Evidence map›Paper›PMID 33255715›Full record

ArticleMicroorganisms2020

Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community.

Claudia Sala, Hanne Mordhorst, Josephine Grützke, Annika Brinkmann, Thomas N Petersen, Casper Poulsen, Paul D Cotter, Fiona Crispie, Richard J Ellis, Gastone Castellani and 14 more

Abstract read
In one paragraph

Article in Microorganisms, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Detection ofItalian journal of food safety · 2026
    Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
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

24 authors.

Claudia SalaDepartment of Physics and Astronomy, University of Bologna, 40127 Bologna, Italy.ORCID 0000-0002-4889-1047
Hanne MordhorstResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kemitorvet, DK-2800 Kgs, 2800 Lyngby, Denmark.
Josephine GrützkeGerman Federal Institute for Risk Assessment, Department of Biological Safety, 12277 Berlin, Germany.ORCID 0000-0003-4769-0443
Annika BrinkmannHighly Pathogenic Viruses, ZBS 1, Centre for Biological Threats and Special Pathogens, Robert Koch Institute, 13353 Berlin, Germany.
Thomas N PetersenResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kemitorvet, DK-2800 Kgs, 2800 Lyngby, Denmark.ORCID 0000-0002-2484-5716
Casper PoulsenResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kemitorvet, DK-2800 Kgs, 2800 Lyngby, Denmark.
Paul D CotterTeagasc Food Research Centre, Moorepark, APC Microbiome Ireland and Vistamilk, T12 YN60 Co. Cork, Ireland.
Fiona CrispieTeagasc Food Research Centre, Moorepark, APC Microbiome Ireland and Vistamilk, T12 YN60 Co. Cork, Ireland.
Richard J EllisSurveillance and Laboratory Services Department, Animal and Plant Health Agency, APHA Weybridge, Addlestone, Surrey, KT15 3NB, UK.
Gastone CastellaniDepartment of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40127 Bologna, Italy.
Clara AmidEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.ORCID 0000-0001-6534-7425
Mikhayil HakhverdyanNational Veterinary Institute, Ulls väg 2B, 75189 Uppsala, Sweden.ORCID 0000-0002-9481-2709
Soizick Le GuyaderLaboratoire de Microbiologie, CEDEX 03, 44311 Nantes, France.
Gerardo ManfredaDepartment of Agricultural and Food Sciences, University of Bologna, 40064 Ozzano dell'Emilia, Italy.
Jöel MossongEpidemiology and Microbial Genomics, Laboratoire National de Santé, L-3555 Dudelange, Luxembourg.
Andreas NitscheHighly Pathogenic Viruses, ZBS 1, Centre for Biological Threats and Special Pathogens, Robert Koch Institute, 13353 Berlin, Germany.
Catherine RagimbeauEpidemiology and Microbial Genomics, Laboratoire National de Santé, L-3555 Dudelange, Luxembourg.ORCID 0000-0001-7399-2379
Julien SchaefferLaboratoire de Microbiologie, CEDEX 03, 44311 Nantes, France.
Joergen SchlundtNanyang Technological University Food Technology Centre (NAFTEC), Nanyang Technological University (NTU), 62 Nanyang Dr, Singapore 637459, Singapore.
Moon Y F TayNanyang Technological University Food Technology Centre (NAFTEC), Nanyang Technological University (NTU), 62 Nanyang Dr, Singapore 637459, Singapore.
Frank M AarestrupResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kemitorvet, DK-2800 Kgs, 2800 Lyngby, Denmark.
Rene S HendriksenResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kemitorvet, DK-2800 Kgs, 2800 Lyngby, Denmark.
Sünje Johanna PampResearch Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kemitorvet, DK-2800 Kgs, 2800 Lyngby, Denmark.ORCID 0000-0002-6236-1763
Alessandra De CesareDepartment of Veterinary Medical Sciences, University of Bologna, Via Tolara di Sopra 50, 40064 Ozzano dell'Emilia, Italy.

Funding

European Commission 643476
6 · The paper itself

Abstract

An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample.

Indexed as

experimentally spiked samplesproficiency testshotgun metagenomicssmoked salmonwet-lab protocols

Identifiers

PMID33255715
PMCPMC7760972

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.