The Warburg Effect is the result of faster ATP production by glycolysis than respiration

Abstract

Many prokaryotic and eukaryotic cells metabolize glucose to organism-specific by-products instead of fully oxidizing it to carbon dioxide and water-a phenomenon referred to as the Warburg Effect. The benefit to a cell is not fully understood, given that partial metabolism of glucose yields an order of magnitude less adenosine triphosphate (ATP) per molecule of glucose than complete oxidation. Here, we test a previously formulated hypothesis that the benefit of the Warburg Effect is to increase ATP production rate by switching from high-yielding respiration to faster glycolysis when excess glucose is available and respiration rate becomes limited by proteome occupancy. We show that glycolysis produces ATP faster per gram of pathway protein than respiration in Escherichia coli, Saccharomyces cerevisiae, and mammalian cells. We then develop a simple mathematical model of energy metabolism that uses five experimentally estimated parameters and show that this model can accurately predict absolute rates of glycolysis and respiration in all three organisms under diverse conditions, providing strong support for the validity of the ATP production rate maximization hypothesis. In addition, our measurements show that mammalian respiration produces ATP up to 10-fold slower than respiration in E. coli or S. cerevisiae, suggesting that the ATP production rate per gram of pathway protein is a highly evolvable trait that is heavily optimized in microbes. We also find that E. coli respiration is faster than fermentation, explaining the observation that E. coli, unlike S. cerevisiae or mammalian cells, never switch to pure fermentation in the presence of oxygen.

Keywords: Warburg Effect; cancer metabolism; energy metabolism; modeling; systems biology.

Fig. 1.

The Warburg Effect emerges from a simple model of energy metabolism that maximizes ATP production rate. (A) Illustration of the model. (B) Overview of the mathematical model. (C) Preferred ATP-producing pathways if parameters of yield of ATP per molecule of glucose (γ) and the specific activity of ATP production ($\gamma \bullet V$) are both higher for respiration, (D) both higher for glycolysis, or (E) if the yield is higher for respiration (${\gamma }_{\mathit{resp}}>{\gamma }_{\mathit{glyc}}$), but the specific activity of ATP production is higher for glycolysis (${\gamma }_{\mathit{resp}}\bullet V_{\mathit{max}}^{\mathit{resp}}<{\gamma }_{\mathit{glyc}}\bullet V_{\mathit{max}}^{\mathit{glyc}}$). In each case, the total ATP production rate is represented by the dashed line. (F) Increasing the proteome space dedicated to ATP-producing enzymes increases ATP production rate across glucose uptake rates and (G) delays the switch from respiration to glycolysis. The box in Fig. 1G is shown in (H) to highlight the delayed onset of glycolysis.

Fig. 2.

Specific activities of ATP production of relevant pathways for E. coli, S. cerevisiae, and mammalian cells. (A) Specific activity of ATP production (μmol mg pathway⁻¹ min⁻¹) for fermentation (red), the Pta-AckA pathway (green), and respiration (blue) for E. coli. (B and C) Specific activity of ATP production (μmol mg pathway⁻¹ min⁻¹) for fermentation (red) and respiration (blue) for S. cerevisiae and mammalian cells, respectively. Specific activity of ATP production rate is given by $V_{\mathit{max}}\bullet \gamma$. Error bars are the 95 percent CI calculated from 10,000 bootstrap iterations.

Fig. 3.

The model with no adjustable parameters that maximizes ATP production rate accurately predicts glycolysis and respiration rates and onset of the Warburg Effect in E. coli, S. cerevisiae, and mammalian cells. (A–C) Comparison of model predictions (lines) and experimental observations (points) for glycolysis (red) and respiration (blue) rates of E. coli, S. cerevisiae, and mammalian cells, respectively. Note that each unique point shape represents data from a distinct publication. The glucose uptake rate for each point is calculated from the sum of oxygen consumption and glycolytic by-product production.

Fig. 4.

The Warburg Effect is driven by glucose availability and not growth rate. (A) Relationship between the growth rate (h⁻¹) and the observed acetate production rate (μmol per mg cellular protein per min) for carbon- and nitrogen-limited cultures (gray and yellow, respectively) in E. coli or (B) the observed ethanol production rate (μmol per mg cellular protein per min) for carbon (glucose, maltose, galactose)-, nitrogen-, phosphorus-limited cultures (gray, burgundy, navy, yellow, green, respectively) in S. cerevisiae. (C) Relationship between the carbon uptake rate (μmol per mg cellular protein per min) and the observed acetate production rate (μmol per mg cellular protein per min) for carbon- and nitrogen-limited cultures (gray and yellow, respectively) in E. coli or (D) the observed ethanol production rate (μmol per mg cellular protein per min) for carbon (glucose, maltose, galactose)-, nitrogen-, phosphorus-limited cultures (gray, burgundy, navy, yellow, green, respectively) in S. cerevisiae. The carbon uptake rate for each point is calculated from the sum of oxygen consumption and glycolytic by-product production.