This work summarizes steps on developing different assays for SARS-CoV-2 detection using a two color ddPCR system. The steps are elaborate and notes have been included on how to improve the assays and experiment performance. These assays may be used for multiple SARS-CoV-2 RT-ddPCR applications.
Diagnosis of the ongoing SARS-CoV-2 pandemic is a priority for all countries across the globe. Currently, reverse transcription quantitative PCR (RT-qPCR) is the gold standard for SARS-CoV-2 diagnosis as no permanent solution is available. However effective this technique may be, research has emerged showing its limitations in detection and diagnosis especially when it comes to low abundant targets. In contrast, droplet digital PCR (ddPCR), a recent emerging technology with superior advantages over qPCR, has been shown to overcome the challenges of RT-qPCR in diagnosis of SARS-CoV-2 from low abundant target samples. Prospectively, in this article, the capabilities of RT-ddPCR are further expanded by showing steps on how to develop simplex, duplex, triplex probe mix, and quadruplex assays using a two-color detection system. Using primers and probes targeting specific sites of the SARS-CoV-2 genome (N, ORF1ab, RPP30, and RBD2), the development of these assays is shown to be possible. Additionally, step by step detailed protocols, notes, and suggestions on how to improve the assays workflow and analyze data are provided. Adapting this workflow in future works will ensure that the maximum number of targets can be sensitively detected in a small sample significantly improving on cost and sample throughput.
Polymerase chain reaction (PCR), a well-recognized technique, has undergone several transformations since its advent to become a powerful technique capable of providing answers to nucleic acid research. These transformations have been a constant improvement of the old technique. These transformations can be summarized into three generations1. The first generation is conventional PCR that relies on gel electrophoresis to quantify and detect amplified targets. The second generation is quantitative real time PCR (qPCR) that can detect samples in real time and rely on a standard curve to directly quantify targets in a sample. The third generation, digital PCR (dPCR), can perform both detection, and absolute quantification of nucleic acid targets without the need of a standard curve. dPCR has also been improved further from reaction chambers being separated by the wells of a wall into emulsions of oil, water, and stabilizing chemicals within the same well as seen in droplet-based digital PCR2. In droplet digital PCR (ddPCR), a sample is partitioned into thousands of nanoliter-sized droplets containing individual targets that will later be quantified using Poisson statistics2,3,4. This technique gives ddPCR an edge in quantifying low abundant targets when compared to the other generations of PCR.
Recently, multiple applications have highlighted the superiority of ddPCR over the commonly used qPCR when detecting and quantifying low abundant targets1,5,6. SARS-CoV-2 is no exception to these applications7,8,9,10,11,12. Since the outbreak of SARS-CoV-2, scientists have been working on all fronts to come up with solutions on how to diagnose the virus and detect it efficiently. The current gold standard still remains to be qPCR13. However, RT-ddPCR has been shown to be more accurate in detecting low abundant SARS-CoV-2 targets from both environmental and clinical samples when compared to RT-qPCR7,8,9,10,11,12. Most of the SARS-CoV-2 ddPCR published works depend on simplex assays with the multiplex ones depending on commercial assays. Hence, more should be done to explain how to develop multiplex RT-dPCR assays for SARS-CoV-2 detection.
In a proper assay design, multiplexing can be used to save on cost, increase sample throughput, and maximize on the number of targets that can be sensitively detected within a small sample. When multiplexing with ddPCR, one must take account of how many fluorophores can be detected in a particular system. Some ddPCR platforms can support up to three channels while others support only two channels. Hence, when multiplexing with two channels, one has to use different approaches, including higher order multiplexing to detect more than two targets14,15,16. In this work, a two color ddPCR detection system is used to show steps on how to develop different SARS-CoV-2 RT-ddPCR assays that can be adapted for different research applications.
Ethical statement
Wuhan Institute of Virology (WHIOV) is among the labs and institutes approved by China CDC of Wuhan city to conduct research on SARS-CoV-2 and detect COVID-19 from clinical samples. Research on developing new diagnostic techniques for COVID-19 using clinical samples has also been approved by the ethical committee of Wuhan Institute of Virology (2020FCA001).
1. Sample processing workflow (Figure 1A)
NOTE: Throughout the protocol, it is important to use separate rooms with dedicated pipettes for sample handling (extraction and storage), reagent/mastermix preparation and storage, reaction mix preparation (sample plus mastermix), and detection, to avoid cross contamination. The assays to be developed can be used in the detection of clinical samples or research samples. All samples should be treated as if they can transmit infectious agents even when using safe laboratory procedures. Sample processing steps should be done in a biosafety level 2 (BSL-2) laboratory following strict BSL-2 rules, including wearing of appropriate personal protective equipment (PPE).
2. Optimization of ddPCR assay and workflow
NOTE: Optimize the assays before/after reading the droplets. Dependent on the results, they can be optimized at any point of the work to achieve better results. Below are some common factors to be considered when optimizing ddPCR experiments.
3. ddPCR workflow (Figure 1B) and assay development (Table 2)
NOTE: Like other ddPCR detection systems, this workflow also consists of four steps (Figure 1B), including reaction mix preparation, droplet generation, PCR amplification, and droplet reading.
4. Data analysis (Supplementary Figures 2 and 3)
In a proof-of-concept study, the multiplex assays analytical performance was tested on clinical and research samples19. The performance of the multiplex assays was superior to that of an RT-PCR19. Since low numbers of droplets may indicate a problem during droplet generation, in this article a cutoff of 10,000 droplets per well was set based on empirical data.
A good separation between positive and negative droplets with minimal rain interference can help in data analysis. Hence, in a good experiment, assay optimization is key19. As seen in the temperature gradient analysis results in Figure 2D, high annealing temperatures (e.g., 65 °C) could not clearly distinguish positive droplets from negative droplets when a duplex assay (N (FAM) and RPP30 (HEX)) was run. However, with a decrease in annealing temperature, optimal separation between positive and negative droplets was achieved. A temperature of 57 °C was found optimal. This can also be observed in other assays19.
Using a two color (FAM/HEX) RT-ddPCR detection system, it is possible to detect one (Figure 2A, B), two (Figure 2C), three (Figure 3A), and four (Figure 3B) SARS-CoV-2 targets within a single sample. During data analysis, the accompanying software used to read droplets can only analyze simplex and duplex assays as shown in Figure 2. This means that for higher order multiplex assays (>3 targets), an external software should be used for data analysis as shown in Figures 3, S2, and S3. It is important to also note that the external software can also be used to analyze simplex and duplex data. For simplex and duplex data, analysis is quite simple as targets are separated as either positive or negative droplets in their respective channels as shown in Figure 2. A NTC sample can help in the location of negative droplets that can in turn help one set thresholds for data analysis as shown in Figure 2A. For the duplex assay, analysis can be done in individual channels (Figure 2B i,ii) or in the 2D Amplitude (Figure 2B iii).
For higher order multiplex assays, data analysis is not straightforward, and attention should be focused on droplet target assignment. After installing the external software, select wells to be analyzed, select the appropriate experiment type, and assign target clusters based on experiment type as shown in Figure S2 and S3. The Select to Assign Cluster window pop will guide one on how to assign clusters in the higher multiplex assays. Use the graph tools to assign up to 8 droplet clusters for the triplex probe mix assay (Figure 3A), and up to 16 droplet clusters for the quadruplex amplitude-based assay (Figure 3B).
After assigning clusters and thresholds, quantification data for each target in the form of copies/µL can be read in the well data window on the lower right of the external software. This data can be used to estimate the number of copies of targets in the starting sample. E.g., if 2.2 µL of the sample was used in a final volume of 22 µL, and the software recorded 30.5 copies/µL for ORF1ab, there were 30.5 x 22 = 671 copies of ORF1ab in the PCR mix. The mix contained 2.2 µL of original sample, hence, there were 671 copies of ORF1ab in the starting sample, and 671/2.2 = 305 copies/µL of ORF1ab in the original sample. This method can be used to estimate the concentration of each target in all assays.
Target | Sequence 5’ to 3’ | Probe dye(s) | Product length (bp) | Ref | |
ORF1ab | Forward | CCCTGTGGGTT TTACACTTAA |
5’- FAM and BHQ1-3’ 5’- HEX and BHQ1-3’ |
119 | [16] |
Reverse | ACGATTGTGCAT CAGCTGA |
||||
Probe | CCGTCTGCGGT ATGTGGAAAGG TTATGG |
||||
N | Forward | GGGGAACTTCTC CTGCTAGAAT |
5’- FAM and BHQ1-3’ 5’- HEX and BHQ1-3’ |
99 | [16] |
Reverse | CAGACATTTTGC TCTCAAGCTG |
||||
Probe | TTGCTGCTGCT TGACAGATT |
||||
RPP30 | Forward | AGTGCATGCTTA TCTCTGACAG |
5’- HEX and BHQ1-3’ | 87 | [8] |
Reverse | GCAGGGCTATAG ACAAGTTCA |
||||
Probe | TTTCCTGTGAAG GCG ATTGACCGA |
||||
RBD2 | Forward | CTCAAGTGTCT GTGGATCACG |
5’- FAM and BHQ1-3’ | 121 | [17] |
Reverse | CCTGTGCCTGT TAAACCATTG |
||||
Probe | ACAGCATCAGT AGTGTCAGCAA TGTCTC |
Table 1: Primer and probe sequences used to develop the different SARS-CoV-2 assays.
Final concentration of primer-probe per assay in nMa | |||||
Target | Primer/probe | Simplexb | Duplexc | Triplex probe mixd | Fourplex amplitudee |
ORF1ab | ORF1ab F | 800 | |||
ORF1ab R | 800 | ||||
ORF1ab FAM | |||||
ORF1ab HEX | 250 | ||||
N | N F | 800 | 800 | 800 | |
N R | 800 | 800 | 800 | ||
N FAM | 250 | 125 | 250 | ||
N HEX | 125 | ||||
RPP30 | RPP30 F | 800 | 800 | 800 | 800 |
RPP30 R | 800 | 800 | 800 | 800 | |
RPP30 FAM | |||||
RPP30 HEX | 250 | 250 | 250 | 125 | |
RBD2 | RBD2 F | 800 | 800 | 800 | |
RBD2 R | 800 | 800 | 800 | ||
RBD2 FAM | 250 | 250 | 125 | ||
RBD2 HEX | |||||
a In all assays, the targets can be interchanged based on the users preference. The used targets are for demonstration purposes of this experiment. | |||||
b Only one target can be detectected at a time in the simplex assay in either the FAM or HEX channel. RBD2 is used to demonstrate FAM channel results while RPP30 is used for the HEX channel. | |||||
c Two target can be detectected at a time in the duplex assay in the FAM and HEX channel. | |||||
d Three targets can be detected using both channels i.e target 1 will be detected in FAM (1× probe concentration), target two in HEX (1× probe concentration), and target 3 in both channels (a mixture of 0.5× HEX and 0.5× FAM probe concentratins to constitute the final 1×). | |||||
e Two targets are detected in each channel (FAM and HEX) with 1× and O.5× probe concentration in each channel. |
Table 2: Final concentration of different primer and probe pairs per assay.
Figure 1: Sample processing and droplet digital PCR workflow. (A) The sample processing workflow includes sample collection and transport to a BSL-2 facility, inactivation, extraction, and cDNA generation. (B) The droplet digital PCR workflow begins with preparation of the mastermix, loading the mastermix into a ddPCR plate and adding sample(s), generating droplets, amplifying targets inside droplets by PCR, and finally reading the amplified droplets using a droplet reader. Please click here to view a larger version of this figure.
Figure 2: Simplex and duplex assay results, including annealing temperature optimization. (A) Simplex assay results when a single target (RBD2) was FAM labeled. (B) Simplex assay results when a single target (RPP30) was HEX labeled. (C) Duplex assay result of two targets in 1D and 2D (iii) Channels after N (i) was FAM labeled and RPP30 (ii) was HEX labeled. (D) Annealing temperature gradient (65 °C to 55 °C) results of a duplex assay labeled with ORF1ab (FAM) and RPP30 (HEX). Please click here to view a larger version of this figure.
Figure 3: Triplex probe mix and quadruplex amplitude-based multiplex assay results. (A) Triplex probe mix assay results when three targets were labeled with the following ratios of FAM:HEX; RBD2 (1:0), N (0.5:0.5), and RPP30 (0:1). (B) Quadruplex amplitude-based assay results after four targets were labeled with the following ratios of FAM:HEX; RBD2(0.5:0), N (1:0), RPP30 (0:0.5), and ORF1ab (0:1). 1 and 0.5 are probe concentrations 250 nM and 125 nM, respectively. Please click here to view a larger version of this figure.
Supplementary Figure 1: Droplet generation using an automated droplet generator. (A) Consumables needed to set up the AutoDG. (B) On the AutoDG touch screen, touch Configure Sample Plate and select columns where samples are located on the sample plate and press OK. (C) Once selected, the screen turns yellow indicating where consumables should be loaded. (D) Open the AutoDG door and load consumables in the respective places. Load consumables from the back working toward the front. Make sure each time a consumable is added the light turns from yellow to green at that location. (E) Ensure the oil type used is oil for probes. (F) Close the AutoDG door and ensure all reagents are set in place by checking whether the AutoDG touch screen is green. (G) Press START Droplet Generation to generate droplets. (H) After droplet generation is complete, open the AutoDG and remove the droplet plate. (I) Seal the droplet plate using a pierceable foil heat seal. Please click here to download this File.
Supplementary Figure 2: Steps on analysis of amplitude-based multiplex ddPCR assay results using an external software. (A) Install the external software on a computer. (B) Open the .qlp file by either right clicking on it and choosing Open with the installed external software or opening the external software and clicking on the Browse option to locate the file in your folder. Alternatively, one can drag the .qlp file and drop it the open external software to open it. (C) Once open, on the right side of the Plate Editor tab, choose probe mix triplex from the drop-down menu and assign target information accordingly, and click on Apply. (D) On the left side of the 2D amplitude tab, use the Graph Tools to assign specific colors to different targets for detection and quantification. Once droplet cluster targets are identified, the quantification results can be seen on the Well Data window in the same 2D amplitude tab. Please click here to download this File.
Supplementary Figure 3: Steps on analysis of amplitude based multiplex ddPCR assay results using an external software. (A) Install the external software on a computer. (B) Open the .qlp file by either right clicking on it and choosing Open with the installed external software, or opening the external software and clicking on the Browse option to locate the file in your folder. Alternatively, one can drag the .qlp file and drop it in the already open external software to open it. (C) Once open, on the right side of the Plate Editor tab, choose amplitude multiplex from the drop-down menu and assign target information accordingly, and click on Apply. (D) On the left side of the 2D amplitude tab, use the Graph Tools to assign specific colors to different targets for detection and quantification. Once droplet cluster targets are identified, the quantification results can be seen on the Well Data window in the same 2D amplitude tab. Please click here to download this File.
Few resources are available on how to develop RT-ddPCR assays for SARS-CoV-2 detection. Though not used in this article, standard samples with known copies may be used to develop and optimize assays. In this work however, SARS-CoV-2 samples grown in Vero-E6 cells were spiked in a background of human genomic RNA and used as standard samples to develop the assays. Proper primer and probe sequences are essential when developing assays. Since most preliminary work on SARS-CoV-2 RT-ddPCR used the China CDC primer and probes targeting the ORF1ab and N gene, they had found them fit to be included in this work7,8,9,10,11. The analytical specificity and sensitivity of these primers have also been compared using ddPCR in the previous work7. The RBD2 primers and probe13 were developed in-house and found fit for RT-ddPCR. Since the assays may be used for different applications, including diagnosis, the Ribonuclease P protein subunit p30 (RPP30) specific human gene was included in all multiplex assays. These gene can be used as a human endogenous control for diagnostic experiments. However, in the case of environmental sampling or other research that do not need the human reference gene, one may alternate this target with another SARS-CoV-2 target.
In all assays, it is important to include controls to validate assays and experimental data. These controls may include: NTC (nuclease free water as sample) to help in setting thresholds and locating negative droplet cluster; positive control (sample with all SARS-CoV-2 targets, including human reference gene) to assess reagent failure, primer and probe integrity, and substantial reverse transcription detection/location of positive droplet targets; and extraction controls (pooled human samples from healthy volunteers or total nucleic acid extracted from a noninfectious cultured human cell) to detect extraction step failure or success.
Most ddPCR systems, including the QX200 system have a narrow dynamic range from 1 to 120,000 copies/20 µL reaction. When detecting unknow samples, the target concentration in the starting sample is often unknown and this may pose challenges when quantifying highly concentrated samples. To overcome this, it is recommended that when quantifying samples suspected to contain high amounts of target molecules (such as cell culture), one should plan to reduce the starting sample accordingly. In the case where the target copy number/genome is unknown, one should determine the optimal starting amount through a series of four tenfold serial dilution of each sample at the expected digital range. By assaying these four points, it is ensured that one of the data points is within the optimal digital range.
Using high primer and low probe concentration is a perquisite of most simplex and duplex ddPCR experiments. This difference in concentration increases the amplitude separation distance between the positive and negative droplet clusters, hence making it easy to analyze data. However, when developing higher order multiplex assays, changes in these concentrations may lead to changes in the position of positive droplet targets as shown in Figure 3 and 4. As a result, one assay optimization option apart from annealing temperature would be to change target primer or probe concentration to distinguish droplets. This phenomenon has been used and explained before14,15,16.
Despite the assay performance, this work is a two-step RT-ddPCR workflow. The extra reverse transcription step before ddPCR, gives room for contamination of samples. However, if careful and proper sample handling techniques are used, this will be a non-issue. Positively, DNA is known to be more stable than RNA. The conversion of RNA to cDNA may extend the sample's shelf life during storage as compared to RNA. A two-step RT-ddPCR experiment is also cheaper than a one-step RT-ddPCR experiment.
Compared to RT-qPCR, RT-ddPCR is expensive. Hence, considerations should be taken when performing RT-ddPCR. For example, during diagnosis, one may use RT-ddPCR in the case where their samples have low abundant targets. However, there is a possibility that the costs of dPCR instruments and reagents will drop soon, and the technique will be adapted in many laboratories, as it happened in the past with regular PCR and qPCR. Hence, it is important to set protocols such as this for current and future users of dPCR. In conclusion, the developed assays give room for prospective users to vary targets based on their applications. Multiplexing will ensure that one can efficiently detect many targets within a single sample in a single reaction. So far, this may be the first protocol that gives a full detail on how to use the AutoDG system, including the external software in SARS-CoV-2 detection. More work on assay optimization still needs to be done to achieve better separation in the quadruplex assay. The use of standards will also help improve the developed assays.
The authors have nothing to disclose.
This research was funded by Megaproject of Infectious Disease Control from Ministry of Health of China, grant number 2017ZX10302301-005 and Sino-Africa Joint Research Center, grant number SAJC201605.
32-channel fully automatic nucleic acid extractor Purifier 32 | Genfine Biotech | FHT101-32 | Automated extractor for RNA |
AutoDG Oil for Probes | BioRad | 12003017 | QX200 AutoDG consumable |
ddPCR 96-Well Plates | BioRad | 12003185 | |
ddPCR Supermix for Probes (No dUTP) | BioRad | 1863024 | Making ddPCR assay mastermix |
DG32 AutoDG Cartridges | BioRad | 1864108 | QX200 AutoDG consumable |
Electronic thermostatic water bath pot | Beijing Changfeng Instrument and Meter Company | XMTD-8000 | Heat inactivation of samples |
FineMag Rapid Bead Virus DNA/RNA Extraction Kit | Genfine Biotech | FMY502T5 | Magnetic bead extraction of inactivated RNA samples |
Pierceable Foil Heat Seals | BioRad | 1814040 | |
Pipet Tips for the AutoDG | BioRad | 1864120 | QX200 AutoDG consumable |
Pipet Tip Waste Bins for the AutoDG | BioRad | 1864125 | QX200 AutoDG consumable |
PrimeScript RT Master Mix (Perfect Real Time) | TaKaRa | RR036A | cDNA generation |
PX1 PCR Plate Sealer | BioRad | 1814000 | Seal the droplet plate from AutoDG |
QuantaSoft 1.7 Software | BioRad | 10026368 | Data acquisition and analysis |
QuantaSoft Analysis Pro 1.0 | BioRad | N/A | Data analysis |
QX200 Automated Droplet Gererator (AutoDG) | BioRad | 1864101 | QX200 AutoDG consumable |
QX200 Droplet Reader | BioRad | 1864003 | Droplet reading and data acquisition |
T100 Thermal Cycler | BioRad | 1861096 | Droplet target amplification (PCR) and cDNA generation |