Multiplexed tracking of combinatorial genomic mutations in engineered cell populations

Developers

Ramsey I Zeitoun, Andrew D Garst, Nanette R Boyle, Ryan T Gill, etc.

Description of the technology

The technology serves for the improving of multiplexed genome approaches with the help of the tracking of combinatorial genomic mutations in engineered libraries. 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 lacked to date.

This technology is 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 were assembled into individual DNA constructs that were compatible with next-generation sequencing strategies. A mathematical model was developed describing the annealing reaction kinetics to predict and generalize high-order assembly. This modeling revealed that large constructs (more than six sites) could be assembled provided that suitable primers and reactions conditions were used within a few dozen PCR cycles. Besides, a computational tool was developed to automate the design of synthetic DNA constructs (primers, linkers). By condensing genotype information into a single construct compatible with high-throughput sequencing technology, the method can track libraries containing >105 members.

TRACE was applied to map growth selection dynamics for Escherichia coli combinatorial libraries created by recursive multiplex recombineering at a depth 104-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.

Practical application

Although in this study the technology (i.e. TRACE) was validated using different multiplexed recombineering libraries generated in E. coli, all of the techniques used, including PCR, emulsion and sequencing technologies were standard. Thus, TRACE should work well in a broad range of model organisms. It was confirmed by the use of this technology for the assessment of combinatorial mutations in the ES2 human ovarian carcinoma cancer cell line.

In addition to the analysis of combinatorial mutagenesis of genomes, TRACE could be applied to track mutations made using different synthetic approaches including small-regulatory RNAs, CRISPR-Cas mutagenesis or barcoded synthetic constructs. TRACE, which utilizes high-throughput sequencing, is compatible with the throughput of library constructing, which thereby enables a fully integrated engineering cycle in which combinatorial design rules can be readily ascertained and leveraged in recursive engineering and optimization processes.

Laboratories

• Department of Chemical and Biological Engineering, University of Colorado Boulder, Boulder (USA)
• Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh (USA)
• Department of Chemical and Biological Engineering, Colorado School of Mines, Golden (USA)

Links

Publications

• Zeitoun, R.I. et al. «Multiplexed tracking of combinatorial genomic mutations in engineered cell populations." 33.6 Nat Biotechnol. (2015): 631−637.
• Liu, R. et al. «Genome scale engineering techniques for metabolic engineering." 32 Metab Eng. (2015): 143−154.
• Warner, J.R., et al. «Rapid profiling of a microbial genome using mixtures of barcoded oligonucleotides." 28 Nat. Biotechnol. (2010): 856–862.