The fully on-line automation of MOX-TMS derivatisation for metabolomics applications
Applications | 2016 | AnatuneInstrumentation
The full automation of methoximation and silylation (MOX-TMS) derivatisation streamlines sample preparation for metabolomics by improving reproducibility and reducing manual handling. This approach enhances the detection of a wide range of metabolites using GC-MS.
This study presents an integrated, fully automated workflow for protein precipitation followed by MOX-TMS derivatisation of serum samples. The performance and reproducibility were evaluated using an internal standard and comprehensive component analysis.
The internal standard (Adonitol 5TMS) exhibited excellent reproducibility with relative standard deviations of 1% (TIC) and 6% (EIC). Automated processing of serum samples revealed approximately 2 300–2 600 components per replicate, with 36–40% library matches and 10–13% confirmed TMS derivatives. The blank control showed 1 517 components, highlighting the method sensitivity and sample complexity.
The fully automated MOX-TMS workflow reduces manual intervention, minimizes variability, and enhances throughput for metabolomics studies. It enables reliable profiling of polar metabolites in complex biological matrices, supporting applications in biomarker discovery, clinical research, and quality control.
Advances may include coupling with high-throughput robotics, integration with data processing platforms for real-time analysis, and adaptation to other sample types. Emerging derivatisation reagents and multi-omics integration are expected to expand the analytical scope.
This work demonstrates a robust, reproducible, and high-throughput solution for on-line protein precipitation and MOX-TMS derivatisation, offering improved efficiency and consistency in GC-MS–based metabolomics.
GC/MSD, GC/MS/MS, GC/HRMS, Sample Preparation, GC/Q-TOF
IndustriesMetabolomics
ManufacturerAgilent Technologies, GERSTEL, Anatune
Summary
Significance of the Topic
The full automation of methoximation and silylation (MOX-TMS) derivatisation streamlines sample preparation for metabolomics by improving reproducibility and reducing manual handling. This approach enhances the detection of a wide range of metabolites using GC-MS.
Objectives and Study Overview
This study presents an integrated, fully automated workflow for protein precipitation followed by MOX-TMS derivatisation of serum samples. The performance and reproducibility were evaluated using an internal standard and comprehensive component analysis.
Methodology and Instrumentation
- Sample preparation: Protein precipitation with methanol followed by centrifugation and evaporation to achieve anhydrous conditions.
- Derivatisation steps: Initial methoximation at 30 °C to stabilize carbonyl groups, followed by trimethylsilyl derivatisation at 37 °C.
- Automation platform: GERSTEL Multipurpose Sampler (MPS) 2 XL Dual head equipped with solvent reservoirs, wash station, vortexer, evaporation station, and robotic centrifuge.
- GC-MS analysis: Agilent 7890B GC with HP-5MS column and Agilent 7200B Q-TOF HRMS in EI mode. Temperature program from 50 °C to 300 °C and mass scan range 35–500 m/z.
Main Results and Discussion
The internal standard (Adonitol 5TMS) exhibited excellent reproducibility with relative standard deviations of 1% (TIC) and 6% (EIC). Automated processing of serum samples revealed approximately 2 300–2 600 components per replicate, with 36–40% library matches and 10–13% confirmed TMS derivatives. The blank control showed 1 517 components, highlighting the method sensitivity and sample complexity.
Benefits and Practical Applications
The fully automated MOX-TMS workflow reduces manual intervention, minimizes variability, and enhances throughput for metabolomics studies. It enables reliable profiling of polar metabolites in complex biological matrices, supporting applications in biomarker discovery, clinical research, and quality control.
Future Trends and Applications
Advances may include coupling with high-throughput robotics, integration with data processing platforms for real-time analysis, and adaptation to other sample types. Emerging derivatisation reagents and multi-omics integration are expected to expand the analytical scope.
Conclusion
This work demonstrates a robust, reproducible, and high-throughput solution for on-line protein precipitation and MOX-TMS derivatisation, offering improved efficiency and consistency in GC-MS–based metabolomics.
Reference
- Liscio C. The fully on-line automation of MOX-TMS derivatisation for metabolomics applications. Chromatography Technical Note No AS164S; 2016.
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