Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx

Pacific Oyster Mortality Syndrome (POMS) affects Crassostrea gigas oysters worldwide and causes important economic losses. Disease dynamic was recently deciphered and revealed a multiple and progressive infection caused by the Ostreid herpesvirus OsHV-1 μVar, triggering an immunosuppression followed...

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Main Authors: Camille Clerissi, Julien de Lorgeril, Bruno Petton, Aude Lucasson, Jean-Michel Escoubas, Yannick Gueguen, Lionel Dégremont, Guillaume Mitta, Eve Toulza
Format: Dataset
Language:unknown
Published: 2020
Subjects:
Online Access:https://doi.org/10.3389/fmicb.2020.00311.s001
https://figshare.com/articles/Data_Sheet_1_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_docx/11905728
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spelling ftfrontimediafig:oai:figshare.com:article/11905728 2023-05-15T15:58:49+02:00 Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx Camille Clerissi Julien de Lorgeril Bruno Petton Aude Lucasson Jean-Michel Escoubas Yannick Gueguen Lionel Dégremont Guillaume Mitta Eve Toulza 2020-02-27T04:07:48Z https://doi.org/10.3389/fmicb.2020.00311.s001 https://figshare.com/articles/Data_Sheet_1_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_docx/11905728 unknown doi:10.3389/fmicb.2020.00311.s001 https://figshare.com/articles/Data_Sheet_1_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_docx/11905728 CC BY 4.0 CC-BY Microbiology Microbial Genetics Microbial Ecology Mycology holobiont microbiome metabarcoding fitness bacteria Dataset 2020 ftfrontimediafig https://doi.org/10.3389/fmicb.2020.00311.s001 2020-03-04T23:54:04Z Pacific Oyster Mortality Syndrome (POMS) affects Crassostrea gigas oysters worldwide and causes important economic losses. Disease dynamic was recently deciphered and revealed a multiple and progressive infection caused by the Ostreid herpesvirus OsHV-1 μVar, triggering an immunosuppression followed by microbiota destabilization and bacteraemia by opportunistic bacterial pathogens. However, it remains unknown if microbiota might participate to protect oysters against POMS, and if microbiota characteristics might be predictive of oyster mortalities. To tackle this issue, we transferred full-sib progenies of resistant and susceptible oyster families from hatchery to the field during a period in favor of POMS. After 5 days of transplantation, oysters from each family were either sampled for individual microbiota analyses using 16S rRNA gene-metabarcoding or transferred into facilities to record their survival using controlled condition. As expected, all oysters from susceptible families died, and all oysters from the resistant family survived. Quantification of OsHV-1 and bacteria showed that 5 days of transplantation were long enough to contaminate oysters by POMS, but not for entering the pathogenesis process. Thus, it was possible to compare microbiota characteristics between resistant and susceptible oysters families at the early steps of infection. Strikingly, we found that microbiota evenness and abundances of Cyanobacteria (Subsection III, family I), Mycoplasmataceae, Rhodobacteraceae, and Rhodospirillaceae were significantly different between resistant and susceptible oyster families. We concluded that these microbiota characteristics might predict oyster mortalities. Dataset Crassostrea gigas Pacific oyster Frontiers: Figshare Pacific
institution Open Polar
collection Frontiers: Figshare
op_collection_id ftfrontimediafig
language unknown
topic Microbiology
Microbial Genetics
Microbial Ecology
Mycology
holobiont
microbiome
metabarcoding
fitness
bacteria
spellingShingle Microbiology
Microbial Genetics
Microbial Ecology
Mycology
holobiont
microbiome
metabarcoding
fitness
bacteria
Camille Clerissi
Julien de Lorgeril
Bruno Petton
Aude Lucasson
Jean-Michel Escoubas
Yannick Gueguen
Lionel Dégremont
Guillaume Mitta
Eve Toulza
Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx
topic_facet Microbiology
Microbial Genetics
Microbial Ecology
Mycology
holobiont
microbiome
metabarcoding
fitness
bacteria
description Pacific Oyster Mortality Syndrome (POMS) affects Crassostrea gigas oysters worldwide and causes important economic losses. Disease dynamic was recently deciphered and revealed a multiple and progressive infection caused by the Ostreid herpesvirus OsHV-1 μVar, triggering an immunosuppression followed by microbiota destabilization and bacteraemia by opportunistic bacterial pathogens. However, it remains unknown if microbiota might participate to protect oysters against POMS, and if microbiota characteristics might be predictive of oyster mortalities. To tackle this issue, we transferred full-sib progenies of resistant and susceptible oyster families from hatchery to the field during a period in favor of POMS. After 5 days of transplantation, oysters from each family were either sampled for individual microbiota analyses using 16S rRNA gene-metabarcoding or transferred into facilities to record their survival using controlled condition. As expected, all oysters from susceptible families died, and all oysters from the resistant family survived. Quantification of OsHV-1 and bacteria showed that 5 days of transplantation were long enough to contaminate oysters by POMS, but not for entering the pathogenesis process. Thus, it was possible to compare microbiota characteristics between resistant and susceptible oysters families at the early steps of infection. Strikingly, we found that microbiota evenness and abundances of Cyanobacteria (Subsection III, family I), Mycoplasmataceae, Rhodobacteraceae, and Rhodospirillaceae were significantly different between resistant and susceptible oyster families. We concluded that these microbiota characteristics might predict oyster mortalities.
format Dataset
author Camille Clerissi
Julien de Lorgeril
Bruno Petton
Aude Lucasson
Jean-Michel Escoubas
Yannick Gueguen
Lionel Dégremont
Guillaume Mitta
Eve Toulza
author_facet Camille Clerissi
Julien de Lorgeril
Bruno Petton
Aude Lucasson
Jean-Michel Escoubas
Yannick Gueguen
Lionel Dégremont
Guillaume Mitta
Eve Toulza
author_sort Camille Clerissi
title Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx
title_short Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx
title_full Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx
title_fullStr Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx
title_full_unstemmed Data_Sheet_1_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.docx
title_sort data_sheet_1_microbiota composition and evenness predict survival rate of oysters confronted to pacific oyster mortality syndrome.docx
publishDate 2020
url https://doi.org/10.3389/fmicb.2020.00311.s001
https://figshare.com/articles/Data_Sheet_1_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_docx/11905728
geographic Pacific
geographic_facet Pacific
genre Crassostrea gigas
Pacific oyster
genre_facet Crassostrea gigas
Pacific oyster
op_relation doi:10.3389/fmicb.2020.00311.s001
https://figshare.com/articles/Data_Sheet_1_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_docx/11905728
op_rights CC BY 4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.3389/fmicb.2020.00311.s001
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