Rapid Cell-Free Combinatorial Mutagenesis Workflow Using Small Oligos Suitable for High-Iteration, Active Learning-Guided Protein Engineering

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Abstract

Active learning-guided protein engineering e2iciently navigates the challenging fitness landscape by screening designs iteratively in a model-guided design-build-test-learn cycle. However, while high iterations boost performance, current workflows are slow and costly due to their reliance on cell-based cloning and expression limiting the number of iterations they can practically implement. To address this problem and enable rapid, high-iteration, active learning-guided protein engineering, we present a novel combinatorial mutagenesis workflow that uses small (∼20-40 bp) mutagenic annealed-oligo fragments and cell-free expression to rapidly and conveniently screen protein variants in <9 hours. The annealed-oligo’s small size is >80% reduction from current shu2ling strategies, minimizing the likelihood of needing to include nearby mutation sites on the same fragment and having the combinatorial increase of unique oligos needed to cover the design space. The oligos are also simple to prepare in bulk for the whole engineering campaign, eliminating the need for PCR mutagenesis or ordering of costly commercial genes each screening round. Our workflow was validated by screening superfolder green fluorescent protein (sfGFP) and uricase mutants assembled using three, five, and ten fragments. We observed high sequence fidelity, predictable mutant activities, and compatibility with automation demonstrating our workflows generality, reliability, and utility for protein engineering.

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