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Comprehensive polyphenol profiling of a strawberry extract (Fragaria × ananassa) by ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry

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Abstract

The aim of metabolic untargeted profiling is to detect and identify unknown compounds in a biological matrix to achieve the most comprehensive metabolic coverage. In phytochemical mixtures, however, the complexity of the sample could present significant difficulties in compound identification. In this case, the optimization of both the chromatographic and the mass-spectrometric conditions is supposed to be crucial for the detection and identification of the largest number of compounds. In this work, a systematic investigation of different chromatographic and mass-spectrometric conditions is presented to achieve a comprehensive untargeted profiling of a strawberry extract (Fragaria × ananassa). To fulfill this aim, an ultra-high-pressure liquid chromatography system coupled via an electrospray source to a hybrid quadrupole–Orbitrap mass spectrometer was used. Spectra were acquired in data-dependent mode, and several parameters were investigated to acquire the largest possible number of both mass spectrometry (MS) features and MS2 mass spectra for unique metabolites. The main classes of polyphenols studied were flavonoids, phenolic acids, dihydrochalcones, ellagitannins, and proanthocyanidins. Method optimization allowed to us identify and tentatively identify 18 and 113 compounds, respectively, among which 74 have never been reported before in strawberries and, to the best of our knowledge, 22 of them have never been reported before. The results show the importance of an extended investigation of the chromatographic and mass-spectrometric method before a complete untargeted profiling of complex phytochemical mixtures.

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References

  1. Gika HG, Wilson ID, Theodoridis GA. LC–MS-based holistic metabolic profiling. Problems, limitations, advantages, and future perspectives. J Chromatogr B. 2014;966:1–6. doi:10.1016/j.jchromb.2014.01.054.

    Article  CAS  Google Scholar 

  2. Kaufmann A. Combining UHPLC and high-resolution MS: a viable approach for the analysis of complex samples? Trends Anal Chem. 2014;63:113–28. doi:10.1016/j.trac.2014.06.025.

    Article  CAS  Google Scholar 

  3. Riedl J, Esslinger S, Fauhl-Hassek C. Review of validation and reporting of non-targeted fingerprinting approaches for food authentication. Anal Chim Acta. 2015;885:17–32. doi:10.1016/j.aca.2015.06.003.

    Article  CAS  Google Scholar 

  4. Kim S, Kim J, Yun EJ, Kim KH. Food metabolomics: from farm to human. Curr Opin Biotechnol. 2016;37:16–23. doi:10.1016/j.copbio.2015.09.004.

    Article  CAS  Google Scholar 

  5. Schuhmacher R, Krska R, Weckwerth W, Goodacre R. Metabolomics and metabolite profiling. Anal Bioanal Chem. 2013;405:5003–4. doi:10.1007/s00216-013-6939-5.

    Article  CAS  Google Scholar 

  6. Zhang R, Watson DG, Wang L, Westrop GD, Coombs GH, Zhang T. Evaluation of mobile phase characteristics on three zwitterionic columns in hydrophilic interaction liquid chromatography mode for liquid chromatography-high resolution mass spectrometry based untargeted metabolite profiling of Leishmania parasites. J Chromatogr A. 2014;1362:168–79. doi:10.1016/j.chroma.2014.08.039.

    Article  CAS  Google Scholar 

  7. Stobiecki M, Kachlicki P, Wojakowska A, Marczak Ł. Application of LC/MS systems to structural characterization of flavonoid glycoconjugates. Phytochem Lett. 2015;11:358–67. doi:10.1016/j.phytol.2014.10.018.

    Article  Google Scholar 

  8. Kind T, Fiehn O. Seven golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinformatics. 2007;8:105. doi:10.1186/1471-2105-8-105.

    Article  Google Scholar 

  9. Mullard G, Allwood JW, Weber R, Brown M, Begley P, Hollywood KA, et al. A new strategy for MS/MS data acquisition applying multiple data dependent experiments on Orbitrap mass spectrometers in non-targeted metabolomic applications. Metabolomics. 2015;11:1068–80. doi:10.1007/s11306-014-0763-6.

    Article  CAS  Google Scholar 

  10. Kloos D-P, Lingeman H, Niessen WMA, Deelder AM, Giera M, Mayboroda OA. Evaluation of different column chemistries for fast urinary metabolic profiling. J Chromatogr B. 2013;927:90–6. doi:10.1016/j.jchromb.2013.02.017.

    Article  CAS  Google Scholar 

  11. Zhang T, Creek DJ, Barrett MP, Blackburn G, Watson DG. Evaluation of coupling reversed phase, aqueous normal phase, and hydrophilic interaction liquid chromatography with Orbitrap mass spectrometry for metabolomic studies of human urine. Anal Chem. 2012;84:1994–2001. doi:10.1021/ac2030738.

    Article  CAS  Google Scholar 

  12. Bajad SU, Lu W, Kimball EH, Yuan J, Peterson C, Rabinowitz JD. Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry. J Chromatogr A. 2006;1125:76–88. doi:10.1016/j.chroma.2006.05.019.

    Article  CAS  Google Scholar 

  13. Sun J, Liu X, Yang T, Slovin J, Chen P. Profiling polyphenols of two diploid strawberry (Fragaria vesca) inbred lines using UHPLC-HRMSn. Food Chem. 2014;146:289–98. doi:10.1016/j.foodchem.2013.08.089.

    Article  CAS  Google Scholar 

  14. Kårlund A, Hanhineva K, Lehtonen M, Karjalainen RO, Sandell M. Nontargeted metabolite profiles and sensory properties of strawberry cultivars grown both organically and conventionally. J Agric Food Chem. 2015;63:1010–9. doi:10.1021/jf505183j.

    Article  Google Scholar 

  15. Kajdžanoska M, Petreska J, Stefova M. Comparison of different extraction solvent mixtures for characterization of phenolic compounds in strawberries. J Agric Food Chem. 2011;59:5272–8. doi:10.1021/jf2007826.

    Article  Google Scholar 

  16. Pluskal T, Castillo S, Villar-Briones A, Orešič M. MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics. 2010;11:395. doi:10.1186/1471-2105-11-395.

    Article  Google Scholar 

  17. Benton HP, Ivanisevic J, Mahieu NG, Kurczy ME, Johnson CH, Franco L, et al. Autonomous metabolomics for rapid metabolite identification in global profiling. Anal Chem. 2015;87:884–91. doi:10.1021/ac5025649.

    Article  CAS  Google Scholar 

  18. Willemse CM, Stander MA, de Villiers A. Hydrophilic interaction chromatographic analysis of anthocyanins. J Chromatogr A. 2013;1319:127–40. doi:10.1016/j.chroma.2013.10.045.

    Article  CAS  Google Scholar 

  19. de Villiers A, Cabooter D, Lynen F, Desmet G, Sandra P. High performance liquid chromatography analysis of wine anthocyanins revisited: effect of particle size and temperature. J Chromatogr A. 2009;1216:3270–9. doi:10.1016/j.chroma.2009.02.038.

    Article  Google Scholar 

  20. Álvarez-Fernández MA, Hornedo-Ortega R, Cerezo AB, Troncoso AM, García-Parrilla MC. Determination of nonanthocyanin phenolic compounds using high-resolution mass spectrometry (UHPLC-Orbitrap-MS/MS) and impact of storage conditions in a beverage made from strawberry by fermentation. J Agric Food Chem. 2016;64:1367–76. doi:10.1021/acs.jafc.5b05617.

    Article  Google Scholar 

  21. McDougall G, Martinussen I, Stewart D. Towards fruitful metabolomics: high throughput analyses of polyphenol composition in berries using direct infusion mass spectrometry. J Chromatogr B. 2008;871:362–9. doi:10.1016/j.jchromb.2008.06.032.

    Article  CAS  Google Scholar 

  22. Newsome AG, Li Y, van Breemen RB. Improved quantification of free and ester-bound gallic acid in foods and beverages by UHPLC-MS/MS. J Agric Food Chem. 2016;64:1326–34. doi:10.1021/acs.jafc.5b04966.

    Article  CAS  Google Scholar 

  23. Álvarez-Fernández MA, Cerezo AB, Cañete-Rodríguez AM, Troncoso AM, García-Parrilla MC. Composition of nonanthocyanin polyphenols in alcoholic-fermented strawberry products using LC–MS (QTRAP), high-resolution MS (UHPLC-Orbitrap-MS), LC-DAD, and antioxidant activity. J Agric Food Chem. 2015;63:2041–51. doi:10.1021/jf506076n.

    Article  Google Scholar 

  24. Hanhineva K, Rogachev I, Kokko H, Mintz-Oron S, Venger I, Kärenlampi S, et al. Non-targeted analysis of spatial metabolite composition in strawberry (Fragaria × ananassa) flowers. Phytochemistry. 2008;69:2463–81. doi:10.1016/j.phytochem.2008.07.009.

    Article  CAS  Google Scholar 

  25. D’Urso G, d’Aquino L, Pizza C, Montoro P. Integrated mass spectrometric and multivariate data analysis approaches for the discrimination of organic and conventional strawberry (Fragaria ananassa Duch.) crops. Food Res Int. 2015;77:264–72. doi:10.1016/j.foodres.2015.04.028.

    Article  Google Scholar 

  26. Spínola V, Pinto J, Castilho PC. Identification and quantification of phenolic compounds of selected fruits from Madeira Island by HPLC-DAD–ESI-MSn and screening for their antioxidant activity. Food Chem. 2015;173:14–30. doi:10.1016/j.foodchem.2014.09.163.

    Article  Google Scholar 

  27. Aaby K, Mazur S, Nes A, Skrede G. Phenolic compounds in strawberry (Fragaria x ananassa Duch.) fruits: composition in 27 cultivars and changes during ripening. Food Chem. 2012;132:86–97. doi:10.1016/j.foodchem.2011.10.037.

    Article  CAS  Google Scholar 

  28. Cerezo AB, Cuevas E, Winterhalter P, Garcia-Parrilla MC, Troncoso AM. Isolation, identification, and antioxidant activity of anthocyanin compounds in Camarosa strawberry. Food Chem. 2010;123:574–82. doi:10.1016/j.foodchem.2010.04.073.

    Article  CAS  Google Scholar 

  29. Lopes-da-Silva F, de Pascual-Teresa S, Rivas-Gonzalo J, Santos-Buelga C. Identification of anthocyanin pigments in strawberry (cv Camarosa) by LC using DAD and ESI-MS detection. Eur Food Res Technol. 2002;214:248–53. doi:10.1007/s00217-001-0434-5.

    Article  CAS  Google Scholar 

  30. Sadilova E, Carle R, Stintzing FC. Thermal degradation of anthocyanins and its impact on color and in vitro antioxidant capacity. Mol Nutr Food Res. 2007;51:1461–71. doi:10.1002/mnfr.200700179.

    Article  CAS  Google Scholar 

  31. IM de Tavares C, Lago-Vanzela ES, Rebello LPG, Ramos AM, Gómez-Alonso S, García-Romero E, et al. Comprehensive study of the phenolic composition of the edible parts of jambolan fruit (Syzygium cumini (L.) Skeels). Food Res Int. 2016;82:1–13. doi:10.1016/j.foodres.2016.01.014.

    Article  CAS  Google Scholar 

  32. Carazzone C, Mascherpa D, Gazzani G, Papetti A. Identification of phenolic constituents in red chicory salads (Cichorium intybus) by high-performance liquid chromatography with diode array detection and electrospray ionisation tandem mass spectrometry. Food Chem. 2013;138:1062–71. doi:10.1016/j.foodchem.2012.11.060.

    Article  CAS  Google Scholar 

  33. Álvarez-Fernández MA, Hornedo-Ortega R, Cerezo AB, Troncoso AM, García-Parrilla MC. Effects of the strawberry (Fragaria ananassa) purée elaboration process on non-anthocyanin phenolic composition and antioxidant activity. Food Chem. 2014;164:104–12. doi:10.1016/j.foodchem.2014.04.116.

    Article  Google Scholar 

  34. Schymanski EL, Jeon J, Gulde R, Fenner K, Ruff M, Singer HP, et al. Identifying small molecules via high resolution mass spectrometry: communicating confidence. Environ Sci Technol. 2014;48:2097–8. doi:10.1021/es5002105.

    Article  CAS  Google Scholar 

  35. Vukics V, Guttman A. Structural characterization of flavonoid glycosides by multi-stage mass spectrometry. Mass Spectrom Rev. 2010;29:1–16. doi:10.1002/mas.20212.

    CAS  Google Scholar 

  36. Cuyckens F, Claeys M. Mass spectrometry in the structural analysis of flavonoids. J Mass Spectrom. 2004;39:1–15. doi:10.1002/jms.585.

    Article  CAS  Google Scholar 

  37. de Villiers A, Venter P, Pasch H. Recent advances and trends in the liquid-chromatography–mass spectrometry analysis of flavonoids. J Chromatogr A. 2016;1430:16–78. doi:10.1016/j.chroma.2015.11.077.

    Article  Google Scholar 

  38. Hooi Poay T, Sui Kiong L, Cheng Hock C. Characterisation of galloylated cyanogenic glucosides and hydrolysable tannins from leaves of Phyllagathis rotundifolia by LC-ESI-MS/MS: characterisation of galloylated cyanogenic glucosides and tannins. Phytochem Anal. 2011;22:516–25. doi:10.1002/pca.1312.

    Article  Google Scholar 

  39. Lin L-Z, Sun J, Chen P, Monagas MJ, Harnly JM. UHPLC-PDA-ESI/HRMSn profiling method to identify and quantify oligomeric proanthocyanidins in plant products. J Agric Food Chem. 2014;62:9387–400. doi:10.1021/jf501011y.

    Article  CAS  Google Scholar 

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Correspondence to Chiara Cavaliere.

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La Barbera, G., Capriotti, A.L., Cavaliere, C. et al. Comprehensive polyphenol profiling of a strawberry extract (Fragaria × ananassa) by ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. Anal Bioanal Chem 409, 2127–2142 (2017). https://doi.org/10.1007/s00216-016-0159-8

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