The complexity of biological interaction networks poses a challenge to understanding the function of individual connections in the overall network. To address this challenge, we developed a high-throughput reverse engineering strategy to analyze how thousands of specific perturbations (encompassing all point mutations in a central gene) impact both a specific edge (interaction to a directly connected node) and an overall network function. We analyzed the effects of ubiquitin mutations on activation by the E1 enzyme and compared these to effects on yeast growth rate. Using this approach, we delineated ubiquitin mutations that selectively impacted the ubiquitin-E1 edge. We find that the elasticity function relating the efficiency of ubiquitin-E1 interaction to growth rate is non-linear and that a greater than 50-fold decrease in E1 activation efficiency is required to reduce growth rate by 2-fold. Despite the robustness of fitness to decreases in E1 activation efficiency, the effects of most ubiquitin mutations on E1 activation paralleled the effects on growth rate. Our observations indicate that most ubiquitin mutations that disrupt E1 activation also disrupt other functions. The structurally characterized ubiquitin-E1 interface encompasses the interfaces of ubiquitin with most other known binding partners, and we propose that this enables E1 in wild-type cells to selectively activate ubiquitin protein molecules capable of binding to other partners from the cytoplasmic pool of ubiquitin protein that will include molecules with chemical damage and/or errors from transcription and translation.
Keywords: E1 activation; elasticity function; quality filtering; systematic mutagenesis.
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