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. 2024 Mar;5(3):e261–e271. doi: 10.1016/S2666-5247(23)00362-2

Development and validation of quantitative PCR assays for HIV-associated cryptococcal meningitis in sub-Saharan Africa: a diagnostic accuracy study

Tshepiso Mbangiwa a,b,c, Aude Sturny-Leclère b, Kwana Lechiile a, Cheusisime Kajanga d, Timothée Boyer-Chammard b,e, Jennifer C Hoving c,f, Tshepo Leeme a, Melanie Moyo d, Nabila Youssouf a,g, David S Lawrence a,g, Henry Mwandumba c,h, Mosepele Mosepele a,i, Thomas S Harrison j,k,l, Joseph N Jarvis a,g, Olivier Lortholary b,m, Alexandre Alanio b,n,∗; AMBITION Study Group∗, on behalf of the
PMCID: PMC10914677  PMID: 38342110

Summary

Background

HIV-associated cryptococcal meningitis is the second leading cause of AIDS-related deaths, with a 10-week mortality rate of 25–30%. Fungal load assessed by colony-forming unit (CFU) counts is used as a prognostic marker and to monitor response to treatment in research studies. PCR-based assessment of fungal load could be quicker and less labour-intensive. We sought to design, optimise, and validate quantitative PCR (qPCR) assays for the detection, identification, and quantification of Cryptococcus infections in patients with cryptococcal meningitis in sub-Saharan Africa.

Methods

We developed and validated species-specific qPCR assays based on DNA amplification of QSP1 (QSP1A specific to Cryptococcus neoformans, QSP1B/C specific to Cryptococcus deneoformans, and QSP1D specific to Cryptococcus gattii species) and a pan-Cryptococcus assay based on a multicopy 28S rRNA gene. This was a longitudinal study that validated the designed assays on cerebrospinal fluid (CSF) of 209 patients with cryptococcal meningitis at baseline (day 0) and during anti-fungal therapy (day 7 and day 14), from the AMBITION-cm trial in Botswana and Malawi (2018–21). Eligible patients were aged 18 years or older and presenting with a first case of cryptococcal meningitis.

Findings

When compared with quantitative cryptococcal culture as the reference, the sensitivity of the 28S rRNA was 98·2% (95% CI 95·1–99·5) and of the QSP1 assay was 90·4% (85·2–94·0) in CSF at day 0. Quantification of the fungal load with QSP1 and 28S rRNA qPCR correlated with quantitative cryptococcal culture (R2=0·73 and R2=0·78, respectively). Both Botswana and Malawi had a predominant C neoformans prevalence of 67% (95% CI 55–75) and 68% (57–73), respectively, and lower C gattii rates of 21% (14–31) and 8% (4–14), respectively. We identified ten patients that, after 14 days of treatment, harboured viable but non-culturable yeasts based on QSP1 RNA detection (without any positive CFU in CSF culture).

Interpretation

QSP1 and 28S rRNA assays are useful in identifying Cryptococcus species. qPCR results correlate well with baseline quantitative cryptococcal culture and show a similar decline in fungal load during induction therapy. These assays could be a faster alternative to quantitative cryptococcal culture to determine fungal load clearance. The clinical implications of the possible detection of viable but non-culturable cells in CSF during induction therapy remain unclear.

Funding

European and Developing Countries Clinical Trials Partnership; Swedish International Development Cooperation Agency; Wellcome Trust/UK Medical Research Council/UKAID Joint Global Health Trials; and UK National Institute for Health Research.

Introduction

HIV-associated cryptococcal meningitis is the second leading cause of all AIDS-related mortality.1 An estimated 152 000 cases of cryptococcal meningitis occur each year, leading to approximately 112 000 deaths.2 Even with the recommended available antifungal regimens such as amphotericin B, flucytosine, and fluconazole, 10-week mortality is still 25–30%.3,4

Research in context.

Evidence before this study

We searched primary and review articles on PubMed, with the search terms cryptococcosis and cryptococcal diagnosis, up until Jan 15, 2023. Only results in English were included. Eight primary studies were identified that had either developed or validated quantitative PCR assays for Cryptococcus neoformans and Cryptococcus gattii in different specimens, such as fungal strains, mice tissue, and clinical samples (cerebrospinal fluid [CSF], sputum, and blood). However, most of these assays were not validated on clinical specimens (only fungal strains) and were qualitative (conventional PCR). One study was quantitative, but it was not validated on human samples, therefore potential use of the primer sets for monitoring patient prognosis is limited.

Added value of this study

We developed and validated qPCR and reverse transcriptase qPCR assays based on QSP1 and 28S rRNA that show good correlation with quantitative cryptococcal culture, which is the current gold standard for cryptococcal infection confirmation and is also a prognostic marker of the disease. Our assays enabled identification of the species involved (C neoformans vs C gattii) on initial CSF samples. We also showed good sensitivity of our designed assays when compared with quantitative cryptococcal culture. We were able to follow the decrease of the fungal load under optimal treatment within the first 14 days of therapy. Our assays could be used in place of quantitative cryptococcal culture to improve turnaround times, which could help to decrease morbidity and mortality of cryptococcal meningitis.

Implications of all the available evidence

The WHO fungal priority pathogens list was released in 2022 to guide research, development, and public health action. One of the key areas identified for action was strengthening laboratory capacity and surveillance. C neoformans, which is the leading cause of cryptococcal meningitis in sub-Saharan Africa, is listed in the critical group of pathogens and therefore urgent attention to the pathogen is essential. Our qPCR assays could improve laboratory surveillance of cryptococcal meningitis due to C neoformans and C gattii species by reducing turnaround times and increasing laboratory efficiency. Identification and quantification on the initial CSF sample is the first step in designing new clinical studies of therapeutic strategies for cryptococcal meningitis. Our assays are currently used in our clinical laboratory to improve the diagnosis of cryptococcal meningitis in France. We recommend the use of our developed assays in mycology laboratories, to improve timely monitoring of patient response to treatment, and in future clinical trials at diagnosis, to identify patients with high fungal burden and evaluate different therapeutic strategies.

Cryptococcus neoformans and Cryptococcus gattii species complexes are responsible for cryptococcosis in humans. C neoformans is the predominant causative organism, with elevated morbidity and mortality in immunocompromised individuals, whereas C gattii is predominant in immunocompetent individuals.5 C neoformans species complex can be characterised into serotype A (C neoformans), serotype D (C deneoformans), and A–D hybrids, and C gattii species complexes are subdivided into serotype B and serotype C, including C gattii, Cryptococcus bacillisporus, Cryptococcus deuterogattii, Cryptococcus tetragattii, and Cryptococcus decagattii.6 At least three quantitative PCR (qPCR) assays have already been developed to discriminate these species on pure colony DNA;7, 8, 9 however, these assays are limited in their diagnostic capacity because most of them are qualitative and not validated on clinical specimens following Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines.10

Methods used to diagnose cryptococcal meningitis include India ink staining, fungal culture, and cryptococcal polysaccharide capsular antigen (CrAg) detection. CrAg detection can be performed with lateral flow assays, which are easy and quick to perform.11, 12, 13, 14 However, CrAg assays are primarily qualitative and semi-quantitative and do not correlate with the fungal load under treatment, which could be important for the timely monitoring of patient prognosis. Kinetics of CrAg in patients on treatment cannot be used as a prognostic marker because they do not correlate well with a decline in quantitative cryptococcal culture. CrAg also remains positive even after patients have cleared colony-forming units (CFU) via quantitative cryptococcal culture, which limits the usefulness of CrAg testing in patient monitoring.14,15 CFU counts using quantitative cryptococcal culture are performed in research studies to quantify the fungal load of culturable yeasts in the cerebrospinal fluid (CSF) and evaluate early fungicidal activity.16,17 However, quantitative cryptococcal culture is fastidious and time-consuming. qPCR allows for DNA quantification and reverse transcriptase qPCR (RT-qPCR) allows for whole nucleic acid (WNA) amplification and evaluation of viability by detecting mRNA18, 19, 20, 21 and is a potential alternative method to monitor patient response to treatment.20

In this study, we aimed to develop and validate qPCR assays for the identification of Cryptococcus species using CSF samples from patients presenting with cryptococcal meningitis.

Methods

Study design

We developed and evaluated four qPCR assays to identify Cryptococcus species or species complexes and quantify Cryptococcus load directly from CSF. We then validated our assays using CSF samples from participants enrolled in the AMBITION-cm trial in sub-Saharan Africa (ISRCTN72509687) to offer a quantitative molecular approach to monitor fungal load dynamics. This study was performed at Institut Pasteur (Paris, France). The AMBITION study compared a single high dose of liposomal amphotericin B (10 mg/kg of bodyweight) on day 1 plus 14 days of flucytosine (100 mg/kg per day) and fluconazole (1200 mg per day) to the reference treatment, which included amphotericin B deoxycholate (1 mg/kg per day) plus flucytosine (100 mg/kg per day) for 7 days, followed by fluconazole (1200 mg per day) for 7 days (control).

qPCR assays and primer design

Primers specific to C neoformans (serotype A), C deneoformans (serotype D), and C gattii species complex (serotype B or C) were designed using Primer3 version 4.0 and checked for secondary structures with the OligoAnalyzer Tool. Primer-BLAST was used to check for in-silico specificity. Two assays were developed, targeting the single copy gene Quorum sensing protein 1 (QSP1) and the multicopy gene 28S rRNA (figure 1). QSP1 is a Cryptococcus-specific gene with no ortholog or paralogs outside of C neoformans and C gattii species complexes.22 The 28S rRNA gene is a repeated gene, a category of genes that is currently recommended to improve the sensitivity of the qPCR assay.10 However, the number of copies can vary between isolates.23 Therefore, for precise quantification, a unique gene (here QSP1) is preferred, when sensitivity of the detection is not an issue. The 28S rRNA assay was designed to capture the complete diversity within the C neoformans and C gattii species complexes in one single assay because designing a specific assay for each recently described species6 is not cost-effective or relevant in routine care.

Figure 1.

Figure 1

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Schematic representation of the assays used in this study

C neoformans=Cryptococcus neoformans. CSF=cerebrospinal fluid. qPCR=quantitative PCR. RT-qPCR=reverse transcriptase quantitative PCR. WNA=whole nucleic acid.

Three QSP1 assays specific to serotype A (QSP1A), D (QSP1D), and B or C (QSP1B/C) were designed for identification and precise quantification (one copy corresponding to one cell; figure 1). The 28S rRNA assay was designed to be pan-Cryptococcus and to improve sensitivity to detect low fungal loads as present in several copies in the genome. An RT-qPCR assay detecting QSP1 mRNA using QSP1A primers was used to validate and check Cryptococcus viability in the clinical specimens. Indeed, mRNA is one of the most abundant transcripts in the Cryptococcus cells.22 Because mRNA transcripts are more fragile than DNA copies, a decreased detection of mRNA as compared with DNA was considered as a proxy of dead yeasts, with only viable cells allowing the production of an increased quantity of mRNA (appendix p 3).

Primer specificity

The primers were tested on the C neoformans reference strain H99, with cells seeded in phosphate-buffered saline (simulated CSF) and in healthy blood samples at different concentrations and stored at –80°C for at least 48 h. This method was intended to mimic the storage conditions of the CSF specimens collected during the trial.3 The assays were tested on all the C neoformans and C gattii species complexes, and a panel of 89 other species (appendix p 2) and 14 human DNA samples from patients undergoing toxoplasma screening in blood without cryptococcosis to rule out cross-reactivity. The primer sequences are shown in the table.

Nucleic acid extractions

For optimisation experiments (appendix p 3), WNA (representing DNA + RNA) was extracted from phosphate-buffered saline (PBS) seeded with H99 cells (simulated CSF) using the MagNA Pure 96 Instrument (Roche Diagnostics, Mannheim, Germany) and Viral NA Large Volume Kit (Roche Diagnostics). We used the DNA Blood LV 1000 (Roche Diagnostics) and the Pathogen Universal 1000 (Roche Diagnostics) kits for DNA extraction and compared their cycle quantification (Cq) values. Different pretreatment conditions were tested, including untreated (control), bead beating, adding 50 μL of proteinase K and 10 min incubation at 65°C, and a combination of bead beating and adding proteinase K.

For patient CSF screening, WNA was extracted from frozen CSF pellet obtained by centrifugation of 1 mL of CSF. The Pathogen Universal 1000 was used for extraction with 100 μL of elution. The RNA Process Control Kit (Roche Diagnostics) was used as an internal control in RT-qPCR, and a DNA internal control kit (DICR-CY5, Diagenode, Seraing, Belgium) was used in qPCR runs, with a defined virus quantity directly added in the sample before extraction, as recommended.10

qPCR and RT-qPCR

A Light Cycler 480 Instrument II (Roche Diagnostics) was used for all qPCR and RT-qPCR amplification and Cq analyses. A Light Cycler 480 Probes Master kit (Roche Diagnostics) was used for all qPCR reactions, and a TaqMan Fast Virus 1-Step Master Mix kit (Thermo Fisher Scientific, Waltham, MA, USA) was used for all RT-qPCR reactions. Final concentrations of 0·5 μM (primer) and 0·2 μM (probe) were used for QSP1, and of 0·4 μM (primer) and 0·2 μM (probe) for 28S rRNA (table). qPCR reactions were run as follows: 95°C for 10 min, and 50 cycles of 95°C for 10 s, 58°C for 30 s, and 40°C for 30 s, with an additional initial step at 50°C for 5 min for RT-qPCR. All Cq values over 40 were considered negative. All qPCR assays were performed blind to quantitative cryptococcal culture results and all clinical information.

Table.

Species-specific primer and probe sets that were designed and used in this study

Sequence (5'-3') Melting temperature (°C) Length (bp) Amplicon length (bp)
H99_QSP1_RNA_F2 ACCACTCTTTTCACTGCTG 56·2 19 105
H99_QSP1_RNA_R2 GGCGCCGAAGTTGTTAG 56·6 17 105
H99_QSP1_RNA_P2 CTTGTCCTCATCGCCCCGGCCCTC 71·9 24 105
WM276_QSP1_F2 ACCACACTTTTCACTGCCG 56·2 19 105
WM276_QSP1_R2 GGCACCGAAGTTCTGAG 56·6 17 105
WM276_QSP1_P3 CTTGTCCTCATCGCCCCTGCCCTC 65·5 24 105
JEC21_QSP1_F2 ACCACCCTTTTCACTGCTG 56·2 19 105
JEC21_QSP1_R2 GGCGCCGAAGTTCTGAG 56·6 17 105
JEC21_QSP1_P2 CTTGTCCTCATCGCCCCGGCCCTC 71·9 24 105
AMB_28S rRNA_F3 GCAGGTCTCCAAGGTGAA 52·8 18 137
AMB_28S rRNA_R4 CCAGCTTCCTTCCGTCAA 55·0 18 137
AMB_28S rRNA_P4 TTGGCTCTAAGGGTTGGGTGCGTCGGG 67·7 27 137
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H99 is a reference strain of Cryptococcus neoformans; WM276 is a reference strain of Cryptococcus gattii; and JEC21 is a reference strain of Cryptococcus deneoformans. F represents a forward primer; R represents a reverse primer; and P represents a probe.

To quantify QSP1A expression, 106 H99 cells were heat-killed (65°C for 2 h) and exposed to 1 mM of H2O2 for 1 h with stationary phase yeasts as control and extracted as above. QSP1 mRNA expression was compared to that of actin (ACT1) considering the efficiency (E) of both assays (QSP1, E=2; ACT1, E=1·92).24

Ten-fold dilutions from the strain H99 cells (QSP1A), WM276 cells (QSP1B/C), and JEC21 cells (QSP1D) were used to create a standard curve, and extrapolation was used to determine the absolute number of Cryptococcus cells present in the sample (appendix p 3).

A semi-quantitative lateral flow CrAg test (CryptoPS; Biosynex, Strasbourg, France) was performed on plasma according to the manufacturer’s instructions.25,26

Study participants and samples

We collected samples from 209 participants with cryptococcal meningitis from Botswana (n=85) and Malawi (n=124) enrolled in the AMBITION-cm randomised controlled trial. Patients aged 18 years or older presenting with a first episode of cryptococcal meningitis, which was diagnosed with India ink or CrAg, were enrolled in the study. For this qPCR analysis, samples collected from patients presenting at Princess Marina Hospital (Gaborone, Botswana) and Blantyre Central Hospital (Blantyre, Malawi) in 2018–21 were used.3 CSF samples collected at day 0 (baseline), day 7, and day 14 post antifungal treatment initiation were tested with quantitative cryptococcal culture27 and qPCR and RT-qPCR assays. Ethical approval was obtained from the University of Botswana Institutional Review Board and the University of Malawi Research and Ethics Committee and national regulatory bodies. Written informed consent was sought from participants for the initial AMBITION study; for those who did not have the capacity to consent, consent was sought from their next of kin.3,27

Statistical analysis

GraphPad Prism 9.4.0 was used for statistical analysis and data visualisation. Diagnostic accuracy outside sensitivity has not been calculated due to the lack of testing of patients without cryptococcal meningitis. Diagnostic measures were compared between the assays using Bland-Altman tests. Missing data were not included in the statistical analyses. Sample size was determined for the clinical study but was not calculated for our analyses because there were no anticipated results available in the literature and previous studies. Kruskal-Wallis tests were used to compare means between three or more matched groups when the data were not normally distributed, and Mann-Whitney tests were used for comparison of two groups when the data were not normally distributed. For the analytical specificity of the assays, the fold change ratio of the strains relative to the reference strain was determined. A ratio of 0–0·3 indicated no amplification to poor amplification, 0·4–0·6 indicated low amplification, and 0·7–1·0 indicated good to very good amplification. p<0·05 was considered to indicate a statistically significant difference.

Role of the funding source

The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Results

The 28S rRNA assay amplified all C neoformans and C gattii species complexes with ratios of 0·46–1·00 depending on the species tested. Species complexes other than C neoformans or C gattii were not amplified or were very poorly amplified with ratios of 0·01–0·33 (appendix p 2). No cross-reaction with non-Cryptococcus species complex strains (100% analytical specificity) was observed.

All QSP1 assays (QSP1A, QSP1B/C, and QSP1D) were tested on the same 93 fungal species and did not amplify any of the species (appendix p 1). The QSP1A assay amplified serotype A DNAs with a ratio of 0·61–1·00, with the exceptions of VNII_T4, VNII_8, and VNBII_Bt1, for which amplification was lower, with a ratio of 0·12–0·27. The QSP1A assay was able to perfectly amplify VNIII (AD hybrid) with a ratio of 1, but not C deneoformans and C gattii species (appendix p 2). The QSP1D assay amplified C deneoformans and VNIII (AD hybrid) with a ratio of 0·67–1·00, but not C neoformans and C gattii species. The QSP1B/C assay allowed amplification of C gattii species, mainly C gattii sensu stricto, C deuterogattii, and C tetragattii (VGI, VGIV, and VGII), with ratios greater than 0·72. However, C bacillisporus DNAs were amplified with ratios of less than 0·1. The QSP1B/C assay did not amplify C neoformans and C deneoformans DNA.

To optimise and validate our qPCR assays, we first used spiked samples. The limit of detection for the QSP1A assay was 50 genomes per reaction and for the 28S rRNA assay was one genome per reaction. The efficiency of the QSP1A assay was 1·98 (slope –3·347, r2=0·998), and of the 28S rRNA assay was 2·08 (slope –3·141, r2=0·993; appendix p 3). For comparison of pre-extraction procedures, amplification of untreated (control) condition after freezing gave a significantly lower Cq value than the other conditions, including bead beating (p<0·0001), addition of proteinase K (p=0·030), and a combination of bead beating and addition of proteinase K (p<0·0001; appendix p 3) suggesting better extraction efficiency. There were no statistically significant differences between the two extraction protocols (Pathogen Universal and DNA Blood) of CSF tested on the MagNA Pure 96 Instrument (appendix p 3).

Upon screening of clinical CSF samples from baseline in 209 participants (demographic characteristics are provided in the appendix p 4), including 85 from Botswana and 124 from Malawi, we found a 67% prevalence (95% CI 55–75) of C neoformans in Botswana and 68% prevalence (57–73) in Malawi. The prevalence of C gattii species complex was higher in Botswana (21%; 14–31) than in Malawi (8%; 4–14). Ten (12%) of 85 samples in Botswana and 29 (23%) of 124 samples in Malawi could not be serotyped due to low fungal load (QSP1 negative, 28S rRNA positive). No C deneoformans cryptococcal meningitis was detected in both countries. Of note, three (4%) samples were missing at baseline in Botswana and one (1%) was missing at baseline in Malawi.

We compared the quantification obtained in CSF pellet samples from C neoformans and C gattii cryptococcal meningitis using QSP1 and 28S rRNA qPCR assays based on Cq values. There was no statistically significant difference in the initial fungal loads (expressed as Cq) of C neoformans and C gattii cryptococcal meningitis with the QSP1 assay (35·18 [IQR 30·45–38·36] vs 34·57 [31·19–37·32], respectively) or the 28S rRNA assay (28·77 [24·66–32·77] vs 27·64 [24·87–31·73], respectively; figure 2C). Similarly, no significant differences were observed for quantification by quantitative cryptococcal culture, QSP1 assay, and 28S rRNA assay with absolute yeast number (figure 3G–I). The differences in Cq value (ΔCq) between QSP1 and 28S rRNA assays for each CSF were significant: ΔCq of 5·71 (IQR 5·09–6·32), reflecting about 50 copies of 28S rRNA per genome in C neoformans, and ΔCq of 6·55 (5·75–7·78), reflecting about 100 copies of 28S rRNA per genome in C gattii (figure 2C). A similar finding was observed in the DNA extracted from strains during previous optimisations (appendix p 3).

Figure 2.

Figure 2

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Comparison of QSP1 and 28S rRNA assays to QCC and description of the proportion of positive quantitative tests in the cohort

(A) Correlation between QSP1 quantification (log10 Cn cells per mL) and QCC (log10 Cn cells per mL), between 28S rRNA quantification (log10 Cn cells per mL) and QCC, and between 28S rRNA and QSP1 using CSF pellet results at baseline (before starting antifungal treatment). (B) Proportion of CSF pellet and supernatant sample fractions amplified by QSP1A, QSP1B/C (combined in the figure as QSP1), and 28S rRNA assays at day 0 (baseline), day 7, and day 14 of antifungal treatment. (C) Fungal loads in CSF at day 0 with QSP1 and 28S rRNA assays in C neoformans and C gattii. The boxes show median and IQR, and the whiskers show the range. Cn=Cryptococcus neoformans or Cryptococcus gattii. Cq=quantification cycles. CSF=cerebrospinal fluid. NS=not significant. QCC=quantitative cryptococcal culture. WNA=whole nucleic acid.

Figure 3.

Figure 3

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Cryptococcal fungal load quantification

Cryptococcal fungal load was quantified at day 0 (baseline), day 7, and day 14 in the cerebrospinal fluid of participants by QCC, QSP1 assay, and 28S rRNA assay in total populations (A–C) and in the control or single-dose regimens (D–F). Serotype-specific fungal load was quantified at day 0 by QCC, QSP1 assay, and 28S rRNA assay (G–I). The boxes show median and IQR, and the whiskers show the range. Cn=Cryptococcus neoformans or Cryptococcus gattii. NS=not significant. QCC=quantitative cryptococcal culture.

We quantified DNA using QSP1 assays and 28S rRNA assays in CSF pellets and in CSF supernatant. We also quantified WNA (RNA plus DNA) in the CSF pellet as a potential proxy of the viability of the yeasts present in the pellet (n=110). At baseline in CSF pellets, the proportion of positivity with DNA was higher with quantitative cryptococcal culture (200 [95%] of 208 participants positive) and 28S rRNA assay (177 [94%] of 184), as compared with the QSP1 assay, with which 163 (88%) of 184 were positive (figure 2B). At day 14, the QSP1 and 28S rRNA assays showed an increased proportion of positive samples (43% and 69%, respectively) compared with quantitative cryptococcal culture (23%).

At baseline in CSF pellets, the sensitivity of the 28S rRNA assay was 98·2% (95% CI 95·1–99·5) and of the QSP1 assay was 90·4% (85·2–94·0) when compared with quantitative cryptococcal culture as the reference standard. Indeed, three CSF samples that were negative on quantitative cryptococcal culture were found to be positive with the 28S rRNA and QSP1 assays. The sensitivity was 98·0% (94·4–99·5) for the 28S rRNA assay and 93·0% (87·9–96·0) for the QSP1 assay when compared with the India ink results. Of note, 27 and 16 CSF samples that were negative on India ink were found to be positive with the 28S rRNA and QSP1 assays, respectively.

Detection of 28S rRNA DNA in CSF supernatant samples gave a lower proportion of positivity compared with CSF pellet samples, with a maximum difference at day 14 (43% in supernatant vs 69% in pellet; figure 2B). QSP1 WNA positivity was lower compared with QSP1 DNA in CSF pellet samples at all timepoints but was still more positive at day 14 than in samples that were quantified with quantitative cryptococcal culture (34% for QSP1 WNA vs 23% for quantitative cryptococcal culture). A Bland-Altman analysis showed an agreement between quantitative cryptococcal culture and QSP1 or 28S rRNA with a ratio bias of 1·24 (SD 0·28) and 0·90 (SD 0·24), respectively (appendix p 5).

We compared the quantification of fungal load with quantitative cryptococcal culture and QSP1 and 28S rRNA qPCR assays in CSF pellet samples at baseline. We found strong positive correlations between the three assays (figure 2A).

QSP1 and 28S rRNA assays showed a significant decrease in cryptococcal fungal load between baseline and day 7 (both p<0·0001), between day 7 and day 14 (p<0·0001 for QSP1 and p=0·0050 for 28S rRNA), and between baseline and day 14 (both p<0·0001; figure 3B, C), which was similar to the decrease observed with quantitative cryptococcal culture (figure 3A). Of note, fungal load dynamics were similar in patients from each treatment group, thereby suggesting a similar fungicidal activity of the two strategies (figure 3D–F).

Of the 151 participant plasma samples that were determined as serotype A or B/C, and which were tested with CryptoPS at baseline, 98 (65%) had a positive T1 and T2 band, 49 (32%) had a positive T1 band, and four (3%) were negative. Negative CryptoPS tests were identified in serotype B/C infections (4/24, 17%), whereas all serotype A participants had a positive CryptoPS test in the plasma at baseline. In serotype B/C, four samples were negative with CrAg but positive with quantitative cryptococcal culture (figure 4A), three were negative with CrAg but positive with the QSP1 assay (figure 4B), and three were negative with CrAg but positive with the 28S rRNA assay (figure 4C).

Figure 4.

Figure 4

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Quantification of the fungal load in the cerebrospinal fluid of participants with a positive T1 and T2 band, a positive T1 band, or who were negative in CryptoPS testing in plasma at baseline (day 0)

Quantification is shown for serotype A and B/C with QCC (A), QSP1 assay (B), and 28S rRNA assay (C). The boxes show median and IQR, and the whiskers show the range. Cn=Cryptococcus neoformans or Cryptococcus gattii. QCC=quantitative cryptococcal culture.

We also wanted to determine whether the DNA detected and quantified in CSF came from viable yeasts using our QSP1 assay with a reverse transcriptase step (RT-qPCR) allowing the detection and quantification of QSP1 mRNA and DNA. We first validated that dead cells in vitro had a decreased expression of QSP1A as compared with ACT1 and a stationary phase control (appendix p 3). Using the H99 WNA, we found an increased quantification with RT-qPCR (median Cq 26·55 [IQR 22·86–32·59]) compared with qPCR (30·61 [27·46–36·61], p<0·0001; appendix p 3).

In patients, we found an increased QSP1A WNA quantification using RT-qPCR as compared with qPCR at all timepoints (baseline, day 7, and day 14, p<0·0001; figure 5A–C). An increase of between 0·8 (baseline) and 1·1 (days 7 and 14) log10 C neoformans cells was observed with WNA, showing that QSP1A mRNA was present in a higher quantity (around 10-times higher) than DNA. This finding suggested that yeast cells detected in the CSF pellet were viable, resulting in the detection of more QSP1 mRNA than DNA, and showing active expression of the QSP1 gene.

Figure 5.

Figure 5

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QSP1 DNA and WNA quantification in CSF pellet and comparison between QCC and QSP1 WNA load

QSP1 DNA (qPCR) and WNA (RT-qPCR) were quantified in CSF pellet at baseline (day 0; A), day 7 (B), and day 14 (C) using QSP1 assays. The boxes show median and IQR, and the whiskers show the range. QSP1 WNA load was compared with QCC at baseline (D), day 7 (E), and day 14 (F). Red circles are participants with negative QCC and positive QSP1 WNA detection. Cn=Cryptococcus neoformans or Cryptococcus gattii. CSF=cerebrospinal fluid. QCC=quantitative cryptococcal culture. qPCR=quantitative PCR. RT-qPCR=reverse transcriptase quantitative PCR. WNA=whole nucleic acid.

We then compared quantitative cryptococcal culture load and QSP1 WNA load in individual samples. Quantitative cryptococcal culture was negative and QSP1 WNA positive in one sample at baseline and day 7, and in 17 samples at day 14 (figure 5D–F, red circles). We thus identified patients with a negative CSF culture but a positive QSP1 RT-qPCR assay, suggesting that viable but non culturable yeasts were observed in the CSF during meningitis. The week 10 mortality of these patients was 25·1% (51/203).

Discussion

In this study, several qPCR and RT-qPCR assays (QSP1A, QSP1B/C, and QSP1D, and 28S rRNA assays), allowing Cryptococcus load quantification and identification of C neoformans, C deneoformans, and C gattii species complexes, were designed, optimised, and clinically evaluated using samples from the AMBITION-cm trial.3 The analytical specificity and the clinical sensitivity have been validated and show optimal performance, following dedicated MIQE guidelines.10 We report optimal qPCR efficiencies of around 100% for all assays. We recommend using the 28S rRNA assay as a screening assay and, when positive, identifying the species and quantifying the fungal load with the three QSP1 qPCR assays.

Of note, we identified a high burden of C gattii species complex infections in Botswana (21%), as already reported (30% for Botswana).28,29 No C deneoformans (serotype D) cases were detected, as already shown.30

The designed QSP1 and 28S rRNA assays showed excellent correlation with quantitative cryptococcal culture quantification. Quantitative cryptococcal culture is the current gold standard for fungal load quantification, with a reported 94·2% sensitivity in South Africa and Uganda.13 We observed a gap between quantitative cryptococcal culture and DNA detection, with an increased number of participants detected with the QSP1 and 28S rRNA qPCR assays, suggesting that yeasts that were unable to grow on culture media or that were dead could be detected by qPCR. Nevertheless, participants had lower fungal loads at day 7 or day 14 (or both) than at baseline, demonstrating the early fungicidal activity of the two different treatment groups of the AMBITION study.3 This finding is important because a decrease of the fungal load and fungicidal activity could be determined using qPCR quantification instead of quantitative cryptococcal culture.17

By using WNA amplification with our QSP1 assay, we validated that most of the yeasts detected, even at day 14, were viable, with an increased QSP1A WNA detection compared with DNA. We thus detected significantly more QSP1 WNA than DNA in participants with negative quantitative cryptococcal culture results at baseline, day 7, and day 14, suggesting that living yeasts were present in the CSF despite a negative culture. These cells are suggestive of viable but non-culturable cells (VBNCs), corresponding to viable living yeasts that are not capable of growth on agar medium. This phenotype is known to exist in Cryptococcus yeasts cells and has been identified and characterised by our team.31,32 This is a major finding because RT-qPCR should be better at characterising the presence of viable cells as compared with quantitative cryptococcal culture. It suggests that VBNCs can be found in CSF and that antifungal treatment could induce this phenomenon. More work is needed to investigate VBNCs in human CSF under treatment.

In Botswana, the sensitivity and specificity of CryptoPS were 61·0% and 96·6%, respectively.25 With this test, the C gattii species complex, including C bacillisporus, C deuterogattii, and C tetragattii species, was not detected in vitro.33 Consistent with these findings, our results showed false negative results only in serotype B/C infections. The high prevalence of C gattii species complex infections in Botswana might explain the low sensitivity rate that was previously reported when using CryptoPS locally.25

One of the limitations of the study was that the qPCR assays were performed on frozen material and not in the centre that handled specimen culture, preventing work on fresh material for qPCR, whereas quantitative cryptococcal culture was performed in enrolling centres. We are not yet able to compare the identification performed with our qPCR assays with that obtained with whole-genome sequencing of the cultured isolates, but this work is ongoing.

In conclusion, we designed and validated three qPCR assays for the detection and quantification of Cryptococcus infections in the CSF. These assays have excellent correlation with the gold standard quantitative cryptococcal culture. qPCR will thus provide an easier fungal load monitoring tool and early information on subsequent outcome during HIV-associated cryptococcal meningitis in sub-Saharan Africa. As a diagnostic tool that can speciate and give fungal load, it will allow for new stratified management of patients. Our assays can be used to measure clearance more quickly and easily as an endpoint to assess novel antifungal regimens.

Data sharing

The anonymised data file can be shared, upon request made to the corresponding author (alexandre.alanio@pasteur.fr), via a link allowing the file to be downloaded though an institutional secured server.

Declaration of interests

AA received honoraria for educational activities and webinars from Gilead Sciences and Pfizer and travel grants from Astellas and Gilead Sciences, outside the submitted work. All other authors declare no competing interests.

Acknowledgments

We thank the AMBITION administrative manager for her extensive support, and the AMBITION-cm team, especially personnel in Blantyre and Gaborone. We also thank the AMBITION-cm trial participants and their families and caregivers, as well as all the clinical, laboratory, and administrative staff at all the sites who were not directly involved in the trial. This trial was funded by a grant through the European Developing Countries Clinical Trials Partnership supported by the Swedish International Development Cooperation Agency (SIDA; TRIA2015-1092), and the UK Department of Health and Social Care, the UK Foreign Commonwealth and Development Office, the UK Medical Research Council, and Wellcome Trust, through the Joint Global Health Trials scheme (MR/P006922/1; trial registration number ISRCTN72509687). This work was also funded by the National Institute for Health Research through a Global Health Research Professorship to JNJ (RP-2017-08-ST2-012) using UK aid from the UK Government to support global health research. This publication was made possible in part by a grant from Carnegie Corporation of New York. The statements made and views expressed are solely the responsibility of the authors.

The AMBITION Study Group

J Goodall, N Mawoko, J Milburn, R Mmipi, C Muthoga, P Ponatshego, I Rulaganyang, K Seatla, N Tlhako, K Tsholo (Botswana Harvard AIDS Institute Partnership/Princess Marina Hospital, Gaborone, Botswana); S April, A Bekiswa, L Boloko, H Bookholane, T Crede, L Davids, R Goliath, S Hlungulu, R Hoffman, H Kyepa, N Masina, D Maughan, T Mnguni, S Moosa, T Morar, M Mpalali, J Naude, I Oliphant, S Sayed, L Sebesho, M Shey, L Swanepoel (University of Cape Town/Mitchells Plain Hospital/Khayelitsha District Hospital, Cape Town, South Africa); M Chasweka, W Chimang’anga, T Chimphambano, E Dziwani, E Gondwe, A Kadzilimbile, S Kateta, E Kossam, C Kukacha, B Lipenga, J Ndaferankhande, M Ndalama, R Shah, A Singini, K Stott, A Zambasa (Malawi-Liverpool-Wellcome Trust Clinical Research Programme/Queen Elizabeth Central Hospital, Blantyre, Malawi); T Banda, T Chikaonda, G Chitulo, L Chiwoko, N Chome, M Gwin, T Kachitosi, B Kamanga, M Kazembe, E Kumwenda, M Kumwenda, C Maya, W Mhango, C Mphande, L Msumba, T Munthali, D Ngoma, S Nicholas, L Simwinga, A Stambuli, G Tegha, J Zambezi (UNC Project, Kamuzu Central Hospital, Lilongwe, Malawi); C Ahimbisibwe, A Akampurira, A Alice, F Cresswell, J Gakuru, D Kiiza, J Kisembo, R Kwizera, F Kugonza, E Laker, T Luggya, A Lule, A Musubire, R Muyise, O Namujju, J Ndyetukira, L Nsangi, M Okirwoth, A Sadiq, K Tadeo, A Tukundane, D Williams (Infectious Diseases Institute/Kiruddu General Hospital, Kampala, Uganda); L Atwine, P Buzaare, M Collins, N Emily, C Inyakuwa, S Kariisa, J Mwesigye, S Niwamanya, A Rodgers, J Rukundo, I Rwomushana, M Ssemusu, G Stead (Infectious Diseases Institute/Mbarara Regional Referral Hospital, Mbarara, Uganda); K Boyd, S Gondo, P Kufa, E Makaha, C Moyo, T Mtisi, S Mudzingwa, T Mwarumba, T Zinyandu (University of Zimbabwe/Parirenyatwa General Hospital, Harare, Zimbabwe); F Dromer (Institut Pasteur, Paris, France); P Johnstone, S Hafeez (London School of Hygiene & Tropical Medicine, London, UK).

Contributors

TM was involved in data collection, data analysis, literature search, verification of the underlying data, data interpretation, and drafting and writing of the manuscript. AS-L was involved in study design, data collection, and data analysis. KL, CK, TB-C, TL, MMoy, NY, DSL, HM, MMos, TSH, and JNJ were involved in participant enrolment and review of the manuscript. DSL was involved in the verification of the underlying data. JCH was involved in the manuscript review. OL was involved in the study design and manuscript review. AA was involved in study design, verification of the underlying data, data analysis, literature search, data interpretation, and writing and supervision of the project. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Contributor Information

Alexandre Alanio, Email: alexandre.alanio@pasteur.fr.

AMBITION Study Group:

J Goodall, N Mawoko, J Milburn, R Mmipi, C Muthoga, P Ponatshego, I Rulaganyang, K Seatla, N Tlhako, K Tsholo, S April, A Bekiswa, L Boloko, H Bookholane, T Crede, L Davids, R Goliath, S Hlungulu, R Hoffman, H Kyepa, N Masina, D Maughan, T Mnguni, S Moosa, T Morar, M Mpalali, J Naude, I Oliphant, S Sayed, L Sebesho, M Shey, L Swanepoel, M Chasweka, W Chimang’anga, T Chimphambano, E Dziwani, E Gondwe, A Kadzilimbile, S Kateta, E Kossam, C Kukacha, B Lipenga, J Ndaferankhande, M Ndalama, R Shah, A Singini, K Stott, A Zambasa, T Banda, T Chikaonda, G Chitulo, L Chiwoko, N Chome, M Gwin, T Kachitosi, B Kamanga, M Kazembe, E Kumwenda, M Kumwenda, C Maya, W Mhango, C Mphande, L Msumba, T Munthali, D Ngoma, S Nicholas, L Simwinga, A Stambuli, G Tegha, J Zambezi, C Ahimbisibwe, A Akampurira, A Alice, F Cresswell, J Gakuru, D Kiiza, J Kisembo, R Kwizera, F Kugonza, E Laker, T Luggya, A Lule, A Musubire, R Muyise, O Namujju, J Ndyetukira, L Nsangi, M Okirwoth, A Sadiq, K Tadeo, A Tukundane, D Williams, L Atwine, P Buzaare, M Collins, N Emily, C Inyakuwa, S Kariisa, J Mwesigye, S Niwamanya, A Rodgers, J Rukundo, I Rwomushana, M Ssemusu, G Stead, K Boyd, S Gondo, P Kufa, E Makaha, C Moyo, T Mtisi, S Mudzingwa, T Mwarumba, T Zinyandu, F Dromer, P Johnstone, and S Hafeez

Supplementary Material

Supplementary appendix
mmc1.pdf (862.2KB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary appendix
mmc1.pdf (862.2KB, pdf)

Data Availability Statement

The anonymised data file can be shared, upon request made to the corresponding author (alexandre.alanio@pasteur.fr), via a link allowing the file to be downloaded though an institutional secured server.

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