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Eukaryotic Cell, April 2006, p. 638-649, Vol. 5, No. 4
1535-9778/06/$08.00+0     doi:10.1128/EC.5.4.638-649.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.

Conserved Fungal Genes as Potential Targets for Broad-Spectrum Antifungal Drug Discovery{dagger}

Mengping Liu,1 Matthew D. Healy,2 Brian A. Dougherty,2 Kim M. Esposito,3 Trina C. Maurice,1 Charles E. Mazzucco,1 Robert E. Bruccoleri,2 Daniel B. Davison,2 Marybeth Frosco,1 John F. Barrett,1 and Ying-Kai Wang1*

Departments of Infectious Diseases,1 Applied Genomics,2 Lead Discovery, Bristol-Myers Squibb Company Pharmaceutical Research Institute, 5 Research Parkway, Wallingford, Connecticut 064923

Received 2 December 2005/ Accepted 26 January 2006


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ABSTRACT
 
The discovery of novel classes of antifungal drugs depends to a certain extent on the identification of new, unexplored targets that are essential for growth of fungal pathogens. Likewise, the broad-spectrum capacity of future antifungals requires the target gene(s) to be conserved among key fungal pathogens. Using a genome comparison (or concordance) tool, we identified 240 conserved genes as candidates for potential antifungal targets in 10 fungal genomes. To facilitate the identification of essential genes in Candida albicans, we developed a repressible C. albicans MET3 (CaMET3) promoter system capable of evaluating gene essentiality on a genome-wide scale. The CaMET3 promoter was found to be highly amenable to controlled gene expression, a prerequisite for use in target-based whole-cell screening. When the expression of the known antifungal target C. albicans ERG1 was reduced via down-regulation of the CaMET3 promoter, the CaERG1 conditional mutant strain became hypersensitive, specifically to its inhibitor, terbinafine. Furthermore, parallel screening against a small compound library using the CaERG1 conditional mutant under normal and repressed conditions uncovered several hypersensitive compound hits. This work therefore demonstrates a streamlined process for proceeding from selection and validation of candidate antifungal targets to screening for specific inhibitors.


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INTRODUCTION
 
Candidiasis, aspergillosis, and cryptococcosis are the leading invasive fungal infections that cause substantial morbidity and mortality in nosocomial settings and among immunocompromised patients (51). Candida species are considered the fourth most common bloodstream isolates in the United States (15). For many years, amphotericin B and fluconazole have been the standard of therapy for treatment of severe fungal infections (13). However, serious side effects such as nephrotoxicity are associated with amphotericin B, while fluconazole suffers from such drawbacks as frequent interactions with coadministered drugs, limited spectrum (for example, it is not effective against aspergillosis), and the increasing emergence of fluconazole-resistant Candida species (for example, Candida krusei and some strains of Candida glabrata) (9, 13, 20). Encouragingly, several new drugs have recently been approved by the U.S. Food and Drug Administration, including voriconazole, caspofungin, and micafungin. Like the other two triazoles (posaconazole and ravuconazole) that are in development, voriconazole displays a broader antifungal spectrum, including Aspergillus strains and resistant Candida species (25, 30). Caspofungin and micafungin represent the first new class (the echinocandin lipopeptides) of antifungal agents approved after several decades of intensive research (2, 28, 56).

In spite of these recent advances, the currently marketed antifungals and those in development represent only three major chemical classes (polyenes, azoles, and echinocandins) and target only two cellular structures (the cell membrane and the cell wall) (49). Therefore, there is a critical need for new classes of broad-spectrum antifungals that bind to novel targets. Microbial genomics offer an unprecedented opportunity to enlarge the repertoire of antimicrobial compounds with the identification of genes that encode potential new targets for chemotherapy. To date, more than 10 fungal genomes have been sequenced (http://ncbi.nih.gov/RefSeq/ [accessed August 2005]), including those of Saccharomyces cerevisiae, Candida albicans, C. glabrata, Aspergillus fumigatus, Cryptococcus neoformans, Debaryomyces hansenii, Kluyveromyces lactis, Schizosaccharomyces pombe, Yarrowia lipolitica, and Eremothecium gossypii. It is expected that tremendous interest and effort will be devoted to the identification of essential genes as potential drug targets from key fungal pathogens. While hundreds of essential genes have been identified in S. cerevisiae (55) and C. albicans (11, 44, 55), target prioritization in terms of, for example, degree of essentiality, broad-spectrum potential, drug target potential, fungal specificity, availability of functional assays, and amenability to high-throughput screening (HTS) would likely present a much greater challenge to the research community.

Recognizing the ever-increasing demands for broad-spectrum antifungals, we sought to identify potential antifungal targets that are conserved among the 10 fungal species mentioned above and to develop a system to identify target-specific inhibitors. To this end, we identified 240 conserved genes among the 10 fungi via the genome comparison tool, determined essentiality of selected genes in C. albicans using a repressible C. albicans MET3 (CaMET3) promoter, and adapted the CaMET3 promoter system to a target-based whole-cell HTS platform.


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MATERIALS AND METHODS
 
Bioinformatics. The completed genome sequences were acquired from the NCBI Reference Sequence database (http://ncbi.nih.gov/RefSeq/) for the following 10 fungal and human strains: S. cerevisiae S288c (5,866 open reading frames [ORFs]), C. albicans SC5314 (13,685 ORFs), C. glabrata CBS138 (5,192 ORFs), A. fumigatus Af293 (9,907 ORFs), Cryptococcus neoformans JEC21 (6,593 ORFs), D. hansenii CBS767 (6,317 ORFs), K. lactis NRRL Y-1140 (5,336 ORFs), Schizosaccharomyces pombe 972 h– (5,035 ORFs), Y. lipolitica CLIB99 (6,544 ORFs), Eremothecium gossypii ATCC 10895 (4,718 ORFs), and Homo sapiens (29,236 ORFs). Other sources of genome sequence and annotation data include Genome Therapeutics Corporation, Waltham, MA, The Institute for Genomic Research (http://www.tigr.org), the Yeast Proteome Database (YPD) (http://www.proteome.com/), and Incyte Pharmaceuticals, Palo Alto, CA. Where incomplete genome sequences were encountered, coverage was increased by adding contiguous sequences for the same organism from multiple public and/or private sources and assembling the data using the PHRAP algorithm (http://www.phrap.org/). Likely genes that were not yet annotated in available yet incomplete genomes were identified using the program CRITICA (4), and MAGPIE (17) was used to visualize genes in context. Similar genes were identified using the "neighbors" function of the concordance system (7). To determine if the predicted gene sequences were full length and of the proper reading frame for incomplete genomes, both BLAST searches and CLUSTAL multiple sequence alignments (1, 26) were conducted.

To identify conserved genes, whole-genome comparisons based on all-versus-all pairwise alignments with the FASTA algorithm (41) were conducted using the concordance function essentially as described previously (7). Briefly, all ORFs (>100 amino acids) of the query genome were compared to ORFs from various other genomes and stored. A list of ORFs and their associated amino acid sequences was then generated at a specified percent protein identity cutoff. When a gene of interest was not found in a genome, FRAMESEARCH (24) was used to determine that it was not due to a failure of the gene-finding algorithm.

Strains and growth media. The C. albicans strains used were SC5314 (wild type; Bristol-Myers Squibb Culture Collection) and its derivative, BWP17 (ura3{Delta}::{lambda}imm434/ura3{Delta}::{lambda}imm434 his1::hisG/his1::hisG arg4::hisG/arg4::hisG), kindly provided by A. P. Mitchell of Columbia University. The S. cerevisiae strain used was ATCC 201390 (MATa/MAT{alpha} his3{Delta}1/his3{Delta}1 leu2{Delta}0/leu2{Delta}1 lys2{Delta}0/LYS2 met15{Delta}0/MET15 ura3{Delta}0/ura30). Escherichia coli strain DH5{alpha} was used for plasmid propagation. Yeast extract-Bacto peptone-dextrose medium (YEPD), synthetic complete (SC) medium, and synthetic dextrose (SD) were prepared according to standard procedures as previously described (46). Uridine (25 µg ml–1) was added according to a method described previously by Fonzi and Irwin (16), and other supplements such as histidine and arginine (20 µg ml–1) were added as described previously (46). In general, 5 mM of methionine and 2.5 mM of cysteine were used in media unless otherwise indicated. Both S. cerevisiae and C. albicans strains were grown at 30°C, and the E. coli strain was grown at 37°C.

DNA manipulations. DNA manipulations were carried out according to standard molecular methods (45) unless otherwise noted. Typical PCRs were carried out in a volume of 100 µl with an initial 2-min jump start at 95°C, 30 cycles of amplification (2 min at 95°C, 1 min at 52°C, and 5 min at 72°C), and a final 10-min extension step at 72°C. Typical reaction mixtures contained 10 mM Tris-HCl, pH 8.3, 1.5 mM MgCl2, 50 mM KCl, 0.2 mM deoxynucleoside triphosphates, 10 pmol of primers, 100 ng of genomic template DNA, and 5 U of Taq DNA polymerase (Gibco-BRL) or Pfu Turbo DNA polymerase (Stratagene). Total genomic DNA from C. albicans was isolated by the glass bead lysis method (27). All PCR primers used in this study are listed in Table S1 in the supplemental material.

Transformation of C. albicans was carried out as described previously (54). Typically, about 20 to 80 µl of the PCR mixture was used for transformation. For disrupting the first allele of a target gene, cells were plated onto selective medium (SC minus uridine or SC minus arginine), while the second round of transformation to disrupt the second allele used SC minus uridine and arginine medium.

Construction of C. albicans MET3 promoter-swapping cassettes. Two plasmids, pUMP and pAMP, which contain a CaMET3 promoter cassette, were constructed. Plasmid pUMP contains the CaURA3 gene, and pAMP harbors CaARG4 as the selective marker. The 1.4-kb C. albicans MET3 promoter region was amplified by PCR from genomic DNA of strain SC5314. To construct pUMP, the CaMET3 promoter PCR product was cut with restriction enzymes SphI and NcoI, gel purified, and ligated into pGEM-URA3 that was linearized by SphI and NcoI. This placed the CaMET3 promoter sequence adjacent to CaURA3 but in the opposite orientation to avoid transcription read-through. To construct pAMP, the C. albicans ARG4 gene was excised from pRS-ARG4{Delta}SpeI after digestion with SacI and KpnI (blunt ended) and ligated into the SacII (blunt ended) and SacI sites of pGEM-URA3 to replace CaURA3. The resulting plasmid was linearized with SphI and NcoI, gel purified, and ligated with the CaMET3 promoter PCR product treated with SphI and NcoI, yielding plasmid pAMP.

Construction of conditional mutants. Two steps were involved in constructing conditional mutants of C. albicans. The first step was the disruption of the first allele of the gene of interest by the PCR-based gene disruption method (54) in strain BWP17, with subsequent verification by PCR analysis. Next, the promoter of the second copy of the gene was replaced by the CaMET3 promoter in the heterozygous strain. To do this, the CaMET3 promoter-swapping cassette was amplified by PCR from plasmid pUMP or pAMP. The PCR primers used contained both template-specific common primer sequences and gene-specific flanking sequences of 50 to 60 bp in length. The common primer sequences annealed to the plasmid template pUMP or pAMP for amplification of the promoter-swapping cassette, whereas the flanking sequences directed the amplified promoter cassette fragment to its specific location on the chromosome during recombination. The resulting PCR product of the CaMET3 promoter-swapping cassette was then introduced into the cells that were heterozygous for the gene of the interest to replace the endogenous promoter of the remaining allele via homologous recombination. Typically, between 500- to 1,000-bp nucleotides upstream of the ATG codon of the gene of interest were removed, and promoter constructs were verified by PCR.

Cell-based high-throughput screening. C. albicans conditional mutants harboring the gene of interest under the control of the CaMET3 promoter were used for screening of target-specific inhibitors in the absence and presence of methionine or cysteine. To carry out HTS, a culture grown overnight was diluted in SD plus His broth medium to 7.5 x 105 CFU/ml, 35 µl of which was dispensed into wells of 384-well plates containing 8 µl of compounds in each well. Ten microliters of SD plus His broth containing or lacking methionine or cysteine was added to these wells. The final compound concentration at screening was 14.2 µM. The concentration of methionine or cysteine used was the 50% inhibitory concentration (IC50) value previously determined, such that cells would proliferate at half the growth rate compared to no-methionine or cysteine control cultures. The plates were then incubated at 30°C for 18 h, and cell growth was determined by reading the absorbance at 590 nm on a Perkin-Elmer 7000 plate reader. Cell growth inhibition was calculated by using plain medium as a "blank" and cells grown in medium with dimethyl sulfoxide only as the "total." To determine dose responses, the compound concentration that causes 50% growth inhibition (IC50) was calculated using the following two-parameter logistic equation: Y = 100/[1 + (IC50/I)H], where Y is the percent growth inhibition, I is the inhibitor concentration, and H is the hill slope, as described by GraphPad Software Inc. (San Diego, CA).


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RESULTS
 
Identification of conserved fungal genes via concordance analysis. It is generally believed in the antimicrobial drug discovery community that conserved, essential genes have great potential to yield broad-spectrum antimicrobial agents. Using the 1,049 essential S. cerevisiae genes (http://www.yeastgenome.org) as a query, we conducted a pairwise genome comparison or concordance analysis across the nine other complete fungal genomes in an effort to identify genes that are conserved across those fungi (see Materials and Methods for details). To determine a legitimate cutoff for gene conservation, we profiled a list of known fungal "drug-able" targets against the 10 fungal genomes. This allowed us to quantitatively correlate the broad-spectrum capacity of the currently marketed drugs to the percent protein identity of their corresponding drug targets. Voriconazole (VFend) and caspofungin (Cancidas) are considered to have broad-spectrum capacity against a number of medically important fungi, including Candida species and Aspergillus species (30, 34). Voriconazole targets lanosterol 14-{alpha}-demethylase, encoded by the essential gene ERG11 in the yeast S. cerevisiae (50). The target of caspofungin is an essential cell wall enzyme, ß-1,3-glucan synthase, encoded by FKS1 and FKS2 and regulated by RHO1 in S. cerevisiae (35, 36). The putative homologs of all four genes were identified in the 10 fungal genomes with protein sequence identity of more than 40% for Erg11p and more than 50% for each of the three gene products for glucan synthase (Table 1). In vitro, terbinafine (Lamisil) has an inhibitory activity against many strains of Candida species, Aspergillus species, and Cryptococcus neoformans (although it is only marketed for the treatment of foot fungus) (31), and its target, squalene epoxidase (Erg1p), was found to be conserved at ≥39% across the 10 fungi (Table 1). In addition, four other known fungal targets, CHS2, RAM2, NMT1, and EFT2, which are the subject of preclinical research but lack a marketed drug, were also compared side by side across the 10 fungal genomes and were found to be conserved at 30% or higher at the protein level (Table 1). Based on the above-described data, we set the benchmark in our search for conserved genes across the fungal genomes to ≥40% identity at protein level.


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  		TABLE 1. Homology comparison of known antifungal targets

A total of 240 genes, denoted conserved fungal genes, were identified with percent identity at ≥40% at the protein level using the 1,049 essential S. cerevisiae genes as a query (see Table S2 in the supplemental material). To view the distribution of those genes by function, we assigned them to the functional and cellular categories described by the YPD (http://www.proteome.com) for S. cerevisiae (Table 2). It was found that the 240 conserved fungal genes encode proteins involved in all 39 cellular processes categorized by the YPD. As shown in Table 2, the top four cellular processes to which the conserved fungal genes were assigned are protein synthesis (13%), RNA processing modification (10%), protein degradation (7%), and polymerase II (Pol II) transcription (5%), the basic, evolutionarily conserved cellular processes. It is interesting that there are 3% of the conserved fungal genes whose biological functions were unknown in S. cerevisiae according to the Saccharomyces Genome Database (SGD) (http://www.yeastgenome.org [accessed October 2005]).


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  		TABLE 2. Functional distribution of the 240 conserved fungal genes identified

The preferred profile for fungal targets are essential proteins conserved among fungi yet absent from the human genome so as to minimize potential toxic side effects exerted by pharmacological inhibition of the cellular targets. With this ideal in mind, the 240 conserved fungal genes were prioritized based on their relatedness to human genes (Fig. 1A). Interestingly, more than half (59%) of the conserved fungal genes have putative human homologs with percent identities ranging from 41 to 60%, whereas each of those having the least (0 to 40%) and most (61 to 100%) identity with human genes constitutes around 20% of the conserved fungal genes identified. When the essential yeast gene set (1,049 genes) as well as the entire yeast gene set (5,866 genes) were compared with the human genome, it was found that the majority of the yeast genes (~76% for the essential gene set and ~88% for whole gene set) do not have significant human homologs (>40% protein identity) (Fig. 1B; data shown for human homologs of the entire yeast gene set only). Similar findings were also made when each of the remaining nine fungal genomes was compared with the human genome, in which between 85 to 93% of the fungal genes for any one organism were found to be unique to fungi (data not shown). This indicates that most (~80%) of the 240 conserved fungal genes identified here come from only 7 to 15% of each fungal genome that is also conserved in the human genome, which at least partly explains the difficulty in developing safe and selective antifungal drugs.


Figure 1
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  		FIG. 1. (A) Illustration of identifiable human homologs of the 240 conserved fungal genes (FCGs) as percent protein identity, with the lower left corner showing the least homology and upper right corner showing the most homology. (B) Human homologs of the genes (5,866) of S. cerevisiae plotted as percent protein identity.

Development of a CaMET3 promoter system for essential gene identification in C. albicans. Although the aforementioned conserved fungal genes are essential in S. cerevisiae, it is necessary to verify their essentiality in the remaining fungi, especially in the pathogenic fungi, in order for them to be considered antifungal targets. Towards this goal, we developed a CaMET3 promoter system capable of large-scale identification of essential genes in the primary fungal pathogen C. albicans. In this system, a conditional mutant where one allele of the gene of interest was disrupted by the PCR-based gene disruption technique (54) and the second allele was placed under the control of the CaMET3 promoter (see Fig. 2A for a schematic illustration of the promoter-swapping approach) was constructed. Homologous recombinations were verified by PCR confirmation analysis using various primer sets (Fig. 2B). Gene essentiality was determined by comparing phenotypes of serially diluted conditional mutants grown on SD agar plates in the absence and presence of methionine and cysteine (Fig. 2C). Scores of 1 to 4 were used to assess the degree of essentiality, with 1 being absolutely required and 4 being not required for cell growth. As expected, three known essential C. albicans genes (CaERG1, CaRAM2, and CaNMT1) were determined to be essential in this work, with scores of 1, 3, and 1, respectively (Fig. 2C). However, CaPFY1, whose essentiality is strain dependent in S. cerevisiae, was found to be not essential in C. albicans (Fig. 2C). It is important that no growth defect by methionine and/or cysteine was observed for any heterozygous parental strains tested (Fig. 2C; data shown for a representative heterozygous strain).


Figure 2
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  		FIG. 2. Construction of C. albicans conditional mutants by using the CaMET3 promoter-swapping cassette. (A) Scheme of promoter swapping in which the PCR-amplified CaMET3 promoter-swapping cassette is transformed to a heterozygous YFG1 strain, replacing the endogenous promoter of the second allele via homologous recombination. Primer sets used for confirmation PCR are shown as arrows and are as follows: 5' promoter/3' PTURA, 5' PTURA/3' promoter, and 5' gene/3' gene. (B) Verification of CaMET3 promoter conditional mutants of the CaERG1 gene, as an example, by PCR confirmation analysis. Lanes labeled "M" contain 1-kb DNA. Lanes 1 and 2 depict examples of wrong constructs, whereas lanes 3 and 4 are examples of correct conditional mutant constructs. The expected sizes of PCR products using the primer sets 5' PTURA/3' promoter, 5' promoter/3' PTURA, and 5' gene/3' gene are 1.6 kb, 1.2 kb, and 2.4 kb, respectively. (C) Growth phenotypes of various CaMET3 promoter conditional mutants grown on SD plus histidine medium (SD plus histidine plus uridine for the CaERG1/Caerg1::ARG4 mutant used as a growth control) in the absence (–) or presence (+) of 5 mM of methionine and 2.5 mM of cysteine after incubation for 2 days at 30°C. Cells were serially diluted (1 to 10) starting at 2 x 106 CFU/ml for the first dilution, and 5 µl of the dilution was spotted from left to right. An arbitrary score of 1, 2, 3, or 4 was assigned to a specific conditional mutant corresponding to its degree of growth defect in SD plus methionine and cysteine, with 1 being most essential and 4 being nonessential.

We previously identified a list of conserved genes between S. cerevisiae and C. albicans using the S. cerevisiae essential gene set (52). A dozen genes with no known biological function (denoted conserved unknown reading frames [CURFs]) were selected in this work to evaluate their essentiality in C. albicans with the hope of identifying novel, broad-spectrum antifungals (Table 3). Each of the 12 CURFs was evaluated by the CaMET3 promoter system, and 10 were determined to be essential in C. albicans (Table 3 and Fig. 2C). To corroborate the essentiality results obtained by the CaMET3 promoter method, all genes tested (known or unknown) were independently evaluated for essentiality by the PCR-based gene disruption method (54). Comparable results were obtained between the two methodologies for all genes except CaYJR072c, which was deemed to be not essential by the CaMET3 promoter method, yet the disruption method failed to obtain the disruption of both alleles (data not shown).


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  		TABLE 3. Properties of fungal genes of unknown function identified in this work

Characterization of the CaMET3 promoter for HTS amenability. It has previously been reported that both bacterial and fungal cells can become hypersensitive to specific inhibitors when the target molecule is rate limiting for cell growth by either using heterozygous strains (11, 21) or using regulatable (either repressible/or inducible) promoters (12, 44). To assess the utility of CaMET3 promoter in this regard, all 13 essential genes (3 known genes and 10 CURFs) identified in this work were individually assessed for repression of growth via controlled expression of the CaMET3 promoter by the addition of methionine or cysteine. A variety of conditions such as inoculum size, methionine or cysteine concentration, and incubation time were explored. Figure 3 shows growth curves of two representative conditional mutants and of the parental BWP17 strain using various concentrations of either methionine or cysteine, demonstrating that the CaMET3 promoter could be titrated by either methionine (for example, CaYDR341c) or cysteine (for example, CaYDR341c and CaNMT1), while neither methionine nor cysteine caused any significant growth defect on the parental BWP17 strain at concentrations up to 5 mM. To assist HTS, the concentration of either methionine or cysteine that inhibits 50% of the cell growth (IC50), was determined for each of the 13 conditional mutants tested (Table 4). As discussed below, the IC50 was the concentration arbitrarily chosen and used to set cells that were rate limiting in growth in the cell-based HTS to identify hypersensitive inhibitors. We found that cysteine alone was capable of repressing all 13 essential genes tested, while methionine was only able to repress 3 (CaYDR341c, CaYOL077c, and CaERG1) at up to 10 mM (Fig. 3 and Table 4).


Figure 3
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  		FIG. 3. Growth curves of different C. albicans strains in media containing or lacking methionine or cysteine. (A to D) Two conditional mutants harboring genes of CaYDR341c and CaNMT1, respectively, in SD plus histidine broth containing methionine (A and C) or cysteine (B and D). (E and F) Growth of the parental control strain BWP17 in YEPD broth containing methionine (E) or cysteine (F). A culture grown overnight was inoculated with an inoculum of 1 x 106 CFU/ml on a 96-well plate containing 200 µl of broth medium with various concentrations (millimolar) of methionine or cysteine as indicated. The plate was incubated at 30°C, and cell growth was monitored by reading the optical density at 600 nm (OD600) at the indicated time intervals.


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  		TABLE 4. Repressibility of essential C. albicans genes by methionine or cysteinea

The C. albicans ERG1 gene, encoding a squalene epoxidase, is specifically inhibited by terbinafine (13, 20). To assess drug hypersensitivity, growth inhibition by terbinafine was determined for the PMET3-CaERG1 conditional mutant in the presence and absence of methionine. As shown in Fig. 4A, a 15-fold increase in terbinafine potency (expressed as IC50) was observed in the presence of methionine compared to the no-methionine control. In addition, the growth inhibition in the presence of methionine varied from about 25 to 90% over a log range of inhibitor concentrations (0.06 to 1 µg/ml), whereas only 0.5 to 3.5% growth inhibition was observed in the absence of methionine over the same terbinafine concentration range (Fig. 4A). On the contrary, the experiments conducted with fluconazole (Fig. 4B) or sordarin (Fig. 4C), which are known inhibitors of ERG11 and EFT2 (29), respectively, showed that sensitivities of the PMET3-CaERG1 conditional mutant to these drugs were not altered by the presence of methionine. Similar results were also obtained when a modified MIC test was conducted for the three antifungals for comparison from the same cultures (data not shown) (the MIC was defined as the drug concentration that gave 100% of cell growth inhibition for terbinafine or sordarin and 80% of inhibition for fluconazole, respectively). Furthermore, the sensitivity of a PMET3-CaRAM2 conditional mutant to these three drugs remained unchanged in either the absence or presence of 5 mM methionine and 1 mM cysteine (data not shown). Taken together, these results established that reduced expression of CaERG1 resulted in cells that were hypersensitive only to the target-specific inhibitor terbinafine.


Figure 4
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  		FIG. 4. Dose-response curves of the PMET3-CaERG1/Caerg1::ARG4 conditional mutant for the antifungal drugs terbinafine (A), fluconazole (B), and sordarin (C) in the absence (–) and presence (+) of methionine. A culture grown overnight was inoculated with an inoculum of 1 x 106 CFU/ml on a 96-well plate containing 200 µl of SD plus histidine broth with various concentrations of drugs as indicated. Where indicated, methionine was added to 0.2 mM, a concentration inhibiting 50% of the cell growth. After 24 h at 30°C, the optical densities were determined with a plate reader at 600 nm.

Parallel high-throughput screening. The utility of the CaMET3 promoter for identifying hypersensitive inhibitors was further explored by conducting a cell-based parallel HTS campaign using the PMET3-CaERG1 conditional mutant. A library of ~12,000 compounds in the Bristol-Myers Squibb Company compound collection was screened in the absence and presence of methionine (denoted Met minus and Met plus, respectively) (see Materials and Methods for details). Using ≥40% growth inhibition as a cutoff at the 14.2 µM compound concentration, 37 hits were identified from the Met-plus screen, 18 of which were also scored positive in the Met-minus screen (Fig. 5). By superimposing the 37 compounds from both the Met-plus and Met-minus screen with respect to percent inhibition of cell growth, we categorized them into three groups. Group I has six hits with percent growth inhibition ranging from 41 to 70% in the Met-plus screen and –11 to 10% in the Met-minus screen. Group II contains hits with >40% inhibition in the Met-plus screen and 11 to 40% inhibition in the Met-minus screen. Group III consists of the 18 hits common to both conditions (both >40%). By referring to the dose-response curves for terbinafine in the presence and absence of methionine (Fig. 4A), those six hits in group I therefore represent the so-called "hypersensitive" hits that would otherwise not be found if normal strains were used in HTS.


Figure 5
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  		FIG. 5. Superimposition of HTS hits from parallel screening of a PMET3-CaERG1/Caerg1::ARG4 conditional mutant in the presence (•) (0.4 mM) and absence ({square}) of methionine (Met-plus and Met-minus screen, respectively). Based on the percent inhibition range in the Met-minus screen, the positive hits identified using a cutoff of >40% growth inhibition in the Met-plus screen were sorted into three groups (group I, –11 to 10%; group II, 11 to 40%; group III, >40% in the Met-minus screen), which are separated by the dashed vertical lines.


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DISCUSSION
 
Identification of conserved fungal genes is a first step towards the discovery and development of future broad-spectrum antifungal agents. Although the inclusion of medically important fungi should conceivably be adequate for the analysis, we chose to include as many available completed fungal genomes as possible for the following reasons. First, a human pathogen is a relative term from a clinical perspective. For example, C. albicans and A. fumigatus are both opportunistic human pathogens that did not produce deep-organ, potentially fatal diseases in humans until recently due to advances in modern medicine (32, 38). Second, broad-spectrum antibiotics and antifungals do not discriminate between pathogenic and nonpathogenic microbes. In addition, we wish to emphasize that the 240 conserved fungal genes identified in this work should serve as a starting point for future fine tuning as more fungal genomes are sequenced and more essential genes in each species are identified.

Although our concordance analysis is a powerful tool for multiple-genome analysis, certain genes would inevitably be missed in our gene set. They include proteins that share conserved function due to structural and/or functional motif (for example, active site) similarity but not primary sequence similarity (14). Other genes that can be missed are those that are nonessential when evaluated individually, yet the protein complex, for example, to which the gene product is assembled can be vital for cell growth. The fungal ß-1,3-glucan synthase is such an example, where neither S. cerevisiae FKS1 (ScFKS1) nor ScFKS2 is required individually for cell viability, yet the disruption of both is lethal (35). Another example is translational elongation factor 2, which is encoded by two nonessential genes (EFT1 and EFT2) (42).

To qualify as potential antifungal targets, the conserved fungal genes have to be essential for fungal cell growth, especially for medically important fungi. Since the verification of gene essentiality is a tremendous task even in the model yeast S. cerevisiae, we decided to initiate the conserved fungal gene identification process by using the essential gene set of S. cerevisiae. We reasoned that fungal genes that are conserved with the essential S. cerevisiae genes would more likely be essential in other fungi. In this regard, the conserved gene set identified previously by Braun et al. (5) from six fungi (C. albicans, S. cerevisiae, Schizosaccharomyces pombe, A. niger, Magnaporthe grisea, and Neurospora crassa) would likely contain many genes that are not essential, even in S. cerevisiae (for example, ARO4, DAL5, and AGP2, to name a few). Those nonessential genes would therefore not be considered antifungal targets.

In addition to finding conserved fungal genes, the identification of conserved genes of unknown function would be another way of prioritizing targets in the hope of finding novel classes of broad-spectrum inhibitors. The 12 CURFs evaluated here fall into this category. They were identified several years ago via the concordance tool by using the two yeast (S. cerevisiae and C. albicans) genome sequences available at that time (52), with the anticipation that genes conserved between these two fungi would likely to be conserved among other fungi as well. Now that more fungal genome sequences are available, we found that 5 out of the 12 genes evaluated are conserved at 40% or greater among the 10 fungal genomes (Table 2). This result suggests that around 50% of the conserved gene set previously identified from S. cerevisiae and C. albicans may not be conserved among other fungi, highlighting the importance of the inclusion of more genome sequences for this type of analysis. On the other hand, unknown functionality of a gene is a relative term, and as time goes on, an increasing number of genes will be found to possess a cellular function or role via either functional characterization or genome annotation. Examples include YLR100w and YDR341c, which recently were found to encode 3-keto sterol reductase (18) and arginyl-tRNA synthetase (47), respectively.

We wish to stress that the successful development of a broad-spectrum antifungal drug requires knowledge and research beyond the identification of conserved fungal genes. For instance, the ß-1,3-glucan synthases (Fks1p and Fks2p) are well conserved, at 52 to 86% identity across the 10 fungi (Table 1), yet its inhibitor, caspofungin, is not active against Cryptococcus neoformans, presumably due to the lack of or the low content of glucan in its cell wall. On the other hand, however, the broad-spectrum inhibitors of Erg11p, voriconazole and posaconazole (conserved at 43% or greater across the 10 fungi studied) (Table 1), have been successfully developed even though the inhibitor fluconazole lacks activity against Aspergillus species.

In an effort to evaluate the essentiality of the conserved fungal genes identified in this work in C. albicans, we developed a repressible MET3 promoter system capable of the large-scale evaluation of gene essentiality. Although the MET3 promoter as well as several other endogenous and exogenous regulatable promoters, including GAL1 (22), MAL1 (6), MAL2 (3), PCK1 (33), and MRP1 (37), have been used for evaluating the essentiality of many genes in C. albicans, only the exogenous tetracycline (Tet) promoter system has been proven to possess the capacity for the identification of essential genes on a genome-wide scale (44). While the recently reported PCR-based promoter (PMET3-green fluorescent protein [GFP], PGAL1-GFP, and PPCK1-GFP) cassettes (19) could conceivably be used for large-scale essential gene evaluation, the cassettes have yet to be demonstrated for this utility. In addition, it is not yet known if the placement of the GFP at the amino terminus of the target protein would complicate the evaluation of gene essentiality and function. Therefore, to extend the utility of the endogenous CaMET3 promoter, in this report, we constructed two PCR-based promoter-swapping cassettes harboring either the CaURA3 or the CaARG4 selective marker for use in the evaluation of gene essentiality in C. albicans. Not only was this CaMET3 promoter system proven in this work to be robust and reliable for evaluating gene essentiality in C. albicans, it may also provide additional features. By using the triply marked BWP17 strain, the availability of two promoter-swapping cassettes with two different selective markers permits the evaluation of a gene in the rare situation where three allelic copies exist (23). In this case, the first allele is deleted using the HIS1 selective marker, followed by sequential placement of the second and third alleles under the control of the CaMET promoter using either the URA3 or the ARG4 cassette. It is noteworthy that out of the 13 essential C. albicans genes identified here, CaYJR072c, which appeared to be nonessential in this study, was reported previously by Davis et al. (10) to be required for cell growth. While the different methodologies used (Tn7-UAU1 insertional mutagenesis versus repressible promoter) may account for the discrepancy, other possibilities could exist, since our attempt to obtain double disruption of this gene also failed (data not shown).

The CaMET3 promoter was further characterized and found to be highly amenable to controlled gene expression. By varying the amount of methionine or cysteine added to the growth medium and thus varying the cellular level of the essential gene product (8), cell growth was correspondingly delayed or inhibited (Fig. 3 and Table 4). Interestingly, we found that cysteine could control expression of the CaMET3 promoter more tightly than methionine, because all 13 conditional mutants could be repressed in growth by cysteine but not all could be repressed by methionine at concentrations up to 10 mM (Table 4). It is conceivable that the CaMET3 promoter is leaky when regulated by methionine alone, since the maximum inhibition of cell growth by methionine never reached beyond 80% for all conditional mutants tested (data not shown). Although the CaMET3 promoter has been utilized for the evaluation of the essentiality of several genes in C. albicans (8, 40, 53), it is not known whether methionine or cysteine was the more effective modulator, since methionine and cysteine were often used simultaneously. Contradictory results were also reported in the S. cerevisiae literature regarding whether methionine, cysteine, or both are the true repressors of the enzymes of sulfur metabolism (39, 48). Nevertheless, our data presented here suggest that in a C. albicans background, cysteine is a much tighter effector of the CaMET3 promoter. It should be noted, though, that a high concentration of cysteine (10 mM) did appear to slightly slow the growth of the parental BWP17 strain (Fig. 3F), albeit with the IC50 of cysteine being ≥10 mM (Table 4).

We demonstrated that the CaERG1 conditional mutant strain displayed, in the presence of a rate-limiting amount of methionine, hypersensitivity to the specific inhibitor terbinafine but not to other antifungals such as fluconazole and sordarin (Fig. 3). It should be noted that hypersensitivity to fluconazole and other azoles was reported with a CaERG1 conditional mutant placed under the control of the CaMET3 promoter (40). While different strain backgrounds (CAI4 versus BWP17) could account for the discrepancy, different assay methods (a spot assay on solid medium [40] versus a modified CLSI macrodilution method used in this work) could also be responsible for the observed differences in drug susceptibility.

Traditionally, antimicrobial agents were identified via whole-cell screening. This approach, however, does not identify the biochemical target of a lead compound. On the other hand, enzyme- or target-based in vitro screening often yields potent enzyme inhibitors but with little or no whole-cell activity. Moreover, there has been little success with attempts to build in "whole-cell activity" for these enzyme inhibitors (43). Using the down-regulatable PMET3-CaERG1 conditional mutant strain, we demonstrated, as a proof of principle, that hypersensitive compound hits with whole-cell activity could be identified in a single parallel HTS campaign. Several lines of evidence suggest that those hypersensitive hits are target specific. First, hypersensitivity of the PMET3-CaERG1 conditional mutant strain in the presence of methionine was observed only with terbinafine and those six hits in group I of Fig. 5. Second, none of the six hits were found to inhibit the growth of an efflux-deficient C. albicans strain as well as a strain of Staphylococcus aureus at the HTS screening concentration (14.2 µM) tested (data not shown). Third, the presence of methionine did not alter the susceptibility of the PMET3-CaERG1 conditional mutant to fluconazole and sordarin (Fig. 4B and C) as well as several other known antifungal inhibitors (control compounds in the HTS), including papulacandin B, ascosteroside, pradimycin, cycloheximide, and benomyl, that bind to targets other than CaErg1p compared to the Met-minus controls (data not shown). On the other hand, while the hypersensitive hits are potential specific inhibitors, the common hits identified from the Met-plus and Met-minus screens may contain specific hits as well. One possible reason for this is that the active concentrations of those compounds in the screening solution were high enough to inhibit cell growth under both Met-plus and Met-minus conditions. Therefore, individual dose-response determinations are needed to identify which common hit(s) is specific to the target under evaluation.

Finally, the construction of conditional mutants by using the CaMET3 promoter makes it possible to screen against any target placed under this promoter, whether or not its function is known or if a functional in vitro assay is available. Although new classes of inhibitors can be identified by rescreening existing drug targets, the new targets identified in this work conceivably offer greater potential for the identification of novel classes of antifungal agents. Admittedly, the successful identification of novel targets as well as inhibitors does not necessarily lead to a drug due to the complexity of the drug development process. Nevertheless, it is our hope that the streamlined process we developed proceeding from selection and validation of candidate antifungal targets to screening for specific inhibitors can be one of many useful approaches for future antifungal drug discovery.


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ACKNOWLEDGMENTS
 
We thank Aaron Mitchell for providing strain BWP17 and plasmids pGEM-URA3, pGEM-HIS1, and pRS-Arg4{Delta}SpeI. We are grateful to Joan C. Fung-Tomc for critical reading of the manuscript and to Mahmound Ghannoum for constructive discussions.

This study was supported by the Bristol-Myers Squibb Company.

We dedicate this paper to our coauthor, John F. Barrett, who died 24 January 2006. He was a strong advocate of genomics-based antimicrobial drug discovery, and we will miss his leadership, enthusiasm, and boundless energy.


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FOOTNOTES
 
* Corresponding author. Mailing address: Bristol-Myers Squibb Company Pharmaceutical Research Institute, 5 Research Parkway, Wallingford, CT 06492. Phone: (203) 677-7015. Fax: (203) 677-6771. E-mail: ying-kai.wang{at}bms.com. Back

{dagger} Supplemental material for this article may be found at http://ec.asm.org/. Back


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Eukaryotic Cell, April 2006, p. 638-649, Vol. 5, No. 4
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