Agilent Captiva EMR–Lipid Automated Plate Preconditioning

Importance of the Topic

Preconditioning solid-phase extraction plates enhances reproducibility and recovery in LC/MS omics workflows. By equilibrating the Agilent Captiva EMR–Lipid sorbent with a solution that mimics sample composition, nonspecific binding is minimized and subsequent fractionation of metabolites, lipids, and proteins from plasma or cell lysates is more efficient.

Objectives and Study Overview

This guide outlines an automated protocol for preconditioning 96-well Captiva EMR–Lipid plates on the Agilent Bravo Metabolomics Sample Prep Platform. The goals are to standardize plate performance, streamline sample preparation, and integrate seamlessly into existing Agilent end-to-end LC/MS omics methods.

Methodology and Instrumentation

The protocol uses a preconditioning solvent composed of water:methanol:ethanol in a 2:1:1 ratio. Key steps include:

• Preparing 180 mL of LC/MS-grade preconditioning solvent per plate.
• Configuring the Bravo software form for plate dimensions and sealing unused wells.
• Automated delivery of two 800 µL aliquots of solvent to each well.
• Vacuum filtration of solvent through the sorbent, with optional additional vacuum time to ensure complete elution.

Used Instrumentation

• Agilent Bravo Metabolomics Sample Prep Platform
• Agilent Captiva EMR–Lipid 96-well plates (part no. 5190-1001)
• LC/MS-grade solvents and a Milli-Q Integral water system with 0.22 µm cartridge

Main Results and Discussion

Automated preconditioning produced uniformly equilibrated plates, reducing variability in subsequent extraction steps. By matching the sorbent environment to sample solvents, analyte recovery improved, particularly for low-abundance metabolites and lipids. The protocol minimized manual intervention and shortened overall sample preparation time.

Benefits and Practical Applications

Implementing this automated preconditioning method offers:

• Increased throughput and consistency for large sample batches.
• Reduced solvent consumption by optimizing elution volumes.
• Enhanced compatibility with downstream automated metabolite and lipid fractionation workflows.

Future Trends and Opportunities

Advances may include further miniaturization of preconditioning volumes, integration with multi-omics platforms, and adaptive protocols that adjust solvent composition based on sample matrix analytics. Machine learning could optimize preconditioning parameters in real time to maximize recovery across diverse sample types.

Conclusion

Automated plate preconditioning using the Agilent Bravo platform and Captiva EMR–Lipid plates standardizes sample preparation for LC/MS omics. The method improves analyte recovery, reduces variability, and integrates smoothly into high-throughput workflows, advancing metabolomics and lipidomics studies.

References

1. Sartain M, et al. Enabling Automated, Low-Volume Plasma Metabolite Extraction with the Agilent Bravo Platform. Agilent Technologies Application Note 5994-2156EN, 2020.
2. Van de Bittner GC, et al. An Automated Dual Metabolite + Lipid Sample Preparation Workflow for Mammalian Cell Samples. Agilent Technologies Technical Overview 5994-5065EN, 2022.
3. Van de Bittner GC, et al. Automated Fractionation of Low-Volume Plasma Samples for LC/MS Multi-Omics. Agilent Technologies Technical Overview 5994-7357EN, 2024.