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Abstract Protocols for the construction of large, deeply mutagenized protein encoding libraries via Golden Gate assembly of synthetic DNA cassettes employ disparate, system‐specific methodology. Here we present a standardized Golden Gate method for building user‐defined libraries. We demonstrate that a 25 μL reaction, using 40 fmol of input DNA, can generate a library on the order of 1 × 10⁶members and that reaction volume or input DNA concentration can be scaled up with no losses in transformation efficiency. Such libraries can be constructed from dsDNA cassettes generated either by degenerate oligonucleotides or oligo pools. We demonstrate its real‐world effectiveness by building custom, user‐defined libraries on the order of 10⁴–10⁷unique protein encoding variants for two orthogonal protein engineering systems. We include a detailed protocol and provide several general‐use destination vectors. 

Precise, stringent, post-translational activation of enzymes is essential for many synthetic biology applications. For example, even a few intracellular molecules of unregulated T7 RNA polymerase can result in growth cessation in a bacterium. We sought to mimic the properties of natural enzymes, where activity is regulated ubiquitously by endogenous metabolites. Here we demonstrate that full-length, single subunit T7-derived RNA polymerases (T7 RNAP) can be activated by physiologically relevant concentrations of indoles. We used rational design and directed evolution to identify T7 RNAP variants with minimal transcriptional activity in the absence of indole, and a 29-fold increase in activity with an EC50 of 344 μM. Indoles control T7-dependent gene expression exogenously, endogenously, and between cells. We also demonstrate indole-dependent bacteriophage viability and propagation in trans. Specificity of different indoles, T7 promoter specificities, and portability to different bacteria are shown. Our ligand activated RNA polymerases (LARPs) represent a new chemically inducible “stop and go” platform immediately deployable for novel synthetic biology applications, including for modulation of synthetic cocultures. 

Predictive understanding for how a particular amino acid sequence encodes enzymatic function is a grand challenge in molecular biology, with profound impacts in fields ranging from industrial biotechnology, computational protein design, and agriculture to predictive identification of disease mutations ( 1 ) and medicinal chemistry. Innovative methods for high-throughput and quantitative measurements of different aspects of enzymatic function are needed to achieve this goal. On page 411 of this issue, Markin et al. ( 2 ) describe a laboratory-on-a-chip platform called High-Throughput Microfluidic Enzyme Kinetics (HT-MEK) as a step in this direction. The technique allows high-fidelity in vitro biochemical and biophysical characterization of more than 1000 mutants of the model enzyme PafA (phosphate-irrepressible alkaline phosphatase of Flavobacterium). HT-MEK identifies partially overlapping yet distinct networks of amino acids that undergird individual reaction steps of PafA, illuminating the mechanistic basis of catalysis for this enzyme. 

Abstract Generating combinatorial libraries of specific sets of mutations are essential for addressing protein engineering questions involving contingency in molecular evolution, epistatic relationships between mutations, as well as functional antibody and enzyme engineering. Here we present optimization of a combinatorial mutagenesis method involving template-based nicking mutagenesis, which allows for the generation of libraries with >99% coverage for tens of thousands of user-defined variants. The non-optimized method resulted in low library coverage, which could be rationalized by a model of oligonucleotide annealing bias resulting from the nucleotide mismatch free-energy difference between mutagenic oligo and template. The optimized method mitigated this thermodynamic bias using longer primer sets and faster annealing conditions. Our updated method, applied to two antibody fragments, delivered between 99.0% (32451/32768 library members) to >99.9% coverage (32757/32768) for our desired libraries in 2 days and at an approximate 140-fold sequencing depth of coverage.