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Amino Acid Metabolic Flux Analysis (MFA) Service for Nitrogen & Carbon Kinetics

Quantify intracellular amino acid biosynthesis, transamination, and catabolic routing under defined experimental conditions. Creative Proteomics provides specialized Amino Acid Metabolic Flux Analysis (Amino Acid MFA) combining customized [U-13C5, 15N2]glutamine, [U-13C6]glucose, and [U-13C6]leucine tracer regimes, rapid metabolic quenching, high-resolution LC-MS and GC-MS profiling, and dual-isotope (13C/15N) stoichiometric network modeling to map transaminase networks, one-carbon transfer, and anaplerotic entry.

Quantitative estimation of intracellular pathway fluxes across 20 canonical amino acids

Dual 13C and 15N isotope tracing resolving carbon backbone vs. amino nitrogen exchange

High-resolution profiling of Branched-Chain Amino Acid (BCAA) transamination and oxidation

Stoichiometric quantification of Serine-Glycine-One-Carbon (SGOC) and urea cycle fluxes

Mathematical network modeling with parameter sensitivity and uncertainty evaluation

Amino Acid Metabolic Flux Analysis — Beyond Static Pool Concentrations

Amino acids serve as essential precursors for protein synthesis, nucleotide biogenesis, glutathione redox defense, and TCA cycle anaplerosis. While conventional metabolomics measures static amino acid pool concentrations (μmol/g or μM), pool sizes alone cannot determine whether accumulation or depletion is driven by altered de novo synthesis, protein turnover, extracellular uptake, or downstream transamination and oxidation.

As a specialized pathway Spoke within our central carbon metabolic flux analysis and broader metabolic flux analysis service, Amino Acid MFA tracks stable isotopes (13C and 15N) to resolve key amino acid reaction velocities:

(i) Glutamine/Glutamate Hub & Transamination Flux: The rate of glutamine deamidation via glutaminase (GLS) versus nitrogen transfer by transaminases (ALT/GPT, AST/GOT) and glutamate dehydrogenase (GDH), connected to our TCA cycle metabolic flux analysis.

(ii) Branched-Chain Amino Acid (BCAA) Kinetics: Reversible transamination of leucine, isoleucine, and valine via BCAT1/2 yielding branched-chain α-keto acids (BCKAs) versus irreversible oxidation via the BCKDH complex.

(iii) Serine-Glycine-One-Carbon (SGOC) Axis: De novo serine synthesis from glycolytic 3-PG (PHGDH, PSAT1, PSPH) and its cleavage by SHMT1/2 to glycine, fueling one-carbon folate pools, purine rings, and methylation.

(iv) Aspartate Shuttle & Urea Cycle Integration: Aspartate transamination and condensation with citrulline via argininosuccinate synthetase/lyase (ASS1/ASL), balancing NADPH generation, arginine synthesis, and nitrogen disposal.

(v) Glutathione Synthesis & Redox Balancing: Condensation fluxes of glutamate, cysteine, and glycine through GCLC and GSS, quantifying antioxidant pool replenishment under oxidative stress.

Looking for amino acid concentration measurements? If your research objective is quantifying absolute or relative pool sizes (μmol/g, μmol/L, or ng/mL) of free amino acids without stable isotope tracing, please explore our Amino Acids Analysis Service.

Analytical Considerations in Dual 13C/15N Amino Acid Fluxomics

Amino acid fluxomics requires robust analytical coverage across polar zwitterionic amino acids, labile α-keto acids, and dual-isotope envelopes:

  • Simultaneous Dual-Isotope (13C / 15N) Resolution: High-resolution mass spectrometry resolves fine isotopic structures (e.g. distinguishing 13C from 15N mass shifts), enabling concurrent tracking of carbon skeleton transitions and amino nitrogen transfer.
  • Keto Acid Stabilization & Derivatization: Labile α-keto acids (α-ketoglutarate, oxaloacetate, pyruvate, BCKAs) undergo fast oximation or silylation derivatization to prevent decarboxylation and enable precise GC-MS or LC-MS measurement.
  • Dual LC-MS & GC-MS Orthogonal Profiling: Underivatized HILIC and reversed-phase LC-MS profile intact polar amino acids, while GC-MS-based metabolic flux analysis using tert-butyldimethylsilyl (TBDMS) or chloroformate derivatization supplies fragment-specific carbon constraints.
  • Multi-Element Background Deconvolution: Algorithmic matrix deconvolution (IsoCor / AccuCor) mathematically corrects raw isotopologue spectra for natural 13C, 15N, 18O, and silyl tag backgrounds.

13C and 15N Tracer Selection Matrix for Transamination & Amino Acid Flux

The choice of isotope tracer dictates which amino acid synthetic, transamination, and catabolic fluxes can be mathematically resolved:

Tracer Substrate Target Amino Acid Pathway Node Diagnostic Labeling Information & Readout
[U-13C5, 15N2]Glutamine Glutamine carbon oxidation vs. amino/amide nitrogen transfer Tracks carbon backbone entry into the TCA cycle (M+4/M+5 α-KG, succinate, malate, citrate) alongside nitrogen transfer: amide-15N into nucleotide rings and asparagine; amine-15N (M+1) into transamination products (glutamate, alanine, aspartate).
[U-13C6]Glucose De novo Non-Essential Amino Acid (NEAA) synthesis Labels glycolytic and TCA precursors, yielding [U-13C3]serine (via 3-PG), [U-13C2]glycine (via SHMT), [U-13C3]alanine (via pyruvate), [U-13C4]aspartate (via oxaloacetate), and [U-13C5]glutamate (via α-KG).
[U-13C6]Leucine / [U-13C5]Valine BCAA transamination (BCAT) vs. terminal oxidation (BCKDH) Transamination yields [U-13C]keto acids (KIC, KIV), while downstream oxidative decarboxylation generates labeled acetyl-CoA and succinyl-CoA entering the TCA cycle. Distinguishes reversible exchange from committed oxidation.
[U-13C3, 15N]Serine Serine-Glycine-One-Carbon (SGOC) and folate transfer SHMT cleavage releases M+2 glycine and a one-carbon unit ([13C]methylene-THF) feeding the methionine cycle (M+1 methionine/SAM) and purine rings (M+1/M+2 adenine/guanine).
[15N]Ammonium Chloride / [15N]Amine Global nitrogen assimilation, GDH flux, and urea cycle disposal Directly quantifies GDH-mediated ammonia fixation versus transaminase distribution into glutamate, glutamine, and urea cycle intermediates (citrulline, arginine, urea).

Technical Capabilities for High-Resolution Amino Acid Flux Analysis

  • Dual Carbon-Nitrogen Balance: Integrated stoichiometric modeling accounting for coupled carbon backbone routing and nitrogen transaminase exchange networks.
  • Sub-Cellular Compartmental Distinction: Resolves cytosolic (BCAT1, GOT1, SHMT1) from mitochondrial (BCAT2, GOT2, SHMT2) isoforms through compartment-specific isotopologue signature deconvolution.
  • Isotopic Steady-State and Dynamic Kinetic Sampling: Supports steady-state fractional contribution studies as well as time-course dynamic and INST metabolic flux analysis to monitor acute enzyme inhibition or nutrient switches.
  • Complementary Positional Validation: High-field NMR-based metabolic flux analysis available for resolving position-specific carbon and nitrogen labeling in complex biofluids.

End-to-End Amino Acid MFA Workflow & Analytical Pipeline

1

Study Scoping & Tracer Configuration

We define the stoichiometric amino acid network (synthesis, transamination, oxidation, one-carbon transfer) and select optimal 13C/15N tracers matched to your biological questions.

2

Tracer Incubation & Rapid Quenching

Cultured cells or tissue systems are labeled with validated stable isotope substrates and rapidly harvested using pre-evaluated organic extraction protocols to arrest enzyme activity.

3

Mass Spectrometry Data Acquisition

Intact amino acids, α-keto acids, and central carbon intermediates are acquired on LC-MS and GC-MS platforms for mass isotopologue distributions (M+0 to M+n); extracellular exchange rates are quantified in parallel.

4

Natural Abundance Deconvolution & QC Review

Raw mass isotopologue profiles are algorithmically stripped of natural isotope background using IsoCor/AccuCor, verified with pooled quality control (QC) standards.

5

Mathematical Modeling & Uncertainty Estimation

Stoichiometric and isotopomer balance equations compute net fluxes, exchange rates, and fractional synthesis rates with parameter sensitivity and confidence interval evaluation.

6

Publication-Ready Flux Maps & Deliverables

Delivery of comprehensive quantitative datasets, model configuration files, and publication-oriented vector pathway maps supported by our fluxomics data analysis service.

Six-step workflow for amino acid metabolic flux analysis

Sample Preparation & Stabilization Guidelines for Amino Acid MFA

Sample amounts and extraction protocols are finalized during feasibility review based on amino acid pool turnover and matrix type:

Sample Type Typical Input Guidelines Harvesting & Quenching Principles Storage & Transport
Adherent Cultured Cells Typically 1–5 × 106 cells (60 mm dish), confirmed by pilot assessment Aspirate tracer medium rapidly, add pre-chilled organic extraction solvent, cell detachment on dry ice/ice. Minimize wash duration. Store at −80 °C; ship on dry ice
Suspension Cultured Cells Typically 2–10 × 106 cells, adjusted to cell density Short, pre-cooled centrifugation (4 °C), aspirate supernatant, extract cell pellet immediately in cold solvent. Store at −80 °C; ship on dry ice
Microbial / Fermentation Pellets Biomass volume determined by pilot extraction and target coverage Fast filtration or direct quenching into pre-chilled solvent to arrest fast-turnover pools. Retain spent broth for extracellular rates. Store at −80 °C; ship on dry ice
Animal & Tumor Tissues 20–50 mg wet weight, depending on metabolic activity Instant freeze-clamping or flash freezing in liquid nitrogen immediately upon collection; cryo-pulverize without intermediate thawing. Store at −80 °C; ship on dry ice
Conditioned Culture Medium ≥ 200 μL matched supernatant Sample matched culture supernatant across labeling time points; clarify by centrifugation (4 °C) to remove debris. Store at −80 °C; ship on dry ice

Deliverables & Quantitative Datasets from Amino Acid MFA

  • Deconvoluted Amino Acid MID Matrix: Natural-abundance-corrected fractional labeling (M+0 to M+n) across all canonical amino acids and key α-keto acids (.csv / Excel).
  • Extracellular Boundary Rates: Quantified amino acid uptake, consumption, and secretion rates providing stoichiometric boundaries for flux calculation.
  • Dual Carbon-Nitrogen Model Specifications: Reaction network definitions, carbon/nitrogen atom transition mappings, and project configuration files.
  • Calculated Reaction Rates & Split Ratios: Net (vnet) and exchange (vxch) fluxes with accompanying sensitivity analysis and confidence intervals.
  • Statistical Fit Diagnostics: Sum of squared residuals (SSR), Chi-square goodness-of-fit evaluation, and residual diagnostic plots.
  • Publication-Ready Pathway Maps: High-resolution vector graphics (PDF/SVG) illustrating amino acid metabolic flux partitioning.
Amino acid mass isotopologue distribution bar plot resolving transamination

Mass isotopologue distribution (MID) bar plot of glutamine, glutamate, aspartate, and alanine resolving transamination and deamidation flux.

Quantitative amino acid metabolic pathway flux map with BCAA and SGOC rates

Publication-oriented amino acid pathway flux map displaying BCAA transamination, serine-glycine-one-carbon flux, and urea cycle integration.

Research Applications of Amino Acid Pathway Flux Analysis & BCAA Tracing

  • Oncology & Glutamine Addiction: Quantify glutaminase dependence, anaplerotic feeding into the TCA cycle, and resistance mechanisms to GLS1 inhibitors.
  • BCAA Catabolism in Diabetes & Heart Failure: Map BCAT/BCKDH flux rewiring in insulin resistance, non-alcoholic fatty liver disease, and cardiac hypertrophy.
  • One-Carbon Metabolism & Epigenetics: Measure de novo serine synthesis, SHMT flux, and methyl-group donor rates (SAM/SAH) fueling DNA and histone methylation.
  • Immunometabolism: Track arginine, tryptophan, and glutamine partitioning during macrophage polarization and T-cell differentiation.
  • Bioprocess & Recombinant Protein Production: Optimize amino acid feeding strategies, eliminate toxic ammonia/urea accumulation, and maximize protein yields in CHO cell cultures.

How does Amino Acid MFA distinguish carbon skeleton flux from nitrogen transamination?

By utilizing dual-labeled tracers such as [U-13C5, 15N2]glutamine or [U-13C3, 15N]serine, mass spectrometry tracks the 13C mass shift (identifying carbon backbone cleavage and oxidation into the TCA cycle) independently from the 15N mass shift (identifying transaminase-mediated amino group transfer to keto acids). Mathematical modeling resolves both carbon and nitrogen exchange networks simultaneously.

How are BCAA transamination (BCAT) and oxidation (BCKDH) fluxes quantified?

Using [U-13C6]leucine or [U-13C5]valine, reversible transamination by BCAT transfers amino groups, generating labeled branched-chain α-keto acids (M+6 KIC or M+5 KIV). Irreversible decarboxylation by BCKDH commits the carbon backbone to terminal oxidation, releasing 13CO2 and forming labeled acetyl-CoA or succinyl-CoA. Comparing the isotopologue distributions of keto acids and downstream TCA intermediates resolves the BCAT exchange velocity versus net BCKDH oxidation rate.

Can Amino Acid MFA measure de novo serine synthesis vs. exogenous uptake?

Yes. By feeding [U-13C6]glucose, de novo synthesized serine from glycolytic 3-PG displays a characteristic M+3 mass shift, whereas unlabelled serine from culture media remains M+0. The ratio of M+3 to total intracellular serine directly yields the fractional synthetic rate (FSR) of the phosphoserine pathway (PHGDH/PSAT1/PSPH).

Why is rapid quenching critical for amino acid and keto acid profiling?

Intracellular amino acid and α-keto acid pools exhibit rapid turnover rates and are subject to continuous transaminase exchange post-harvest. Fast low-temperature quenching in organic extraction solvents halts transaminase and dehydrogenase activity within seconds, preserving accurate mass isotopologue distributions.

What statistical metrics validate the calculated amino acid fluxes?

Calculated fluxes are validated using global Chi-square goodness-of-fit testing against measurement variance. Furthermore, parameter sensitivity analysis and confidence intervals are computed for all estimated fluxes to verify that reported parameters are mathematically identifiable and robustly constrained by the experimental dataset.

For Research Use Only. Not for use in diagnostic procedures.
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