Genome-modification technologies enable the rational engineering and perturbation of biological systems. Historically, these methods have been limited to gene insertions or mutations at random or at a few pre-defined locations across the genome. The handful of methods capable of targetedgene editing suffered from low efficiencies, significant labor costs, or both. Recent advances have dramatically expanded our ability to engineer cells in a directed and combinatorial manner. Here, we review current technologies and methodologies for genome-scale engineering, discuss the prospects for extending efficient genome modification to new hosts, and explore the implications of continued advances toward the development of flexibly programmable chasses, novel biochemistries, and safer organismal and ecological engineering.
Keywords:directed evolution; genome engineering; metabolic engineering; synthesis; synthetic chassis
Introduction The phrase ‘genome-scale engineering’ invokes a future in which organisms are custom designed to serve humanity. Yet humans have sculpted the genomes of domesticated plants and animals for generations. Darwin’s contemporary William Youatt described selective breeding as ‘that which enables the agriculturalist, not only to modify the character of his flock, but to change it altogether. It is the magician's wand, by means of which he may summon into life whatever form and mold he pleases’ (Youatt, 1837). Selective breeding has transformed aurochs into Holsteins, wolves into Chihuahuas and Great Danes, and teosinte into maize. All of these examples involved genomic changes at a scale dwarfing any attempted through rational design. Understanding why genomes have been more readily shaped by evolutionary principles than conventional design-based approaches is important for current and future genome engineering endeavors.
Engineering is a human enterprise consisting of iterative cycles of design, construction, and testing. Optimizing this iterative process involves balancing the relative time, costs, and expected benefits gained at each phase. However, rationally designing and building a genome to produce the desired phenotype has proven exceedingly difficult. Designing organisms to specification requires accurately predicting phenotype from genotype, a complex problem that is worsened by our incomplete knowledge of biomolecule production, degradation, and interaction rates. Moreover, the computational resources required to run bottom-up molecular-level simulations are daunting even for simpler systems (Karr et al, 2012; Koch, 2012). Nevertheless, models have been useful for generating new hypotheses and targeting promising areas for engineering. Yet, even with the best in silico predictions, we are still limited by our ability to construct the designed genome. More than any other factor, the absence of molecular tools for manipulating genomic sequences has forced us to rely on selective breeding and evolutionary optimization (Conrad et al, 2011) rather than rational genome design.
Recent breakthroughs in genomics and genome editing have promised a greater role for rational design in biological engineering (Figure 1), offering new opportunities for systems and synthetic biologists aiming to reverse-engineer naturally evolved systems and to build new systems. In particular, advances in high-throughput DNA sequencing and large-scale biomolecular modeling of metabolic and signaling networks represent two important new frontiers that aid genome-scale engineering. Over the last few years, thousands of bacterial genomes have been sequenced from a wide variety of natural species and numerous laboratory-generated strains (Pagani et al, 2012). These efforts have illuminated many essential features of the core genome (Lukjancenko et al, 2010), the extent and importance of genetic heterogeneity across populations (Avery, 2006), the ubiquity of horizontal gene transfer (Smillie et al, 2011), and the evolution and selection of functional genetic elements (David and Alm, 2011). At the same time, new computational tools have used the flood of data to model metabolic processes and signaling networks across the entire cell, generating many new testable hypotheses (Lewis et al, 2012). Most importantly, emerging advances in de novo synthesis and in vivo gene targeting allow empirical validation of these model-driven hypotheses. By building and testing synthetic variants of biological systems, we have a unique opportunity to decipher the constraints imposed by the complexity of evolved systems and develop strategies for engineering living systems more conducive to quantitative modeling and rational design.
Figure 1 A historical timeline of selected advances leading to genome-scale engineering.
Here we review recent technologies that empower design-based genome engineering approaches, identify potential bottlenecks, discuss strengths and limitations of strategies employing rational design versus evolution, and consider future applications of genome-scale engineering. We advocate a synergistic engineering strategy that adopts the best aspects of rational genome design and evolutionary optimization."
This paper is part of the series on Systems Biology Technologies.
Genome-scale engineering for systems and synthetic biology. Kevin M Esvelt & Harris H Wang
(Via.) Molecular Systems Biology