Temporal changes in skin and gill microbiomes of Atlantic salmon in a recirculating aquaculture system – Why do they matter?

Lorgen-Ritchie, Marlene; Clarkson, Michael; Chalmers, Lynn; Taylor, John F.; Migaud, Hervé; Martín, Samuel

doi:10.1016/j.aquaculture.2022.738352

Cited by 17 publications

(7 citation statements)

References 54 publications

(96 reference statements)

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“…Our results indicate that overall, 12% of beta diversity was explained by fish culturing systems in fresh and also within saltwater conditions. This supports previous studies indicating that different aquaculture environments can result in different fish microbiome community structures (Minich et al 2020b , Lorgen-Ritchie et al 2022 ). Skin microbiomes in fish held in flow-through aquaculture systems differed most from all other types of fish cultivation systems (RAS, wild-caught, and outdoor aquaculture), with RAS systems more closely resembling fish captured from the wild or from aquaculture environments, which were broadly similar.…”

Section: Discussionsupporting

confidence: 92%

“…Other factors, therefore, relating their maintenance or other aspects of water chemistry must play a role in determining fish skin microbiome community composition. These factors likely include salmon genetics (seed stocks), water microbiota, husbandry practice, life history and/or diet (Minniti et al 2017 , Bledsoe et al 2022 , Lorgen-Ritchie et al 2022 ). Our analysis on the effect of water temperature on the skin microbiome in Atlantic salmon was extremely limited due to the available data but nevertheless the indication from that analysis was for water temperature associated changes in the abundance of 69 genera of bacteria in Atlantic salmon skin microbiomes.…”

Section: Discussionmentioning

confidence: 99%

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Influence of host phylogeny and water physicochemistry on microbial assemblages of the fish skin microbiome

Bell,

McMurtrie,

Bolaños

et al. 2024

FEMS Microbiology Ecology

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The skin of fish contains a diverse microbiota that has symbiotic functions with the host, facilitating pathogen exclusion, immune system priming and nutrient degradation. The composition of fish skin microbiomes varies across species and in response to a variety of stressors, however, there has been no systematic analysis across these studies to evaluate how these factors shape fish skin microbiomes. Here, we examined 1922 fish skin microbiomes from 36 studies that included 98 species and nine rearing conditions to investigate associations between fish skin microbiome, fish species, and water physiochemical factors. Proteobacteria, particularly the class Gammaproteobacteria, were present in all marine and freshwater fish skin microbiomes. Acinetobacter, Aeromonas, Ralstonia, Sphingomonas and Flavobacterium were the most abundant genera within freshwater fish skin microbiomes, and Alteromonas, Photobacterium, Pseudoalteromonas, Psychrobacter and Vibrio were the most abundant in saltwater fish. Our results show that different culturing (rearing) environments have a small but significant effect on the skin bacterial community compositions. Water temperature, pH, dissolved oxygen concentration and salinity significantly correlated with differences in beta-diversity but not necessarily alpha-diversity. To improve study comparability on fish skin microbiomes, we provide recommendations for approaches to the analyses of sequencing data and improve study reproducibility.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Influence of host phylogeny and water physicochemistry on microbial assemblages of the fish skin microbiome

Bell,

McMurtrie,

Bolaños

et al. 2024

FEMS Microbiology Ecology

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“…The best DISTLM model explained 21.7% of the variation in bacterial community and showed that, as well as fish sex, community membership covaried significantly with the date on which the trial was conducted ( pseudo-F = 1.88, p = 0.001), as has been shown previously [65][66][67]. Among females, community membership covaried with activity level ( pseudo-F = 1.42, p = 0.034).…”

Section: (B) Activity Levelsupporting

confidence: 65%

“…For example, we co-housed fish from birth until adulthood, and group-level factors may have affected the behaviour and microbiome of our test fish [75]. We also found that both behaviour and the microbiome (as has been shown previously [65][66][67]) changed over the weeks during which we collected data (see electronic supplementary material).…”

Section: Discussionmentioning

confidence: 57%

Skin bacterial microbiome diversity predicts lower activity levels in female, but not male, guppies,Poecilia reticulata

2022

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While the link between the gut microbiome and host behaviour is well established, how the microbiomes of other organs correlate with behaviour remains unclear. Additionally, behaviour–microbiome correlations are likely sex-specific because of sex differences in behaviour and physiology, but this is rarely tested. Here, we tested whether the skin microbiome of the Trinidadian guppy, Poecilia reticulata , predicts fish activity level and shoaling tendency in a sex-specific manner. High-throughput sequencing revealed that the bacterial community richness on the skin (Faith's phylogenetic diversity) was correlated with both behaviours differently between males and females. Females with richer skin-associated bacterial communities spent less time actively swimming. Activity level was significantly correlated with community membership (unweighted UniFrac), with the relative abundances of 16 bacterial taxa significantly negatively correlated with activity level. We found no association between skin microbiome and behaviours among male fish. This sex-specific relationship between the skin microbiome and host behaviour may indicate sex-specific physiological interactions with the skin microbiome. More broadly, sex specificity in host–microbiome interactions could give insight into the forces shaping the microbiome and its role in the evolutionary ecology of the host.

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“…Flavobacterial diseases in fish are caused by multiple bacterial species within the genus Flavobacterium and are responsible for devastating losses in wild and farmed fish stock worldwide [81]- [83]. Finally, Hydrogenophaga is a group of hydrogenoxidizing bacteria that perform denitrification services [84]. The identified biofilm-enriched genera have previously been implicated in nutrient-recycling processes.…”

Section: Community Compositionmentioning

confidence: 99%

Metagenomics and metabarcoding experimental choices and their impact on microbial community characterization in freshwater recirculating aquaculture systems

Rieder

Kapopoulou

Bank

et al. 2022

Preprint

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Recirculating aquaculture systems (RAS) heavily depend on microbial communities to maintain water quality. These communities therefore influence the growth, development, and welfare of farmed fish. With the increasing socio-economic role of fish farming e.g. regarding food security, an in-depth understanding of aquaculture microbial communities is also relevant from a management perspective. However, the data situation regarding the composition of microbial communities within RAS is patchy. Since this is partly ascribed to method choices, there clearly is a need for accurate, standardized, and user-friendly methods to study microbial communities in aquaculture systems.Here, we compare the performance of 16S amplicon sequencing, Pac-Bio long-read amplicon sequencing, and amplification-free shotgun metagenomics in the characterization of microbial communities in two commercial-size RAS fish farms. We show that, even though primer choice affects read quality, diversity, and assigned taxa, distinct primer pairs uncover similar spatio-temporal patterns between sample types, farms, and time points. We find that long-read amplicons underperform regarding quantitative resolution of spatio-temporal patterns, but allow for species-level identification of functional services and pathogens. Finally, shotgun metagenomics data identified fungi, viruses, and bacteriophages, opening avenues for an exploration of natural approaches regarding antipathogenic treatments. Overall, the datasets agreed on major prokaryotic players.In conclusion, different sequencing approaches yield overlapping and highly complementary results, with each contributing data no other approach could. Such a tiered approach therefore constitutes a practical and cost-effective strategy for obtaining the maximum amount of information on aquaculture microbial communities. These data could lead to better farm management practices and at the same time inform basic research on community evolution dynamics.

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Temporal changes in skin and gill microbiomes of Atlantic salmon in a recirculating aquaculture system – Why do they matter?

Cited by 17 publications

References 54 publications

Influence of host phylogeny and water physicochemistry on microbial assemblages of the fish skin microbiome

Influence of host phylogeny and water physicochemistry on microbial assemblages of the fish skin microbiome

Skin bacterial microbiome diversity predicts lower activity levels in female, but not male, guppies,Poecilia reticulata

Metagenomics and metabarcoding experimental choices and their impact on microbial community characterization in freshwater recirculating aquaculture systems

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