Mapping temperature-sensitive mutations at a genome scale to engineer growth switches in Escherichia coli.

Temperature-sensitive (TS) mutants are a unique tool to perturb and engineer cellular systems. Here, we constructed a CRISPR library with 15,120 Escherichia coli mutants, each with a single amino acid change in one of 346 essential proteins. 1,269 of these mutants showed temperature-sensitive growth in a time-resolved competition assay. We reconstructed 94 TS mutants and measured their metabolism under growth arrest at 42°C using metabolomics. Metabolome changes were strong and mutant-specific, showing that metabolism of nongrowing E. coli is perturbation-dependent. For example, 24 TS mutants of metabolic enzymes overproduced the direct substrate metabolite due to a bottleneck in their associated pathway. A strain with TS homoserine kinase (ThrBF267D ) produced homoserine for 24 h, and production was tunable by temperature. Finally, we used a TS subunit of DNA polymerase III (DnaXL289Q ) to decouple growth from arginine overproduction in engineered E. coli. These results provide a strategy to identify TS mutants en masse and demonstrate their large potential to produce bacterial metabolites with nongrowing cells.

Metabolism of non-growing bacteria.

A main function of bacterial metabolism is to supply biomass building blocks and energy for growth. This seems to imply that metabolism is idle in non-growing bacteria. But how relevant is metabolism for the physiology of non-growing bacteria and how active is their metabolism? Here, we reviewed literature describing metabolism of non-growing bacteria in their natural environment, as well as in biotechnological and medical applications. We found that metabolism does play an important role during dormancy and that especially the demand for ATP determines metabolic activity of non-growing bacteria.

Pervasive cooperative mutational effects on multiple catalytic enzyme traits emerge via long-range conformational dynamics.

Multidimensional fitness landscapes provide insights into the molecular basis of laboratory and natural evolution. To date, such efforts usually focus on limited protein families and a single enzyme trait, with little concern about the relationship between protein epistasis and conformational dynamics. Here, we report a multiparametric fitness landscape for a cytochrome P450 monooxygenase that was engineered for the regio- and stereoselective hydroxylation of a steroid. We develop a computational program to automatically quantify non-additive effects among all possible mutational pathways, finding pervasive cooperative signs and magnitude epistasis on multiple catalytic traits. By using quantum mechanics and molecular dynamics simulations, we show that these effects are modulated by long-range interactions in loops, helices and ß-strands that gate the substrate access channel allowing for optimal catalysis. Our work highlights the importance of conformational dynamics on epistasis in an enzyme involved in secondary metabolism and offers insights for engineering P450s.

Unbiased libraries in protein directed evolution.

Directed evolution is a powerful approach to study the molecular basis of protein evolution and to engineer proteins for a wide range of applications in synthetic organic chemistry and biotechnology. There are many methods based on random or focused mutagenesis to engineer successfully any protein trait. Focused approaches such as site-directed and saturation mutagenesis have become methods of choice for improving protein activity, selectivity, stability and many other traits because the screening step can be practically handled (bottleneck in directed evolution). Although novel mutagenesis methods based on CRISPR or solid-phase gene synthesis can eliminate bias when creating protein libraries, traditional PCR approaches, although imperfect, remain widely used due to their ease and low cost. One of the most common approaches in focused mutagenesis relies on NNK mutagenesis, however, the primer-based 22c-trick and small-intelligent methods have emerged as key tools for constructing less biased and unbiased libraries when all 20 canonical amino acids are needed for various reasons. In this minireview, we assess studies employing such methods for library creation and their areas of application. We also discuss the advantages and disadvantages of both methods and provide a perspective for creating smarter libraries.