Establishing the Limit of Detection for the |Q| SARS-CoV-2 Triplex Assay


Widespread testing has been proven to be an important tactic to combat widespread infections during the COVID-19 pandemic. Many types of tests have been brought to the market in an effort to expand test availability to all corners of the globe. However, in order to choose the most appropriate option, it is important to understand and consider both the sensitivity and accuracy of the test in addition to its availability. False negatives could lead to an increase in community spread and significantly increase the risk of large scale outbreaks.

Limit of detection (LoD), also known as analytical sensitivity, is often used to describe the lowest concentration of input that can be reliably distinguished from a blank. In this study, we characterize the LoD of the Combinati |Q| SARS-CoV-2 RT-dPCR Triplex Kit by diluting reference materials into a pooled negative matrix to determine the lowest concentration at which the assay can reliably identify the sample as containing SARS-CoV-2 targets.

The traditional quantitative PCR (qPCR) approach, the current gold standard for COVID-19 diagnosis, generates results in terms of Ct or Cq. These values do not provide quantitative measurements of the virus without a standard curve. Instead, a predetermined qPCR threshold result determines if a sample is deemed positive or negative. In contrast to this binary result provided by qPCR, digital PCR (dPCR) provides absolute quantification of nucleic acid targets without a standard curve. Each dPCR assay provides a quantitative measure of the targets present in the original sample. In this study, we present quantitative dPCR data to demonstrate the ability to use the Combinati |Q| SARS-CoV-2 RT-dPCR Triplex Kit for applications that look to quantify viral load changes between samples or over time.

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Experimental Protocol

Serial dilution of input materials: Synthetic virus from SeraCare (AccuPlex™ SARS-CoV-2 Reference Material Kit, Cat No. 0505-0126) was serially diluted into a pooled negative swab matrix (VTM/UTM). The samples contained target concentrations from 1600cp/mL to 50cp/mL in 2-fold dilutions.

Nucleic acid purification: The Promega Maxwell RSC16 (Cat No. AS4500) and the Maxwell® RSC Viral Total Nucleic Acid Purification Kit (AS1330) were used to extract RNA from the dilution series samples. For each extraction, 150µL of sample input volume and 60µL elution volume were used.

Digital PCR protocol: For each dPCR run, 6.5µL of extracted sample was combined with 2.5µL of RT-dPCR MasterMix and 1µL of the Triplex Assay. 9µL of the reaction mixture was then loaded into a single well of the MAP16 consumable. Each MAP16 plate run included one NTC (no template control) to ensure that no contamination occurred during testing.

Thermal cycling protocol for the Absolute Q Digital PCR Platform is shown below in Table 1.

Table 1 Thermocycling Parameters

Interpretation of assay results: The determination of whether a sample is “positive” for SARS-CoV-2 was made according to Table 2.

Table 2 Interpretation of Assay Results

As described in the table, any sample that contained two or more positive partitions for either N1 or N2 target is considered positive for SARS-CoV-2.

Limit of detection determination and confirmation: Two sets of experiments were performed to determine the LoD. First, nine replicates for each of the dilutions from 1600cp/mL to 50cp/mL were tested to determine the preliminary LoD. Subsequently, the three lowest concentrations that demonstrated positive signal for all nine replicates (100% accuracy) were selected for additional testing. For each of these concentrations, 20 extraction replicates were tested to confirm the limit of detection.


Preliminary LoD determination: Results from the LoD determination experiment are summarized below in Table 3.

Table 3 Preliminary LoD Determination Results

For all concentrations down to 200cp/mL, nine out of nine replicates (100%) resulted in positive calls for both N1 and N2 targets. For 100cp/mL input, only four out nine replicates were called correctly for N1 and six out of nine replicates were called correctly for N2. Based on these results, the three concentrations selected for the confirmation experiment were 800cp/mL, 400cp/mL, and 200cp/mL.

LoD confirmation: For LoD confirmation, 20 extraction replicates were performed for each of the three concentrations selected. The LoD is defined as the lowest input concentration that results in greater than or equal to 95% of all true positive replicates testing positive for SARS-CoV-2. Results for the confirmation experiment are summarized below in Table 4.

Table 4 Confirmation of LoD

The LoD was determined to be 200 cp/mL, as 20 out of 20 replicates were correctly identified as positive for SARS-CoV-2 for both N1 and N2.

Quantitative measurement of serially diluted samples: As dPCR provides absolute measurements instead of a cycle number, small changes can be accurately detected and quantified. Figure 1 shows the number of positive partitions for each of the dilutions used in the preliminary LOD study.

Figure 1. Number of Positive Partitions with Various Input Concentrations

A linear relationship between the input concentration and number of positive partitions detected was identified (N1 R2 = 0.994, N2 R2 = 0.993). This provides strong evidence for the feasibility of accurate and precise quantitative monitoring of viral presence changes using the Absolute Q Digital PCR Platform.


In this study, we established the limit of detection of the Combinati |Q| SARS-CoV-2 Triplex Kit as 200 cp/mL and defined the protocol used to determine the LoD. Additionally, we demonstrated the ability to accurately quantify across a large range of input sample. In summary, the Combinati |Q| SARS-CoV-2 RT-dPCR Triplex kit combined with the Absolute Q Digital PCR Platform enabled highly sensitive detection and quantification of SARS-CoV-2 when coupled with the Promega RSC for nucleic acid purification. The quantitative measurement provided by the assay can be used for a wide range of applications, including tracking viral load changes and wastewater monitoring.

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