A multidimensional 1H NMR lipidomics workflow to address chemical food safety issues

IntroductionAlthough it is still at a very early stage compared to its mass spectrometry (MS) counterpart, proton nuclear magnetic resonance (NMR) lipidomics is worth being investigated as an original and complementary solution for lipidomics. Dedicated sample preparation protocols and adapted data acquisition methods have to be developed to set up an NMR lipidomics workflow; in particular, the considerable overlap observed for lipid signals on 1D spectra may hamper its applicability.ObjectivesThe study describes the development of a complete proton NMR lipidomics workflow for application to serum fingerprinting. It includes the assessment of fast 2D NMR strategies, which, besides reducing signal overlap by spreading the signals along a second dimension, offer compatibility with the high-throughput requirements of food quality characterization.MethodThe robustness of the developed sample preparation protocol is assessed in terms of repeatability and ability to provide informative fingerprints; further, different NMR acquisition schemes—including classical 1D, fast 2D based on non-uniform sampling or ultrafast schemes—are evaluated and compared. Finally, as a proof of concept, the developed workflow is applied to characterize lipid profiles disruption in serum from β-agonists diet fed pigs.ResultsOur results show the ability of the workflow to discriminate efficiently sample groups based on their lipidic profile, while using fast 2D NMR methods in an automated acquisition framework.ConclusionThis work demonstrates the potential of fast multidimensional 1H NMR—suited with an appropriate sample preparation—for lipidomics fingerprinting as well as its applicability to address chemical food safety issues.

[1]  M. Wenk The emerging field of lipidomics , 2005, Nature Reviews Drug Discovery.

[2]  Takehiko Yokomizo,et al.  Applications of mass spectrometry-based targeted and non-targeted lipidomics. , 2018, Biochemical and biophysical research communications.

[3]  F. Dunshea Effect of metabolism modifiers on lipid metabolism in the pig. , 1993, Journal of animal science.

[4]  Friedrich Spener,et al.  Editorial: What is lipidomics? , 2003 .

[5]  P. Giraudeau Quantitative 2D liquid‐state NMR , 2014, Magnetic resonance in chemistry : MRC.

[6]  B. Le Bizec,et al.  Rapid evaporative ionisation mass spectrometry and chemometrics for high-throughput screening of growth promoters in meat producing animals , 2018, Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment.

[7]  Oliver Fiehn,et al.  Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry. , 2014, Trends in analytical chemistry : TRAC.

[8]  Timothy D Veenstra,et al.  Metabolomics: the final frontier? , 2012, Genome Medicine.

[9]  Markus R Wenk,et al.  Lipidomics: New Tools and Applications , 2010, Cell.

[10]  P. Giraudeau Challenges and perspectives in quantitative NMR , 2017, Magnetic resonance in chemistry : MRC.

[11]  B. Le Bizec,et al.  Serum-based metabolomics characterization of pigs treated with ractopamine , 2017, Metabolomics.

[12]  Kim-Anh Lê Cao,et al.  A novel approach for biomarker selection and the integration of repeated measures experiments from two assays , 2012, BMC Bioinformatics.

[13]  S. Akoka,et al.  Fast determination of absolute metabolite concentrations by spatially encoded 2D NMR: application to breast cancer cell extracts. , 2012, Analytical chemistry.

[14]  Gerald T. Ankley,et al.  Profiling lipid metabolites yields unique information on sex- and time-dependent responses of fathead minnows (Pimephales promelas) exposed to 17α-ethynylestradiol , 2009, Metabolomics.

[15]  T. Mavromoustakos,et al.  13C NMR analysis of the triacylglycerol composition of Greek virgin olive oils , 1997 .

[16]  A. Behari,et al.  Lipid profiling of cancerous and benign gallbladder tissues by 1H NMR spectroscopy , 2010, NMR in biomedicine.

[17]  I. Young,et al.  Lipid metabolism. , 2002, Current opinion in lipidology.

[18]  F. Malz Chapter 2 – Quantitative NMR in the Solution State NMR , 2008 .

[19]  Fast n-Dimensional Data Acquisition Methods , 2017 .

[20]  S. Akoka,et al.  Fast quantitative 1H-13C two-dimensional NMR with very high precision. , 2013, Analytical chemistry.

[21]  M. Orešič,et al.  Lipidomics in biomedical research-practical considerations. , 2017, Biochimica et biophysica acta. Molecular and cell biology of lipids.

[22]  Robert Powers,et al.  Combining DI-ESI–MS and NMR datasets for metabolic profiling , 2015, Metabolomics.

[23]  C. Larive,et al.  Quantitative NMR for bioanalysis and metabolomics , 2012, Analytical and Bioanalytical Chemistry.

[24]  F. Dunshea,et al.  Ractopamine increases glucose turnover without affecting lipogenesis in the pig , 1998 .

[25]  Gabriele Cruciani,et al.  LC/MS lipid profiling from human serum: a new method for global lipid extraction , 2014, Analytical and Bioanalytical Chemistry.

[26]  Yann Guitton,et al.  Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics. , 2017, Current opinion in biotechnology.

[27]  F. Dunshea,et al.  Temporal response of plasma metabolites to ractopamine treatment in the growing pig , 1994 .

[28]  L. Pereira,et al.  Effect of ractopamine on lipid metabolism in vivo - a systematic review , 2013 .

[29]  Li Yang,et al.  Analytical methods in lipidomics and their applications. , 2014, Analytical chemistry.

[30]  S. Caldarelli,et al.  Resolution‐enhanced 2D NMR of complex mixtures by non‐uniform sampling , 2015, Magnetic resonance in chemistry : MRC.

[31]  W. F. Owsley,et al.  Lipid metabolism related gene-expression profiling in liver, skeletal muscle and adipose tissue in crossbred Duroc and Pietrain Pigs. , 2007, Comparative biochemistry and physiology. Part D, Genomics & proteomics.

[32]  S. Akoka,et al.  Fast hybrid multi‐dimensional NMR methods based on ultrafast 2D NMR , 2015, Magnetic resonance in chemistry : MRC.

[33]  Daniel Figeys,et al.  Lipidomics era: accomplishments and challenges. , 2010, Mass spectrometry reviews.

[34]  Ying-Yong Zhao,et al.  Ultra-performance liquid chromatography-mass spectrometry as a sensitive and powerful technology in lipidomic applications. , 2014, Chemico-biological interactions.

[35]  Hydrophilic interaction (HILIC) and reverse phase liquid chromatography (RPLC)–high resolution MS for characterizing lipids profile disruption in serum of anabolic implanted bovines , 2015, Metabolomics.

[36]  Xianlin Han,et al.  Lipidomics: Techniques, Applications, and Outcomes Related to Biomedical Sciences. , 2016, Trends in biochemical sciences.

[37]  S. Caldarelli,et al.  Evaluation of fast 2D NMR for metabolomics. , 2014, Analytical chemistry.

[38]  Age K. Smilde,et al.  Multivariate paired data analysis: multilevel PLSDA versus OPLSDA , 2009, Metabolomics.

[39]  B. Le Bizec,et al.  Metabolomics in food analysis: application to the control of forbidden substances. , 2012, Drug testing and analysis.

[40]  B. Le Bizec,et al.  LC-HRMS based metabolomics screening model to detect various β-agonists treatments in bovines , 2014, Metabolomics.

[41]  Jingbo Li,et al.  Applications of nuclear magnetic resonance in lipid analyses: An emerging powerful tool for lipidomics studies. , 2017, Progress in lipid research.

[42]  A. Moing,et al.  Absolute quantification of metabolites in tomato fruit extracts by fast 2D NMR , 2015, Metabolomics.

[43]  G. Vlahov Quantitative 13C NMR method using the DEPT pulse sequence for the detection of olive oil adulteration with soybean oil , 1997 .

[44]  R. Tauler,et al.  Compression of multidimensional NMR spectra allows a faster and more accurate analysis of complex samples. , 2018, Chemical communications.

[45]  S. Akoka,et al.  A strategy for simultaneous determination of fatty acid composition, fatty acid position, and position-specific isotope contents in triacylglycerol matrices by 13C-NMR , 2016, Analytical and Bioanalytical Chemistry.

[46]  S. Akoka,et al.  "Multi-scan single shot" quantitative 2D NMR: a valuable alternative to fast conventional quantitative 2D NMR. , 2011, The Analyst.

[47]  Laura K. Schnackenberg,et al.  Metabonomic models of human pancreatic cancer using 1D proton NMR spectra of lipids in plasma , 2006, Metabolomics.

[48]  R. H. Dalrymple,et al.  Use of a β-Agonist to Alter Fat and Muscle Deposition in Steers1, 2 , 1984 .

[49]  B. Le Bizec,et al.  Targeted and untargeted profiling of biological fluids to screen for anabolic practices in cattle , 2010 .

[50]  B. Kaphalia,et al.  Lipidomic changes in rat liver after long-term exposure to ethanol. , 2011, Toxicology and applied pharmacology.

[51]  Johan Trygg,et al.  CV‐ANOVA for significance testing of PLS and OPLS® models , 2008 .