Abstract
AbstractProteins vary in their cost to the cell and natural selection may favour the use of proteins that are cheaper to produce. We develop a novel approach to estimate the amino acid biosynthetic cost based on genome-scale metabolic models, and directly investigate the effects of biosynthetic cost on transcriptomic, proteomic and metabolomic data in Saccharomyces cerevisiae. We find that our systems approach to formulating biosynthetic cost produces a novel measure that explains similar levels of variation in gene expression compared with previously reported cost measures. Regardless of the measure used, the cost of amino acid synthesis is weakly associated with transcript and protein levels, independent of codon usage bias. In contrast, energetic costs explain a large proportion of variation in levels of free amino acids. In the economy of the yeast cell, there appears to be no single currency to compute the cost of amino acid synthesis, and thus a systems approach is necessary to uncover the full effects of amino acid biosynthetic cost in complex biological systems that vary with cellular and environmental conditions.
Highlights
Everything in a living cell has a cost: from the energy needed to transform molecules against thermodynamic equilibria, to the raw materials needed to produce the constituents of a new cell
As in previous studies[14, 31, 20, 33, 35], we focus on amino acid synthesis, because this allows us to analyse the effects of cost on gene expression
We showed that our systems biology approach can be applied to calculate environment-specific biosynthetic costs, which highlighted the effects of limiting elements of amino acid cost
Summary
Everything in a living cell has a cost: from the energy needed to transform molecules against thermodynamic equilibria, to the raw materials needed to produce the constituents of a new cell. Natural selection may be expected to minimise such cellular costs, and evidence for adaptation to require less energy and matter may exist at the molecular or cellular level Testing this hypothesis requires answering several questions about the meaning of cost in the cell, and how to measure it. Craig and Weber [14] pioneered the quantitative analysis of cost at the cellular level to investigate the effects on the synthesis and evolution of a small number of Escherichia coli proteins Their approach to estimate the cost of a protein is the sum of how many units of high energy phosphate bonds (e.g. ATP) and reducing hydrogen atoms (e.g. NADPH) are diverted from the available energy pool to produce each of the constituent amino acids from glucose, averaged over the length of the protein. Wagner [35] developed a method similar to Craig and Weber [14] that includes the energetic costs of synthesising both mRNA and protein for Saccharomyces cerevisiae, and showed that the cost of doubling gene expression after a gene duplication is likely to be significant enough to come under under selection pressure
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