Dataset Information

Untargeted HILIC-MS-Based Metabolomics Approach to Evaluate Coffee Roasting Process: Contributing to an Integrated Metabolomics Multiplatform.

ABSTRACT: An untargeted metabolomics strategy using hydrophilic interaction chromatography-mass spectrometry (HILIC-MS) was developed in this work enabling the study of the coffee roasting process. Green coffee beans and coffee beans submitted to three different roasting degrees (light, medium, and strong) were analyzed. Chromatographic separation was carried out using water containing 10 mM ammonium formate with 0.2 % formic acid (mobile phase A) and acetonitrile containing 10 mM ammonium formate with 0.2 % formic acid (mobile phase B). A total of 93 molecular features were considered from which 31 were chosen as the most statistically significant using variable in the projection values. 13 metabolites were tentatively identified as potential biomarkers of the coffee roasting process using this metabolomic platform. Results obtained in this work were complementary to those achieved using orthogonal techniques such as reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) and capillary electrophoresis-mass spectrometry (CE-MS) since only one metabolite was found to be common between HILIC-MS and RPLC-MS platforms (caffeoylshikimic acid isomer) and other between HILIC-MS and CE-MS platforms (choline). On the basis of these results, an untargeted metabolomics multiplatform is proposed in this work based on the integration of the three orthogonal techniques as a powerful tool to expand the coverage of the roasted coffee metabolome.

SUBMITTER: Perez-Miguez R

PROVIDER: S-EPMC7070313 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Untargeted HILIC-MS-Based Metabolomics Approach to Evaluate Coffee Roasting Process: Contributing to an Integrated Metabolomics Multiplatform.

Pérez-Míguez Raquel R Castro-Puyana María M Sánchez-López Elena E Plaza Merichel M Marina María Luisa ML

Molecules (Basel, Switzerland) 20200217 4

An untargeted metabolomics strategy using hydrophilic interaction chromatography-mass spectrometry (HILIC-MS) was developed in this work enabling the study of the coffee roasting process. Green coffee beans and coffee beans submitted to three different roasting degrees (light, medium, and strong) were analyzed. Chromatographic separation was carried out using water containing 10 mM ammonium formate with 0.2 % formic acid (mobile phase A) and acetonitrile containing 10 mM ammonium formate with 0. ...[more]

PMID: 32079306

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Project description:IntroductionRecent advances in high-throughput methodologies in the 'omics' and synthetic biology fields call for rapid and sensitive workflows in the metabolic phenotyping of complex biological samples.ObjectiveThe objective of this research was to evaluate a straightforward to implement LC-MS metabolomics method using a commercially available chromatography column that provides increased throughput. Reducing run time can potentially impact chromatography and therefore the effects of ion mobility spectrometry to expand peak capacity were also evaluated. Additional confidence provided via collision cross section measurements for detected features was also explored.MethodsA rapid untargeted metabolomics workflow was developed with broad metabolome coverage, combining zwitterionic-phase hydrophilic interaction chromatography (HILIC-Z) with drift tube ion mobility-quadrupole time-of-flight (DTIM-qTOF) mass spectrometry. The analytical performance of our method was explored using extracts from complex biological samples, including a reproducibility study on chicken serum and a simple comparative study on a bacterial metabolome.ResultsThe method is acronymised RHIMMS for rapid HILIC-Z ion mobility mass spectrometry. We present the RHIMMS workflow starting with data acquisition, followed by data processing and analysis. RHIMMS demonstrates improved chromatographic separation for a selection of metabolites with wide physicochemical properties while maintaining reproducibility at better than 20% over 200 injections at 3.5 min per sample for the selected metabolites, and a mean of 13.9% for the top 50 metabolites by intensity. Additionally, the combination of rapid chromatographic separation with ion mobility allows improved annotation and the ability to distinguish isobaric compounds.ConclusionOur results demonstrate RHIMMS to be a rapid, reproducible, sensitive and high-resolution analytical platform that is highly applicable to the untargeted metabolomics analysis of complex samples.

Project description:IntroductionIn the last years, consumers increased the demand for high-quality and healthy beverages, including coffee. To date, among the techniques potentially available to determine the overall quality of coffee beverages, metabolomics is emerging as a valuable tool.ObjectiveIn this study, 47 ground coffee samples were selected during the 2018 Edition of the "International coffee tasting" (ICT) in order to provide discrimination based on both chemical and sensory profiles. In particular, 20 samples received a gold medal ("high quality" group), while lower sensory scores characterized 27 samples (without medal).MethodsUntargeted metabolomics based on ultra-high pressure liquid chromatography coupled with quadrupole-time-of-flight (UHPLC-QTOF) and head space-gas chromatography coupled with mass spectrometry platforms followed by multivariate statistical approaches (i.e., both supervised and unsupervised) were used to provide new insight into the searching of potential markers of sensory quality.ResultsSeveral compounds were identified, including polyphenols, alkaloids, diazines, and Maillard reaction products. Also, the headspace/GC-MS highlighted the most important volatile compounds. Polyphenols were scarcely correlated to the sensory parameters, whilst the OPLS-DA models built using typical coffee metabolites and volatile/Maillard compounds possessed prediction values?>?0.7. The "high quality" group showed specific metabolomic signatures, thus corroborating the results from the sensory analysis. Overall, methyl pentanoate (ROC value?=?0.78), 2-furfurylthiol (ROC value?=?0.75), and L-Homoserine (ROC value?=?0.74) established the higher number of significant (p?<?0.05) correlations with the sensory parameters.ConclusionAlthough ad-hoc studies are advisable to further confirm the proposed markers, this study demonstrates the suitability of untargeted metabolomics for evaluating coffee quality and the potential correlations with the sensory attributes.

Dataset Information

Untargeted HILIC-MS-Based Metabolomics Approach to Evaluate Coffee Roasting Process: Contributing to an Integrated Metabolomics Multiplatform.

Publications

Untargeted HILIC-MS-Based Metabolomics Approach to Evaluate Coffee Roasting Process: Contributing to an Integrated Metabolomics Multiplatform.

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