Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX
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...
Main Authors: | , , , , , , , , |
---|---|
Format: | Dataset |
Language: | unknown |
Published: |
2020
|
Subjects: | |
Online Access: | https://doi.org/10.3389/fmicb.2020.00311.s008 https://figshare.com/articles/Table_4_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_XLSX/11905752 |
id |
ftfrontimediafig:oai:figshare.com:article/11905752 |
---|---|
record_format |
openpolar |
spelling |
ftfrontimediafig:oai:figshare.com:article/11905752 2023-05-15T15:58:49+02:00 Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX Camille Clerissi Julien de Lorgeril Bruno Petton Aude Lucasson Jean-Michel Escoubas Yannick Gueguen Lionel Dégremont Guillaume Mitta Eve Toulza 2020-02-27T04:07:50Z https://doi.org/10.3389/fmicb.2020.00311.s008 https://figshare.com/articles/Table_4_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_XLSX/11905752 unknown doi:10.3389/fmicb.2020.00311.s008 https://figshare.com/articles/Table_4_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_XLSX/11905752 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.s008 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 Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX |
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 |
Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX |
title_short |
Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX |
title_full |
Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX |
title_fullStr |
Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX |
title_full_unstemmed |
Table_4_Microbiota Composition and Evenness Predict Survival Rate of Oysters Confronted to Pacific Oyster Mortality Syndrome.XLSX |
title_sort |
table_4_microbiota composition and evenness predict survival rate of oysters confronted to pacific oyster mortality syndrome.xlsx |
publishDate |
2020 |
url |
https://doi.org/10.3389/fmicb.2020.00311.s008 https://figshare.com/articles/Table_4_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_XLSX/11905752 |
geographic |
Pacific |
geographic_facet |
Pacific |
genre |
Crassostrea gigas Pacific oyster |
genre_facet |
Crassostrea gigas Pacific oyster |
op_relation |
doi:10.3389/fmicb.2020.00311.s008 https://figshare.com/articles/Table_4_Microbiota_Composition_and_Evenness_Predict_Survival_Rate_of_Oysters_Confronted_to_Pacific_Oyster_Mortality_Syndrome_XLSX/11905752 |
op_rights |
CC BY 4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.3389/fmicb.2020.00311.s008 |
_version_ |
1766394581309456384 |