(2020). Oyster hemolymph is a complex and dynamic ecosystem hosting bacteria, protists and viruses. Animal Microbiome. 2 (1). 12 (16p.). https://doi.org/10.1186/s42523-020-00032-w, https://archimer.ifremer.fr/doc/00627/73916/
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Oyster hemolymph is a complex and dynamic ecosystem hosting bacteria, protists and viruses
Background
The impact of the microbiota on host fitness has so far mainly been demonstrated for the bacterial microbiome. We know much less about host-associated protist and viral communities, largely due to technical issues. However, all microorganisms within a microbiome potentially interact with each other as well as with the host and the environment, therefore likely affecting the host health.
Results
We set out to explore how environmental and host factors shape the composition and diversity of bacterial, protist and viral microbial communities in the Pacific oyster hemolymph, both in health and disease. To do so, five oyster families differing in susceptibility to the Pacific oyster mortality syndrome were reared in hatchery and transplanted into a natural environment either before or during a disease outbreak. Using metabarcoding and shotgun metagenomics, we demonstrate that hemolymph can be considered as an ecological niche hosting bacterial, protist and viral communities, each of them shaped by different factors and distinct from the corresponding communities in the surrounding seawater. Overall, we found that hemolymph microbiota is more strongly shaped by the environment than by host genetic background. Co-occurrence network analyses suggest a disruption of the microbial network after transplantation into natural environment during both non-infectious and infectious periods. Whereas we could not identify a common microbial community signature for healthy animals, OsHV-1 μVar virus dominated the hemolymph virome during the disease outbreak, without significant modifications of other microbiota components.
Conclusion
Our study shows that oyster hemolymph is a complex ecosystem containing diverse bacteria, protists and viruses, whose composition and dynamics are primarily determined by the environment. However, all of these are also shaped by oyster genetic backgrounds, indicating they indeed interact with the oyster host and are therefore not only of transient character. Although it seems that the three microbiome components respond independently to environmental conditions, better characterization of hemolymph-associated viruses could change this picture.
Keyword(s)
Oyster genetic background, Hemolymph microbiota dynamics, Early-life microbiota, Trans-kingdom interactions, Crassostrea gigas, Within-host ecosystem
Full Text
| File | Pages | Size | Access | |
|---|---|---|---|---|
Publisher's official version | 16 | 2 Mo | ||
Additional file 1: Table S1. Overview of specificity of primers used to amplify V1-V2 region of 18S rRNA genes. | - | 49 Ko | ||
Additional file 2: Table S2. Bacteria OUT table with sequence tag count per sample and taxonomic affiliations. | - | 5 Mo | ||
Additional file 3: Table S3. Protist OUT table with sequence tag count per sample and taxonomic affiliations. | - | 521 Ko | ||
Additional file 4: Table S 4. Viral contig table with sequence tag count per sample and taxonomic affiliations. | - | 13 Mo | ||
Additional file 5: Figure S1. Sample rarefaction curves of alpha diversity indices for bacterial (a) and protists (b) datasets. | - | 995 Ko | ||
Additional file 6: Table S5. Orthogonal contrasts used to examine the differences between the oyster families. | - | 14 Ko | ||
Additional file 7: Table S6. Indicator taxa for the oyster environment, family origin and phenotype. | - | 173 Ko | ||
Additional file 8: Table S7. Generalized least squares by maximum likelihood linear models testing for differences in alpha diversity between the seawater and hemolymph microbiota within each environm | - | 16 Ko | ||
Additional file 9: Table S8. Generalized least squares by maximum likelihood linear models testing for differences in alpha diversity between the families in the hatchery. | - | 14 Ko | ||
Additional file 10: Table S9. Permanova based on Bray-Curtis dissimilarities testing for differences in beta diversity between the families in the hatchery. | - | 12 Ko | ||
Additional file 11: Table S10. Linear mixed-effects models testing for effects of the environment, genitors’ origin, selection pressure and their interactions on alpha diversity. | - | 18 Ko | ||
Additional file 12: Table S11. Permanova based on Bray-Curtis dissimilarities testing for effects of the environment, genitors’ origin and selection pressure and their interactions on beta diversity. | - | 13 Ko | ||
Additional file 13: Table 12. Permanova based on Bray-Curtis dissimilarities testing for differences in beta diversity between the families in the infectious environment. | - | 12 Ko |
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