Untargeted Comprehensive Two-Dimensional Liquid Chromatography Coupled with High-Resolution Mass Spectrometry Analysis of Rice Metabolome Using Multivariate Curve Resolution

Abstract

In this work, a new strategy for the chemometric analysis of two-dimensional liquid chromatography-high-resolution mass spectrometry (LC × LC-HRMS) data is proposed. This approach consists of a preliminary compression step along the mass spectrometry (MS) spectral dimension based on the selection of the regions of interest (ROI), followed by a further data compression along the chromatographic dimension by wavelet transforms. In a secondary step, the multivariate curve resolution alternating least squares (MCR-ALS) method is applied to previously compressed data sets obtained in the simultaneous analysis of multiple LC × LC-HRMS chromatographic runs from multiple samples. The feasibility of the proposed approach is demonstrated by its application to a large experimental data set obtained in the untargeted LC × LC-HRMS study of the effects of different environmental conditions (watering and harvesting time) on the metabolism of multiple rice samples. An untargeted chromatographic setup coupling two different liquid chromatography (LC) columns [hydrophilic interaction liquid chromatography (HILIC) and reversed-phase liquid chromatography (RPLC)] together with an HRMS detector was developed and applied to analyze the metabolites extracted from rice samples at the different experimental conditions. In the case of the metabolomics study taken as example in this work, a total number of 154 metabolites from 15 different families were properly resolved after the application of MCR-ALS. A total of 139 of these metabolites could be identified by their HRMS spectra. Statistical analysis of their concentration changes showed that both watering and harvest time experimental factors had significant effects on rice metabolism. The biochemical insight of the effects of watering and harvesting experimental factors on the changes in concentration of these detected metabolites in the investigated rice samples is attempted.

Phenotypic and lipidomic characterization of primary human epidermal keratinocytes exposed to simulated solar UV radiation

“…First, a data compression step based on the Regions of Interest (ROI) concept [17], and second, the analysis of the compressed data using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) [18] methodology. This combined approach (ROIMCR) has been successfully used in different untargeted metabolomics investigations on LC-MS data [19][20][21][22].…”

“…In the first compression step, the ROI procedure searches for signals at m/z values with significant intensity MS values, higher than a threshold value (estimated from the instrumental noise level). Apart from having higher values than the threshold value, ROI values have also to be represented by a minimum of consecutive data points in the chromatogram, within a predefined m/z deviation error (related to the MS instrument mass accuracy) [19][20][21][22]. ROI compression step takes advantage of the sparse structure of the measured MS data reducing considerably the computer storage and computation time needed without losing the instrumental mass accuracy and resolution.…”

“…This method allowed the simultaneous resolution of all the elution and MS spectral profiles of the different sample lipid constituents [24,25]. MCR-ALS has been previously applied for the resolution of the elution and spectral profiles of the constituents of complex sample mixtures analysed by LC-MS and it has been extended more recently to omic studies [16,[26][27][28][29][30][31][32].…”

High‐resolution gas chromatography/mass spectrometry metabolomics of non‐human primate serum

“…(D) Number of confidently quantified metabolites obtained using the 1D-GC/Orbitrap-MS and 2D-GC/TOF-MS platforms [Color figure can be viewed at wileyonlinelibrary.com]Previous studies using 2D-GC/TOF-MS using spleen extracts have led to the detection of around 1200 compounds compared with only 500 in the 1D-GC/TOF-MS of the same samples 19. Very recently, the power of 2D-LC/HRMS was exploited for the analysis of the rice metabolome 41. Three-dimensional (3D) gas chromatography with time-of-flight mass spectrometric (GC 3 /TOF-MS) detection allowed the analytical advantages of employing three varied chemical selectivities in the 3D separation coupled with TOF-MS for the resolution of complex mixtures in equivalent modulation period conditions 42.…”

Recent applications of chemometrics in one‐ and two‐dimensional chromatography

“…The approach is often applied in combination with deconvolution strategies, such as multivariate curve resolution-alternating least squares (MCR-ALS, see Sections 2.2.2 and 3.4), as in this case peak alignment is not required [89]. Such an ROI-MCR approach has been applied by Navarro-Reig et al [90] in combination with LC×LC-HRMS for the identification of metabolites in the rice metabolome. They selected the ROIs based on S/N ratio (0.1% of maximum MS signal intensity), mass accuracy of the MS (0.05 Da/e for the ToF mass analyzer used) and the minimum number of times the same m/z signal had to be detected consecutively (set at 25).…”