LETTER
Candida auris is a multidrug-resistant yeast that causes severe invasive infections among patients in health care facilities. C. auris was first reported in 2009 after being isolated from the ear canal of a patient in Japan and in the decade since has become an emerging global pathogen of concern, with increasing prevalence (1–2). Multidrug resistance, high mortality rates, persistence in the environment, and transmission between patients are among the many challenges posed by this pathogen (2–6). Patients colonized with C. auris can remain asymptomatic for months and are at risk of developing clinical cases of severe invasive infections of the bloodstream, ear, wounds, and other body sites (7). They also contribute to transmission by shedding yeast cells from the skin into the environment (8–9). Early detection is therefore critical for the timely implementation of therapy and infection control practices.
Rapid and accurate diagnostics remain a challenge for C. auris. Classic yeast identification methods often mistake C. auris for multiple yeast species (10–14). A reliable method to isolate C. auris was developed in 2017, but it requires an enrichment step that extends the total time to result up to 10 days (4). A number of rapid culture-independent methods have been developed in the last 2 years, including a TaqMan-based quantitative PCR (qPCR) assay developed at the Wadsworth Center. This test is not FDA approved but is currently the most widely implemented molecular test for C. auris (15). Additionally, the Centers for Disease Control and Prevention (CDC) recently evaluated a SYBR green-based C. auris-specific qPCR assay developed by Kordalewska et al. (16). This assay performed well with axilla-groin composite surveillance swabs, demonstrating a sensitivity and specificity of 0.93 and 0.96, respectively, compared to the enrichment culture-based method (gold standard) (9).
Current surveillance strategies at the CDC, including the Antibiotic Resistance Lab Network (ARLN), use bilateral axilla-groin composite swabs for colonization screening. This guidance is derived from 2017 surveillance data which indicated the axilla and groin as the most colonized sites (4). However, accumulating evidence indicates that the anterior nares are also frequently colonized, can harbor high concentrations of C. auris, and may also be a site worth considering for surveillance (17, 18). Because of differences between the nature of anterior nares and the axilla-groin swabs, we revisited the C. auris SYBR green qPCR assay to evaluate whether its use may be extended to anterior nares samples.
Anterior nares surveillance samples were submitted to the CDC by health care facilities using the BD ESwab collection and transport system (catalog no. 220245; BD Diagnostics). A total of 70 samples were received from five facilities located in either California or Illinois. Samples were processed within 4 days of collection using aliquots of equal volumes (100 μl) for both the enrichment culture gold standard and the SYBR green qPCR assay (4, 16). This work was permitted by CDC institutional review board approval (IRB no. 7073). DNA from the swabs was extracted with the Qiagen DNeasy PowerLyzer microbial kit (catalog no. 12255-50) with the following protocol modifications: (i) 5 min of cell collection by centrifugation and (ii) 5 min of incubation in elution buffer. Each sample was eluted in 50 μl and stored at −80°C. Positive and negative extraction controls were included in each run. A pure culture of C. auris was quantified, diluted to a known concentration, and used as the positive control (2 × 104 CFU of C. auris AR-0384 from the CDC and FDA Antibiotic Resistance [AR] Isolate Bank). The SYBR green qPCR was performed on the C1000/CFX 96 system (Bio-Rad) as described previously, with primer pairs CauF/CauR and LambdaF/LambdaR used to amplify the C. auris and internal amplification control (lambda phage) target sequences, respectively (9, 16). Calculation of the metrics used to evaluate assay performance included sensitivity, specificity, and Cohen’s kappa analysis. A receiver operating characteristic (ROC) curve analysis was performed, and the Youden index (J) was calculated, to optimize the melt peak threshold. Data analysis and figures were generated using Python 3.7 scripts dependent on the Pandas, NumPy, MATPLOTlib, and Sklearn packages.
ROC analysis of the C. auris SYBR green qPCR melt curve data returned an area under the curve (AUC) of 1 (Fig. 1A). The maximum Youden index (Jmax = 1) was used as a metric to identify 184 – d(RFU)/dT (where RFU is relative fluorescence units and T is temperature) as the optimum melt peak amplitude threshold used to differentiate samples as positive or negative (Fig. 1B and C). At this threshold, there was perfect agreement between the C. auris SYBR green qPCR and the culture-based gold standard (Cohen’s kappa = 1). Specifically, of the 70 samples processed, the C. auris SYBR green qPCR detected 27 true positives and 43 true negatives; no false positives or false negatives were observed (sensitivity and specificity = 1). Inhibition, as evidenced by failure of the internal amplification control in C. auris-negative samples, was not observed, indicating that the C. auris SYBR green qPCR was robust to interference in this sample set. A limitation of this test, as well as of other existing C. auris diagnostics, is that it lacks a control for the quality of sampling. Current quality assurance depends on adherence to a standard protocol for sample collection as well as expectations that testing facilities require strict criteria to be met before accepting samples for processing. Incorporating quality-of-sampling control measures into the qPCR itself would improve this test as well as other existing methods. The lack of false-positive results highlights the high sensitivity of culture-based detection methods; however, the prolonged time needed for culture results prevents timely implementation of infection control. A limitation of this study is the small sample size available (n = 70); given the fundamental trade-off in diagnostic sensitivity and specificity, we expect the perfect agreement observed to break down with a large enough sample set. Although more samples would be ideal, those used are a valuable representation, because they were collected from several facilities located in two geographically separate regions where different genetic clades of C. auris are found.
Optimization of the threshold selected to translate the continuous melt peak data into a binary diagnostic result based on a ROC curve (A), a plot of sensitivity and specificity as a function of the threshold (B), and the raw melt peak data with the optimized threshold [184 – d(RFU)/dT] shown as a dotted horizontal line (C).
Currently, the TaqMan C. auris qPCR is the most widely implemented culture-independent test for C. auris surveillance. However, the C. auris SYBR green qPCR has several characteristics that make it an attractive option for certain contexts. First, the C. auris SYBR green qPCR can be adapted to a wider variety of qPCR instruments, making this assay accessible to a larger number of laboratories. So far, its good performance in different laboratories has been shown on the Mx3005P (Stratagene) and CFX 96 (Bio-Rrad) qPCR systems (9, 19). The SYBR green qPCR also has fewer components, as it does not require any probe. A limitation of the assay is that the inclusion of the internal amplification control renders the assay qualitative rather than quantitative. In contrast, the quantification cycle (Cq) values returned by the TaqMan qPCR data can be used to assess the concentration of C. auris in the sample. Although quantitative data currently are not used to inform patient care decisions, they may be valuable for colonization burden assessment.
In summary, we have demonstrated that the C. auris SYBR green qPCR can be used as a rapid culture-independent screening diagnostic that is highly concordant with the culture-dependent gold standard in a collection of anterior nares samples. Evaluating established tests with new sample types is important as we learn more about the colonization patterns of this emergent pathogen. Additional work such as this will help improve the capacity to detect/identify and control C. auris.
ACKNOWLEDGMENTS
We thank Anastasia P. Litvintseva for helpful conversations.
D.S.P. receives funding from the U.S. National Institutes of Health and contracts with The Centers for Disease Control and Prevention, Amplyx, Astellas, Cidara, and Scynexis. He serves on advisory boards for Amplyx, Astellas, Cidara, Matinas, N8 Medical and Scynexis. In addition, D.S.P. has an issued U.S. patent concerning echinocandin resistance. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The use of product names in this manuscript does not imply their endorsement by the U.S. Department of Health and Human Services. The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the CDC.
This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.
