To test mechanisms that are responsible for altered regulation of steady-state levels of metabolites, in the cell, measurements of metabolic flux through pathways is required. By providing stable-isotope labeled metabolic substrates (such as isotopic labeled glucose, glutamine, or lactate) to living cells, isotopomer patterns of key metabolites can be precisely measured using mass spectrometry. These analyses can provide valuable information on both pathway activities and metabolite pool sizes. Since all metabolites are either reactants or products in metabolic pathways, changes in their levels due to either altered production or altered disposal are determined by the kinetic rates of key steps within those pathways. Nutrients or metabolic precursors labeled with stable isotopes can be used to feed cells in vitro or tissues in vivo in different mouse models, followed by measurement of the relative uptake and absorption of the isotopes and Metabolic flux analysis (MFA) to trace the usage and labeled products synthesized. This enables the measurement pre-cursor conversion to other biochemical compounds or end-products, or their utilization to synthesize larger biomolecules such as peptides and proteins. The amount of label transferred from a precursor to its products is measured by mass spectrometry.

(Note: Services available currently use cell lines only and are confined to the targeted analysis of pathways as indicated below)    

Targeted Flux

A. Glucose Metabolic Flux

Enrichment of [13C] glucose and other tracers in conjunction with glycolysis and pentose pathways will be performed. For comprehensive analysis of glucose turnover, [13C] glucose tracer is analyzed by LC/MS for mass isotopomer distribution.

B. Citric Acid Cycle (TCA cycle) Metabolic Flux

The TCA flux is the key process in many metabolic pathways. To provide information on TCA cycle, quantitative analysis of lactic acid, pyruvic acid, citrate, cis-aconitate, isocitrate, ketoglutarate, succinate, fumarate, malate and oxaloacetate is determined by LCMS. To test  possible mechanisms responsible for altered regulation, flux analysis is performed within the cycle via the isotopomer approach with 13C tracers.

C. Glutamine Flux

Glutamine is an alternative source of carbon for de novo fatty acid synthesis in some cancer cells. The pathway for fatty acid synthesis from glutamine may follow either of two distinct pathways after it enters the citric acid cycle. The glutaminolysis pathway follows the citric acid cycle, whereas the reductive carboxylation pathway travels in reverse of the citric acid cycle from α-ketoglutarate to citrate . To quantify fluxes in these pathways, cells are incubated with [U-13C]glutamine or [5-13C]glutamine [1-13C]glutamine and analyzed by the mass isotopomer distribution of key metabolites using models that fit the isotopomer distribution.

D. Lipid or Fatty acid Metabolism

Acetyl-CoA is an important anabolic precursor for lipid biosynthesis. In the conventional view of mammalian metabolism, acetyl-CoA is primarily derived by the oxidation of glucose-derived pyruvate in mitochondria. When cells are grown under conditions of hypoxia or with defective mitochondria, a major fraction of acetyl-CoA is produced by an alternate route, via reductive carboxylation of glutamine-derived α-ketoglutarate (catalyzed by reverse flux through isocitrate dehydrogenase, IDH). A quantitative flux model using [13C] glutamine or [13C] glucose can be used to show oxidative and reductive flux respectively in hypoxia and in cells with defective mitochondria.

Investigator vs Core Responsibilities

Core: Targeted metabolic flux services will include consultation for protocol design based on the specific questions and hypotheses of the investigators (including hypotheses derived from metabolomic analyses), preparation of cell extracts, appropriate MS analysis of samples (GC/QQQ, LC/QQQ and LC-QTOF) ,  primary data analysis and assistance with interpretation of data.

Investigator: is responsible for providing and preparing cell cultures, purchasing isotopic tracers and labeling cell cultures.   This must be done in consultation with the Core using protocols supplied by the Core after an initial meeting with Core directors to design the experiments.

Core Prices

Core Prices

Metabolomics Flux Primary (Tier 1) Data Analysis

Metabolomics flux primary (Tier 1) data analysis provided as a package with the MS analysis. 

The statistical analyses will be carried out by the Dr. Cristian Coarfa associated with Alkek Center for Molecular Discovery, at Baylor College of Medicine. He has been working with Metabolomics core over the past two years and has been developing algorithms for analyses of metabolomics datasets. Accordingly, total percentage incorporation of C13 into is calculated with respect to each metabolite for all experimental time points and biological replicates respectively and are normalized for natural abundance in each isotope.  Statistical significance is obtained using two sided t-test [1-5].

Metabolomics Flux Tier 2 Data Analysis:

Higher level data analysis, graphical representation and comparative analysis can be provided upon request as a separate negotiation with Dr. Coarfa. 


  1. Bhowmik, S.K., et al., Application of 13C isotope labeling using liquid chromatography mass spectrometry (LC-MS) to determining phosphate-containing metabolic incorporation. J Mass Spectrom, 2013. 48(12): p. 1270-5.
  2. Dasgupta, S., et al., Coactivator SRC-2-dependent metabolic reprogramming mediates prostate cancer survival and metastasis. J Clin Invest, 2015. 125(3): p. 1174-88.
  3. Kang, Y.K., et al., CAPER is vital for energy and redox homeostasis by integrating glucose-induced mitochondrial functions via ERR-alpha-Gabpa and stress-induced adaptive responses via NF-kappaB-cMYC. PLoS Genet, 2015. 11(4): p. e1005116.
  4. Terunuma, A., et al., MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis. J Clin Invest, 2014. 124(1): p. 398-412.
  5. Zaslavsky, A.B., et al., Platelet-Synthesized Testosterone in Men with Prostate Cancer Induces Androgen Receptor Signaling. Neoplasia, 2015. 17(6): p. 490-6.