Figures
Abstract
Genetic diversity analyses were performed by sero-genotyping and multi-locus sequence typing on 252 cryptococcal isolates from 13 HIV-positive Ivorian patients followed-up for cryptococcal meningitis. Antifungal susceptibility analyses were performed according to the CLSI M27A3 method. The majority (67.8%) of the isolates belonged to the Cryptococcus neoformans (serotype A) species complex, with 93% being VNI and 7% being VNII. Cryptococcus deuterogattii VGII (serotype B) represented 16.7% of the strains, while C. neoformans/C. deneoformans VNIII (serotype AD) hybrids accounted for 15.1% of the strains. One strain (0.4%) was not identifiable. Nine different sequence types (STs 5, 6, 23, 40, 93, 207, 311, and a new ST; 555) were identified in the C. neoformans population, while the C. deuterogattii population comprised the single ST 173. The distribution of the strains showed that, while the majority of patients (9/13) harboured a single sequence type, 4 patients showed mixed infections. These patients experienced up to 4 shifts in strain content either at the species and/or ST level during their follow-up. This evolution of diversity over time led to the co-existence of up to 3 different Cryptococcus species and 4 different ST within the same individual during the course of infection. Susceptibility testing showed that all strains were susceptible to amphotericin B while 3.6% of them had a none-wild type phenotype to 5-flucytosine. Concerning fluconazole, 2.9% of C.neoformans serotype A strains and 2.4% of C. deuterogattii had also respectively a none-wild type phenotype to this molecule. All C. neoformans x C. deneoformans serotype AD hybrids had however a wild type phenotype to fluconazole. The present study showed that mixed infections exist and could be of particular importance for care outcomes. Indeed, (i) the different Cryptococcus species are known to exhibit different virulence and different susceptibility patterns to antifungal drugs and (ii) the strains genetic diversity within the samples may influence the susceptibility to antifungal treatment.
Author summary
Cryptococcal meningitis is a neglected fungal disease responsible for 181 000 deaths worldwide in 2014, with 75% of deaths occurring in sub-Saharan Africa. Cryptococcal meningitis is caused by environmental yeasts belonging to the Cryptococcus neoformans/Cryptococcus gattii species complexes. The evolution of the diversity of the yeast populations within the patients and during the course of treatment is poorly understood. Indeed, it was believed for a long time that infections were of a single strain type. It was only recently that the complexity of the yeast diversity during infection began to be assessed. Here, the researchers evaluated the diversity of the Cryptococcus population within Ivoirian patients. The purpose was to generate data about the overall diversity of such yeast in Western Africa where the data are scarce and to better understand the evolution of the pathogen populations during patient follow-up. This last point is particularly important because some species are more virulent or naturally more resistant to antifungal treatments and could be an issue in the case of relapses during care protocols.
Citation: Kassi FK, Drakulovski P, Bellet V, Roger F, Chabrol A, Krasteva D, et al. (2019) Cryptococcus genetic diversity and mixed infections in Ivorian HIV patients: A follow up study. PLoS Negl Trop Dis 13(11): e0007812. https://doi.org/10.1371/journal.pntd.0007812
Editor: Nelesh Premapragasan Govender, National Institute for Communicable Diseases, Johannesburg, South Africa, SOUTH AFRICA
Received: April 4, 2019; Accepted: September 26, 2019; Published: November 18, 2019
Copyright: © 2019 Kassi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Alleles type Sequences were deposited in Genbank under accession numbers: MN431741, MN431742, MN431743, MN431744, MN431745, MN431746, MN431747, MN431748, MN431749, MN431750, MN431751, MN431752, MN431753, MN431754, MN431755, MN431756, MN431757, MN431758, MN431759, MN431760, MN431761, MN431762, MN431763, MN431764, MN431765, MN431766, MN431767, MN431768, MN431769, MN431770, MN431771. ST555 allele combination is accessible at the following URL: http://mlst.mycologylab.org/ Concerning the strains: We nominated an independent administrator/contact at our institution who would be responsible for responding to requests to strains. This contact is Professor Eric Delaporte (eric.delaporte@ird.fr). It is however to be noted that, according to the Nagoya Protocol, the initial entire cultures belong to Ivory Coast which make their availability more difficult. The cloned isolates were selected and characterized in the Laboratoire de Parasitologie et Mycologie médicale, France and are easier to share on demand to the strain administrator aforementioned above.
Funding: The author(s) received no specific funding for this work
Competing interests: The authors have declared no competing interests exist.
Introduction
The Cryptococcus neoformans and Cryptococcus gattii yeast species complexes are the aetiological agents of cryptococcosis [1], a fungal disease affecting mainly immunocompromised hosts [2]. The course of this disease leads in most clinical cases to cryptococcal meningitis (CM), which is often lethal. CM is mainly acquired through inhalation of dehydrated yeast cells and spores from environmental sources, including pigeon excreta, plant debris and decaying wood [3–4]. Cryptococcus may cause pneumonia and is able to disseminate to the central nervous system (CNS), where it infects the brain parenchyma [5]. In 2014, annual fatalities from CM were estimated to be 181 100 deaths globally, with 135 900 deaths occurring in sub-Saharan Africa [2]. Globally, CM results in 15% of AIDS-related mortality, with sub-Saharan Africa bearing the greatest burden of this disease. CM is an excellent metric of HIV (human immunodeficiency virus) treatment programme failure [6]. Indeed, the frequent final outcome in a failed cascade of HIV care is the development of CM because of late diagnosis, no HAART (highly active antiretroviral therapy) access, care breakdown, and virological failure of HAART [2]. Furthermore, the increasing number of people living with other immunodeficiencies, including transplant and cancer patients, represents a growing population at risk for CM [7].
Several molecular methods have been used for the detection of specific genetic sequences of the C. neoformans and C. gattii species complexes. The most commonly used approaches are PCR fingerprinting, PCR-RFLP of the URA5 gene, AFLP and multi-locus sequence typing (MLST) [8–11]. Initially restricted to C. neoformans (with two varieties grubii and neoformans)[12,13] and C. gattii and 2 serotypes [14,15], the taxonomy of C. neoformans/C. gattii species complex was revised recently by Hagen et al. due to these methods. The taxonomy now contains seven species and nine genotypes based on phylogenetic and genotypic studies. C. neoformans variety grubii has been renamed C. neoformans (serotype A, genotype AFLP1/VNI, AFLP1A/VNB/VNII and AFLP1B/VNII). C. neoformans var. neoformans has been renamed to C. deneoformans (serotype D, genotype AFLP2/VNIV). Within the C. gattii species complex, five distinct species have been described, namely, C. gattii (serotype B, genotype AFLP4/ VGI), C. bacillisporus (serotype C, genotype AFLP5/VGIII), C. deuterogattii (serotype B, genotype AFLP6/VGII), C. tetragattii (serotype C, genotype AFLP7/VGIV) and C. decagattii (serotype B, AFLP10/VGIV) [16, 17]. The precise mechanisms that determine the prevalence of the various cryptococcal species are still unknown but seem to be associated with host status, as well as geographical and environmental factors [18]. Cryptococcus neoformans genotypes VNI and VNII are widely distributed throughout the world and are strongly associated with urban areas and bird guano as well as several trees [19], with VNI being the major cause of CM in HIV-infected individuals [20,21]. VNB genotypes have been identified in South Africa, Botswana, DRC, Rwanda and Zambia, where they represent up to 30% of the isolates and are associated with an arboreal environment [20,22]] but also in few other countries [23]. The C. gattii complex species were initially found in tropical and subtropical areas, but currently, the geographic distribution of C. gattii infections has expanded to temperate climate regions, including Canada and the USA [11]. Clinical manifestations in patients with C. gattii infections tend to be more severe than those with C. neoformans. With C. gattii infection, cerebral involvement causes more hydrocephalus, focal CNS signs, ataxia, hearing loss, altered mentation, and neurological sequelae. Simultaneous pulmonary involvement is also observed, and cryptococcomas are associated with a prolonged clinical course and slow response to therapy [24].
Currently, therapeutic management of cryptococcal meningitis (CM) in severely immunosuppressed hosts is formalized around the concepts of induction, consolidation, and maintenance phases. The therapeutic regimen currently recommended by the WHO for the control of CM in HIV patients, particularly during consolidation and maintenance phase, uses a combination of either amphotericin B and 5-flucytosine (5FC) or fluconazole and 5FC, depending on the access to these drugs. In sub-Saharan Africa, amphotericin B and 5FC are rarely or not available. Consequently, fluconazole (FCZ) is the most commonly administered drug for cryptococcosis treatment in this region, with up to 80% of infections treated by FCZ monotherapies [25]. This limited drug arsenal leads to variable prognoses and poor survival outcomes [26]. Furthermore, different antifungal susceptibility patterns have been observed among the cryptococcal species. In general, the C. gattii species complex shows higher minimum inhibitory concentrations (MICs) for azoles than isolates from the C. neoformans species complex [27, 28], making patient care even more difficult in high-burden low-resource countries.
The authors previously reported a high genetic diversity and antifungal susceptibility of C. neoformans/C. gattii species complexes from clinical sources in Yaoundé, Cameroon and Abidjan, and Ivory Coast and showed that C. neoformans (A, AFLP1/VNI) is widespread in the environment and is associated with the majority of cases of cryptococcosis in Ivory Coast [29–31]. During these studies, the authors demonstrated that some patients suffered concurrent infections by different sero-genotypes, including mixed infections by two different Cryptococcus species, C. neoformans AFLP1/VNI and C. deuterogattii AFLP6/VGII [29]. Thus, the possibility of mixed infection must be considered for the management of cryptococcosis. Detection of such infections in samples without follow-up was possible by analysing multiple isolates instead of a single isolate for each clinical sample.
However, little is known about Cryptococcus population diversity evolution in the same HIV-positive patient with cryptococcal disease in follow-up samples over time. The present study analysed the epidemiology of strains from follow-up samples in each patient and between several patients by the same multiple isolate methodology. In addition, the genetic diversity of the Cryptococcus species complex from the current cohort was compared by MLST typing with that of isolates collected from other countries. Susceptibilities of isolated strains to fluconazole and flucytosine, two drugs used during patient infection, and against amphotericin B, the gold standard treatment, were assessed.
Methods
Prospective study protocol: Patient inclusion and strain identification
This prospective study was performed as an ancillary study to the ANRS 12257 Study [32] at the teaching hospital of Treichville, Infectious and Tropical Diseases Unit (SMIT) of Abidjan, Ivory Coast, between May 2014 and September 2015. The included patients were HIV positive, and none had received a systemic antifungal treatment prior to the study. After inclusion, patients received fluconazole (FCZ) (1600 mg per day) for 14 days in combination with flucytosine (100 mg/kg per day) followed by FCZ alone (800 mg per day) for up to 10 weeks of follow-up and FCZ (200 mg/day) until immunity restoration Antiretroviral treatment with emtricitabine, tenofovir and efavirenz started on Day 15 (D15). CM was confirmed by the identification of Cryptococcus in CSF (cerebrospinal fluid) using direct examination with China ink by detection in CSF of the cryptococcal antigen latex agglutination slide tests with Pastorex Crypto Plus kit (Bio-Rad, Marnes-la-Coquette, France) and by positive culture on Sabouraud’s medium. The identification of each strain after culturing was performed via a positive urea–indole test and the commercial identification kit ID32C (Biomerieux, Marcy-l’Étoile, France). The CSF was recovered at regular intervals for each patient: on the first day (D0), the 7th day (D7), the 14th day (D14), the 28th (D28), the 10th week (W10) and more if needed. One patient was resampled in the 26th week following a relapse. For each patient, the entire culture and five isolates of Cryptococcus were recovered as previously described [29–31, 33]. Phenotypic characterization of the Cryptococcus species was achieved by chemotyping in L-canavanine-glycine-bromothymol blue (CGB) agar. CGB agar was used to differentiate C. neoformans complex species and C. gattii complex species as described previously. The blue colour of glycine assimilation on CGB agar indicated a positive reaction caused by the C. gattii species complex, whereas the C. neoformans species complex did not cause a colour change [34].
Demographic, clinical, biological and therapeutic data were collected using a structured form.
Patients, isolates and strains
On 32 HIV-positive patients with cryptococcal meningitis included in the ANRS 12257 study at Treichville site, 13 patients with at least two positive cultures between D0 and W24 were included in our study for a total of 42 samples and thus 252 isolates.
A set of standard laboratory reference strains representing each of the eight major molecular types were used for molecular typing: WM148 (= CBS10085 = ATCC MYA-4564, VNI, serotype A), WM626 (= CBS10084 = ATCC MYA-4565, VNII, serotype A), WM628 (= CBS10080 = ATCC MYA4566, VNIII, serotype AD), WM629 (= CBS10079 = ATCC MYA-4567, VNIV, serotype D), WM179 (= CBS10078 = ATCC MYA-4560, VGI, serotype B), WM178 (= CBS10082 = ATCC MYA-4561, VGII, serotype B), WM161 (= CBS10081 = ATCC MYA-4562, VGIII, serotype B) and WM779 (= CBS10101 = ATCC MYA-4563, VGIV, serotype C)[9].
DNA extraction
Genomic DNA was extracted for each strain and entire culture using extraction kit NucleoSpin blood quick (Macherey-Nagel Gmb and Co. KG, Duren, Germany) with modifications as previously described [29]. One aliquot was used for each of the experiments described in this study.
Molecular typing
Multiplex PCR serotyping.
To determine the molecular type, four primers designed for cloning LAC1 and a pair of primers for CAP64 [35, 36] were used in a slightly modified method as previously described [29, 30].
URA5-RFLP PCR genotyping.
PCR-RFLP analyses were performed using the URA5 and SJ01 primers [29, 30]. The reaction conditions were as follows: initial denaturation (94°C, 2 minutes), 35 cycles of denaturation (94°C, 45 seconds), annealing (61°C, 1 minute) and extension (72°C, 2 minutes), and a final extension cycle (72°C for 10 minutes). Ten microliters of each PCR product was double digested using Sau96I (15 U) and Hhal (15 U) for 5 hours at 37°C, and the digested fragments were visualized on 1.5% agarose gels stained with ethidium bromide [9]. Migration patterns were captured with an Ingenius LR apparatus (Syngene, UK) Molecular profiles obtained via PCR fingerprinting were analysed based on the presence or absence of readily apparent and well-defined bands in the digitized gel images with GeneSnap and Genetool software (Syngene, UK) and integrated in a database using GeneDirectory software (http://www.syngene.com/genedirectory-2/ Syngene, UK).
MultiLocus Sequence Typing (MLST) and analysis.
The International Society for Human and Animal Mycology (ISHAM) MLST consensus schemes described for the C. neoformans and C. gattii species complex was used in this study [10]. The six genes CAP59, GPD, LAC1, PLB1, SOD1, URA5 and the IGS1 region have been partially amplified [10]. PCR amplicons were purified and sequenced with forward primers by Genewiz, London, United Kingdom. Sequences were manually edited and aligned using BioEdit software [37]. Alleles types (AT) and sequences types (ST) were assigned by sequences comparisons with the C. neoformans and C. gattii databases in access at http://mlst.mycologylab.org. DnaSP 5.10 (http://www.ub.edu/dnasp/) [38] was used to determine genetic features. Minimum Spanning Tree (MST) was generated with Phyloviz 2.0 software (http://phyloviz.net/wiki/) using goeBURST algorithm. We compared allelic profiles (ST) obtained in our study among themselves. Then, we compared our allelic profiles with all other ST described for C. neoformans available on mycologylab database. The diagrams show clonal complex (CC) defined by a single locus variant (SLV) between two linked STs [39].
Antifungal susceptibility testing
The in vitro susceptibility profile of Cryptococcus species against antifungal agents was determined using the reference broth microdilution method in accordance with document M27-A3 of the Clinical and Laboratory Standards Institute (CLSI) [40]. The final antifungal concentrations ranged from 0.125 to 16 μg mL-1 for amphotericin B and from 0.25 to 64 μg mL-1 for fluconazole and flucytosine. The minimal inhibitory concentrations (MICs) for fluconazole and flucytosine were defined as concentrations causing a 50% reduction in turbidity compared to the growth of the control at 72 hours. For amphotericin B, the MIC was defined as the concentration resulting in 100% inhibition relative to the growth of the control. Candida krusei ATCC 6258 and Candida parapsilosis ATCC 22019 were used as control strains [40].
For the C. neoformans and C. gattii species complex, no break-points are available to follow, and in this case, we used epidemiological cut-off values to discriminate wild-type strains from mutants with reduced susceptibility to some antifungals [41–44].
Ethics statement
This study was approved by the Ethical Sciences Committees of Life and Health of the Ivory Coast (021/MSLS/CNER-kp). Written inform consent forms were signed by patients or a family member prior to the sample collection and data collected concerning them were anonymized.
Accession numbers
Allele type sequences described in this study were previously deposited at EMBL by Beale et al in 2015 for South African strains [45]. The allele type sequences for Ivory Coast strains from the present study were registered on Genbank under the following accession numbers:
MN431741, MN431742, MN431743, MN431744, MN431745, MN431746, MN431747, MN431748, MN431749, MN431750, MN431751, MN431752, MN431753, MN431754, MN431755, MN431756, MN431757, MN431758, MN431759, MN431760, MN431761, MN431762, MN431763, MN431764, MN431765, MN431766, MN431767, MN431768, MN431769, MN431770, MN431771.
Correspondences for C. neoformans are the following ones:
Cap59 alleles 1, 2 and 7 are referenced respectively under MN431741, MN431742, and MN431743.
GPD1 alleles 1, 3, 9 and 23 are referenced respectively under MN431745, MN431746, MN431747, and MN431748.
IGS1 alleles 1, 10 and 14 are registered respectively under MN431750, MN431751, and MN431752 accession numbers.
LAC1 alleles 2, 3, 5 and 8 are referenced respectively under MN431754, MN431755, MN431756, and MN431757.
PLB1 alleles 1, 2, 4 and 11 are referenced respectively under MN431759, MN431760, MN431761, and MN431762.
SOD1 alleles 1 and 12 are registered respectively under MN431764 and MN431765 accession numbers.
URA5 alleles 1, 2, 4 and 5 are referenced respectively under MN431767, MN431768, MN431769, and MN431770.-
Corresponding accession numbers for C. gattii (ST 173) are: MN431744 for Cap59 allele 4; MN431749 for GPD1 allele 21; MN431753 for IGS1 allele 21; MN431758 for LAC1 allele 4; MN431763 for PLB1 alleles 16; MN431766 for SOD1 allele 93 and MN431771 for URA5 allele 2.
Results
Demographic characteristics of the study population
From May 2014 to December 2015, thirteen HIV-positive patients with CM were included in the study. All patients were infected with HIV type 1, except for one patient, who was infected with HIV types 1 and 2 (patient 6, S1 Table). The male/female ratio was 6/7. The mean age was 43 ± 7 years. The two major reasons for consultation were generalized prurigo (5/13) and significant weight loss (5/13). The other reasons for consultation were cerebellar toxoplasmosis, tuberculosis, fever, ophthalmic zoster, genital herpes, and furunculosis. For each patient, from the CSF, the initial culture and five separate colonies randomly collected from each initial sample were analysed. In total, the authors analysed 42 entire cultures and 210 clones for a total of 252 isolates.
At the beginning of the study, the CD4 count for each patient was <100/mm3, indicating an advanced stage of HIV infection (S1 Table)
Global species and genotype distribution
Among the 252 isolates, the majority (n = 171; 67.8%) belonged to the C. neoformans (serotype A) species complex. The isolates were distributed between 159 VNI (93%) and 12 VNII (7%). C. deuterogattii VGII (serotype B) and C. neoformans/C. deneoformans VNIII (serotype AD) hybrids were identified in 42/252 (16.7%) and 38/252 strains (15.1%), respectively. The content of one isolate (entire culture from patient 4, sampling point D7) was not determined at sero-genotype levels due to mixed profile. This was the only unreadable sample (0.4%) (Fig 1).
(a) Indicate a depletive spinal tap; (b) indicate patient sampled at W9, dead at W10; (c) indicate spinal fluid positive, culture negative in Ivory Coast, positive in Montpellier, (d) indicate a patient sampled outside ANRS protocol because of relapse at W24, (e) indicate a patient sampled outside ANRS protocol with a discharge spinal tap at W26, (f) indicate a patient sampled at D10, death at D14, (g) and light grey indicate negative spinal fluid and cultures, (h) indicate positive spinal fluid, cultures positives in Ivory Coast negative in Montpellier, (i) and middle grey indicate a patient lost to follow up, (j) and strong grey indicate a deceased patient. ND shows undetermined ST. The red bar shows the ANRS 12257 Study Endpoint. MIC of the strains with a not wild type phenotype for fluconazole and flucytosine are shown in bold and in red squares.
Global ST distribution
Among the C. neoformans VNI group, 5 sequence types (ST) were found: ST 5 (n = 115/159, 72.3%), ST 6 (n = 6/159, 3.8%), ST 23 (n = 24/159, 15.1%), ST 93 (n = 2/159, 1.3%) and ST 311 (n = 12/159, 7.5%) (Fig 1). In the C. neoformans VNII group, three STs were identified: ST 40 (n = 9/12, 75%), ST 207 (n = 1/12, 8.3%) and a new allelic type combination described for the first time (n = 2/12, 16.7%), deposited in the mycologylab C. neoformans database and assigned the number 555. This new ST 555 is defined by allele numbers combination 2-3-14-8-11-12-4.corresponding respectively to CAP59, GPD1, IGS1 region, LAC1, PLB1, SOD1 and URA5 genes.
In the C. deuterogattii group, all the strains (n = 42/42) had the same ST 173 MLST allelic profile. STs in the C. neoformans x C. deneoformans VNIII hybrid group were undetermined.
In only one entire culture (patient 4, D7) the MLST profile could not be determined, most likely due to mixed profiles (Fig 1).
Genetic polymorphism analyses
In C. neoformans group, results showed a low diversity with few polymorphic sites (between 7 to 12), low nucleotide (π < 0.003), low allelic type (h, 2 to 4) and low haplotype (0.158< Hd <0.526) diversities (Table 1).
When analysing only the STs found in this study, we found that they are distributed in one CC (ST 23 and 311) and three singletons (ST 5, 6 and 93) for VNI isolates. Distribution of ST for VN II isolates resulted in a single CC. (Fig 2).
Each patient is identified by one colour. ST forming CC are indicated by coloured circles; with a red circle showing CC including VN I isolates and a green circle showing CC including VN II isolates from the present study. Not circled STs form singletons.
The diversity of the C. neoformans population characterized here was then compared with the overall diversity in the C. neoformans database (i.e., 487 STs already present in the database + 1 new ST described in this study). Using a single locus variant (SLV) to determine the clonal complexes (CC), the 488 STs were distributed in 38 CCs and 182 singletons. The strains isolated during this study were then found in 2 distinct CCs according to their genotypes, ST 5, 6, 23, 93 and 311 for VNI isolates and ST 40, 207 and 555 for VNII isolates (S1 Fig).
Concerning the C. deuterogattii group, the population was homogenous with only one ST.
Situation by patient
Species distribution by patient.
Among the 13 patients studied, 11/13 were infected by C. neoformans group yeast during the course of their infection. Eight out eleven of these patients were infected only by this species (patients 5, 6, 7, 8, 9, 11, 12, and 13), while 3/11 had mixed infections involving other species (patients 1, 3 and 4) (Fig 1 and S2 Table).
C. deuterogattii was found in 3/13 patients, with one patient showing a single-species infection (patient 2) and two patients showing a mixed infection (patient 1 and 3). C. neoformans x C. deneoformans hybrids were found in 3/13 patients. One patient harboured a pure infection with the hybrid (patient 10), while two patients (patient 1 and 4) harboured a mixed-species infection (Fig 1 and S2 Table).
ST distribution by patient.
Nine patients (9/13) were infected with a single ST during the course of their infection. Patients 5, 6, 9 and 11 were infected with 100% of isolates belonging to C. neoformans ST 5 while patient 7 and 13 were infected with 100% of C. neoformans ST 23 and 100% of C. neoformans ST 311 isolates respectively. Patient 2 was infected with 100% of C. deuterogattii ST 173 isolates. Patient 10 was also fully infected with strains identified as AD hybrid C. neoformans x deneoformans (Fig 1)). The absence of MLST data for serotype AD prevented us from determining the genetic links between isolates. Four patients were infected with several strains/different STs.
Concerning the four patients with mixed infections, Patient 1 presented 60% of isolates belonging to C. deuterogattii ST 173, alongside C. neoformans ST5 and C. neoformans x C. deneoformans hybridwhile Patient 3 was infected with 50% C. deuterogattii ST 173 and 50% C. neoformans ST 6 isolates. Patient 4 was infected with 50% C. neoformans x C. deneoformans hybrid, alongside C. neoformans ST 23, C. neoformans ST 93, and one isolate whose ST identification failed. Finally, patient 8 had 75% of his strains belonging to C. neoformans ST 40, alongside ST 555 and ST 207 (Fig 1).
Evolution of diversity over time
The aforementioned patients with mixed infections (patients 1, 3, 4 and 8) showed different variations in their strain content between various follow-up dates (Fig 1).
Patient 1 presented 4 shifts in strain content from D0 to W10. At D0, his strain content was C. deuterogattii ST 173 and C. neoformans ST 5. This content changed to pure C. deuterogattii ST 173 at D7. The strain content changed again to C. deuterogattii ST 173 and C. neoformans x C. deneoformans hybrid content at D14 to return to a pure C. deuterogattii ST 173 infection at D28. Finally, the infection in patient 1 consisted of 3 different species in the same sample: C. deuterogattii ST 173, C. neoformans ST 5 and C. neoformans x C. deneoformans hybrid concurrently at W10. Interestingly, for this patient, C. deuterogattii ST 173 was persistent during the whole length of the follow-up. It is also worth noting that the C. neoformans ST 5 strain present early at D0, was not detected between D7 and D28 and was identified again at the W10 follow up point. Patients 3, 4 and 8 also showed a shift in content from D0 to D7. Patient 3’s infection shifted from C. neoformans ST 6 to C. deuterogattii ST 173. Patient 4’s infection strain composition went from full C. neoformans x C. deneoformans hybrid content at D0 to the occurrence of C. neoformans ST 93 strains alongside the hybrid at D7 and changed again to a pure C. neoformans ST 23 at D28. The infection of patient 8 went from C. neoformans ST 40 and ST 207 infection to a C. neoformans ST 40 and ST 555 infection (Fig 1).
Antifungal susceptibility testing
Fig 1 and Table 2 summarize the in vitro susceptibility data for fluconazole and flucytosine obtained from the 252 clinical strains using the broth microdilution method, according to the CLSI M27-A3 protocol.
All isolates had an MIC ≤ 1 μg mL-1 to amphotericin B (Table 2 and S3 Table), with a geometric mean equal to 1 μg mL-1.
A total of 243/252 for flucytosine, (Fig 1 and Table 2). These strains (96.4%) had a wild-type phenotype. Nine (9/252; 3.6%) non-wild type strains with an MIC > 64 μg mL-1 were observed. Four out of nine isolates were hybrid C. neoformans/C. deneoformans types, 2/9 were C. deuterogattii, and 3/9 were C. neoformans. Six of the nine strains came from the same patient. The geometric mean for these clinical strains was equal to 1.18 μg mL-1 (Table 2).
Concerning fluconazole, 166/171 (97.1%) C. neoformans serotype A isolates had MICs ≤ 8 μg mL-1 and thus were wild type phenotype. Five isolates out of 171 (2.9%) had a MIC between 16 and 32 μg mL-1 so a none-wild type phenotype. They were all isolated from the same patient (Patient 11, W20). For the C. deuterogatii serotype B isolates, 41/42 (97.6%) had a wild-type phenotype with a MICs ≤ 32 μg mL-1 and 1/42 (2.4%) had a none-wild type phenotype with MIC > 64 μg mL-1(Fig 1). Finally, for the C. neoformans x C. deneoformans serotype AD hybrids, all proved to be of wild type phenotype with a MIC ≤ 16 μg mL-1.
Global geometric mean for fluconazole was equal to 1.14 μg mL-1 (Table 2).
Discussion
Genetic diversity and analyses of susceptibility to antifungals of Cryptococcus neoformans/Cryptococcus gattii species from serial patient series are usually performed on a single isolate or well isolated single yeast colony by sample. The rationale behind this method is that serial isolates from the same patients belong mainly to the same genotype [46–48]. However, this approach harbours the risk of losing information and missing mixed infections. Moreover, Cryptococcus genetic diversity data are limited in sub-Saharan Africa, from which very few strains have been isolated and characterized.
In this study, the authors decided to apply a multiple isolate analysis (the whole initial culture grown from the CSF sample plus 5 randomly selected colonies) for each sample in order to obtain the largest overview of cryptococcal diversity in the cohort of Ivoirian patients.
First, the species/serotype distribution was analysed, and C. neoformans (serotype A) represented the majority of the isolated strains. This finding is in accordance with most epidemiological studies across the world. Indeed, C.neoformans serotype A forms the majority (72.5 to 96%) of the isolates identified whether in Africa [29, 49], China [50–52], Brazil [53] or Europe [17, 54–56]. A significant number of C. deuterogattii serotype B or C. neoformans x C. deneoformans hybrids serotype AD were also found in this study. In comparison, in most other studies, fewer AD hybrids and fewer serotype B were detected [17, 29, 49–52, 54–56]. These differences may be due to the originality of the sampling strategy in the present study. The serial sampling of patients combined with the analyses of multiple isolates per patient may have allowed us to highlight minor strains hidden in the background during mixed infections cases, which in turn may explain the higher proportion of C. deuterogattii serotype B and C. neoformans x C. deneoformans AD hybrids found here.
Comparison of this study population to the overall described STs showed two different situations for C. neoformans and C. deuterogattii species. In the C. neoformans group, two different genotypes, VNI with 5 different STs (ST 5, 6 23, 93 and 311) and VNII with 3 different STs (ST 40, 207 and 555), were grouped into two separate clonal complexes, one for each genotype. Thus, the C. neoformans population was clonal. Studies referencing the VNI genotype and related ST dispersal are abundant, with the STs found in this study showing a global dispersal. The ST 5 was the dominant ST found in this study. This ST, reported worldwide [19, 45, 51, 57–66], is frequently isolated from clinical samples but also from environmental and veterinary samples [58–60]. Its highest frequencies of detection occur in Asia. In Africa, ST 5 was isolated with variable rates depending on the study [19, 45]. Others STs such as ST 6 and ST 23 have been reported in America (North and South), Asia, Europe and Africa, [45, 57, 62, 64, 67]. ST 93 is frequently described in Asia and South America [48, 57, 62, 68] but seems uncommon in Africa [62]. To date, ST 311 has only been identified in Brazil [69] in both clinical and environmental samples. Finally, ST 23 was identified in South Africa [45] and Uganda [23] as well as in the present study.
The C. deuterogattii (VGII) population was more homogeneous than the C. neoformans population since all strains belonged to the same ST 173. On the contrary to C. neoformans VNI related ST, numerous C. deuterogattii STs seem to be linked specifically to a given geographical region [70–72]. Interestingly, ST 173 was first isolated in only one study from six patients, among whom five were immigrants from Africa to France and one was a resident of Senegal (http://mlst.mycologylab.org/Biolomics.aspx?Table=Sequence%20types%20C.%20gattii) [73]. Our results from Ivory Coast strengthen the hypothesis that ST 173 may be of African origin even if it could become more widely distributed in the future due to population movements. STs for C.neoformans x C. deneoformans hybrids were not determined because of unreadable profiles with the traditional MLST method. New methods to discriminate the hybrids as well as for identifying mixed infections in a single sample described by Chen et al. would be valuable in this situation [74,75].
Concerning the strain diversity in each patient, data in the literature vary based on the methods used. Desnos et al., 2010 [65], for example, recovered mixed cryptococcal infections in up to 18.4% of patients (9/49) by analysing from 4 to 33 single colonies/patients by serotyping and mating-type-specific locus PCR amplification. Previous studies with minisatellite and microsatellite amplifications showed higher levels of mixed infections ranging from 39% to 42% [30, 31] in series without follow-up when analysing 6 isolates per patient. Tomazin et al., 2018 also reported mixed infections within the same patient with serial series and sampling from 2 to 9 isolates per patient either at species, microsatellite genotype or AFLP fingerprinting levels [76]. In the present study, with serial sampling and analysis of 6 isolates, a majority of patients had constant strain content during their available follow-up period, while 4/13 patients were found with mixed species, mixed genotypes or mixed ST infections. Interestingly, two of the patients with constant strain content (patients 6 and 11) showed negative CSF during their follow-up before a relapse of CM with the same strains isolated before the negative culture. Whether the relapse was due to reactivation of the infection rendered dormant due to partially successful antifungal treatment [77] or a reinfection with strains more commonly present in the environment is, however, unclear.
Among the patients with mixed infections, patient 1 showed the highest number of different species by sample with up to 3 different species (C. deuterogattii/C. neoformans/C. neoformans x C. deneoformans hybrid). Such a number of species during mixed infection in the same patient and the same sample has not been described in the literature thus far. Patient 1 also experienced the most numerous switches in ST content. It is interesting to note that some strains present in the initial sampling (C. neoformans ST 5) were lost to detection, only to be found again at the last sampling time point, ten weeks later. This observation could represent a case of reinfection as the time delay of ten weeks between the loss and re-discovery of this ST is consistent with its definition in literature [49]. However, a relapse of infection caused by the same strain, hidden because of population shift during the course of treatment, cannot be excluded as it was shown that a same strain can persist into a patient for over 100 days [78].
Patient 3, in contrast, did not show a mixed infection in the same sample series but between series with a species content change (C. neoformans to C. deuterogattii) during the first week of follow-up. This short timeframe suggests that it is unlikely to be due to reinfection. In contrast, that patient may have been simultaneously infected by both strains with C. deuterogattii later overwhelming C. neoformans. Indeed, the high dose of FCZ treatment started on inclusion may have allowed the emergence of C. deuterogattii yeast due to the lower susceptibility of this species to the antifungal [79,80].
Patient 4 experienced a progressive change in strain content with a full C. neoformans x deneoformans hybrid population on inclusion, turning into a mixed hybrid and C. neoformans ST 93 after one week and ending into 100% C. neoformans ST 23, 3 weeks later. This strain change could be explained by two hypotheses: either the C. neoformans x deneoformans hybrid and ST 93 isolate became significantly reduced in quantity over time in regard to the emerging ST 23 isolates and were missed during cloning at W10, or the initial high dose of fluconazole (1600 mg/day) in the first week of the protocol helped to eliminate the early strains, leaving an available ecological niche for the emergence of the ST23 on late stages.
Finally, patient 8 did not show any mixed infection at the species level. However, he presented a change in STs during his first week of follow-up with VNI ST40 and VNI ST 207 turning into VNI ST40 and VNI ST 555. ST 207 and ST 555 are included in the same clonal complex but differ by only a single nucleotide in the GPD1 sequence. All these results confirm that the analysis of several isolates for each patient sample allows to report a diversity possibly masked by an isolate having a better fitness or over-represented in the initial sample. This sampling approach limits the loss of information regarding minor strains. The largest assessment of cryptococcal genetic diversity is important because it was shown for other yeast, i.e., Candida sp., that mixed infections could lead to treatment complications or failures [81–83] and to the emergence of species or strains resistant to antifungal drugs [84,85].
Finally, susceptibility to fluconazole, flucytosine and amphotericin B was analysed for the 252 isolates. All strains proved to be susceptible to amphotericin B. Very few none-wild type phenotypes to flucytosine were found and numbers were in accordance with previous studies in in Africa [86] and Asia [87]. Concerning fluconazole, very few none-wild type strains were detected either. The overall resistance level to fluconazole is thus lower than what can be found in previous studies in Cameroon [33], Kenya [88], Uganda [89] and South Africa [90]. It is also 3 time lower than the mean resistance rate of 12.4% assessed for the whole African region [91,92] It was proposed that this high resistance rate in Africa may have been due to limited access to amphotericin B, flucytosine or ARTs and to the use of fluconazole in low-dose monotherapy as first-line therapy [93]. Thus, the low resistance level found in the present study could be explained by: i) the high dose fluconazole protocol based on previous empirical trials [94–96]. ii) the fluconazole-flucytosine combination, shown to limit the amplification of resistance [97] iii) the monitoring of the patients to ensure they took their ARV and antifungal treatments correctly. iv) the variation in ECVs between ancient studies [88–90] and more recent recommendations, especially for C. gattii [44].
Because of the high dose of FCZ in the initial treatment followed by lower doses over 20 weeks, MIC increases between the initial and follow-up samples in the same patient were expected [98–100]. It is known that in vitro growth of C. neoformans in the presence of sub lethal concentrations of FCZ induces the selection of resistant colonies with elevated MICs to FCZ [101,102], and a similar increase was shown to occur in infected mice that were treated with FCZ [103]. In this study, no significant increase in the MIC to FCZ was observed over time possibly thanks to the fluconazole-flucytosine combination protocol [97]. However, the sampling strategy allowed us to show that the coexistence of a mix of wild-type and none-wild type strains was possible in the same patient (as described elsewhere [33]) and same sample. In such cases, the MIC ranges showed variations up to 5 dilutions. These variations were observed for isolates including those showing the same sequence type. No correlation between Cryptococcus neoformans VNI and VNII STs, or Cryptococcus deuterogattii VGII ST and an elevated MIC to FCZ was found.
In conclusion, this study showed that mixed infections could be identified at the species level down to the sequence type level, as well as at the susceptibility to antifungal level in the same patients over time. Up to 3 different species were found alongside up to 4 different STs in the same patient. This diversity could be due to reinfections from nearby environmental strains during follow-up, the emergence of minor populations due to antifungal pressure, degradation of patient health or genetic microevolution of the strains. This study provides new data on the Cryptococcus epidemiology in West Africa and Ivory Coast and shows the complexity of the evolution of a cryptococcal population in a pool of patients as well as the various mechanisms leading to this evolution.
Supporting information
S1 Table. Demographic characteristics of the patients and outcome of infection.
https://doi.org/10.1371/journal.pntd.0007812.s001
(DOCX)
S2 Table. Distribution of the Cryptococcus serotypes, genotypes, STs and MICs to antifungal ranges by patients throughout the whole follow up.
MICs ranges to antifungals are expressed in μg mL-1.
https://doi.org/10.1371/journal.pntd.0007812.s002
(DOCX)
S3 Table. Demographic characteristics of the patients, sero-genotyping, ST characterization and MIC (μg mL-1) to amphotericin B for the totality of the strains isolated during the follow up.
(a) Indicate a depletive spinal tap; (b) indicate patient sampled at W9, dead at W10; (c) indicate spinal fluid positive, culture negative in Ivory Coast, positive in Montpellier, (d) indicate a patient sampled outside ANRS protocol because of relapse at W24, (e) indicate a patient sampled outside ANRS protocol with a discharge spinal tap at W26, (f) indicate a patient sampled at D10, death at D14, (g) and light grey indicate negative spinal fluid and cultures, (h) indicate positive spinal fluid, cultures positives in Ivory Coast negative in Montpellier, (i) and middle grey indicate a patient lost to follow up, (j) and strong grey indicate a deceased patient. ND shows undetermined ST. The red bar shows the ANRS 12257 Study Endpoint.
https://doi.org/10.1371/journal.pntd.0007812.s003
(TIF)
S1 Fig. Minimum Spanning Tree showing distribution of the isolates found in Ivorian patients from this study and compared to the global diversity described for C. neoformans in literature.
The figure shows the distribution of the isolates found in the present study when compared to the global diversity of 488 ST forming 38 CC and 182 singletons described for C. neoformans. ST forming CC including all the VN I isolates or including all the VN II isolates found in the present study are surrounded in red and green respectively. The ST in grey are shown the ST described in literature but not found in this study.
https://doi.org/10.1371/journal.pntd.0007812.s004
(PDF)
References
- 1. Kwon-Chung KJ, Fraser JA, Doering TL, Wang Z, Janbon G, Idnurm A, Bahn Y-S. Cryptococcus neoformans and Cryptococcus gattii, the Etiologic Agents of Cryptococcosis. Cold Spring Harb Perspect Med. 2014;4(7): a019760. pmid:24985132
- 2. Rajasingham R, Smith RM, Park BJ, Jarvis JN, Govender NP, Chiller TM, Denning DW, Loyse A, Boulware DR. Global burden of disease of HIV-associated cryptococcal meningitis: an updated analysis. Lancet Infect Dis. 2017;17(8):873–81. pmid:28483415
- 3. Ellis DH, Pfeiffer TJ. Ecology, life cycle, and infectious propagule of Cryptococcus neoformans. Lancet. 1990; 336(8720):923–5. pmid:1976940
- 4. Velagapudi R, Hsueh YP, Geunes-Boyer S, Wright JR, Heitman J. Spores as infectious propagules of Cryptococcus neoformans. Infect Immun. 2009;77(10):4345–55. pmid:19620339
- 5. Zaragoza O. Basic principles of the virulence of Cryptococcus. Virulence. 2019;10(1):490–501. pmid:31119976
- 6. Jarvis JN, Boulle A, Loyse A, Bicanic T, Rebe K, Williams A, Harrison TS, Meintjes G. High ongoing burden of cryptococcal disease in Africa despite antiretroviral roll out. AIDS. 2009;23(9):1182–83. pmid:19451796
- 7. Maziarz EK, Perfect JR. Cryptococcosis. Infect Dis Clin North Am. 2016;30(1):179–206. pmid:26897067
- 8. Meyer W, Marszewska K, Amirmostofian M, et al. Molecular typing of global isolates of Cryptococcus neoformans var. neoformans by polymerase chain reaction fingerprinting and randomly amplified polymorphic DNA-a pilot study to standardize techniques on which to base a detailed epidemiological survey. Electrophoresis. 1999;20:1790–1799. pmid:10435451
- 9. Meyer W., Castañeda A., Jackson S., Huynh M., Castañeda E., & the IberoAmerican Cryptococcal Study Group. Molecular Typing of IberoAmerican Cryptococcus neoformans Isolates. Emerging Infectious Diseases. 2003;9(2):189–95 pmid:12603989
- 10. Meyer W, Aanensen DM, Boekhout T, Cogliati M, Diaz MR, Esposto MC, et al. Consensus multi-locus sequence typing scheme for Cryptococcus neoformans and Cryptococcus gattii. Med Mycol. 2009;47(6):561–70. pmid:19462334
- 11. Hagen F, Illnait-Zaragozi M-T, Bartlett KH, et al. In vitro antifungal susceptibilities and amplified fragment length polymorphism genotyping of a worldwide collection of 350 clinical, veterinary, and environmental Cryptococcus gattii isolates. Antimicrob Agents Chemother. 2010;54:5139–5145. pmid:20855729
- 12. Franzot SP, Salkin IF, Casadevall A. Cryptococcus neoformans var. grubii: separate varietal status for Cryptococcus neoformans serotype A isolates J. Clin. Microbiol. 1999; 37(3): 838–840.
- 13.
Kwon-Chung KJ. Filobasidiella. In: Kurtzman C.P., Fell J.W., Boekhout T.(Editors). The Yeasts–A Taxonomic Study, vol. 3, Elsevier Science, Amsterdam, The Netherlands. 2011; Chapter 114: pp1443–1455
- 14. Kwon-Chung KJ, Boekhout T, Fell JW, Diaz M. Proposal to conserve the name Cryptococcus gattii against C. hondurianus and C. bacillisporus (Basidiomycota, Hymenomycetes, Tremellomycetidae). Taxon 2002;51:804–806.
- 15. Ngamskulrungroj P, Gilgado F, Faganello J, Litvintseva AP, Leal AL, Tsui KM, Mitchell TG, Vainstein MH, Meyer W. Genetic diversity of the Cryptococcus species complex suggests that Cryptococcus gattii deserves to have varieties. PLoS One. 2009;4(6):e5862. Erratum in: PLoS One. 2009;4(7). doi: 10.1371/annotation/348c3375-3918-4e41-bb8c-27aa15d2bdc4. PLoS One. 2009;4(7). doi: 10.1371/annotation/3037bb69-1b8e-4d99-b169-afdf4b74ace2. pmid:19517012
- 16. Hagen F, Hare Jensen R, Meis JF, Arendrup MC. Molecular epidemiology and in vitro antifungal susceptibility testing of 108 clinical Cryptococcus neoformans sensu lato and Cryptococcus gattii sensu lato isolates from Denmark. Mycoses. 2016;59(9):576–84. pmid:27061834
- 17. Hagen F, Lumbsch HT, Arsic Arsenijevic V, Badali H, Bertout S, Billmyre RB, et al. Importance of Resolving Fungal Nomenclature: the Case of Multiple Pathogenic Species in the Cryptococcus Genus. mSphere. 2017;Aug 30;2(4).
- 18. Cogliati M, D'Amicis R, Zani A, Montagna MT, Caggiano G, De Giglio O,et al.Environmental distribution of Cryptococcus neoformans and C. gattii around the Mediterranean basin. FEMS Yeast Res. 2016;16(7). http://dx.doi.org/10.1155/2013/675213
- 19. Chen Y, Litvintseva AP, Frazzitta AE. Comparative analyses of clinical and environmental populations of Cryptococcus neoformans in Botswana. Molecular Ecology. 2015;24,3559–71. pmid:26053414
- 20. Cogliati M. Global Molecular Epidemiology of Cryptococcus neoformans and Cryptococcus gattii: An Atlas of the Molecular Types. Scientifica (Cairo). 2013;675213. pmid:24278784
- 21. Hagen F, Khayhan K, Theelen B, Kolecka A, Polacheck I, Sionov E, Falk R, Parnmen S, Lumbsch HT, Boekhout T. Recognition of seven species in the Cryptococcus gattii/Cryptococcus neoformans species complex. Fungal Genet Biol. 2015;78:16–48. pmid:25721988
- 22. Vanhove M, Beale MA, Rhodes J, Chanda D, Lakhi S, Kwenda G, et al. Genomic epidemiology of Cryptococcus yeasts identifies adaptation to environmental niches underpinning infection across an African HIV/AIDS cohort. Mol Ecol. 2017;26(7):1991–2005. pmid:27862555
- 23. Cogliati M, Zamfirova RR, Tortorano AM, Viviani MA; Fimua Cryptococcosis Network. Molecular epidemiology of Italian clinical Cryptococcus neoformans var. grubii isolates. Med Mycol. 2013;51(5):499–506. pmid:23286351
- 24. Herkert PF, Hagen F, Pinheiro RL, Muro MD, Meis JF, Queiroz-Telles F. Ecoepidemiology of Cryptococcus gattii in Developing Countries. J Fungi (Basel). 2017;3(4).
- 25. Assogba K, Belo M, Wateba MI, Gnonlonfoun DD, Ossou-Nguiet PM, Tsanga BB, Ndiaye M, Grunitzky EK. Neuromeningeal cryptococcosis in sub-Saharan Africa: Killer disease with sparse data. J Neurosci Rural Pract. 2015;6(2):221–224. pmid:25883484
- 26. Sloan DJ, Parris V. Cryptococcal meningitis: epidemiology and therapeutic options. Clin Epidemiol. 2014;6:169–82. pmid:24872723
- 27. Trilles L, Meyer W, Wanke B, Guarro J, Lazéra M. Correlation of antifungal susceptibility and molecular type within the Cryptococcus neoformans/C. gattii species complex. Med Mycol. 2012;50(3)328–32. pmid:21859388
- 28. Gomez-Lopez A, Zaragoza O, Dos Anjos Martins M, Melhem MC, Rodriguez-Tudela JL, Cuenca-Estrella M. In vitro susceptibility of Cryptococcus gattii clinical isolates. Clin Microbiol Infect. 2008;14(7):727–30. pmid:18558948
- 29. Kassi FK, Drakulovski P, Bellet V, Krasteva D, Gatchitch F, Doumbia A et al. Molecular epidemiology reveals genetic diversity amongst 363 strains of the Cryptococcus neoformans and C. gattii species complex in 61 Ivorian HIV positive patients. Mycoses. 2016;59:811–17. pmid:27461533
- 30. Kassi FK, Bellet V, Drakulovski P, Krasteva D, Roger F, Valérie BA et. Comparative typing analyses of clinical and environmental strains of the Cryptococcus neoformans/Cryptococcus gattii species complex from Ivory Coast. J Med Microbiol. 2018;67(1):87–96. pmid:29214970
- 31. Bertout S, Drakulovski P, Kouanfack C, Krasteva D, Ngouana T, Dunyach-Rémy C et al. Genotyping and antifungal susceptibility testing of Cryptococcus neoformans isolates from Cameroonian HIV-positive adult patients. Clin Microbiol Infect. 2013;19(8):763–69. pmid:23033854
- 32.
Chabrol A. 9th IAS Conference on HIV Science, Abs, WEPDB0103, 23–26 July, 2017, Paris, France
- 33. Kammalac Ngouana T, Drakulovski P, Krasteva D, Kouanfack C, Reynes J, Delaporte E, et al. Cryptococcus neoformans isolates from Yaoundé human immunodeficiency virus-infected patients exhibited intra-individual genetic diversity and variation in antifungal susceptibility profiles between isolates from the same patient. J Med Microbiol. 2016;65(7):579–89. pmid:27100672
- 34. Klein KR, Hall L, Deml SM, Rysavy JM, Wohlfiel SL et al. Identification of Cryptococcus gattii by use of L-canavanine glycine bromothymol blue medium and DNA sequencing. J Clin Microbiol. 2009;47: 3669–72. pmid:19794048
- 35. Ito-Kuwa S, Nakamura K, Aoki S, Vidotto V. Serotype identification of Cryptococcus neoformans by multiplex PCR. Mycoses. 2007;50(4):277–281. pmid:17576319
- 36. Ito-Kuwa S, Nakamura K, Valderrama B, Aoki S, Vidotto V, Osafune T. Diversity of laccase among Cryptococcus neoformans serotypes. Microbiol Immunol. 2008;52(10):492–98. pmid:18822083
- 37. Hall TABioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser. 1999;41:95–98.
- 38. Rozas J, Ferrer-Mata A, Sánchez-DelBarrio JC, Guirao-Rico S, Librado P, Ramos-Onsins SE and Sánchez-Gracia A. DnaSP 6: DNA Sequence Polymorphism Analysis of Large Data Sets. Mol Biol Evol. 2017;34: 3299–3302. pmid:29029172
- 39. Ribeiro-Gonçalves B, Francisco AP, Vaz C, Ramirez M and Carriço JA « PHYLOViZ Online: Web-Based Tool for Visualization, Phylogenetic Inference, Analysis and Sharing of Minimum Spanning Trees ». Nucleic Acids Research. 2016; 44(1):246–51.
- 40.
Clinical and Laboratory Standards Institute. Reference Methods for Broth Dilution Antifungal Susceptibility Testing of Filamentous Fungi, Approved Standard. 2nd edition 2008; Wayne PA: Clinical Laboratory Standards Institute.
- 41. Espinel-Ingroff A, Aller AI, Canton E, Castañón-Olivares LR, Chowdhary A et al. Cryptococcus neoformans-Cryptococcus gattii species complex: an international study of wild-type susceptibility endpoint distributions and epidemiological cutoff values for fluconazole, itraconazole, posaconazole, and voriconazole. Antimicrob Agents Chemother. 2012;56:5898–906. pmid:22948877
- 42. Espinel-Ingroff A, Chowdhary A, Cuenca-Estrella M, Fothergill A, Fuller J et al. Cryptococcus neoformans-Cryptococcus gattii species complex: an international study of wild-type susceptibility endpoint distributions and epidemiological cutoff values for amphotericin B and flucytosine. Antimicrob Agents Chemother. 2012;56:3107–113. pmid:22391546
- 43. Pfaller MA, Castanheira M, Messer SA, Moet GJ, Jones RN. Echinocandin and triazole antifungal susceptibility profiles for Candida spp., Cryptococcus neoformans, and Aspergillus fumigatus: application of new CLSI clinical breakpoints and epidemiologic cutoff values to characterize resistance in the SENTRY Antimicrobial Surveillance Program (2009) Diagn Microbiol Infect Dis. 2019;69:45–50.
- 44.
Clinical and Laboratory Standards Institute.M59. Epidemiological Cutoff Values for Antifungal Susceptibility Testing.2nd Edition 2018; Wayne PA: Clinical Laboratory Standards Institute.
- 45. Beale MA, Sabiiti W, Robertson EJ, Fuentes-Cabrejo KM, O'Hanlon SJ, Jarvis JN,et al. Genotypic Diversity Is Associated with Clinical Outcome and Phenotype in Cryptococcal Meningitis across Southern Africa. PLoS Negl Trop Dis. 2015 25;9(6):e0003847. pmid:26110902
- 46. Ormerod KL, Fraser JA. Balancing stability and flexibility within the genome of the pathogen Cryptococcus neoformans. PLoS Pathog. 2013;9(12):e1003764. pmid:24348244
- 47. Martins MA, Pappalardo MC, Melhem MS, Pereira-Chioccola VL. Molecular diversity of serial Cryptococcus neoformans isolates from AIDS patients in the city of São Paulo, Brazil. Mem Inst Oswaldo Cruz. 2007;102(7):777–84. pmid:18094886
- 48. Hatthakaroon C, Pharkjaksu S, Chongtrakool P, Suwannakarn K, Kiratisin P, Ngamskulrungroj P. Molecular epidemiology of cryptococcal genotype VNIc/ST5 in Siriraj Hospital, Thailand. PLoS One. 2017;12(3):e0173744. eCollection 2017. pmid:28323835
- 49. Van Wyk M, Govender NP, Mitchell TG, Litvintseva AP; GERMS SA. Multilocus sequence typing of serially collected isolates of Cryptococcus from HIV-infected patients in South Africa. J Clin Microbiol. 2014;52(6):1921–31. pmid:24648562
- 50. Feng X, Yao Z, Ren D, Liao W, Wu J. Genotype and mating type analysis of Cryptococcus neoformans and Cryptococcus gattii isolates from China that mainly originated from non-HIV-infected patients. FEMS Yeast Res. 2008;8(6):930–8. pmid:18671745
- 51. Dou HT, Xu YC, Wang HZ, Li TS. Molecular epidemiology of Cryptococcus neoformans and Cryptococcus gattii in China between 2007 and 2013 using multilocus sequence typing and the DiversiLab system. Eur J Clin Microbiol Infect Dis. 2015;34(4):753–62. pmid:25471194
- 52. Wu SY, Lei Y, Kang M, Xiao YL, Chen ZX. Molecular characterisation of clinical Cryptococcus neoformans and Cryptococcus gattii isolates from Sichuan province, China. Mycoses. 2015;58(5):280–87. pmid:25808662
- 53. Spina-Tensini T, Muro MD, Queiroz-Telles F, Strozzi I, Moraes ST et al. Geographic distribution of patients affected by Cryptococcus neoformans/Cryptococcus gattii species complexes meningitis, pigeon and tree populations in Southern Brazil. Mycoses. 2017;60:51–58. pmid:27561904
- 54. Hagen F, Illnait‐Zaragozí MT, Meis JF, Chew WHM, Curfs-Breuker I, Mouton JW,AIM Hoepelman AIMet al,. Extensive genetic diversity within the Dutch clinical Cryptococcus neoformans population. J Clin Microbiol. 2012;50: 1918–26. pmid:22442325
- 55. Sanchini A, Smith IM, Sedlacek L, Schwarz R, Tintelnot K, Rickerts V. Molecular typing of clinical Cryptococcus neoformans isolates collected in Germany from 2004 to 2010. Med Microbiol Immunol. 2014;203: 333–40. pmid:24838744
- 56. Dromer F, Mathoulin‐Pélissier S, Launay O, Lortholary O; French Cryptococcosis Study Group. Determinants of disease presentation and outcome during cryptococcosis: the CryptoA/D study. PLoS Med. 2007;4: e21. pmid:17284154
- 57. Ferreira-Paim K, Andrade-Silva L, Fonseca FM, Ferreira TB, Mora DJ, Andrade-Silva J,et al. MLST-Based Population Genetic Analysis in a Global Context Reveals Clonality amongst Cryptococcus neoformans var. grubii VNI Isolates from HIV Patients in Southeastern Brazil. PLoS Negl Trop Dis. 2017;11(1):e0005223. pmid:28099434
- 58. Danesi P, Firacative C, Cogliati M, Otranto D, Capelli G, Meyer W. Multilocus sequence typing (MLST) and M13 PCR fingerprinting revealed heterogeneity amongst Cryptococcus species obtained from Italian veterinary isolates. FEMS Yeast Res. 2014;14(6):897–909. pmid:24981157
- 59. Chen YH, Yu F, Bian ZY, Hong JM, Zhang N, Zhong QS, Hang YP et al. Multilocus Sequence Typing Reveals both Shared and Unique Genotypes of Cryptococcus neoformans in Jiangxi Province, China. Sci Rep. 2018 Jan 24;8(1):1495. pmid:29367679
- 60. Park SH, Choi SC, Lee KW, Kim MN, Hwang SM. Genotypes of Clinical and Environmental Isolates of Cryptococcus neoformans and Cryptococcus gattii in Korea. Mycobiology. 2015;43(3):360–365. pmid:26539057
- 61. Fan X, Xiao M, Chen S, Kong F, Dou HT, Wang H,et al. Predominance of Cryptococcus neoformans var. grubii multilocus sequence type 5 and emergence of isolates with non-wild-type minimum inhibitory concentrations to fluconazole: a multi-centre study in China. Clin Microbiol Infect. 2016;(10):887.e1–887.e9.
- 62. Khayhan K, Hagen F, Pan W, Simwami S, Fisher MC, Wahyuningsih R,et al. Geographically structured populations of Cryptococcus neoformans Variety grubii in Asia correlate with HIV status and show a clonal population structure. PLoS One. 2013 3;8(9):e72222. pmid:24019866
- 63. Choi YH, Ngamskulrungroj P, Varma A, Sionov E, Hwang SM, Carriconde F, et al. Prevalence of the VNIc genotype of Cryptococcus neoformans in non-HIV-associated cryptococcosis in the Republic of Korea. FEMS Yeast Res. 2010;10(6):769–78. pmid:20561059
- 64. Litvintseva AP, Thakur R, Vilgalys R, Mitchell TG. Multilocus sequence typing reveals three genetic subpopulations of Cryptococcus neoformans var. grubii (serotype A), including a unique population in Botswana. Genetics. 2006;172(4):2223–38. pmid:16322524
- 65. Desnos-Ollivier M, Patel S, Spaulding AR, Charlier C, Garcia-Hermoso D, Nielsen K, et al. Mixed infections and In Vivo evolution in the human fungal pathogen Cryptococcus neoformans. MBio. 2010;1(1).
- 66. Sanchini A, Smith IM, Sedlacek L, Schwarz R, Tintelnot K, Rickerts V. Molecular typing of clinical Cryptococcus neoformans isolates collected in Germany from 2004 to 2010. Med Microbiol Immunol. 2014;203(5):333–40. pmid:24838744
- 67. Montagna MT, De Donno A, Caggiano G, Serio F, De Giglio O, Bagordo F, et al. Molecular characterization of Cryptococcus neoformans and Cryptococcus gattii from environmental sources and genetic comparison with clinical isolates in Apulia, Italy. Environ Res. 2018;160:347–52. pmid:29054089
- 68. Simwami SP, Khayhan K, Henk DA, Aanensen DM, Boekhout T, Hagen F, et al. Low diversity Cryptococcus neoformans variety grubii multilocus sequence types from Thailand are consistent with an ancestral African origin. PLoS Pathog. 2011;7(4):e1001343. pmid:21573144
- 69. Andrade-Silva LE, Ferreira-Paim K, Ferreira TB, Vilas-Boas A, Mora DJ, Manzato VM,et al. Genotypic analysis of clinical and environmental Cryptococcus neoformans isolates from Brazil reveals the presence of VNB isolates and a correlation with biological factors. PLoS One. 2018;13(3):e0193237. pmid:29505557
- 70. Firacative C., Ferreira-Paim K., Trilles L., Engelthaler DM and Meyer W. Australia in the global picture of the molecular epidemiology of Cryptococcus gattii molecular type VGII. Microbiology Australia. 2015;67–70.
- 71. Souto AC, Bonfietti LX, Ferreira-Paim K, Trilles L, Martins M, Ribeiro-Alves M, et al. Population Genetic Analysis Reveals a High Genetic Diversity in the Brazilian Cryptococcus gattii VGII Population and Shifts the Global Origin from the Amazon Rainforest to the Semi-arid Desert in the Northeast of Brazil. PLoS Negl Trop Dis. 2016;10(8):e0004885. pmid:27529479
- 72. Maruyama FH, de Paula DAJ, Menezes IG, Favalessa OC, Hahn RC, de Almeida ADBPFet al. Genetic Diversity of the Cryptococcus gattii Species Complex in Mato Grosso State, Brazil. Mycopathologia. 2019;184(1):45–51. pmid:30627957
- 73. Hagen F, Colom MF, Swinne D, Tintelnot K, Iatta R, Montagna MT, et al. Autochthonous and dormant Cryptococcus gattii infections in Europe. Emerg Infect Dis. 2012;18(10):1618–24. pmid:23017442
- 74. Chen Y, Frazzitta AE, Litvintseva AP, Fang C, Mitchell TG, Springer DJ, Ding Y, Yuan G, Perfect JR. Next generation multilocus sequence typing (NGMLST) and the analytical software program MLSTEZ enable efficient, cost-effective, high-throughput, multilocus sequencing typing. Fungal Genet Biol. 2015;75:64–71. pmid:25624069
- 75. Chen Y, Perfect JR. Efficient, Cost-Effective, High-Throughput, Multilocus Sequencing Typing (MLST) Method, NGMLST, and the Analytical Software Program MLSTEZ. Methods Mol Biol. 2017;1492:197–202. pmid:27822866
- 76. Tomazin R, Matos T, Meis JF, Hagen F. Molecular Characterization and Antifungal Susceptibility Testing of Sequentially Obtained Clinical Cryptococcus deneoformans and Cryptococcus neoformans Isolates from Ljubljana, Slovenia. Mycopathologia. 2018;183(2):371–80. pmid:29064061
- 77. Alanio A, Vernel-Pauillac F, Sturny-Leclère A, Dromer F. Cryptococcus neoformans host adaptation: toward biological evidence of dormancy. MBio. 2015;6(2).
- 78. Rhodes J, Beale MA, Vanhove M, Jarvis JN, Kannambath S, Simpson JA, Ryan A, Meintjes G, Harrison TS, Fisher MC, Bicanic T. A Population Genomics Approach to Assessing the Genetic Basis of Within-Host Microevolution Underlying Recurrent Cryptococcal Meningitis Infection. G3 (Bethesda). 2017 Apr 3;7(4):1165–1176. pmid:28188180
- 79. Yang ML, Uhrig J, Vu K, Singapuri A, Dennis M, Gelli A, Thompson GR 3rd. Fluconazole Susceptibility in Cryptococcus gattii Is Dependent on the ABC Transporter Pdr11. Antimicrob Agents Chemother. 2015;60(3):1202–7. pmid:26643330
- 80. Gutch RS, Nawange SR, Singh SM, Yadu R, Tiwari A, Gumasta R, Kavishwar A. Antifungal susceptibility of clinical and environmental Cryptococcus neoformans and Cryptococcus gattii isolates in Jabalpur, a city of Madhya Pradesh in Central India. Braz J Microbiol. 2015;46(4):1125–33. pmid:26691471
- 81. Rossoni RD, Barbosa JO, Vilela SF, dos Santos JD, de Barros PP, Prata MC, Anbinder AL, Fuchs BB, Jorge AO, Mylonakis E, Junqueira JC. Competitive Interactions between C. albicans, C. glabrata and C. krusei during Biofilm Formation and Development of Experimental Candidiasis. PLoS One. 2015;10(7):e0131700. eCollection 2015. pmid:26146832
- 82. Grosset M, Desnos-Ollivier M, Godet C, Kauffmann-Lacroix C, Cazenave-Roblot F. Recurrent episodes of Candidemia due to Candida glabrata, Candida tropicalis and Candida albicans with acquired echinocandin resistance. Med Mycol Case Rep. 2016 7;14:20–23. pmid:27995055
- 83. Barbedo LS, Vaz C, Pais C, Figueiredo-Carvalho MH, Muniz Mde M, Zancope-Oliveira RM, Sampaio P. Different scenarios for Candida parapsilosis fungaemia reveal high numbers of mixed C. parapsilosis and Candida orthopsilosis infections. J Med Microbiol. 2015;64(1):7–17.
- 84. Andes D, Forrest A, Lepak A, Nett J, Marchillo K, Lincoln L. Impact of antimicrobial dosing regimen on evolution of drug resistance in vivo: fluconazole and Candida albicans. Antimicrob Agents Chemother. 2006;50(7):2374–83. pmid:16801415
- 85. Vipulanandan G, Herrera M, Wiederhold NP, Li X, Mintz J, Wickes BL, Kadosh D. Dynamics of Mixed- Candida Species Biofilms in Response to Antifungals. J Dent Res. 2018;97(1):91–98. pmid:28850289
- 86. Nyazika TK, Herkert PF, Hagen F, Mateveke K, Robertson VJ, Meis JF. In vitro antifungal susceptibility profiles of Cryptococcus species isolated from HIV-associated cryptococcal meningitis patients in Zimbabwe. Diagn Microbiol Infect Dis. 2016;86(3):289–292. pmid:27608538
- 87. Pan W, Khayhan K, Hagen F, Wahyuningsih R, Chakrabarti A, Chowdhary A,et al. Resistance of Asian Cryptococcus neoformans serotype A is confined to few microsatellite genotypes. PLoS One. 2012;7(3):e32868. pmid:22427900
- 88. Bii CC, Makimura K, Abe S, Taguchi H, Mugasia OM, Revathi G,et al. Antifungal drug susceptibility of Cryptococcus neoformans from clinical sources in Nairobi, Kenya. Mycoses. 2007;50(1):25–30. pmid:17302744
- 89. Smith KD, Achan B, Hullsiek KH, McDonald TR, Okagaki LH, Alhadab AA et al. ASTRO-CM/COAT Team. Increased Antifungal Drug Resistance in Clinical Isolates of Cryptococcus neoformans in Uganda. Antimicrob Agents Chemother. 2015;59(12):7197–204. pmid:26324276
- 90. Bicanic T, Meintjes G, Wood R, Hayes M, Rebe K, Bekker LG, et al. Fungal burden, early fungicidal activity, and outcome in cryptococcal meningitis in antiretroviral-naive or antiretroviral-experienced patients treated with amphotericin B or fluconazole. Clin Infect Dis. 2007;45(1):76–80. pmid:17554704
- 91. Matos CS, de Souza Andrade A, Oliveira NS, Barros TF. Microbiological characteristics of clinical isolates of Cryptococcus spp. in Bahia, Brazil: molecular types and antifungal susceptibilities. Eur J Clin Microbiol Infect Dis. 2012;31(7):1647–52. pmid:22278291
- 92. Pfaller MA, Diekema DJ, Gibbs DL, Newell VA, Ellis D, Tullio V,et al. Global Antifungal Surveillance Group. Results from the ARTEMIS DISK Global Antifungal Surveillance Study, 1997 to 2007: a 10.5-year analysis of susceptibilities of Candida Species to fluconazole and voriconazole as determined by CLSI standardized disk diffusion. J Clin Microbiol. 2010;48(4):1366–77. pmid:20164282
- 93. Pfaller MA. Antifungal drug resistance: mechanisms, epidemiology, and consequences for treatment. Am J Med. 2012;125(1 Suppl):S3–13.
- 94. Longley N, Muzoora C, Taseera K, Mwesigye J, Rwebembera J, Chakera A, et al. Dose response effect of high-dose fluconazole for HIV-associated cryptococcal meningitis in southwestern Uganda. Clin Infect Dis. 2008 15;47(12):1556–61. pmid:18990067
- 95. Milefchik E, Leal MA, Haubrich R, Bozzette SA, Tilles JG, Leedom JM, McCutchan JA, et al. Fluconazole alone or combined with flucytosine for the treatment of AIDS-associated cryptococcal meningitis. Med Mycol. 2008;46(4):393–95. pmid:18415850
- 96. Murphy RA, Hatlen TJ, Moosa MS. High-Dose Fluconazole Consolidation Therapy for Cryptococcal Meningitis in Sub-Saharan Africa: Much to Gain, Little to Lose. AIDS Res Hum Retroviruses. 2018;34(5):399–403. pmid:29353491
- 97. Stone NR, Rhodes J, Fisher MC, Mfinanga S, Kivuyo S, Rugemalila J, Segal ES, Needleman L, Molloy SF, Kwon-Chung J, Harrison TS, Hope W, Berman J, Bicanic T. Dynamic ploidy changes drive fluconazole resistance in human cryptococcal meningitis. J Clin Invest. 2019;129(3):999–1014. pmid:30688656
- 98. Birley HD, Johnson EM, McDonald P, Parry C, Carey PB, Warnock DW. Azole drug resistance as a cause of clinical relapse in AIDS patients with cryptococcal meningitis. Int J STD AIDS. 1995;6(5):353–355. pmid:8547418
- 99. Davey KG, Johnson EM, Holmes AD, Szekely A, Warnock DW. In-vitro susceptibility of Cryptococcus neoformans isolates to fluconazole and itraconazole. J Antimicrob Chemother. 1998;42(2):217–220. pmid:9738839
- 100. Aller AI, Martin-Mazuelos E, Lozano F, Gomez-Mateos J, Steele-Moore L, Holloway WJ,et al. Correlation of fluconazole MICs with clinical outcome in cryptococcal infection. Antimicrob Agents Chemother. 2000;44(6):1544–48. pmid:10817706
- 101. Xu J, Onyewu C, Yoell HJ, Ali RY, Vilgalys RJ, Mitchell TG. Dynamic and heterogeneous mutations to fluconazole resistance in Cryptococcus neoformans. Antimicrob. Agents Chemother. 2001;45:420–27. pmid:11158735
- 102. Sionov E, Chang YC, Garraffo HM, Kwon-Chung KJ. Heteroresistance to fluconazole in Cryptococcus neoformans is intrinsic and associated with virulence. Antimicrob. Agents Chemother. 2009;53:2804–15. pmid:19414582
- 103. Sionov E, Chang YC, Kwon-Chung KJ. Azole heteroresistance in Cryptococcus neoformans: emergence of resistant clones with chromosomal disomy in the mouse brain during fluconazole treatment. Antimicrob. Agents Chemother. 2013;57:5127–30. pmid:23836187