Simultaneous quantitation of amino acid mixtures using clustering agents

Area of Science:

• Analytical Chemistry
• Biochemistry
• Physical Chemistry

Background:

• Accurate determination of solution-phase molar fractions in multi-component mixtures is crucial for various scientific disciplines.
• Traditional methods often rely on specific standards, which may not always be readily available for complex mixtures.
• Electrospray ionization (ESI) is a powerful technique for analyzing biomolecules, but ionization biases can affect quantitative accuracy.

Purpose of the Study:

• To demonstrate a novel method for determining solution-phase molar fractions of amino acids using cluster abundances from ESI.
• To assess the accuracy and limitations of this clustering method in multi-component amino acid mixtures.
• To explore the potential applications of this technique, especially in scenarios lacking traditional standards.

Main Methods:

• Utilizing the relative abundances of large clusters formed during electrospray ionization.
• Analyzing four- and 10-component mixtures of amino acids.
• Comparing molar fractions derived from cluster abundances with actual solution-phase molar fractions.

Main Results:

• For four-component mixtures, molar fractions determined from large clusters (≥19 molecules) were within 25% of solution values.
• For 10-component mixtures, accuracy decreased, with values typically within a factor of three of solution molar fractions.
• Significant differences (up to 30-fold and 100-fold) were observed between solution molar fractions and relative abundances of protonated molecules in four- and 10-component mixtures, respectively.

Conclusions:

• The abundance and composition of large ESI clusters reflect relative amino acid concentrations in solution, reducing ionization and detection biases.
• The clustering method shows promise for quantifying amino acids when traditional standards are unavailable, particularly for simpler mixtures.
• Lower accuracy in complex mixtures may stem from specific clustering effects or signal-to-noise limitations, warranting further investigation.