PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of jcmPermissionsJournals.ASM.orgJournalJCM ArticleJournal InfoAuthorsReviewers
 
J Clin Microbiol. 2013 July; 51(7): 2195–2203.
PMCID: PMC3697714

Development and Evaluation of a Next-Generation Digital PCR Diagnostic Assay for Ocular Chlamydia trachomatis Infections

Abstract

Droplet digital PCR (ddPCR) is an emulsion PCR process that performs absolute quantitation of nucleic acids. We developed a ddPCR assay for Chlamydia trachomatis infections and found it to be accurate and precise. Using PCR mixtures containing plasmids engineered to include the PCR target sequences, we were able to quantify with a dynamic range between 0.07 and 3,160 targets/μl (r2 = 0.9927) with >95% confidence. Using 1,509 clinical conjunctival swab samples from a population in which trachoma is endemic in Guinea Bissau, we evaluated the specificity and sensitivity of the quantitative ddPCR assay in diagnosing ocular C. trachomatis infections by comparing the performances of ddPCR and the Roche Amplicor CT/NG test. We defined ddPCR tests as positive when we had ≥95% confidence in a nonzero estimate of target load. The sensitivity of ddPCR against Amplicor was 73.3% (95% confidence interval [CI], 67.9 to 78.7%), and specificity was 99.1% (95% CI, 98.6 to 99.6%). Negative and positive predictive values were 94.6% (95% CI, 93.4 to 95.8%) and 94.5% (95% CI, 91.3 to 97.7%), respectively. Based on Amplicor CT/NG testing, the estimated population prevalence of C. trachomatis ocular infection was ~17.5%. Receiver-operator curve analysis was used to select critical cutoff values for use in clinical settings in which a balance between higher sensitivity and specificity is required. We concluded that ddPCR is an effective diagnostic technology suitable for both research and clinical use in diagnosing ocular C. trachomatis infections.

INTRODUCTION

Trachoma, caused by ocular Chlamydia trachomatis infection, remains the leading infectious cause of blindness worldwide. In 1998, a World Health Assembly resolution called for its elimination as a public health problem by 2020. Considerable progress has been made toward achieving this goal by implementing the SAFE strategy: surgery for those with end-stage disease, community-wide mass treatment with antibiotics, promotion of facial cleanliness, and environmental improvement. Since 1998, more than 250 million doses of azithromycin have been donated to trachoma control programs and eight countries in which trachoma was formerly endemic report having met the elimination targets set by the World Health Organization (WHO) (1).

Since the clinical signs of trachoma can persist for months or even years after the elimination of ocular C. trachomatis infection in the community, tests for infection have been valuable in monitoring and optimizing the impact of various control strategies (27). Quantitative tests, which measure the bacterial load, have been particularly useful, as they can identify population subgroups in greatest need of treatment (2, 3, 58). Nucleic acid amplification tests (NAATs) for the diagnosis and quantitation of clinical C. trachomatis infections are widely used, and a number of quantitative PCR (qPCR) assays have been described (912).

Droplet digital PCR (ddPCR) (13, 14) is a next-generation implementation of digital PCR (dPCR) that facilitates the accurate and precise quantitation of nucleic acid targets without the need for calibration curves (15). In the format described here, microfluidic focused-flow droplet generator chips (16) are used to partition a duplex fluorescent-probe-based PCR assay into ~15,000 highly uniform one-nanoliter-volume reverse (water-in-oil) micelles that are stable at high temperatures. The droplet PCR is performed in a normal thermal cycler. Each droplet in the emulsion is an independent nano-PCR. During the PCR process, the emulsion droplets gel in a manner presumably similar to that reported by Leng et al. (17) to form semisolid microspheres. Post-PCR, droplets are focused into a single file beam of droplets which are flowed through a cytometer under LED excitation that allows highly accurate enumeration of PCR-positive and -negative droplets at high speed.

The digital PCR is formulated in such a way that there are fewer copies of the DNA template than the number of droplets generated, which ensures microfluidic stochastic confinement. The qualitative (positive/negative) endpoint of PCR is determined in each droplet, and given that the distribution of templates to droplets adheres to the Poisson distribution, the counts of positive and negative droplets can be converted into an absolute quantitation of the number of templates in the total PCR volume (15, 18, 19). Almost every PCR-positive droplet in the ddPCR is the endpoint of a reaction that was seeded by a single template molecule, and this, by implication, means that ddPCR is able to reproducibly detect DNA templates at terminal (one-target-per-test) dilution (13, 19, 20). In ddPCR, the absolute concentration of a single target molecule, relative to the PCR reagents, is substantially higher in the nanoliter volume than in conventional microliter-scale PCR. The likelihood of favorable primer-template interactions, and thus, the efficiency, specificity, and sensitivity of ddPCR, is increased in comparison to that of conventional PCR tests (21). Similarly, the fluorescent product is confined to the droplet volume, and so, small changes in fluorescence intensity are more readily detected by photonics equipment than a similar absolute amount of fluorescence would be by conventional qPCR platforms (21). ddPCR is robust against many of the factors that can negatively influence conventional PCR because the DNA template, when confined, is sequestered from cross-reacting DNA templates, inhibitory moieties, and spurious PCR amplicons, such as primer-dimers (20).

The benefits of digital PCR make it a process that has clear utility in the field of quantitative infectious disease diagnostics (2224). It remains unclear how accurately qPCR methods are able to measure C. trachomatis infectious load in clinical samples in which inhibitory agents, competing DNA, and nonexponential amplification during early PCR cycles can potentially affect changes in PCR amplification efficiency. ddPCR is robust against these factors, which, coupled with its superiority in performance, based on the theoretical arguments presented above, leads to a potentially more accurate and precise assay than preexisting methods. We aimed to evaluate the diagnostic performance of a ddPCR-based C. trachomatis assay and to highlight the utility of the ddPCR method in clinical diagnostics.

MATERIALS AND METHODS

ddPCR.

The ddPCR primers targeted the C. trachomatis cryptic plasmid (10) and the Homo sapiens RNase P/MRP 30-kDa subunit (RPP30) gene (25). The sequences of the oligonucleotides used in this study are given in Table 1. ddPCR reaction mixtures were 20-μl volumes that contained final concentrations of 1× ddPCR Supermix (Bio-Rad, Hemel Hempstead, United Kingdom), 0.3 μM each primer and probe (PLASMID/RPP30), and 4.95 μl sample DNA of unknown quantity. Droplet generation and droplet reading for ddPCR were carried out according to the manufacturer's instructions using Bio-Rad reagents. The thermal cycling profile was 95°C for 10 minutes followed by 40 cycles of 95°C for 15 seconds and 60°C for 30 seconds.

Table 1
Oligonucleotides used in this study

ddPCR data processing.

Raw ddPCR data were collected on the Bio-Rad QX100 instrument using Quantalife software (Bio-Rad) and were then exported for analysis using Perl and R scripts (see data S1 and S2 in the supplemental material). ddPCR data analysis was performed masked to the results of the Amplicor test and the details of clinical phenotypes. The Poisson calculation was used to estimate the number of plasmids/μl of the reaction and confidence intervals (18). For classification purposes, we used the estimated mean concentration of the target and its standard deviation to define the cumulative distribution function (c.d.f.) at x = 0. This value describes the probability that the true concentration is less than or equal to zero copies/μl. The classifier ζ was defined as 1 − c.d.f. and describes the probability that the true concentration is greater than zero copies/μl.

We excluded samples from further analysis if the ζ value for the RPP30 assay was below 0.95. Samples for which there was at least 99% droplet occupancy by plasmids were judged as being oversaturated with plasmid templates and potentially contravened assumptions of the Poisson distribution. In these cases, we retested a 1:10 dilution of the specimen and corrected the estimates for this post hoc test.

Accuracy and precision.

The accuracy (closeness of concentration estimates to the true concentration) and precision (reproducibility of replicate tests) of the ddPCR test were examined by assaying a calibration curve of 17 serial doubling dilutions of a sample of a plasmid vector construct (pCTL12A) that contained the entire sequence of the Chlamydia trachomatis plasmid of an L2 biovar (26). The doubling dilution series was made using a diluent that contained a constant amount of a PCR product containing the RPP30 target sequence. Linear regression was used to determine the r2, slope, and intercept values for the relationship between ddPCR estimates of plasmid concentration and the standard dilution series.

Community survey and clinical examination.

A population-based trachoma survey was conducted on four islands of the Bijagós Archipelago of Guinea Bissau in West Africa, where ocular infection with C. trachomatis and trachomatous eye disease are hyperendemic. Trachoma survey methodology has been described previously (2729). Individuals from randomly selected households in these communities attended for clinical examination and conjunctival sampling between January and March 2012.

A single trained examiner assessed each participant. In this analysis, the WHO simplified grading system was used to assign a trachoma grade to the right and left upper tarsal conjunctivae of each consenting participant.

Ocular swab specimens were collected from a consecutive series of participants. Samples were taken from the left upper tarsal conjunctiva of each participant with Dacron swabs (Fisher Scientific, Loughborough, United Kingdom) using a validated, well-tolerated, standardized protocol (8). Swabs were kept on ice in the field and frozen to −80°C within 8 h of collection. Negative-control specimens were collected in the presence of a participant by passing the swab in front of the participant's eye without making contact.

DNA extraction.

Swabs were suspended in sterile phosphate-buffered saline (PBS) after being thawed at room temperature. The swabs were then thoroughly vortexed. Liquid was expressed from the swab head against the side of the tube, and swabs were then discarded. DNA was extracted from the PBS suspension using an adapted whole-blood DNA extraction protocol on the QIAxtractor (Qiagen, Manchester, United Kingdom) automated instrument.

Roche CT/NG Amplicor test.

We used the Roche Amplicor C. trachomatis/Neisseria gonorrhoeae (CT/NG) PCR assay (Roche Molecular Systems, NJ) as the reference test in this evaluation since the clinical specimens came from an epidemiological population sample in which Amplicor had been used to detect C. trachomatis infections. The ddPCR study was performed post hoc. We have used Amplicor widely and extensively in trachoma studies (8, 3033), and it was the test of choice in a large multicountry study to evaluate trachoma control (34). Others have also evaluated its performance in clinical testing for C. trachomatis infections in numerous studies (3542). To perform the Amplicor test on purified DNA samples, we diluted 9 μl DNA extract in 94.5 μl of a 1:1 diluent/lysis buffer solution and used 50 μl of this in the standard assay as described previously (28). Positive and negative samples were classified according to the manufacturer's instructions (rev. 3.0; 2010). Amplicor CT/NG testing was performed between April and May 2012. Amplicor “equivocal” samples were confirmed by testing two further aliquots of the same DNA specimen by Amplicor CT/NG according to the manufacturer's instructions (rev. 3.0; 2010). Specimens with at least two of three results with an optical density at 450 nm (OD450) of ≥0.2 were classified as positive.

Diagnostic evaluation.

In the initial analysis, presumptive sample positivity for C. trachomatis was determined when ζ was ≥0.95. A two-by-two comparison against Amplicor CT/NG was performed, and the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), negative likelihood ratio (LR−), and respective 95% confidence intervals of the ddPCR test were calculated (43).

We used receiver-operator curve (ROC) analysis to establish the estimated plasmid concentration threshold values at which, compared to Amplicor, (i) sensitivity was maximized, (ii) the optimal balance between specificity and sensitivity was achieved, (iii) specificity was ≥99%, (iv) specificity was ≥99.9%, and (v) specificity was 100%.

Written, informed consent was collected from all study participants. The research committee of the Ministry of Health, Guinea Bissau, and the London School of Hygiene and Tropical Medicine ethics committee granted permission for the study.

RESULTS

Visualization of droplet PCR and data processing.

Prior to commencing the clinical evaluation, we visualized under fluorescence microscopy a sample of post-PCR droplets from a human DNA specimen that was infected with C. trachomatis (Fig. 1). We clearly identified numerous droplets that were positive for each of the two targets, thus demonstrating that the assay was functioning correctly. In all successive tests, raw flow cytometric data were processed using automated R scripts to generate a scatterplot of individual droplet fluorescence intensities and a number of technical reports that presented ζ values and estimated concentrations. The open-source R scripts that we developed during this study have been released on a Creative Commons Attribution ShareAlike license, are included in data S1 and S2 in the supplemental material, and can be downloaded for unrestricted free and open use.

Fig 1
Confocal photomicrograph of ddPCR droplets from a representative C. trachomatis positive sample post-PCR. A bright-field image of droplets is shown at the bottom left. C. trachomatis plasmid PCR-positive droplets are shown on the 6-carboxyfluorescein ...

ddPCR accuracy and precision.

Using serial dilutions of pCTL12A (C. trachomatis plasmid containing a positive-control sample), we assayed a standard calibration curve, which is shown in Fig. 2A (C. trachomatis plasmid) and B (human RPP30). The r2 value for the correlation between the dilution factor and the experimentally obtained quantitation was 0.9927. The intercept with the y axis was at 0.03776 plasmids/μl, and the slope was 1.01218.

Fig 2
(A) Standard calibration curve of ddPCR concentrations (plasmids/μl) against dilution factors, r2 = 0.9927, intercept = 0.037 plasmids/μl, slope = 1.01. (B) Standard calibration curve of ddPCR concentrations (human RPP30 copies/μl) ...

ddPCR testing of clinical specimens.

The population sampled was 43% male, with a median age of 13 years (range, 0 to 88 years). We tested 1,495 clinical samples and 14 control swabs. Fourteen hundred seventy-seven specimens were retained for analysis after data entry, cleaning, Amplicor CT/NG, ddPCR, and quality control tests (Fig. 3). The spectrum of clinical signs of trachoma in the population sample is described in Table 2. The association between C. trachomatis quantitation and clinical severity of signs of trachoma is not the focus of this paper and is the subject of a subsequent manuscript (A. R. Last, C. h. Roberts, E. Cassama, M. Nabicassa, D. C. W. Mabey, M. J. Holland, and R. L. Bailey, unpublished data).

Fig 3
Flow diagram of participant samples in the retrospective validation of ddPCR against the standard Amplicor CT/NG test. Numbers in parentheses refer to Amplicor CT/NG results.
Table 2
Comparison of Amplicor CT/NG and ddPCR to clinical exama

At least one C. trachomatis PCR-positive droplet was detected in 305 (20.64%) samples. The median ddPCR droplet count was 14,514 (minimum, 1,171; 1st quartile, 13,720; 3rd quartile, 15,150; maximum, 17,720). The minimum detected quantity of plasmid targets by ddPCR was 0.062 targets/μl (95% confidence interval [CI], 0.209 to 0.184). Droplet occupancy of 99% was reached when the PCR mixture contained ~5,000 targets/μl (95% CI, 4,868 to 5,217). In specimens that had one or more PCR-positive droplet, the percentage of the total number of droplets that were occupied by a template was uniformly low in both the human and C. trachomatis assays. In the context of the PCR plasmid test, a median of just 0.119% of droplets (minimum, 0.006%; 1st quartile, 0.007%; 3rd quartile, 9.972%; maximum, 98.97%) were occupied by the C. trachomatis plasmid target. Similarly, the percentage of the total number of droplets that was occupied by human RPP30 targets had a median value of 0.015% (minimum, 0.0003%; 1st quartile, 0.007%; 3rd quartile, 0.036%; maximum, 0.757%). The overwhelming majority of all droplets in all tests that were performed contained neither target.

Comparison to Amplicor CT/NG.

The classification threshold for ddPCR was a ζ value of 0.95. Table 3 shows the sensitivity, specificity, PPV, and NPV of ddPCR compared to those of Amplicor CT/NG at this threshold. Comparisons of Amplicor CT/NG and ddPCR to clinical exam are shown in Table 2. Infection was more likely to be detected in cases of active trachoma than in those without signs of active disease, but there appeared to be no obvious differences between the two tests in the different clinical groups. None of the negative-control swabs taken in the field were positive by Amplicor or by ddPCR for either human or C. trachomatis DNA.

Table 3
Diagnostic performance of ddPCR compared to Amplicor CT/NGa

ROC-determined sensitivity, specificity, NPV, PPV, LR+, and LR− at different thresholds are shown in Table 4. The overall diagnostic efficiency of the ddPCR assay compared to that of Amplicor CT/NG, defined by the area under the curve (AUC), was 90.8%. The AUC gives the probability that a randomly selected positive specimen will be ranked higher than a randomly selected negative specimen and, as such, is a general indicator of the performance, or “predictiveness,” of the assay (44).

Table 4
ROC-determined sensitivity, specificity, PPV, NPV, LR+, and LR− at different ddPCR concentration threshold values

Figure 4A shows the distribution of Amplicor CT/NG OD450 values in the sample population data. There are clear negative and positive populations at the extremes of the OD450 range, and we used the data presented in Fig. 4 to define an extended area of intermediate values (0.8 < OD450 < 3.1) which is more extensive than those described in the Amplicor literature and for which the classification is less clear. Figure 4B shows correlations between the Amplicor CT/NG OD450 values and the ddPCR estimates of plasmid concentrations. Specimens that had intermediate OD450 values (0.8 < OD450 < 3.1) were unlikely to have high plasmid loads according to ddPCR, and the median concentration of C. trachomatis plasmid in an Amplicor CT/NG-positive, ddPCR-positive sample was just 0.24 plasmids/μl (minimum, 0.071; 1st quartile, 0.076; 3rd quartile, 0.458; maximum, 682.9) when the Amplicor CT/NG optical density signal at 450 nm was between 0.8 and 3.1. Conversely, samples were much more likely to have high plasmid loads when the Amplicor CT/NG OD450 value was in the clear positive range (OD450 ≥ 3.1). The median plasmid concentration of specimens in this group was 94.94 plasmids/μl (minimum, 0.206; 1st quartile, 7.188; 3rd quartile, 608.900; maximum, 5,029.000).

Fig 4
(A) Distribution of Amplicor CT/NG test OD450 values, showing (i) the most-recent Amplicor CT equivocal zone, (ii) the earlier Amplicor equivocal zone, and (iii) the broad equivocal zone identified using the observations of this study. (B) Amplicor CT ...

DISCUSSION

Recent studies in several countries have shown that a high prevalence of follicular trachoma (TF) can persist for months or years in communities in which the prevalence of ocular C. trachomatis has been reduced to a very low level, or even eliminated, following mass treatment (32, 45, 46). Current recommendations are to continue mass treatment with azithromycin until the prevalence of TF in children ages 1 to 9 years is below 5%, but this can lead to repeated rounds of mass treatment for communities in which few, if any, individuals are infected. Basing the decision to stop mass treatment on the prevalence of C. trachomatis infection would save resources and reduce the risk of selecting for macrolide-resistant strains of important pathogens, such as Streptococcus pneumoniae (47). As the prevalence of infection falls, so does the positive predictive value of a test for infection. It is therefore particularly important, in designing a test that will be used to determine that infection has been eliminated from a community, to ensure that it is highly specific. Based on the evidence of a comparison to a well-validated reference test, Amplicor CT/NG, the ddPCR assay fulfills this criterion.

The standard calibration curve is a simultaneous test in which a single metric, the coefficient of determination (the r2 value), is used to describe the accuracy and intraoperator precision of PCR assays. Using a serial dilution calibration series, we found that the ddPCR test is a highly precise and accurate (r2 = ~0.9927) assay that can detect and quantify chlamydial plasmids across a wide range of concentrations. Sampling error in the ddPCR test was assessed by examination of the 95% confidence intervals (Fig. 2) of the concentration estimates. The increase in sampling error that we observed at lower dilutions clearly reflected the stochastic sampling process that takes place when an aliquot is taken from a larger specimen volume. Slight variation in the levels of RPP30 that were detected (Fig. 2B) was able to be explained by error introduced by liquid-handling procedures.

We chose to use a confidence measure (ζ) to classify the results of ddPCR tests. This value is derived from the normal probability distribution of the ddPCR concentration and describes the probability that the true concentration is above zero copies/μl. For the classification of specimens as positive for the PCR targets of either the human or C. trachomatis assays, we initially chose an arbitrary cutoff value for ζ of 0.95. At this threshold, there is 95% confidence that the true target concentration is not zero. In using a threshold of ζ of 0.95, we define a highly specific assay in which there is a theoretical maximum probability of false-positive results in any given test that is less than 5%.

We took a standard approach to diagnostic evaluation and used ROC analysis to compare the ddPCR test results to a set of Amplicor CT/NG data that had been classified according to the most recent version of the manufacturer's protocol (rev. 3.0; 2010). In this case, we used the estimated concentration of plasmids per microliter of the PCR mixture as the classifier. This value, which is proportional to ζ, is the biologically meaningful quantitative output of the ddPCR assay. We found that ddPCR performed extremely well in this population (ROC AUC was above 90%; Amplicor CT/NG estimated prevalence was ~17.47%). Table 4 shows how differing threshold values of the ddPCR classifier can be used to optimize the assay (highly sensitive/highly specific/balanced) for use in different prevalence settings.

The evidence from our direct comparison to Amplicor CT/NG indicated that the ddPCR test was less sensitive (maximally 83.7%) than Amplicor CT/NG. We acknowledge that our ddPCR C. trachomatis test may be inferior to Amplicor CT/NG both in general terms and particularly with respect to sensitivity. The observation of lower-than-expected sensitivity is similar to the findings of a previous study (22), in which a human cytomegalovirus (CMV) ddPCR assay was found to be less sensitive than a qPCR assay for the same target. These findings are surprising given the theoretical technological advantage of ddPCR over conventional microliter-scale fluidic PCR. If false-positive classification by the Amplicor CT/NG assay had occurred, the result would be a false indication of low sensitivity in ddPCR. Previous studies have used discrepant analysis to resolve divergent results between the index and reference tests (36, 37, 41, 42), and conditionally independent tests to arbitrate discrepancies (with proven high sensitivity), such as the Gen-Probe Aptima test, (48) are available. This test is based on C. trachomatis RNA detection, and we did not have access to RNA specimens or any other biological material from the individuals who participated in the study. The use of a third DNA-based test, such as qPCR, would not be conditionally independent, and the validity of arbitration by discrepant analysis remains controversial in any case (49, 50).

The diagnostic classifiers in the qualitative Amplicor CT/NG (OD450) and quantitative ddPCR (estimated target concentration) tests are both continuous variables. Although the Amplicor CT/NG OD450 value is not thought to be an accurate estimate of the DNA targets contained in the original specimen, this value is the continuous quantitative measure that is used to define boundaries for sample positivity. Changing the critical threshold value at which positive/negative classification is made can affect the outcome of comparative diagnostic evaluations, as demonstrated in Table 4. The choice of threshold in the reference is therefore a critical determinant of the diagnostic evaluation because misclassification by the reference has deleterious downstream effects on the estimation of the diagnostic performance of the comparative test. Figure 4A shows how a large number (n = 172) of data points fell within what we describe as an expanded equivocal zone in the Amplicor CT/NG data (0.1 to 3.1), wherein the classification would change if different Amplicor CT/NG thresholds were chosen.

In the product insert for the Amplicor CT/NG test (rev. 3.0; 2010), the manufacturer recommended a cutoff threshold for Amplicor CT of 0.8 OD450 units, with triplicate testing indicated for all equivocal values between 0.2 and 0.8 in the initial test. Earlier versions (available online at http://www.fda.gov/downloads/BiologicsBloodVaccines/SafetyAvailability/TissueSafety/ucm100246.pdf) present figures of data and recommend a much wider equivocal zone for which testing by alternate methods would be required (0.2 to 2.0). We believe that the most recent guidelines limit the equivocal range to the area in which false positives are most likely (OD450 = 0.2 to 0.8) instead of the area in which they are possible (OD450 = 0.2 to ~3) and that this may increase the cost-effectiveness of C. trachomatis screening, as these guidelines require fewer replicate or alternate tests than the earlier guidelines. The result of these measures is the implementation of a highly sensitive test, but with the consequence of a significant number of false-positive results. The Amplicor test guidelines were optimized for use in testing for genitourinary tract infections, for which the risk of false-negative results would be minimized. While Amplicor CT/NG has been validated and widely used in testing ocular samples (8, 3034), any misclassification that has occurred in this study might be the result of using Amplicor classification cutoff values that are not appropriate to the ocular specimens. Nonetheless, when we chose a ddPCR threshold (~0.07 plasmids/μl) that maximized sensitivity, 42 Amplicor-positive but ddPCR-negative specimens remained. We anticipate that some proportion of these is attributable to misclassification by Amplicor CT/NG testing.

A second source of error in the sensitivity estimate is shown in Fig. 4B. We assessed samples that were ddPCR and Amplicor CT/NG (i.e., OD450 of >0.8) positive and found that the ddPCR estimate of the plasmid concentration was uniformly low (median, 0.24 plasmids/μl) when the Amplicor CT/NG OD450 value was in the range of 0.2 to 3.1, which we defined as the “expanded equivocal zone.” Samples in the Amplicor CT-positive range (OD450 > 3.1) had much higher concentration estimates by ddPCR (median, 87.99 plasmids/μl). We take these observations to indicate that a significant number of the discrepancies are the result of sampling error (which affects the performance of most NAATs) and/or suboptimal performance when presented with a specimen that has a low target sequence load.

We developed a highly specific test that is widely applicable for C. trachomatis testing and may be useful in monitoring infection post-mass drug administration (MDA). We aim to maintain high specificity, which we can define by a stringent threshold value of ζ of ≥0.95. Reducing the threshold value of ζ would lead to dramatic increases in sensitivity, but the confidence with which we would accept a sample as positive is reduced, and this might lead to overdiagnosis. This is particularly important when or if MDA treatment decisions are informed by a test for current ocular chlamydial infection rather than by clinical signs of trachoma alone (51).

Previous studies by us and others have suggested that there is a threshold of C. trachomatis infection prevalence and intensity below which the infection will spontaneously disappear from a population—the so-called Allee effect (5, 45, 46). A test that accurately estimates the bacterial load, such as the ddPCR assay, may be especially valuable in determining when this threshold has been reached and it is therefore safe to discontinue MDA.

The ddPCR technology has great utility as a diagnostic. Unlike most other NAATs, this method requires no external or internal calibration yet delivers a highly accurate estimation of target load. The inclusion of a human target allows a system of internal control that indicates (but does not discriminate between) experimental failures that are due to either technical PCR failure or the absence of a sample of human origin in the specimen.

We have validated a highly specific quantitative ddPCR assay and applied it to population monitoring of ocular C. trachomatis infections. This method can rapidly be adapted for use in the detection of sexually transmitted C. trachomatis infections, for which a higher sensitivity than that which we have estimated would be desirable. This study represents an early example of the usefulness of this next-generation digital PCR method in diagnosing infections in clinical specimens within the arena of infectious diseases.

Supplementary Material

Supplemental material:

ACKNOWLEDGMENTS

All reagents for this study were purchased at full list price. We are grateful to Bio-Rad Laboratories, Inc., who loaned the QX-100 platform to us free of charge for the purposes of carrying out this study. We also thank Ian Clarke, who provided the Chlamydia trachomatis plasmid clone, Emma Harding-Esch for critical review of the manuscript, and our Guinea-Bissauan study participants for volunteering to take part in the study.

The Wellcome Trust provided financial support (grant number GR079246MA).

C.H.R., A.L., and M.J.H. conceived the study. C.H.R., A.L., S.M.-G., R.B., and M.J.H. performed the experiments. E.M. performed the confocal microscopy. A.L., E.C., S.E.B., M.N., M.J.H., and R.L.B. planned the field study, collected samples, and graded phenotypes. C.H.R. analyzed the data. C.H.R., M.J.H., and D.C.M. wrote the paper. M.J.H., R.L.B., and D.C.M. obtained the funding.

We declare no conflict of interest.

Footnotes

Published ahead of print 1 May 2013

Supplemental material for this article may be found at http://dx.doi.org/10.1128/JCM.00622-13.

REFERENCES

1. WHO 2012. Global WHO alliance for the elimination of blinding trachoma by 2020. Wkly. Epidemiol. Rec. 87:161–168. [PubMed]
2. Burton MJ, Holland MJ, Makalo P, Aryee EAN, Alexander NDE, Sillah A, Faal H, West SK, Foster A, Johnson GJ, Mabey DCW, Bailey RL. 2005. Re-emergence of Chlamydia trachomatis infection after mass antibiotic treatment of a trachoma-endemic Gambian community: a longitudinal study. Lancet 365:1321–1328. [PubMed]
3. Chidambaram JD, Alemayehu W, Melese M, Lakew T, Yi E, House J, Cevallos V, Zhou Z, Maxey K, Lee DC, Shapiro BL, Srinivasan M, Porco T, Whitcher JP, Gaynor BD, Lietman TM. 2006. Effect of a single mass antibiotic distribution on the prevalence of infectious trachoma. JAMA 295:1142–1146. [PubMed]
4. Schachter J, West SK, Mabey D, Dawson CR, Bobo L, Bailey R, Vitale S, Quinn TC, Sheta A, Sallam S, Mkocha H, Faal H. 1999. Azithromycin in control of trachoma. Lancet 354:630–635. [PubMed]
5. Solomon AW, Holland MJ, Alexander NDE, Massae PA, Aguirre A, Natividad-Sancho A, Molina S, Safari S, Shao JF, Courtright P, Peeling RW, West SK, Bailey RL, Foster A, Mabey DCW. 2004. Mass treatment with single-dose azithromycin for trachoma. N. Engl. J. Med. 351:1962–1971. [PubMed]
6. West ES, Munoz B, Mkocha H, Holland MJ, Aguirre A, Solomon AW, Bailey R, Foster A, Mabey D, West SK, Any W. 2005. Mass treatment and the effect on the load of Chlamydia trachomatis infection in a trachoma-hyperendemic community. Invest. Ophthalmol. Vis. Sci. 46:83–87. [PubMed]
7. West SK, Munoz B, Mkocha H, Holland MJ, Aguirre A, Solomon AW, Foster A, Bailey RL. 2005. Infection with Chlamydia trachomatis after mass treatment of a trachoma hyperendemic community in Tanzania: a longitudinal study. Lancet 366:1296–1300. [PubMed]
8. Solomon AW, Holland MJ, Burton MJ, West SK, Alexander NDE, Aguirre A, Massae PA, Mkocha H, Muñoz B, Johnson GJ, Peeling RW, Bailey RL, Foster A. 2003. Strategies for control of trachoma: observational study with quantitative PCR. Lancet 362:198–204. [PubMed]
9. McGowin CL, Whitlock GC, Pyles RB. 2009. High-throughput multistrain polymerase chain reaction quantification of Chlamydia trachomatis from clinical and preclinical urogenital specimens. Diagn. Microbiol. Infect. Dis. 64:117–123. [PMC free article] [PubMed]
10. Pickett MA, Everson JS, Pead PJ, Clarke IN. 2005. The plasmids of Chlamydia trachomatis and Chlamydophila pneumoniae (N16): accurate determination of copy number and the paradoxical effect of plasmid-curing agents. Microbiology 151:893–903. [PubMed]
11. Stevens MP, Twin J, Fairley CK, Donovan B, Tan SE, Yu J, Garland SM, Tabrizi SN. 2010. Development and evaluation of an ompA quantitative real-time PCR assay for Chlamydia trachomatis serovar determination. J. Clin. Microbiol. 48:2060–2065. [PMC free article] [PubMed]
12. Wei H, Zou S, Yang X, Yang D, Chen X. 2012. Development of multiplex real-time quantitative PCR for simultaneous detection of Chlamydia trachomatis and Ureaplasma parvum. Clin. Biochem. 45:663–667. [PubMed]
13. Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, Bright IJ, Lucero MY, Hiddessen AL, Legler TC, Kitano TK, Hodel MR, Petersen JF, Wyatt PW, Steenblock ER, Shah PH, Bousse LJ, Troup CB, Mellen JC, Wittmann DK, Erndt NG, Cauley TH, Koehler RT, So AP, Dube S, Rose KA, Montesclaros L, Wang S, Stumbo DP, Hodges SP, Romine S, Milanovich FP, White HE, Regan JF, Karlin-Neumann GA, Hindson CM, Saxonov S, Colston BW. 2011. High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal. Chem. 83:8604–8610. [PMC free article] [PubMed]
14. Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR. 2012. Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification. Anal. Chem. 84:1003–1011. [PMC free article] [PubMed]
15. Vogelstein B, Kinzler KW. 1999. Digital PCR. Proc. Natl. Acad. Sci. U. S. A. 96:9236–9241. [PubMed]
16. Tan Y-C, Cristini V, Lee AP. 2006. Monodispersed microfluidic droplet generation by shear focusing microfluidic device. Sens. Actuators B Chem. 114:350–356.
17. Leng X, Zhang W, Wang C, Cui L, Yang CJ. 2010. Agarose droplet microfluidics for highly parallel and efficient single molecule emulsion PCR. Lab Chip 10:2841–2843. [PubMed]
18. Dube S, Qin J, Ramakrishnan R. 2008. Mathematical analysis of copy number variation in a DNA sample using digital PCR on a nanofluidic device. PLoS One 3:e2876. doi: 10.1371/journal.pone.0002876. [PMC free article] [PubMed] [Cross Ref]
19. Kalinina O, Lebedeva I, Brown J, Silver J. 1997. Nanoliter scale PCR with TaqMan detection. Nucleic Acids Res. 25:1999–2004. [PMC free article] [PubMed]
20. Nakano M, Komatsu J, Matsuura S, Takashima K, Katsura S, Mizuno A. 2003. Single-molecule PCR using water-in-oil emulsion. J. Biotechnol. 102:117–124. [PubMed]
21. Vincent ME, Liu W, Haney EB, Ismagilov RF. 2010. Microfluidic stochastic confinement enhances analysis of rare cells by isolating cells and creating high density environments for control of diffusible signals. Chem. Soc. Rev. 39:974–984. [PMC free article] [PubMed]
22. Hayden RT, Gu Z, Ingersoll J, Abdul-Ali D, Shi L, Pounds S, Caliendo AM. 2013. Comparison of droplet digital PCR to real-time PCR for quantitative detection of cytomegalovirus. J. Clin. Microbiol. 51:540–546. [PMC free article] [PubMed]
23. Henrich TJ, Gallien S, Li JZ, Pereyra F, Kuritzkes DR. 2012. Low-level detection and quantitation of cellular HIV-1 DNA and 2-LTR circles using droplet digital PCR. J. Virol. Methods 186:68–72. [PMC free article] [PubMed]
24. White RA, Quake SR, Curr K. 2012. Digital PCR provides absolute quantitation of viral load for an occult RNA virus. J. Virol. Methods 179:45–50. [PubMed]
25. Luo W, Yang H, Rathbun K, Pau C-P, Ou C-Y. 2005. Detection of human immunodeficiency virus type 1 DNA in dried blood spots by a duplex real-time PCR assay. J. Clin. Microbiol. 43:1851–1857. [PMC free article] [PubMed]
26. Wang Y, Kahane S, Cutcliffe LT, Skilton RJ, Lambden PR, Clarke IN. 2011. Development of a transformation system for Chlamydia trachomatis: restoration of glycogen biosynthesis by acquisition of a plasmid shuttle vector. PLoS Pathog. 7:e1002258. doi: 10.1371/journal.ppat.1002258. [PMC free article] [PubMed] [Cross Ref]
27. Bennett S, Woods T, Liyanage WM, Smith DL. 1991. A simplified general method for cluster-sample surveys of health in developing countries. World Health Stat. Q. 44:98–106. [PubMed]
28. Harding-Esch EM, Edwards T, Sillah A, Sarr-Sissoho I, Aryee EA, Snell P, Holland MJ, Mabey DC, Bailey RL. 2008. Risk factors for active trachoma in The Gambia. Trans. R. Soc. Trop. Med. Hyg. 102:1255–1262. [PubMed]
29. Solomon AW, Zondervan M, Kuper H, Buchan JC, Mabey DCW, Foster A. 2006. Trachoma control: a guide for programme managers. World Health Organization, Geneva, Switzerland.
30. Andreasen AA, Burton MJ, Holland MJ, Polley S, Faal N, David CW, Bailey RL. 2008. Chlamydia trachomatis ompA variants in trachoma: what do they tell us? PLoS Negl. Trop. Dis. 2:e306. doi: 10.1371/journal.pntd.0000306. [PMC free article] [PubMed] [Cross Ref]
31. Burton MJ, Ramadhani A, Weiss HA, Hu V, Massae P, Burr SE, Shangali W, Holland MJ, Mabey DCW, Bailey RL. 2011. Active trachoma is associated with increased conjunctival expression of IL17A and profibrotic cytokines. Infect. Immun. 79:4977–4983. [PMC free article] [PubMed]
32. Harding-Esch EM, Edwards T, Sillah A, Sarr I, Roberts CH, Snell P, Aryee E, Molina S, Holland MJ, Mabey DCW, Bailey RL. 2009. Active trachoma and ocular Chlamydia trachomatis infection in two Gambian regions: on course for elimination by 2020? PLoS Negl. Trop. Dis. 3:e573. doi: 10.1371/journal.pntd.0000573. [PMC free article] [PubMed] [Cross Ref]
33. Harding-Esch EM, Holland MJ, Schémann Molina J-FS, Sarr I, Andreasen AA, Roberts CH, Sillah A, Sarr B, Harding EF, Edwards T, Bailey RL, Mabey DCW. 2011. Diagnostic accuracy of a prototype point-of-care test for ocular Chlamydia trachomatis under field conditions in The Gambia and Senegal. PLoS Negl. Trop. Dis. 5:e1234. doi: 10.1371/journal.pntd.0001234. [PMC free article] [PubMed] [Cross Ref]
34. Stare D, Harding-Esch E, Munoz B, Bailey R, Mabey D, Holland M, Gaydos C, West S. 2011. Design and baseline data of a randomized trial to evaluate coverage and frequency of mass treatment with azithromycin: the Partnership for Rapid Elimination of Trachoma (PRET) in Tanzania and The Gambia. Ophthalmic Epidemiol. 18:20–29. [PubMed]
35. Bass CA, Jungkind DL, Silverman NS, Bondi JM. 1993. Clinical evaluation of a new polymerase chain reaction assay for detection of Chlamydia trachomatis in endocervical specimens. J. Clin. Microbiol. 31:2648–2653. [PMC free article] [PubMed]
36. Bassiri M, Mårdh PA, Domeika M. 1997. Multiplex AMPLICOR PCR screening for Chlamydia trachomatis and Neisseria gonorrhoeae in women attending non-sexually transmitted disease clinics. J. Clin. Microbiol. 35:2556–2560. [PMC free article] [PubMed]
37. Cheng A, Qian Q, Kirby JE. 2011. Evaluation of the Abbott RealTime CT/NG assay in comparison to the Roche Cobas Amplicor CT/NG assay. J. Clin. Microbiol. 49:1294–1300. [PMC free article] [PubMed]
38. Jaschek G, Gaydos CA, Welsh LE, Quinn TC. 1993. Direct detection of Chlamydia trachomatis in urine specimens from symptomatic and asymptomatic men by using a rapid polymerase chain reaction assay. J. Clin. Microbiol. 31:1209–1212. [PMC free article] [PubMed]
39. Miyashita N, Lijima Y, Matsumoto A. 1994. Evaluation of the sensitivity and specificity of polymerase chain reaction test kit, AMPLICOR Chlamydia trachomatis. Microbiol. Immunol. 38:81–85. [PubMed]
40. Rumpianesi F, La Placa M, D'Antuono A, Negosanti M, Pavan G. 1993. Assessment of the “Amplicor” PCR test in the diagnosis of Chlamydia trachomatis infection. New Microbiol. 16:293–295. [PubMed]
41. Van Der Pol B, Martin DH, Schachter J, Quinn TC, Gaydos CA, Jones RB, Crotchfelt K, Moncada J, Jungkind D, Turner B, Peyton C, Kelly JF, Weiss JB, Rosenstraus M. 2001. Enhancing the specificity of the COBAS AMPLICOR CT/NG test for Neisseria gonorrhoeae by retesting specimens with equivocal results. J. Clin. Microbiol. 39:3092–3098. [PMC free article] [PubMed]
42. Vincelette J, Schirm J, Bogard M, Bourgault AM, Luijt DS, Bianchi A, Van Voorst Vader PC, Butcher A, Rosenstraus M. 1999. Multicenter evaluation of the fully automated COBAS AMPLICOR PCR test for detection of Chlamydia trachomatis in urogenital specimens. J. Clin. Microbiol. 37:74–80. [PMC free article] [PubMed]
43. Banoo S, Bell D, Bossuyt P, Herring A, Mabey D, Poole F, Smith PG, Sriram N, Wongsrichanalai C, Linke R, O'Brien R, Perkins M, Cunningham J, Matsoso P, Nathanson CM, Olliaro P, Peeling RW, Ramsay A. 2006. Evaluation of diagnostic tests for infectious diseases: general principles. Nat. Rev. Microbiol. 4:S20–S32. [PubMed]
44. Vihinen M. 2012. How to evaluate performance of prediction methods? Measures and their interpretation in variation effect analysis. BMC Genomics 13(Suppl 4):S2. [PMC free article] [PubMed]
45. Burton MJ, Holland MJ, Makalo P, Aryee EAN, Sillah A, Cohuet S, Natividad A, Alexander NDE, Mabey DCW, Bailey RL. 2010. Profound and sustained reduction in Chlamydia trachomatis in The Gambia: a five-year longitudinal study of trachoma endemic communities. PLoS Negl. Trop. Dis. 4:e835. doi: 10.1371/journal.pntd.0000835. [PMC free article] [PubMed] [Cross Ref]
46. Solomon AW, Harding-Esch E, Alexander NDE, Aguirre A, Holland MJ, Bailey RL, Foster A, Mabey DCW, Massae PA, Courtright P, Shao JF. 2008. Two doses of azithromycin to eliminate trachoma in a Tanzanian community. N. Engl. J. Med. 358:1870–1871. [PubMed]
47. Skalet AH, Cevallos V, Ayele B, Gebre T, Zhou Z, Jorgensen JH, Zerihun M, Habte D, Assefa Y, Emerson PM, Gaynor BD, Porco TC, Lietman TM, Keenan JD. 2010. Antibiotic selection pressure and macrolide resistance in nasopharyngeal Streptococcus pneumoniae: a cluster-randomized clinical trial. PLoS Med. 7:e1000377. doi: 10.1371/journal.pmed.1000377. [PMC free article] [PubMed] [Cross Ref]
48. Yang JL, Schachter J, Moncada J, Habte D, Zerihun M, House JI, Zhou Z, Hong KC, Maxey K, Gaynor BD, Lietman TM. 2007. Comparison of an rRNA-based and DNA-based nucleic acid amplification test for the detection of Chlamydia trachomatis in trachoma. Br. J. Ophthalmol. 91:293–295. [PMC free article] [PubMed]
49. Green TA, Black CM, Johnson RE. 2001. In defense of discrepant analysis. J. Clin. Epidemiol. 54:210–211. [PubMed]
50. Hadgu A. 1999. Discrepant analysis: a biased and an unscientific method for estimating test sensitivity and specificity. J. Clin. Epidemiol. 52:1231–1237. [PubMed]
51. Keenan JD, See CW, Moncada J, Ayele B, Gebre T, Stoller NE, McCulloch CE, Porco TC, Gaynor BD, Emerson PM, Schachter J, Lietman TM. 2012. Diagnostic characteristics of tests for ocular Chlamydia after mass azithromycin distributions. Invest. Ophthalmol. Vis. Sci. 53:235–240. [PMC free article] [PubMed]

Articles from Journal of Clinical Microbiology are provided here courtesy of American Society for Microbiology (ASM)