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Discovery of Food Intake Biomarkers Using Metabolomics

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Mass Spectrometry for Metabolomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2571))

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Abstract

Due to the high impact of diet exposure on health, it is crucial the generation of robust data of regular dietary intake, hence improving the accuracy of dietary assessment. The metabolites derived from individual food or group of food have great potential to become biomarkers of food intake (BFIs) and provide more objective food consumption measurements.

Herein, it is presented an untargeted metabolomic workflow for the discovery BFIs in blood and urine samples, from the study design to the biomarker identification. Samples are analyzed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). A wide variety of compounds are covered by separate analyses of medium to nonpolar molecules and polar metabolites based on two LC separations as well as both positive and negative electrospray ionization. The main steps of data treatment of the comprehensive data sets and statistical analysis are described, as well as the principal considerations for the BFI identification.

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References

  1. Weckwerth W (2003) Metabolomics in sytems biology. Annu Rev Plant Biol 54:669–689. https://doi.org/10.1146/annurev.arplant.54.031902.135014

    Article  CAS  PubMed  Google Scholar 

  2. Maruvada P, Lampe JW, Wishart DS, Barupal D, Chester DN, Dodd D, Djoumbou-Feunang Y, Dorrestein PC, Dragsted LO, Draper J, Duffy LC, Dwyer JT, Emenaker NJ, Fiehn O, Gerszten RE, Hu FB, Karp RW, Klurfeld DM, Laughlin MR, Little AR, Lynch CJ, Moore SC, Nicastro HL, O’Brien DM, Ordovás JM, Osganian SK, Playdon M, Prentice R, Raftery D, Reisdorph N, Roche HM, Ross SA, Sang S, Scalbert A, Srinivas PR, Zeisel SH (2019) Perspective: dietary biomarkers of intake and exposure—exploration with omics approaches. Adv Nutr 11:200–215. https://doi.org/10.1093/advances/nmz075

    Article  PubMed Central  Google Scholar 

  3. O’Gorman A, Brennan L (2017) The role of metabolomics in determination of new dietary biomarkers. Proc Nutr Soc 76:295–302. https://doi.org/10.1017/S0029665116002974

    Article  CAS  PubMed  Google Scholar 

  4. Hedrick VE, Dietrich AM, Estabrooks PA, Savla J, Serrano E, Davy BM (2012) Dietary biomarkers: advances, limitations and future directions. Nutr J 11:1. https://doi.org/10.1186/1475-2891-11-109

    Article  Google Scholar 

  5. Dunn WB, Wilson ID, Nicholls AW, Broadhurst D (2012) The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans. Bioanalysis 4:2249–2264. https://doi.org/10.4155/bio.12.204

    Article  CAS  PubMed  Google Scholar 

  6. Lacalle-Bergeron L, Izquierdo-Sandoval D, Sancho JV, López FJ, Hernández F, Portolés T (2021) Chromatography hyphenated to high resolution mass spectrometry in untargeted metabolomics for investigation of food (bio)markers. TrAC Trends Anal Chem 135:116161. https://doi.org/10.1016/j.trac.2020.116161

    Article  CAS  Google Scholar 

  7. Castro-Puyana M, Pérez-Míguez R, Montero L, Herrero M (2017) Application of mass spectrometry-based metabolomics approaches for food safety, quality and traceability. TrAC Trends Anal Chem 93:102–118. https://doi.org/10.1016/j.trac.2017.05.004

    Article  CAS  Google Scholar 

  8. Segers K, Declerck S, Mangelings D, Vander HY, Van EA (2019) Analytical techniques for metabolomic studies: a review. Bioanalysis 11:2297–2318. https://doi.org/10.4155/bio-2019-0014

    Article  CAS  PubMed  Google Scholar 

  9. Mairinger T, Causon TJ, Hann S (2018) The potential of ion mobility–mass spectrometry for non-targeted metabolomics. Curr Opin Chem Biol 42:9–15

    Article  CAS  Google Scholar 

  10. Paglia G, Smith AJ, Astarita G (2021) Ion mobility mass spectrometry in the omics era: challenges and opportunities for metabolomics and lipidomics. Mass Spectrom Rev:mas.21686. https://doi.org/10.1002/mas.21686

  11. Worley B, Powers R (2012) Multivariate analysis in metabolomics. Curr Metabolomics 1:92–107. https://doi.org/10.2174/2213235X130108

    Article  Google Scholar 

  12. Bijlsma L, Bade R, Celma A, Mullin L, Cleland G, Stead S, Hernandez F, Sancho JV (2017) Prediction of collision cross-section values for small molecules: application to pesticide residue analysis. Anal Chem 89:6583–6589. https://doi.org/10.1021/acs.analchem.7b00741

    Article  CAS  PubMed  Google Scholar 

  13. Zhou Z, Tu J, Xiong X, Shen X, Zhu Z-J (2017) LipidCCS: prediction of collision cross-section values for lipids with high precision to support ion mobility–mass spectrometry-based lipidomics. Anal Chem 89:9559–9566. https://doi.org/10.1021/acs.analchem.7b02625

    Article  CAS  PubMed  Google Scholar 

  14. Plante P-L, Francovic-Fontaine É, May JC, McLean JA, Baker ES, Laviolette F, Marchand M, Corbeil J (2019) Predicting ion mobility collision cross-sections using a deep neural network: DeepCCS. Anal Chem 91:5191–5199. https://doi.org/10.1021/acs.analchem.8b05821

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Correspondence to Tania Portolés .

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Lacalle-Bergeron, L., Izquierdo-Sandoval, D., Sancho, J.V., Portolés, T. (2023). Discovery of Food Intake Biomarkers Using Metabolomics. In: González-Domínguez, R. (eds) Mass Spectrometry for Metabolomics. Methods in Molecular Biology, vol 2571. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2699-3_4

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  • DOI: https://doi.org/10.1007/978-1-0716-2699-3_4

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2698-6

  • Online ISBN: 978-1-0716-2699-3

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