HIGH THROUGHPUT SAMPLE PREPARATION IN AMINO ACID ANALYSIS

Significance of the Topic

Automated amino acid analysis is critical for quality control in food, feed, and beverage industries, ensuring compliance with regulatory standards and accommodating rising sample volumes while minimizing manual labor and errors.

Objectives and Study Overview

This study aimed to develop and validate a 32-sample automated sample preparation protocol on the Andrew+ platform using the AccQ-Tag Ultra reagent kit and Food and Feed Standards Kit, and to benchmark its performance against manual preparation and existing high-throughput scripts on Hamilton Microlab Star and Tecan Freedom EVO systems.

Methodology and Instrumentation

• Automated derivatization workflow employing AccQ-Tag Ultra reagents in a 3 × 32 format with additional reagent volume to accommodate automation.
• Sample loading into 96-well plates for heating and transfer steps.
• Preparation of three solvent panels containing 21 amino acids at 10 µM, 200 µM, and 400 µM for recovery, linearity, and precision assessments.
• Instrumentation:
  • ACQUITY UPLC H-Class and H-Class Bio systems
  • Andrew+ automated pipetting platform
• Chromatographic conditions:
  • Column: AccQ-Tag Ultra 2.1 × 100 mm, 1.7 µm
  • Mobile phases: AccQ-Tag Ultra eluent A, eluent B, and water
  • Flow rate: 700 µL/min; column temperature: 49 °C; sample temperature: 20 °C; detection wavelength: 260 nm; injection volume: 1 µL

Key Results and Discussion

• Recovery: Mean recoveries for all 21 amino acids across 10, 200, and 400 µM panels were within ±10% of expected values for both automated and manual preparations.
• Linearity: Calibration curves over 0.5–500 µM (0.25–250 µM for cystine) displayed correlation coefficients (R²) ≥ 0.995 in all cases.
• Precision: The Andrew+ protocol achieved %CV values ≤ 1.2% for individual amino acids, outperforming manual preparation (%CV up to 2.9%) and matching or exceeding other automation platforms.
• Throughput: The complete derivatization and sample preparation for 96 samples was accomplished in under one hour, requiring minimal user intervention (start and end of run).

Benefits and Practical Applications

• Enhanced throughput reduces sample backlogs and accelerates routine quality control workflows.
• Standardized automation minimizes contamination risk and human error.
• Remote operation capability and simplified training improve laboratory flexibility and resource utilization.
• Consistent protocols facilitate method transfer across different laboratory environments and platforms.

Future Trends and Potential Applications

Integration of advanced sample tracking and laboratory information management systems (LIMS) with high-throughput platforms will further improve data integrity and workflow efficiency. Expanding the methodology to include non-proteinogenic amino acids, peptide mapping, and coupling with mass spectrometry detection could open new applications in food safety, pharmaceutical development, and clinical diagnostics.

Conclusion

The 32-sample Andrew+ automated protocol combined with AccQ-Tag Ultra chemistry delivers robust recovery, excellent precision, and strong linearity, matching or surpassing manual and other automated methods. This solution significantly enhances analytical capacity for amino acid profiling in food and feed quality control laboratories.

References

• Cullen D., Staffford N., Zhang N. High Throughput Sample Preparation in Amino Acid Analysis. Waters Technologies Ireland Ltd; Waters Corporation, 2020.