Most antibiotics and chemotherapies target the products of essential genes that are necessary for proliferation or survival of cells in vitro. The effectiveness of such therapeutics also depends on the repertoire or drug- resistance genes that help defend against such assaults. To improve the effectiveness of current antibiotics, and to facilitate development of novel antibiotics, high-throughput methods for comprehensively identifying essential genes and genes affecting drug susceptibility are sorely needed. Here we will implement a new method termed HIP (Hermes Insertion Profiling) in the pathogenic yeast Candida glabrata and a new deep- sequencing pipeline termed QIseq to identify all essential genes in this organism as well as all of non-essential genes that influence resistance to several classes of antifungals in clinical use today. HIP involves mobilizing a marked transposon to insert almost randomly at very high density throughout the small genome of C. glabrata, and then deep-sequencing millions of independent insertion events in the resulting pool of mutants. Essential genes will be identified based on their inability to tolerate insertions within the coding sequences, and this first complete essentialome in a pathogenic fungus will be compared to those of the model yeasts in order to reveal the core essential genes and potentially to improve essentialome predictions in other pathogens. Similarly, we will exploit HIP and QIseq to quantify enrichment/depletion of insertions in pools exposed to moderate concentrations of three clinical antifungals: amphotericin B, fluconazole, and caspofungin. Such insertions will define all the non-essential genes that regulate drug resistance, and modifications of this experiment will be used to define all genes that regulate the epi-genetic phenomena of drug tolerance and persistence, where small numbers of ?persister? cells become transiently refractory to the drugs even though they do not contain drug-resistance mutations. This project provides immediate insights into how C. glabrata generates and maintains resistance to, and tolerance of, several classes of clinical antifungals. It produces a very useful pool of bar-coded C. glabrata mutant strains to the research community for broader genome-wide studies of gene functions, and it serves as a model for how new drug targets and drug resistance mechanisms can be comprehensively evaluated in other pathogenic eukaryotes at low cost and high speed and accuracy using HIP-like approaches.
The research proposed here implements a powerful new platform of functional genomics, termed HIP, for the first time in a deadly pathogen of humans (the yeast Candida glabrata). We will use to HIP to identify all the genes that help this pathogen resist and evade our current antibiotics. We will also identify all the genes of C. glabrata that could be targeted for development of new antibiotics in the future. Therefore, this research provides important new insights into current and future therapeutics to treat life-threatening fungal infections.