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Use of information dependent acquisition mass spectra and sequential window acquisition of all theoretical fragment-ion mass spectra for fruit juices metabolomics and authentication

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A Correction to this article was published on 30 July 2020

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Abstract

Introduction

LC–MS based untargeted metabolomics are the main untargeted methods used for juice metabolomics to solve the authentication problem faced in fruit juice industry.

Objectives

To evaluate the performances of different untargeted metabolomics methods on fruit juices metabolomics and authentication, orange and apple fruit juices were selected for this study.

Methods

IDA-MS and SWATH-MS based on UHPLC-QTOF were used for the metabolomics and authenticity determination of apple and orange juices, including the lab-made samples of oranges (Citrus sinensis Osb.) from Jiangxi Province, apples (Malus domestica Borkh) from Shandong Province, and different brands of commercial orange and apple juice samples from markets.

Results

IDA-MS and SWATH-MS could both acquire numerous MS1 features and MS2 information of juice components, while SWATH-MS excels at the acquisition rate of MS2. Distinctive separation between authentic orange juice and not authentic orange juice could be seen from principal component analysis and hierarchical clustering analysis based on both IDA-MS and SWATH-MS. After analysis of variance, fold change analysis and orthogonal projection to latent structures discriminant mode, 53 and 46 potential markers were defined by IDA-MS and SWATH-MS (with 77.4% and 100% MS2 acquisition rate) separately. Subsequently, these potential markers were putatively annotated using general chemical databases with 6 more annotated by SWATH-MS. Furthermore, 7 of the potential markers, l-asparagine, umbelliferone, glucosamine, phlorin, epicatechin, phytosphingosine and chlorogenic acid, were identified with standards. For the consideration of model simplicity, two determined makers (umbelliferone and chlorogenic acid) were selected to construct the DD-SIMCA model in commercial samples because of their good correlation with apple adulteration proportion, and the sensitivity and specificity of the model were 100% and 95%.

Conclusion

SWATH-MS excels at the MS2 acquisition of juice components and potential markers. This study provides an overall performance comparison between IDA-MS and SWATH-MS, and guidance for the method selection on fruit juice metabolomics and juice authenticity determination. Two of the potential markers determined, umbelliferone and chlorogenic acid, could be used as apple juice indicators in orange juice.

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Change history

  • 30 July 2020

    Following publication of the original article, the authors would like to correct the authors and author affiliations.

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Acknowledgements

We acknowledge the funding from National Key R&D Program of China (2017YFD0400705), and the data analysis training support from International Atomic Energy Agency (IAEA) project of Peaceful Uses Initiative TN-PUI-JPN-EVT1902783.

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Authors and Affiliations

  1. Institute of Quality Standard & Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-Food Safety and Quality, Ministry of Agriculture and Rural Affairs, Beijing, 100081, China

    Lei Xu & Xiaojun Liao

  2. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing Key Laboratory for Food Nonthermal Processing, Key Lab of Fruit and Vegetable Processing, Ministry of Agriculture and Rural Affairs, Beijing, 100083, China

    Lei Xu & Zhenzhen Xu

  3. School of Chemistry, University of Manchester, Brunswick Street, Manchester, UK

    Ilya Strashnov

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Contributions

LX and ZX conceived and designed research. LX conducted experiments. XL contributed reagents and analytical tools. LX and ZX analyzed data. LX wrote the manuscript. IS improved the language expression. All authors discussed the results from the experiments, read and approved the manuscript.

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Correspondence to Zhenzhen Xu.

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Xu, L., Xu, Z., Strashnov, I. et al. Use of information dependent acquisition mass spectra and sequential window acquisition of all theoretical fragment-ion mass spectra for fruit juices metabolomics and authentication. Metabolomics 16, 81 (2020). https://doi.org/10.1007/s11306-020-01701-2

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