Multiplexed tracking of combinatorial genomic mutations in engineered cell populations

Abstract

Multiplexed genome engineering approaches can be used to generate targeted genetic diversity in cell populations on laboratory timescales, but methods to track mutations and link them to phenotypes have been lacking. We present an approach for tracking combinatorial engineered libraries (TRACE) through the simultaneous mapping of millions of combinatorially engineered genomes at single-cell resolution. Distal genomic sites are assembled into individual DNA constructs that are compatible with next-generation sequencing strategies. We used TRACE to map growth selection dynamics for Escherichia coli combinatorial libraries created by recursive multiplex recombineering at a depth 10(4)-fold greater than before. TRACE was used to identify genotype-to-phenotype correlations and to map the evolutionary trajectory of two individual combinatorial mutants in E. coli. Combinatorial mutations in the human ES2 ovarian carcinoma cell line were also assessed with TRACE. TRACE completes the combinatorial engineering cycle and enables more sophisticated approaches to genome engineering in both bacteria and eukaryotic cells than are currently possible.

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