Targeted and untargeted metabolomics – a powerful hybrid workflow enabled by a biocrates kit on timsMetabo HRMS

Significance of the topic

The integration of targeted quantitative workflows with high-resolution, ion-mobility-enabled untargeted metabolomics addresses a key analytical challenge: obtaining reproducible, absolute concentrations for defined metabolite panels while simultaneously expanding biochemical coverage to discover unexpected or low-abundance species. This hybrid approach supports robust clinical and translational studies, quality-controlled biomarker verification, and broader exposome and pathway interrogation from a single LC-TIMS-MS acquisition.

Objectives and study overview

• Develop and demonstrate a hybrid targeted/untargeted metabolomics workflow that uses the biocrates standardized kit for absolute quantification together with TIMS-PASEF full-scan acquisition on the timsMetabo HRMS for expanded structural annotation.
• Compare quantitative performance of timsMetabo (MS1 accurate-mass based quantification) to a conventional triple-quadrupole instrument (EVOQ TQ+).
• Showcase untargeted, 4D (m/z, RT, intensity, CCS) annotation depth and biological insights in human plasma samples.

Methods

• Sample set: 21 individual human plasma samples (11 male including one lipemic, 10 female) plus NIST SRM 1950; samples arranged on 96-well plates and measured in triplicate.
• Biocrates kit-based preparation: two patented 96-well filter plates; sample aliquoting of 30 µL split across two plates (10 µL and 20 µL); derivatization with PITC (positive mode) or 3-NPH (negative mode), followed by extraction.
• Acquisition: single LC-TIMS-PASEF data acquisition using optimized MoRE PASEF methods on the timsMetabo (Bruker) HRMS. Parallel comparison measurements performed on EVOQ TQ+ (triple quad).
• Data processing: targeted absolute quantification and reporting in TASQ 2026b / WebIDQ; untargeted feature discovery, ion-mobility-resolved MS/MS annotation and confidence scoring in MetaboScape 2026b. Export of quantified results for visualization and performance evaluation.
• Annotation resources: spectral libraries (NIST 2023; Maurer, Meyer, Helfer, Weber LC-HR-MS/MS library of drugs and poisons; Bruker HMDB Metabolite Library 2.0). In-silico derivatization and auto MS/MS/CCS prediction applied for greater annotation coverage.

Used instrumentation

• timsMetabo HRMS with TIMS-PASEF capability (Bruker) using MoRE PASEF LC-HRMS methods.
• EVOQ TQ+ triple quadrupole mass spectrometer (comparison platform).
• Biocrates targeted metabolomics kit (two 96-well filter plates, calibration standards, internal standards, QCs).
• Software: TASQ 2026b, WebIDQ, MetaboScape 2026b.
• Spectral libraries: NIST 2023; Maurer et al. LC-HR-MS/MS Library; Bruker HMDB Metabolite Library 2.0.

Main results and discussion

• Quantitative performance: timsMetabo achieved detection of 250 ± 11 targeted analytes in plasma (six counted as sum-signals of coeluting isomers), compared with 259 ± 14 on EVOQ TQ+. Median replicate CV on timsMetabo was 8% (EVOQ TQ+: 6%), indicating comparable reproducibility.
• Accuracy and comparability: measured concentrations between instruments were consistent, and certified analytes in NIST 1950 SRM measured on timsMetabo showed accuracies within the 80–120% range.
• Untargeted annotation depth: combining TIMS-resolved MS/MS with MetaboScape annotation workflows produced a ~3-fold increase in annotated features versus the targeted list alone. In spiked pooled plasma QC3, 528 annotated features were reported (291 analytes + 237 internal standards) at high confidence (Level 1) when using target-list-based and library-based workflows.
• Mode- and derivatization-specific coverage: PITC derivatization (positive mode) and 3-NPH derivatization (negative mode) yielded complementary annotation sets. Example counts included positive-mode subsets (178 annotations: 107 targets + 71 ISTDs) and negative-mode subsets (350 annotations: 184 targets + 166 ISTDs).
• Annotation confidence tiers: MetaboScape supported a multilayered annotation strategy (L1: confirmed by standards / libraries; L2a/b: library or spectral match with MS/MS score/coverage thresholds; L3: in-silico derivatization with explained MS/MS coverage), enabling structured interpretation of discovery identifications.
• Biological insights: the untargeted TIMS-PASEF data revealed biology beyond the kit panel, including lysophosphatidylcholine (LPC) markers characteristic of a lipemic sample (M11) and exposome-related molecules such as piperine and aspartame. PCA separated the lipemic sample and showed partial sex-related separation; individual-level variation was observable for exposome compounds.

Benefits and practical applications of the method

• Single-run capability: a single LC-TIMS-PASEF acquisition supports both validated targeted quantification and broad untargeted discovery, improving throughput and sample economy.
• Standardization and scalability: the biocrates kit provides validated retention times, calibration curves and internal standards for absolute quantification; combining this with timsMetabo retains standardization while extending coverage.
• Enhanced structural confidence: ion mobility (CCS), library MS/MS, predicted in-silico MS/MS and RT constraints increase annotation reliability for discovery features.
• Practical use cases: clinical research and cohort studies that require both absolute concentration data for biomarker panels and the ability to discover novel or exogenous metabolites (exposome) from the same dataset.

Future trends and possibilities for application

• Expanded reference resources: growth of validated spectral libraries, reference CCS, and retention-time libraries will further raise annotation confidence and enable more L1 assignments from untargeted data.
• Machine learning integration: improved in-silico MS/MS and CCS prediction models will boost annotation speed and reliability for molecules lacking reference spectra.
• Automation and workflows: tighter integration of acquisition, automated annotation confidence scoring, and standardized reporting will facilitate adoption in regulated QA/QC and clinical pipelines.
• 4D multiomics integration: combining TIMS-enhanced metabolomics with lipidomics, proteomics and other omics layers will create richer, mobility-resolved multiomic datasets for systems biology.
• Isomer resolution and targeted method refinement: leveraging TIMS separation to resolve coeluting isomers and to refine quantitation strategies for structurally similar analytes.

Conclusion

The presented hybrid workflow demonstrates that standardized biocrates kit-based absolute quantification can be harmonized with TIMS-PASEF untargeted discovery on the timsMetabo HRMS. Performance metrics (coverage, precision, accuracy) are comparable to triple-quadrupole quantitation while delivering substantially deeper annotation through ion mobility-resolved MS/MS. This unified approach enables scalable, reproducible targeted measurements together with enhanced structural insight, supporting broader biological interpretation from a single, efficient analytical pipeline.

References

• Hai Pham-Tuan, Aiko Barsch, Cristian De Gobba, Nikolas Kessler, Ilmari Krebs, Martin Buratti, Agnes Scharrer, Doreen Kirchberg, Ulf Sommer, Guido Dallmann, Matthew R Lewis. Targeted and untargeted metabolomics – a powerful hybrid workflow enabled by a biocrates kit on timsMetabo HRMS. SMS 2026, WP 519. Bruker Corporation, 2026. Poster. For Research Use Only.