bg image

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

  • accueil
  • Publications
  • Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community
Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community
2020 11-25

Authors: Sala C, Mordhorst H, Grützke J, Brinkmann A, Petersen TN, Poulsen C, Cotter PD, Crispie F, Ellis RJ, Castellani G, Amid C, Hakhverdyan M, Le Guyader S, Manfreda G, Mossong J, Nitsche A, Ragimbeau C, Schaeffer J, Schlundt J, Tay MYF, Aarestrup FM, Hendriksen RS, Pamp SJ, De Cesare A

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