COVID-19 and Diagnostic Testing for SARS-CoV-2 by RT-qPCR—Facts and Fallacies

Bustin, Stephen A.; Mueller, Reinhold; Shipley, Gregory L.; Nolan, Tania

doi:10.3390/ijms22052459

Cited by 25 publications

(33 citation statements)

References 109 publications

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“…Additionally, it is important to note that variation between RT-qPCR replicates, experimental runs, instruments, and laboratories is expected to a degree, and is well documented for various SARS-CoV-2 RT-qPCR assays (Bustin et al, 2021). While it is not possible to independently account for this expected variation, the variability observed in this review often exceeded recommend best practices strongly suggesting that the wastewater surveillance community must make a concerted effort to improve both reporting of RT-qPCR parameters and optimization of SARS-CoV-2 RT-qPCR assays.…”

Section: Discussionmentioning

confidence: 99%

Inherent Bias of SARS-CoV-2 RNA Quantification for Wastewater Surveillance Due to Variable RT-qPCR Assay Parameters

Bivins¹,

Kaya²,

Bibby³

et al. 2021

Preprint

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The coronavirus disease 2019 (COVID-19) pandemic has led to wastewater surveillance becoming an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. As a result, molecular methods, in particular reverse transcription-quantitative PCR (RT-qPCR), have been employed to generate large data sets aimed at the detection and quantification of SARS-CoV-2 in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method that fits all use cases, there are no certified quantification standards and experiments are carried out using numerous different assays, reagents, instruments, and data analysis protocols. These variations can lead to the reporting of erroneous quantitative data resulting in potentially misleading interpretations and conclusions. We have reviewed the SARS-CoV-2 wastewater surveillance literature focusing on the variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices as described in The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

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Section: Discussionmentioning

confidence: 99%

Inherent Bias of SARS-CoV-2 RNA Quantification for Wastewater Surveillance Due to Variable RT-qPCR Assay Parameters

Bivins¹,

Kaya²,

Bibby³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…and (d) the control of sample processing/extraction. These types of quality controls should not be added externally [31] but should be intrinsically present in the sample [1,3,16,21,22,32]. SAC unifies these quality assurance controls.…”

Section: Introductionmentioning

confidence: 99%

“…Quality control requirements for screening assays: The MIQE rules are among some of the primary quality requirements to be followed when validating a new screening qPCR assay [ 21 , 22 , 23 , 24 ]. These rules also stipulate that quantitative, or semi-quantitative qPCR analysis can be performed by relative quantification with a second biomarker control, equivalent to SAC [ 22 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

“…For example, even though emergency uses of different COVID-19 tests are authorized, recommendations made by CDC ( or , accessed on 6 June 2021) and WHO ( , accessed on 6 June 2021) which assure quality of testing must include: (a) control of sampling, (b) control of reaction inhibition, (c) control of the chemical integrity of biomarker (RNA, or DNA, or protein…) and (d) the control of sample processing/extraction. These types of quality controls should not be added externally [ 31 ] but should be intrinsically present in the sample [ 1 , 3 , 16 , 21 , 22 , 32 ]. SAC unifies these quality assurance controls.…”

Section: Introductionmentioning

confidence: 99%

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Sample Adequacy Control (SAC) Lowers False Negatives and Increases the Quality of Screening: Introduction of “Non-Competitive” SAC for qPCR Assays

et al. 2021

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Sample Adequacy Control (SAC) has critical analytical, clinical and epidemiological value that increases confidence in a negative test result. The SAC is an integral qPCR assay control, which ensures that all pre-analytical and analytical steps are adequate for accurate testing and reporting. As such, a negative SAC with a negative result on pathogen screen specifies that the result should be reported as inconclusive instead of negative. Despite this, many regulatory approved tests do not incorporate SAC into their assay design. Herein, we emphasize the universal value of SAC and offer for the first time, a simple technical strategy to introduce non-competitive SAC which does not interfere with the limit of detection for the screened pathogen. Integration of SAC can provide key benefits towards identifying, isolating, quarantining and contact tracing infected individuals and in turn can improve worldwide efforts in infection control.

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“…The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the aetiological agent for coronavirus disease in 2019 has enhanced the role of RT-qPCR as an essential tool for the early diagnosis of this disease, but also highlighted the previously ignored challenges [27]. Initial difficulties have been early and openly acknowledged [28], especially with regards to the 2.3.…”

Section: Introductionmentioning

confidence: 99%

RT-qPCR Diagnostics: The “Drosten” Sars-Cov-2 Assay Paradigm

Bustin

Kirvell

Huggett

et al. 2021

Preprint

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The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is an established tool for the diagnosis of RNA pathogens. Its potential for automation has caused it to be used as a presence/absence diagnostic tool even when RNA quantification is not required. This technology has been pushed to the forefront of public awareness by the COVID-19 pandemic, as its global application has enabled rapid and analytically sensitive mass testing, with the first test targeting three viral genes published within days of the publication of the SARS-CoV-2 genomic sequence. One of those, targeting the RNA-dependent RNA polymerase gene, has been heavily criticised for supposed scientific flaws at the molecular and methodological level and this criticism has been extrapolated to doubts about the validity of RT-qPCR for COVID-19 testing in general. We have analysed this assay in detail and our findings reveal some limitations, but also highlight the robustness of the RT-qPCR methodology for SARS-CoV-2 detection. Whilst our data show that some errors can be tolerated, it is always prudent to confirm that primer and probe sequences complement their intended target, since when errors do occur, they may result in a reduction in the analytical sensitivity. However, in this case it is unlikely that a mismatch will result in poor specificity or significant number of false positive SARS-CoV-2 diagnoses, especially as this is routinely checked by diagnostic laboratories as part of their quality assurance.

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COVID-19 and Diagnostic Testing for SARS-CoV-2 by RT-qPCR—Facts and Fallacies

Cited by 25 publications

References 109 publications

Inherent Bias of SARS-CoV-2 RNA Quantification for Wastewater Surveillance Due to Variable RT-qPCR Assay Parameters

Inherent Bias of SARS-CoV-2 RNA Quantification for Wastewater Surveillance Due to Variable RT-qPCR Assay Parameters

Sample Adequacy Control (SAC) Lowers False Negatives and Increases the Quality of Screening: Introduction of “Non-Competitive” SAC for qPCR Assays

RT-qPCR Diagnostics: The “Drosten” Sars-Cov-2 Assay Paradigm

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