Affiliation: | (1) Howard Hughes Medical Institute, Broad Institute of Harvard and MIT, 7 Cambridge Center, Cambridge, MA 02142, USA;(2) Department of Molecular and Cellular Biology, Harvard University, 7 Divinity Avenue, Cambridge, MA 02138, USA;(3) Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA |
Abstract: | The “cognate bias hypothesis” states that early in evolutionary history the biosynthetic enzymes for amino acid x gradually lost residues of x, thereby reducing the threshold for deleterious effects of x scarcity. The resulting reduction in cognate amino acid composition of the enzymes comprising a particular amino acid biosynthetic pathway is predicted to confer a selective growth advantage on cells. Bioinformatic evidence from protein-sequence data of two bacterial species previously demonstrated reduced cognate bias in amino acid biosynthetic pathways. Here we show that cognate bias in amino acid biosynthesis is present in the other domains of life—Archaebacteria and Eukaryota. We also observe evolutionarily conserved underrepresentations (e.g., glycine in methionine biosynthesis) and overrepresentations (e.g., tryptophan in asparagine biosynthesis) of amino acids in noncognate biosynthetic pathways, which can be explained by secondary amino acid metabolism. Additionally, we experimentally validate the cognate bias hypothesis using the yeast Saccharomyces cerevisiae. Specifically, we show that the degree to which growth declines following amino acid deprivation is negatively correlated with the degree to which an amino acid is underrepresented in the enzymes that comprise its cognate biosynthetic pathway. Moreover, we demonstrate that cognate fold representation is more predictive of growth advantage than a host of other potential growth-limiting factors, including an amino acid’s metabolic cost or its intracellular concentration and compartmental distribution. Electronic supplementary material The online version of this article (doi: ) contains supplementary material, which is available to authorized users. Reviewing Editor: Dr. Niles Lehman Ethan O. Perlstein and Benjamin L. de Bivort contributed equally to this work. |