Briefings in Functional Genomics, 15(2), 2016, 85–94 doi: 10.1093/bfgp/elv035 Advance Access Publication Date: 30 September 2015 Review paper

Budding off: bringing functional genomics to Candida albicans Matthew Z. Anderson and Richard J. Bennett Corresponding author: Richard J. Bennett, Department of Microbiology and Immunology, Brown University, Providence, RI 02912, USA. Tel.: (401) 863-6341; Fax: (401) 863-2925; E-mail: [email protected]

Abstract Candida species are the most prevalent human fungal pathogens, with Candida albicans being the most clinically relevant species. Candida albicans resides as a commensal of the human gastrointestinal tract but is a frequent cause of opportunistic mucosal and systemic infections. Investigation of C. albicans virulence has traditionally relied on candidate gene approaches, but recent advances in functional genomics have now facilitated global, unbiased studies of gene function. Such studies include comparative genomics (both between and within Candida species), analysis of total RNA expression, and regulation and delineation of protein–DNA interactions. Additionally, large collections of mutant strains have begun to aid systematic screening of clinically relevant phenotypes. Here, we will highlight the development of functional genomics in C. albicans and discuss the use of these approaches to addressing both commensalism and pathogenesis in this species. Key words: genome plasticity; comparative genomics; transcriptional rewiring; aneuploidy

The human fungal pathogen Candida albicans is a commensal of the gut, mouth and genital tract, but is also capable of causing disease in mucosal niches or spreading to the bloodstream to cause more serious systemic infections [1]. Individuals with compromised immune systems are traditionally those primarily at risk for C. albicans pathogenesis [2–4]. In addition, the increased usage of immunosuppressive drugs, steroids and antibiotics has further amplified the prevalence of C. albicans in the clinic and its importance as a human pathogen [2, 5]. The Candida community has made great strides in defining the biological traits that contribute to both commensalism and virulence. Initial studies established that multiple traits contribute to C. albicans pathogenesis, particularly the ability to switch between yeast and hyphal forms, as well as to sense and adapt to multiple environmental cues [6–8]. To define the genetic determinants that contribute to pathogenicity, functional genomics approaches have been increasingly applied [9–11]. In particular, sequencing and annotation of the standard laboratory strain of C. albicans, SC5314, has greatly advanced the utility of ‘omics’ approaches [9, 12, 13]. In the post-genomic era, numerous techniques ranging from comparative genomics and

transcriptional profiling to construction of a complete gene deletion collection are being used to dissect key traits in C. albicans biology, as will be outlined in this review.

Comparative phylogenetic analysis of C. albicans Molecular typing of Candida species initially relied on DNA fingerprinting to differentiate strain types [14–16]. This method used variations in DNA repeat lengths to define the Candida species and strain subtype [15, 17]. However, variation in fingerprinting methods and loci led to the development of a consensus multi-locus sequence typing (MLST) scheme, in which researchers analyzed the sequences of seven genetically unlinked loci encoding 107 distinct single nucleotide polymorphisms (SNPs) [18, 19]. Subsequent MLST analysis of large numbers of isolates revealed a structured population with most strains falling into 1 of 17 clades [20, 21]. These methods have provided an overview of the phylogenetic relationship among isolates and showed C. albicans to be a largely clonal

Richard Bennett is a Professor in the Department of Molecular Microbiology and Immunology at Brown University. His interests include mechanisms of pathogenesis in human and animal fungal pathogens. Matthew Anderson is a Postdoctoral research associate in the laboratory of Dr. Richard Bennett at Brown University. His interests lie in determining the contributions of natural genomic variation to phenotypic diversity. C The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: [email protected] V

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population [20, 21]. However, MLST karyotyping relied on genetic information at a limited number of loci, which may have obfuscated identification of hybrid strains or introgressed genomic regions resulting from sexual exchange [22]. Sequencing of the C. albicans SC5314 genome established that there are eight diploid chromosomes [12] with extensive heterozygosity between chromosome homologs [23]. A finished draft of the genome [10] identified 6100 open reading frames (ORFs), including several multi-gene families related to pathogenesis. Comparison of gene content among eight Candida species revealed gene family expansions of cell surface transporters, lipases, proteases and genes associated with hyphal formation in C. albicans [9]. Subsequent comparison of C. albicans with its closest known relative, Candida dubliniensis, uncovered expansion of two gene families specifically in C. albicans, that of subtelomeric transcriptional regulators (TLOs) and transmembrane transporters (IFAs) [24]. Taken together, these studies alluded to both previously identified [25, 26] and additional expanded gene families in C. albicans, with potential implications for pathogenesis.

Comparative genomics among C. albicans isolates Comparison of a second sequenced C. albicans isolate, WO-1, with the reference strain, SC5314, revealed the strains to be largely syntenic with relatively few strain-specific genes [9]. To provide a more detailed analysis of genotypic and phenotypic diversity within C. albicans, a recent study [11] sequenced 21 clinical C. albicans isolates representing seven divergent MLST types [19]. The average nucleotide diversity between any two sequenced strains was 0.37%, with 6069 (98.1%) of the genes shared by any two isolates. Among all 21 strains, 461 genes (7.4%) were disrupted in at least 1 strain compared with 57 genes (0.86%) disrupted by nonsense mutations among 71 sequenced Saccharomyces cerevisiae and Saccharomyces paradoxus isolates [27]. Genes with the highest indicators of positive selection encoded cell wall proteins (PGAs), secreted virulence factors (SAP5 and PEP3) and regulators of filamentous growth (FGRs) [11]. The greatest variation in gene copy number was associated with repetitive elements such as the TAR1 gene within the rDNA array and the TLOs in subtelomeric regions. The sequences of the TLO homologs were also highly variable, with novel TLO clades evident that do not resemble those of previously sequenced family members [28]. TLO genes encode a single component of the Mediator transcriptional complex [29], and diversification of these paralogs may indicate specialized roles for different TLOs in modulating Mediator activity. Intraspecies comparisons between C. albicans isolates have also begun to reveal natural polymorphisms that contribute to pathogenesis. One clinical isolate, P94015, encoded a homozygous nonsense mutation in the master transcriptional regulator EFG1 that controls white-opaque switching [30, 31] and filamentation [32]. Loss of EFG1 function in P94015 decreased virulence in a systemic model of infection but enhanced fitness in a model of commensal gut colonization, similar to the phenotypes of efg1D/D mutants in the SC5314 background [33, 34]. Comparative genomics is, therefore, beginning to reveal natural genetic differences that contribute to fitness advantages in specific host niches. Application of whole-genome sequencing to Candida strains undergoing experimental evolution is still in its infancy but is already providing fascinating insights into C. albicans biology.

Engulfment of C. albicans by macrophages normally elicits a filamentation response that ultimately leads to rupture of the phagocyte and release of the ingested cells [35–37]. Transcription factor mutants defective in filamentation were co-cultured with macrophages, leading to an evolved C. albicans lineage that regained the ability to undergo filamentation. Sequencing of the evolved strain identified a single nucleotide mutation in the SSN3 gene, encoding a component of the Mediator complex, which rescued the filamentation response to macrophage internalization and circumvented the missing transcription factors [38]. This study demonstrates how central transcriptional pathways can be readily bypassed by rewiring of existing signaling networks. Genome sequencing of sequential C. albicans isolates recovered from patients undergoing antifungal treatment has established that multiple isolates can be present in a single infection, and that resident strains evolve extensively during the course of antifungal treatment [39]. In particular, loss of heterozygosity (LOH) was often observed in these isolates and was associated with increased drug resistance. Aneuploid forms also frequently arose in the population and, although not directly associated with increased drug resistance, may facilitate strain adaptation by promoting additional genomic changes.

Genomic architecture Genome plasticity is a hallmark feature of C. albicans and other fungal species that can promote adaptation to host or environmental stresses. Although C. albicans is typically isolated as a diploid, it is also capable of propagating in the haploid or tetraploid states [22, 40]. Furthermore, as noted above, aneuploid cells carrying an abnormal complement of chromosomes are frequently found among clinical C. albicans strains [11, 41–43], suggesting they can provide a selective advantage in some host contexts. Indeed, C. albicans exposure to the most frequently administered antifungal fluconazole induces aneuploidy in vitro [44], and resistance in the clinic is associated with an extra isochromosome of chromosome 5 in a subset of strains [42, 43, 45, 46]. This isochromosome encodes the molecular target of fluconazole, ERG11 [47], as well as TAC1, the transcriptional regulator of drug efflux pumps [48], and the increased copy numbers of both of these genes contribute to the increased drug resistance [43, 46]. Comparative genome hybridization (CGH) served as the first genome-wide method to identify whole chromosome and segmental aneuploidy (Figure 1) [49, 50]. The microarrays used for CGH were designed to distinguish 39 000 alleles between SC5314 chromosome homologs based on SNP differences. CGH arrays were used to determine both the chromosome copy number and the allelic composition, the latter allowing the identification of LOH events [49, 51]. LOH occurs frequently in C. albicans [11, 51–53], although less so than in diploid S. cerevisiae strains [54], and often influences clinically relevant phenotypes. For example, loss of a low-activity TAC1 allele and gain of a hyperactive allele increased fluconazole resistance in C. albicans [45, 55]. Studies of C. albicans karyotypes have transitioned to using next-generation sequencing (NGS) to assess chromosome copy number and allelic configuration. NGS offers many advantages over the SNP–CGH approach including: increased genome coverage, greater sensitivity and the ability to assess strains independent of genetic background [11, 39, 56, 57]. Techniques such as restriction-site-associated DNA sequencing (RAD-Seq)

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Figure 1. Methods to detect the genomic architecture of C. albicans strains. Candida albicans karyotyping can be performed via a number of different methods including contour-clamped homogenous electric field (CHEF) electrophoresis, SNP–CGH, RAD-Seq and whole-genome sequencing (WGS). All methods are able to detect aneuploidy, although CHEF electrophoresis is often limited to atypical-sized chromosomes. Resolution has increased with advancements in genome sequencing, which provides the ability to detect allelic ratios from different strain backgrounds. (A colour version of this figure is available online at: http://bfg.oxfordjournals.org)

are also emerging, primarily because they dramatically reduce the cost of karyotyping fungal strains by NGS [58, 59]. This approach was recently applied to identifying relative chromosome copy numbers in C. albicans [60] and, similar to full genome sequencing, requires complementary analysis by DNA staining and flow cytometry to infer overall ploidy [56, 60]. Sequencing methods allow SNP frequencies to define allelic ratios and LOH events [11, 39, 40], and can be performed independently of a reference genome sequence [61]. YMAP, a recently developed informatics pipeline, facilitates this analysis for several C. albicans strain backgrounds by processing sequence reads directly and constructing a visualization of copy number variation and allelic ratios from SNP–CGH or NGS data [62].

Investigation of chromatin structure and transcriptional regulation Epigenetic switches are a critical aspect of C. albicans biology, and yet the chromatin changes that accompany such transitions have not been extensively evaluated. C. albicans modifies histones through acetylation [63–65], methylation [66], phosphorylation [67] and, interestingly, biotinylation [67], but the contribution of specific chromatin marks to gene regulation remains unclear. Nearly all studies to date have investigated chromatin modifications at select loci instead of whole-genome profiling. However, the effects of individual chromatin marks cannot be easily interpreted in isolation, and the entire repertoire of modifications should be considered at any given locus [68]. One of the few examples of genome-wide chromatin mapping is that performed on the C. albicans Set3C histone deacetylase complex [69]. This complex controls the yeastto-hyphal transition by regulating the expression levels of four transcription factors, BRG1, EFG1, NRG1 and TEC1. Chromatin immunoprecipitation and DNA sequencing (ChIP-Seq) showed that the Set3C complex is selectively recruited to the coding sequences of these regulators and downstream target genes, where it modulates their transcription kinetics and thereby controls the yeast-to-hyphal transition [69]. Epigenetic regulation also contributes to another major cell state decision, that of the white-opaque switch. C. albicans cells

can alternate between white and opaque forms, and these two heritable states show marked differences in mating, immune cell interactions and virulence [70, 71]. The master transcription factor regulating the white-opaque transition is Wor1, which ensures stable switching to the opaque state by positive feedback on its own promoter [72–74]. Switching is also regulated by acetylation of the WOR1 promoter; acetylation of histone H3 on lysine 56 (H3K56) by the fungal-specific acetyltransferase Rtt109 promotes stable formation of the opaque state [63]. Interestingly, Rtt109 also functions in protecting cells from genotoxic stresses, including free reactive oxygen species produced by macrophages [64]. However, the molecular targets of Rtt109 that contribute to stress resistance are unknown, and highlight the need for genome-wide studies to assess the function of chromatin marks as part of the ‘histone code’. In contrast to chromatin modifications, the genome-wide binding profiles of multiple C. albicans transcription factors have now been mapped either by chromatin immunoprecipitation and microarray analysis (ChIP-chip) or, more rarely, by ChIPseq. In the case of the white-opaque switch, a network of at least six transcription factors (AHR1, CZF1, EFG1, WOR1, WOR2 and WOR3) controls expression of 748 target genes [30, 75–78]. A detailed analysis of this circuit included ChIP-chip, global transcriptome analysis and mechanically induced trapping of molecular interactions (MITOMI) [75]. The latter technique involves testing the binding of an in vitro translated protein to all possible 8-mer DNA sequences to determine DNA-binding specificity [79, 80]. Using ChIP-chip, the six transcription factors regulating the white-opaque switch were found to bind to a restricted number of genomic regions (72–370), with significant overlap among the binding sites for all six proteins. These transcription factors, therefore, co-regulate target genes, as well as one other, to form a highly connected network of feedback and feedforward loops to establish the two heritable cell states. A similar interlocking network of six transcription factors was shown to regulate biofilm formation in C. albicans [81]. Biofilms are three-dimensional communities of cells surrounded by an extracellular matrix, and play important roles in device-associated infections and drug resistance by C. albicans strains [81, 82]. EFG1 is a central regulator of both the white-opaque circuit and the biofilm circuit, indicating a mechanistic connection between the two programs [83, 84]. Investigation of regulatory circuits such as these is providing

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new insights into the evolution of genetic networks, and reveals that complex networks are not necessarily a consequence of optimization by natural selection, but can instead arise via mostly nonadaptive mutations [85]. Studies in C. albicans have also investigated the mechanisms by which transcription factors can evolve to recognize new sets of target genes. For example, one recent study used ChIP-chip and MITOMI to determine the in vivo binding sites and in vitro DNA-binding specificities of four transcription factors that arose by successive duplications of an ancestral gene [86]. Functional specialization was due to a combination of mechanisms including small changes in intrinsic binding specificities, differences in half-site preferences (e.g. direct versus inverted repeats) and association with different cofactors [86]. These and other studies [87–90] are highlighting how comparative studies between C. albicans and related yeast species are addressing fundamental aspects of transcription circuit evolution.

Transcriptional profiling of C. albicans Custom microarrays were initially used to assay expression of select gene subsets following preliminary characterization of the C. albicans genome [91–93]. Completion of the genome sequence subsequently enabled global analysis of gene expression [94, 95], including the use of high-resolution tiling arrays to assay genome-wide transcription and identify noncoding RNAs and antisense transcripts [96]. Most recent studies of gene expression have used RNA sequencing (RNA-Seq) to obtain greater sensitivity and to reduce bias in assayed gene targets. RNA-Seq studies have identified 600 novel coding and over 1000 noncoding transcripts in C. albicans, many of which are regulated by environment and cell state [97, 98]. Transcriptional profiles have now been defined under a wide variety of conditions both in vitro and in vivo [99–103]. Profiling of unique phenotypic states, including white, opaque, gray and GUT (gastrointestinally induced transition), has been used to define the transcriptional networks regulating these states, and has revealed that these networks resemble those controlling cell fate in metazoans [34, 75, 98, 104]. RNA-Seq has also provided new mechanistic insights into gene regulation in C. albicans. For example, experiments have revealed the widespread presence of antisense transcripts and untranslated regions of varying lengths, dependent both on cell state and environmental conditions [97, 98, 105]. In the case of the white-opaque switch, RNA-Seq analysis of sense–antisense transcript pairs showed a significant anti-correlation, suggesting that many antisense transcripts act to repress their sense counterparts [98]. Antisense transcripts also regulate the yeastto-hyphal switch; the Brg1 transcription factor induces an antisense transcript against the NRG1 sense transcript, thereby targeting the sense transcript for destruction and stimulating hypha-specific gene expression [106]. Candida albicans is a diploid organism, with most strains showing extensive heterozygosity between chromosome homologs. This has enabled analysis of allele-specific expression (ASE) by both RNA-Seq and ribosome profiling [107, 108]. Ribosome profiling provides a quantitative measure of protein translation by determining which messenger RNA transcripts are physically protected from enzymatic digestion by ribosome binding. Experiments revealed differential expression of C. albicans alleles because of biases in both transcriptional and translational regulation of the two alleles. Interestingly, these processes often favored the same allele, thereby exacerbating differences in ASE [107].

To examine the transcriptional response of C. albicans to the host, much effort has focused on the development of in vitro models of the host environment. Interaction with both macrophages and neutrophils has highlighted C. albicans gene expression changes in metabolism, filamentation and protective enzymes for reactive oxygen species and other antimicrobial factors [109–112]. Expression profiling has also been performed using C. albicans cells grown on either reconstituted human oral epithelia or epithelial monolayers [113, 114]. Here, gene transcription reflected the various chronological stages of attachment, hyphal production, cell invasion and tissue destruction [99]. A similarly ordered transcriptional profile was also identified using a murine model of vulvovaginal candidiasis [115, 116]. More recently, RNA-Seq was used to evaluate both C. albicans and host transcriptomes during the interaction between fungal cells and human endothelial or oral epithelial cells [117]. These detailed studies implicated platelet-derived growth factor BB (PDGF BB) and neural precursor-cell-expressed developmentally down-regulated protein 9 (NEDD9) as host factors that promote the uptake of C. albicans cells by host cells. Both host pathways were also implicated in systemic infection, as PDGF-and NEDD9-pathway genes were up-regulated in murine kidneys during disseminated candidiasis [117]. Expression profiling of C. albicans cells during murine systemic infection has been facilitated by microarrays that limit cross-hybridization of host transcripts [100, 118]. Candida albicans genes differentially expressed during renal infection were associated with multiple processes including filamentation, stress response, adhesion and fatty acid metabolism. A subsequent analysis used nanoString to assay expression of 248 C. albicans genes during systemic infection [119]. The nanoString technology relies on the hybridization of RNA transcripts with specific capture and reporter probes; the reporter probe carries a fluorescent bar code for detection, while the capture probe allows the tripartite RNA/probe complex to be immobilized for imaging [120]. This provides for a highly sensitive and specific measure of RNA across a broad range of expression levels. Application of this technique to C. albicans revealed that systemic infection could be divided into early and late responses. The early response correlated with hyphal production and zinc and iron regulation, whereas the late response resembled that of cells grown in the presence of macrophages, including a response to oxidative stress [110]. A similar temporal analysis using microarrays divided C. albicans infections of zebrafish into sequential adhesion, invasion and damage phases [121]. Colonization of the host gastrointestinal (GI) tract by C. albicans has also been analyzed by expression profiling. Cells isolated from the cecum during mouse colonization expressed genes associated with both exponential and post-exponential growth [122]. Interestingly, a subsequent study [123] demonstrated that gene expression of cells in different GI niches (the cecum versus the ileum) varied as much from each other as they did from in vitro conditions. Furthermore, cells from both sites expressed hyphal-associated genes, despite growing exclusively in the yeast form [122, 123]. Taken together, these data suggest the GI tract includes diverse microenvironments that C. albicans is able to recognize and adapt to. A constant improvement in bioinformatic tools for C. albicans has provided methods for examining these large data sets. The Candida Genome Database (CGD; candidagenome.org) has played a key role in providing diverse tools for the study of C. albicans and related Candida pathogens. For example, CGD implemented Gene Ontology (GO) assignments to genes as well as tools to identify overrepresented GO terms on user-defined

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sets of gene IDs [124]. Furthermore, expression patterns associated with genes involved in known processes have provided functional assignment of novel regulators to critical processes such as hypoxia [125], drug resistance [126] and filamentation [127]. Network analysis has allowed integration of both temporal expression data and transcription factor binding data to construct complex models of transcriptional regulation during the hypoxic response [125]. As the number of data sets increases and the complexity of the systems multiply, new programs must weigh the ability of these models to accurately depict transcriptional effects [128–130]. Progressively, integration of previously published expression data sets is informing our understanding of C. albicans transcriptional networks to create more robust and dynamic models of regulation [75, 125].

Construction of systematic strain collections Genetic analysis of C. albicans is complicated by an altered genetic code (translation of the CTG codon as serine instead of leucine) [131], the lack of a conventional sexual cycle [132] and the requirement for two rounds of disruption to make homozygous deletion mutants. Despite these constraints, concerted efforts from multiple labs have generated large strain collections of mutants for high-throughput screening (Table 1). One of the first C. albicans deletion libraries used a transposonmediated strategy involving a Tn7-UAU1 vector system. This method was used to construct 217 homozygous deletion strains [133], and identified a key regulator of alkaline-dependent filamentation [134]. This technique was subsequently used in targeted gene disruptions [135, 136] and additional deletion libraries [137–140]. A separate approach relied on the generation of heterozygous mutants by insertional mutagenesis with a URA3-marked transposon into the genome [141]. Subsequently, a heterozygous mutant library of 3633 unique strains was constructed that allowed easier identification of the disrupted locus and facilitated pooling experiments by bar coding each heterozygous mutant [142]. A further development was a library in which one allele was deleted and the second was placed under the control of a tetracycline-repressible promoter [143]. This library, known as the gene replacement and controlled expression (GRACE) collection, includes 2356 genes and has proven useful in assessing conditional lethality [143], functional conservation between S. cerevisiae and C. albicans genes [142], chemical genetic approaches for novel therapeutics [144] and gene function [145]. However, leaky gene expression at some

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loci can complicate analysis [143] and argues for the use of complementary approaches to define function. A systematic approach to constructing a large, signaturetagged deletion collection was undertaken and comprised strains for 674 individually deleted genes [146]. Phenotyping of these strains identified 115 gene deletions with significant defects in virulence in a murine systemic model, 133 gene deletions with defects in filamentation in vitro and 68 mutants with defects in doubling times at 37 C [146]. Significant correlations existed between virulence and filamentation, but not between virulence and growth rates. Related work analyzed the function of 143 C. albicans transcription factors using a gene deletion collection [147], as well as the function of many of these transcription factors in GI colonization [148]. Currently, there are ongoing efforts to construct a C. albicans ORFeome containing a gene deletion library for all 6200 ORFs in the SC5314 genome [149], which will provide a powerful resource for genetic studies upon its release. Genetic redundancy and epistasis can often mask the effects of gene deletion on a given phenotype. Overexpression of candidate genes can therefore be used to complement studies of gene disruption [150]. A number of regulatable promoters have been developed to regulate gene expression, including the MET3 promoter [151], the MAL2 promoter [152] and tetracyclineregulated promoters (Tet-OFF and Tet-ON) [153, 154]. A library of overexpression strains was constructed in a Tet-ON system for 107 putative transcription factors, most with a known biological role [155]. Exploration of novel functions among these defined regulators identified a role for TEC1 and GAT2 in biofilm formation [155, 156]. An alternative overexpression strategy fused the Gal4 activation domain [157] to the C-terminus of 82 zinc cluster transcription factors to construct hyperactive forms of the fusion proteins [158]. The C. albicans ORFeome project is concurrently building an overexpression library for all 6200 genes under the control of the Tet-ON or PCK1 promoters [159, 160]. Future efforts in genome engineering will be greatly facilitated by the recent development of CRISPR/Cas9 for C. albicans, which allows efficient and rapid editing of individual genes and even gene families in the diploid organism [161].

Conclusions Functional genomics has provided profound insights into C. albicans pathogenesis. Fortuitously, increased access to these technologies, reduced costs and more comprehensive methods to analyze the resulting data are expected to translate to

Table 1. Mutant libraries constructed in C. albicans Library

Method

Number of mutants

Number of loci affected

Number of alleles affected

Essential genes

Davis et al. (2002) [134], Noble and Mitchell (2005) [138] and Blankenship et al. (2010) [139] Uhl et al. (2003) [141] Roemer et al. (2003) [143] Homann et al. (2009) [147] Sahni et al. (2010) [155] Oh et al. (2010) [142] Noble et al. (2010) [146] Chauvel et al. (2012) [159]

UAU method (transposon)

2000

380

Both

No

Insertional (transposon) Het. deletion and ptet replacement Targeted disruption ptet overexpression Insertional (transposon) Targeted disruption ptet overexpression/ pPCK1 overexpression ptet overexpression

18 000 2304 365 107 21 468 3000 768

Unknown 1152 166 107 3633 674 384

One Both Both One One Both One

Yes Yes No Yes Yes No Yes

82

82

One

Possibly

Schillig and Morschauser (2013) [158]

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increased usage of these approaches. Many of the most enlightening discoveries in C. albicans have combined multiple approaches to address a biological question. Combinatorial approaches will continue to require advancements in analysis and tool development and standardization of technique methodologies, as has occurred with other systems [162–164]. These measures will aid the increasing rate of discovery in Candida biology and ensure consistency between researchers in this rapidly emerging field.

Key Points

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• Comparative genomics provides evidence of selective

expansion of gene families in C. albicans, as well as rapid evolution of gene products involved in host interactions. • Use of whole-genome approaches such as ChIP-chip and RNA-Seq has proven instrumental in revealing the regulatory architecture of key biological processes such as cell state switching. • Development of multiple strain deletion libraries has provided powerful genetic tools for dissection of gene functions.

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Acknowledgements The authors would like to thank Iuliana Ene and Emily Mallick for comments on the article. We would like to pay special attention to the contributions of the Stanford Genome Technology Center in the original effort to sequence C. albicans, the Broad Institute in sequencing multiple Candida species and addressing genomic diversity within C. albicans and the Candida Genome Database (CGD) for the construction and maintenance of an invaluable resource to the Candida community for investigation and annotation of the C. albicans genome.

Funding This work was supported by NIH grants AI081704 and AI12363 (to R.J.B.), by the Burroughs Wellcome Fund (Investigator in Pathogenesis of Infectious Disease award to R.J.B.) and a NIH Research Supplement to Promote Diversity in Health-Related Research AI081704-S1 (to M.Z.A.).

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