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.
Highlights
Metabolism constitutes a fundamental component of cell physiology
The proteomic quantification for the NCI-60 panel makes use of a standardized cell protein copy number (CPC) metric, which is derived from the Label Free Quantification (LFQ) quantification from Gholami et al [19]
We considered a recent data set that utilized deep proteomic measurements across the NCI-60 cell line panel and a regression model to estimate protein abundance from mass spectrometry data (S1 Table)[19]
Summary
Metabolism constitutes a fundamental component of cell physiology. It allows for the processing of nutrients through chemical reaction networks, resulting in the production of energy and biosynthetic components and regulation of signal transduction processes by affecting the levels of metabolites that control the activity of proteins. A quantitative, predictive understanding of metabolism has countless possibilities[3,4,5], but has been limited by the lack of available data at the level of metabolite levels, enzyme expression, and flux. One major limitation in this systems level understanding stems from the lack of quantitative measurements of protein abundance[6]. The absolute protein concentration is essential for understanding enzyme kinetics and flux through a metabolic pathway[7]. For any PLOS ONE | DOI:10.1371/journal.pone.0117131 January 26, 2015
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