The SAGA and NuA4 component Tra1 regulates Candida albicans drug resistance and pathogenesis.

Candida albicans is the most common cause of death from fungal infections. The emergence of resistant strains reducing the efficacy of first-line therapy with echinocandins, such as caspofungin calls for the identification of alternative therapeutic strategies. Tra1 is an essential component of the SAGA and NuA4 transcriptional co-activator complexes. As a PIKK family member, Tra1 is characterized by a C-terminal phosphoinositide 3-kinase domain. In Saccharomyces cerevisiae, the assembly and function of SAGA and NuA4 are compromised by a Tra1 variant (Tra1Q3) with three arginine residues in the putative ATP-binding cleft changed to glutamine. Whole transcriptome analysis of the S. cerevisiae tra1Q3 strain highlights Tra1's role in global transcription, stress response, and cell wall integrity. As a result, tra1Q3 increases susceptibility to multiple stressors, including caspofungin. Moreover, the same tra1Q3 allele in the pathogenic yeast C. albicans causes similar phenotypes, suggesting that Tra1 broadly mediates the antifungal response across yeast species. Transcriptional profiling in C. albicans identified 68 genes that were differentially expressed when the tra1Q3 strain was treated with caspofungin, as compared to gene expression changes induced by either tra1Q3 or caspofungin alone. Included in this set were genes involved in cell wall maintenance, adhesion, and filamentous growth. Indeed, the tra1Q3 allele reduces filamentation and other pathogenesis traits in C. albicans. Thus, Tra1 emerges as a promising therapeutic target for fungal infections.

A data library of Candida albicans functional genomic screens.

Functional genomic screening of genetic mutant libraries enables the characterization of gene function in diverse organisms. For the fungal pathogen Candida albicans, several genetic mutant libraries have been generated and screened for diverse phenotypes, including tolerance to environmental stressors and antifungal drugs, and pathogenic traits such as cellular morphogenesis, biofilm formation and host-pathogen interactions. Here, we compile and organize C. albicans functional genomic screening data from ∼400 screens, to generate a data library of genetic mutant strains analyzed under diverse conditions. For quantitative screening data, we normalized these results to enable quantitative and comparative analysis of different genes across different phenotypes. Together, this provides a unique C. albicans genetic database, summarizing abundant phenotypic data from functional genomic screens in this critical fungal pathogen.

Genetic interaction analysis in microbial pathogens: unravelling networks of pathogenesis, antimicrobial susceptibility and host interactions.

Genetic interaction (GI) analysis is a powerful genetic strategy that analyzes the fitness and phenotypes of single- and double-gene mutant cells in order to dissect the epistatic interactions between genes, categorize genes into biological pathways, and characterize genes of unknown function. GI analysis has been extensively employed in model organisms for foundational, systems-level assessment of the epistatic interactions between genes. More recently, GI analysis has been applied to microbial pathogens and has been instrumental for the study of clinically important infectious organisms. Here, we review recent advances in systems-level GI analysis of diverse microbial pathogens, including bacterial and fungal species. We focus on important applications of GI analysis across pathogens, including GI analysis as a means to decipher complex genetic networks regulating microbial virulence, antimicrobial drug resistance and host-pathogen dynamics, and GI analysis as an approach to uncover novel targets for combination antimicrobial therapeutics. Together, this review bridges our understanding of GI analysis and complex genetic networks, with applications to diverse microbial pathogens, to further our understanding of virulence, the use of antimicrobial therapeutics and host-pathogen interactions. .

Author Correction: Design, execution, and analysis of CRISPR-Cas9-based deletions and genetic interaction networks in the fungal pathogen Candida albicans.

The version of this paper originally published contained reference errors. The sentence "To dissect complex genetic interactions in C. albicans, a CRISPR-Cas9-based Gene Drive Array (GDA) was developed" incorrectly cited ref. 13, and should have cited ref. 14. In addition, the reference included as ref. 13 in the original paper was incorrect, and should have been the following: Shapiro, R. S., Chavez, A. & Collins, J. J. CRISPR-based genomic tools for the manipulation of genetically intractable microorganisms. Nat. Rev. Microbiol. 16, 333-339 (2018). This reference should have been cited after the sentence "Recent innovations in CRISPR-Cas9-based genome editing have facilitated such genetic interaction analyses." The original reference 13 (Gerami-Nejad, M., Zacchi, L. F., McClellan, M., Matter, K. & Berman, J. Shuttle vectors for facile gap repair cloning and integration into a neutral locus in Candida albicans. Microbiology 159, 565-579 (2013)) should have been cited later in the paper, and is now in the reference list as ref. 27. As a result, original references 27-33 have been renumbered in the reference list and in the text. These changes have been made in the PDF and HTML versions of the protocol.

Design, execution, and analysis of CRISPR-Cas9-based deletions and genetic interaction networks in the fungal pathogen Candida albicans.

The study of fungal pathogens is of immediate importance, yet progress is hindered by the technical challenges of genetic manipulation. For Candida species, their inability to maintain plasmids, unusual codon usage, and inefficient homologous recombination are among the obstacles limiting efficient genetic manipulation. New advances in genomic biotechnologies-particularly CRISPR-based tools-have revolutionized genome editing for many fungal species. Here, we present a protocol for CRISPR-Cas9-based manipulation in Candida albicans using a modified gene-drive-based strategy that takes ~1 month to complete. We detail the generation of Candida-optimized Cas9-based plasmids for gene deletion, an efficient transformation protocol using C. albicans haploids, and an optimized mating strategy to generate homozygous single- and double-gene diploid mutants. We further describe protocols for quantifying cell growth and analysis pipelines to calculate fitness and genetic interaction scores for genetic mutants. This protocol overcomes previous limitations associated with genetic manipulation in C. albicans and advances researchers' ability to perform genetic analysis in this pathogen; the protocol also has broad applicability to other mating-competent microorganisms.