Minor isozymes tailor yeast metabolism to carbon availability

Abstract

AbstractIsozymes are enzymes that differ in sequence but catalyze the same chemical reactions. Despite their apparent redundancy, isozymes are often retained over evolutionary time for reasons that can be unclear. We find that, in yeast, isozymes are strongly enriched in central carbon metabolism. Using a gene expression compendium, we find that many isozyme pairs show anticorrelated expression during the respirofermentative shift, suggesting roles in adapting to changing carbon availability. Building on this observation, we assign function to two minor central carbon isozymes, aconitase 2 (ACO2) and pyruvate kinase 2 (PYK2).ACO2is expressed during fermentation and proves advantageous when glucose is limiting.PYK2is expressed during respiration and proves advantageous for growth on three-carbon substrates.PYK2’s deletion is rescued by expressing the major pyruvate kinase, but only if that enzyme carries mutations mirroringPYK2’s allosteric regulation. Thus, central carbon isozymes enable more precise tailoring of metabolism to changing nutrient availability.ImportanceGene duplication is one of the main evolutionary drivers of new protein function. However, some gene duplicates have nevertheless persisted long-term without apparent divergence in biochemical function. Further, under standard lab conditions, many isozymes have subtle or no knockout phenotypes. These factors make it hard to assess the unique contributions of individual isozymes to fitness. We therefore developed a method to identify experimental perturbations that could expose such contributions, and applied it to yeast gene expression data, revealing a potential role for a set of yeast isozymes in adapting to changing carbon sources. Our experimental confirmation of distinct roles for two “minor” yeast isozymes, including one with no previously described knockout phenotype, highlight that even apparently redundant paralogs can have important and unique functions, with implications for genome-scale metabolic modeling and systems-level studies of quantitative genetics.