Antonie van Leeuwenhoek

, Volume 111, Issue 7, pp 1117–1129 | Cite as

The impact of depuration on mussel hepatopancreas bacteriome composition and predicted metagenome

  • J. A. RubioloEmail author
  • A. Lozano-Leon
  • R. Rodriguez-Souto
  • N. Fol Rodríguez
  • M. R. Vieytes
  • L. M. Botana
Original Paper


Due to the rapid elimination of bacteria through normal behaviour of filter feeding and excretion, the decontamination of hazardous contaminating bacteria from shellfish is performed by depuration. This process, under conditions that maximize shellfish filtering activity, is a useful method to eliminate microorganisms from bivalves. The microbiota composition in bivalves reflects that of the environment of harvesting waters, so quite different bacteriomes would be expected in shellfish collected in different locations. Bacterial accumulation within molluscan shellfish occurs primarily in the hepatopancreas. In order to assess the effect of the depuration process on these different bacteriomes, in this work we used 16S RNA pyrosequencing and metagenome prediction to assess the impact of 15 h of depuration on the whole hepatopancreas bacteriome of mussels collected in three different locations.


Mussel depuration 16S RNA sequencing Taxonomic profiling Metagenome prediction 



The research leading to these results has received funding from the following FEDER cofunded-grants. From CDTI and Technological Funds, supported by Ministerio de Economía y Competitividad, AGL2012-40185-CO2-01, AGL2014-58210-R, andConsellería de Cultura, Educación e Ordenación Universitaria, GRC2013-016, and through Axencia Galega de Innovación, Spain, ITC-20133020 SINTOX. From CDTI under ISIP Programme, Spain, IDI-20130304 APTAFOOD. From the European Union’s Seventh Framework Programme managed by REA—Research Executive Agency (FP7/2007-2013) under grant agreement 312184 PHARMASEA.

Conflict of interests

The authors declare that they have no conflict of interest.

Supplementary material

10482_2018_1015_MOESM1_ESM.pdf (69 kb)
Significant differences at the phyla level observed in D and ND samples (main graph, green bars). Graph insert shows the differences observed in the tenericutes and proteobacteria phyla, purple and pink bars respectively. [**p < 0.01, *p < 0.05, n = 3 (ND), n = 2 (D)]. Supplementary material 1 (PDF 68 kb)
10482_2018_1015_MOESM2_ESM.pdf (1.6 mb)
Networks showing OTU interactions between all rarified samples from ND (blue dots) and D samples (red dots). OTUs are represented by white dots and were grouped according on the microbiomes they were found. The lines radiating from each sample link them to their microbiome. Supplementary material 2 (PDF 1610 kb)
10482_2018_1015_MOESM3_ESM.pdf (768 kb)
a Heatmap of core OTU frequencies for all samples analyzed clustered according to the phylogenetic tree and sample condition. b Frequencies of core phyla observed before and after depuration [**p < 0.01, *p < 0.05, n = 3 (ND), n = 2 (D)]. Supplementary material 3 (PDF 768 kb)
10482_2018_1015_MOESM4_ESM.pdf (19 kb)
Supplementary material 4 (PDF 18 kb)
10482_2018_1015_MOESM5_ESM.pdf (51 kb)
Supplementary material 5 (PDF 51 kb)


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • J. A. Rubiolo
    • 1
    Email author
  • A. Lozano-Leon
    • 2
  • R. Rodriguez-Souto
    • 2
  • N. Fol Rodríguez
    • 3
  • M. R. Vieytes
    • 3
  • L. M. Botana
    • 4
  1. 1.Departamento de Zoología, Genética y Antropología FísicaUniversidad de Santiago de CompostelaLugoSpain
  2. 2.Institute of Applied Microbiology ASMECRUZBueuSpain
  3. 3.Departamento de Fisiología, Facultad de VeterinariaUniversidad de Santiago de CompostelaLugoSpain
  4. 4.Departamento de Farmacología, Facultad de VeterinariaUniversidad de Santiago de CompostelaLugoSpain

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