Genetic Structure of Candida glabrata Populations in AIDS and Non-AIDS Patients

The genotypes of 63 strains (11 reference strains and 52 strainsfrom hospitalized patients) of the haploid yeast Candida glabratawere determined from 33 putative gene enzymatic loci. This enabledthe characterization of 26 different multilocus genotypes. Geneticdifferentiation was found between distant hospitals (locatedin Montpellier and Paris, France) but not for other parameters(anatomic origins or human immunodeficiency virus-positive [HIV⁺]and HIV^- patients). Strong nonrandom association between locicould be seen. Such statistical linkages were confirmed uponcomparing the patterns of 14 RAPD [random(ly) amplified polymorphicDNA] primers from 20 of these strains to results obtained frommultilocus enzyme electrophoresis analysis. This finding suggestsa mainly clonal mode of reproduction of C. glabrata. The consequencesof the clonality displayed by C. glabrata populations on theepidemiology of this yeast are also discussed.

INTRODUCTION

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Introduction

Analysis of the population genetics structure of natural populationselucidates the functioning and evolutionary capabilities ofnatural populations. It is particularly appropriate for organismsthat cannot be directly observed (37). Indeed, the genotypicstructure can provide useful clues for estimating the reproductivemode, gene flow, geographical structure, and approximate sizesof reproductive units (10).

Infectious diseases involve organisms whose population biologyis difficult to assess. This is why molecular markers are usefultools in increasing our understanding of their epidemiology(40).

Candidoses are cosmopolitan infections due to yeast-like fungi.These yeasts are responsible for severe mucocutaneous or systemicinfections, particularly in premature infants, pregnant women(in that case the infection is mildly self-limiting), afterinvasive intervention, in AIDS and immunodeficient patients(e.g., cancer, graft, and transplantation patients), and duringchemotherapy (corticoids or antimitotics) and radiotherapy (26).Oropharyngeal candidosis is the earliest and the most commonfungal infection found in AIDS patients (5, 6, 16). Moreover,susceptibility to other mycoses increases with the developmentof AIDS (17). Primary infections are essentially due to Candidaalbicans. After antifungal treatments, relapses are common andare often due to Candida glabrata (also known as Torulopsisglabrata) (2, 7, 18). Furthermore, the use of antifungal azolesseems to enhance the development of such mycoses (8, 15).

C. glabrata is a commensal yeast commonly isolated from thehuman digestive tract. This yeast is considered to be haploidand without a sexual cycle (45). Until know, very little attentionhas been devoted to the genetics of this opportunistic pathogencompared to the related C. albicans (1, 3, 28, 48). Thus, basicinformation on the biology and epidemiology of C. glabrata isneeded.

We report here the enzyme polymorphism observed for 33 putativegene loci in 63 C. glabrata strains in 11 reference strainsand in 52 strains isolated from hospitalized patients (22 inParis and 30 in Montpellier). Furthermore, the patterns of 24RAPD [random(ly) amplified polymorphic DNA] primers from 20of these strains are compared to the multilocus enzyme electrophoresis(MLEE) results. This allows inferences to be made regardingthe genetic structure and reproductive modality displayed byC. glabrata populations with respect to geography, infectedorgans, and the human immunodeficiency virus (HIV) status ofthe patient.

MATERIALS AND METHODS

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Materials and Methods

Origin of the different strains. We used 11 reference strains. Strain 774 comes from the Centraalbureauvoor Schimmelcultures (Delft, The Netherlands), along with thereference CBS 138^T; strains 918, 949, 957, 960, 962, 965, 970,and 971 were provided by the Institut Pasteur (Paris, France)with reference numbers IP 3, 811, 13, 20, 14, 12, 32, and 9,respectively, and strains 1109 and 1110 came from SANOFI (Montpellier,France) with reference numbers SANOFI 2223 and 2231. Informationconcerning the hospital strains (anatomic location, geographicalorigin, antifungal resistance, prophylaxy, and HIV⁺ versus HIV^-status) is presented in Table 1. All strains were identifiedby the ID32 C (bioMérieux SA, Marcy l'Etoile, France)protocol. These strains were isolated, one per person, from52 patients.

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TABLE 1. Sources of clinical isolates of C. glabrata strains^a

Enzymatic and RAPD protocols. Enzymatic extracts were obtained as previously described (28).Starch gel electrophoresis and enzymatic assays were performedas described previously (27, 33). Activity data were obtainedfor the following 26 enzymes: aldolase (EC 4.1.2.13), alpha-glyceraldehydedehydrogenase (EC 1.1.1.8), creatine kinase (EC 2.7.3.2), diaphorase(EC 1.6.4.3), alcohol dehydrogenase (EC 1.1.1.1), esterase (EC3.1.1.1), fructokinase (EC 2.7.1.4), fumarase (EC 4.2.1.2),glucose phosphate isomerase (EC 5.3.1.9), glucose-6-phosphatedehydrogenase (EC 1.1.1.49), isocitrate dehydrogenase (1.1.1.42),leucine aminopeptidase (EC 3.4.11), lactate dehydrogenase (EC1.1.1.27), malic enzyme (EC 1.1.1.40), mannose-6-phosphate isomerase(EC 5.3.1.8), purine nucleoside phosphorylase (EC 2.4.2.1),peptidase A (EC 3.4.13, substrate Val-Leu), peptidase B (EC3.4.13, substrate Leu-Gly-Gly), peptidase C (EC 3.4.13, substrateLys-Leu), peptidase D (EC 3.4.13 substrate Phe-Pro), phosphoglucomutase(EC 2.7.5.1), glyceraldehyde phosphate dehydrogenase (EC 1.2.1.12),octopine dehydrogenase (EC 1.5.1.11), acid phosphatase (EC 3.1.3.2),sorbitol dehydrogenase (EC 1.1.1.14), and superoxide dismutase(EC 1.15.1.1.).

Creatine kinase, fructokinase, leucine aminopeptidase, mannose-6-phosphateisomerase, peptidase 3, phosphoglucomutase, and superoxide dismutaseenzymatic activities were each expressed by two loci. Thus,data were obtained for 33 genetic loci. Alleles were numberedaccording to their anodal mobility.

To test for the possible correlation between two independentsets of genetic markers (MLEE and RAPD), a subset of 20 of theavailable strains was selected. These strains were chosen inorder to examine the existing enzymatic variability (see below).Each strain was cultured in two vials containing Sabouraud agar(Difco) for 48 h at 27°C. Cultures were then suspended andground in a cell homogenizer under CO₂ monitored cold conditions(dry ice). DNA was extracted according to a standard protocol(19). Forty primers belonging to the E and F kits (Operon Technologies,Inc., Alameda, Calif.) were tested. A band was considered polymorphicif it is present (amplified) in at least two strains and notall strains. Among these primers we retained 24 bands (assumedto be loci) that were reproductive (one individual always displayedthe same profile after each PCR). These 24 bands were obtainedby using 14 primers (E4, E6, E14, E17, E18, F1, F2, F4, F6,F10, F12, F13, F14, and F16). Thus, one primer provides oneor more bands that are each interpreted as a locus with twoalleles (band present = 1, band absent = 0). We used this informationfor the comparative analysis between MLEE and RAPD data.

Data analysis. The genetic distance used to build a dendrogram linking thedifferent strains of C. glabrata was the Cavalli-Sforza andEdwards (4) chord distance matrix, which is the most appropriatefor tree construction (38). The distances were computed by theGENETIX v.4 software package (Laboratoire Génome et Populations,CNRS UPR 9060, Université de Montpellier II, Montpellier,France). The distance matrix obtained was then used to builda dendrogram (neighbor-joining method) (35) computed by thesoftware NJTree v2.0 of the RESTSITE v1.1 package (24). Thisdendrogram provided a visual picture to illustrate the geneticstructure of our sample.

Linkage disequilibrium between loci gives a clue regarding thereproductive regime of the population under investigation.

Nonrandom association between each pair of loci was tested bythe exact test for genotypic disequilibrium provided by thesoftware GENEPOP v3.2.a (30). For each locus pair, an unbiasedestimate of the P value of the probability test (or Fisher exacttest) was operated by the Markov chain method (30). The totalnumber of iterations (randomization) was set to 10⁶. The probabilityof each randomized table is computed, and the P value is calculatedas the sum of the probabilities of all tables (with marginalvalues the same as the observed one) with a probability lowerthan or equal to that of the observed table.

Additionally, the level of significance for nonrandom associationbetween multilocus repeated genotypes was tested by the combinatorialprobability of sampling a given genotype as often as or moreoften than that actually observed (d1) (41). A multilocus standardizedindex of linkage disequilibrium I^s_A was also computed by usingLIAN 3.0 software (12), which tests the null hypothesis of nolinkage by a Monte Carlo simulation (10,000 permutations) onthe variance of genetic distances between isolates (V_D) (12,13).

The significance of genetic differentiation between strainsobtained at the two different hospitals, between HIV⁺ and HIV^-patients, or between strains found in the respiratory tractand those obtained in the anal or urogenital spheres was testedby the G-based exact test for population differentiation (11).The test is performed after 15,000 permutations of genotypesbetween samples by the software F-Stat 2.9 (http://www.unil.ch/izea/softwares/fstat.html)(9). For each permutation, the log-likelihood statistic (G)is computed, at each locus, from the allelic contingency tableamong populations. The P value corresponds to the proportionof randomized G that was above or equal to the G of the observeddata. This software was also used to compute F_st (a standardizedmeasure of genetic differentiation) unbiased estimates (42)for each locus and over all loci. The F_st value varies between0 (no differentiation) and 1 (all samples fixed for a differentallele).

Nei's 1972 genetic distance (21) was used for the study of correlationbetween distance matrices because it best estimates the branchlength for electrophoretic data (38). The distances were computedby the GENETIX v.4 software package.

Allelic frequencies cannot be computed for RAPD markers. Forthese markers, the measure of genetic distances between strainswas computed with Nei and Li's distance finding (23). The RAPDistancePackage of Armstrong and coworkers (available from the ResearchSchool of Biological Sciences, Canberra, ACT 2601, Australia[http://life.anu.edu.au/molecular/software/RAPDistance]) wasused. The correlation between the two half matrices obtained(MLEE and RAPD) was then tested by a Mantel test (20), whichis appropriate for matrix comparisons. A mixture of individualsfrom differentiated population may generate linkage disequilibria(Wahlund effect). In order to control for the possible influenceof geographical distances, Mantel tests were also made betweenthe matrix of geographical distances coded 0 (local), 1 (Paris-Delft),2 (Paris-Montpellier), and 3 (Montpellier-Delft) and geneticdistances (MLEE or RAPD). Furthermore, each genetic distancematrix (MLEE and RAPD) was regressed against these geographicaldistances, and the residuals were kept. Theoretically, the residualsrepresent the part of the variance not explained by geographicaldistances. The matrix of these residuals was used for an additionalMantel test, which hopefully corrected for geographical influences.Mantel tests were performed by using GENEPOP v3.2.a.

Since multiple testing enhances type I error, we applied thesequential Bonferroni procedure when required (32). For example,if one kind of test is repeated 100 times on a population thatfulfills the null hypothesis, the definition of statisticalinferences predict that five of these tests will be significantat the 5% level. A technique to avoid this caveat is the sequentialBonferroni procedure, where the desired significant level (say, ${alpha}$ ) is divided by the number of remaining tests. Thus, for n tests,the lowest P value (among the n available) is compared to thecorrected level ${alpha}$ /n, the second lowest P value is compared to ${alpha}$ /(n - 1), etc. The sequential Bonferroni significant P valueswill then be the i + 1 ones that stay below the correspondingcorrected significant level, ${alpha}$ /(n - i). As a complement, theproportion of tests significant at the 5% level was comparedto the expected 0.05 proportion by an exact binomial test performedby using S-Plus 2000 (Professional Release 2; MathSoft, Inc.).This alternative procedure allows testing of whether the proportionof significant tests is equal to or below the 5% expected underthe null hypothesis (at the 5% level of significance). Thisapproach may be useful for procedures involving many tests thatare not very powerful individually (small sample sizes) as inlinkage disequilibrium testing between pairs of loci. In suchcases, indeed, the sequential Bonferroni procedure may be tooconservative.

The power of the tests was evaluated by running simulationsof asexual clonal haploids with the software EASYPOP v1.6 (IZEA;Lausanne University, Lausanne, Switzerland [http://www.unil.ch/izea/softwares/easypop.html]).The computer simulation was performed with an island model (47)of 100 subpopulations of 100 haploid individuals each, witha migration rate of 0.04. The 33 loci (as in our data) displayeda random mutation rate of 10^-5 into five possible allelic states.All of these parameters were found after a trial-and-error processinvolving several simulations with different parameter setsuntil we observed equilibrium values similar to those observedin our real samples in terms of the mean number of polymorphicloci (13.8 versus 13 in the real samples), unbiased heterozygosity(0.088 versus 0.11), and differentiation between samples (F_st= 0.12 versus 0.11). Each population began in a monomorphicstate with a strict clonal mode of reproduction. The simulationran for 10,000 generations (sufficient to reach a stable equilibriumbetween drift, migration, and mutation), after which 30 samplesof 22 and 30 individuals (from Paris and Montpellier, respectively)were randomly sampled from 2 of the 100 subpopulations. Thesesimulations provided a null hypothesis for a case of 100% clonality.In other words, this supplied 30 data sets equivalent to theC. glabrata samples we disposed of but with a 100% clonal modeof reproduction. Such data sets allowed us to test the powerof detection of linkage disequilibria in sample sizes of 22and 30 isolates drawn from a strictly asexual species in orderto compared them to what we observed in C. glabrata isolatesfrom Paris and Montpellier, where the reproductive mode is unknown.

RESULTS

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Results

Genetic variability within C. glabrata. Among the 33 enzymatic loci analyzed, 20 display the same allelefor the 64 strains and 13 are polymorphic (Table 2). The unbiasedestimate of expected heterozygosity (22) is 0.11. This is alow value compared to that reported for C. albicans (0.17 [29]and 0.35 [1]) and could be attributed to the haploid state ofC. glabrata (everything else being equal, haploids display halfthe genes). There were 26 multilocus genotypes (I to XXVI inTable 2), 7 of which are represented by more than one strain(up to 13, genotype X [Table 2]). Figure 1 gives a representationof the genetic relationships between the different strains accordingto their geographical origin, anatomic location, and patientpathology. None of the apparent structures in this dendrogramseems to correlate with any of these parameters (Fig. 1 andsee below).

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TABLE 2. Genotypes (I to XXVII) observed at the different polymorphic loci analyzed^a

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FIG. 1. Genetic relationships between the different strains of C. glabrata grouped according to (i) their geographical origin (Montpellier in Green, Paris in blue, and reference strains in red), (ii) anatomic location (A, bronchial tubes; B, buccal cavity; C, bronchioalveolar liquid; D, pharynx; E, stools; F, urine; and G, vagina), and (iii) patient pathology (HIV⁺, underlined). This is an unrooted phenogram built according to the neighbor-joining method applied to the Cavalli-Sforza and Edwards (4) chord distance matrix.

Genetic structure of different samples of C. glabrata. For this study, reference strains were removed from the analysis.Consequently, Idh (monomorphic in the remaining strains) wasnot considered in the following.

Nonrandom association between loci. In Paris, among the 66 possible pairs of loci, six (9%) displayedsignificant nonrandom association at the 5% level which is notsignificantly different to what is expected under the null hypothesis(exact binomial test, P = 0.15). Nevertheless, one pair (Acp-PepB,P = 0.000000) remained significant after Bonferroni correction( ${alpha}$ ' = 0.05/66 = 0.0008).

In Montpellier, among the 66 possible pairs of loci, 55 displayedenough polymorphism for a genotypic association test to be done.Among these, 19 pairs (35%) displayed significant nonrandomassociation at the 5% level, which is far more than expected(P = 0.000, binomial test); 13 of these remained significantafter sequential Bonferroni corrections (Fig. 2).

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FIG. 2. The eight loci involved in significantly nonrandom pairs at the Bonferroni level. The exact P value for nonrandom association is given for each pair of loci. Note that Acp and Pgm-1 are not significantly linked together but are strongly linked to each of the remaining loci.

Significance for nonrandom association between multilocus repeated genotypes. The four most common multilocus genotypes (Paris genotypes VIIIand XXV and Montpellier genotypes VIII and X) (Table 2) wereanalyzed by this test. In each case the probability obtainedwas highly significant (Table 3). It should be noted that thesegenotypes are frequently found in more than one place (Paris,Montpellier, or within reference strains). For example, genotypeVIII is found in the three groups.

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TABLE 3. Distribution and number of repetitions (n) of multilocus genotypes among Montpellier, Paris, and reference strains^a

Multilocus linkage disequilibrium. The standardized indices of association were 0.0768 and 0.1945for Paris and Montpellier, respectively. The absence of linkagewas strongly rejected in each case (P = 0.0008 and P = 0.0001for Paris and Montpellier, respectively).

Population structure. There was a marginally significant differentiation between Parisand Montpellier over all loci (F_st = 0.11, P = 0.054) (Table4). Three loci (Acp, Est, and Sod [Table 4]) of twelve (25%)displayed a significant F_st that was far more than that expectedunder the null hypothesis (exact binomial test, P = 0.02). Thedifferentiation between strains from HIV⁺ and HIV^- patientscould only be tested in Paris (there was only one HIV^- strainin Montpellier; see Table 1). No differentiation was seen atany locus or overall (F_st = 0.015, P = 0.16) (Table 4). Similarly,anatomic location could only be tested in Paris. Here again,no differentiation was suggested from our sample (F_st = 0, P= 0.56) (Table 4). Nevertheless, a statistical linkage couldbe found between loci. This means that the information carriedby these loci is redundant (correlation between loci) and maybias differentiation analysis. Excluding loci that were linkedin both samples (i.e., Acp, Pep2, Lap1, and Pep3) did not alterour conclusions. The existence of repeated multilocus genotypesmay suggest clonal propagation. It may thus be more appropriateto consider all loci as a whole and each multilocus genotypeas the different allelic states of a single locus. Doing sodid not considerably change the F_st estimate between Paris andMontpellier (F_st = 0.1), but differentiation became highly significant(P = 0.005). HIV status or anatomic location still appearedto be uninfluential (P = 1.0 and P = 0.7, respectively). Itshould be noted, however, that our sample sizes could have onlydetected strong signals. We can thus conclude that no strongdifferences exist between strains found in different body partsor in different immunological contexts.

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TABLE 4. F_st estimate ( ${theta}$ ) and the associated probability required to observe a P value as large as or larger than ${theta}$ obtained between Paris and Montpellier isolates, between HIV⁺ and HIV^- patients, and between strain samples from the respiratory tract (RT) and from the anal and urogenital spheres (AUG) in Paris

Simulation study. For the n = 22 case, among the 30 samples obtained, 28 samples(93%) yielded a higher number of significant genotypic associationtests (at the 5% or sequential Bonferroni levels) than for C.glabrata in Paris. For the n = 30 samples, the proportion ofsamples giving higher significant levels than C. glabrata inMontpellier was 16.6% (five samples) for the 5% level of significanceand 10% (three samples) for the sequential Bonferroni levels.We conclude that the results obtained for C. glabrata do notsignificantly differ from those obtained from this simulatedpurely asexual haploid population. We noticed, however, thatthe Paris sample displays fewer significant tests compared tothe simulation results, in which 20.6% of the tests were significantat the 5% level.

Comparison between the two genetic data sets obtained by MLEE and RAPD. For this study, a subsample of 20 strains (774, 918, 965, 1110,1328, 1379, 1380, 1414, 1464, 1471, 1510, 6033, 6038, 6039,6041, 6043, 6045, 6046, 6048, and 6050), corresponding to 17genotypes, were chosen in order to examine the existing enzymaticvariability presented in Fig. 1. For the computation of geneticdistances, all 33 loci were taken into account. The RAPD patternsobtained (Fig. 3) are presented in Tables 5 and 6. Geographydid not significantly influence genetic distances for enzymes(P = 0.17) or RAPD analysis (P = 0.32) (Mantel tests). Thisresult is in agreement with the low degree of overall loci differentiationpreviously observed. The correlation between the two matricesobtained for enzymes and RAPD is highly significant (Manteltest, P = 0.00009). This was confirmed by the highly significantcorrelation between the two half-matrices (RAPD and enzymes)of residuals corrected for geography (Mantel test, P = 0.00006).

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FIG. 3. RAPD patterns (primers E18 and E4) obtained for different strains of C. glabrata (see Materials and Methods). For instance, E18 displays two bands (loci): E18.1, amplified in strain 6043 but not in strain 1510, which amplified band E18.2. Thus, strain 1510 carries allele 0 at locus E18.1 and allele 1 at E18.2.

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TABLE 5. RAPD profiles obtained with the primers of Kit E (see Materials and Methods) for the different strains of C. glabrata tested

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TABLE 6. RAPD profiles obtained with the primers of Kit F (see Materials and Methods) for the different strains of C. glabrata tested

In agreement with these results, strains sharing an identicalelectrophoretic pattern (strains 1110, 6039, and 6043 for genotypeXXV and strains 1510 and 6038 for genotype VIII) also appearedto have identical RAPD patterns (Tables 5 and 6).

DISCUSSION

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Discussion

The difference observed between hospitals in Paris and Montpellierreveals that the frequency of multilocus genotypes varies inspace and that the "clone flow" is thus restricted to some extent.Nevertheless, the level of differentiation remains low. Withlarger geographical distances, differentiation would probablyhave been much more pronounced, as suggested by mitochondrialDNA data for several strains of C. glabrata from Brazil andthe United States (36).

For the 63 strains of C. glabrata analyzed, our study revealsthe presence of 26 different multilocus genotypes. Among the33 loci used, no heterozygous profile could be found. Consideringthe polymorphism observed for these strains, this result supportsthe haploid chromosomal structure for this yeast, as suggestedby other studies (43, 44, 46).

The results obtained with the genetic analysis of C. glabrataallow inferences to be made about the reproductive modalityof this yeast. Indeed, (i) the evidence of strong nonrandomassociation between pairs of loci or overall loci (ii) the existenceof multilocus repeated genotypes among different patients anddifferent localities, (iii) the demonstration of a strong correlationbetween two independent genetic data sets (MLEE and RAPD), and(iv) the confirmation by RAPD of two multilocus repeated genotypesfound by MLEE strongly support a mainly clonal mode of reproduction.Such a reproductive strategy thus appears frequent in pathogenicfungi (1, 29, 34; but see also reference 39). This would meanthat the multilocus genotype represents the informative andvariable character in yeast populations. This mode of reproduction,already recognized for laboratory-reared strains, is confirmedfor natural populations by the present study. As confirmed byour simulation study, our data set is fully consistent withwhat can be expected from a purely clonal population. This,however, cannot exclude episodic sexuality and its consequenceson clonal stability through time. A very low rate of recombinationcould indeed exist. In particular, this may be the case in Pariswhere statistical association between pairs of loci seemed weakerthan expected with pure clonality.

A statistical linkage between loci may be the consequence ofa physical tight linkage or to epistatic selection. This interpretationis not supported by our results since our loci are expectedto be randomly sampled in the genome. Moreover, the loci involvedin statistical linkages are not necessarily the same in Parisand Montpellier; some multilocus genotypes are repeated in differentsamples (Paris, Montpellier, and reference strains), and a strongcorrelation exists between allozymes and RAPD markers. Theselast observations do not support an effect of biased samplingof C. glabrata in humans (Wahlund effect hypothesis) since geographydoes not seem to be a sufficiently strong structuring factor.Indeed, F_st does not exceed 0.11 between Montpellier and Paris(800 km), and it is not likely that each hospital recruits strainsfrom sufficiently distant areas to promote the required strongWahlund effect, in particular in Montpellier where many pairsof loci displayed highly significant linkage.

Strong genotypic associations are also expected in the caseof the coexistence of numerous and differentiated species ina sample. Although it is difficult to absolutely reject thishypothesis, the lack of any specificity of any clone for anyof the available parameters (organs, immunocompetence, etc.)implies that these putative species share identical ecologicalrequirements. In our view, this hypothesis is not the most parsimoniousavailable.

A clonal genetic structure has many consequences for the epidemiologyof such pathogens. We did not observe any correlation betweenparticular multilocus genotypes and organ specificity, e.g.,the respiratory tract and the anal and urogenitary sphere (Table4) or associated pathology (HIV⁺ or HIV^-). This means that anyclone can be pathogenic in any infection site. In Montpellier,more than one-third of the patients were infected by the samestrain. This suggests that nosocomial infection or frequentinterpatient transfers may be important factors in the transmissionof this yeast. The second point is more likely because manymultilocus genotypes are present in distant places. However,we need data from more strains, sampled both within and outsideof hospitals, to confirm this.

C. glabrata displays a weak susceptibility to fluconazole (8,25, 31), leading to many C. glabrata-associated relapses aftertreatments (46). RFLP typing showed that only specific multilocusgenotypes of C. glabrata survive fluconazole treatment (14).Fluconazole treatments thus favor certain clones against theothers. Our samples did not allow for a real test, but our datado not suggest any correlation between MLEE genotypes and fluconazoleresistance (Table 1 and Fig. 1). The mutation rate of resistancemay be high (appearing in association with many MLEE combinations),or antifungal treatments may be insufficient in the hospitalsinvolved in this study. Sexual reproduction involving resistantclones may prevent resistant genes from being "marked" by otherloci. However, further investigations are needed before definiteconclusions can be drawn.

ACKNOWLEDGMENTS

We thank Patrick Durand for help in genetic distance computationsfor RAPD markers, Austin Burt for very useful comments on anearly version of the manuscript, Phil Agnew for critical readingof the manuscript, and two anonymous referees who helped considerablyto improve the manuscript.

FOOTNOTES

* Corresponding author. Mailing address: Laboratoire d'Immunologie et de Parasitologie, Faculté de Pharmacie, 15Ave. Charles Flahaut, 34060 Montpellier Cedex 1, France. Phone: (33) 467-63-52-02. Fax: (33) 467-41-16-17. E-mail: Jean-Marie.Bastide{at}pharma.univ-montp1.fr.

REFERENCES

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