Simultaneous Quantitation and Discovery (SQUAD) analysis: Combining targeted and untargeted metabolomics on Orbitrap-based mass spectrometers

Importance of the Topic

Metabolomics has traditionally relied on either untargeted workflows for broad profiling or targeted assays for precise quantitation. Each approach faces limitations: untargeted metabolomics often sacrifices quantification accuracy, while targeted methods narrow the metabolite scope. Simultaneous Quantitation and Discovery (SQUAD) analysis addresses this trade-off by merging hypothesis-driven quantitation with discovery-based profiling in a single analysis, maximizing information yield from limited samples and supporting comprehensive molecular insights.

Objectives and Study Overview

This white paper aims to present the principles, workflow structures, and performance of SQUAD analysis on Orbitrap-based platforms. It reviews the challenges of conventional metabolomics, outlines the integrated SQUAD strategy, and demonstrates its implementation across three instrument classes: Orbitrap Exploris series, Orbitrap Tribrid, and the novel Orbitrap Astral. Case studies highlight sensitivity, dynamic range, throughput, and discovery capacity.

Methodology and Instrumentation

• Core Workflow: Single-injection LC-MS acquisition combining high-resolution accurate-mass (HRAM) full-scan MS1 for quantitation and data-dependent MS2 (DDA) for discovery.
• Quantitation Strategy: Use of authentic chemical standards and isotopically labeled internal standards to generate calibration curves for absolute or relative quantitation; one-point calibration or class-matched internal standards when necessary.
• Discovery Approach: HRAM MS1 data and rapid DDA or intelligent AcquireX workflows to annotate unknowns via spectral libraries.
• Quality Control: Pooled QC samples for signal normalization, system stability checks, and deep fragmentation mapping.

Main Results and Discussion

• Sensitivity and Dynamic Range: Orbitrap Exploris platforms achieved linear ranges of 5 orders of magnitude (25 nM–2.5 mM) with on-column LLOQ of 50 fmol. Orbitrap Tribrid extended this to 6 orders (2.5 nM–2.5 mM) with 5 fmol LLOQ via targeted MS2.
• Throughput and Coverage: Fast polarity switching on Exploris enabled >8 scans/peak for both positive and negative modes. The AcquireX intelligent acquisition increased MS2 sampling of relevant ions by up to 90%.
• Astral Performance: The Orbitrap Astral platform delivered MS1 LLOQ of 10 fmol (5 fmol LLOD) and maintained >8 scans/peak at 120K resolution. A 5-minute LC method on Astral yielded 25% more MS2 events and higher unknown annotation rates compared to a 15-minute Orbitrap-only run.
• Discovery Depth: Use of HCD, CID, and UVPD fragmentation (on Tribrid) enriched structural elucidation of lipids and glucuronides. Real-time library matching improved confidence in unknown annotation.

Benefits and Practical Applications

• Single-Injection Efficiency: Conserves sample, reduces analysis time, and minimizes variability across injections.
• Hybrid Insights: Enables concurrent targeted quantitation of known metabolites and annotation of novel compounds from the same dataset.
• Versatile Use Cases: Applicable in clinical biomarker studies, microbiome-host interaction, pharmacomicrobiomics, metabolic engineering, and natural product research.
• Data Reusability: Retrospective mining permits exploration of additional metabolites without new experiments.

Future Trends and Possibilities

• Expanded Spectral Libraries: Growth of curated HRAM fragmentation databases will enhance annotation coverage.
• Advanced Acquisition Automation: Further refinement of intelligent workflows (AcquireX) to target low-abundance features in real time.
• Integrated Pathway Analytics: Tighter coupling of SQUAD output with bioinformatics tools for pathway mapping and kinetic modeling.
• High-Throughput Applications: Adoption of ultrafast LC gradients with Astral to scale metabolomics for large-cohort studies.
• Broader Standard Accessibility: Collaborative efforts to synthesize and share authentic and labeled standards for under-represented metabolites.

Conclusion

SQUAD analysis unifies targeted and untargeted metabolomics into a robust, single-injection workflow. By leveraging HRAM MS1 quantitation alongside rapid MS2 discovery, laboratories can achieve accurate measurement of known compounds while capturing novel metabolic changes. The approach enhances throughput, conserves precious samples, and streamlines data interpretation, representing a transformative advancement in mass spectrometry-based metabolomics.

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