Organization of enzyme concentration across the metabolic network in cancer cells

Abstract

Rapid advances in mass spectrometry have allowed for estimates of absolute concentrations across entire proteomes, permitting the interrogation of many important biological questions. Here, we focus on a quantitative aspect of human cancer cell metabolism that has been limited by a paucity of available data on the abundance of metabolic enzymes. We integrate data from recent measurements of absolute protein concentration to analyze the statistics of protein abundance across the human metabolic network. At a global level, we find that the enzymes in glycolysis comprise approximately half of the total amount of metabolic proteins and can constitute up to 10% of the entire proteome. We then use this analysis to investigate several outstanding problems in cancer metabolism, including the diversion of glycolytic flux for biosynthesis, the relative contribution of nitrogen assimilating pathways, and the origin of cellular redox potential. We find many consistencies with current models, identify several inconsistencies, and find generalities that extend beyond current understanding. Together our results demonstrate that a relatively simple analysis of the abundance of metabolic enzymes was able to reveal many insights into the organization of the human cancer cell metabolic network.

Fig 1. Global intracellular distribution of metabolic protein concentrations across all cell lines.

(a) Pie chart diagraming the total percentage of metabolic proteins across all cell lines. Metabolic proteins are differentiated by a different color inset. (b) Probability distribution function of cell protein copy (CPC) values for all proteins and the metabolic subset—different subsets are denoted by different colors. Log₁₀ values were binned with a bin difference of 10^0.3 and the relative frequency, or percentage of values falling into that bin, were plotted.

Fig 2. Distribution of metabolic proteome percentage across all cell lines for various pathways.

For each distribution the median, standard deviations, max, and min are indicated. Inset contains a magnified look at the pathways with the highest percentages of the metabolic proteome.

Fig 3. Global profile of glycolytic enzyme concentrations across all cell lines.

(a) Distribution of cell protein copy (CPC) values for all glycolytic/gluconeogenic proteins across all cell lines. For each protein the median, standard deviations, max, and min are indicated. (b) Probability distribution function of CPC values for all metabolic proteins and the glycolytic/gluconeogenic subset—different subsets are denoted by different colors. Values were binned with a bin difference of 10^0.2 and the relative frequency, or percentage of values falling into that bin, were plotted. (c) Distribution of 11 glycolytic proteins in a sequential pathway order. Center dot indicates average CPC value for each protein with bars indicating the max and min measurements across all cell lines. (d) Pathway diagram of glycolysis activity. Blue squares indicate branching into other biological pathways, blue hexagons indicate intermediate metabolites, and purple circles indicate reacting enzymes. Size of purple circle is proportional to the average CPC value for that enzyme across all cell lines.

Fig 4. Branch point analysis across the human metabolic protein network.

(a) Diagram clarifying method for computing various Branch Divergence scores in 2 different circumstances. Orange squares indicate reactant and product metabolites with blue ovals indicating the reacting enzymes. (b) Histogram of Branch Divergence Scores based on top 2 values. Each bin is lower end inclusive with a bin size of 0.1. (c) Histogram of Branch Divergence Scores based on top 3 values. Each bin is lower end inclusive with a bin size of 0.1. (d) Plot indicating the p-values for pathways that have significantly different counts in one-sided and equally distributed pathways (defined as a p-value < 0.05). (e) Ratio of one-sided counts to equally distributed counts for significant pathways.

Fig 5. Cofactor and protein concentration analysis within the human metabolic protein network.

Network diagram of glycolysis illustrating the abundance of aminotransferases and enzymes that utilize NAD(P)/NAD(P)H as a cofactor. The size of the nodes corresponds to the average abundance of the proteins.

Fig 6. Analysis of enzyme concentrations in relation to kinetic and thermodynamic properties.

(a) Scatter plot of the log of the average K_M and ΔG° value with each dot representing a different metabolic protein. (b) Scatter plot of the log of the average cell protein copy (CPC) and ΔG° values with each dot representing a different metabolic protein. (c) Scatter plot of the log of both the average K_M and average CPC value with each dot representing a different metabolic protein. (d) Connectivity analysis of CPC, ΔG° and K_M values for the various enzymes.