RESUMO
Within the budding yeasts, the opportunistic pathogen Candida glabrata and other members of the Nakaseomyces clade have developed virulence traits independently from C. albicans and C. auris To begin exploring the genetic basis of C. glabrata virulence and its innate resistance to antifungals, we launched the Hermes transposon from a plasmid and sequenced more than 500,000 different semi-random insertions throughout the genome. With machine learning, we identified 1278 protein-encoding genes (25% of total) that could not tolerate transposon insertions and are likely essential for C. glabrata fitness in vitro Interestingly, genes involved in mRNA splicing were less likely to be essential in C. glabrata than their orthologs in S. cerevisiae, whereas the opposite is true for genes involved in kinetochore function and chromosome segregation. When a pool of insertion mutants was challenged with the first-line antifungal fluconazole, insertions in several known resistance genes (e.g., PDR1, CDR1, PDR16, PDR17, UPC2A, DAP1, STV1) and 15 additional genes (including KGD1, KGD2, YHR045W) became hypersensitive to fluconazole. Insertions in 200 other genes conferred significant resistance to fluconazole, two-thirds of which function in mitochondria and likely down-regulate Pdr1 expression or function. Knockout mutants of KGD2 and IDH2, which consume and generate alpha-ketoglutarate in mitochondria, exhibited increased and decreased resistance to fluconazole through a process that depended on Pdr1. These findings establish the utility of transposon insertion profiling in forward genetic investigations of this important pathogen of humans.
Assuntos
Candida glabrata , Proteínas de Saccharomyces cerevisiae , Antifúngicos/farmacologia , Candida glabrata/genética , Candida glabrata/metabolismo , Farmacorresistência Fúngica/genética , Fluconazol/farmacologia , Genes Essenciais , Humanos , Testes de Sensibilidade Microbiana , Proteínas de Transferência de Fosfolipídeos , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/genética , Fatores de Transcrição/genéticaRESUMO
In vivo transposon mutagenesis, coupled with deep sequencing, enables large-scale genome-wide mutant screens for genes essential in different growth conditions. We analyzed six large-scale studies performed on haploid strains of three yeast species (Saccharomyces cerevisiae, Schizosaccaromyces pombe, and Candida albicans), each mutagenized with two of three different heterologous transposons (AcDs, Hermes, and PiggyBac). Using a machine-learning approach, we evaluated the ability of the data to predict gene essentiality. Important data features included sufficient numbers and distribution of independent insertion events. All transposons showed some bias in insertion site preference because of jackpot events, and preferences for specific insertion sequences and short-distance vs long-distance insertions. For PiggyBac, a stringent target sequence limited the ability to predict essentiality in genes with few or no target sequences. The machine learning approach also robustly predicted gene function in less well-studied species by leveraging cross-species orthologs. Finally, comparisons of isogenic diploid versus haploid S. cerevisiae isolates identified several genes that are haplo-insufficient, while most essential genes, as expected, were recessive. We provide recommendations for the choice of transposons and the inference of gene essentiality in genome-wide studies of eukaryotic haploid microbes such as yeasts, including species that have been less amenable to classical genetic studies.
Assuntos
Elementos de DNA Transponíveis/genética , Genes Essenciais/genética , Filogenia , Saccharomyces cerevisiae/genética , Candida albicans/genética , Genoma Fúngico/genética , Haploidia , Sequenciamento de Nucleotídeos em Larga Escala , Mutagênese InsercionalRESUMO
Knowing the full set of essential genes for a given organism provides important information about ways to promote, and to limit, its growth and survival. For many non-model organisms, the lack of a stable haploid state and low transformation efficiencies impede the use of conventional approaches to generate a genome-wide comprehensive set of mutant strains and the identification of the genes essential for growth. Here we report on the isolation and utilization of a highly stable haploid derivative of the human pathogenic fungus Candida albicans, together with a modified heterologous transposon and machine learning (ML) analysis method, to predict the degree to which all of the open reading frames are required for growth under standard laboratory conditions. We identified 1,610 C. albicans essential genes, including 1,195 with high "essentiality confidence" scores, thereby increasing the number of essential genes (currently 66 in the Candida Genome Database) by >20-fold and providing an unbiased approach to determine the degree of confidence in the determination of essentiality. Among the genes essential in C. albicans were 602 genes also essential in the model budding and fission yeasts analyzed by both deletion and transposon mutagenesis. We also identified essential genes conserved among the four major human pathogens C. albicans, Aspergillus fumigatus, Cryptococcus neoformans, and Histoplasma capsulatum and highlight those that lack homologs in humans and that thus could serve as potential targets for the design of antifungal therapies.IMPORTANCE Comprehensive understanding of an organism requires that we understand the contributions of most, if not all, of its genes. Classical genetic approaches to this issue have involved systematic deletion of each gene in the genome, with comprehensive sets of mutants available only for very-well-studied model organisms. We took a different approach, harnessing the power of in vivo transposition coupled with deep sequencing to identify >500,000 different mutations, one per cell, in the prevalent human fungal pathogen Candida albicans and to map their positions across the genome. The transposition approach is efficient and less labor-intensive than classic approaches. Here, we describe the production and analysis (aided by machine learning) of a large collection of mutants and the comprehensive identification of 1,610 C. albicans genes that are essential for growth under standard laboratory conditions. Among these C. albicans essential genes, we identify those that are also essential in two distantly related model yeasts as well as those that are conserved in all four major human fungal pathogens and that are not conserved in the human genome. This list of genes with functions important for the survival of the pathogen provides a good starting point for the development of new antifungal drugs, which are greatly needed because of the emergence of fungal pathogens with elevated resistance and/or tolerance of the currently limited set of available antifungal drugs.