Evidence map›Paper›PMID 33964860›Full record

ArticleBiotechnology journal2021

Lyophilization of premixed COVID-19 diagnostic RT-qPCR reactions enables stable long-term storage at elevated temperature.

Michael J Hammerling, Katherine F Warfel, Michael C Jewett

Abstract read
In one paragraph

Article in Biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Michael J HammerlingDepartment of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, USA.ORCID https://orcid.org/0000-0002-0499-6795
Katherine F WarfelDepartment of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, USA.
Michael C JewettDepartment of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) diagnostic tests for SARS-CoV-2 are the cornerstone of the global testing infrastructure. However, these tests require cold-chain shipping to distribute, and the labor of skilled technicians to assemble reactions and interpret the results. Strategies to reduce shipping and labor costs at the point-of-care could aid in diagnostic testing scale-up and response to the COVID-19 outbreak, as well as in future outbreaks. In this study we test both lab-developed and commercial SARS-CoV-2 diagnostic RT-qPCR mixes for the ability to be stabilized against elevated temperature by lyophilization. Fully assembled reactions were lyophilized and stored for up to a month at ambient or elevated temperature and were subsequently assayed for their ability to detect dilutions of synthetic SARS-CoV-2 RNA. Of the mixes tested, we show that one commercial mix can maintain activity and sensitivity after storage for at least 30 days at ambient temperature after lyophilization. We also demonstrate that lyoprotectants such as disaccharides can stabilize freeze-dried diagnostic reactions against elevated temperatures (up to 50°C) for at least 30 days. We anticipate that the incorporation of these methods into SARS-CoV-2 diagnostic testing will improve testing pipelines by reducing labor at the testing facility and eliminating the need for cold-chain shipping.

Indexed as

COVID-19Freeze DryingHumansRNA, ViralSARS-CoV-2Sensitivity and SpecificityTemperatureRNA, Viralcell-freeCOVID-19 diagnosticslyophilizationRT-qPCRsynthetic biology

Identifiers

PMID33964860
PMCPMC8237061

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.