The genetic tools and resources available in the model organism Saccharomyces cerevisiae have enabled large-scale functional genomics studies that collectively provide new insight into how genes function as networks to fulfill the requirements of biological systems. The cornerstone of these tools was the collaborative creation of a complete set of non-essential gene deletions of all open reading frames in yeast1,2. A striking observation was that only ~20% of yeast genes are required for viability when grown as haploids under standard laboratory conditions. This highlights the ability of a cell to buffer against genomic perturbations through the utilization of alternative biological pathways. Genetic mutants that are viable individually, but lethal in combination, signal connected or convergent parallel biological pathways and form genetic interaction networks that describe biological function. With the development of conditional temperature-sensitive and hypomorphic alleles of essential genes the technology has not been limited to the study of non-essential genes3,4. This concept has been applied at a genomic scale producing an unbiased genetic interaction map illustrating how genes involved in similar cellular processes cluster together5.
Chemical perturbations of genetic networks mimic gene deletions (Figure 1)6. Querying growth-inhibitory compounds against a high-density array of deletion strains for hypersensitivity identifies a chemical-genetic interaction profile, i.e. a list of genes that is required to tolerate chemical stress. Like genetic interactions, large-scale screens of chemical libraries have shown that compounds with a similar mode of action cluster together7. Therefore, by establishing the chemical-genetic interaction profile of a compound the mode of action may be inferred by comparing it with large-scale synthetic genetic and chemical genetic interaction datasets8,9.
Large-scale chemical-genetic screens, where scores of compounds are interrogated, have been performed by barcode competition assays. In this approach, the pooled collection of deletion strains is grown en masse for several generations in a small volume of media containing a chemical. Since each deletion mutant harbors a unique genetic barcode, the viability/growth of individual mutants within the pool of deletion strains is tracked by microarray or high-throughput sequencing10.
Inferring fitness by monitoring colony size of physically arrayed mutants grown on solid agar containing a bioactive compound is also an effective method to identify chemical-genetic interactions11,12. This approach provides a cost-effective alternative to competition-based screening and is well suited for assaying small libraries of chemicals. Outlined here is a simple methodology for producing a list of chemical-genetic interactions in S. cerevisiae that does not rely on molecular biology manipulations or infrastructure. It requires only a yeast deletion collection, a robotic or manual pinning apparatus, and freely available image analysis software.