Performance comparison of fiveextraction kits for SARS-CoV-2 RNA extraction
Bibliographic record
Abstract
A new type of coronavirus, SARS-CoV-2, was identified in January 2020 Its associated disease, COVID-19, wasannounced as a pandemic by the World Health Organization in March 2020 The Ontario Institute for CancerResearch quickly engaged to support viral sequencing, not only in frontline health care workers but in cancerpatients A key deliverable was the selection of an extraction methodology that would not impact the supply ofapproved diagnostic testing reagents This consideration was in response to reports of possible shortages predictedearly in the pandemic and as indicated by the Public Health Agency of Canada (PHAC), through their call forreagents in April 2020 Five commercially available kits for automated nucleic acid extraction were compared TheKingFisher Flex Purification System (ThermoFisher, 5400610) was used for nucleic acid extraction Four kits wereselected based on availability, system compatibility, and exclusion from PHAC's call for COVID-19 testing reagents The MagMAX CORE Nucleic Acid Purification Kit (CORE;ThermoFisher, A32702), MagMAX Total Nucleic AcidIsolation Kit (Total NA;ThermoFisher, AM1840), MagMAX Total RNA Isolation Kit (Total RNA;ThermoFisher, AM1830), and Mag-Bind Viral DNA/RNA 96 Kit (Omega;Omega BioTek, M6246-03) were evaluated The MagMAXViral/Pathogen Kit (MVP;ThermoFisher, A42352), approved by the Food and Drug Administration of Canada fordiagnostic testing, was used as a benchmark Test samples were prepared using Universal Human RNA (Agilent,740000), lambda DNA solution (Sigma Aldrich, ERMAD442K), SARS-CoV-2 RNA (ATCC, VR1986D) and heat-inactivated virus (ATCC, VR-1986HK) Extractions were performed by two operators on replicate samples Protocols were assessed on reproducibility, yield, reagent availability, run time, and ease of use The top two kits were validated with nasopharyngeal swab samples from SARS-CoV-2-positive patients Four of five kits demonstratedreproducible yields, while yields from the Total RNA kit were inconsistent The CORE and Omega kits possessedthe best overall extraction efficiencies (both 70%) The MVP kit and Total NA kit were 59% and 44% efficient inrecovery, respectively The CORE and Omega kits ranked best after overall assessment Patient samples weresubsequently extracted using both kits and successfully sequenced Extraction kits do not all perform to the samespecification In our hands, we found the MVP kit did not perform as well as others, despite being approved fordiagnostic use, and the Total RNA kit showed inconsistent results Many reagents are commercially available andshould be explored as alternatives to the approved SARS-CoV-2 diagnostic reagents, particularly during a globalcrisis Interestingly, following our validation testing, supply of the CORE kit became limited with unknown futureavailability This illustrated the need to validate multiple methods during uncertain times in order to maintain criticaltesting
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".