Characterisation of the Pacific Oyster Microbiome During a Summer Mortality Event

King, William L.; Jenkins, Cheryl; Go, Jeffrey; Siboni, Nachshon; Seymour, Justin R.; Labbate, Maurizio

doi:10.1007/s00248-018-1226-9

Cited by 82 publications

(79 citation statements)

References 48 publications

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“…The elevated abundance of Vibrio spp. in oyster beds has been recently confirmed by 16S microbiota analyses that demonstrated the implication of the Vibrio community either as infective agents or opportunistic colonizers in oyster mass mortality events (King et al, ). In our study, 50% and 30% of significantly over‐represented taxa in T4 and T7, respectively were assigned to Vibrio genera or Vibrionaceae family.…”

Section: Discussionmentioning

confidence: 84%

Host‐microbiota interactions shed light on mortality events in the striped venus clam Chamelea gallina

et al. 2019

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Mass mortalities due to disease outbreaks have recently affected a number of major taxa in marine ecosystems. Climate‐ and pollution‐induced stress may compromise host immune defenses, increasing the risk of opportunistic diseases. Despite growing evidence that mass mortality events affecting marine species worldwide are strongly influenced by the interplay of numerous environmental factors, the reductionist approaches most frequently used to investigate these factors hindered the interpretation of these multifactorial pathologies. In this study, we propose a broader approach based on the combination of RNA‐sequencing and 16S microbiota analyses to decipher the factors underlying mass mortality in the striped venus clam, Chamelea gallina, along the Adriatic coast. On one hand, gene expression profiling and functional analyses of microbial communities showed the over‐expression of several genes and molecular pathways involved in xenobiotic metabolism, suggesting potential chemical contamination in mortality sites. On the other hand, the down‐regulation of several genes involved in immune and stress response, and the over‐representation of opportunistic pathogens such as Vibrio and Photobacterium spp. indicates that these microbial species may take advantage of compromised host immune pathways and defense mechanisms that are potentially affected by chemical exposure, resulting in periodic mortality events. We propose the application of our approach to interpret and anticipate the risks inherent in the combined effects of pollutants and microbes on marine animals in today's rapidly changing environment.

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Section: Discussionmentioning

confidence: 84%

Host‐microbiota interactions shed light on mortality events in the striped venus clam Chamelea gallina

et al. 2019

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“…Alphaproteobacteria was the most abundant and active bacterial Class, comprising the largest number of metagenomic reads and metaproteomic peptide spectral matches (PSMs). The phylum Proteobacteria, which contains the Classes Alpha-, Beta-, Delta-, and Gammaproteobacteria, often dominates marine 16SrRNA microbiome datasets associated with hatcheries and shell sh [2,[28][29][30][31][32]. Gammaproteobacteria, Flavobacteriia, and Cytophagia had higher relative abundances in the metagenomic datasets compared to the metaproteomic datasets, suggesting relatively low metabolic activity.…”

Section: Discussionmentioning

confidence: 99%

“…[1]). Shifts in marine microbiomes can forecast impending disease or death in bivalves and can thus be important biomarkers for ecosystem health (e.g., [2]). The same dynamics between host and microbiome occur in commercial aquaculture, where microbiome dynamics may hold the key to understanding previously unexplained massive larval mortality events.…”

Section: Introductionmentioning

confidence: 99%

Coupled Microbiome Analyses Highlights Relative Functional Roles of Bacteria in a Bivalve Hatchery

Timmins‐Schiffman

White

Thompson³

et al. 2020

Preprint

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Background: Microbial communities are ubiquitous throughout ecosystems and are commensal with hosts across taxonomic boundaries. Environmental and species-specific microbiomes are instrumental in maintaining ecosystem and host health, respectively. The introduction of pathogenic microbes that shift microbiome community structure can lead to illness and death. Understanding the dynamics of microbiomes across a diversity of environments and hosts will help us to better understand which taxa forecast survival and which forecast mortality events. Results: We characterized the microbiome in the water of a commercial shellfish hatchery in Washington state, USA, where the hatchery has been plagued by recurring and unexplained larval mortality events. By applying the complementary methods of metagenomics and metaproteomics we were able to more fully characterize the bacterial taxa in the hatchery at high (pH 8.2) and low (pH 7.1) pH that were metabolically active versus present but not contributing metabolically. There were shifts in the taxonomy and functional profile of the microbiome between pH and over time. Based on detected metagenomic reads and metaproteomic peptide spectral matches, some taxa were more metabolically active than expected based on presence alone (Deltaproteobacteria, Alphaproteobacteria) and some were less metabolically active than expected (e.g., Betaproteobacteria, Cytophagia). There was little correlation between potential and realized metabolic function based on Gene Ontology analysis of detected genes and peptides. Conclusion: Analyzed together, the metagenomics and metaproteomics datasets reveal that a complete understanding of water quality and interactions with a microbiome require multiple data types to fully reveal the relationship between potential and realized microbiome function.

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“…Some taxonomic characteristics of pathobiomes are frequently encountered; for example, certain bacterial taxa (notably Vibrio and Photobacterium) are consistently elevated in diseased animals [55][56][57][58][59]. Patterns such as these can be uncovered through microbiome-wide association studies, where microbial consortia can be linked to disease states [60].…”

Section: More Diverse Communities Of Symbiontsmentioning

confidence: 99%

The Pathobiome in Animal and Plant Diseases

Bass

Stentiford

Wang

et al. 2019

Trends in Ecology & Evolution

257

189

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A growing awareness of the diversity and ubiquity of microbes (eukaryotes, prokaryotes, and viruses) associated with larger 'host' organisms has led to the realisation that many diseases thought to be caused by one primary agent are the result of interactions between multiple taxa and the host. Even where a primary agent can be identified, its effect is often moderated by other symbionts. Therefore, the one pathogen-one disease paradigm is shifting towards the pathobiome concept, integrating the interaction of multiple symbionts, host, and environment in a new understanding of disease aetiology. Taxonomically, pathobiomes are variable across host species, ecology, tissue type, and time. Therefore, a more functionally driven understanding of pathobiotic systems is necessary, based on gene expression, metabolic interactions, and ecological processes. Disease in a Microbe-Dominated World The pathobiome (see Glossary) concept arose from human studies in which disruption of a healthpromoting and ecologically stable gut microbiome resulted in dysbiosis: a microbiome community of low-diversity and modified metabolic state, exposing the gut to invasion by, and proliferation of, pathogenic agents [1,2]. Dysbiotic communities can subvert the immune system and lead to further deleterious effects [3]. This concept is being adopted for research into the pathology of other animals and plants because attempts to explain syndromic conditions by identifying a single pathogenic agent are often incomplete (i.e., the one pathogen-one disease paradigm is often insufficient to explain many diseases [4-6]). Pathobiomes differ from those assemblages representing healthy or 'normal' states. What is 'normal' likely encompasses a range of assemblages that need to be understood before a pathobiome can be reliably distinguished from them. There is a lack of consistency in defining 'pathobiome' in the literature, ranging from a single pathogenic agent interacting with its biotic and abiotic environments (e.g., [5]) to the effects of interacting communities of microbes on host health [7]. Our synthesis (Box 1) is based on the effects of multiple symbionts, across all domains of life, on host health. The term 'microbiome' generally excludes eukaryotes; therefore, in this review, we use the term 'symbiome' to describe the whole assemblage of associated organisms excluding the host, and 'symbiont' for individual taxa within that assemblage. This definition is concordant with an inclusive scheme of symbiosis acknowledged in [9], which ranges from neutralism (neutral effect on both partners) to mutual beneficial effects and mutual antagonistic effects, and all other possible combinations of neutral, beneficial, and antagonistic effects. The duration of the association need not necessarily be long-term, as interactions can be effective on even short timescales; great variability in duration of association is both possible and likely. This inclusive definition is not inconsistent with some previous usages of the term, and is required by the large div...

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Characterisation of the Pacific Oyster Microbiome During a Summer Mortality Event

Cited by 82 publications

References 48 publications

Host‐microbiota interactions shed light on mortality events in the striped venus clam Chamelea gallina

Host‐microbiota interactions shed light on mortality events in the striped venus clam Chamelea gallina

Coupled Microbiome Analyses Highlights Relative Functional Roles of Bacteria in a Bivalve Hatchery

The Pathobiome in Animal and Plant Diseases

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