Quantitative Tracking of Combinatorially Engineered Populations with Multiplexed Binary Assemblies

Highly Combinatorial Genetic Interaction Analysis Reveals a Multi-Drug Transporter Influence Network

Many traits are complex, depending non-additively on variant combinations. Even in model systems, such as the yeast S. cerevisiae, carrying out the high-order variant-combination testing needed to dissect complex traits remains a daunting challenge. Here, we describe “X-gene” genetic analysis (XGA), a strategy for engineering and profiling highly combinatorial gene perturbations. We demonstrate XGA on yeast ABC transporters by engineering 5,353 strains, each deleted for a random subset of 16 transporters, and profiling each strain’s resistance to 16 compounds. XGA yielded 85,648 genotype-to-resistance observations, revealing high-order genetic interactions for 13 of the 16 transporters studied. Neural networks yielded intuitive functional models and guided exploration of fluconazole resistance, which was influenced non-additively by five genes. Together, our results showed that highly combinatorial genetic perturbation can functionally dissect complex traits, supporting pursuit of analogous strategies in human cells and other model systems.

Celaj et al. introduce “X-gene” genetic analysis (XGA), a strategy for modeling complex systems by engineering and profiling highly combinatorial genetic perturbations. They apply XGA to 16 yeast ABC transporters, revealing many high-order genetic interactions. Neural network models yielded intuitive functional models and illuminated an ABC transporter influence network, supporting application of XGA to other organisms and processes.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

A versatile platform strain for high-fidelity multiplex genome editing

Precision genome editing accelerates the discovery of the genetic determinants of phenotype and the engineering of novel behaviors in organisms. Advances in DNA synthesis and recombineering have enabled high-throughput engineering of genetic circuits and biosynthetic pathways via directed mutagenesis of bacterial chromosomes. However, the highest recombination efficiencies have to date been reported in persistent mutator strains, which suffer from reduced genomic fidelity. The absence of inducible transcriptional regulators in these strains also prevents concurrent control of genome engineering tools and engineered functions. Here, we introduce a new recombineering platform strain, BioDesignER, which incorporates (i) a refactored λ-Red recombination system that reduces toxicity and accelerates multi-cycle recombination, (ii) genetic modifications that boost recombination efficiency, and (iii) four independent inducible regulators to control engineered functions. These modifications resulted in single-cycle recombineering efficiencies of up to 25% with a 7-fold increase in recombineering fidelity compared to the widely used recombineering strain EcNR2. To facilitate genome engineering in BioDesignER, we have curated eight context--neutral genomic loci, termed Safe Sites, for stable gene expression and consistent recombination efficiency. BioDesignER is a platform to develop and optimize engineered cellular functions and can serve as a model to implement comparable recombination and regulatory systems in other bacteria.

Deep scanning lysine metabolism in Escherichia coli

Our limited ability to predict genotype-phenotype relationships has called for strategies that allow testing of thousands of hypotheses in parallel. Deep scanning mutagenesis has been successfully implemented to map genotype-phenotype relationships at a single-protein scale, allowing scientists to elucidate properties that are difficult to predict. However, most phenotypes are dictated by several proteins that are interconnected through complex and robust regulatory and metabolic networks. These sophisticated networks hinder our understanding of the phenotype of interest and limit our capabilities to rewire cellular functions. Here, we leveraged CRISPR-EnAbled Trackable genome Engineering to attempt a parallel and high-resolution interrogation of complex networks, deep scanning multiple proteins associated with lysine metabolism in Escherichia coli We designed over 16,000 mutations to perturb this pathway and mapped their contribution toward resistance to an amino acid analog. By doing so, we identified different routes that can alter pathway function and flux, uncovering mechanisms that would be difficult to rationally design. This approach sets a framework for forward investigation of complex multigenic phenotypes.