Evidence map›Paper›PMID 34488633›Full record

ArticleBMC microbiology2021

An optimised protocol for detection of SARS-CoV-2 in stool.

Tianqi Li, Enriqueta Garcia-Gutierrez, Daniel A Yara, Jacob Scadden, Jade Davies, Chloe Hutchins, Alp Aydin, Justin O'Grady, Arjan Narbad, Stefano Romano and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 46% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

11 authors at 2 institutions in 2 countries.

Tianqi Li *Gut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Enriqueta Garcia-Gutierrez *Gut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Daniel A YaraGut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Jacob ScaddenGut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Jade DaviesGut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Chloe HutchinsGut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Alp AydinMicrobes in the Food Chain, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Justin O'GradyMicrobes in the Food Chain, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Arjan NarbadGut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK.
Stefano RomanoGut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK. Stefano.Romano@quadram.ac.uk.ORCID 0000-0002-7600-1953
Lizbeth SayavedraGut Health and Microbes, Quadram Institute Bioscience, Norwich Research Park, Norwich, UK. Lizbeth.Sayavedra@quadram.ac.uk.
Norwich Research Park · GBJiangnan University · CN

Funding

Biotechnology and Biological Sciences Research Council BB/M011216/1Biotechnology and Biological Sciences Research Council BB/R012490/1Biotechnology and Biological Sciences Research Council BB/R012504/1Biotechnology and Biological Sciences Research Council BB/S506679/1Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10348Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10349Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10351Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10352Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10355Biotechnology and Biological Sciences Research Council BBS/E/F/000PR10356Biotechnology and Biological Sciences Research Council BBS/OS/NW/000006
6 · The paper itself

Abstract

backgroundSARS-CoV-2 has been detected in stool samples of COVID-19 patients, with potential implications for faecal-oral transmission. Compared to nasopharyngeal swab samples, the complexity of the stool matrix poses a challenge in the detection of the virus that has not yet been solved. However, robust and reliable methods are needed to estimate the prevalence and persistence of SARS-CoV-2 in the gut and to ensure the safety of microbiome-based procedures such as faecal microbiota transplant (FMT). The aim of this study was to establish a sensitive and reliable method for detecting SARS-CoV-2 in stool samples.

resultsStool samples from individuals free of SARS-CoV-2 were homogenised in saline buffer and spiked with a known titre of inactivated virus ranging from 50 to 750 viral particles per 100 mg stool. Viral particles were concentrated by ultrafiltration, RNA was extracted, and SARS-CoV-2 was detected via real-time reverse-transcription polymerase chain reaction (RT-qPCR) using the CDC primers and probes. The RNA extraction procedure we used allowed for the detection of SARS-CoV-2 via RT-qPCR in most of the stool samples tested. We could detect as few as 50 viral particles per 100 mg of stool. However, high variability was observed across samples at low viral titres. The primer set targeting the N1 region provided more reliable and precise results and for this primer set our method had a limit of detection of 1 viral particle per mg of stool.

conclusionsHere we describe a sensitive method for detecting SARS-CoV-2 in stool samples. This method can be used to establish the persistence of SARS-CoV-2 in stool and ensure the safety of clinical practices such as FMT.

Indexed as

COVID-19COVID-19 Nucleic Acid TestingFecesHumansLimit of DetectionRNA, ViralSARS-CoV-2RNA, ViralClinical-testCOVID19FMTRT-qPCRStool

Identifiers

PMID34488633
PMCPMC8419809
OpenAlexW3196666393

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.