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Title: Metagenomics-based proficiency test of smoked salmon spiked with a mock community
Authors: Sala, Claudia
Mordhorst, Hanne
Grützke, Josephine
Brinkmann, Annika
Petersen, Thomas N.
Poulsen, Casper
Cotter, Paul D.
Crispie, Fiona
Ellis, Richard J.
Castellani, Gastone
Amid, Clara
Hakhverdyan, Mikhayil
Guyader, Soizick Le
Manfreda, Gerardo
Mossong, Jöel
Nitsche, Andreas
Ragimbeau, Catherine
Schaeffer, Julien
Schlundt, Joergen
Tay, Moon Yue Feng
Aarestrup, Frank M.
Hendriksen, Rene S.
Pamp, Sünje Johanna
De Cesare, Alessandra
Keywords: Science::Biological sciences
Issue Date: 2020
Source: Sala, C., Mordhorst, H., Grützke, J., Brinkmann, A., Petersen, T. N., Poulsen, C., . . . De Cesare, A. (2020). Metagenomics-based proficiency test of smoked salmon spiked with a mock community. Microorganisms, 8(12), 1861-. doi:10.3390/microorganisms8121861
Journal: Microorganisms 
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.
ISSN: 2076-2607
DOI: 10.3390/microorganisms8121861
Schools: School of Chemical and Biomedical Engineering 
Research Centres: NTU Food Technology Centre 
Rights: © 2020 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

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