PSVI-5 Bacteriophage biocontrol of avian pathogenic <i>Escherichia coli</i> in laying hens does not produce collateral effects on the cecal microbiota
Bibliographic record
Abstract
Abstract Bacteriophages have shown promise as an alternative to antibiotics for managing or preventing avian pathogenic Escherichia coli (APEC) in the egg industry. In a previous study, a phage cocktail comprising 3 virulent phages was shown to prevent APEC infections in laying hens. The aim of this study was to investigate whether orally and intramuscularly administered phages affect the intestinal barrier function of chickens, with a focus on cecal microbiome. In a 4-d trial, a total of 35 laying hens were randomly assigned to one of four treatment groups: 1) Medium control group (bacterial broth + phage buffer), 2) APEC only control (APEC + buffer); 3) IM group (Phage +APEC), or 4) DW group (phage in drinking water (4 d prior to APEC + APEC). Cecum samples were subjected to 16S rRNA gene sequencing targeting the V4 region to assess the effects of phages on cecal bacterial diversity. A 1-way ANOVA was used to evaluate alpha diversity with respect to treatment and time. Microbial community structure was analyzed using β-dispersion and permutational multivariate analysis of variance (PERMANOVA) to determine the effect of each treatment. Significant (P < 0.05) differentially abundant genera were identified with DESeq2 by fitting a negative binomial model to each treatment vs treatment comparison (“~Treatment”). Across the treatment and control groups, 13 phyla were identified. Firmicutes (53.81%), Bacteroidota (23.83%), Actinobacteriota (1.84%), and Proteobacteria (1.02%) were the most abundant phyla among the amplicon sequence variants (ASVs), with 18.39% being unclassified. Neither richness (P = 0.448) nor Shannon diversity (P = 0.687) exhibited significance in α- diversity metric between treatment and control groups. β-dispersion analysis showed no significant difference (P = 0.239) between treatment and control groups, indicating similar bacterial variability among groups. Moreover, the β-diversity representing microbiota structure was not affected by any phage treatment (P = 0.083). In each treatment group, 76 unique genera were identified, with Megamonas (15.80 %), Lactobacillus (8.76%), Faecalibacterium (7.70 %), Megasphaera (1.58%), Alloprevotella (1.54%), [Ruminococcus] torques group (1.29%), Prevotellaceae UCG-001 (1.14%), Bifidobacterium (1.04%), and Olsenella (0.48%) being the most abundant. Notably, Lactobacillus was more abundant (~ 10 to 20%) in medium control group compared with phage treated and APEC only treatment groups. Furthermore, gene expression profiles of various genera (pairwise) were analyzed using log2 fold change (log2FC), revealing differences (P < 0.05) between control and treatment groups for a total of 58 genera. It was concluded that bacteriophage selectively killed APEC population without comprising the population and structure of cecal microbiome in laying hens.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".