadruple fragmentor voltages

Highlights

• A novel data combination and partition strategy for LC-MS in full scan mode was presented.

• The strategy efficiently avoids a hard chromatographic segmentation in traditional chemometric LC-MS analysis.

• The use of data combination allowed increasing analytical sensitivity and improving significantly the prediction performances.

• The quantitative results from the proposed strategy were compared with the LC-MS/MS method.

Abstract

A novel soft strategy for combination and partition of mass spectra data recorded at different fragmentor voltages in full scan mode of a mass spectrometer was developed to generate abundant multi-way data. It is the first time that non-linear four-way and combined three-way LC-MS data have been obtained simultaneously in a single chromatographic run. This strategy ensures that each analyte can be ionized and detected at the most appropriate MS conditions (ionization modes, fragmentor voltages) and avoids a hard chromatographic segmentation in subsequent chemometric analysis. Two different experimental datasets were analyzed to validate the feasibility and applicability of this strategy. Some simple pretreatments were carried out before LC-MS analysis to prevent potential matrix effects. Proper chemometric tools were used to resolve three-way (partitioned data) and enhanced three-way LC-MS (combined data) data, respectively. The method was assessed by comparing the analytical results obtained from the same chemometric algorithm with both combined and partitioned datasets: (1) the combined data provided the best global overall resolution, higher sensitivity and more reliable results, (2) the partitioned data provided higher selectivity for some specific analytes. The results showed that the developed method could be a soft and ingenious tool to handle the unordered but information-rich raw LC-MS data. Moreover, the proposed strategy could take extra analytical advantages in terms of higher sensitivity and more reliable quantitative results when compared with LC-MS (with single fragmentor voltage) strategy and showed nearly the same capability in analytical quality as classic LC-MS/MS method.

Introduction

Liquid chromatography coupled to mass spectrometry (MS) has long been a popular and powerful analytical tool in use for small molecules quantification and metabolomics studies. Low resolution MS platform techniques such as triple quadrupole (QQQ) and quadrupole-ion trap (QIT) usually have fast scan speed and high sensitivity (such as QQQ), but they can’t often obtain high accurate MS spectra. Due to its characteristics, the classic target analysis based on multiple reaction monitoring (MRM) of a triple quadrupole mass spectrometer is the most commonly used strategy for determination of multiple analytes in complex systems, and has been regarded as the gold standard for its high sensitivity, wide dynamic range, reliable quantification accuracy and stability [1]. However, only a limited number of pre-selected analytes can be quantified by this method. Meanwhile, high resolution full-scan MS platform techniques can obtain high quality MS1 and MS/MS spectra to reliably identify unknown analytes, but the scan speed is relatively slow, which are often applied to untargeted molecules and/or metabolomics analysis and they can theoretically cover all analytes in a sample [2]. So far, many new strategies such as data-dependent acquisition (DDA) [3] and sequential window acquisition of all theoretical spectra (SWATH) [4] have been developed to accommodate this kind of instrument, mainly for qualitative analysis with two conceptual analytical approaches: (i) suspects screening without reference standards; (ii) untargeted screening of unknowns. Based on these, by monitoring both specific precursor ions and characteristic product ions of each metabolite (analyte), a triple quadrupole LC-MS system is frequently used for reliable quantitative analysis of large numbers of metabolites (analytes) in complex systems [5]. And high resolution full-scan MS techniques are often committed to untargeted metabolomics studies including biomarkers discovery, unknown metabolites identification, and the further interpretation of biological processes or mechanisms [6].

Different from these two strategies, the coupling chemometric tools with liquid chromatography coupled to single-quadrupole mass spectrometer (LC-MS) operated in full scan mode have proved to be a prominent and powerful technique for simultaneously determination multi substances which are heavily overlapped and/or strongly co-eluted with unknown interferences in complex systems [[7], [8], [9], [10]]. In that case, no ion isolation is performed and all the ions that elute at a given time are fragmented and detected jointly. A significant benefit of this strategy is that it only needs single-quadrupole mass spectrometers to reach the quantitative goal, by using chemometric algorithms to extract characteristic fragment ions of target analytes for analysis. However, according to the literature published [7,9,10], often a single fragmentor voltage (FV) was utilized in the whole chromatographic run for quantitative analysis. It may be regarded as a compromised and hard strategy as not all analytes can be ionized under the most appropriate MS conditions such as ionization modes and fragmentor voltages. Recently, a novel strategy that used varying fragmentor voltages in chromatographic run was performed for the analysis of mycotoxins in cereal samples [8]. With a simple voltage subdivision strategy, each analyte could be ionized at the optimum mass conditions and the analytical quality such as sensitivity and selectivity could be largely improved. Nevertheless, the applications of multivariate methods in LC-MS resolution are usually conducted by a hard chromatographic segmentation, i.e., windowing or dividing the chromatogram by selecting those regions with known information – compounds – to be resolved [11]. As a result, it is impractical as multi targeted compounds are heavily overlapped in chromatogram therefore splitting compounds on window borders or losing useful information is unavoidable.

Interestingly, we found that real-time quadruple fragmentor voltages could be set as mass spectrometers working in full scan mode, allowing each analyte to be detected at the most appropriate mass conditions. Moreover, a further idea was to combine the LC-MS data recorded at different voltages, instead of treating them independently. It is likely that the information content will be enhanced by a synergistic effect [12]. Strictly speaking, data fusion is a technique which involves the combination of data from different sources or detectors to produce a single model or decision [13]. However, significant differences could be observed for the mass spectra data recorded at different fragmentor voltages. Hence, the data combination and partition strategy we proposed could be considered as one special case of the data fusion approaches. Analogously, several works dealing with the joint use of chemometric tools and data fusion strategies to explore and obtain extra analytical advantages have been published. Pellegrino Vidal combined DAD and FLD data for the chemometric analysis of endocrine disruptors in real water samples, concluding that data fusion of both techniques improved the analytical quality compared with individual detector [12]. Ortiz-Villanueva proposed a knowledge integration data fusion strategy for untargeted metabolomics studies, demonstrating that the joint analysis of the CE-MS and LC-MS platform results enabled better metabolite coverage than without combining the information from both techniques [14].

Hence, in this work, a novel strategy was proposed to combine and partition the MS1 full scan ion peaks recorded at different fragmentor voltages of a mass spectrometer. Throughout the entire chromatographic run, a flexible varying quadruple voltages strategy was adopted, allowing each analyte to obtain highly sensitive and selective analytical results and a hard chromatographic segmentation could be avoided. Three types of LC-MS data including one combined data and two partitioned data, which originated from the raw data, were resolved via chemometric second-order calibration methods characterized by “mathematical resolution”. Two experimental systems including estrogens (entogenous estrogens and xenoestrogens) and small molecules were analyzed and validated, respectively, to explore extra advantages in analytical quality for the combined and partitioned data in chemometric analysis. Estrogens are a group of steroid hormones or analogues which can bring out the feminine characteristics, control reproductive cycles and pregnancy as well as influence bone growth, skin tissues, the cardiovascular system, and immunity [15]. As their high carcinogenicity and teratogenic effects, estrogens exposed to environment have caught wide concern and have been investigated all over the world recently. Amino acids, neurotransmitters and purines are bioactive molecules that play fundamental roles in maintaining various physiological functions [[16], [17], [18], [19], [20], [21]]. Herein, eight small molecule compounds including four amino acids (Glu, Tyr, Phe and Trp), two purines (HX, XA) and two metabolites (Kyn, Kyna) were selected for analysis. The accurate and precise determination of these compounds in biological specimens is a powerful tool to understand the biochemical state of several diseases [[22], [23], [24], [25], [26], [27], [28]]. Moreover, the performance of the proposed strategy was investigated by an overall comparison with the results obtained from combined, partitioned data and from LC-MS/MS method. A schematization of the global chemometric analysis flow is shown in Fig. 1.