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BMC Microbiology logoLink to BMC Microbiology
. 2014 May 13;14:125. doi: 10.1186/1471-2180-14-125

Real-time PCR assays for genotyping of Cryptococcus gattii in North America

Erin J Kelley 1,, Elizabeth M Driebe 1, Kizee Etienne 2, Mary E Brandt 2, James M Schupp 1, John D Gillece 1, Jesse S Trujillo 1, Shawn R Lockhart 2, Eszter Deak 2,3, Paul S Keim 1,4, David M Engelthaler 1
PMCID: PMC4032356  PMID: 24886039

Abstract

Background

Cryptococcus gattii has been the cause of an ongoing outbreak starting in 1999 on Vancouver Island, British Columbia and spreading to mainland Canada and the US Pacific Northwest. In the course of the outbreak, C. gattii has been identified outside of its previously documented climate, habitat, and host disease. Genotyping of C. gattii is essential to understand the ecological and geographical expansion of this emerging pathogen.

Methods

We developed and validated a mismatch amplification mutation assay (MAMA) real-time PCR panel for genotyping C. gattii molecular types VGI-VGIV and VGII subtypes a,b,c. Subtype assays were designed based on whole-genome sequence of 20 C. gattii strains. Publically available multilocus sequence typing (MLST) data from a study of 202 strains was used for the molecular type (VGI-VGIV) assay design. All assays were validated across DNA from 112 strains of diverse international origin and sample types, including animal, environmental and human.

Results

Validation revealed each assay on the panel is 100% sensitive, specific and concordant with MLST. The assay panel can detect down to 0.5 picograms of template DNA.

Conclusions

The (MAMA) real-time PCR panel for C. gattii accurately typed a collection of 112 diverse strains and demonstrated high sensitivity. This is a time and cost efficient method of genotyping C. gattii best suited for application in large-scale epidemiological studies.

Keywords: Cryptococcus gattii, Genotyping, Real-time PCR, Epidemiology

Background

Cryptococcosis, a potentially fatal fungal disease, has primarily been observed in immune-compromised individuals and mainly associated with Cryptococcus neoformans infection. It is now recognized that Cryptococcus gattii, once considered to be a variety of the Cryptococcus neoformans complex, is also capable of causing serious disease in immunocompetent individuals and animals [1,2]. C. gattii has been associated with a number of tree species in tropical and subtropical regions [3]. More recently, C. gattii caused an outbreak that began in 1999 on Vancouver Island, British Columbia and has spread to mainland Canada and the US Pacific Northwest [4]. This outbreak is unique in that it marked the identification of a Cryptococcus species in a new climatic region (from tropical to temperate), habitat (from tropical trees to temperate; e.g., Douglas Fir) and host disease (from primary neurologic to primary pulmonary) [3,5].

Recent epidemiological studies of C. gattii in North America provide insight into the organism’s geographical expansion as well as the distribution of molecular genotypes [6-9]. C. gattii has been classically classified into four molecular types by MLST/AFLP, VGI/AFLP4, VGII/AFLP6, VGIII/AFLP5, VGIV/AFLP7 [3,5], with additional molecular types recently identified [10]. Interestingly, molecular types have been associated with significant differences in disease type [3,5], antifungal susceptibilities [3,5,10], and severity and outcome [3,5].

Contemporary methods for genotyping C. gattii are PCR-restriction fragment length polymorphism (PCR-RFLP), amplified fragment length polymorphism (AFLP), multilocus microsatellite typing (MLMT), multilocus sequence typing (MLST), and most recent, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) [11-14]. High resolution melting (HRM) is a method that has been used to identify the Cryptococcus neoformans-Cryptococcus gattii complex, though it has not been employed for genotyping within either species [15]. PCR-RFLP and AFLP require extensive lab work involving restriction enzyme digestion and gel electrophoresis [11]. Results are based on interpretation of gel electrophoresis profiles and as such, are not readily transferred or analyzed between laboratories. MLST, which requires DNA sequencing of seven housekeeping genes, is the preferred genotyping method for C. gattii and is easily transferrable between laboratories [16]. MLMT allows for finer genotype resolution than MLST and has high reproducibility between laboratories [14]. In some laboratories, real-time PCR is a preferable option to methods involving DNA sequencing (MLMT and MLST), which require either out-sourcing to a sequencing capable laboratory or investment in, and the maintenance of, an in-house instrument. Although MALDI-TOF MS shows promise as a new genotyping method, instrumentation is expensive and thus prohibitive for many public health laboratories. Conversely, real-time PCR instruments are becoming ubiquitous, easily maintained, and the use of unlabeled primers and no probe makes reagents inexpensive [17]. Therefore, real-time PCR is an accessible and increasing popular technology for widespread molecular epidemiological efforts.

Here, we present a panel of real-time PCR assays, based on mismatch amplification mutation assay (MAMA) methodology, for rapid and sensitive molecular genotyping of Cryptococcus gattii molecular types (VGI-VGIV) and the dominant North American VGII subtypes (VGIIa-c) [18,19]. MAMA, a form of allele-specific PCR (ASPCR), employs primers that are designed for SNP genotyping. We use known MLST sequences for the VGI-VGIV molecular type assay design and whole genome sequences of 20 strains to identify SNPs specific to each of the targeted VGII subtypes [9,20].

Methods

SYBR MAMA design

MAMA primers have an intentional penultimate mismatch nucleotide at the 3′ end; the ultimate base is always the SNP assay target and is a perfect match for the target SNP [18]. Mismatches decrease the efficiency of primer extension by Taq polymerase, such that if two mismatches are found together under the 3′ end of the primer, the efficiency of the PCR is significantly reduced. However, if a single mismatch at the penultimate base is present, extension occurs from the 3′ matched base, and efficiency of the PCR remains relatively high. Costly fluorogenic oligonucleotide probes are not needed to discriminate SNPs with this method. This discriminatory design results in a cost-efficient, powerful and simple method of SNP genotyping [17,21]. Separate PCR reactions are performed with a MAMA primer specific for only one of the two target SNPs and with one universal primer for amplification from the alternate direction. Comparison of cycle threshold (Ct) values will reveal which reaction is more efficient (has the smaller Ct value). The more efficient reaction corresponds to the SNP that is present in the sample.

MAMA design for MLST groups VGI, VGII, VGIII, and VGIV

The MLST SYBR MAMA design was informed by MLST data collected for 202 C. gatii strains from a worldwide collection [20]. The MLST library included sequences from 77, 75, 26, and 24 isolates of the VGI, VGII, VGIII, VGIV molecular types, respectively. The gene encoding mannitol-1-phosphate dehydrogenase (MPD1) was selected as the best candidate for assay design based on its sequence conservation within each of the four molecular types that allowed for design of assay primers with a minimum number of degenerate bases. All 15 of the known MPD1 allele sequences were aligned with SeqMan Pro v.9.0.4 (DNASTAR, Madison, WI). SNPs specific for each of the molecular types were identified in the sequence alignment. MAMA primers were manually designed in Primer Express 3.0 (Life Technologies, Carlsbad, CA) software with optimal mismatches chosen as suggested by Li et. al. [19] (Table 1).

Table 1.

MAMA real-time PCR assay sequences and targets for genotyping C. gattii

Genotype Assay Name Gene (SNP position) Base call match/mismatch Universal Primer sequence 5′ -- > 3′ Match MAMA Primer sequence 5′ -- > 3′ Mismatch MAMA Primer sequence 5′ -- > 3′
VGI
VGI-MPD471
MPD1 (471)
G/A
AGACTGTCCCAATGTCAAGCTTTC
GCCTTGTATGTGGTAACACCAGTG
GWGCCTTGTATGTGGTAACACCAGTA
VGII
VGII-MPD495
MPD1 (495)
T/A
AGACTGTCCCAATGTCAAGCTTTC
ATTAACCTTAGTGTTGGAGACCTTGACT
AACCTTAGTGTTGGAGACCTTGACA
VGIIa
VGIIa-45211
hypothetical protein
A/C
CCCAGCAACCTTGATCTGGA
AGCTGCTCTAAGAGACACATCATCA
AGCTGCTCTAAGAGACACATCATCC
VGIIb
VGIIb-502129
not annotated
G/A
AATCGCTCGTCCTCATATGACA
GTAGGCGGTGGGATAAGGTG
GGTAGGCGGTGGGATAAGGTA
VGIIc
VGIIc-257655
non-coding region
C/T
CGTTAATTTGGTTGTTTGACAACCT
AGCAACTCACGCAGAAACAGAC
GAGCAACTCACGCAGAAACAGAT
VGIII
VGIII-MPD198
MPD1 (198)
T/A
TGACATTGGGACAGTCTGCAAT
ACTGCTGCTTCTCCCGTTGT
CTGCTGCTTCTCCCGTTGA
VGIV VGIV-MPD423 MPD1 (423) A/C ACCCAGTCATTAACCTTAGTGTTGGA CTCGTTCGTCAAYCACGTTAGA TCGTTCGTCAAYCACGTTAGC

MAMA design for VGIIa, VGIIb, and VGIIc subtypes

Whole genome sequence typing (WGST) analysis of 20 C. gattii strains from a previous study revealed canonical SNPs specific for each of the VGII a, b and c subtypes (n = 2720, 3547, and 3819, respectively) [9]. In order to minimize interference of adjacent mutations with primer design, the genotype-specific SNPs were sorted according to nearest neighboring mismatch within the sequence alignment; in short, the SNPs with the most-conserved flanking regions were the top candidates for assay design. Sequence from the R265 strain reference genome [GenBank: CH408164] [2] surrounding the genotype-specific SNPs was used for assay design. SYBR MAMA primers were designed using the same criteria as previously described for the MLST MAMA (Table 1).

Isolate selection

Initially, assays were validated with genomic DNA extracted from 57 C. gattii strains of North American origin and some historical isolates. The panel of isolates including: 13 VGIIa, 4 VGIIb, and 24 VGIIc, and 8 each of VGI and VGIII, was analyzed using each of the assays (Table 2). All DNAs were genotyped by MLST prior to screening. Further validation of the assays was accomplished by employing a more diverse isolate collection of 55 strains including isolates of international origin; this panel was comprised of 10 VGI, 10 VGIIa, 9 VGIIb, 8 VGIIc, 8 VGIII, and 10 VGIV molecular types (Table 3). The strains came from a variety of environmental, human and animal sources, including cats, a dog, an alpaca, a porpoise, a sheep and a cow.

Table 2.

C. gattii strains for initial assay validation

Isolate ID MLST Year Geographic origin Source
B7488
VGI
2009
Oregon
Human
B7496
VGI
2009
Hawaii
Dolphin
B8551
VGI
2010
Oregon
Human
B8852
VGI
2010
Oregon
Human
B8886
VGI
2010
Oregon
Soil
B8887
VGI
2010
Oregon
Soil
B8990
VGI
2010
California
Human
B9009
VGI
2011
Washington
Human
B6864
VGIIa
2004
Oregon
Human
B7395
VGIIa
2008
Washington
Dog
B7422
VGIIa
2009
Oregon
Cat
B7436
VGIIa
2009
California
Alpaca
B7467
VGIIa
2009
Oregon
Porpoise
B8555
VGIIa
2006
Washington
Human
B8577
VGIIa
2009
British Columbia
Soil
B8793
VGIIa
2010
Oregon
Canine
B8849
VGIIa
2010
Oregon
Environmental
CA-1014
VGIIa
unknown
California
Human
CBS-7750
VGIIa
1990
California
Environmental
ICB-107
VGIIa
unknown
Brazil
Human
NIH-444
VGIIa
1972
Washington
Human
B7394
VGIIb
2008
Washington
Cat
B7735
VGIIb
2009
Oregon
Human
B8554
VGIIb
2010
Oregon
Dog
B8828
VGIIb
2010
Washington
Porpoise
B6863
VGIIc
2005
Oregon
Human
B7390
VGIIc
2008
Idaho
Human
B7432
VGIIc
2009
Oregon
Human
B7434
VGIIc
2008
Oregon
Human
B7466
VGIIc
2008
Oregon
Cat
B7491
VGIIc
2009
Oregon
Human
B7493
VGIIc
2009
Oregon
Sheep
B7641
VGIIc
2008
Oregon
Cat
B7737
VGIIc
2009
Oregon
Human
B7765
VGIIc
2009
Oregon
Dog
B8210
VGIIc
2008
Oregon
Human
B8214
VGIIc
2009
Oregon
Human
B8510
VGIIc
2009
Oregon
Human
B8549
VGIIc
unknown
Oregon
Human
B8552
VGIIc
unknown
Oregon
Human
B8571
VGIIc
2009
Washington
Human
B8788
VGIIc
2010
Oregon
Human
B8798
VGIIc
2005
Oregon
Human
B8821
VGIIc
2010
Oregon
Human
B8825
VGIIc
2009
Oregon
Human
B8833
VGIIc
2010
Oregon
Cat
B8838
VGIIc
2010
Washington
Human
B8843
VGIIc
2010
Oregon
Human
B8853
VGIIc
2010
Oregon
Cat
B7415
VGIII
2009
California
Alpaca
B7495
VGIII
2009
California
Human
B8212
VGIII
2007
Oregon
Human
B8260
VGIII
2009
Washington
Cat
B8262
VGIII
1992
California
Human
B8516/B8616
VGIII
2009
Oregon
Cat
B9143
VGIII
2011
California
Human
B9146 VGIII 2011 California Human

Table 3.

C. gattii strains for additional assay validation

Culture collection ID Geographic origin Sample type MLST Year of isolation
B4501
Australia
Human
VGI
unknown
B4503
Australia
Human
VGI
unknown
B4504
Australia
Human
VGI
unknown
B4516
Australia
Human
VGI
unknown
B5765
India
Environmental
VGI
unknown
B9018
California
Human
VGI
2011
B9019
New Mexico
Human
VGI
2011
B9021
Rhode Island
Human
VGI
2011
B9142
Georgia
Human
VGI
2011
B9149
California
Human
VGI
2011
B8508
Oregon
Human
VGIIa
2009
B8512
Oregon
Alpaca
VGIIa
2009
B8558
Washington
Human
VGIIa
2010
B8561
Washington
Human
VGIIa
2010
B8563
Washington
Human
VGIIa
2010
B8567
Washington
Dog
VGIIa
2010
B8854
Washington
Human
VGIIa
2010
B8889
Oregon
Environmental
VGIIa
2010
B9077
Washington
Environmental
VGIIa
2011
B9296
British Columbia
Environmental
VGIIa
2011
B8211
Oregon
Human
VGIIb
2009
B8966
Oregon
Horse
VGIIb
2010
B9076
Washington
Environmental
VGIIb
2011
B9157
Washington
Horse
VGIIb
2011
B9170
Washington
Porpoise
VGIIb
2011
B9234
Washington
Cat
VGIIb
2011
B9290
British Columbia
Cat
VGIIb
2011
B9241
Oregon
Human
VGIIb
2011
B9428
Washington
Cat
VGIIb
2012
B9159
Washington
Sheep
VGIIc
2011
B9227
Oregon
Cat
VGIIc
2011
B9235
Oregon
Human
VGIIc
2011
B9244
Oregon
Human
VGIIc
2011
B9245
Oregon
Human
VGIIc
2011
B9295
British Columbia
Environmental
VGIIc
2011
B9302
Oregon
Environmental
VGIIc
2011
B9374
Oregon
Human
VGIIc
2011
B8965
New Mexico
Human
VGIII
2010
B9148
California
Human
VGIII
2011
B9151
Michigan
Human
VGIII
2011
B9163
New Mexico
Human
VGIII
2011
B9237
New Mexico
Cat
VGIII
2011
B9372
California
Cow
VGIII
2011
B9422
Oregon
Cat
VGIII
2012
B9430
Alaska
Cat
VGIII
2012
B7238
Botswana
Human
VGIV
2005
B7240
Botswana
Human
VGIV
2005
B7243
Botswana
Human
VGIV
2005
B7247
Botswana
Human
VGIV
2005
B7249
Botswana
Human
VGIV
2005
B7260
Botswana
Human
VGIV
2006
B7262
Botswana
Human
VGIV
2006
B7263
Botswana
Human
VGIV
2006
B7264
Botswana
Human
VGIV
2006
B7265 Botswana Human VGIV 2006

Isolate culturing and DNA extraction

Isolates were grown on Yeast Peptone Glucose (YPD) agar plus 0.5% NaCl at 37°C for 24 hours; and DNA was prepared using an UltraClean DNA Isolation Kit as described by the manufacturer, with some modifications (MO BIO Laboratories, Carlsbad, CA). Briefly, ~0.5 grams of microbial cells were suspended in lysis solution in a MicroBead tube and heated to 65°C for 15 minutes to increase lysis efficiency. The MicroBead tube was then secured horizontally using the MO BIO vortex adapter tube holder (MO BIO Laboratories, Carlsbad, CA) and vortexed at maximum speed for 10 minutes; post cell lysis, microtubes were immediately placed on ice for 5 minutes. After the lysis steps, DNA extraction was completed per manufacturer’s instructions. DNA was stored at −20°C.

Real-time PCR

Real-time PCR was performed on the ABI 7900HT real-time PCR System (Life Technologies, Carlsbad, CA). Reactions for both perfect match and mismatch primer sets were conducted in separate wells of a 384-well optical plate, and reactions for each primer set were run in triplicate. Reactions were 10 μL total volume composed of 1X Platinum SYBR Green qPCR SuperMix-UDG with ROX (Invitrogen, Grand Island, NY), 200 nM each of forward and reverse primers, and 1 μL DNA extract (diluted 1:10). Reactions were incubated for 3 min at 50°C for UDG digest followed by 3 min at 95°C for Taq polymerase activation. PCR consisted of 45 cycles of 15 s at 95°C for denaturation followed by 1 min at 60°C annealing and extension. Dissociation of PCR product was performed for 15 sec at 95°C, 15 sec at 60°C and 15 sec at 95°C as a quality assurance step to inspect reactions for primer-dimer. Dissociation curves were not used for isolate genotyping, rather to ensure amplification was specific for the targeted sequence and to preclude non-specific amplification associated with the ability of SYBR Green chemistry to bind any double-stranded DNA. Data were analyzed in Sequence Detection Systems 2.3 software (Life Technologies, Carlsbad, CA) for calculation of cycle threshold (Ct) values and interpretation of dissociation curves.

For MAMA results, the perfect match primer set will amplify earlier and yield the lowest Ct value, corresponding to the SNP genotype of the isolate; secondary delayed amplification plots with a higher Ct value, if present, are due to mismatch priming (Figure 1). An algorithm for genotype calling was implemented to expedite data analysis. The delta Ct value was calculated by subtracting the match primer mean Ct from the mismatch primer mean Ct. If the mismatch priming fails to yield a Ct value because it is beyond the instrument range, a Ct value = 40 is assigned in order to calculate a ΔCt.

ΔCt=mismatchmeanCtperfectmatchmeanCt

Figure 1.

Figure 1

VGIIb MAMA plots with VGII DNA show the specificity of VGIIb MAMA for VGIIb DNA. (A) The VGIIb match primers amplify VGIIb DNA efficiently and yield a lower Ct value than the VGIIb mismatch primers, resulting in a VGIIb genotype call. (B) The VGIIb mismatch primers amplify VGIIa DNA more efficiently than the VGIIb match primers, resulting in a non-VGIIb genotype call. (C) VGIIb mismatch primers amplify VGIIc DNA more efficiently than the VGIIb match primers, again resulting in a non-VGIIb genotype call.

A negative ΔCt value indicates a mismatch allele, whereas a positive ΔCt indicates a match allele. A stringent threshold of |ΔCt| ≥ 3.3, approximately equivalent to one log10 difference in the dynamic range, was established to ensure accuracy of allele calls. If |ΔCt| < 3.3 is below the stringent threshold, this could result in an inaccurate genotype call. In this case, it is advisable to re-screen the sample across the failed assays.

Sensitivity and specificity of the assay panel were calculated as well as concordance with the known MLST type as determined by sequencing the MLST house keeping genes. Assay repeatability and reproducibility were tested by screening nine replicate reactions with the matching primer sets and DNA for each assay on three separate days. The lower limit of detection for each assay and its matching template pair was tested. Each matching template and assay pair was tested using six log10 serial dilutions of a single template DNA, starting with 0.5 ng/μl. Template DNA was quantified in triplicate by NanoDrop 3300 fluorospectrometer (NanoDrop Technologies, Wilmington, DE) using Quant-iT PicoGreen dsDNA Reagent (Life Technologies, Carlsbad, CA), according to manufacturer’s instructions. Real-time PCR reactions were performed in triplicate for each dilution.

Results

Initial validation revealed the assay panel was 100% sensitive; each assay appropriately identified the known isolate genotypes. The ΔCt values for our validation panel confirmed the stringent threshold ΔCt = 3.3 sufficient to discriminate the genotypes. In addition, the assay panel was 100% specific; no cross reactivity occurred between assays and non-matching genotypes. Further validation of the assay panel with additional strains revealed 100% sensitivity and specificity. A total of 112 strains were screened across the MLST assay panel and 100% sensitivity and specificity was observed (Table 4). A total of 68 previously genotyped strains were screened across the VGII subtyping assay panel with 100% sensitivity and specificity (Table 5). The assay coefficients of variation ranged from 0.22% to 4.33% indicating high assay repeatability and reproducibility within and between runs (Table 6). The assays were designed for genotyping of DNA from known C. gattii isolates, and are not validated for application to clinical specimens; they were able to detect DNA concentrations as low as 0.5 pg/μl (Table 7).

Table 4.

MLST SYBR MAMA Ct values and genotype assignments for VGI-VGIV

 
VGI_MPD471
VGII_MPD495
VGIII_MPD198
VGIV_MPD423
Isolate ID Strain type via MLST VGI Ct Mean non-VGI Ct Mean Delta Ct Type call via assay VGII Ct Mean non-VGII Ct Mean Delta Ct Type call via assay VGIII Ct Mean non-VGIII Ct Mean Delta Ct Type call via assay VGIV Ct Mean non-VGIV Ct Mean Delta Ct Type call via assay Final Call
B7488
VGI
17.0
29.0
11.9
VGI
37.4
17.7
−19.7
non-VGII
28.4
14.9
−13.5
non-VGIII
32.4
16.3
−16.1
non-VGIV
VGI
B7496
VGI
18.2
28.0
9.8
VGI
35.3
19.0
−16.3
non-VGII
24.5
16.4
−8.1
non-VGIII
31.7
17.9
−13.8
non-VGIV
VGI
B8551
VGI
17.3
29.6
12.3
VGI
36.2
17.9
−18.3
non-VGII
28.7
15.3
−13.4
non-VGIII
39.0
16.7
−22.3
non-VGIV
VGI
B8852
VGI
21.1
30.9
9.8
VGI
36.5
21.9
−14.6
non-VGII
27.8
19.1
−8.8
non-VGIII
32.0
20.6
−11.4
non-VGIV
VGI
B8886
VGI
18.9
29.2
10.3
VGI
38.1
19.3
−18.8
non-VGII
26.7
16.4
−10.3
non-VGIII
32.3
17.9
−14.4
non-VGIV
VGI
B8887
VGI
15.9
28.3
12.4
VGI
23.6
15.5
−8.1
non-VGII
33.6
16.2
−17.4
non-VGIII
34.1
15.5
−18.7
non-VGIV
VGI
B8990
VGI
18.8
30.9
12.1
VGI
37.2
20.1
−17.1
non-VGII
31.3
16.9
−14.3
non-VGIII
40.0
19.3
−20.7
non-VGIV
VGI
B9009
VGI
21.6
31.0
9.4
VGI
36.5
23.1
−13.4
non-VGII
28.6
19.4
−9.2
non-VGIII
40.0
21.1
−18.9
non-VGIV
VGI
B4501
VGI
16.1
26.7
10.6
VGI
30.5
18.1
−12.4
non-VGII
30.6
17.3
−13.3
non-VGIII
29.4
16.4
−13.0
non-VGIV
VGI
B4503
VGI
15.9
27.2
11.2
VGI
32.7
18.6
−14.1
non-VGII
33.8
17.9
−15.9
non-VGIII
28.7
16.1
−12.6
non-VGIV
VGI
B4504
VGI
15.6
27.2
11.5
VGI
33.1
18.1
−15.1
non-VGII
33.9
17.4
−16.4
non-VGIII
28.7
15.8
−13.0
non-VGIV
VGI
B4516
VGI
15.3
26.8
11.5
VGI
31.5
17.6
−13.9
non-VGII
33.4
16.8
−16.6
non-VGIII
29.7
15.3
−14.3
non-VGIV
VGI
B5765
VGI
17.2
28.0
10.8
VGI
32.8
19.7
−13.0
non-VGII
34.4
19.2
−15.2
non-VGIII
29.0
16.3
−12.7
non-VGIV
VGI
B9018
VGI
17.7
30.0
12.3
VGI
34.6
17.9
−16.7
non-VGII
31.8
18.6
−13.2
non-VGIII
35.0
18.3
−16.8
non-VGIV
VGI
B9019
VGI
16.9
26.1
9.2
VGI
35.4
16.7
−18.7
non-VGII
34.9
16.7
−18.2
non-VGIII
30.5
16.8
−13.7
non-VGIV
VGI
B9021
VGI
21.4
32.9
11.5
VGI
33.4
19.9
−13.5
non-VGII
32.7
20.5
−12.2
non-VGIII
35.5
20.4
−15.2
non-VGIV
VGI
B9142
VGI
16.0
26.3
10.3
VGI
27.8
15.9
−11.9
non-VGII
32.7
16.5
−16.2
non-VGIII
31.7
16.6
−15.1
non-VGIV
VGI
B9149
VGI
17.7
26.8
9.1
VGI
28.5
17.5
−11.0
non-VGII
28.5
18.2
−10.3
non-VGIII
31.0
18.3
−12.6
non-VGIV
VGI
B6864
VGIIa
27.8
17.5
−10.3
non-VGI
19.3
33.1
13.8
VGII
34.7
19.7
−15.0
non-VGIII
40.0
16.1
−23.9
non-VGIV
VGII
B7395
VGIIa
28.9
18.8
−10.1
non-VGI
21.3
32.6
11.3
VGII
40.0
19.2
19.2
non-VGIII
40.0
18.8
−21.2
non-VGIV
VGII
B7422
VGIIa
27.4
17.4
−10.0
non-VGI
19.5
32.3
12.8
VGII
35.4
19.1
−16.3
non-VGIII
40.0
15.6
−24.4
non-VGIV
VGII
B7436
VGIIa
27.8
17.9
−9.9
non-VGI
20.7
35.4
14.7
VGII
36.5
16.9
−19.6
non-VGIII
40.0
15.6
−24.4
non-VGIV
VGII
B7467
VGIIa
30.9
20.7
−10.1
non-VGI
22.7
32.7
9.9
VGII
37.7
23.4
−14.2
non-VGIII
40.0
19.1
−20.9
non-VGIV
VGII
B8555
VGIIa
27.9
17.7
−10.2
non-VGI
19.7
32.1
12.4
VGII
34.6
20.8
−13.8
non-VGIII
40.0
16.6
−23.4
non-VGIV
VGII
B8577
VGIIa
31.1
20.9
−10.2
non-VGI
21.8
34.1
12.3
VGII
33.1
23.4
−9.8
non-VGIII
40.0
19.8
−20.2
non-VGIV
VGII
B8793
VGIIa
27.4
17.4
−10.0
non-VGI
18.9
32.6
13.7
VGII
39.0
24.9
−14.1
non-VGIII
40.0
16.3
−23.7
non-VGIV
VGII
B8849
VGIIa
28.9
18.7
−10.1
non-VGI
22.9
35.1
12.2
VGII
36.0
22.7
−13.3
non-VGIII
40.0
18.4
−21.6
non-VGIV
VGII
CA-1014
VGIIa
20.4
11.6
−8.8
non-VGI
13.6
32.4
18.9
VGII
31.1
12.8
−18.3
non-VGIII
40.0
11.0
−29.0
non-VGIV
VGII
CBS-7750
VGIIa
27.2
17.3
−9.9
non-VGI
18.8
33.1
14.3
VGII
38.0
25.5
−12.5
non-VGIII
40.0
15.8
−24.2
non-VGIV
VGII
ICB-107
VGIIa
28.1
18.2
−9.9
non-VGI
20.0
34.7
14.8
VGII
37.5
25.4
−12.1
non-VGIII
40.0
15.6
−24.4
non-VGIV
VGII
NIH-444
VGIIa
24.9
14.9
−10.0
non-VGI
17.0
33.2
16.2
VGII
34.9
17.7
−17.2
non-VGIII
40.0
13.3
−26.7
non-VGIV
VGII
B8508
VGIIa
23.7
14.8
−8.9
non-VGI
17.4
30.4
13.0
VGII
34.5
16.2
−18.2
non-VGIII
29.1
14.9
−14.2
non-VGIV
VGII
B8512
VGIIa
23.5
14.6
−9.0
non-VGI
16.7
30.6
13.9
VGII
31.4
15.7
−15.6
non-VGIII
29.7
14.8
−14.9
non-VGIV
VGII
B8558
VGIIa
22.5
13.7
−8.8
non-VGI
15.9
29.9
14.0
VGII
30.6
14.9
−15.7
non-VGIII
30.1
14.3
−15.9
non-VGIV
VGII
B8561
VGIIa
26.5
17.7
−8.8
non-VGI
20.3
34.2
14.0
VGII
34.1
19.1
−15.0
non-VGIII
33.2
22.2
−11.0
non-VGIV
VGII
B8563
VGIIa
24.4
16.0
−8.4
non-VGI
18.4
32.8
14.4
VGII
32.8
20.4
−12.4
non-VGIII
32.2
17.3
−14.9
non-VGIV
VGII
B8567
VGIIa
25.6
17.0
−8.6
non-VGI
19.4
34.1
14.7
VGII
33.8
18.2
−15.6
non-VGIII
35.1
16.8
−18.2
non-VGIV
VGII
B8854
VGIIa
24.7
15.8
−8.9
non-VGI
18.1
32.7
14.6
VGII
33.0
17.1
−15.9
non-VGIII
33.2
15.8
−17.4
non-VGIV
VGII
B8889
VGIIa
28.0
17.6
−10.4
non-VGI
20.3
33.1
12.7
VGII
33.7
19.1
−14.6
non-VGIII
32.4
17.5
−15.0
non-VGIV
VGII
B9077
VGIIa
33.6
17.8
−15.9
non-VGI
15.4
28.6
13.2
VGII
40.0
18.6
−21.5
non-VGIII
40.0
18.6
−21.4
non-VGIV
VGII
B9296
VGIIa
27.3
19.8
−7.5
non-VGI
18.6
34.0
15.4
VGII
32.4
20.8
−11.6
non-VGIII
34.9
19.2
−15.7
non-VGIV
VGII
B7394
VGIIb
31.9
22.5
−9.5
non-VGI
23.5
33.5
10.0
VGII
33.7
19.3
−14.4
non-VGIII
40.0
20.2
−19.8
non-VGIV
VGII
B7735
VGIIb
26.9
17.8
−9.1
non-VGI
18.3
33.3
15.0
VGII
0.0
15.8
15.8
non-VGIII
40.0
15.4
−24.6
non-VGIV
VGII
B8554
VGIIb
28.8
18.3
−10.5
non-VGI
20.8
32.2
11.3
VGII
35.5
22.0
−13.4
non-VGIII
40.0
18.3
−21.7
non-VGIV
VGII
B8828
VGIIb
28.8
18.5
−10.3
non-VGI
20.7
32.7
11.9
VGII
35.9
19.2
−16.7
non-VGIII
40.0
31.9
−8.1
non-VGIV
VGII
B8211
VGIIb
22.9
12.8
−10.1
non-VGI
15.1
30.1
15.1
VGII
33.0
13.9
−19.0
non-VGIII
33.8
12.9
−21.0
non-VGIV
VGII
B8966
VGIIb
24.6
15.5
−9.0
non-VGI
17.3
25.9
8.6
VGII
29.3
15.6
−13.7
non-VGIII
28.9
14.7
−14.2
non-VGIV
VGII
B9076
VGIIb
40.0
17.5
−22.5
non-VGI
17.1
27.5
10.5
VGII
40.0
18.4
−21.6
non-VGIII
30.6
18.0
−12.6
non-VGIV
VGII
B9157
VGIIb
25.4
15.3
−10.2
non-VGI
17.6
29.4
11.9
VGII
31.2
16.1
−15.1
non-VGIII
31.6
16.1
−15.5
non-VGIV
VGII
B9170
VGIIb
26.2
16.9
−9.3
non-VGI
17.5
28.7
11.2
VGII
29.5
17.6
−11.9
non-VGIII
31.1
17.7
−13.4
non-VGIV
VGII
B9234
VGIIb
24.7
15.0
−9.6
non-VGI
15.4
30.3
14.9
VGII
30.2
15.7
−14.5
non-VGIII
33.3
15.8
−17.5
non-VGIV
VGII
B9290
VGIIb
24.8
16.0
−8.8
non-VGI
15.9
34.1
18.2
VGII
30.6
20.8
−9.7
non-VGIII
33.2
16.6
−16.6
non-VGIV
VGII
B9241
VGIIb
23.4
13.2
−10.3
non-VGI
15.5
28.0
12.5
VGII
30.0
13.9
−16.0
non-VGIII
34.0
13.5
−20.5
non-VGIV
VGII
B9428
VGIIb
25.2
14.4
−10.7
non-VGI
18.7
28.3
9.6
VGII
30.2
15.5
−14.7
non-VGIII
34.1
15.0
−19.1
non-VGIV
VGII
B6863
VGIIc
28.9
18.6
−10.2
non-VGI
20.7
34.2
13.5
VGII
33.2
22.7
−10.6
non-VGIII
40.0
18.1
−21.9
non-VGIV
VGII
B7390
VGIIc
27.7
18.3
−9.5
non-VGI
19.9
33.9
13.9
VGII
39.5
24.7
−14.8
non-VGIII
40.0
16.9
−23.1
non-VGIV
VGII
B7432
VGIIc
28.2
18.3
−9.9
non-VGI
20.0
32.6
12.7
VGII
34.8
18.0
−16.8
non-VGIII
40.0
17.2
−22.8
non-VGIV
VGII
B7434
VGIIc
25.6
16.2
−9.4
non-VGI
17.7
34.5
16.8
VGII
34.4
17.9
−16.5
non-VGIII
40.0
13.8
−26.2
non-VGIV
VGII
B7466
VGIIc
30.8
20.8
−10.0
non-VGI
22.4
33.6
11.2
VGII
37.4
23.7
−13.7
non-VGIII
40.0
19.5
−20.5
non-VGIV
VGII
B7491
VGIIc
26.9
17.3
−9.6
non-VGI
19.2
33.0
13.8
VGII
0.0
16.8
16.8
non-VGIII
40.0
16.7
−23.3
non-VGIV
VGII
B7493
VGIIc
27.1
17.4
−9.7
non-VGI
18.6
33.6
15.1
VGII
36.6
20.7
−15.8
non-VGIII
40.0
16.1
−23.9
non-VGIV
VGII
B7641
VGIIc
26.0
17.3
−8.7
non-VGI
18.7
32.3
13.7
VGII
34.3
20.0
−14.3
non-VGIII
40.0
15.6
−24.4
non-VGIV
VGII
B7737
VGIIc
28.0
18.5
−9.6
non-VGI
20.1
34.3
14.2
VGII
37.0
23.0
−14.0
non-VGIII
40.0
18.0
−22.0
non-VGIV
VGII
B7765
VGIIc
22.5
13.0
−9.5
non-VGI
14.5
34.1
19.6
VGII
33.1
23.4
−9.7
non-VGIII
40.0
12.9
−27.1
non-VGIV
VGII
B8210
VGIIc
27.8
18.1
−9.7
non-VGI
19.6
33.3
13.7
VGII
33.0
19.4
−13.5
non-VGIII
40.0
16.8
−23.2
non-VGIV
VGII
B8214
VGIIc
27.1
17.7
−9.5
non-VGI
19.8
34.9
15.1
VGII
34.1
20.1
−14.0
non-VGIII
40.0
16.1
−23.9
non-VGIV
VGII
B8510
VGIIc
26.8
17.6
−9.2
non-VGI
18.8
33.2
14.5
VGII
35.2
19.1
−16.1
non-VGIII
40.0
15.6
−24.4
non-VGIV
VGII
B8549
VGIIc
26.8
16.2
−10.6
non-VGI
18.7
33.5
14.8
VGII
37.4
20.5
−16.9
non-VGIII
40.0
29.6
−10.4
non-VGIV
VGII
B8552
VGIIc
27.1
17.0
−10.1
non-VGI
18.6
33.2
14.6
VGII
34.3
19.7
−14.6
non-VGIII
40.0
16.6
−23.4
non-VGIV
VGII
B8571
VGIIc
28.8
19.4
−9.4
non-VGI
21.5
33.4
11.9
VGII
34.5
22.8
−11.8
non-VGIII
40.0
19.5
−20.5
non-VGIV
VGII
B8788
VGIIc
26.0
16.0
−10.0
non-VGI
18.5
29.5
11.0
VGII
38.0
20.4
−17.6
non-VGIII
40.0
16.6
−23.4
non-VGIV
VGII
B8798
VGIIc
36.0
24.7
−11.4
non-VGI
26.5
33.3
6.8
VGII
37.2
19.2
−18.0
non-VGIII
40.0
22.5
−17.5
non-VGIV
VGII
B8821
VGIIc
30.5
20.5
−10.0
non-VGI
22.3
33.0
10.7
VGII
37.0
29.0
−8.0
non-VGIII
40.0
18.7
−21.3
non-VGIV
VGII
B8825
VGIIc
27.4
17.8
−9.6
non-VGI
19.6
33.7
14.1
VGII
36.0
20.5
−15.5
non-VGIII
40.0
17.5
−22.5
non-VGIV
VGII
B8833
VGIIc
29.2
20.7
−8.6
non-VGI
19.5
33.4
13.9
VGII
35.4
19.6
−15.8
non-VGIII
40.0
15.5
−24.5
non-VGIV
VGII
B8838
VGIIc
29.2
19.1
−10.1
non-VGI
21.5
32.8
11.3
VGII
32.9
22.3
−10.6
non-VGIII
40.0
18.5
−21.5
non-VGIV
VGII
B8843
VGIIc
29.5
19.4
−10.1
non-VGI
21.5
33.7
12.2
VGII
37.5
22.1
−15.4
non-VGIII
40.0
19.1
−20.9
non-VGIV
VGII
B8853
VGIIc
33.3
23.1
−10.2
non-VGI
24.8
33.7
8.9
VGII
34.2
27.8
−6.4
non-VGIII
40.0
21.5
−18.5
non-VGIV
VGII
B9159
VGIIc
29.6
17.5
−12.1
non-VGI
19.1
29.9
10.7
VGII
40.0
26.0
−14.0
non-VGIII
40.0
18.0
−22.0
non-VGIV
VGII
B9227
VGIIc
24.4
15.3
−9.1
non-VGI
15.5
28.1
12.6
VGII
27.9
16.1
−11.9
non-VGIII
31.0
16.3
−14.7
non-VGIV
VGII
B9235
VGIIc
24.6
15.1
−9.5
non-VGI
15.3
28.9
13.7
VGII
29.2
16.4
−12.7
non-VGIII
31.2
15.9
−15.3
non-VGIV
VGII
B9244
VGIIc
27.3
18.4
−8.9
non-VGI
18.5
31.8
13.3
VGII
28.2
21.0
−7.2
non-VGIII
30.6
18.8
−11.8
non-VGIV
VGII
B9245
VGIIc
26.8
17.9
−8.9
non-VGI
18.0
33.5
15.5
VGII
31.2
19.3
−11.9
non-VGIII
34.2
18.5
−15.6
non-VGIV
VGII
B9295
VGIIc
28.6
19.5
−9.1
non-VGI
19.9
40.0
20.1
VGII
33.6
25.5
−8.1
non-VGIII
34.4
20.3
−14.2
non-VGIV
VGII
B9302
VGIIc
24.6
14.1
−10.5
non-VGI
16.9
26.7
9.8
VGII
28.8
15.1
−13.7
non-VGIII
31.5
14.1
−17.3
non-VGIV
VGII
B9374
VGIIc
24.8
14.2
−10.6
non-VGI
18.2
27.3
9.1
VGII
29.1
15.2
−13.9
non-VGIII
32.8
14.4
−18.4
non-VGIV
VGII
B7415
VGIII
26.8
15.9
−10.9
non-VGI
35.0
17.7
−17.3
non-VGII
12.4
27.1
14.7
VGIII
30.9
15.9
−15.0
non-VGIV
VGIII
B7495
VGIII
28.1
18.0
−10.1
non-VGI
36.1
18.8
−17.3
non-VGII
14.1
30.1
16.0
VGIII
31.8
17.6
−14.2
non-VGIV
VGIII
B8212
VGIII
26.0
15.7
−10.3
non-VGI
35.3
17.0
−18.3
non-VGII
12.4
28.5
16.1
VGIII
32.5
15.6
−16.9
non-VGIV
VGIII
B8260
VGIII
29.6
19.6
−10.0
non-VGI
36.7
20.8
−15.9
non-VGII
15.9
30.7
14.8
VGIII
36.0
19.1
−16.9
non-VGIV
VGIII
B8262
VGIII
27.2
17.2
−10.0
non-VGI
33.8
18.3
−15.5
non-VGII
13.5
30.0
16.4
VGIII
40.0
16.9
−23.1
non-VGIV
VGIII
B8516/B8616
VGIII
28.4
18.5
−9.9
non-VGI
37.8
19.5
−18.3
non-VGII
14.6
29.1
14.5
VGIII
31.8
18.0
−13.8
non-VGIV
VGIII
B9143
VGIII
28.6
18.3
−10.3
non-VGI
38.3
19.6
−18.7
non-VGII
14.5
30.2
15.7
VGIII
33.3
18.0
−15.3
non-VGIV
VGIII
B9146
VGIII
30.3
19.5
−10.8
non-VGI
38.5
21.2
−17.3
non-VGII
15.8
30.1
14.3
VGIII
31.2
19.3
−11.9
non-VGIV
VGIII
B8965
VGIII
26.2
16.8
−9.4
non-VGI
30.6
17.1
−13.5
non-VGII
16.1
30.6
14.5
VGIII
35.0
17.4
−17.6
non-VGIV
VGIII
B9148
VGIII
26.0
16.6
−9.4
non-VGI
31.0
16.6
−14.4
non-VGII
15.9
30.6
14.7
VGIII
32.8
17.4
−15.4
non-VGIV
VGIII
B9151
VGIII
25.7
16.5
−9.3
non-VGI
30.7
16.2
−14.4
non-VGII
15.4
30.3
14.9
VGIII
34.9
18.0
−17.0
non-VGIV
VGIII
B9163
VGIII
26.9
17.5
−9.4
non-VGI
29.8
17.3
−12.5
non-VGII
16.9
29.7
12.8
VGIII
33.4
18.0
−15.4
non-VGIV
VGIII
B9237
VGIII
26.7
17.9
−8.9
non-VGI
31.6
17.4
−14.2
non-VGII
17.3
35.0
17.7
VGIII
38.1
19.3
−18.9
non-VGIV
VGIII
B9372
VGIII
23.5
12.7
−10.9
non-VGI
29.3
13.1
−16.1
non-VGII
14.8
27.4
12.6
VGIII
32.6
13.0
−19.6
non-VGIV
VGIII
B9422
VGIII
23.9
12.8
−11.1
non-VGI
28.9
12.9
−15.9
non-VGII
14.6
26.8
12.2
VGIII
33.0
13.3
−19.7
non-VGIV
VGIII
B9430
VGIII
23.5
12.9
−10.6
non-VGI
30.1
13.4
−16.8
non-VGII
15.1
28.5
13.4
VGIII
35.5
13.4
−22.0
non-VGIV
VGIII
B7238
VGIV
25.2
16.4
−8.8
non-VGI
33.2
18.5
−14.7
non-VGII
34.6
17.9
−16.7
non-VGIII
16.3
27.4
11.1
VGIV
VGIV
B7240
VGIV
25.8
17.1
−8.8
non-VGI
33.9
19.5
−14.5
non-VGII
34.2
18.5
−15.7
non-VGIII
17.0
28.8
11.8
VGIV
VGIV
B7243
VGIV
26.1
17.3
−8.8
non-VGI
32.0
19.6
−12.4
non-VGII
32.3
18.7
−13.6
non-VGIII
16.8
27.1
10.2
VGIV
VGIV
B7247
VGIV
25.6
16.5
−9.1
non-VGI
33.4
19.2
−14.2
non-VGII
32.0
18.1
−13.9
non-VGIII
16.3
28.4
12.1
VGIV
VGIV
B7249
VGIV
23.4
14.8
−8.6
non-VGI
31.6
16.7
−14.9
non-VGII
32.6
16.0
−16.6
non-VGIII
14.5
31.1
16.5
VGIV
VGIV
B7260
VGIV
26.0
16.5
−9.4
non-VGI
30.9
18.0
−13.0
non-VGII
34.2
17.4
−16.8
non-VGIII
15.7
27.0
11.2
VGIV
VGIV
B7262
VGIV
26.3
16.8
−9.5
non-VGI
31.4
18.7
−12.7
non-VGII
33.4
18.0
−15.4
non-VGIII
15.8
27.5
11.6
VGIV
VGIV
B7263
VGIV
24.5
15.7
−8.9
non-VGI
33.1
17.9
−15.3
non-VGII
37.3
17.0
−20.3
non-VGIII
15.8
28.0
12.2
VGIV
VGIV
B7264
VGIV
24.4
15.0
−9.4
non-VGI
31.2
16.9
−14.3
non-VGII
30.6
16.0
−14.6
non-VGIII
14.8
26.8
12.0
VGIV
VGIV
B7265 VGIV 27.5 17.3 −10.2 non-VGI 34.1 19.6 −14.5 non-VGII 32.1 18.8 −13.3 non-VGIII 16.9 28.8 11.9 VGIV VGIV

Table 5.

VGII subtyping SYBR MAMA Ct values and genotype assignments for VGIIa,b,c

 
VGIIa_Assay_45211
VGIIb_Assay_502129
VGIIc_Assay_257655
Isolate ID Strain type via MLST VGIIa Ct Mean non-VGIIa Ct Mean Delta Ct Type call via assay VGIIb Ct Mean non-VGIIb Ct Mean Delta Ct Type call via assay VGIIc Ct Mean non-VGIIc Ct Mean Delta Ct Type call via assay Final Call
B6864
VGIIa
17.2
30.5
13.3
VGIIa
31.0
17.5
−13.5
non-VGIIb
40.0
27.8
−12.2
non-VGIIc
VGIIa
B7395
VGIIa
19.8
33.5
13.7
VGIIa
33.1
20.3
−12.9
non-VGIIb
40.0
30.6
−9.4
non-VGIIc
VGIIa
B7422
VGIIa
18.3
33.6
15.4
VGIIa
26.4
17.6
−8.8
non-VGIIb
39.2
28.6
−10.6
non-VGIIc
VGIIa
B7436
VGIIa
18.6
31.7
13.1
VGIIa
30.1
17.0
−13.2
non-VGIIb
38.0
29.1
−8.9
non-VGIIc
VGIIa
B7467
VGIIa
20.5
37.3
16.8
VGIIa
35.1
20.3
−14.7
non-VGIIb
40.0
30.9
−9.1
non-VGIIc
VGIIa
B8555
VGIIa
17.1
31.2
14.1
VGIIa
30.3
17.5
−12.8
non-VGIIb
40.0
27.7
−12.3
non-VGIIc
VGIIa
B8577
VGIIa
20.8
36.8
16.0
VGIIa
32.8
20.8
−12.1
non-VGIIb
40.0
31.4
−8.6
non-VGIIc
VGIIa
B8793
VGIIa
15.1
29.8
14.7
VGIIa
30.7
18.6
−12.1
non-VGIIb
40.0
29.8
−10.2
non-VGIIc
VGIIa
B8849
VGIIa
19.8
34.4
14.6
VGIIa
33.6
20.2
−13.4
non-VGIIb
40.0
30.6
−9.4
non-VGIIc
VGIIa
CA-1014
VGIIa
13.1
27.3
14.2
VGIIa
27.0
14.0
−13.0
non-VGIIb
34.9
24.2
−10.7
non-VGIIc
VGIIa
CBS-7750
VGIIa
21.8
32.2
10.4
VGIIa
33.4
21.5
−11.9
non-VGIIb
40.0
34.1
−5.9
non-VGIIc
VGIIa
ICB-107
VGIIa
21.8
33.6
11.8
VGIIa
33.2
21.2
−12.0
non-VGIIb
40.0
33.8
−6.2
non-VGIIc
VGIIa
NIH-444
VGIIa
14.8
27.3
12.5
VGIIa
28.5
15.3
−13.1
non-VGIIb
36.1
25.7
−10.3
non-VGIIc
VGIIa
B8508
VGIIa
17.0
27.8
10.8
VGIIa
26.5
17.3
−9.2
non-VGIIb
31.7
22.7
−9.1
non-VGIIc
VGIIa
B8512
VGIIa
17.6
28.1
10.4
VGIIa
26.3
18.0
−8.3
non-VGIIb
33.2
24.2
−9.0
non-VGIIc
VGIIa
B8558
VGIIa
16.3
24.8
8.5
VGIIa
27.3
15.3
−12.0
non-VGIIb
29.4
20.0
−9.4
non-VGIIc
VGIIa
B8561
VGIIa
15.8
27.5
11.8
VGIIa
25.0
16.9
−8.1
non-VGIIb
33.4
23.2
−10.2
non-VGIIc
VGIIa
B8563
VGIIa
14.5
27.3
12.8
VGIIa
23.9
15.6
−8.3
non-VGIIb
31.7
21.7
−10.0
non-VGIIc
VGIIa
B8567
VGIIa
15.0
36.2
21.2
VGIIa
24.5
16.0
−8.5
non-VGIIb
31.8
22.2
−9.5
non-VGIIc
VGIIa
B8854
VGIIa
14.7
26.7
12.0
VGIIa
24.1
15.1
−9.0
non-VGIIb
31.4
22.2
−9.2
non-VGIIc
VGIIa
B8889
VGIIa
17.0
28.1
11.0
VGIIa
25.9
17.3
−8.7
non-VGIIb
33.2
23.8
−9.4
non-VGIIc
VGIIa
B9077
VGIIa
16.7
27.8
11.1
VGIIa
25.6
16.7
−9.0
non-VGIIb
32.9
24.4
−8.4
non-VGIIc
VGIIa
B9296
VGIIa
17.0
27.5
10.5
VGIIa
25.5
17.3
−8.2
non-VGIIb
32.9
24.8
−8.1
non-VGIIc
VGIIa
B7394
VGIIb
40.0
19.0
−21.0
non-VGIIa
17.3
29.6
12.3
VGIIb
40.0
29.0
−11.0
non-VGIIc
VGIIb
B7735
VGIIb
31.0
18.3
−12.8
non-VGIIa
18.7
31.3
12.6
VGIIb
38.1
28.9
−9.3
non-VGIIc
VGIIb
B8554
VGIIb
32.9
21.2
−11.7
non-VGIIa
22.2
35.0
12.8
VGIIb
40.0
30.4
−9.6
non-VGIIc
VGIIb
B8828
VGIIb
31.9
21.1
−10.8
non-VGIIa
19.9
35.1
15.2
VGIIb
40.0
30.5
−9.5
non-VGIIc
VGIIb
B8211
VGIIb
27.8
16.9
−10.9
non-VGIIa
17.4
28.8
11.4
VGIIb
32.3
22.3
−10.0
non-VGIIc
VGIIb
B8966
VGIIb
26.2
14.7
−11.5
non-VGIIa
16.3
24.1
7.9
VGIIb
31.8
23.2
−8.6
non-VGIIc
VGIIb
B9076
VGIIb
30.0
18.8
−11.2
non-VGIIa
19.7
30.9
11.4
VGIIb
39.1
27.0
−12.1
non-VGIIc
VGIIb
B9157
VGIIb
29.1
16.6
−12.4
non-VGIIa
15.4
23.8
8.5
VGIIb
30.3
21.3
−9.0
non-VGIIc
VGIIb
B9170
VGIIb
26.6
15.4
−11.2
non-VGIIa
16.9
24.8
7.9
VGIIb
31.0
22.7
−8.3
non-VGIIc
VGIIb
B9234
VGIIb
26.1
13.9
−12.2
non-VGIIa
15.3
23.8
8.5
VGIIb
30.2
21.2
−9.1
non-VGIIc
VGIIb
B9290
VGIIb
26.1
13.8
−12.3
non-VGIIa
15.1
24.5
9.5
VGIIb
30.6
21.2
−9.5
non-VGIIc
VGIIb
B9241
VGIIb
26.7
20.2
−6.5
non-VGIIa
14.5
24.0
9.4
VGIIb
30.5
21.4
−9.1
non-VGIIc
VGIIb
B9428
VGIIb
27.5
14.8
−12.6
non-VGIIa
16.0
24.3
8.2
VGIIb
32.0
22.4
−9.6
non-VGIIc
VGIIb
B6863
VGIIc
31.9
20.3
−11.5
non-VGIIa
33.4
20.2
−13.2
non-VGIIb
27.5
40.0
12.5
VGIIc
VGIIc
B7390
VGIIc
32.7
18.9
−13.8
non-VGIIa
31.1
17.9
−13.2
non-VGIIb
25.9
40.0
14.1
VGIIc
VGIIc
B7432
VGIIc
40.0
18.5
−21.5
non-VGIIa
30.7
17.6
−13.1
non-VGIIb
25.7
40.0
14.3
VGIIc
VGIIc
B7434
VGIIc
27.5
15.5
−12.0
non-VGIIa
28.5
15.4
−13.1
non-VGIIb
23.3
40.0
16.7
VGIIc
VGIIc
B7466
VGIIc
31.7
20.8
−10.9
non-VGIIa
33.5
20.6
−12.8
non-VGIIb
28.1
40.0
11.9
VGIIc
VGIIc
B7491
VGIIc
28.7
17.4
−11.2
non-VGIIa
30.4
16.9
−13.5
non-VGIIb
24.0
40.0
16.0
VGIIc
VGIIc
B7493
VGIIc
28.8
18.3
−10.6
non-VGIIa
31.1
18.0
−13.1
non-VGIIb
25.5
40.0
14.5
VGIIc
VGIIc
B7641
VGIIc
29.2
17.2
−12.0
non-VGIIa
30.0
17.2
−12.8
non-VGIIb
24.5
40.0
15.5
VGIIc
VGIIc
B7737
VGIIc
32.6
20.1
−12.5
non-VGIIa
30.8
20.5
−10.4
non-VGIIb
28.4
40.0
11.6
VGIIc
VGIIc
B7765
VGIIc
32.2
19.3
−12.8
non-VGIIa
32.3
18.9
−13.3
non-VGIIb
27.5
40.0
12.5
VGIIc
VGIIc
B8210
VGIIc
29.7
17.6
−12.0
non-VGIIa
30.1
17.4
−12.7
non-VGIIb
25.9
40.0
14.1
VGIIc
VGIIc
B8214
VGIIc
30.1
17.5
−12.5
non-VGIIa
30.9
17.5
−13.4
non-VGIIb
26.1
40.0
13.9
VGIIc
VGIIc
B8510
VGIIc
29.6
17.5
−12.0
non-VGIIa
31.0
17.3
−13.7
non-VGIIb
24.5
40.0
15.5
VGIIc
VGIIc
B8549
VGIIc
29.9
17.7
−12.1
non-VGIIa
31.0
17.8
−13.2
non-VGIIb
24.8
40.0
15.2
VGIIc
VGIIc
B8552
VGIIc
29.2
17.1
−12.0
non-VGIIa
30.3
17.2
−13.1
non-VGIIb
24.4
40.0
15.6
VGIIc
VGIIc
B8571
VGIIc
33.0
20.3
−12.7
non-VGIIa
32.6
20.2
−12.5
non-VGIIb
28.1
40.0
11.9
VGIIc
VGIIc
B8788
VGIIc
29.1
17.3
−11.7
non-VGIIa
30.0
17.2
−12.8
non-VGIIb
25.0
40.0
15.0
VGIIc
VGIIc
B8798
VGIIc
36.5
22.8
−13.7
non-VGIIa
34.5
22.2
−12.3
non-VGIIb
31.0
40.0
9.0
VGIIc
VGIIc
B8821
VGIIc
37.7
24.5
−13.2
non-VGIIa
37.1
24.4
−12.7
non-VGIIb
33.0
40.0
7.0
VGIIc
VGIIc
B8825
VGIIc
29.6
17.7
−11.9
non-VGIIa
30.6
17.7
−12.9
non-VGIIb
25.8
40.0
14.2
VGIIc
VGIIc
B8833
VGIIc
29.0
17.0
−12.0
non-VGIIa
30.1
17.0
−13.1
non-VGIIb
25.2
40.0
14.8
VGIIc
VGIIc
B8838
VGIIc
32.0
19.5
−12.5
non-VGIIa
32.9
19.3
−13.7
non-VGIIb
28.7
40.0
11.3
VGIIc
VGIIc
B8843
VGIIc
32.4
19.9
−12.5
non-VGIIa
33.0
19.5
−13.5
non-VGIIb
28.6
40.0
11.4
VGIIc
VGIIc
B8853
VGIIc
32.8
21.5
−11.3
non-VGIIa
36.0
23.4
−12.6
non-VGIIb
33.1
40.0
6.9
VGIIc
VGIIc
B9159
VGIIc
27.4
20.3
−7.1
non-VGIIa
25.8
16.7
−9.1
non-VGIIb
20.5
34.5
14.0
VGIIc
VGIIc
B9227
VGIIc
25.6
13.6
−12.0
non-VGIIa
23.9
14.9
−9.0
non-VGIIb
18.0
31.5
13.4
VGIIc
VGIIc
B9235
VGIIc
25.9
13.7
−12.1
non-VGIIa
24.1
14.9
−9.2
non-VGIIb
18.4
32.4
14.0
VGIIc
VGIIc
B9244
VGIIc
27.2
19.1
−8.1
non-VGIIa
26.2
16.9
−9.2
non-VGIIb
20.2
32.5
12.3
VGIIc
VGIIc
B9245
VGIIc
28.4
22.9
−5.5
non-VGIIa
25.2
17.4
−7.8
non-VGIIb
20.7
34.5
13.8
VGIIc
VGIIc
B9295
VGIIc
21.0
17.1
−3.8
non-VGIIa
26.0
19.6
−6.4
non-VGIIb
22.1
28.1
5.9
VGIIc
VGIIc
B9302
VGIIc
26.7
15.6
−11.1
non-VGIIa
23.7
15.4
−8.3
non-VGIIb
19.4
34.3
15.0
VGIIc
VGIIc
B9374 VGIIc 27.4 21.6 −5.8 non-VGIIa 24.0 15.3 −8.7 non-VGIIb 19.4 33.4 14.0 VGIIc VGIIc

Table 6.

Interassay and Intraassay for MLST and Subtyping MAMA

Assay interrun CV (%) intrarun CV (%)
VGI
4.33
1.56
VGII
2.35
0.22
VGIII
0.43
0.60
VGIV
1.37
1.08
VGIIa
0.22
0.50
VGIIb
1.27
0.92
VGIIc 1.61 0.32

Table 7.

Lower limit dynamic range for MLST and subtyping MAMA primer sets

Primer set tested Limit (pg) Median Ct
VGI
0.5
31.7
non-VGI
0.5
31.1
VGII
0.5
29.5
non-VGII
0.5
28.7
VGIII
0.5
28.5
non-VGIII
0.5
29.9
VGIV
0.5
33.7
non-VGIV
0.5
33.2
VGIIa
0.5
30.2
non-VGIIa
0.5
31.2
VGIIb
0.5
30.1
non-VGIIb
0.5
28.5
VGIIc
0.5
37.4
non-VGIIc 0.05 39.4

Discussion

C. gattii is an emerging pathogen in the US Pacific Northwest and British Columbia. Molecular and epidemiological investigations revealed the Vancouver Island, BC outbreak was attributed to a novel and seemingly hypervirulent VGIIa genotype [7,20,22]; moreover, the recent PNW outbreak was attributed to an additional novel genotype, VGIIc [23]. These apparent new genotypes (VGIIa and VGIIc), are responsible for greater than 90% of C. gattii infections in the BC/PNW region [7]. Given the increased virulence, varying antifungal susceptibilities and clinical outcomes caused by these genotypes, as compared to other C. gattii genotypes, it will be useful to conduct regular genotyping of C. gattii isolates for both clinical and epidemiological response purposes [5,7,9,16].

We have developed a MAMA real-time PCR panel for cost-efficient and rapid genotyping of C. gattii molecular types (I-IV) and VGII subtypes (a-c) as a means to better understand genotype distribution of C. gattii in North America. To validate the assays, we screened DNA from a diverse North American and international isolate collection of C. gattii isolates from human, environmental, and animal sources. All DNA had been previously typed by MLST. The assay panel performed with 100% sensitivity and specificity and was 100% concordant with MLST results. The VGII subtype specific assays may be more pertinent to the North American public health and medical communities; the molecular type (I-IV) specific assays will be useful for both North American and global genotyping. The assay is designed for screening in a cost-effective, step-wise manner. The molecular type-specific assays should be performed first on all isolates. In North America, the VGIV assay can be withheld for the first screen, as isolates of this molecular type have not yet been isolated from North America. For those North American isolates that are VGII by molecular type, the subtype-specific assays should be performed for typing VGIIa, VGIIb, or VGIIc. As we further our understanding of C. gattii populations around the world and their genotype-phenotype relationships, additional subtype specific assays can be similarly developed for local and global research purposes.

Conclusions

These PCR-based assays are an affordable, efficient, and sensitive means of genotyping C. gattii isolates. Both the assay methods and results can be easily transferred among laboratories. Assay results are based on real-time PCR cycle threshold values and are therefore objective and straightforward for local analysis. The assay panel presented here is a useful tool for conducting large-scale molecular epidemiological studies by public health and research laboratories.

Ethics statement

This study does not involve subjects or materials that would require approval by an ethics committee.

Abbreviations

MAMA: Mismatch amplification mutation assay; MLST: Multilocus sequence typing; PCR-RFLP: PCR-restriction fragment length polymorphism; AFLP: Amplified fragment length polymorphism; MLMT: Multilocus microsatellite typing; HRM: High resolution melting; MALDI-TOF MS: Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry; ASPCR: Allele-specific PCR; SNP: Single nucleotide polymorphism; Ct: Cycle threshold; MPD1: Mannitol-1-phosphate dehydrogenase; WGST: Whole genome sequence typing.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

EK designed the assays, assisted with assay validation, data analysis and drafted the manuscript. EMD participated in the design and coordination of the study, data analysis and assisted with drafting the manuscript. KE performed assay validation and data analysis and assisted with drafting the manuscript. MB was involved in the study conception, design and coordination. JS and JG assisted with data analysis for study design. JT performed assay validation and assay data analysis. SL and ED assisted with study conception, design and coordination and manuscript review. PK assisted with study design, coordination and manuscript review. DE assisted with study conception, design, coordination, and drafting of the manuscript. All authors read and approved the final manuscript.

Contributor Information

Erin J Kelley, Email: ekelley@tgen.org.

Elizabeth M Driebe, Email: edriebe@tgen.org.

Kizee Etienne, Email: guf1@cdc.gov.

Mary E Brandt, Email: mbb4@cdc.gov.

James M Schupp, Email: jschupp@tgen.org.

John D Gillece, Email: jgillece@tgen.org.

Jesse S Trujillo, Email: jst46@email.arizona.edu.

Shawn R Lockhart, Email: gyi2@cdc.gov.

Eszter Deak, Email: edeak@mednet.ucla.edu.

Paul S Keim, Email: paul.keim@nau.edu.

David M Engelthaler, Email: dengelthaler@tgen.org.

Acknowledgements

The findings and conclusions of this article are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.

The authors wish to thank the members of the Cryptococcus gattii Public Health Working Group for submission of many of the isolates used in this study.

This work was supported by funds from the National Institutes of Health: R21AI098059.

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