Summary Directed evolution is a powerful approach for engineering biomolecules and understanding adaptation. However, experimental strategies for directed evolution are notoriously laborintensive and low-throughput, limiting access to demanding functions, multiple functions in parallel, and the study of molecular evolution in replicate. We report OrthoRep, an orthogonal DNA polymerase-plasmid pair in yeast that stably mutates ~100,000-fold faster than the host genome in vivo, exceeding the error threshold of genomic replication that causes singlegeneration extinction. User-defined genes in OrthoRep continuously and rapidly evolve through serial passaging, a highly straightforward and scalable process. Using OrthoRep, we evolved drug-resistant malarial DHFRs in 90 independent replicates. We uncovered a more complex fitness landscape than previously realized, including common adaptive trajectories constrained by epistasis, rare outcomes that avoid a frequent early adaptive mutation, and a suboptimal fitness peak that occasionally traps evolving populations. OrthoRep enables a new paradigm of routine, high-throughput evolution of biomolecular and cellular function.

11Directed evolution is a powerful approach for engineering biomolecules and understanding 12 adaptation 1-3 . However, experimental strategies for directed evolution are notoriously low-13 throughput, limiting access to demanding functions, multiple functions in parallel, and the 14 study of molecular evolution in replicate. Here, we report OrthoRep, a yeast orthogonal 15DNA polymerase-plasmid pair that stably mutates ~100,000-fold faster than the host 16 genome in vivo, exceeding error thresholds of genomic replication that lead to single-17 generation extinction 4 . User-defined genes in OrthoRep continuously and rapidly evolve 18 through serial passaging, a highly scalable process. Using OrthoRep, we evolved drug 19 resistant malarial DHFRs 90 times and uncovered a more complex fitness landscape than 20 previously realized 5-9 . We find rare fitness peaks that resist the maximum soluble 21 concentration of the antimalarial pyrimethamine -these resistant variants support growth 22 at pyrimethamine concentrations >40,000-fold higher than the wild-type enzyme can 23 tolerate -and also find that epistatic interactions direct adaptive trajectories to convergent 24 outcomes. OrthoRep enables a new paradigm of routine, high-throughput evolution of 25 biomolecular and cellular function. 26 27

BackgroundThe mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question.ResultsIn this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations.ConclusionsOverall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-016-0283-2) contains supplementary material, which is available to authorized users.

We present automated continuous evolution (ACE), a platform for the hands-free directed evolution of biomolecules. ACE pairs OrthoRep, a genetic system for continuous targeted mutagenesis of user-selected genes in vivo, with eVOLVER, a scalable and automated continuous culture device for precise, multi-parameter regulation of growth conditions. By implementing real-time feedback-controlled tuning of selection stringency with eVOLVER, genes of interest encoded on OrthoRep autonomously traversed multimutation adaptive pathways to reach desired functions, including drug resistance and improved enzyme activity. The durability, scalability, and speed of biomolecular evolution with ACE should be broadly applicable to protein engineering as well as prospective studies on how selection parameters and schedules shape adaptation.Continuous evolution has emerged as a powerful paradigm for the evolution of proteins and enzymes 1-3 towards challenging functions 4,5 . In contrast to classical directed evolution approaches that rely on stepwise rounds of ex vivo mutagenesis, transformation into cells, and selection 6 , continuous evolution systems achieve rapid diversification and functional selection autonomously, often through in vivo targeted mutagenesis systems (Fig. 1a). The result is a mode of directed evolution that requires only the basic culturing of cells, in theory, enabling extensive speed, scale, and depth in evolutionary search 3 . In practice, however, developing a continuous evolution method that realizes all three properties has been challenging.Recently, our groups made two independent advances that can pair to achieve continuous evolution at significant speed, scale, and depth. These advances are OrthoRep and eVOLVER. First, OrthoRep. OrthoRep is an engineered genetic system for continuous in vivo targeted mutagenesis of genes of interest (GOIs) 2,7 . OrthoRep uses a highly error-prone, orthogonal DNA polymerase-plasmid pair in yeast that replicates GOIs at a mutation rate of 10 -5 substitutions per base (spb) without increasing the genomic mutation rate of 10 -10 spb (Fig. 1a). This ~100,000-fold increase in the mutation rate of GOIs drives their accelerated evolution (speed). Because the OrthoRep system functions entirely in vivo and culturing yeast is straightforward, independent GOI evolution experiments can be carried out in high-throughput (scale). In addition, long multimutation pathways can be traversed using OrthoRep, owing to the durability of mutagenesis over many generations (depth). However, to practically realize depth in evolutionary search, in vivo