In silico, in vitro and in vivo characterization of host-associated Latilactobacillus curvatus strains for potential probiotic applications in farmed Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
Salmon aquaculture is the fastest growing animal protein production system in the world; however, intensive farming leads to poor weight gain, stress, and disease outbreaks. Probiotics offer the potential to enhance growth performance and feed efficiency in Atlantic salmon, as well as immunostimulate fish against common pathogens, benefitting farmers and consumers with more efficient production. Here, we isolated and identified 900 native microbial isolates including 18 Lactobacilli from the farmed salmon intestines. Based on whole-genome sequencing and phylogenetic analysis, the Lactobacillus candidates belonged to Latilactobacillus curvatus (L. curvatus) species and formed two distinct phylogenetic groups. Using bioinformatics and in vitro analyses, we selected two candidates L. curvatus ATCC PTA-127116 and L. curvatus ATCC PTA-127117, which showed desirable safety and probiotic properties. The two L. curvatus candidates were evaluated for safety and efficacy (higher final weight) in Atlantic salmon alongside spore-forming Bacilli isolated from salmon, poultry, and swine. All the tested candidates were safe to salmon with no adverse effects. While we did not see efficacy in any Bacillus supplemented groups, compared to untreated group, the group administered with the two L. curvatus strains consortium in feed for seven weeks in freshwater showed indicators of improvement in final body weight by 4.2%. Similarly, the two L. curvatus candidates were also evaluated for safety and efficacy in Atlantic salmon in saltwater; the group administered with the two L. curvatus strains consortium in feed for 11 weeks showed indicators of improvement in final body weight by 4.7%. Comprehensive metabolomics analyses in the presence of different prebiotics and/or additives identified galactooligosaccharide as a potential prebiotic to enhance the efficacy of two L. curvatus candidates. All together, these data provide comprehensive genomic, phenotypic and metabolomic evidence of safety and desirable probiotic properties as well as indicators of in vivo efficacy of two novel endogenous L. curvatus candidates for potential probiotic applications in Atlantic salmon. The in vivo findings need to be confirmed in larger performance studies, including field trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".