Mapping of Greek olive oil using magnetic resonance mass spectrometry flow injection analysis and multivariate data analysis

In this study, LC free magnetic resonance mass spectrometry (MRMS) analysis was employed for mapping and quality control assessment of Greek extra virgin olive oil (EVOO) using a new and intuitive software workflow.

Introduction

The increasing popularity of EVOO over the last decade has provided the need for quality and authenticity control [1]. Its chemi- cal complexity impedes the

transaction of the typical analytical methodologies [2]. In this study, a holistic approach to map Greek EVOO is presented. The workflow takes advantage of the rapid, LC free, flow injection analysis (FIA) based data acquisition by

ultra-high resolution MRMS. The obtained mass spectra were evaluated using the new MetaboScape® 3.0 software for deisotoping, as well as for identifying the most significant metabolites.

Keywords: MetaboScape 3.0, Magnetic Resonance Mass Spectrometry, MRMS, Olive Oil profiling, Authenticity, Metabolomics

Authors: Matthias Witt 1, Aiko Barsch 1, Theodora Nikou 2, Maria Halabalaki 2, Christopher J Thompson 3. 1 Bruker Daltonik GmbH, Bremen, Germany; 2 Division of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece; 3 Bruker Daltonics Inc., Billerica, MA, USA.

Additionally, the data was subjected to multivariate data analysis (MDA), which revealed interesting clusters and trends according to significant discriminating factors of EVOO, such as geographical origin, cultivation practice and production procedure.

Methods

Sample collection: Samples were collected from the main Greek olive oil producing regions and stored at room temperature, in darkness, under nitrogen. Sample Prep: Stock solutions were prepared by dissolving 10 µL of samples in 500 µL MeOH. The stock solutions were then diluted 1:20 in 50% MeOH + 10 mM Ammonium Acetate.MS analysis: EVOO samples and their biophenolic extracts were analyzed

using a Bruker solariX XR 7T mass spectrometer using ESI (-) mode by FIA.

Data Preprocessing

The complete experimental work-flow is shown graphically in Figure 1. A detailed explanation for each step is as follows:

A Data was acquired via FIA-MRMS on a solariX XR 7T. Samples were run in five replicates, with a single mass spectrum acquired for each replicate.

B The 596 individual mass spectra were then loaded into Metabo- Scape 3.0, where the first step is the creation of a feature matrix (bucket table). Each feature is comprised of the molecular ion and its associated

Isotopic Fine Structure (IFS), if available. Additionally, the features may include possible adduct peaks and the associated isotopologues.

C Features were then annotated with a molecular formula using SmartFormula™ (SF). Annotation qualities are provided for each result (the first green bar means below 0.2 ppm mass deviation, the second green bar reports a mSigma below 50).

D Features can also be matched with known databases for putative structure annotations of interesting features. Again, matching qualities are provided for each result.

E Finally, the data was exported for advanced statistical analysis (SIMCA 14.1, Umetrics, Sweden), in order to identify the features of interest.

Figure 2: A OPLS-DA plot (scores plot-pareto scaling) of EVOO samples clustered according to geographical origin. Samples were separated in the first component according to the region and in the second component according to specific areas of each region. B OPLS-DA plot (scores plot-pareto scaling) of EVOO samples clustered according to cultivation practice.

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Figure 1: Schematic of the workflow performed in MetaboScape 3.0

A B D E

T-ReX 2D feature

extractions

596 FIA-MRMS measurements with

sub-ppm mass accuracy

596 x 2088 Feature Matrix incl. Isotope Patterns and

Isotopic Fine Structure

C

1104 Unique Molecular Formulas 678 Formulas with High-Score

50 Putative Structure Annotations

SmartFormula with IFS

Targeted Analyte List

e.g. elenolic acid

Data export for advanced

statistics

A BGeographical origin-EVOO Cultivation practice-EVOO

Conclusions

• LC free, FIA-MRMS based profiling enabled to distinguish different Greek extra virgin olive oils (EVOO).

• FIA facilitates EVOO analysis, requiring limited sample preparation.

• Interesting clusterings were revealed according to geographical origin of EVOO and the used cultivation practice.

• The responsible metabolite biomarkers were identified.

• MetaboScape 3.0 provides an intuitive and powerful new workflow which enabled the profiling of FIA-MRMS data and confident assignment of molecular formula for metabolite markers.

Acknowledgements

The present work is implemented with a State Scholarship Foundation (IKY). It is funded by the action “Strengthening Human Resources Research Potential via Doctorate Research.” With addi-tional funding from the operational program “Human Resources Develop-ment Program, Education and Lifelong Learning”, 2014-2020, and co-funding from the European Social Fund (ESF) and Hellenic government. The authors would like also to thank Greek olive oil producers for their kind support.

Figure 3: OPLS-DA plot (left scores plot-pareto scaling) of biophenolic extracts clustered according to geographical origin. The scores plot shows similar trend as Figure 2a. The dialdehydic forms of decarboxymethyl oleuropein and oleuropein could differentiate biophenolic EVOO extracts by region (right, loadings plot). Both compounds were significantly higher in extracts Heraklion and Lasithi (Crete) compared to the other regions.

Results

FIA-MRMS data acquired from EVOO samples enabled a clustering according to geographical origin, harvesting year, cultivation practice and the used oil production procedure using OPLS-DA multivatiate data analysis methods. Target compounds responsible for differentiation could tentatively be identified based on ultra-high resolution accurate mass information.

Table 1: The most significant metabolites responsible for sample separation in biophenolic extracts. These were tentatively identified by exact molecular formula annotation making use of accurate mass and isotopic fidelity.

Sample Molecular formula

Putative Name

Biophenolic

extracts

C8H10O3 Hydroxytyrosol

C11H14O6 Elenolic acid

C19H22O8 Oleuropein aglycon

C17H20O5 Dialdehydic form of decarboxymethyl ligstroside aglycon

C17H20O6 Dialdehydic form of decarboxymethyl oleuropein aglycon

0

-0.4

-0.1

-0.3

-0.2

0.2

0.1

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0.99

7301

* p

q[2]

-10,000

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10,000

0

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30,000

-80,000 -40,000 0 40,000 80,0001.00017 * t[1]

1.0

034

* t[2]

Geographical origin-Biophenols

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References

[1] Dion et al.; Food Chemistry 2008, 107:897-911[2] Kalogeropoulos et al.; Antioxidants 2014, 3:387-413