Simultaneous quantitation and discovery (SQUAD) analysis of the fruit juice metabolome

Significance of the topic

Comprehensive chemical profiling of fruit juices is important for nutrition science, food quality control, authentication, and discovery of novel bioactive compounds. Flavonoids and other polyphenols contribute to health-related properties and can serve as markers of raw material origin and processing. A workflow that combines accurate targeted quantitation with untargeted discovery and structural elucidation in a single LC-MS run increases laboratory throughput and provides richer insight into complex food matrices.

Goals and study overview

The application note demonstrates a simultaneous quantitation-and-discovery (SQUAD) workflow applied to commercially available fruit juices (cranberry, grape, tart cherry, lemonade, watermelon lemonade). Objectives were to: enable accurate targeted quantitation of selected polyphenols; perform untargeted discovery of known and novel natural products; apply multi-stage MSn fragmentation to support structure-based flavonoid profiling; and perform differential statistical analyses to identify discriminating metabolites across juice types.

Methodology

Samples were filtered and diluted 1:1 with methanol. Polyphenol calibration standards (e.g., rutin, quercetin, rosmarinic acid) were prepared in 1:1 water:methanol and used to build calibration curves across 10–1,000 ppb for absolute quantitation. The analytical workflow integrated targeted and untargeted acquisition within the same batch by interleaving calibration standards, blanks, pooled QCs, and sample injections to support both TraceFinder-based quantitation and Compound Discoverer–based discovery.

Key acquisition strategies:

• Reversed-phase UHPLC separation using an Accucore aQ column (100 x 2.1 mm, 2.6 μm) with 0.1% formic acid in water (A) and methanol (B), gradient 97:3 to 5:95, 0.4 mL/min, 35 °C, 2 μL injection.
• Full-scan polarity-switching HRAM MS at 120,000 resolution (m/z 150–1,200) with data-dependent MS2/MS3 (ddMSn) acquisition and a 0.9 s cycle time.
• Decision-tree MSn strategy: HCD MS2 for precursors <420 Da; CID MS2 + CID MS3 for precursors >420 Da when characteristic sugar neutral losses were detected, enabling detailed glycoside structural characterization.
• AcquireX Deep Scan intelligent workflow to populate targeted and exclusion lists and enhance fragmentation coverage for pooled matrix samples.

Used instrumentation

The analyses were performed on a Thermo Scientific Vanquish Flex UHPLC coupled to an Orbitrap Ascend MultiOmics Tribrid Mass Spectrometer with OptaMax NG H-ESI source. Key MS features exploited include dual ion-routing multipoles (IRM) for parallelized ion handling, a dual-pressure linear ion trap enabling true MSn, availability of multiple fragmentation methods (CID, HCD, optional UVPD), and EASY-IC internal calibration for high mass accuracy. Data acquisition used Xcalibur with AcquireX; TraceFinder v5.2 was used for targeted quantitation and Compound Discoverer v3.5 for untargeted processing, annotation, and statistics.

Main results and discussion

The SQUAD workflow successfully combined absolute quantitation and in-depth structural discovery in the same runs. Calibration curves for rosmarinic acid and rutin were linear across 10–1,000 ppb, supporting confident quantitation. The decision-tree MSn approach generated informative MS2 and MS3 spectra that aided in discriminating flavonoid aglycones and glycosides, and enabled localization of glycosylation sites through saccharide neutral loss triggering.

Compound Discoverer produced an integrated list of detected features with multi-source annotations (mzCloud, mzVault, ChemSpider, mass lists, predicted formulas). Key capabilities demonstrated:

• Spectral library matching rapidly identified known polyphenols (example: kaempferol 3-robinobioside identified by MSn spectral matches).
• FISh scoring provided in silico fragmentation comparisons to rank structural candidates for unknowns (example: differentiation between gossypetin 3-glucuronide and myricetin 5-O-glucuronide proposals for an m/z 493.065 feature).
• Molecular networking clustered related flavonoid features, revealing putative chemical transformations (e.g., glucuronidation, nitro reduction) and assisting discovery of novel analogs.
• Differential analyses (PCA, hierarchical clustering, volcano plots) identified compounds that discriminate juice types and visualized trends across sample groups.

Benefits and practical applications

The SQUAD workflow provides multiple practical advantages:

• Higher throughput by combining targeted quantitation and untargeted discovery in a single LC-MS sequence.
• Improved confidence in structural assignments through MSn-enabled fragmentation and FISh-supported ranking.
• Comprehensive profiling useful for food authenticity, quality control, nutraceutical discovery, and research into processing effects.
• Flexible application of AcquireX to maximize fragmentation of sample-relevant ions while minimizing redundant MSn on background ions.

Future trends and potential uses

Opportunities building on this approach include:

• Extension to broader natural-product classes (e.g., alkaloids, terpenoids) and other food and beverage matrices.
• Integration with ion mobility and orthogonal separations to resolve isomers and improve structural confidence.
• Improved automated structure annotation using expanding spectral libraries and machine-learning fragmentation predictors to accelerate unknown identification.
• Application in routine QA/QC pipelines for authentication, adulteration detection, and monitoring of processing-induced chemical changes.

Conclusion

The reported SQUAD workflow demonstrates that high-resolution Orbitrap Ascend MultiOmics Tribrid MS combined with Compound Discoverer and TraceFinder software can deliver simultaneous accurate quantitation and comprehensive discovery of the fruit juice metabolome within a single LC-MS run. Multi-stage MSn acquisition and intelligent acquisition strategies provide enhanced structural information that improves identification confidence and supports structure-based flavonoid profiling, while integrated statistical tools facilitate comparative analyses across sample types.

Reference

1. Thermo Fisher Scientific Application Note 003277: Novel structure-based profiling and annotation workflow—high-throughput analysis of flavonoids using the Thermo Scientific Orbitrap ID-X Tribrid MS.
2. Thermo Fisher Scientific Technical Note 004327: Simultaneous Quantitation and Discovery analysis: Combining targeted and untargeted metabolomics on Orbitrap mass spectrometers.
3. Thermo Fisher Scientific Application Note 003385: Confident transformation site localization of PROTAC drug metabolites facilitated by multi-stage fragmentation LC-MS.
4. Thermo Fisher Scientific Application Note 002154: Increased confidence in drug metabolite identification through intelligent data acquisition strategies and multiple fragmentation techniques on the Orbitrap Tribrid MS platform.
5. Thermo Fisher Scientific Product Specification 002859: Scale up your multiomics research—Orbitrap Ascend MultiOmics Tribrid mass spectrometer.