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High throughput targeted metabolomics library generation on a novel mass spectrometer applied to microbiome analysis

Posters | 2024 | Thermo Fisher Scientific | ASMSInstrumentation
LC/HRMS, LC/MS, LC/Orbitrap, LC/MS/MS
Industries
Metabolomics, Clinical Research
Manufacturer
Thermo Fisher Scientific

Summary

Significance of the topic


Advances in gut microbiome research have highlighted the crucial role of fecal metabolites in health and disease. Targeted metabolomics enables detailed profiling of amino acids, lipids, bile acids, and other small molecules in complex biological matrices. High-throughput, sensitive, and selective methods are essential to translate metabolomic insights into clinical diagnostics and biomarker discovery.

Objectives and study overview


This study aimed to develop and implement a comprehensive LC–MS library for fecal metabolites using the Thermo Scientific Stellar mass spectrometer. The primary goals were to achieve rapid, high-sensitivity quantitation across diverse compound classes and to demonstrate robust performance in a mouse dietary intervention model.

Methodology and instrumentation


Sample preparation involved extraction of fecal material with methanol or methanol–water mixtures to capture nonpolar and medium/high-polarity metabolites. Three chromatographic separations were employed on a Vanquish Horizon UHPLC system:
  • Reversed-phase on Hypersil GOLD C18 with 0.1% formic acid in water and methanol
  • HILIC on Accucore 150-Amide with 10 mM ammonium formate/0.1% formic acid and acetonitrile
  • Mixed-mode on Acclaim Trinity P2 with 40 mM ammonium acetate/0.1% acetic acid and acetonitrile

All analyses were performed on the Stellar mass spectrometer, featuring:
  • MS2 scan speed up to 140 Hz and MS3 up to 40 Hz
  • Rapid polarity switching in 5 ms
  • Dual HCD and CID fragmentation for MSn selectivity
  • Extended linear dynamic range over five orders of magnitude

Data acquisition and quantitation used Thermo Scientific Xcalibur and TraceFinder software with isotope-labeled internal standards.

Main results and discussion


  • Limits of quantitation as low as 12.7 fmol on-column for bile acids with linear response across 5 log units
  • High selectivity in distinguishing co-eluting isomers (e.g., GCDCA vs. GDCA) using diagnostic MS2 and MS3 ions without ion-pairing reagents
  • Reproducible retention times, mass accuracy, and low coefficients of variation across replicates
  • Heatmap visualization of dozens of metabolites in fecal extracts from mice fed varied diets, demonstrating biological differentiation
  • Shortened LC gradients (<25 min) without loss of sensitivity, enabling high-throughput operation

Benefits and practical applications


The method delivers rapid, comprehensive fecal metabolite profiling suitable for translational studies. Key advantages include minimal sample load requirements, high scan rates for more data points per peak, robust quantitation in complex matrices, and reduced solvent consumption. The Stellar platform streamlines biomarker verification workflows in metabolomics and lipidomics research.

Future trends and potential applications


Ongoing developments may integrate high-resolution imaging, enhanced real-time data processing, and artificial intelligence–driven compound identification. Expansion to clinical fecal diagnostics, personalized nutrition monitoring, and large-scale cohort studies will leverage the Stellar’s throughput and selectivity benefits. Coupling with automated sample preparation could further accelerate discovery-to-validation pipelines.

Conclusion


The Thermo Scientific Stellar mass spectrometer establishes a new benchmark for targeted fecal metabolomics by uniting ultrafast MSn acquisition, high sensitivity, and broad dynamic range. Its ability to quantify co-eluting isomers and handle diverse metabolite classes in a single workflow positions it as an essential tool for biomarker verification and translational research.

References


No formal literature list was provided in the source document.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

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