Abstract
Cryptococcosis is a globally distributed infectious fungal disease. However, much remains unknown about its molecular epidemiology in many parts of the world. In this study, we analyzed 86 clinical Cryptococcus neoformans isolates from 14 regions in Jiangxi Province in south central China. Each isolate was from a different patient and 35 of the 86 (40.7%) patients were infected with HIV. All strains belonged to serotype A and mating type α (MATα). Genotyping based on DNA sequences at seven nuclear loci revealed eight sequence types (STs) among the 86 isolates, including two novel STs that have not been reported from other parts of the world. ST5 was the dominant genotype and our comparative analyses showed that these genotypes in Jiangxi likely originated by dispersal from other regions within and outside of China and/or mutations from another genotype within Jiangxi. Though none of the isolates was resistant to the five tested antifungal drugs (flucytosine, amphotericin B, fluconazole, itraconazole, and voriconazole), obvious differences in their minimum inhibitory concentrations were observed, even among isolates of the same ST. Our results suggest that continuous monitoring should be conducted to understand the changing dynamics of C. neoformans in this and other regions.
Introduction
Cryptococcus is a genus of basidiomycetous fungi1. Two species in this genus, Cryptococcus neoformans and Cryptococcus gattii, are major pathogens of humans and other animals and can cause a diversity of diseases collectively called cryptococcosis1. Each year, approximately 960,000 new cases of cryptococcal meningitis occur in predominantly HIV-infected patients. In regions without access to antiviral and antifungal treatments, ~60% of those with cryptococcal meningitis die soon after infection2. While most of the deadly infections are in Sub-Sahara Africa, several other regions have also reported increasing cases, including China3. According to the latest review, 8,769 cases of cryptococcal infections were reported in China from 1985 to 2010, many of which were in HIV-negative hosts3. For successful control and prevention of cryptococcosis, it’s critical to understand the molecular epidemiology of cryptococcal infections in these emerging regions.
Both C. neoformans and C. gattii have broad geographic distributions and they can grow in a diversity of environments. For example, they are commonly found in soil, pigeon droppings, and debris of trees such as Eucalyptus camaldulensis4–6. Jiangxi Province in south central China has a subtropical environment ideally suited for the growth and reproduction of both C. neoformans and C. gattii, and contains a large number of E. camaldulensis trees6. However, little is known about the populations of these two species in Jiangxi Province. For example, only five clinical strains of C. neoformans from Jiangxi have been reported in previous reports6.
To understand the genotypes and molecular epidemiology of cryptococcal infections in Jiangxi Province, here we analyzed 86 cases of clinical cryptococcosis in patients from different regions of Jiangxi. The isolates were first identified based on the Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS)7,8. The isolates were then analyzed for their mating types, multilocus genotypes derived based on sequencing at seven nuclear loci, and susceptibilities to five antifungal drugs.
The taxonomy and systematics of the human pathogenic Cryptococcus have undergone multiple revisions and a broad consensus is still not available. In this study, we follow the commonly used approach that sub-divide the human pathogenic Cryptococcus into two species complexes, the C. neoformans species complex (CNSC) and the C. gattii species complex (CGSC). CNSC includes three serotypes (serotypes A, D, and AD) and four molecular types (VNI, VNB/VNII, VNIII and VNIV). This species complex is mainly responsible for cryptococcal infections in AIDS patients. CGSC has two serotypes (serotypes B and C), four molecular types (VGI, VGII, VGIII and VGIV), and is geographically relatively limited and more commonly diagnosed in immuno-competent than immuno-compromised individuals9–12. Several molecular techniques have been employed for identifying the molecular types and/or genotypes for strains in these two species complexes, including polymerase chain reaction (PCR) fingerprinting, pulsed-field gel electrophoresis (PFGE), amplified fragment length polymorphism (AFLP), multilocus microsatellite typing (MLMT), repetitive-sequence-based PCR, restriction fragment length polymorphism of the URA5 gene (URA5-RFLP), and multilocus sequence typing (MLST)13. Among these methods, MLST has become the preferred method by the International Society for Human and Animal Mycology (ISHAM)11. The objectives of this study are to analyze the genotypes and antifungal drug susceptibilities of isolates causing cryptococcosis in Jiangxi Province and to compare their genotypes with those from other regions.
Materials and Methods
Cryptococcal Isolates
In this study, 86 isolates of C. neoformans were obtained from patients hospitalized in Jiangxi hospitals from January 2016 to November 2017. These patients came from all major regions of the Province, spanning ~600 km from the south (Ganzhou) to north (Jiujiang) and ~500 km from east (Leping) to west (Pingxiang). The detailed information about each of the samples is presented in Table 1. Request for the clinical isolates and patient information followed institutional guidelines of Nanchang University. The isolates were stored in skim milk at −80 °C until use and were maintained on SDA (Sabouraud Dextrose Agar, 1% yeast extract, 2% peptone, 2% glucose, 1.8% agar) medium at 25 °C during this study for genotyping and MIC testing.
Table 1.
Information of the 86 clinical isolates of Cryptococcus neoformans in Jiangxi Province, China.
| Isolate | Location | Sex | Age | Specimen | Underlying condition | ST |
|---|---|---|---|---|---|---|
| CN9 | Dexing | F | 39 | CSF | HIV(+) | 5 |
| CN6 | Dexing | M | 49 | CSF | Immunocompetent | 5 |
| CN1 | Fengcheng | F | 74 | Blood | Systemic lupus erythematosus | 5 |
| CN8 | Fuzhou | F | 62 | Blood | Anca - associated vasculitis | 5 |
| CN51 | Fuzhou | F | 63 | CSF | Chronic hepatitis | 5 |
| CN12 | Fuzhou | M | 37 | Blood | HIV(+) | 5 |
| CN56 | Fuzhou | M | 31 | Blood | HIV(+) | 5 |
| CN2 | Fuzhou | M | 33 | CSF | HIV(+) | 5 |
| CN26 | Fuzhou | M | 28 | CSF | Immunocompetent | 139 |
| CN69 | Fuzhou | M | 48 | CSF | Nephrotic syndrome | 5 |
| CN45 | Fuzhou | M | 47 | Blood | Unknown | 5 |
| CN76 | Fuzhou | M | 68 | CSF | Chronic hepatitis | 359 |
| CN28 | Ganzhou | M | 18 | Blood | Immunocompetent | 5 |
| CN41 | Ganzhou | M | 64 | CSF | Malignant lymphoma | 31 |
| CN63 | Ganzhou | F | 50 | CSF | Unknown | 5 |
| CN88 | Ganzhou | F | 66 | CSF | Emphysema | 5 |
| CN92 | Ganzhou | M | 57 | CSF | Chronic hepatitis | 5 |
| CN37 | Gaoan | F | 43 | CSF | Unknown | 5 |
| CN14 | Ji’an | F | 48 | CSF | HIV(+) | 5 |
| CN49 | Ji’an | M | 44 | Blood | HIV(+) | 5 |
| CN61 | Ji’an | M | 22 | CSF | HIV(+) | 5 |
| CN21 | Ji’an | M | 43 | Sputum | Unknown | 319 |
| CN50 | Ji’an | F | 36 | CSF | Unknown | 5 |
| CN53 | Ji’an | F | 61 | Blood | Unknown | 5 |
| CN73 | Ji’an | F | 28 | CSF | Kidney transplant | 5 |
| CN74 | Ji’an | M | 67 | CSF | Tuberculosis | 5 |
| CN79 | Ji’an | F | 33 | CSF | HIV(+) | 5 |
| CN94 | Ji’an | F | 51 | Blood | SLE | 359 |
| CN36 | JiuJiang | F | 67 | CSF | Diabetes mellitus | 5 |
| CN31 | Jiujiang | M | 39 | Blood | HIV(+) | 5 |
| CN48 | Jiujiang | F | 69 | CSF | HIV(+) | 5 |
| CN65 | Jiujiang | M | 37 | Blood | HIV(+) | 5 |
| CN68 | Jiujiang | M | 49 | CSF | Immunocompetent | 5 |
| CN64 | Jiujiang | M | 65 | CSF | Unknown | 5 |
| CN86 | Jiujiang | M | 25 | CSF | HIV(+) | 5 |
| CN87 | Jiujiang | M | 62 | CSF | Myasthenia gravis | 5 |
| CN27 | Leping | M | 53 | CSF | Chronic hepatitis | 5 |
| CN19 | Leping | M | 42 | CSF | HIV(+) | 5 |
| CN44 | Leping | M | 38 | CSF | HIV(+) | 5 |
| CN3 | Leping | M | 42 | CSF | Immunocompetent | 186 |
| CN10 | Leping | M | 44 | Blood | Malignant lymphoma | 5 |
| CN34 | Nanchang | M | 38 | CSF | Brain trauma | 5 |
| CN7 | Nanchang | M | 70 | Blood | Chronic hepatitis | 5 |
| CN11 | Nanchang | M | 23 | Blood | HIV(+) | 5 |
| CN22 | Nanchang | M | 49 | CSF | HIV(+) | 5 |
| CN23 | Nanchang | M | 33 | CSF | HIV(+) | 5 |
| CN35 | Nanchang | M | 40 | CSF | HIV(+) | 5 |
| CN58 | Nanchang | M | 26 | CSF | HIV(+) + tuberculosis | 5 |
| CN18 | Nanchang | M | 76 | CSF | Immunocompetent | 5 |
| CN24 | Nanchang | M | 20 | CSF | Immunocompetent | 5 |
| CN13 | Nanchang | M | 52 | CSF | Kidney transplant | 359 |
| CN39 | Nanchang | F | 33 | CSF | Systemic lupus erythematosus | 5 |
| CN16 | Nanchang | M | 38 | Marrow | Tuberculosis | 5 |
| CN57 | Nanchang | F | 74 | CSF | Unknown | 5 |
| CN71 | Nanchang | M | 41 | CSF | HIV(+) | 5 |
| CN81 | Nanchang | M | 48 | CSF | Malignant tumor | 5 |
| CN85 | Nanchang | M | 79 | CSF | Chronic steroid usage | 359 |
| CN93 | Nanchang | M | 51 | CSF | Silicosis | 5 |
| CN46 | Pingxiang | M | 50 | CSF | Unknown | 5 |
| CN29 | Shangrao | M | 65 | Blood | Chronic hepatitis | 5 |
| CN30 | Shangrao | F | 43 | Blood | HIV(+) | 32 |
| CN32 | Shangrao | M | 41 | Blood | HIV(+) | 5 |
| CN33 | Shangrao | F | 38 | Blood | HIV(+) | 5 |
| CN42 | Shangrao | M | 27 | CSF | HIV(+) | 5 |
| CN52 | Shangrao | F | 55 | CSF | HIV(+) | 5 |
| CN54 | Shangrao | M | 45 | CSF | HIV(+) | 5 |
| CN67 | Shangrao | M | 55 | CSF | HIV(+) | 5 |
| CN70 | Shangrao | M | 26 | CSF | HIV(+) | 5 |
| CN40 | Shangrao | M | 29 | CSF | HIV(+) + tuberculosis | 5 |
| CN4 | Shangrao | M | 53 | CSF | Immunocompetent | 5 |
| CN15 | Shangrao | F | 50 | CSF | Unknown | 5 |
| CN75 | Shangrao | F | 61 | CSF | Immunocompetent | 5 |
| CN80 | Shangrao | F | 55 | CSF | HIV(+) | 5 |
| CN84 | Shangrao | M | 62 | CSF | Immunocompetent | 5 |
| CN66 | Xinyu | F | 4 | CSF | Anaphylactoid purpura | 5 |
| CN91 | Xinyu | F | 27 | CSF | HIV(+) | 5 |
| CN17 | Yichun | M | 50 | CSF | Cerebral infarction | 5 |
| CN25 | Yichun | M | 52 | Hydrothorax | Drug taking and diabetes mellitus | 226 |
| CN43 | Yichun | M | 31 | CSF | HIV(+) | 5 |
| CN38 | Yichun | M | 51 | CSF | Nephrotic syndrome | 5 |
| CN60 | Yichun | M | 67 | CSF | Unknown | 5 |
| CN82 | Yichun | M | 17 | CSF | Nephrotic syndrome | 186 |
| CN20 | Yingtan | M | 26 | CSF | HIV(+) | 5 |
| CN55 | Yingtan | M | 61 | CSF | HIV(+) | 5 |
| CN83 | Yingtan | M | 40 | CSF | tuberculosis | 186 |
| CN90 | Yingtan | F | 49 | CSF | HIV(+) | 186 |
DNA Extraction
Genomic DNA was extracted from each isolate following the protocol described by Alessandro et al.14, with slight modifications. Briefly, cells were incubated on SDA agar containing 0.5 M NaCl at 30 °C overnight. Protoplasts were generated by incubating cells in 2 ml of urea buffer (8 M urea, 0.5 M NaCl, 20 mM Tris, 20 mM EDTA, 2% SDS (Sigma, USA), pH 8.0) for 3–4 h at room temperature. The protoplasts were collected by centrifugation and vortexed in 400 μl lysis buffer (1% w/v SDS in TE, pH 7.5). After vortexing, 400 μl of phenol-chloroform (1:1, pH 8.0) and 400 μl of 2-μm acid-washed glass beads were added and further vortexed. The mixes were centrifuged and the extracted DNA was washed with 100% ethanol, re-suspended in 100 μl TE, and then stored at −20 °C.
Identification of Species, Lineages, and Mating Types
To confirm that the isolates all belonged to the human pathogenic Cryptococcus species complexes, we used the MALDI-TOF MS (BioMerieux, Marcy L’Etoile, France), following the protocols described in Mctaggart et al. using the on-plate protein extraction method8. Briefly, isolates were first cultured on SDA and incubated at 30 °C for 24 h. One single colony of each isolate was smeared onto each MALDI-TOF MS analysis plate, and the proteome of each isolate was extracted via 0.5 μl formic acid and 1.0 μl matrix liquid. The protein profile was automatically generated for those proteins with molecular weights ranging from 2 to 20 kDa. Escherichia coli ATCC8739 was used as a quality control.
To identify whether the isolates belonged to either the C. neoformans species complex or the C. gattii species complex, we plated all isolates on L-canavanine-glycine-bromothymol blue agar15, followed by sequencing of all isolates at the SOD1 gene16. The sequences were then compared with those of five strains representing the known molecular types of C. neoformans: WM148 (serotype A, VNI), WM 626 (serotype A, VNII), Bt63 (serotype A, Botswana), WM 628 (serotype D, VNIII), and WM629 (serotype AD, VNIV) as well as those in the GenBank and the ISHAM MLST database. Furthermore, the standard strains H99 (serotype A, MATα), JEC21 (serotype D, MATα), and JEC20 (serotype D, MATa) were used as references to determine the serotype and mating type for each of the isolates, following the methods described by Yan et al. using serotype and mating type-specific primers at the STE20 gene for PCR17. These primers target the STE20Aa, STE20Aα, STE20Da and STE20Dα alleles. After amplification, all the PCR products were electrophoresed on 1% agarose gels in 0.5xTBE buffer at 100 V for 60 min and then visualized under UV light by comparison with their reference strains.
MLST Analysis
Aside from obtaining the SOD1 gene sequence for each of the isolates for species identification, we also obtained the sequences at six other genes as suggested by the ISHAM consensus MLST scheme for C. neoformans and C. gattii11. Briefly, these six DNA fragments were located in the following genes CAP59, GPD1, IGS1, LAC1, PLB1, and URA5. Primers and PCR conditions followed that described in Hiremath et al.18. All sequences were submitted to the National Center for Biotechnology Information (NCBI) database to acquire GenBank accession numbers and the C. neoformans/C. gattii species complex database (http://mlst.mycologylab.com) to obtain sequence type (ST) numbers.
Phylogenetic Analysis
Phylogenetic analysis of the concatenated sequences of seven MLST loci was performed using MEGA version 7.0 software19. A phylogenetic tree was produced by the Neighbor-Joining algorithm using alignments of the concatenated sequences at the seven gene loci from our isolates and two reference strains H99 and WM148.
Comparison with Other Geographic Populations from China
To investigate the potential genetic differences between the Jiangxi population of C. neoformans and those from other geographic regions in China, we extracted all the published genotype information for all the Chinese isolates at the seven sequenced loci from the Cryptococcus MLST database (http://mlst.mycologylab.com). These Chinese populations were then analyzed using the GenAlEx software (version 6.5)20. Two analyses were performed. In the first, the overall genetic variation was partitioned into within and between geographic populations through AMOVA. In the second, the genetic differences between all pairwise geographic populations were analyzed. All regional populations with a sample size of greater than five isolates were included in the above analyses. Statistical significance of the observed genetic differences was determined by 1000 permutations using the GenAlEx software20.
Antifungal Susceptibility Testing
The in vitro antifungal susceptibility testing of all 86 isolates of amphotericin B (AMB), flucytosine (5FC), fluconazole (FLU), voriconazole (VOR), itraconazole (ITR) was performed using the ATBTM FUNGUS-3 kit (BioMerieux, Marcy L’Etoile, France). The minimal inhibitory concentrations (MIC) were determined following instructions provided by the User’s Manual. Candida krusei ATCC6258 and Candida parapsilosis ATCC22019 were used as reference quality controls.
The obtained MIC values were compared to those recommended breakpoints to determine whether the strains were susceptible or resistant to specific antifungal drugs. The MIC breakpoints for fluconazole and flucytosine were ≥16 μg/ml and ≥32 μg/ml respectively as suggested based on the User’s Manual of ATBTM FUNGUS-3. For amphotericin B, we followed the resistance breakpoint of ≥2 μg/ml as suggested by CLSI document M27-A321 and Nguyen et al.22. At present, there are no consensus interpretive breakpoints of ITR and VOR based on the ATBTM FUNGUS-3 system for C. neoformans. Here we follow previous studies and used a MIC ≥ 1 μg/ml as the resistance breakpoint for both ITR and VOR23,24.
Data availability statement
All the data described in this manuscript are presented in the paper (for genotype information and MIC values of all 86 isolates) as well as deposited in the publicly accessible database (http://mlst.mycologylab.com) for all nucleotide sequences.
Statements on study approvals
We confirm that all methods used in this study were carried out in accordance with relevant guidelines and regulations. In addition, all experimental protocols were approved by Nanchang University and that informed consent was obtained from all subjects for the Cryptococcus neoformans isolates analyzed in this study.
Results
Demographic Data of the Clinical Isolates
In total, 86 clinical isolates of C. neoformans were obtained from patients in 14 cities/counties distributed across Jiangxi Province (Table 1). Each of these isolates was from a different patient. Of the 86 isolates, 60 originated from male patients and 26 from female patients. The age distribution of these 86 cases ranged from 4 to 79 years, and the numbers from each age group were as follows: four (≤20 years), 11 (21–30 years), 17 (31–40 years), 22 (41–50 years), 11 (51–60 years), 17 (61–70 years), and four (>70 years). A majority of these isolates were obtained from cerebrospinal fluid (n = 65; 75.5%), followed by blood (n = 18; 20.9%), and one each from bone marrow, sputum and hydrothorax (n = 1 each; 1.2%). Of these 86 isolates, 35 (40.7%) were from HIV-positive individuals, 40 from HIV-negative hosts, and eleven from individuals of unknown disease status. The majority (31) of the 40 HIV-negative hosts (31/86 total hosts, 36.0%) had deficient or suppressed immune systems associated with cancer or liver disease treatments or chronic steroid usage. Only nine hosts (10.5%) had no known risk factors for cryptococcosis (Table 1).
Serotype, Mating Types, and MLST Results
All 86 clinical isolates were identified as C. neoformans serotype A, molecular type VNI, and mating type α. MLST analysis divided the 86 isolates into eight sequence types (STs), including 73 isolates of ST5 (84.9%). Of the remaining 7 STs, two (ST186 and ST359) were represented by four isolates each while the remaining five (ST31, ST32, ST139, ST226, and ST319) were represented by one isolate each. The multilocus sequence types of all 86 strains are presented in Table 1. The 73 isolates with the ST5 multilocus genotype came from all sampled regions in Jiangxi Province. Similarly, the remaining two STs, ST186 and ST359, represented by four isolates each were also distributed broadly, in three regions each. The remaining five isolates each with a different multilocus genotype came from different regions of Jiangxi, including Shangrao (ST32) in the northeast; Fuzhou (ST139) and Ji’an (ST319) in the center; Yichun (ST226) in the west; and Ganzhou (ST31) in the south.
The allelic assignments of our individual gene sequences in the MLST database for each of the eight multilocus sequence types are presented in Table 2. Table 2 also shows the distributions of the individual alleles in the Jiangxi population among all the known sequence types in the MLST database. In total, 18 alleles were found at the seven loci in Jiangxi. Two loci, SOD1 and URA5 were monomorphic in Jiangxi and their alleles (#1 at both loci) were distributed broadly in many other STs within and outside of China. The remaining five loci were polymorphic, with allele numbers ranging from two (CAP59) to six (GPD1). At each of the remaining five loci, the Jiangxi population shared alleles with a diversity of known STs from other geographic regions (Tables 2 and 3). Among these 18 alleles at the seven loci, none was specific to Jiangxi and all have been found elsewhere (Tables 2 and 3).
Table 2.
Allelic assignments of the eight multilocus sequence types found in this study.
| ST | CAP59 1 | GPD1 2 | IGS1 3 | LAC1 4 | PLB1 5 | SOD1 6 | URA5 7 | VN8 |
|---|---|---|---|---|---|---|---|---|
| ST5 | 1 | 3 | 1 | 5 | 2 | 1 | 1 | 1 |
| ST31 | 1 | 1 | 10 | 3 | 2 | 1 | 1 | 1 |
| ST32 | 1 | 1 | 10 | 3 | 4 | 1 | 1 | 1 |
| ST139 | 1 | 6 | 22 | 18 | 4 | 1 | 1 | 1 |
| ST186 | 1 | 26 | 1 | 5 | 2 | 1 | 1 | 1 |
| ST226 | 7 | 3 | 1 | 5 | 2 | 1 | 1 | 1 |
| ST319 | 1 | 23 | 10 | 18 | 4 | 1 | 1 | 1 |
| ST359 | 1 | 25 | 1 | 5 | 2 | 1 | 1 | 1 |
1CAP59: Allele #1 has been found in 139 known STs; allele #7 in 55 STs.
2GPD1: Allele #1 has been found in 106 known STs; allele #3 in 32 STs; allele #6 in 6 STs; allele #23 in 20 STs; allele #25 in one ST (i.e. ST359); and allele #26 in one ST (i.e. ST186).
3IGS1: Allele #1 has been found in 124 known STs; allele #10 in 33 STs; allele #22 in one ST (ST139).
4LAC1: Allele #3 has been found in 65 known STs; allele #5 in 31 STs; and allele 18 in 39 STs.
5PLB1: Allele #2 has been found in 68 known STs; allele #4 in 71 STs.
6SOD1: allele #1 has been found in 183 STs.
7URA5: allele #1 has been found in 91 STs.
8VN: These eight STs found in Jiangxi are among 487 total STs in the VNI molecular type in the MLST database accessed on September 16, 2017.
Table 3.
Summary distributions of the eight sequence types identified in Jiangxi Province in other parts of the world.
| ST | Geographic location | Percentage of the population | ||
|---|---|---|---|---|
| ST5 | Asia | China | Beijing | 30.4% (34/112)13,34 |
| Shanghai | 72.7% (16/22)33 | |||
| Sichuan Province | 89.5% (119/133)35,39 | |||
| Guangdong Province | 87.1% (27/31)33 | |||
| Henan Province | 93.3% (14/15)34 | |||
| Heilongjiang Province | 76.0% (19/25)39 | |||
| Liaoning Province | 83.3% (10/12)39 | |||
| Jiangxi Province | 84.9% (73/86) | |||
| Hong Kong | 85.7% (12/14)33 | |||
| Japan | 61.4% (51/83)30,33 | |||
| Thailand | 13.8% (41/297)32,33,40 | |||
| South Korea | 56.2% (9/16)37 | |||
| Vietnam | 47.8% (65/136)41 | |||
| United States of America | 28.7% (58/202)33,42,43 | |||
| Europe | 11.3% (8/71)33,42,44 | |||
| Brazil | 2.1% (3/144)42 | |||
| South Africa | 12% (28/230)33,42,45 | |||
| ST31 | Asia | China | Beijing | 49.1% (55/112)13,34 |
| Hebei Province | 8.6% (3/35)39 | |||
| Henan Province | 6.7% (1/15)34 | |||
| Heilongjiang Province | 4.0% (1/25)39 | |||
| Liaoning Province | 8.3% (1/12)39 | |||
| Sichuan Province | 7.5% (10/133)35,39 | |||
| Jiangxi Province | 1.2% (1/86) | |||
| Japan | 1.2% (1/83)33 | |||
| Thailand | 2.0% (6/297)32,33 | |||
| India | 11.5% (7/61)33 | |||
| South Africa | 0.4% (1/230)45 | |||
| Brazil | 2.1% (3/144)42 | |||
| ST32 | Japan | 1.2% (1/83)30 | ||
| United States of America | 0.5% (1/202)43 | |||
| South Africa | 8.3% (16/230)33,45 | |||
| Europe | 1.4% (1/71)42 | |||
| Brazil | 2.1% (3/144)42 | |||
| Vietnam | 5.1% (7/136)41 | |||
| Thailand | 0.3% (1/297)40 | |||
| Jiangxi Province | 1.2% (1/86) | |||
| ST186 | Shanghai | 4.5% (1/22)33 | ||
| Jiangxi Province | 4.7% (4/86) | |||
| ST139 | Africa | Unknown frequency33 | ||
| Jiangxi Province | 1.2% (1/86) | |||
| ST359 | Zhejiang Province | 9.1%(1/11)35 | ||
| Hebei Province | 2.9%(1/35)35 | |||
| Jiangxi Province | 4.7% (4/86) | |||
| ST319 | Novel, Jiangxi Province | 1.2% (1/86) | ||
| ST226 | Novel, Jiangxi Province | 1.2% (1/86) | ||
Among the eight multilocus STs in our Jiangxi population of C. neoformans, six (ST5, ST31, ST32, ST139, ST186, and ST359) have been reported previously from other geographic areas (Table 3). The remaining two genotypes (ST226 and ST319) have only been found in our study population. The geographic distributions of these eight STs are shown in Table 3. Of the six shared STs between Jiangxi and other regions, three (ST5, ST31, and ST32) have been found in multiple continents/countries. For example, ST5 has been reported from the US, Europe, Brazil, South Africa, and several countries in eastern and southeastern Asia. The high prevalence of ST5 in the Jiangxi population is consistent with what has been reported previously from other parts of China and China’s neighbouring countries, such as Korea, Japan, and Vietnam. The remaining three STs (ST139, ST186, and ST359) were geographically unique, had been reported so far only from Africa, Shanghai and Sichuan Province in China, respectively.
Phylogenetic Analysis
To further reveal the relationships among the isolates and genotypes, we conducted a Neighbour-joining analysis of the concatenated gene sequences at the seven MLST loci (Fig. 1). Here, only one representative strain of each of the eight sequence types was included in this analysis to allow better visualization. Two reference strains H99 and WM148, both of the VNI molecular type group, were also included (Fig. 1). Our analysis showed that ST5, ST186, and ST359 were genetically very similar, differ from each other by one to a few nucleotides at one (GPD1) of the seven sequenced loci (Fig. 1 and Table 2). Similarly, ST31 and ST32 were very close to each other, differed from each other by a few nucleotides at the PLB1 locus. Overall, these five STs formed a tight cluster with each other. In contrast, the other three STs (ST139, ST226, and ST319) were more distantly related to each other and to those five STs described above based on the concatenated gene sequences at these seven loci.
Figure 1.
Phylogenetic tree constructed using the Neighbour-joining method, based on the concatenated sequences at seven MLST loci. Only one representative isolate of each ST from Jiangxi Province is shown here. Two reference strains (WM148 and H99) of VNI are included for comparisons.
Relationships Among Geographic Populations of C. neoformans in China
The multilocus genotypes of all isolates from China in the Cryptococcus MLST database were retrieved. A total of 385 isolates from 27 provinces/municipalities in China have been deposited in the database, including the 86 isolates from Jiangxi Province in our study. Among the 27 geographic populations, 12 had isolates of less than five each (most of these 12 populations had only 1–2 isolates each!) and these populations were excluded from our population genetic comparisons. The remaining 15 populations included a total of 364 isolates (Table 4). Our analyses revealed that overall, geographic separation contributed significantly to the total observed genetic variations of the Chinse population of C. neoformans. Specifically, AMOVA result showed that about 65% of the observed genetic variation were due to geographic separation while 35% was found within geographic populations (P < 0.001). Among the seven loci, five (GPD1, IGS1, LAC1, SOD1, and URA1) showed significant geographic differentiations while the remaining two (CAP59 and PLB1) showed no significant differentiations (detailed data not shown). Our further analyses identified that the observed genetic differentiations were mostly due to the genetic uniqueness of the population from Beijing (Table 4). Of the remaining 91(14 × 13/2) pairwise comparisons, only the Jiangxi-Sichuan populations showed statistically significant genetic differentiation (Table 4).
Table 4.
Evidence for genetic differentiation among geographic populations of C. neoformans in China.
| BJ (112) | JX (86) | GD (31) | SH (22) | SC (19) | HN (15) | HK (14) | HEB (13) | ZJ (11) | JS (8) | SD (8) | HUB (7) | LN (7) | AH (6) | SX (5) | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Beijing (BJ) | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.001 | 0.002 | |
| Jiangxi (JX) | 0.426 | 0.379 | 0.225 | 0.012 | 0.334 | 0.118 | 0.176 | 0.259 | 0.336 | 0.355 | 0.344 | 0.331 | 0.324 | 0.295 | |
| Guangdong (GD) | 0.382 | 0.000 | 0.422 | 0.059 | 0.359 | 0.101 | 0.429 | 0.310 | 0.243 | 0.313 | 0.266 | 0.251 | 0.212 | 0.182 | |
| Shanghai (SH) | 0.289 | 0.009 | 0.000 | 0.273 | 0.390 | 0.383 | 0.304 | 0.327 | 0.354 | 0.310 | 0.346 | 0.363 | 0.313 | 0.263 | |
| Sichuan (SC) | 0.195 | 0.093 | 0.081 | 0.000 | 0.360 | 0.347 | 0.196 | 0.270 | 0.292 | 0.127 | 0.369 | 0.139 | 0.450 | 0.516 | |
| Henan (HN) | 0.337 | 0.000 | 0.000 | 0.000 | 0.021 | 0.222 | 0.525 | 0.161 | 0.332 | 0.363 | 0.294 | 0.305 | 0.270 | 0.249 | |
| Hongkong (HK) | 0.323 | 0.031 | 0.041 | 0.005 | 0.026 | 0.000 | 0.503 | 0.489 | 0.507 | 0.284 | 0.377 | 0.407 | 0.139 | 0.063 | |
| Hebei (HEB) | 0.369 | 0.019 | 0.002 | 0.008 | 0.069 | 0.000 | 0.007 | 0.466 | 0.397 | 0.399 | 0.321 | 0.333 | 0.312 | 0.282 | |
| Zhejiang (ZJ) | 0.379 | 0.000 | 0.000 | 0.007 | 0.085 | 0.000 | 0.015 | 0.000 | 0.421 | 0.711 | 0.487 | 0.636 | 0.573 | 0.313 | |
| Jiangsu (JS) | 0.380 | 0.000 | 0.000 | 0.000 | 0.080 | 0.000 | 0.009 | 0.000 | 0.000 | 1.000 | 0.485 | 0.478 | 0.440 | 0.001 | |
| Shandong (SD) | 0.381 | 0.000 | 0.000 | 0.011 | 0.083 | 0.000 | 0.019 | 0.000 | 0.006 | 0.000 | 0.720 | 0.738 | 0.692 | 0.406 | |
| Hubei (HUB) | 0.356 | 0.000 | 0.000 | 0.000 | 0.043 | 0.000 | 0.000 | 0.000 | 0.000 | 0.020 | 0.001 | 1.000 | 0.740 | 0.422 | |
| Liaoning (LN) | 0.377 | 0.000 | 0.000 | 0.006 | 0.074 | 0.000 | 0.000 | 0.000 | 0.013 | 0.020 | 0.001 | 0.000 | 0.728 | 0.423 | |
| Anhui (AH) | 0.313 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.026 | 0.051 | 0.007 | 0.002 | 0.002 | 0.473 | |
| Shanxi (SX) | 0.358 | 0.000 | 0.000 | 0.000 | 0.027 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
The pairwise population FST values are shown below diagonal. The probability of the observed FST values being statistically significant is shown above diagonal, with a P value of <0.05 rejecting the null hypothesis that the two compared populations are genetically similar to each other.
The abbreviations on the top row are the same as those in the left column. Numbers in parenthesis of the top row are the numbers of isolates from each of the geographic populations.
Antifungal Susceptibility
The antifungal drug susceptibility results are presented in Table 4. Our comparisons with recommended resistance breakpoints for these drugs indicated that all 86 cryptococcal isolates were susceptible to 5FC, AMB, FCA, ITR, and VRC. Even though no drug resistant cryptococcal isolates were found among these 86 isolates, there are several noteworthy features. First, variations in MIC values were found for all five tested drugs, with as high as 4-fold differences for itraconazole and 8-fold differences for fluconazole and voriconazole. Second, the differences in MICs were not associated with sequence types. For example, strains in ST5 had a range of MIC values similar to those observed in the overall population. Similarly, the MICs of other seven STs were within the range shown by strains of ST5. Third, strains with relatively high MIC values were broadly distributed. For example, five strains with fluconazole MICs of 8 µg/ml were found in four cities/counties (Shangrao, Leping, Yichun, and Nanchang) (Tables 1 and 5). Fourth, there were significant positive correlations in MIC values among the three triazole drugs in the Jiangxi population of C. neoformans. Specifically, the Pearson’s correlation coefficients were 0.781, 0.598, and 0.686 respectively for FCA vs. ITR, FCA vs. VRC, and ITR vs. VRC (p values all smaller than 0.001). Finally, despite not being called drug resistant, among the 86 isolates, one (CN29, ST5) showed consistently high MIC values for all five drugs.
Table 5.
Susceptibilities of the 86C. neoformans isolates from Jiangxi Province against five common antifungal drugs.
| Isolate | Location | ST1 | 5FC2 | AMB3 | FCA4 | ITR5 | VRC6 |
|---|---|---|---|---|---|---|---|
| CN6 | Dexing | 5 | <4 | <0.5 | 1 | 0.125 | 0.06 |
| CN9 | Dexing | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN1 | Fengcheng | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN12 | Fuzhou | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN2 | Fuzhou | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN26 | Fuzhou | 139 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN45 | Fuzhou | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN51 | Fuzhou | 5 | <4 | <0.5 | 2 | 0.25 | 0.25 |
| CN56 | Fuzhou | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN69 | Fuzhou | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN8 | Fuzhou | 5 | <4 | <0.5 | 2 | 0.125 | 0.125 |
| CN76 | Fuzhou | 359 | <4 | <0.5 | 1 | 0.125 | 0.06 |
| CN28 | Ganzhou | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN41 | Ganzhou | 31 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN63 | Ganzhou | 5 | <4 | <0.5 | 2 | 0.25 | 0.25 |
| CN88 | Ganzhou | 5 | <4 | <0.5 | 1 | 0.125 | 0.06 |
| CN92 | Gaozhou | 5 | <4 | <0.5 | 1 | 0.125 | 0.125 |
| CN37 | Gaoan | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN14 | Ji’an | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN21 | Ji’an | 319 | <4 | <0.5 | 4 | 0.125 | 0.25 |
| CN49 | Ji’an | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN50 | Ji’an | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN53 | Ji’an | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN61 | Ji’an | 5 | <4 | <0.5 | 2 | 0.25 | 0.25 |
| CN73 | Ji’an | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN74 | Ji’an | 5 | <4 | <0.5 | 2 | 0.125 | 0.125 |
| CN79 | Ji’an | 5 | <4 | <0.5 | 1 | 0.125 | 0.06 |
| CN94 | Ji’an | 359 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN31 | Jiujiang | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN36 | JiuJiang | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN48 | Jiujiang | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN64 | Jiujiang | 5 | <4 | <0.5 | 2 | 0.125 | 0.125 |
| CN65 | Jiujiang | 5 | <4 | <0.5 | 2 | 0.25 | 0.25 |
| CN68 | Jiujiang | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN86 | Jiujiang | 5 | <4 | <0.5 | 1 | 0.125 | 0.125 |
| CN87 | Jiujiang | 5 | <4 | <0.5 | 4 | 0.125 | 0.25 |
| CN10 | Leping | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN19 | Leping | 5 | <4 | <0.5 | 8 | 0.5 | 0.25 |
| CN27 | Leping | 5 | 4 | 0.5 | 2 | 0.25 | 0.06 |
| CN3 | Leping | 186 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN44 | Leping | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN11 | Nanchang | 5 | <4 | 1 | 4 | 0.25 | 0.125 |
| CN13 | Nanchang | 359 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN16 | Nanchang | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN18 | Nanchang | 5 | <4 | <0.5 | 8 | 0.5 | 0.5 |
| CN22 | Nanchang | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN23 | Nanchang | 5 | <4 | 0.5 | 2 | 0.25 | 0.125 |
| CN24 | Nanchang | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN34 | Nanchang | 5 | <4 | <0.5 | 4 | 0.125 | 0.125 |
| CN35 | Nanchang | 5 | <4 | <0.5 | 2 | 0.25 | 0.25 |
| CN39 | Nanchang | 5 | <4 | <0.5 | 1 | 0.125 | 0.06 |
| CN57 | Nanchang | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN58 | Nanchang | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN7 | Nanchang | 5 | <4 | <0.5 | 2 | 0.125 | 0.125 |
| CN71 | Nanchang | 5 | <4 | <0.5 | 2 | 0.25 | 0.06 |
| CN81 | Nanchang | 5 | <4 | <0.5 | 1 | 0.25 | 0.125 |
| CN85 | Nanchang | 359 | <4 | <0.5 | 2 | 0.125 | 0.125 |
| CN93 | Nanchang | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN46 | Pingxiang | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN15 | Shangrao | 5 | <4 | 1 | 4 | 0.125 | 0.06 |
| CN29 | Shangrao | 5 | 4 | 1 | 8 | 0.5 | 0.25 |
| CN30 | Shangrao | 32 | <4 | 0.5 | 4 | 0.25 | 0.125 |
| CN32 | Shangrao | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN33 | Shangrao | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN4 | Shangrao | 5 | 4 | <0.5 | 1 | 0.125 | 0.06 |
| CN40 | Shangrao | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN42 | Shangrao | 5 | 4 | <0.5 | 4 | 0.25 | 0.125 |
| CN52 | Shangrao | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN54 | Shangrao | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN67 | Shangrao | 5 | <4 | <0.5 | 2 | 0.25 | 0.25 |
| CN70 | Shangrao | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN75 | Shangrao | 5 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN80 | Shangrao | 5 | <4 | <0.5 | 1 | 0.125 | 0.06 |
| CN84 | Shangrao | 5 | <4 | <0.5 | 2 | 0.125 | 0.125 |
| CN66 | Xinyu | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN91 | Xinyu | 5 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN17 | Yichun | 5 | <4 | <0.5 | 8 | 0.5 | 0.25 |
| CN25 | Yichun | 226 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN38 | Yichun | 5 | <4 | <0.5 | 2 | 0.25 | 0.125 |
| CN43 | Yichun | 5 | <4 | <0.5 | 8 | 0.5 | 0.25 |
| CN60 | Yichun | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN82 | Yichun | 186 | <4 | <0.5 | 2 | 0.125 | 0.06 |
| CN20 | Yingtan | 5 | <4 | 1 | 4 | 0.125 | 0.125 |
| CN55 | Yingtan | 5 | <4 | <0.5 | 4 | 0.25 | 0.25 |
| CN83 | Yingtan | 186 | <4 | <0.5 | 4 | 0.25 | 0.125 |
| CN90 | Yingtan | 186 | <4 | <0.5 | 1 | 0.125 | 0.125 |
1ST: sequence type as determined based on the combined sequences at the seven loci.
25FC: 5-Flucytocine.
3AMB: Amphotericin B.
4FCA: Fluconazole.
5ITR: Itriconazole.
6VRC: Voriconazole.
Discussions
In this study, we analyzed the genotypes and drug susceptibility profiles of 86 isolates obtained from across Jiangxi Province in China. Our analyses identified eight multilocus sequence types, with five of which represented by only one isolate each. Of the eight STs found in our sample from Jiangxi, six have been reported from other geographic regions while two were novel, identified so far only in Jiangxi Province. The dominant sequence type in Jiangxi, ST5, is a broadly distributed genotype and has been commonly found in other parts of China as well as in the Far East. These eight genotypes show several types of allelic and phylogenetic relationships. Our antifungal drug susceptibility test results showed that none of the 86 strains were resistant to the five tested antifungal drugs. However, some of the strains showed relatively high MIC values. Below we discuss the relevance of our results to earlier studies and the potential implications of these results to the management of cryptococcosis in Jiangxi Province.
Although a considerable amount of information exists on the epidemiology and molecular typing of C. neoformans strains in China, there is very little data on cryptococcosis from Jiangxi Province. Studies from the Chinese Mainland, Taiwan, and Hong Kong indicated that the prevalence of cryptococcosis in HIV/AIDS patients ranged from 12.9% to 24.7%, which is significantly lower than that of many other regions in the world25. While the total number of HIV-positive patients are not known in Jiangxi Province, HIV-positive patients account for over 40% of the sources of our strains in this study. In contrast, the percentage of isolates from individuals without obvious predisposing risk factors was significantly lower (9/86, 10.5%) than those reported before from other parts of China26, but more similar to those from regions outside of China. In Jiangxi Province, cryptococcal infection was more commonly found in middle-aged people, the main group with HIV infections in our samples, than in other age groups. Furthermore, unlike previous studies that found no prominent gender bias in the incidence of cryptococcosis in China26, our data showed that the male–female gender ratio was 2.3:1. The ratio in Jiangxi is similar to those reported from Brazil and Europe27,28, in which the male to female gender ratio was about 2.9:1.
Similar to observations from other parts of China and other Asian countries, such as Korea, Japan and Thailand19–32, our data showed that the 86 clinical isolates of C. neoformans from Jiangxi Province had relatively limited amount of genetic variation. All isolates were of the same mating type and the same genotype group VNI. The genotype group VNI is globally the dominant lineage of C. neoformans responsible for cryptococcosis27,28. A previous study by Fang et al.25. indicated that serotype A, molecular type VNI, and MATα strains of C. neoformans predominate HIV-negative patients in China. Our study suggests this genotype group also predominates the HIV-infected patients in Jiangxi.
To date, seventeen STs of C. neoformans var. grubii have been identified in China. They include ST5, ST31, ST38, ST53, ST57, ST63, ST93, ST186, ST191, ST194, ST195, ST295, ST296, ST359, and ST360 in Mainland China, while ST4 and ST6 are found in Hong Kong13,33–35. In this study, eight STs (i.e. ST5, ST31, ST32, ST139, ST186, ST226, ST319, and ST359) were founded in Jiangxi Province and only four of these eight STs overlap with those reported from other parts of China. This result suggests that there is likely abundant unique genetic diversity of C. neoformans in Jiangxi Province. Among the shared STs between Jiangxi and outside of Jiangxi, the majority belonged to ST5, the most common ST in all East Asian countries where epidemiology data are available, including China, Japan, and South Korea30,36,37. Interestingly, two other STs, ST31 and ST32, found in Jiangxi were also broadly distributed. According to Khayhan et al.33, ST139 has so far been found only in Africa. However, its relative frequency in Africa is not known. The geographic distribution patterns of these six shared STs found in Jiangxi suggest that both long- and short- distance dispersals are common in C. neoformans. Consistent with this hypothesis, aside from the Beijing population, we found limited evidence for genetic differentiation between most pairs of geographic populations of C. neoformans in China. At present, the reason(s) for the genetic distinctiveness of the Beijing population is not known. However, as suggested previously1,18, a diversity of factors such as wind, animals such as pigeons, and anthropogenic activities could have contributed to the dispersals of genotypes between Jiangxi Province and other regions both within and outside of China.
In this study, all 86 cryptococcal isolates were susceptible to 5FC, AMB, FCA, ITR, and VRC. Our results suggest that the standard initial therapy for cryptococcosis, AMB combined with 5FC, should still work for patients in Jiangxi Province38. However, variations in MICs were observed among the isolates. For each of the drugs, there were isolates showing high MIC values. At present, there was no apparent relationship between MIC to any of the drugs and geographic origins and/or strain genotypes. We would like to note that some of the strains showed high MIC values to multiple drugs. Our results thus call for close monitoring of drug susceptibilities of cryptococcal strains in Jiangxi Province.
In conclusion, our study revealed both shared and divergent genotypes and patterns of cryptococcal epidemiology between Jiangxi Province and other parts of China. Specifically, in both Jiangxi and other parts of China, ST5 was the predominant sequence type. In addition, both unique STs and evidence for long distance dispersals were found among most surveyed regions in China. However, different from previous studies in China, our results identified that most patients in Jiangxi Province with cryptococcosis had underlying risk factors associated with compromised immunity. At present, the mechanism for the predominance of ST5 in East Asian populations is not known. One possibility is that ST5 is more virulent than other sequence types to East Asians. Another possibility is that ST5 was the founder clone in East Asia that has adapted to the local ecological niches. Additional investigations are needed in order to test these possibilities.
Acknowledgements
We thank Drs. Zeyuan Bian and Jiangming Hong for their help in providing samples of C. neoformans for this study. This research was supported by grants from the National Natural Science Foundation of China (81460327) and the Natural Sciences and Engineering Research Council (NSERC) of Canada.
Author Contributions
L.-H.H., J.X., and N.Z.: conceived and designed the experiments; Y.-H.C., F.Y., Z.-Y.B., J.-M.H., N.Z., Q.-S.Z., and Y.-P.H. performed the experiments; Y.-H.C. and J.X. analyzed the data; Y.-H.C., L.-H.H., and J.X. drafted the manuscript. All co-authors reviewed and approved the manuscript.
Competing Interests
The authors declare that they have no competing interests.
Footnotes
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Jianping Xu, Email: jpxu@mcmaster.ca.
Long-Hua Hu, Email: longhuahu@163.com.
References
- 1.Kidd SE, et al. A rare genotype of Cryptococcus gattii caused the cryptococcosis outbreak on Vancouver Island (British Columbia, Canada) Proc Natl Acad Sci USA. 2004;101:17258. doi: 10.1073/pnas.0402981101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Park BJ, et al. Estimation of the current global burden of cryptococcal meningitis among persons living with HIV/AIDS. Aids. 2009;23:525. doi: 10.1097/QAD.0b013e328322ffac. [DOI] [PubMed] [Google Scholar]
- 3.Yuchong C, et al. Cryptococcosis in China (1985–2010): review of cases from Chinese database. Mycopathologia. 2012;173:329. doi: 10.1007/s11046-011-9471-1. [DOI] [PubMed] [Google Scholar]
- 4.Ellis DH, Pfeiffer TJ. Natural habitat of Cryptococcus neoformans var. gattii. J Clin Microbiol. 1990;28:1642. doi: 10.1128/jcm.28.7.1642-1644.1990. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Baro T, et al. Serotyping of Cryptococcus neoformans isolates from clinical and environmental sources in Spain. J Clin Microbiol. 1999;37:1170. doi: 10.1128/jcm.37.4.1170-1172.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Li AS, et al. Ecological surveys of the Cryptococcus species complex in China. Chin Med J (Engl) 2012;125:511. [PubMed] [Google Scholar]
- 7.Firacative C, Trilles L, Meyer W. MALDI-TOF MS enables the rapid identification of the major molecular types within the Cryptococcus neoformans/C. gattii species complex. Plos One. 2012;7:e37566. doi: 10.1371/journal.pone.0037566. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.McTaggart LR, et al. Rapid identification of Cryptococcus neoformans and Cryptococcus gattii by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol. 2011;49:3050. doi: 10.1128/JCM.00651-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kwon-Chung KJ, Varma A. Do major species concepts support one, two or more species within Cryptococcus neoformans? Fems Yeast Res. 2006;6:574. doi: 10.1111/j.1567-1364.2006.00088.x. [DOI] [PubMed] [Google Scholar]
- 10.Mitchell TG, Perfect JR. Cryptococcosis in the era of AIDS–100 years after the discovery of Cryptococcus neoformans. Clin Microbiol Rev. 1995;8:515. doi: 10.1128/cmr.8.4.515. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Meyer W, et al. Consensus multi-locus sequence typing scheme for Cryptococcus neoformans and Cryptococcus gattii. Med Mycol. 2009;47:561. doi: 10.1080/13693780902953886. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ngamskulrungroj, P., Chang, Y., Sionov, E. & Kwon-Chung, K. J. The primary target organ of Cryptococcus gattii is different from that of Cryptococcus neoformans in a murine model. Mbio3 (2012). [DOI] [PMC free article] [PubMed]
- 13.Dou, H. et al. Molecular characterization of Cryptococcus neoformans isolated from the environment in Beijing, China. Med Mycol (2017). [DOI] [PubMed]
- 14.Bolano A, et al. Rapid methods to extract DNA and RNA from Cryptococcus neoformans. Fems Yeast Res. 2001;1:221. doi: 10.1111/j.1567-1364.2001.tb00037.x. [DOI] [PubMed] [Google Scholar]
- 15.Kwon-Chung KJ, Polacheck I, Bennett JE. Improved diagnostic medium for separation of Cryptococcus neoformans var. neoformans (serotypes A and D) and Cryptococcus neoformans var. gattii (serotypes B and C) J Clin Microbiol. 1982;15:535. doi: 10.1128/jcm.15.3.535-537.1982. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Chowdhary A, et al. Genetic differentiation, recombination and clonal expansion in environmental populations of Cryptococcus gattii in India. Environ Microbiol. 2011;13:1875. doi: 10.1111/j.1462-2920.2011.02510.x. [DOI] [PubMed] [Google Scholar]
- 17.Yan Z, Li X, Xu J. Geographic distribution of mating type alleles of Cryptococcus neoformans in four areas of the United States. J Clin Microbiol. 2002;40:965. doi: 10.1128/JCM.40.3.965-972.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hiremath SS, et al. Long-distance dispersal and recombination in environmental populations of Cryptococcus neoformans var. grubii from India. Microbiology+ 2008;154:1513. doi: 10.1099/mic.0.2007/015594-0. [DOI] [PubMed] [Google Scholar]
- 19.Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Mol Biol Evol. 2013;30:2725. doi: 10.1093/molbev/mst197. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Peakall R, Smouse PE. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics. 2012;28:2537. doi: 10.1093/bioinformatics/bts460. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Clinical Laboratory Standards Institute M27–A3. Reference method for broth dilution antifungal susceptibility testing of yeasts: approved standard Wayne, PA (2008).
- 22.Nguyen MH, Yu CY. In vitro comparative efficacy of voriconazole and itraconazole against fluconazole-susceptible and -resistant Cryptococcus neoformans isolates. Antimicrob Agents Chemother. 1998;42:471. doi: 10.1128/aac.42.2.471. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Pan W, et al. Resistance of Asian Cryptococcus neoformans serotype A is confined to few microsatellite genotypes. Plos One. 2012;7:e32868. doi: 10.1371/journal.pone.0032868. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Pfaller MA, et al. In vitro activities of voriconazole, posaconazole, and fluconazole against 4,169 clinical isolates of Candida spp. and Cryptococcus neoformans collected during 2001 and 2002 in the ARTEMIS global antifungal surveillance program. Diagn Microbiol Infect Dis. 2004;48:201. doi: 10.1016/j.diagmicrobio.2003.09.008. [DOI] [PubMed] [Google Scholar]
- 25.Fang W, Fa Z, Liao W. Epidemiology of Cryptococcus and cryptococcosis in China. Fungal Genet Biol. 2015;78:7. doi: 10.1016/j.fgb.2014.10.017. [DOI] [PubMed] [Google Scholar]
- 26.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;8:930. doi: 10.1111/j.1567-1364.2008.00422.x. [DOI] [PubMed] [Google Scholar]
- 27.Casali AK, et al. Molecular typing of clinical and environmental Cryptococcus neoformans isolates in the Brazilian state Rio Grande do Sul. Fems Yeast Res. 2003;3:405. doi: 10.1016/S1567-1356(03)00038-2. [DOI] [PubMed] [Google Scholar]
- 28.Viviani MA, et al. Molecular analysis of 311 Cryptococcus neoformans isolates from a 30-month ECMM survey of cryptococcosis in Europe. Fems Yeast Res. 2006;6:614. doi: 10.1111/j.1567-1364.2006.00081.x. [DOI] [PubMed] [Google Scholar]
- 29.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;43:360. doi: 10.5941/MYCO.2015.43.3.360. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Mihara T, et al. Multilocus sequence typing of Cryptococcus neoformans in non-HIV associated cryptococcosis in Nagasaki, Japan. Med Mycol. 2013;51:252. doi: 10.3109/13693786.2012.708883. [DOI] [PubMed] [Google Scholar]
- 31.Umeyama T, et al. Determination of epidemiology of clinically isolated Cryptococcus neoformans strains in Japan by multilocus sequence typing. Jpn J Infect Dis. 2013;66:51. doi: 10.7883/yoken.66.51. [DOI] [PubMed] [Google Scholar]
- 32.Kaocharoen S, et al. Molecular epidemiology reveals genetic diversity amongst isolates of the Cryptococcus neoformans/C. gattii species complex in Thailand. PLoS Negl Trop Dis. 2013;7:e2297. doi: 10.1371/journal.pntd.0002297. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Khayhan K, 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;8:e72222. doi: 10.1371/journal.pone.0072222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.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;34:753. doi: 10.1007/s10096-014-2289-2. [DOI] [PubMed] [Google Scholar]
- 35.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;58:280. doi: 10.1111/myc.12312. [DOI] [PubMed] [Google Scholar]
- 36.Chen J, et al. Cryptococcus neoformans strains and infection in apparently immunocompetent patients, China. Emerg Infect Dis. 2008;14:755. doi: 10.3201/eid1405.071312. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Choi YH, et al. Prevalence of the VNIc genotype of Cryptococcus neoformans in non-HIV-associated cryptococcosis in the Republic of Korea. Fems Yeast Res. 2010;10:769. doi: 10.1111/j.1567-1364.2010.00648.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Brouwer AE, et al. Combination antifungal therapies for HIV-associated cryptococcal meningitis: a randomised trial. Lancet. 2004;363:1764. doi: 10.1016/S0140-6736(04)16301-0. [DOI] [PubMed] [Google Scholar]
- 39.Fan X, 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;22:881. doi: 10.1016/j.cmi.2016.07.008. [DOI] [PubMed] [Google Scholar]
- 40.Hatthakaroon C, et al. Molecular epidemiology of cryptococcal genotype VNIc/ST5 in Siriraj Hospital, Thailand. Plos One. 2017;12:e173744. doi: 10.1371/journal.pone.0173744. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Day JN, et al. Comparative genomics of Cryptococcus neoformans var. grubii associated with meningitis in HIV infected and uninfected patients in Vietnam. PLoS Negl Trop Dis. 2017;11:e5628. doi: 10.1371/journal.pntd.0005628. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Ferreira-Paim K, 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:e5223. doi: 10.1371/journal.pntd.0005223. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Litvintseva AP, Kestenbaum L, Vilgalys R, Mitchell TG. Comparative analysis of environmental and clinical populations of Cryptococcus neoformans. J CLIN MICROBIOL. 2005;43:556. doi: 10.1128/JCM.43.2.556-564.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Sanchini A, et al. Molecular typing of clinical Cryptococcus neoformans isolates collected in Germany from 2004 to 2010. Med Microbiol Immunol. 2014;203:333. doi: 10.1007/s00430-014-0341-6. [DOI] [PubMed] [Google Scholar]
- 45.Beale MA, et al. Genotypic diversity is associated with clinical outcome and phenotype in cryptococcal meningitis across Southern Africa. PLoS Negl Trop Dis. 2015;9:e3847. doi: 10.1371/journal.pntd.0003847. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All the data described in this manuscript are presented in the paper (for genotype information and MIC values of all 86 isolates) as well as deposited in the publicly accessible database (http://mlst.mycologylab.com) for all nucleotide sequences.