title: Combining DI-ESI-MS and NMR datasets for metabolic profiling.
abstract: Metabolomics datasets are commonly acquired by either mass spectrometry (MS) or nuclear magnetic resonance spectroscopy (NMR), despite their fundamental complementarity. In fact, combining MS and NMR datasets greatly improves the coverage of the metabolome and enhances the accuracy of metabolite identification, providing a detailed and high-throughput analysis of metabolic changes due to disease, drug treatment, or a variety of other environmental stimuli. Ideally, a single metabolomics sample would be simultaneously used for both MS and NMR analyses, minimizing the potential for variability between the two datasets. This necessitates the optimization of sample preparation, data collection and data handling protocols to effectively integrate direct-infusion MS data with one-dimensional (1D)1H NMR spectra. To achieve this goal, we report for the first time the optimization of (i) metabolomics sample preparation for dual analysis by NMR and MS, (ii) high throughput, positive-ion direct infusion electrospray ionization mass spectrometry (DI-ESI-MS) for the analysis of complex metabolite mixtures, and (iii) data handling protocols to simultaneously analyze DI-ESI-MS and 1D1H NMR spectral data using multiblock bilinear factorizations, namely multiblock principal component analysis (MB-PCA) and multiblock partial least squares (MB-PLS). Finally, we demonstrate the combined use of backscaled loadings, accurate mass measurements and tandem MS experiments to identify metabolites significantly contributing to class separation in MB-PLS-DA scores. We show that integration of NMR and DI-ESI-MS datasets yields a substantial improvement in the analysis of neurotoxin involvement in dopaminergic cell death.
authors.affiliation: Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304.
authors.forename: Darrell D
authors.initials: DD
authors.lastname: Marshall
authors.affiliation: Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304.
authors.forename: Shulei
authors.initials: S
authors.lastname: Lei
authors.affiliation: Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304.
authors.forename: Bradley
authors.initials: B
authors.lastname: Worley
authors.affiliation: Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304.
authors.forename: Yuting
authors.initials: Y
authors.lastname: Huang
authors.affiliation: Redox Biology Center, University of Nebraska-Lincoln, Lincoln, NE 68583-0905 ; School of Veterinary Medicine and Biomedical Sciences, University of Nebraska-Lincoln, Lincoln, NE 68583-0905.
authors.forename: Aracely
authors.initials: A
authors.lastname: Garcia-Garcia
authors.affiliation: Redox Biology Center, University of Nebraska-Lincoln, Lincoln, NE 68583-0905 ; School of Veterinary Medicine and Biomedical Sciences, University of Nebraska-Lincoln, Lincoln, NE 68583-0905.
authors.forename: Rodrigo
authors.initials: R
authors.lastname: Franco
authors.affiliation: Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304.
authors.forename: Eric D
authors.initials: ED
authors.lastname: Dodds
authors.affiliation: Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304 ; Redox Biology Center, University of Nebraska-Lincoln, Lincoln, NE 68583-0905.
authors.forename: Robert
authors.initials: R
authors.lastname: Powers
keywords: DI-ESI-MS; Metabolomics; Multiblock PCA; Multiblock PLS; Multivariate Statistics; NMR