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.

Pooled-matrix protein interaction screens using Barcode Fusion Genetics.

High-throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome-scale interaction mapping. Here, we report Barcode Fusion Genetics-Yeast Two-Hybrid (BFG-Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG-Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein-pair barcodes that can be quantified via next-generation sequencing. We applied BFG-Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG-Y2H increases the efficiency of protein matrix screening, with quality that is on par with state-of-the-art Y2H methods.

Tunable oscillations and chaotic dynamics in systems with localized synthesis.

Biological systems contain biochemical control networks that reside within a remarkable spatial structure. We present a theoretical study of a biological system in which two chemically coupled species, an activating species and an inhibiting species forming a negative feedback, are synthesized at unique sites and interact with each other through diffusion. The dynamical behaviors in these systems depend on the spatial locations of these synthetic sites. In a negative feedback system with two sites, we find two dynamical modes: fixed point and stable oscillations whose frequency can be tuned by varying the distance between the sites. When there are multiple synthetic sites, we find more diverse dynamics, including chaos, quasiperiodicity, and bistability. Based on this theoretical analysis, it should be possible to create in the laboratory synthetic circuits displaying these dynamics. This study illustrates the concept of "spatial switching," in which bifurcations in the dynamics occur as a function of the geometry of the system.