Optimization of 13C isotopic tracers for metabolic flux analysis in mammalian cells.

Mammalian cells consume and metabolize various substrates from their surroundings for energy generation and biomass synthesis. Glucose and glutamine, in particular, are the primary carbon sources for proliferating cancer cells. While this combination of substrates generates static labeling patterns for use in (13)C metabolic flux analysis (MFA), the inability of single tracers to effectively label all pathways poses an obstacle for comprehensive flux determination within a given experiment. To address this issue we applied a genetic algorithm to optimize mixtures of (13)C-labeled glucose and glutamine for use in MFA. We identified tracer combinations that minimized confidence intervals in an experimentally determined flux network describing central carbon metabolism in tumor cells. Additional simulations were used to determine the robustness of the [1,2-(13)C(2)]glucose/[U-(13)C(5)]glutamine tracer combination with respect to perturbations in the network. Finally, we experimentally validated the improved performance of this tracer set relative to glucose tracers alone in a cancer cell line. This versatile method allows researchers to determine the optimal tracer combination to use for a specific metabolic network, and our findings applied to cancer cells significantly enhance the ability of MFA experiments to precisely quantify fluxes in higher organisms.

An elementary metabolite unit (EMU) based method of isotopically nonstationary flux analysis.

Nonstationary metabolic flux analysis (NMFA) is at present a very computationally intensive exercise, especially for large reaction networks. We applied elementary metabolite unit (EMU) theory to NMFA, dramatically reducing computational difficulty. We also introduced block decoupling, a new method that systematically and comprehensively divides EMU systems of equations into smaller subproblems to further reduce computational difficulty. These improvements led to a 5000-fold reduction in simulation times, enabling an entirely new and more complicated set of problems to be analyzed with NMFA. We simulated a series of nonstationary and stationary GC/MS measurements for a large E. coli network that was then used to estimate parameters and their associated confidence intervals. We found that fluxes could be successfully estimated using only nonstationary labeling data and external flux measurements. Addition of near-stationary and stationary time points increased the precision of most parameters. Contrary to prior reports, the precision of nonstationary estimates proved to be comparable to the precision of estimates based solely on stationary data. Finally, we applied EMU-based NMFA to experimental nonstationary measurements taken from brown adipocytes and successfully estimated fluxes and some metabolite concentrations. By using NFMA instead of traditional MFA, the experiment required only 6 h instead of 50 (the time necessary for most metabolite labeling to reach 99% of isotopic steady state).

13 C Flux Analysis Reveals that Rebalancing Medium Amino Acid Composition can Reduce Ammonia Production while Preserving Central Carbon Metabolism of CHO Cell Cultures.

13 C metabolic flux analysis (MFA) provides a rigorous approach to quantify intracellular metabolism of industrial cell lines. In this study, 13 C MFA was used to characterize the metabolic response of Chinese hamster ovary (CHO) cells to a novel medium variant designed to reduce ammonia production. Ammonia inhibits growth and viability of CHO cell cultures, alters glycosylation of recombinant proteins, and enhances product degradation. Ammonia production was reduced by manipulating the amino acid composition of the culture medium; specifically, glutamine, glutamate, asparagine, aspartate, and serine levels were adjusted. Parallel 13 C flux analysis experiments determined that, while ammonia production decreased by roughly 40%, CHO cell metabolic phenotype, growth, viability, and monoclonal antibody (mAb) titer were not significantly altered by the changes in media composition. This study illustrates how 13 C flux analysis can be applied to assess the metabolic effects of media manipulations on mammalian cell cultures. The analysis revealed that adjusting the amino acid composition of CHO cell culture media can effectively reduce ammonia production while preserving fluxes throughout central carbon metabolism.

Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells.

(13)C metabolic flux analysis (MFA) is the most comprehensive means of characterizing cellular metabolic states. Uniquely labeled isotopic tracers enable more focused analyses to probe specific reactions within the network. As a result, the choice of tracer largely determines the precision with which one can estimate metabolic fluxes, especially in complex mammalian systems that require multiple substrates. Here we have experimentally determined metabolic fluxes in a tumor cell line, successfully recapitulating the hallmarks of cancer cell metabolism. Using these data, we computationally evaluated specifically labeled (13)C glucose and glutamine tracers for their ability to precisely and accurately estimate fluxes in central carbon metabolism. These methods enabled us to identify the optimal tracer for analyzing individual fluxes, specific pathways, and central carbon metabolism as a whole. [1,2-(13)C(2)]glucose provided the most precise estimates for glycolysis, the pentose phosphate pathway, and the overall network. Tracers such as [2-(13)C]glucose and [3-(13)C]glucose also outperformed the more commonly used [1-(13)C]glucose. [U-(13)C(5)]glutamine emerged as the preferred isotopic tracer for the analysis of the tricarboxylic acid (TCA) cycle. These results provide valuable, quantitative information on the performance of (13)C-labeled substrates and can aid in the design of more informative MFA experiments in mammalian cell culture.

Systematic identification of conserved metabolites in GC/MS data for metabolomics and biomarker discovery.

Analysis of metabolomic profiling data from gas chromatography-mass spectrometry (GC/MS) measurements usually relies upon reference libraries of metabolite mass spectra to structurally identify and track metabolites. In general, techniques to enumerate and track unidentified metabolites are nonsystematic and require manual curation. We present a method and software implementation, freely available at http://spectconnect.mit.edu, that can systematically detect components that are conserved across samples without the need for a reference library or manual curation. We validate this approach by correctly identifying the components in a known mixture and the discriminating components in a spiked mixture. Finally, we demonstrate an application of this approach with a brief analysis of the Escherichia coli metabolome. By systematically cataloguing conserved metabolite peaks prior to data analysis methods, our approach broadens the scope of metabolomics and facilitates biomarker discovery.

Increasing the clearance of protein-bound solutes by addition of a sorbent to the dialysate.

The capacity of sorbent systems to increase solute clearances above the levels that are provided by hemodialysis has not been well defined. This study assessed the extent to which solute clearances can be increased by addition of a sorbent to the dialysate. Attention was focused on the clearance of protein-bound solutes, which are cleared poorly by conventional hemodialysis. A reservoir that contained test solutes and artificial plasma was dialyzed first with the plasma flow set at 46 +/- 3 ml/min and the dialysate flow (Q(d)) set at 42 +/- 3 ml/min using a hollow fiber kidney with mass transfer area coefficients greater than Q(d) for each of the solutes. Under these conditions, the clearance of urea (Cl(urea)) was 34 +/- 1 ml/min, whereas the clearances of the protein-bound solutes indican (Cl(ind)), p-cresol sulfate (Cl(pcs)), and p-cresol (Cl(pc)) averaged only 5 +/- 1, 4 +/- 1, and 14 +/- 1 ml/min, respectively The effect of addition of activated charcoal to the dialysate then was compared with the effect of increasing Q(d) without addition of any sorbent. Addition of charcoal increased Cl(ind), Cl(pcs), and Cl(pc) to 12 +/- 1, 9 +/- 2, and 35 +/- 4 ml/min without changing Cl(urea). Increasing Q(d) without the addition of sorbent had a similar effect on the clearance of the protein-bound solutes. Mathematical modeling predicted these changes and showed that the maximal effect of addition of a sorbent to the dialysate is equivalent to that of an unlimited increase in Q(d). These results suggest that as an adjunct to conventional hemodialysis, addition of sorbents to the dialysate could increase the clearance of protein-bound solutes without greatly altering the clearance of unbound solutes.

The clearance of protein-bound solutes by hemofiltration and hemodiafiltration.

BACKGROUND: Hemofiltration in the form of continuous venovenous hemofiltration (CVVH) is increasingly used to treat acute renal failure. Compared to hemodialysis, hemofiltration provides high clearances for large solutes but its effect on protein-bound solutes has been largely ignored. METHODS: Standard clinical systems were used to remove test solutes from a reservoir containing artificial plasma. Clearances of the protein-bound solutes phenol red (C(PR)) and indican (C(IN)) were compared to clearances of urea (C(UREA)) during hemofiltration and hemodiafiltration. A mathematical model was developed to predict clearances from values for plasma flow Q(p), dialysate flow Q(d), ultrafiltration rate Q(f), filter size and the extent of solute binding to albumin. RESULTS: When hemofiltration was performed with Q(p) 150 mL/min and Q(f) 17 mL/min, clearance values were C(PR) 1.0 +/- 0.1 mL/min; C(IN) 3.7 +/- 0.5 mL/min; and C(UREA) 14 +/- 1 mL/min. The clearance of the protein-bound solutes was approximately equal to the solute-free fraction multiplied by the ultrafiltration rate corrected for the effect of predilution. Addition of Q(d) 42 mL/min to provide HDF while Q(p) remained 150 mL/min resulted in proportional increases in the clearance of protein-bound solutes and urea. In contrast, the clearance of protein-bound solutes relative to urea increased when hemodiafiltration was performed using a larger filter and increasing Q(d) to 300 mL/min while Q(p) was lowered to 50 mL/min. The pattern of observed results was accurately predicted by mathematical modeling. CONCLUSION: In vitro measurements and mathematical modeling indicate that CVVH provides very limited clearance of protein-bound solutes. Continuous venous hemodiafiltration (CVVHDF) increases the clearance of protein-bound solutes relative to urea only when dialysate flow rate and filter size are increased above values now commonly employed.