10 research outputs found

    Initial Mutations Direct Alternative Pathways of Protein Evolution

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    Whether evolution is erratic due to random historical details, or is repeatedly directed along similar paths by certain constraints, remains unclear. Epistasis (i.e. non-additive interaction between mutations that affect fitness) is a mechanism that can contribute to both scenarios. Epistasis can constrain the type and order of selected mutations, but it can also make adaptive trajectories contingent upon the first random substitution. This effect is particularly strong under sign epistasis, when the sign of the fitness effects of a mutation depends on its genetic background. In the current study, we examine how epistatic interactions between mutations determine alternative evolutionary pathways, using in vitro evolution of the antibiotic resistance enzyme TEM-1 β-lactamase. First, we describe the diversity of adaptive pathways among replicate lines during evolution for resistance to a novel antibiotic (cefotaxime). Consistent with the prediction of epistatic constraints, most lines increased resistance by acquiring three mutations in a fixed order. However, a few lines deviated from this pattern. Next, to test whether negative interactions between alternative initial substitutions drive this divergence, alleles containing initial substitutions from the deviating lines were evolved under identical conditions. Indeed, these alternative initial substitutions consistently led to lower adaptive peaks, involving more and other substitutions than those observed in the common pathway. We found that a combination of decreased enzymatic activity and lower folding cooperativity underlies negative sign epistasis in the clash between key mutations in the common and deviating lines (Gly238Ser and Arg164Ser, respectively). Our results demonstrate that epistasis contributes to contingency in protein evolution by amplifying the selective consequences of random mutations

    Figure S1 and Model extantion from Errors in mutagenesis and the benefit of cell-to-cell signalling in the evolution of stress-induced mutagenesis

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    Figure S1 - The mean fitness difference between populations with SIM or qSIM relative to populations with NM. Full model for competition between mutagenesis strategie

    Negative Epistasis and Evolvability in TEM-1 \u3b2-Lactamase\u2014The Thin Line between an Enzyme's Conformational Freedom and Disorder

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    Epistasis is a key factor in evolution since it determines which combinations of mutations provide adaptive solutions and which mutational pathways toward these solutions are accessible by natural selection. There is growing evidence for the pervasiveness of sign epistasis\u2014a complete reversion of mutational effects, particularly in protein evolution\u2014yet its molecular basis remains poorly understood. We describe the structural basis of sign epistasis between G238S and R164S, two adaptive mutations in TEM-1 \u3b2-lactamase\u2014 an enzyme that endows antibiotics resistance. Separated by 10 \uc5, these mutations initiate two separate trajectories toward increased hydrolysis rates and resistance toward second and third-generation cephalosporins antibiotics. Both mutations allow the enzyme's active site to adopt alternative conformations and accommodate the new antibiotics. By solving the corresponding set of crystal structures, we found that R164S causes local disorder whereas G238S induces discrete conformations. When combined, the mutations in 238 and 164 induce local disorder whereby nonproductive conformations that perturb the enzyme's catalytic preorganization dominate. Specifically, Asn170 that coordinates the deacylating water molecule is misaligned, in both the free form and the inhibitor-bound double mutant. This local disorder is not restored by stabilizing global suppressor mutations and thus leads to an evolutionary cul-de-sac. Conformational dynamism therefore underlines the reshaping potential of protein's structures and functions but also limits protein evolvability because of the fragility of the interactions networks that maintain protein structures
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