Combining chemogenomic and gene-dose assays to investigate drug synergy

From the earliest days of using natural remedies to modern applications of clinically tested medications, combining therapies for disease treatment has been standard practice. Combination treatments can exhibit synergistic effects, broadly defined as a greater-than-additive effect of two or more therapeutic agents. Indeed, clinicians often use their experience and expertise to tailor such combinations in the hopes of maximizing the therapeutic effect. Alongside these efforts, computational studies into understanding and predicting the biophysical underpinnings of how synergy is achieved have benefitted from high-throughput screening and computational biology. One challenge is how to best design and analyze the results of synergy studies performed at scale, especially because the number of possible combinations to test quickly becomes unmanageable, and the tools to analyze the resulting data are quite new. Nevertheless, the benefits of such studies are clear -- by combining multiple drugs in the treatment of infectious disease and cancer, for instance, one can lessen host toxicity and simultaneously reduce the likelihood of resistance to treatment. In this study, we extend the widely validated chemogenomic HIPHOP assay to drug combinations. We identify a class of "combination-specific sensitive strains" that suggest mechanisms for the synergies we observe and further suggest focused follow-up studies.