JOURNAL OF CLINICAL MICROBIOLOGY, June 2004, p. 2480–2488 Vol. 42, No. 60095-1137/04/$08.00�0 DOI: 10.1128/JCM.42.6.2480–2488.2004Copyright © 2004, American Society for Microbiology. All Rights Reserved.

Multilocus Sequence Typing Is a Reliable Alternative Method to DNAFingerprinting for Discriminating among Strains of Candida albicans

Juan C. Robles,1 Larry Koreen,1,2 Steven Park,1 and David S. Perlin1,2*Public Health Research Institute, International Center for Public Health,1 and Department of Microbiology and Molecular

Genetics, New Jersey Medical School, University of Medicine and Dentistry of New Jersey,2 Newark, New Jersey 07103

Received 21 February 2004/Returned for modification 8 March 2004/Accepted 18 March 2004

Multilocus sequence typing (MLST) has emerged as a powerful new DNA-typing tool for the evaluation ofintraspecies genetic relatedness. This method relies on DNA sequence analysis of nucleotide polymorphisms inhousekeeping genes and has shown a high degree of intraspecies discriminatory power for bacterial and fungalpathogens. However, the results of the MLST scheme for Candida albicans have heretofore never been formallycompared to those of other established typing techniques. To assess the value of MLST relative to those ofother DNA fingerprinting tools for discriminating among strains of C. albicans, we applied it to a previouslywell-characterized set of 29 C. albicans isolates evaluated by the random amplified polymorphic DNA (RAPD),multilocus enzyme electrophoresis (MLEE), and Ca3 Southern hybridization probe techniques. MLST iden-tified three clusters of genetically related isolates, with 82.3% direct concordance with MLEE, 82.7% withRAPD analysis, and 86.2% with the Ca3 Southern hybridization technique. When MLST was applied to asubset of 22 isolates of unrelated origins, it identified 21 independent diploid sequence types (DSTs), resultingin a discriminatory power of 99.6%. These DSTs were 96.9, 99.6, and 99.6% concordant with the genotypesidentified by RAPD analysis, MLEE, and Ca3 Southern hybridization, respectively. These results demonstratethat MLST is a highly effective technique that performs at least comparably to other established DNAfingerprinting techniques.

The introduction of novel antifungal agents has helped stemthe steady rise of systemic fungal infections observed over theyears (4, 16, 17, 28). Nevertheless, nosocomial Candida albi-cans infections remain a major cause of morbidity and mortal-ity among immunosuppressed patients (7, 22). In fact, a recentstudy showed that the mortality rate for patients with nosoco-mial candidemia is 61%, a 49% increase over that for othermatched hospitalized patients (9). Successful treatment andprevention of these infections within the hospital setting de-pend not only on improved therapy but also on limitation oftheir spread through rapid and accurate detection of thesepathogens. For this purpose, several image-based genotypingtechniques have been developed and are widely used to char-acterize C. albicans strains. Unfortunately, these techniquesare not well suited for rapid and high-throughput sample pro-cessing. They are also technically demanding and often requireassumptions about hybridization and/or gel migration effi-ciency.

As opposed to image-based techniques, DNA sequence-based genotyping techniques are rapid and often rely on thenucleotide sequences of genes that are under stabilizing selec-tive pressure (e.g., housekeeping genes). Typing schemes thatuse DNA sequence size and nucleotide polymorphisms havebeen shown to be effective for the identification of Candidaspecies. For example, the nucleotide polymorphisms of a396-bp fragment of the mitochondrial cytochrome b gene ac-curately distinguish between isolates of C. albicans, C. glabrata,C. parapsilosis, C. tropicalis, C. lusitaniae, and C. stellatoidea (1,

30). Similarly, amplicon size variations of the CaACT1 geneintron discriminate among isolates of C. dubliniensis and C.albicans (5). In addition, some degree of intraspecies discrim-ination was achieved by sequence analysis of these genes, un-derlining the utility of DNA sequencing for the accurate char-acterization of yeast pathogens.

In much the same way that it has been used for bacterialpathogens (27, 29), multilocus sequence typing (MLST) hasemerged as an alternative typing tool that has a high degree ofresolution and that has the capacity to rapidly characterizelarge numbers of clinical C. albicans isolates. MLST is basedon the DNA sequence analysis of nucleotide polymorphismswithin housekeeping genes, and it has shown a high degree ofintraspecies discriminatory power for bacterial pathogens (13,14, 23) and, most recently, fungal species, such as C. albicans(2, 26). MLST studies of C. albicans isolates (2, 3, 26) demon-strated that this technique is applicable to a diploid species andcan effectively characterize sets of unrelated and related iso-lates.

However, MLST has not been formally validated by com-parison to other conventional fingerprinting methods. Randomamplified polymorphic DNA (RAPD) analysis, multilocus en-zyme electrophoresis (MLEE), and Ca3 Southern hybridiza-tion, among others, have been shown to be effective for thestudy of both local and global epidemiological populations ofCandida spp. (18, 24). MLEE can effectively identify geneticmacrovariations that accumulate very slowly and that can thusbe used to assess the phylogeny of C. albicans (24). Ca3 South-ern hybridization can detect both rapidly and slowly accumu-lating genetic microvariations within strains, making it a suit-able technique for characterization of both local and globalpopulations of C. albicans (19, 25). It is important to determine

* Corresponding author: Mailing address: Public Health ResearchInstitute, International Center for Public Health, 225 Warren St., New-ark, NJ 07103. Phone: (973) 854-3200. Fax: (973) 854-3101. E-mail:perlin@phri.org.

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if MLST is as reliable as other established DNA fingerprintingtechniques, and in this study MLST was applied to a panel ofC. albicans isolates (n � 29) that had previously been analyzedby RAPD analysis, MLEE, and Ca3 Southern hybridization(18). First, the genetic diversity found among the 29 C. albicansstrains by MLST is reported. Second, the discriminatory powerof MLST was compared to those of RAPD analysis, MLEE,and Ca3 Southern hybridization for different groups of strains.Finally, the congruence between MLST and the other typingtechniques at various genetic depths was determined.

MATERIALS AND METHODS

C. albicans isolates. The 29 C. albicans strains used in this study have beendescribed previously (18). All cells were maintained on glycerol stocks at �80°Cand were grown on YPD broth (1% [wt/vol] yeast extract, 2% [wt/vol] peptone,2% [wt/vol] dextrose [pH 5.7]). The strain collection included isolates FC-1 andFC-2 (switch phenotypes of laboratory strain 3153A) and isolates FC-3 and FC-4(switch phenotypes of laboratory strain WO-1); the remaining 25 isolates (FC-5to FC-29) were clinical isolates. As assigned previously (18), the strain collectionwas analyzed as three different groups: the first included all 29 C. albicansisolates, the second was a subset that included 22 isolates from unrelated hosts,and the third was a different subset that included seven isolate pairs that con-sisted of pairs of strains acquired from the same or related hosts (FC-11 andFC-12 [same patient], FC-13 and FC-14 [same patient], FC-17 and FC-18 [sexualpartners], FC-19 and FC-20 [same patient], and FC-23 and FC-24 [sexual part-ners]) and the pairs of switch phenotype strains described above (these 14isolates are referred to as “related-origin isolates”) (18).

Choice of loci. MLST based on seven housekeeping genes was performed forthe 29 C. albicans strains. Six C. albicans housekeeping genes have been de-scribed previously for use in MLST: loci CaVPS13, CaADP1, CaRPN2, andCaSYA1 (2, 26) and loci CaACC1 and CaGLN4 (2). In this study C. albicansCaPMA1 (plasma membrane H�-ATPase) (15) was also included as a seventhgene to enhance the discriminatory power of MLST (Table 1).

Fragment amplification. Fragment amplifications were carried out in a 50-�lreaction volume containing 50 ng of genomic DNA, 0.5 �M each primer, 0.5 mMdeoxynucleoside triphosphate mixture (Promega Corp.), 2.5 U of Triplemasterpolymerase (Brinkmann), and 5.0 �l of 10� High Fidelity Buffer (Brinkmann).The PCR conditions used for all primer sets were 30 cycles of 95°C for 30 s, 60°Cfor 45 s, and 72°C for 1 min, followed by a final extension step of 72°C for 5 min;the PCRs were performed in a PTC100 96-well thermal cycler (MJ Research).

DNA sequencing was performed by using the same primers used for PCR. Allsequencing reactions were carried out in 20-�l reaction volume and analyzedwith a CEQ 8000 Genomic Analysis System (Beckman). For all strains all sevenloci were sequenced in both directions.

MLST data analysis. MLST was performed with each of the isolates as de-scribed previously (2, 26). For each gene, distinct alleles were identified andnumbered by using the nonredundant databases program (http://calbicans.mlst.net/). The alleles at each of the seven loci constituted a strain’s allelic profile, i.e.,diploid sequence type (DST). Each distinct allelic profile was considered aunique DST, or genotype. A dendrogram based on the pairwise differences in theallelic profiles of the seven genes was constructed by the unweighted pair groupmethod with the arithmetic mean (UPGMA) by using the START program(http://www.medawar.ox.ac.uk/maiden/software.shtml). BURST, a noncommer-cial algorithm previously designed for MLST of bacterial pathogens, was used todivide the 29 C. albicans strains into clusters of genetically related strains. TheBURST algorithm groups strains according to their allelic profiles by using auser-specified group definition, which is the number of alleles that the isolatesneed to have in common to belong to the same group (http://www.mlst.net/). Therelatedness among the 29 C. albicans strains was also assessed by SplitsTreeanalysis (11), an alternative algorithm for analysis and visualization of evolution-ary data. Typing of the 29 C. albicans strains by RAPD analysis, MLEE, and Ca3Southern hybridization was done previously (18).

Discriminatory power. The discriminatory power of each typing technique forall three isolate groups was measured with Simpson’s index of diversity (10),which calculates the probability that any two isolates will have different geno-types. The genotypes assigned by RAPD analysis, MLEE, and Ca3 Southernhybridization were determined at the most discriminatory level of each previ-ously published respective dendrogram (18); any two isolates not labeled asidentical were given a different genotype. For MLST the genotypes were basedon individual DSTs.

Congruence between techniques. As defined and performed previously (18),for RAPD analysis, MLEE, and Ca3 Southern hybridization, the average SAB

values (i.e., measures of genetic relatedness) for the 29 C. albicans defined thecutoff points used to group the strains into genetically related clusters. ForMLST, the number of alleles from the seven loci chosen to group strains intogenetically related clusters was determined by exploring the use of differentnumbers of alleles and determining which resulting cluster was in closest agree-ment to the clusters identified by the other techniques. To test the agreementbetween MLST and the other techniques on the placement of isolates intoclusters, two-by-two tables were constructed and evaluated by Fisher’s exact test(21). Statistical significance was defined as a P value �0.05. The congruencebetween techniques was further evaluated by cross-classification analysis (12, 21)at the individual genotype and cluster genetic depths of the dendrogram as

TABLE 1. Genes and primers used for MLSTa

Locus Gene product Primer Sequence (5�-3�) Fragmentsize (bp)

No. of variablenucleotide sites

No. ofalleles

CaACC1 Acetyl coenzyme A carboxylase 466 Forward GCAAGAGAAATTTTAATTCAATG 407 5 8466 Reverse TTCATCAACATCATCCAAGTG

CaVPS13 Vacuolar protein sorting protein 552 Forward TCGTTGAGAGATATTCGACTT 403 10 14552 Reverse ACGGATGGATCTCCAGTCC

CaGLN4 Glutaminyl tRNA synthetase 598 Forward GAGATAGTCAAGAATAAAAAAGT 404 8 8598 Reverse ATCTCTTTCATCTTTTGGACC

CaADP1 ATP-dependent permease 904 Forward GAGCCAAGTATGAATGATTTG 443 11 10904 Reverse TTGATCAACAAACCCGATAAT

CaRPN2 26S proteasome regulatory subunit 1041 Forward TTCATGCATGCTGGTACTAC 306 10 91041 Reverse TAATCCCATACCCAAAGCAG

CaSYA1 Alanyl RNA synthetase 1369 Forward AGAAGAATTGTTGCTGTTACTG 391 12 151369 Reverse GTTACCTTTACCACCAGCTTT

CaPMA1 Plasma membrane H�-ATPase 2460 Forward GCCATTTTCGCTGATGTTGC 480 5 43017 Reverse CGTGTTGAGTAGATACTCTTTGC

a The genes and primers used for MLST, along with the genetic diversity observed at each locus, are shown. The CaACC1, CaVPS13, CaGLN4, CaADP1, CaRPN2,and CaSYA1 loci were previously used for MLST (2,26); and CaPMA1 was introduced in this MLST study. The genetic diversities of the 29 C. albicans strains arepresented as the number of variable nucleotide sites and the number of alleles identified at each locus.

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follows. For each possible pair of isolates (n � 91 for the 14 related-originisolates, n � 231 for the set of unrelated isolates, and n � 406 for all 29 isolates),it was determined whether the strains comprising the pair were or were not fromthe same cluster or genotype by each typing technique. A two-by-two table wasconstructed for each two-technique comparison, and the percent concordancewas calculated.

RESULTS

Genetic diversity. MLST was performed by evaluating theDNA sequences of segments from seven different housekeep-ing genes, which yielded a set of 2,834 nucleotides for eachstrain. Sixty-one variable nucleotide sites were identifiedamong the 29 C. albicans strains, of which 55 were heterozy-gous. The number of variable nucleotides at each locus rangedfrom 5 to 12, indicating a sizable amount of genetic diversityfor each of the loci chosen (Table 1). The resulting proportionof variable nucleotide sites for the seven housekeeping geneswas 2.2% (61 of 2,834 nucleotides), which is comparable to theresults obtained in two recent MLST studies with C. albicans(2, 26) that showed 2.9 and 2.8% nucleotide site variabilities,respectively. The nucleotides present at each variable site andtheir positions relative to the gene fragment sequenced areshown in Fig. 1. The majority of these variable nucleotide siteshad been identified previously (2, 26), and the ones newlyidentified in this study (n � 15) are highlighted in Fig. 1.

The number of alleles identified for the 29 C. albicans strainsvaried from 4 to 15 per gene; CaPMA1 generated the leastnumber of alleles (n � 4), while CaSYA1 generated the most(n � 15). The allelic diversity found at the seven loci resultedin 24 unique DSTs for the 29 isolates (Table 2). Each of theisolates in isolate pairs FC-1 and FC-2, FC-3 and FC-4, FC-5and FC-6, FC-11 and FC-12, and FC-17 and FC-18 shared thesame DST; and the remaining DSTs were each found in asingle isolate only. On the basis of the number of alleles foundat each of the seven loci and the diploid nature of C. albicans,MLST can theoretically resolve more than 9 million distinctDSTs: (8 � 14 � 8 � 10 � 9 � 15 � 4) � 2.

Discriminatory power. Simpson’s index of diversity for thegenotypes distinguished by each of the four typing techniqueswas calculated for the three groups of isolates described inMaterials and Methods (Table 3). Overall, MLST displayed avery high discriminatory power. As an example, the discrimi-natory power of MLST was 95.6% for the related-origin iso-lates and 99.6% for the unrelated isolates. In comparison toother typing techniques, the discriminatory power of MLSTwas higher than that of RAPD analysis, often equal to that ofMLEE, and slightly lower than that of Ca3 Southern hybrid-ization for all groups of strains (Table 3). For example, MLSTidentified 24 distinct DSTs for the 29 C. albicans isolates,resulting in a discriminatory power of 98.8%, compared todiscriminatory powers of 95.0% for RAPD, 98.3% for MLEE,and 99.3% for Ca3 Southern hybridization. When MLST wasapplied to the 22 unrelated-origin isolates, it identified 21distinct DSTs, resulting in a discriminatory power (99.6%) thatwas higher than that of RAPD analysis (96.5%), equal to thatof MLEE (99.6%), and slightly lower than that of Ca3 South-ern hybridization (100%). The slight differences in discrimina-tory power between MLST and Ca3 Southern hybridizationcan be attributed to the fact that MLST identified FC-5 as

identical to FC-6 and FC-11 as identical to FC-12, while Ca3Southern hybridization did not.

MLST data analysis. Three similar clusters of geneticallyrelated strains were identified among the 29 strains by all fourtyping techniques. For the RAPD, MLEE, and Ca3 Southernhybridization techniques, these clusters were determined pre-viously (18) by using the average SAB relatedness value for the29 C. albicans strains as a truncation point on each technique’sdendrogram. After analysis of the MLST results with theBURST algorithm with different numbers of shared identicalalleles as the inclusion criterion for a cluster, it was determinedthat any three shared alleles from seven loci formed clusters inoptimal agreement with those of the other three techniques.This group definition obtained with the BURST algorithmdivided the 29 C. albicans strains into three clusters of genet-ically related isolates and six outliers (isolates that were notincluded in any cluster): the first cluster was strains FC-1,FC-2, FC-5, FC-6, FC-11, FC-12, FC-15, FC-19, FC-20, FC-21,FC-25, and FC-27; the second cluster was strains FC-8, FC-13,FC-14, FC-17, FC-18, FC-22, FC-23, and FC-24; the thirdcluster was strains FC-7, FC-28, FC-and 29; and the outlierstrains were FC-3, FC-4, FC-9, FC-10, FC16, and FC-26. Thesegroups of strains corresponded to the clusters I, II, and III andoutliers, respectively, identified by Pujol et al. (18). The differ-ences between MLST and all three of the other techniqueswere as follows: isolates FC-3 and FC-4 were identified asoutliers by MLST but were placed into a cluster by the otherthree techniques; and by MLST, isolates FC-19 and FC-20were both placed into a cluster different from the cluster intowhich they were placed by the other techniques. A UPGMAdendrogram (left portion of Fig. 2) based on the pairwisedifferences in the allelic profiles of the seven genes shows thatthe strains clustered in a manner similar to that according tothe results obtained with the BURST algorithm. Furthermore,the relatedness among the 29 C. albicans strains was also as-sessed by analysis with SplitsTree (11), an alternative algorithmfor the analysis and visualization of evolutionary data not al-ways best represented by a standard tree. The SplitsTree graph(right portion of Fig. 2) showed a clustering of strains highlysimilar to those obtained with both the BURST algorithm andthe UPGMA dendrogram. This agreement indicates that thesequence data were reliable and accurately represented bythese relatedness algorithms. It is also worth noting that thesestrain clusters did not correlate with either the geographicdistribution or the body site of isolation of the strains.

All (100%) of the isolates in the three clusters determinedby MLST with the BURST algorithm were in the clustersdetermined by the other techniques; 82, 88, and 92% of theisolates in the clusters determined by RAPD analysis, MLEE,and Ca3 Southern hybridization, respectively, were in the clus-ters identified by MLST (Table 4). Specifically, the results ofMLST in terms of the assignment of the strains into clusters oras outliers were in very strong agreement with those of MLEE(P � 0.005) and were in even stronger agreement with those ofCa3 Southern hybridization (P � 0.0006) (Table 4). Similar toan analysis done previously (18), the typing techniques werefurther compared by using the seven isolate pairs that comprisethe 14 related-origin isolates by determining how often MLSTversus how often the other techniques assigned the isolateswithin each pair identical genotypes or nonidentical genotypes.

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FIG. 1. Variable nucleotide sites and alleles identified at each locus. The numbers in the vertical format represent the positions of the variablenucleotides relative to the fragment sequenced. The highlighted nucleotide positions were newly identified as variable in this study; the others wereidentified previously (2, 26). The nucleotides present at each variable site for the 29 C. albicans isolates analyzed are shown for all alleles;heterozygous variable sites are represented as follows: K, G or T; M, A or C; R, A or G; S, C or G; W, A or T; Y, C or T. The numbers inparentheses represent the number of isolates with that allele.

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Table 5 lists how each technique classified each isolate pair.The MLST classifications agreed with those of MLEE, RAPDanalysis, and Ca3 Southern hybridization for 57, 71, and 86%of the pairs, respectively. The high discriminatory power ofMLST and its potential to discern more accurate genetic dif-ferences may be the cause of the lower agreement values forthe related-origin isolates. Nevertheless, the results of MLSTagain had the highest levels of agreement with those of Ca3Southern hybridization, considered the most accurate of thethree techniques (18).

Cross-classification analysis. To further test the agreementbetween MLST and the other techniques, cross-classificationanalyses were conducted at the deep genetic cluster level. Thecluster concordance values resulting from these analyses be-tween MLST and the other techniques for each group of iso-lates are shown in Table 3. Overall, the isolate clusters iden-tified by MLST and the other techniques were substantiallyconcordant, ranging from 72.5% for MLST and all of the othertechniques for the related-origin isolates to 90.5% for MLSTand Ca3 Southern hybridization for the unrelated isolates. Asan example, the latter indicates that 90.5% of the time any two

strains that were assigned to matching (i.e., the same) or mis-matching (i.e., different) clusters by MLST, the exact matchingand mismatching determinations were made by Ca3 Southernhybridization. For all 29 isolates, MLST and Ca3 Southernhybridization were in 86.2% direct concordance for clusterclassification.

In addition to the cluster analysis, it was important to test foragreement between the typing techniques at a highly discrim-inating genotypic level in light of MLST’s high degree of re-solving power. The results of cross-classification analyses per-formed by using MLST DSTs and the genotypes distinguishedby each of the other techniques are shown in Table 3. Overall,for all three groups of isolates analyzed, there was a very highdegree of concordance between the DSTs and the genotypesobtained by the other techniques, ranging from 91.2% for therelated-origin isolates by RAPD analysis to 99.6% for theunrelated isolates by Ca3 Southern hybridization and MLEE.Compared with MLST, the results of Ca3 Southern hybridiza-tion were less concordant with those of RAPD analysis(96.5%) and equally concordant with those of MLEE (99.6%)for the unrelated C. albicans strains. The very high level of

TABLE 2. Isolate descriptions and MLST resultsa

Isolate Characteristic or site of isolation Geographic originAllele no.b

DSTCaACC1 CaVPS13 CaGLN4 CaADP1 CaRPN2 CaSYA1 CaPMA1

FC-1 Smooth phenotype of laboratory strain3153A

1 1 1 1 1 1 1 1

FC-2 Star phenotype of laboratory strain3153A

1 1 1 1 1 1 1 1

FC-3 White phenotype of laboratory strainWO-1

Iowa City 2 2 2 2 2 2 1 2

FC-4 Opaque phenotype of laboratory strainWO-1

Iowa City 2 2 2 2 2 2 1 2

FC-5 Oral El Paso, Tex. 3 1 2 1 1 3 1 3FC-6 Oral El Paso, Tex. 3 1 2 1 1 3 1 3FC-7 Oral El Paso, Tex. 4 3 2 3 3 4 2 4FC-8 Oral El Paso, Tex. 1 4 3 4 4 5 1 5FC-9 Oral El Paso, Tex. 5 5 4 5 5 1 3 6FC-10 Oral El Paso, Tex. 5 6 5 6 6 6 4 7FC-11 Oral Ann Arbor, Mich. 3 1 2 1 1 7 1 8FC-12 Fecal; same source as FC-11 Ann Arbor, Mich. 3 1 2 1 1 7 1 8FC-13 Seminal Ann Arbor, Mich. 2 7 3 7 4 8 1 9FC-14 Oral; same source as FC-13 Ann Arbor, Mich. 5 7 3 4 7 9 1 10FC-15 Vaginal Ann Arbor, Mich. 3 8 6 6 1 7 1 11FC-16 Vaginal Ann Arbor, Mich. 6 3 7 8 8 10 1 12FC-17 Vaginal Ann Arbor, Mich. 2 9 3 4 4 11 1 13FC-18 Fecal; sexual partner from whom isolate

FC-17 was obtainedAnn Arbor, Mich. 2 9 3 4 4 11 1 13

FC-19 Vaginal Iowa City 7 10 6 3 1 12 1 14FC-20 Vaginal; same source as FC-19 Iowa City 8 11 6 9 1 12 1 15FC-21 Vaginal Iowa City 1 1 2 1 1 13 1 16FC-22 Vulval Iowa City 2 12 3 7 4 9 1 17FC-23 Vulval Iowa City 2 9 3 4 4 14 1 18FC-24 Oral; sexual partner from whom isolate

FC-23 was obtainedIowa City 2 9 3 4 9 8 1 19

FC-25 Oral Iowa City 3 8 8 1 1 1 1 20FC-26 Oral Iowa City 1 13 6 10 2 15 1 21FC-27 Oral Iowa City 1 1 6 1 1 1 1 22FC-28 Oral Iowa City 5 14 2 10 3 12 2 23FC-29 Vulval Iowa City 5 3 8 10 3 11 2 24

a The collection of 29 C. albicans strains was characterized previously (18), and the allele number for each of the seven genes and the DSTs determined by MLSTin this study are shown; each distinct DST is a unique set of alleles for the seven genes.

b The numbers assigned to each allele are not the same as those used for CaACC1, CaVPS13, CaGLN4, CaADP1, CaRPN2, and CaSYA1 in previous studies (2, 26);instead, each allele was numbered in the order of identification with the nonredundant database program.

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agreement of MLST with Ca3 Southern hybridization at boththe cluster and the individual genotype levels is important, asCa3 Southern hybridization has been determined to be themost discriminating and effective of the fingerprinting tech-niques (18).

The concordance values between MLST and the other tech-niques were slightly higher for the unrelated isolates than for

the related-origin isolates at the cluster and genotype levels(Table 3). For example, cluster concordance between MLSTand all of the other techniques for the 14 related-origin isolateswas 72.5%, but it increased to 83.1% with RAPD analysis, to85.3% with MLEE, and to 90.5% with Ca3 Southern hybrid-ization for the 22 unrelated C. albicans isolates. As indicatedabove, dendrogram analysis revealed that four related-origin

FIG. 2. Dendrogram and SplitsTree analyses. A dendrogram showing the genetic relatedness among the 29 C. albicans isolates is shown on theleft; the corresponding allelic profile (in parentheses), DST (sequence type) number, and isolate identifier (FC numbers) are shown. The SplitsTreeanalysis (right) also demonstrates the genetic relatedness among the same set of isolates.

TABLE 3. Discriminatory power of typing techniques and congruence between MLST and the other typing techniques for the three groupsof C. albicans isolatesa

Isolate group Technique No. of genotypesidentified

Index ofdiversity (%)

Congruence between MLST andfingerprinting techniques

Cluster level Genotype level

14 related-origin isolates RAPD 7 89.0 72.5 91.2MLEE 9 94.5 72.5 96.7Ca3 11 96.7 72.5 98.9MLST 10 95.6

22 unrelated isolates RAPD 16 96.5 83.1 96.9MLEE 21 99.6 85.3 99.6Ca3 22 100 90.5 99.6MLST 21 99.6

All 29 isolates RAPD 17 95.0 82.7 95.8MLEE 23 98.3 82.3 98.5Ca3 26 99.3 86.2 99.5MLST 24 98.8

a The 14 related-origin isolates and 22 unrelated isolates are subsets of the original 29 C. albicans isolates used in this study. The genotypes for RAPD analysis, MLEE,and Ca3 Southern hybridization (Ca3) were based on the most discriminatory level of the previously produced dendrograms (18); any two isolates not labeled asidentical were given a different genotype. The genotypes for MLST were based on the DSTs. The genotypes for RAPD analysis, MLEE, and Ca3 Southern hybridizationand the DSTs for MLST were used to calculate the discriminatory power by using Simpson’s index of diversity. For RAPD analysis, MLEE, and Ca3 Southernhybridization, the average SAB value for the 29 C. albicans isolates was used as the cutoff point to divide the isolates into clusters of genetically related isolates (18);for MLST analysis, the sharing of three identical alleles of seven loci was used as the cutoff point to divide the 29 C. albicans isolates into clusters of genetically relatedisolates. The congruence between techniques, conducted at two genetic levels (genotype and cluster), was determined by cross-classification analyses of all possible pairsof isolates (n � 91 for the 14 related-origin isolates, n � 231 for the set of unrelated isolates, and n � 406 for all 29 isolates).

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isolates (isolates FC-3, FC-4, FC-19, and FC-20) were classi-fied into clusters differently by MLST than by the other tech-niques. This resulted in a lowering of the cluster concordancevalues for the related-origin isolates more so than for theunrelated isolates, which had only two of these four isolateswith discordant classifications. This was also the primary rea-son why genotype concordance values were generally higherthan cluster concordance values. Also, at the genotype level itwas observed that there was an important difference in theconcordance values between related-origin isolates (91.2%)and unrelated isolates (96.9%) only between MLST and theleast discriminatory typing method, RAPD analysis. This dif-ference resulted simply because RAPD analysis distinguishedfewer genotypes than MLST.

Evaluation of locus utility. In order to explore whetherMLST could be based on fewer than seven loci and still clusterstrains accurately, BURST analysis was performed with differ-ent numbers of loci. The sharing of any two alleles among sixloci (i.e., excluding CaPMA1) or any two alleles among onlyfive loci (i.e., excluding CaACC1 and CaPMA1) divided the 29C. albicans strains into the exact same three clusters and out-liers obtained by using the BURST group definition of threeshared alleles from seven loci detailed in “MLST data analysis”above. Also, strain and genetic relationships determined withthe UPGMA dendrogram based on the pairwise differences inthe allelic profiles with the five loci were virtually the same asthose determined with all seven loci (data not shown). Fur-thermore, the discriminatory power of MLST was in no wayaffected by the exclusion of CaPMA1 and CaACC1 (data notshown). Although nucleotide polymorphisms were detected inCaPMA1, they did not enhance the discriminatory power of

MLST because they were in linkage disequilibrium with thegenetic variation of the other loci. Such linkage is furtherevidence for the previously documented notion that C. albicanshas a clonal population structure (18).

DISCUSSION

Although MLST has been developed as a tool for the typingof C. albicans, it had never been formally compared to thetechniques already established for the study of C. albicans. Ourresults presented here show that MLST was more discriminat-ing than RAPD analysis and was essentially as discriminatingas MLEE and Ca3 Southern hybridization, with Ca3 Southernhybridization usually being accepted as the most discriminatingof the image-based techniques and as being effective in epide-miological investigations (18, 24). The overall high discrimina-tory power of MLST detected here is corroborated by theresults of Bougnoux et al. (2) and Tavanti et al. (26). Also, thediscriminatory ability of MLST stems from nucleotide poly-morphisms, changes that are presumably stable and accurate,whereas elsewhere (6) some image-based techniques havebeen shown to be hypervariable in certain cases and to inap-propriately subdivide known related isolates. The allelic poly-morphisms of the seven genes used for MLST in this study canpotentially resolve more than 9 million distinct DSTs, and theprobability that two isolates would incorrectly be consideredidentical is very minimal. Therefore, MLST can be used in lieuof other techniques as a highly informative and reliable tool foroutbreak investigations and other local epidemiological studysettings.

Even in light of its high discriminatory power, the results ofMLST still had a high level of agreement with those of Ca3Southern hybridization at various genetic depths, as demon-strated by the cross-classification analyses. Furthermore, it wasrevealed that in comparison with the results of Ca3 Southernhybridization, the results of MLST were, in certain cases, lesscongruent with those of MLEE and always less congruent withthose of RAPD analysis. These results are largely because theRAPD and MLEE schemes produce fewer genotypes thanMLST. Differences in the levels of agreement between tech-niques may also be due in part to the differences in some of thetechnique-specific methods of analysis used (e.g., some clus-tering and phylogenetic algorithms) or to MLST’s establishingmore accurate genetic relationships because of its use of DNAsequence data. Our results also suggest that the present MLST

TABLE 4. Association between the clusters identified by MLSTand the other typing techniques

Technique MLSTa P valueb

RAPD 100, 82 0.207MLEE 100, 88 0.005Ca3 Southern hybridization 100, 92 0.0006

a The first number represents the percentage of isolates in the three clustersidentified by MLST that were in clusters identified by the other technique; thesecond number represents the percentage of isolates in clusters identified by theother technique that were also in the clusters identified by MLST.

b The statistical significance of the agreement between techniques in assign-ment of strains into clusters or as outliers was evaluated by Fisher’s exact test(21); statistical significance was defined as a P value of �0.05.

TABLE 5. Agreement between techniques for related-origin isolatesa

Isolate pair Epidemiological relatednessClassification by technique

RAPD MLEE Ca3 MLST

FC-1 and FC-2 Switch phenotypes of laboratory strain 3153A Id Id Id IdFC-3 and FC-4 Switch phenotypes of laboratory strain WO-1 Id Id Id IdFC-11 and FC-12 Same patient, distinct sites of isolation (i.e., oral and fecal) Id Id NId IdFC-13 and FC-14 Same patient, distinct sites of isolation (i.e., seminal and oral) NId NId NId NIdFC-17 and FC-18 Sexual partners, distinct sites of isolation (i.e., vaginal and fecal) NId NId Id IdFC-19 and FC-20 Same patient, both vaginal isolates NId Id NId NIdFC-23 and FC-24 Sexual partners, distinct site of isolation (i.e., vulval and oral) Id Id NId NId

a The 14 isolates (seven pairs) are a subset of the 29 C. albicans isolates (18). Each pair was classified as identical (Id) if both isolates shared the same genotype andnonidentical (NId) if both isolates did not share the same genotype. The genotypes for RAPD analysis, MLEE, and Ca3 Southern hybridization (Ca3) were based onthe most discriminatory level of their dendrograms (18); genotypes for MLST were based on DSTs.

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scheme is as good at clustering related strains as MLEE, thewell-established tool of evolutionary and population biologists.Consistent with the latter is the fact that SplitsTree analysisrevealed nearly the same results as those revealed by MLSTwith the BURST algorithm, thus indicating that MLST pro-duced sound phylogenetic information. Therefore, MLST caneffectively be used for molecular typing in both global andlong-term investigations and local investigations.

Among the techniques of RAPD analysis, MLEE, and Ca3Southern hybridization, Ca3 Southern hybridization has beensingled out as the most effective (18); and the results of MLSTwere almost always in greater agreement with those of Ca3Southern hybridization than with those of the other techniquesand performed more comparably to Ca3 Southern hybridiza-tion than to the other fingerprinting techniques. For the 29isolates, the results of MLST and Ca3 Southern hybridizationwere in 86.2% concordance at the cluster level and 99.5%concordance at the genotype level. Such high levels of concor-dance and the similar discriminatory powers (for all 29 isolates,discriminatory powers were 98.8% for MLST and 99.3% forCa3 Southern hybridization), along with MLST’s DNA se-quence-based accuracy and ease of performance, storage, anddata comparison and sharing, make MLST more advantageousthan Ca3 Southern hybridization. With the trend toward low-cost high-throughput DNA sequencing, MLST will becomeeven more desirable.

A reliable, rapid, objective, and high-throughput moleculartyping approach has certainly become more necessary in thehealth care environment for addressing reported nosocomialC. albicans infections. Gil-Lamaignere et al. (8) pointed outthat large amounts of MLST data from clinical isolates accu-mulated from spatiotemporally diverse locations can easily beanalyzed (a website for C. albicans MLST [http://calbicans.mlst.net/] developed by d’Enfert and colleagues contains such adatabase), whereas image-based techniques are usually moredifficult because they require processing of isolates together foraccurate visual comparisons. Also, as the use of MLST in-creases, more genotypes will be found and the technique willbe further optimized. In this study 15 polymorphic nucleotidesites were newly identified (Fig. 1). We also found that theaddition of CaPMA1 to the six other loci used for MLST didnot contribute major discriminatory power. However, it addedfour more individual alleles, and if more isolates are charac-terized, it may indeed contribute substantially to the discrim-inatory ability of MLST (potentially up to 7,000 more DSTs).CaPMA1 polymorphisms also verified the strain relationshipsdetermined by use of the other loci. Nevertheless, if simplifi-cation or cost savings is a priority, five of the seven loci (i.e., allloci except CaPMA1 and CaACC1) perform nearly as accu-rately as all seven loci together. Four of the seven loci used inthis study are the same loci found among a set of seven house-keeping genes recently proposed for use in C. albicans MLST(3). Therefore, if assays with this other proposed locus set werecompared to the fingerprinting techniques analyzed here, theresults should be similar to ours. Furthermore, by the use ofcomprehensive MLST data banks, highly informative nucleo-tide polymorphisms may be identified and the many benefits ofMLST could be obtained by detection of just these sites byreal-time PCR (20) and allele-specific probing techniques,such as the molecular beacon or Taqman technology. This

would allow accurate and even quicker analysis of large num-bers of isolates. We are in the process of evaluating whethersuch an approach is effective for C. albicans.

ACKNOWLEDGMENT

We are grateful to David Soll for making available the 29 referenceisolates used in this study.

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