Protein Evolution: Mapping the Fitness Landscape and the Role of Constraints Imposed by the Genetic Code
Embargo until
2014-12-01
Date
2013-10-14
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Johns Hopkins University
Abstract
Mutations are central to evolution, providing the genetic variation upon which selection acts. A mutation’s impact on fitness can be positive, negative, or neutral. Knowledge of the distribution of fitness effects (DFE) of mutations is fundamental for understanding evolutionary dynamics, molecular-level genetic variation, complex genetic disease, the accumulation of deleterious mutations, the molecular clock, and the impact of constraints imposed by the genetic code. In order to facilitate study of the DFE, we developed a new mutagenesis technique, termed PFunkel, by which large gene libraries can be created in a single day, single tube reaction with user-control over the type and position of mutations as well as the number of mutations per gene. We used PFunkel to create several types of libraries of the E. coli TEM-1 β-lactamase gene. By analyzing adaptive mutations in these libraries we found that the architecture of the genetic code significantly constrains the adaptive exploration of sequence space. However, the constraints endow the code with the ability to restrict access to amino acid mutations with a strong negative effect and, most remarkably, the ability to enrich for adaptive mutations. Furthermore, we present a comprehensive DFE for codon substitutions of the TEM-1 gene and amino acid substitutions in the TEM-1 protein. This DFE provides insight into the origin of the genetic code, support for the hypothesis that mRNA stability dictates codon usage at the beginning of genes, an extensive framework for understanding protein mutational tolerance, and evidence that mutational effects on protein thermodynamic stability shape the DFE. Contrary to prevailing expectations, we find that deleterious effects of mutation primarily arise from a decrease in specific protein activity and not protein cellular levels.
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Keywords
fitness landscape, mutations, genetic code, distribution of fitness effects, mutagenesis, deep sequencing