Fitness Loss and Library Size Determination in Saturation Mutagenesis

Abstract

Saturation mutagenesis is a widely used directed evolution technique, in which a large number of protein variants, each having random amino acids in certain predetermined positions, are screened in order to discover high-fitness variants among them. Several metrics for determining the library size (the number of variants screened) have been suggested in the literature, but none of them incorporates the actual fitness of the variants discovered in the experiment. We present the results of an extensive simulation study, which is based on probabilistic models for protein fitness landscape, and which investigates how the result of a saturation mutagenesis experiment – the fitness of the best variant discovered – varies as a function of the library size. In particular, we study the loss of fitness in the experiment: the difference between the fitness of the best variant discovered, and the fitness of the best variant in variant space. Our results are that the existing criteria for determining the library size are conservative, so smaller libraries are often satisfactory. Reducing the library size can save labor, time, and expenses in the laboratory.

Speeding up Directed Evolution: Combining the Advantages of Solid-Phase Combinatorial Gene Synthesis with Statistically Guided Reduction of Screening Effort

“…34 Nov also argues that "...existing criteria and practices for determining the library size in saturation mutagenesis experiments are often too conservative...". 42 Therefore, to determine the effect of library coverage reduction on the probability of finding 1 out of the nth-best mutants, we assessed the relationship between the traditional Patrick−Firth and Nov metrics (Figure 4). Interestingly, aiming for finding the best mutant corresponds to 95% library coverage as shown elsewhere, 34 whereas finding at least 1 out of the second, third, fourth, and fifth best mutants corresponds to 78%, 63%, 53%, and 45% library coverage, respectively, regardless of library size and design (Figure 4).…”

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

“…Rational approaches have been reviewed, 588 including from the perspective of the necessary library size. 589 As a result, there is significant interest in the development of novel methodologies that can address these issues to produce accurate variant libraries, with larger numbers of simultaneous mutations in an economical workflow.…”

Darwin Assembly: fast, efficient, multi-site bespoke mutagenesis

“…Library quality is a major contributing factor to directed evolution ( 36 ). It impacts the minimum library size that has to be generated to adequately sample a given sequence landscape ( 16 , 37 ) and it impacts the choice of selection strategy (depending on the relative rarity of a ‘successful’ variant and gain of function over wild-type). Generating high-quality libraries that target multiple distal sites in a gene is challenging, with commercial library synthesis and modular assembly of the library being available only recently.…”