Amino Acid Analysis Methods

Amino acid profiling serves as a vital investigative tool across diverse domains, including biochemistry, biomedical research, nutritional sciences, and pharmaceutical development. Over decades, analytical methodologies for amino acid characterization have evolved significantly, transitioning from classical chromatographic techniques to advanced high-throughput mass spectrometry (MS), each offering distinct advantages tailored to specific applications.

This review systematically examines contemporary approaches for amino acid analysis, encompassing chromatographic separation, electrophoretic techniques, enzymatic assays, and MS-based platforms. A critical comparison of these methodologies is presented to underscore the superior resolution, sensitivity, and multiplexing capabilities of modern MS technologies. By evaluating technical parameters such as detection limits, throughput efficiency, and compatibility with complex matrices, we emphasize how MS has revolutionized amino acid quantification and structural elucidation in both fundamental research and industrial settings.

Chromatographic Techniques

Chromatographic methods are pivotal for amino acid characterization, with HPLC, GC, and IEC being widely employed across research and industrial applications. Below is an expanded overview of their principles, applications, and evolving advancements:

(1) HPLC

• Principle of Operation: Separation relies on differential partitioning of analytes between a stationary phase (e.g., C18 column) and a mobile phase (e.g., gradient elution with water/acetonitrile).
• Operational Steps:
  • Sample Preparation: Plasma/serum samples are centrifuged, filtered (0.22 μm), and diluted to remove particulates.
  • Column Conditioning: Equilibrate the C18 column with initial mobile phase (e.g., 95% water, 5% acetonitrile, 0.1% formic acid).
  • Gradient Elution: Program a gradient from low to high organic phase (e.g., 5% → 95% acetonitrile over 30–60 min) to elute analytes based on hydrophobicity.
  • Detection: Eluted analytes are ionized (e.g., ESI) and analyzed via tandem mass spectrometry (MRM mode) for quantification.
  • Data Analysis: Retention times and peak areas are compared to reference standards for identification and quantification.
• Derivatization Requirement: Pre-column derivatization with agents like OPA or Dansyl Chloride enhances UV/fluorescence detection sensitivity. Newer reagents (e.g., AccQ-Tag) reduce reaction time.
• Strengths: Exceptional resolving power for complex matrices (e.g., biological fluids, food extracts). Compatibility with mass spectrometry (LC-MS) for structural confirmation.
• Limitations: Prolonged runtimes for gradient elution (30–60 minutes). Derivatization inefficiency for secondary amines (e.g., proline).
• Applications:
  • Protein hydrolysate analysis: Gac seed protein was hydrolyzed by simulated gastrointestinal digestion, and ACE inhibitory peptides were screened from complex hydrolysates by using HILIC and RP-HPLC. RP-HPLC was further purified by hydrophobic difference, and the highly active fraction (RP-F8) was screened out. A novel tetrapeptide Alvy (IC = 7.03 μ m) was identified by LC-MS/MS, which acted as a competitive inhibitor by binding to S1/S2 active pocket of ACE (molecular docking verification) (Ngamsuk S et al., 2020).

RP-HPLC chromatogram of HILIC FT fraction (Ngamsuk S et al., 2020).

• Clinical diagnostics (plasma amino acid profiling): The distribution difference of D/L- amino acids in plasma and urine was accurately analyzed by 2D-HPLC technology, and its clinical value was revealed. Trace D- amino acids in plasma (1% of total amino acids) suggest endogenous metabolism or flora, while the excretion rate of D- type in urine is more than 10 times higher than that in plasma, indicating an efficient renal clearance mechanism. Plasma D/L ratio was positively correlated with renal function indexes (BUN, Cystatin C) (p<0.01), or it was a new marker of early renal injury. The level of L- amino acids (such as leucine) is associated with obesity, abnormal liver function and hyperuricemia (p<0.05), which points to the regulatory target of metabolic syndrome (Suzuki M et al., 2022).

(2) GC

• Principle of Operation: Volatility-driven separation in the gaseous phase using inert carrier gases (e.g., helium) under temperature-programmed conditions.
• Operational Steps:
  • Sample Derivatization: Convert amino acids to volatile derivatives (e.g., esterify with trifluoroacetic anhydride (TFA) or silylate with BSTFA) to enhance vaporization.
  • Injection: Introduce the derivatized sample into a vaporizing injector (split/splitless mode) at controlled temperatures (e.g., 250°C).
  • Temperature Programming: Set a gradient (e.g., start at 50°C, ramp at 10°C/min to 300°C) to separate analytes based on boiling points.
  • Column Separation: Use a capillary column (e.g., DB-5MS) with stationary phase polarity matched to analyte volatility.
  • Detection: Eluted compounds are ionized (e.g., electron impact in GC-MS) and detected via FID (flame ionization) or mass spectrometry (selected ion monitoring, SIM).
  • Data Analysis: Quantify peaks via retention time alignment with standards and integrate signal intensity for quantification.
• Derivatization Requirement: Amino acids are converted to volatile derivatives (e.g., TFA-modified esters) for vaporization. New silylation agents (e.g., BSTFA) improve derivatization efficiency.
• Strengths: Superior resolution for small, volatile derivatives (e.g., branched-chain amino acids). High sensitivity when coupled with flame ionization (FID) or mass detectors (GC-MS).
• Limitations: Restricted to thermally stable derivatives; degradation occurs above 250°C. Inapplicable to polar, non-volatile amino acids (e.g., arginine) without extensive modification.

(3) IEC

• Principle of Operation: Charge-based separation via electrostatic interactions between amino acids and functionalized resins (e.g., sulfonated polystyrene for cation exchange).
• Operational Steps:
  • Sample Preparation: Acidify biological samples (e.g., serum) to protonate amino acids, then filter (0.45 μm) to remove particulates.
  • Column Equilibration: Pre-treat the cation-exchange column with low-concentration buffer (e.g., pH 2.2 sodium citrate) to activate binding sites.
  • Loading & Elution: Inject sample, then apply a pH/ionic strength gradient (e.g., pH 3.3–10.0 with lithium citrate buffers) to elute amino acids based on charge and hydrophobicity.
  • Post-Column Derivatization: React eluted amino acids with ninhydrin (heated reaction coil at 120°C) to form colored complexes, or OPA-thiol for fluorescence (ex/em: 340/450 nm).
  • Detection: Measure absorbance at 570 nm (ninhydrin) or fluorescence intensity (OPA), correlating peak area to concentration via calibration curves.
  • System Regeneration: Re-equilibrate column with starting buffer for ≥30 minutes to ensure reproducibility.
• Derivatization Requirement: Post-column ninhydrin reactions generate chromophores detectable at 570 nm. Modern systems use OPA-thiol for real-time fluorescence detection.
• Strengths: Simultaneous quantification of 20+ amino acids in a single run. Cost-effective for routine analysis in agricultural or clinical labs.
• Limitations: Lower sensitivity (micromolar range) compared to LC-MS. Buffer equilibration times extend total analysis duration (≥90 minutes).
• Applications:
  • Detection of phenylketonuria: IEC realizes accurate quantification of Phe based on amino acid charge difference. By comparing IEC with FIA-MS-MS, it is found that the concentration of Phe in red blood cells is significantly lower than that in EDTA plasma (p<0.01), resulting in a systematic low detection value of dried blood spots (DBS) of 19%. Aiming at the nonlinear heteroscedasticity relationship between DBS and plasma concentration, a quantile regression model (75th percentile slope β=0.81) was proposed to correct DBS results, which reduced the error from 28% to 9% and ensured the consistency between PKU treatment decision and plasma-based guidelines (Haas D et al., 2021).

Comparison of Phe concentrations in dried blood (DBS) (a) and erythrocytes (DES) (b) measured by IEC (x-axis) and FIA-MS-MS (y-axis) (n = 10) (Haas D et al., 2021).

Electrophoretic Techniques

Electrophoretic approaches serve as critical tools for amino acid characterization, with capillary electrophoresis (CE) and gel-based systems being widely utilized in research and industrial contexts. Below is an expanded overview of their methodologies, advancements, and practical considerations:

(1) Capillary Electrophoresis (CE)

• Operational Principle: Separation is achieved through differential electrophoretic mobility of charged amino acids under an applied electric field within narrow fused-silica capillaries (50–100 μm inner diameter).
• Operational Steps:
  • Capillary Pretreatment: Rinse capillary sequentially with NaOH (0.1 M, 5 min), deionized water (2 min), and running buffer (e.g., borate pH 9.2, 3 min) to activate the silanol groups and stabilize electroosmotic flow (EOF).
  • Sample Derivatization: Label amino acids with FITC (fluorescein isothiocyanate) in alkaline conditions (pH 9.5, 60°C, 30 min), then purify via solid-phase extraction to remove excess reagent.
  • Hydrodynamic Injection: Introduce nanoliter-scale sample into the capillary via pressure (e.g., 50 mbar for 10 s) or electrokinetic injection (5 kV, 10 s).
  • Electrophoretic Separation: Apply high voltage (15–30 kV) across the capillary to drive analyte migration, leveraging pH-controlled buffer (e.g., borate with SDS micelles) to modulate charge and mobility differences.
  • Detection: Use laser-induced fluorescence (LIF, ex/em: 488/520 nm) for FITC-labeled analytes, or couple with CE-MS via sheath-flow interface for structural identification.
  • Data Normalization: Compensate for migration time variability by adding internal standards (e.g., D-camphorsulfonic acid) and calibrating retention indices against reference libraries.
• Chemical Modification: Pre-analysis fluorescent tagging (e.g., FITC, dansyl chloride) enhances detection sensitivity, particularly for UV-transparent analytes. Emerging labels like AccQ-Fluor™ reduce derivatization time while improving signal stability.
• Key Advantages: Ultra-high separation efficiency (theoretical plates > 500,000/m) due to minimized diffusion. Minimal sample consumption (nanoliter volumes), ideal for rare biological specimens. Compatibility with advanced detectors (e.g., laser-induced fluorescence (LIF) or mass spectrometry (CE-MS)).
• Technical Constraints: Moderate sensitivity (micromolar range) compared to LC-MS/MS. Migration time variability caused by buffer composition fluctuations or capillary wall interactions.
• Applications:
  • Food evaluation: In this study, derivatization-free capillary electrophoresis (CZE) was used to directly analyze 16 hydrophobic/alkaline amino acids (such as Phe, His and Tyr) in salted herring fillets and brine, and a new maturity index was established. With the advantages of high separation efficiency (resolution > 1.5) and no need for derivatization, CE can accurately capture the dynamic changes of amino acids in the pickling process: the peak-to-height ratio of Phe/Tyr in fish increases with maturity (↑37%), while the peak-to-height ratio of His/Tyr in brine decreases (↓52%), which is 2.1 times more sensitive than the traditional non-protein nitrogen index. Statistical regression (R²adj=0.92) and PCA confirmed that CE index was highly correlated with sensory texture (TPA hardness) (r=0.85), which overcame the problem of amino acid composition deviation caused by acetic acid pickling (Felisiak K et al., 2021).

Electrophoregrams of TCA extract of (A) raw herring meat and after 1–21 days of salting and (B) brine (Felisiak K et al., 2021).

• Metabolic monitoring: Short capillary electrophoresis (effective length of 18 cm) combined with non-contact conductivity detection (CD) is used, and only 15 μL plasma can be directly injected after acetonitrile precipitation, which simplifies the pretreatment. Clinical verification showed that the basic levels of plasma BCAA and glutamine in patients with pancreatic cancer and cachexia were significantly decreased (38% compared with the healthy group), and they lost the ability of insulin regulation. CE/CD provides an efficient solution for monitoring metabolic abnormalities with its advantages of rapidity (valine 2.01 min/ glutamine 2.84 min), high sensitivity and low sample size (Tůma P et al., 2021).

(2) Gel Electrophoresis

• Operational Principle: Differential migration of amino acids through a porous gel matrix (e.g., polyacrylamide or agarose) under electrophoretic conditions, driven by charge-to-mass ratios.
• Operational Steps:
  • Sample Preparation: Acid-hydrolyze protein samples (6 M HCl, 110°C, 24 h) to release free amino acids. Reduce disulfide bonds (e.g., with β-mercaptoethanol) and denature proteins in loading buffer (SDS-containing).
  • Gel Casting: Prepare polyacrylamide gel (e.g., 12% resolving gel with Tris-HCl pH 8.8, 4% stacking gel with Tris-HCl pH 6.8) to optimize pore size for amino acid separation.
  • Electrophoresis Setup: Load samples and molecular weight markers into wells. Submerge gel in running buffer (Tris-glycine-SDS, pH 8.3) and apply constant voltage (e.g., 100 V for stacking, 150 V for resolving phase) for 1–2 hours.
  • Post-Run Staining: Fix proteins/amino acids in gel with 40% ethanol/10% acetic acid (30 min). Stain with Coomassie Brilliant Blue (0.1% in 40% methanol/10% acetic acid, 1 h) or SYPRO Ruby (overnight for fluorescence). Destain (40% methanol/10% acetic acid) until background clears (2–4 h).
  • Imaging & Analysis: Scan gels with densitometry (Coomassie) or fluorescence imaging systems (SYPRO Ruby). Compare band intensity against pre-stained markers and internal standards (e.g., norleucine) for semi-quantitative assessment.
• Visualization Methods: Coomassie Brilliant Blue: Stains proteins/amino acids via non-covalent binding, with detection limits ~1 μg. Silver Staining: Offers higher sensitivity (ng-level detection) but requires stringent protocols. Fluorescent Dyes (e.g., SYPRO Ruby): Enable quantitative analysis via imaging systems.
• Key Advantages: Cost-effective for bulk screening of amino acid profiles in protein hydrolysates. Semi-quantitative assessment of relative abundance in complex mixtures.
• Technical Constraints: Limited resolution for isomers (e.g., leucine vs. isoleucine). Challenges in absolute quantification due to dye-binding variability. Time-consuming post-electrophoretic processing (staining/destaining).
• Applications:
  • Protein separation: In this study, two protease bands with chymosin activity, 44 kDa and 108 kDa, were screened from Rhodophyta by SDS-PAGE combined with zymogram analysis. The zymogram method directly locates the active region in the gel to guide the digestion of the target protein in the gel; Subsequent LC-MS/MS analysis showed that its peptide was more than 80% homologous to the metal/serine protease of bacteria (such as Gallaecimonas and Alteromonas), suggesting that horizontal gene transfer may mediate the sharing of protease genes between algae and bacteria (Arbita AA et al., 2022).

Enzymatic Approaches

Enzymatic strategies employ specialized biocatalysts to facilitate amino acid-specific reactions, enabling quantitative assessment through product detection. Two principal methodologies are outlined below, alongside emerging innovations and comparative insights:

(1) Enzyme-Linked Immunosorbent Assay (ELISA)

• Operational Principle: Target amino acids bind to immobilized antibodies, followed by enzymatic signal amplification (e.g., horseradish peroxidase (HRP) or alkaline phosphatase (AP)) to generate measurable colorimetric/fluorometric signals.
• Operational Steps:
  • Antibody Coating: Immobilize monoclonal antibodies specific to the target amino acid (e.g., D-serine) on a 96-well microplate via passive adsorption (4°C overnight in carbonate buffer, pH 9.6).
  • Blocking: Incubate with blocking agents (e.g., 5% BSA or casein) for 1–2 hours to minimize nonspecific binding.
  • Sample Incubation: Add serum/plasma samples (pre-diluted in assay buffer) and calibrators to wells, incubating at 37°C for 1 hour to enable antigen-antibody binding.
  • Washing: Remove unbound analytes using PBS-Tween (0.05% Tween-20) in 3–5 wash cycles.
  • Enzyme-Linked Detection: Add HRP/AP-conjugated secondary antibodies (e.g., anti-D-amino acid IgG-HRP) for 1-hour incubation, followed by another wash cycle.
  • Signal Amplification: Introduce substrate (e.g., TMB for HRP, yielding blue color; or pNPP for AP, yielding yellow product) and incubate 10–30 minutes.
  • Reaction Termination & Measurement: Stop enzymatic activity with 1 M H₂SO₄ (for TMB, turning solution yellow) and measure absorbance at 450 nm (TMB) or 405 nm (pNPP) using a microplate reader.
  • Quantification: Generate a 4-parameter logistic standard curve from calibrators to calculate target amino acid concentrations in samples.
• Key Advantages:
  • Exceptional sensitivity: Detection limits as low as 1 pg/mL (picomolar range).
  • High specificity: Minimal cross-reactivity due to monoclonal antibody precision.
• Technical Constraints:
  • Antibody dependency: Requires costly, custom-developed antibodies for non-standard amino acids (e.g., D-amino acids).
  • Multiplexing limitations: Traditional ELISA formats typically analyze one analyte per well.
• Applications:
  • Function verification of antibody: The structure-function relationship of 80.2 Fab antibody was verified by ELISA technology: the single heavy chain (HC) or light chain (LC) has no antigen binding activity and stereoselectivity, which indicates that the synergy between them is necessary for function. Furthermore, competitive ELISA was used to quantify the affinity difference of antibodies to amino acid enantiomers. It was found that low concentration of competitors could inhibit the binding of high affinity ligands (such as L- type amino acids) (IC₅₀ decreased by 4.6 times), while higher concentration was needed for D- type, revealing the stereochemical specificity of antibody binding sites (Eleniste PP et al., 2013).

Results of competitive ELISAs (Eleniste PP et al., 2013).

(2) Enzymatic Kinetic Assays

• Operational Principle: Real-time monitoring of enzyme-catalyzed reaction kinetics (e.g., glutamate dehydrogenase (GDH)-mediated NADH oxidation for α-ketoglutarate/ammonia detection).
  • Example: Coupling L-amino acid oxidase (LAAO) with peroxidase allows colorimetric detection of H₂O₂ generated during amino acid oxidation.
• Operational Steps:
  • Sample Preparation: Deproteinize serum/plasma using ultrafiltration (10 kDa cutoff) to remove endogenous enzymes. Dilute samples in reaction buffer (e.g., Tris-HCl pH 8.0 with 0.1 mM NADH and 1 mM ADP for GDH assay).
  • Reaction Initiation: In a 96-well microplate, mix 50 μL sample with 25 μL enzyme cocktail (e.g., 5 U/mL GDH + 0.2 U/mL diaphorase for NADH recycling). For L-amino acid detection, add 25 μL LAAO (1 U/mL) and peroxidase (0.5 U/mL) with chromogen (e.g., o-dianisidine, 0.1 mg/mL).
  • Kinetic Monitoring: Immediately load the plate into a pre-warmed (37°C) microplate reader. Record absorbance changes at 340 nm (NADH depletion) or 450 nm (H₂O₂-dianisidine product) every 30 seconds for 15–30 minutes.
  • Signal Calibration: Generate a standard curve using known concentrations of target analytes (e.g., 0–200 μM glutamate for GDH assay). Calculate reaction rates (ΔA/min) from the linear phase of kinetic curves.
  • Specificity Control: Include inhibitors (e.g., 10 mM hydroxylamine for GDH suppression) in parallel wells to confirm enzyme-specific signals.
  • Data Normalization: Correct for background noise using blank wells (enzyme-free reaction mix) and express results as μmol analyte/min/mg protein.
• Key Advantages:
  • High-throughput compatibility: Automated microplate readers enable parallel analysis of 96–384 samples.
  • Cost efficiency: Minimal reagent consumption compared to chromatographic methods.
• Technical Constraints:
  • Sensitivity thresholds: Typically limited to micromolar concentrations without signal amplification.
  • Enzyme specificity: Requires highly purified enzymes to avoid off-target catalysis (e.g., proline dehydrogenase cross-reacting with hydroxyproline).

MS Techniques

MS represents a cornerstone methodology in contemporary amino acid analysis, distinguished by its exceptional sensitivity, superior resolution, and high-throughput capabilities. Below, we delineate three principal MS-based approaches alongside emerging innovations and comparative insights:

(1) Liquid Chromatography-Mass Spectrometry (LC-MS)

• Operational Principle: Chromatographic Separation: Reversed-phase HPLC (C18 columns) or hydrophilic interaction chromatography (HILIC) resolves amino acids based on hydrophobicity/polarity. Mass Detection: Electrospray ionization (ESI) or atmospheric pressure chemical ionization (APCI) converts analytes into gas-phase ions for mass-to-charge (m/z) analysis.
• Operational Steps:
  • Sample Pretreatment: Centrifuge biological samples (e.g., serum) at 10,000 × g (10 min), filter (0.22 μm), then purify via solid-phase extraction (SPE, e.g., Oasis HLB cartridges) to remove lipids/salts.
  • Chromatographic Setup: For C18-RP: Equilibrate column with 95% water/5% acetonitrile (0.1% formic acid). For HILIC: Use 90% acetonitrile/10% ammonium formate (10 mM, pH 3.0) as starting phase. Apply gradient elution (e.g., 5% → 95% acetonitrile over 25 min for C18; 90% → 50% acetonitrile for HILIC).
  • Ionization Optimization: ESI settings: Capillary voltage 3.5 kV, source temperature 300°C, desolvation gas (N₂) flow 800 L/h. APCI parameters (for non-polar AA): Corona current 4 μA, vaporizer temperature 400°C.
  • Mass Spectrometry: Operate in MRM mode (triple quadrupole) for targeted quantification (e.g., m/z 147.1→84.1 for alanine). For untargeted profiling (Q-TOF): Use data-dependent acquisition (DDA) or SWATH® (DIA) with mass accuracy<5 ppm.
  • Data Processing: Align peaks using retention time (±0.2 min) and fragment ion ratios. Quantify via internal standards (e.g., isotopically labeled ¹³C-lysine) and software (Skyline, XCMS).
• Key Advantages: Ultra-high sensitivity: Detection limits down to femtomolar levels (e.g., 10–100 fg/μL for tryptophan). Matrix tolerance: Effective in complex biological fluids (serum, cerebrospinal fluid) and food extracts.
• Technical Constraints:Cost: High-end systems (e.g., Q-Exactive HF-X) exceed $500,000. Method development: Requires optimization of mobile phase gradients and ionization parameters.
• Applications:
  • Detection of tumor metabolism: LC-MS/MS was used to accurately quantify the amino acid levels in serum and tumor tissues, revealing that serum alanine, α -aminobutyric acid (AABA), Lys and cysteine in patients with high-grade glioma were significantly increased (↑32%~58% compared with the healthy group), while aspartic acid, histidine and taurine were significantly decreased (↓24%~41%) in serum and tumor. LC-MS's high sensitivity (detection limit reaches nM level) and multi-target analysis ability systematically analyze the characteristics of amino acid metabolic imbalance in glioma for the first time, lock alanine as a potential diagnostic marker, and find that the tumor volume is positively correlated with the serum concentration of specific amino acids (such as taurine) (r=0.67), which provides key data support for understanding the metabolic reprogramming of glioma and developing non-invasive screening tools (Toklu S et al., 2023).
  • Chiral analysis: In this study, a two-dimensional chiral LC-MS/MS method was developed. By combining reversed-phase column (one-dimensional) with chiral column (two-dimensional) and triple quadrupole mass spectrometry, the highly selective separation and accurate quantification of D/L- tryptophan were realized (the detection limit reached pmol level). This technique breaks through the limitation of traditional chromatography and proves for the first time that only L-Trp exists in the urine of healthy people; The urine of wild-type mice contains 6.18% D-Trp, while the proportion of D-Trp of DAO-deficient mice (B6DAO mice) rises to 27.43%. It is clear that D- amino acid oxidase (DAO) is the key enzyme to regulate D-Trp metabolism in mammals (Ishii C et al., 2022).

(2) Gas Chromatography-Mass Spectrometry (GC-MS)

• Operational Principle:
  • Derivatization: Amino acids are converted to volatile derivatives (e.g., N-trifluoroacetyl isopropyl esters) via silylation or acylation.
  • Sepection/Detection: Capillary GC columns (DB-5MS) separate derivatives, followed by electron ionization (EI) and quadrupole mass analysis.
• Operational Steps:
  • Sample Derivatization:
    Acylation: React amino acids with trifluoroacetic anhydride (TFA, 100 μL) in isopropanol (50°C, 30 min) to form N-TFA isopropyl esters.
    Silylation Alternative: For hydroxyl-containing amino acids (e.g., serine), use BSTFA + 1% TMCS (100 μL, 70°C, 1 h) for trimethylsilylation.
    Purification: Extract derivatives with hexane, evaporate under N₂, and reconstitute in ethyl acetate for GC injection.
  • GC Conditions:
    Column: DB-5MS (30 m × 0.25 mm, 0.25 μm film).
    Temperature Program: 80°C (hold 2 min) → 10°C/min → 280°C (hold 5 min) → 5°C/min → 300°C (hold 3 min) to resolve isomers.
    Carrier Gas: Helium, constant flow (1.2 mL/min).
  • EI-MS Detection:
    Ionization: Electron energy 70 eV, ion source 230°C.
    Scan Mode: Full scan (m/z 50–500) for untargeted analysis or SIM for targeted quantitation (e.g., m/z 158 for leucine/isoleucine).
  • Data Interpretation:
    Match EI fragmentation patterns (e.g., base peak m/z 158 for leucine vs. m/z 144 for isoleucine) against NIST library (similarity >85%).
    Use deuterated internal standards (e.g., D₃-leucine) to correct for derivatization efficiency.
• Key Advantages:
  • Structural specificity: EI generates reproducible fragment patterns for library matching (NIST database).
  • High resolution: Distinguishes isomers (e.g., leucine vs. isoleucine) with baseline separation.
• Technical Constraints:
  • Thermal limitations: Degrades heat-sensitive compounds (e.g., asparagine) above 300°C.
  • Derivatization time: Multi-step protocols require 2–4 hours per sample batch.
• Applications:
  • Plant metabolism analysis: In this study, a high-sensitivity (detection limit of 0.1% enrichment) 13C isotope position analysis method was established by combining GC-MS with TMS derivatization technology, and the detection reliability of key metabolites (glycine, malic acid, etc.) at specific atomic sites (such as glycine C1/C2 and malic acid C1) was successfully verified. Using the standard with known 13C distribution, it is confirmed that the C1 position analysis error of glutamic acid _3TMS and malic acid _3TMS is less than 3%, and the multi-segment calculation error is overcome.
  • Flavor chemistry: The mechanism of flavor formation of Guizhou fermented pork tenderloin ham was analyzed by GC-MS. It was found that volatile esters (such as ethyl octanoate 12.3 μg/g and ethyl hexanoate) accumulated continuously with fermentation time (7-42 days), contributing to fruity, sweet and grassy flavor, and their synthesis was highly correlated with free amino acid metabolism (deamination of Asp/Glu to α-keto acid) (the peak value of total amino acids was 1245 mg) (Dellero Y wt al., 2023).

(3) Tandem Mass Spectrometry (MS/MS)

• Operational Principle:
  • Fragmentation Strategies: Collision-induced dissociation (CID) or higher-energy collisional dissociation (HCD) generates diagnostic fragment ions.
  • Quantitation: Multiple reaction monitoring (MRM) enhances specificity for targeted assays (e.g., phenylalanine in newborn screening).
• Operational Steps:
  • Sample Preparation: Deproteinize plasma/serum with methanol (3:1 v/v, −20°C, 20 min), centrifuge (14,000 × g, 10 min), and filter (0.22 μm) to remove particulates.
  • LC-MS/MS Setup: Chromatography: Load sample onto a C18 column (2.1 × 50 mm, 1.7 μm) with gradient elution (5% → 95% acetonitrile/0.1% formic acid over 8 min). Ionization: Set ESI source parameters (spray voltage 3.5 kV, capillary temperature 320°C, sheath gas 40 arb).
  • MRM Method Development: Define precursor-product ion pairs (e.g., phenylalanine: m/z 166.1 → 103.1) based on CID/HCID fragmentation patterns. Optimize collision energy (CE) for each transition (e.g., CE = 15 eV for phenylalanine) to maximize ion intensity.
  • Data Acquisition: Operate triple quadrupole in MRM mode with dwell times ≥10 ms per transition to ensure ≥12 data points per peak. For isomer differentiation (e.g., isoleucine vs. allo-isoleucine), use pseudo-MRM with unique fragment ions (m/z 86.1 vs. 84.1).
  • Spectral Analysis: Process raw data with Skyline: Align retention times (±0.2 min), integrate peaks, and normalize against isotopically labeled internal standards (e.g¹³C₆-phenylalanine). Confirm identities via spectral library matching (mzCloud or NIST) for untargeted peaks.
  • Quality Control: Run calibration standards (0.1–200 μM) and QC samples (low/medium/high) every 20 injections to monitor system drift.
• Key Advantages:
  • Unambiguous identification: MS/MS spectra differentiate co-eluting isomers (e.g., allo-isoleucine).
  • High-throughput: Automated data acquisition supports 1,000+ samples/day in clinical labs.
• Technical Constraints:
  • Data complexity: Requires advanced software (e.g., Skyline, Xcalibur) for spectral interpretation.
  • Cost: Triple quadrupole systems range from from 300,000 to 1M.
• Applications:
  • Metabolic imbalance: LC-MS/MS technology was used to compare and analyze the differences of plasma amino acid spectrum between 24 HIV-positive patients and 24 healthy individuals. The results showed that the levels of 15 amino acids and their derivatives such as alanine, valine and aspartic acid in HIV group decreased significantly, while the levels of 4 substances such as 3- methyl -L- histidine and asparagine increased. These differences may reflect the metabolic disorder and cell damage mechanism caused by HIV infection, especially the abnormal changes of immune-related amino acids such as methionine and glutamine. For the first time, the study systematically revealed the characteristic amino acid metabolic imbalance pattern of asymptomatic HIV-infected people, which provided a basis for developing biomarkers for auxiliary diagnosis (Binici I et al., 2022).
  • Neuropathy: Based on HPLC-MS/MS, the serum D- amino acid spectrum of 37 AD patients and 34 healthy controls was analyzed. It was found that D- proline, D- aspartic acid and their ratio to total amino acids in AD group decreased significantly, and D- phenylalanine increased, and the age correlation of D- proline and D- phenylalanine in healthy people disappeared in AD patients. Combined with D- proline, D- phenylalanine, D- aspartic acid and age, the AUC of distinguishing AD reached 0.87 (specificity 97.0%, sensitivity 83.8%), and the level of D- aspartic acid gradually decreased with the decline of cognitive function (the score of clinical dementia scale deteriorated). This study reveals that the imbalance pattern of peripheral D- amino acids (especially proline, phenylalanine and aspartic acid) can be used as a potential biomarker of AD, and its dynamic changes are related to disease progression (Liu M et al., 2023).

If you want to know more about sample preparation for amino acid analysis, please click "Sample preparation and pretreatment for amino acid analysis".

Advantages of MS in Amino Acid Analysis

MS offers distinct advantages for amino acid characterization, underpinned by the following key attributes:

• Exceptional Sensitivity: MS achieves ultra-low detection limits, enabling precise quantification of amino acids at trace concentrations (femtomolar to attomolar ranges), critical for applications such as biomarker discovery and metabolomic profiling.
• Superior Resolving Power: Advanced MS platforms (e.g., high-resolution Orbitrap systems) differentiate structurally similar isomers (e.g., leucine/isoleucine) and resolve complex mixtures, ensuring accurate identification in biological matrices.
• High-Throughput Capacity: Modern MS configurations support parallel analysis of multiple amino acid species across large sample cohorts, enhancing efficiency in clinical studies and industrial quality control.
• Multifunctional Profiling Capabilities: Beyond quantification, MS enables comprehensive characterization, including post-translational modification mapping (e.g., phosphorylation, glycosylation) and de novo sequence determination, essential for proteomic and structural biology research.

If you want to know more about amino acid analysis, please refer to "Amino Acid Analysis: a Comprehensive Overview".

If you want to know more about the application of amino acid analysis, please refer to "Application of Amino Acid Analysis in Protein: a Comprehensive Overview".

Technical comparison

References

1. Ngamsuk S, Huang TC, Hsu JL. "ACE Inhibitory Activity and Molecular Docking of Gac Seed Protein Hydrolysate Purified by HILIC and RP-HPLC." Molecules. 2020 Oct 12;25(20):4635. doi: 10.3390/molecules25204635
2. Suzuki M, Shimizu-Hirota R, Mita M, Hamase K, Sasabe J. "Chiral resolution of plasma amino acids reveals enantiomer-selective associations with organ functions." Amino Acids. 2022 Mar;54(3):421-432. doi: 10.1007/s00726-022-03140-w
3. Tian Z, Zhu Q, Chen Y, Zhou Y, Hu K, Li H, Lu K, Zhou J, Liu Y, Chen X. "Studies on Flavor Compounds and Free Amino Acid Dynamic Characteristics of Fermented Pork Loin Ham with a Complex Starter." Foods. 2022 May 21;11(10):1501. doi: 10.3390/foods11101501
4. Haas D, Hauke J, Schwarz KV, Consalvi L, Trefz FK, Blau N, Hoffmann GF, Burgard P, Garbade SF, Okun JG. "Differences of Phenylalanine Concentrations in Dried Blood Spots and in Plasma: Erythrocytes as a Neglected Component for This Observation." Metabolites. 2021 Oct 3;11(10):680. doi: 10.3390/metabo11100680
5. Felisiak K, Szymczak M. "Use of Rapid Capillary Zone Electrophoresis to Determine Amino Acids Indicators of Herring Ripening during Salting." Foods. 2021 Oct 20;10(11):2518. doi: 10.3390/foods10112518
6. Tůma P, Hložek T, Kamišová J, Gojda J. "Monitoring of circulating amino acids in patients with pancreatic cancer and cancer cachexia using capillary electrophoresis and contactless conductivity detection." Electrophoresis. 2021 Oct;42(19):1885-1891. doi: 10.1002/elps.202100174
7. Arbita AA, Paul NA, Cox J, Zhao J. "Amino acid sequence of two new milk-clotting proteases from the macroalga Gracilaria edulis." Int J Biol Macromol. 2022 Jun 30;211:499-505. doi: 10.1016/j.ijbiomac.2022.05.038
8. Eleniste PP, Hofstetter H, Hofstetter O. "Expression and characterization of an enantioselective antigen-binding fragment directed against α-amino acids." Protein Expr Purif. 2013 Sep;91(1):20-9. doi: 10.1016/j.pep.2013.06.010
9. Toklu S, Kemerdere R, Kacira T, Gurses MS, Benli Aksungar F, Tanriverdi T. "Tissue and plasma free amino acid detection by LC-MS/MS method in high grade glioma patients." J Neurooncol. 2023 Jun;163(2):293-300. doi: 10.1007/s11060-023-04329-z
10. Ishii C, Takizawa N, Akita T, Mita M, Ide T, Konno R, Hamase K. "Off-line two-dimensional LC-MS/MS determination of tryptophan enantiomers in mammalian urine and alteration of their amounts in d-amino acid oxidase deficient mice." J Pharm Biomed Anal. 2022 Sep 20;219:114919. doi: 10.1016/j.jpba.2022.114919
11. Dellero Y, Filangi O, Bouchereau A. "Evaluation of GC/MS-Based 13C-Positional Approaches for TMS Derivatives of Organic and Amino Acids and Application to Plant 13C-Labeled Experiments." Metabolites. 2023 Mar 23;13(4):466. doi: 10.3390/metabo13040466
12. Binici I, Alp HH, Karsen H, Koyuncu I, Gonel A, Çelik H, Karahocagil MK. "Plasma Free Amino Acid Profile in HIV-Positive Cases." Curr HIV Res. 2022;20(3):228-235. doi: 10.2174/1570162X20666220428103250
13. Liu M, Li M, He J, He Y, Yang J, Sun Z. "Chiral Amino Acid Profiling in Serum Reveals Potential Biomarkers for Alzheimer's Disease." J Alzheimers Dis. 2023;94(1):291-301. doi: 10.3233/JAD-230142