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Record W4391654086 · doi:10.1128/spectrum.02943-23

Characterization of gill bacterial microbiota in wild Arctic char ( <i>Salvelinus alpinus</i> ) across lakes, rivers, and bays in the Canadian Arctic ecosystems

2024· article· en· W4391654086 on OpenAlexafffundabout
Flora Amill, Jeff Gauthier, Milla Rautio, Nicolas Derôme

Bibliographic record

VenueMicrobiology Spectrum · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsUniversité du Québec à ChicoutimiUniversité Laval
FundersCanada First Research Excellence FundSentinelle Nord, Université LavalPolar Knowledge CanadaGenome CanadaUniversité Laval
KeywordsArctic charSalvelinusArcticEcologyBiologyPermafrostFisheryTrout

Abstract

fetched live from OpenAlex

ABSTRACT Teleost gill mucus has a highly diverse microbiota, which plays an essential role in the host’s fitness and is greatly influenced by the environment. Arctic char ( Salvelinus alpinus ), a salmonid well adapted to northern conditions, faces multiple stressors in the Arctic, including water chemistry modifications, that could negatively impact the gill microbiota dynamics related to the host’s health. In the context of increasing environmental disturbances, we aimed to characterize the taxonomic distribution of transcriptionally active taxa within the bacterial gill microbiota of Arctic char in the Canadian Arctic in order to identify active bacterial composition that correlates with environmental factors. For this purpose, a total of 140 adult anadromous individuals were collected from rivers, lakes, and bays belonging to five Inuit communities located in four distinct hydrologic basins in the Canadian Arctic (Nunavut and Nunavik) during spring (May) and autumn (August). Various environmental factors were collected, including latitudes, water and air temperatures, oxygen concentration, pH, dissolved organic carbon (DOC), salinity, and chlorophyll-a concentration. The taxonomic distribution of transcriptionally active taxa within the gill microbiota was quantified by 16S rRNA gene transcripts sequencing. The results showed differential bacterial activity between the different geographical locations, explained by latitude, salinity, and, to a lesser extent, air temperature. Network analysis allowed the detection of a potential dysbiosis signature (i.e., bacterial imbalance) in fish gill microbiota from Duquet Lake in the Hudson Strait and the system Five Mile Inlet connected to the Hudson Bay, both showing the lowest alpha diversity and connectivity between taxa. IMPORTANCE This paper aims to decipher the complex relationship between Arctic char ( Salvelinus alpinus ) and its symbiotic microbial consortium in gills. This salmonid is widespread in the Canadian Arctic and is the main protein and polyunsaturated fatty acids source for Inuit people. The influence of environmental parameters on gill microbiota in wild populations remains poorly understood. However, assessing the Arctic char’s active gill bacterial community is essential to look for potential pathogens or dysbiosis that could threaten wild populations. Here, we concluded that Arctic char gill microbiota was mainly influenced by latitude and air temperature, the latter being correlated with water temperature. In addition, a dysbiosis signature detected in gill microbiota was potentially associated with poor fish health status recorded in these disturbed environments. With those results, we hypothesized that rapid climate change and increasing anthropic activities in the Arctic might profoundly disturb Arctic char gill microbiota, affecting their survival.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.206
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes3
Has abstractyes

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