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Non-Derivatization LC/MS/MS Method for Determination of Amino Acids in Infant and Adult Nutritional Formulas Following AOAC Requirements

Applications | 2019 | ShimadzuInstrumentation
LC/MS, LC/MS/MS, LC/QQQ
Industries
Food & Agriculture
Manufacturer
Shimadzu

Summary

Importance of the Topic


Accurate quantification of proteinogenic amino acids, including essential amino acids and taurine, is critical for quality control of infant and adult nutritional formulas. Traditional HPLC methods require laborious derivatization steps; a non-derivatization LC/MS/MS approach streamlines analysis and improves throughput while meeting regulatory requirements such as AOAC SMPR 2014.013.

Objectives and Study Overview


This study validated a non-derivatization LC/MS/MS method for simultaneous determination of 18 amino acids and taurine in infant and adult formula matrices. Validation employed NIST SRM 1849a and commercially available infant and adult milk powders to assess accuracy, repeatability, and matrix effects.

Applied Instrumentation


  • Liquid Chromatograph: Shimadzu LC system equipped with Intrada Amino Acid Column (100 mm × 3 mm I.D., 3 µm)
  • Mass Spectrometer: Shimadzu LCMS-8045 triple quadrupole with heated ESI source
  • Detection Mode: Multiple Reaction Monitoring (positive and negative ion modes)
  • Mobile Phases: A (ACN/THF/25 mM ammonium formate/formic acid = 9/75/16/0.3), B (ACN/100 mM ammonium formate); gradient elution over 21 minutes
  • Source Conditions: Interface temperature 300°C, block 400°C, desolvation line 250°C; nebulizing gas N₂ (2 L/min), drying gas N₂ (10 L/min), heating gas zero air (10 L/min), collision gas Ar (230 kPa)

Methodology


  • Sample Hydrolysis:
    • Acid hydrolysis: 37% HCl with propionic acid, 160°C for 1 h
    • Alkaline hydrolysis: 4 N NaOH, 195°C for 1 h, pH adjusted to 4 post-hydrolysis (for tryptophan)
    • Pre-oxidation + acid hydrolysis: performic acid oxidation at 50°C for 1 h followed by acid hydrolysis (for cysteine/cystine)
  • Calibration: Six-point calibration curves (0.1 to 50 µM) prepared in 0.1 N HCl; repeatability assessed by replicate injections of 20 µM standard

Main Results and Discussion


Calibration curves demonstrated excellent linearity across the concentration range for all analytes. Method recovery for 6 amino acids (Ile, Val, Glu, Cys, His, Tau) fell within 86–109% of NIST values; 11 analytes showed recoveries between 71% and 138%, while alanine recovery was notably low (26%). Matrix effects ranged from 80% to 136% for acid-hydrolyzed samples. Application to six formula samples revealed that adult formulas contain over twice the total amino acid content compared to infant formulas, with glutamic acid, lysine, and aspartic acid as the most abundant residues.

Benefits and Practical Applications


  • Eliminates derivatization steps, reducing sample preparation time and potential sources of error
  • Single-run analysis of all target amino acids and taurine enhances laboratory throughput
  • Meets AOAC requirements for nutritional formula testing, supporting quality assurance and regulatory compliance

Future Trends and Potential Applications


Advancements may include automation of hydrolysis protocols, integration with high-throughput sample introduction systems, and extension of non-derivatization MS methods to additional bioactive compounds in complex food matrices. Further work addressing low analyte recovery, particularly alanine, will refine method robustness.

Conclusion


The validated non-derivatization LC/MS/MS method on the Shimadzu LCMS-8045 provides a reliable and efficient workflow for quantifying 18 amino acids and taurine in infant and adult nutritional formulas. While most analytes matched NIST reference values, the low recovery of alanine warrants additional optimization.

References


  • AOAC SMPR 2014.013. Standard Method Performance Requirements for Determination of Amino Acids in Infant Formula and Adult/Pediatric Nutritional Formula.
  • Spindler M, Stadler R, Tanner H. J Agric Food Chem. 1984;32:1366–1371.
  • Sun Z, Xing J, Khoo PY, Zhan Z. ASMS 2016; TP 740.

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