Elsevier

Analytica Chimica Acta

Volume 1026, 5 October 2018, Pages 87-100
Analytica Chimica Acta

A high-resolution HPLC-QqTOF platform using parallel reaction monitoring for in-depth lipid discovery and rapid profiling

https://doi.org/10.1016/j.aca.2018.03.062Get rights and content

Highlights

  • A lipidomics workflow merging targeted and untargeted approaches using PRM strategy.

  • Discovery of 2349 unknown features and 634 known lipid species in barley roots.

  • Rapid profiling of 291 species based on MS/MS data by a single injection using sPRM.

  • An application of the workflow on salt stress-induced lipid changes in barley roots.

Abstract

Here, we developed a robust lipidomics workflow merging both targeted and untargeted approaches on a single liquid chromatography coupled to quadrupole-time of flight (LC-QqTOF) mass spectrometry platform with parallel reaction monitoring (PRM). PRM assays integrate both untargeted profiling from MS1 scans and targeted profiling obtained from MS/MS data. This workflow enabled the discovery of more than 2300 unidentified features and identification of more than 600 lipid species from 23 lipid classes at the level of fatty acid/long chain base/sterol composition in a barley root extracts. We detected the presence of 142 glycosyl inositol phosphorylceramides (GIPC) with HN(Ac)-HA as the core structure of the polar head, 12 cardiolipins and 17 glucuronosyl diacylglycerols (GlcADG) which have been rarely reported previously for cereal crops. Using a scheduled algorithm with up to 100 precursors multiplexed per duty cycle, the PRM assay was able to achieve a rapid profiling of 291 species based on MS/MS data by a single injection. We used this novel approach to demonstrate the applicability and efficiency of the workflow to study salt stress induced changes in the barley root lipidome. Results show that 221 targeted lipids and 888 unknown features were found to have changed significantly in response to salt stress. This combined targeted and untargeted single workflow approach provides novel applications of lipidomics addressing biological questions.

Introduction

Lipidomics is an emerging technology and a branch of metabolomics which aims at the global characterisation and quantification of lipids within biological matrices including biofluids, cells, whole organs and tissues [1]. In the past 15 years, the field of lipidomics has been largely driven by advances in modern analytical techniques, especially mass spectrometry. Targeted and untargeted lipidomics are the two major approaches used in mass spectrometry-based lipidomics. Untargeted lipidomics involves a non-biased screening of all the potential lipids in a sample but is often limited in sensitivity and selectivity. By contrast, targeted lipidomics is both sensitive and accurate for lipid analysis, but focuses only on expected (or known) lipid species while unknown lipid species are not detected [2]. To reveal the suite of differences between lipids and other metabolites, a combination of different platforms and techniques is often employed [3,4]. Traditionally, a targeted strategy is achieved by employing multiple reaction monitoring (MRM) on a triple quadrupole (QqQ) or quadrupole linear-ion trap (QTRAP) coupled to high performance liquid chromatography (HPLC) or ultra-high performance liquid chromatography (UHPLC) [2]. Untargeted lipidomics techniques employ high-resolution mass spectrometers (HRMS) including TOF, FT-ICR or Orbitrap platforms with high resolution and high mass accuracy to resolve isobaric lipid species which have the same nominal mass but different exact masses [2,4]. However, one limiting factor of using multiple platforms is the high economic cost of maintaining and operating several instruments, as well as the computationally more demanding integration of datasets from different platforms. In addition, different instrumental conditions and parameters used for ionization and fragmentation during MS/MS can lead to severe difficulties when integrating targeted and untargeted data.

Parallel reaction monitoring (PRM), also referred to as high-resolution multiple reaction monitoring (MRM-hr), is an example of a recently developed acquisition strategy to integrate targeted and untargeted data by combining HPLC with quadrupole-equipped HRMS [5]. In a PRM assay, a duty circle in the MS is often initiated with a MS1 survey scan followed by a series of targeted MS/MS experiments. The MS1 survey collects untargeted high-resolution mass spectra enabling profiling of all precursors across a large m/z range (approximately 50–2000 m/z). A MS/MS experiment in PRM mode isolates a preset precursor ion in the quadrupole and detects all product ions generated from collision-induced dissociation (CID) on the HRMS [6]. PRM has been shown to successfully enable quantitative studies in both proteomics and metabolomics applications [5,[7], [8], [9]]. Very recently, Zhou et al. used a SCIEX 4600 TripleTOF™ system to monitor 222 lipid species from 15 lipid classes in human serum in PRM mode [10]. Compared with traditional MRM on QqQ instruments, PRM offers more accurate m/z and narrower peak width of ions in MS spectra. The high resolution and mass accuracy of the resulting MS/MS spectra enables more precise identification of product ions of the corresponding precursor ion. Moreover, with full MS/MS spectra obtained in PRM mode, selection of fragment ions for targeted profiling can be determined post data acquisition. Intensities of multiple fragment ions can also be summed to achieve better sensitivity [5].

One of the weaknesses of targeted analysis by MS/MS experiments in PRM is the low scan rate which limits the capability of MS/MS experiments when performed on a large-scale [8,11]. Recent technological advances have included increased scan and data acquisition rates on quadrupole time-of-flight mass spectrometry (QqTOF) instruments to allow for multiplexing large-scale numbers of precursors [11,12]. The latest SCIEX TripleTOF™ 6600 QqTOF can deliver up to 100 MS/MS experiments per duty cycle with high sensitivity and resolution achieving considerable throughput gains in targeted monitoring [11]. Furthermore, implementing retention time (RT) scheduling significantly increases the capacity for targeting compounds during a whole LC chromatogram [8,13]. In scheduled acquisition, each compound is monitored for a short period of time in a specific time window around the expected RT. This expands the total number of overall precursors that can be monitored in a single LC-MS run without sacrificing accumulation or duty cycle time.

In previous PRM applications, the MS1 survey scan was often used only as a complementary profiling strategy [9]. To exploit the full potential of MS1 scans, a greater number of mass features with specific RTs, m/z and intensities can be extracted and used to produce a global lipid profile of the whole sample extract.

Lipids are important signaling messengers and membrane structural regulators that play roles in many plant responses, including those to abiotic stresses such as salinity and drought [[14], [15], [16]]. Barley is one of the most salt-tolerant cereal crops and has been used as a model plant to study salt stress in recent years [17]. Natera et al. studied salt-induced lipid compositional changes of two barley varieties differing in their ability to tolerate salinity [18]. A total of 708 mass features were extracted from untargeted HPLC-ESI-QqTOF analysis and 64 lipid species quantified by HPLC-ESI-QqQ analysis were compared. A range of alterations induced by salt stress were observed particularly for glycerophospholipids.

In our study, we demonstrate the applicability of parallel analysis of untargeted and targeted lipidomics by taking advantage of both untargeted profiling by MS1 and targeted analysis by MS/MS experiments. This novel approach enables the discovery of a large number of unidentified lipid species, while simultaneously identifying fatty acid composition and the head group of most of the lipid species. In addition, this robust lipidomics platform using sPRM mode on a HPLC-ESI-QqTOF was established to achieve comprehensive lipidome investigation of barley root extracts and to apply the platform to the study of plant salinity stress.

Section snippets

Lipid nomenclature and abbreviations

Lipid nomenclature used across the manuscript follows the “Comprehensive Classification System for Lipids” presented by the International Lipid Classification and Nomenclature Committee (ILCNC) [19]. The nomenclature can be viewed online on the LIPID MAPS website (http://www.lipidmaps.org/data/classification/LM_classification_exp.php). However, structural information gained from mass spectrometry is usually insufficient to cover the precise structural information of LIPID MAPS nomenclature,

Optimization of chromatography conditions

The lipid separation was carried out on reversed phase columns with mobile phases modified from a previously developed lipidomics platform by Tarazona et al. [3]. To improve compatibility of the mobile phases with our instruments, THF was replaced by 2-propanol, which has a similar polarity index (3.9) as THF (4.0). A significant disadvantage of 2-propanol as a mobile solvent is the relatively higher viscosity (2.4 cP at 20 °C; THF: 0.55 cP at 20 °C) which can generate high back pressure

Conclusion

In this study, comprehensive and accurate lipid discovery was achieved by combining strategies of building block restriction, high mass accuracy of MS1 data, RT behavior in reversed phase separation and MS/MS spectral analysis. Simultaneously, we constructed sPRM assays to achieve rapid profiling of compounds with high-resolution MS/MS data. In addition, MS1 data in PRM assays also enabled high-resolution (∼resolving power of 35,000) untargeted lipid profiling. Emerging targeted and untargeted

Acknowledgements

This project and U.R. were funded through an Australian Research Council Future Fellowship program. D.Y has been funded through a Melbourne International Research Scholarship (MIRS) (University of Melbourne). I.F. was funded by the German Research Council (DFG,INST 186/1167-1). U.R., I.F. and D.Y. were also supported by a University Australia– Germany Joint Research Cooperation Scheme (DAAD 57140637). LC-MS experiments were carried out at Metabolomics Australia which is supported by funds from

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