Large-scale implementation of pooled RNA-extraction and RT-PCR for SARS-CoV-2 detection

Ben-Ami, Roni; Klochendler, Agnes; Seidel, Matan; Sido, Tal; Gurel-Gurevich, Ori; Yassour, Moran; Meshorer, Eran; Benedek, Gil; Fogel, Irit; Oiknine‐Djian, Esther; A, Gertler; Rotstein, Zeev; Lavi, Bruno; Dor, Yuval; Wolf, Dana; Salton, Maayan; Drier, Yotam

doi:10.1101/2020.04.17.20069062

Cited by 51 publications

(59 citation statements)

References 31 publications

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“…However, appraising the performance of a pooling method exclusively by its efficiency would ignore one of the major drawbacks of pooling: loss of sensitivity due to dilution of the target. This issue becomes most pertinent when the viral load is low [9][10][11]13,14 . Our results confirm that all tested pooling methods suffer from false negatives, to a variable degree (Figure 2).…”

Section: Sensitivity Loss In Function Of Viral Loadmentioning

confidence: 99%

Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for SARS-CoV-2 RT-qPCR screening purposes

Verwilt

Mestdagh

Vandesompele

2020

Preprint

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As SARS-CoV-2 continues to spread around the world while the pandemic lasts, testing facilities are forced to massively increment their testing capacities to handle the increasing number of samples. While sample pooling methods have been proposed or are effectively implemented in some labs, no systematic and large-scale simulations have been performed using real-life quantitative data from testing facilities. Here, we use anonymous data from 1632 positive cases to simulate and compare 1D and 2D pooling strategies. We show that the choice of pooling method and pool size is an intricate decision with a prevalence-dependent efficiency-sensitivity trade-off.

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Section: Sensitivity Loss In Function Of Viral Loadmentioning

confidence: 99%

Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for SARS-CoV-2 RT-qPCR screening purposes

Verwilt

Mestdagh

Vandesompele

2020

Preprint

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“…Recently, several pooling tests for COVID-19 using probe-based assays have shown efficient viral detection. These studies have shown a wide range of pooling settings, from eight to 32 samples per pool, increasing up to 8 folds the testing efficiency compared to individual testing (Shenta et al, 2020;Viehweger et al, 2020;Ben-Ami et al, 2020). Here, we showed an efficient performance in the range of setting pools tested before the RNA extraction step, with an analytical sensitivity that shown that pooling setting between 5 to 20 samples per pool retain the accuracy of the test obtaining a shift to the right of the amplification curve up to 5.9 cycles in the dye-based assay and 4.4 cycles in the probe-based assay.…”

Section: Pooling Testmentioning

confidence: 99%

A comparative evaluation of a dye-based and probe-based RT-qPCR assay for the screening of SARS-CoV-2 using individual and pooled-sample testing

Verdugo

Plaza

Acosta‐Jamett

et al. 2020

Preprint

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Effective interventions are mandatory to control the transmission and spread of SARS-CoV-2, a highly contagious virus causing devastating effects worldwide. Cost-effective approaches are pivotal tools required to increase the detection rates and escalate further in massive surveillance programs, especially in countries with limited resources that most of the efforts have focused on symptomatic cases only. Here, we compared the performance of the RT-qPCR using an intercalating dye with the probe-based assay. Then, we tested and compared these two RT-qPCR chemistries in different pooling systems: after RNA extraction (post-RNA extraction) and before RNA extraction (pre-RNA extraction) optimizing by pool size and template volume. We evaluated these approaches in 610 clinical samples. Our results show that the dye-based technique has a high analytical sensitivity similar to the probe-based detection assay used worldwide. Further, this assay may also be applicable in testing by pool systems post-RNA extraction up to 20 samples. However, the most efficient system for massive surveillance, the pre-RNA extraction pooling approach, was obtained with the probe-based assay in test up to 10 samples adding 13.5 uL of RNA template. The low cost and the potential use in pre-RNA extraction pool systems, place of this assays as a valuable resource for scalable sampling to larger populations. Implementing a pool system for population sampling results in an important savings of laboratory resources and time, which are two key factors during an epidemic outbreak. Using the pooling approaches evaluated here, we are confident that it can be used as a valid alternative assay for the detection of SARS-CoV-2 in human samples.

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“…In spite of these idealizations, the practical utility of the predictions are quantitatively validated by recent SARS-CoV-2 pooled testing data. [2][3][4][5][6] The results indicate that pooled testing can significantly reduce the number of the SARS-CoV-2 tests required to identify each positive individual, even in populations with infection rates above 10%, although pooled testing is most advantageous in populations with lower infection rates. The field testing validation studies also confirm that the present predictions provide conservative testing efficiency estimates, as non-uniform clustering of infections is predicted to lead to an increase in testing efficiency, above that predicted assuming a uniform infection rate.…”

Section: Introductionmentioning

confidence: 98%

“…The optimal pool size, n, for a population with a given infection probability p was first obtained obtained by Dorfman 1 (and has since spawned numerous generalizations). 5,7,8 Here Dorfman's results are extended to yield practically useful predictions of the range of infection rates over which a given fixed pool size remains nearly optimal, as well as the significant additional efficiency that may be obtainable from using a second round of pooling for popula-3 tions with 0.001 ≤ p < 0.1 (0.1% ≤ p% < 10%). For a populations with a very low infection rate of 0.1%, the predicted 1st round optimal pool size is 32.…”

Section: Introductionmentioning

confidence: 99%

Optimally Pooled Viral Testing

Ben‐Amotz

2020

Preprint

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It has long been known that pooling samples may be used to minimize the total number of tests required in order to identify each infected individual in a population. Pooling is most advantageous in populations with low infection probability, but remains better than non-pooled testing up to an infection probability of 30%. The present predictions imply that optimal pooling may be used to extremely efficiently test populations with infection percentages down to 0.1%, in which case a single round of optimal pooling with an average of as few as 6 tests may be sufficient to uniquely identify every infected individual in a population of 100 (and increases to 20 tests when at 1% infection). Additional testing efficiency may be realized by performing a second round of pooled testing, thus reducing the average number of tests required to test a population with 1% infection from 20 to 14 out of 100 (and from 6 to 4 with 0.1% infections). These best case predictions, obtained assuming perfect test accuracy and specificity, provide a quantitative measure of the optimal pool size and expected testing efficiency gains in populations with infection probabilities ranging from 0.1% to 30%, and are supported by recent COVID-19 detection sensitivity and optimized pool size experiments.

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Large-scale implementation of pooled RNA-extraction and RT-PCR for SARS-CoV-2 detection

Cited by 51 publications

References 31 publications

Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for SARS-CoV-2 RT-qPCR screening purposes

Evaluation of efficiency and sensitivity of 1D and 2D sample pooling strategies for SARS-CoV-2 RT-qPCR screening purposes

A comparative evaluation of a dye-based and probe-based RT-qPCR assay for the screening of SARS-CoV-2 using individual and pooled-sample testing

Optimally Pooled Viral Testing

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