Gut microbiota shift in layer pullets fed on black soldier fly larvae-based feeds towards enhancing healthy gut microbial community
Bibliographic record
Abstract
Globally, most gut microbiota-related studies have focused on broilers due to their diverse microbial communities compared to that of layer chicken. However, in Africa few studies have been undertaken despite the increasing benefits to the poultry industry. The utilization of Insect-Based diets to improve the gastrointestinal function and gut health in poultry is increasingly gaining global attention. Here, we evaluated the potential roles of commercial black soldier fly larvae-based feeds (BSFLF) in reshaping the abundance, composition and diversity of the gut microbiota of layer chickens using high throughput Oxford nanopore Minion sequencing of the full length bacterial 16S rRNA gene. Two hundred and fifty ISA Brown layer chicks were reared in pens for a period of 20 weeks. The layer pullets were allotted 5 dietary treatments that were formulated as follows: control diet (T1): 100% FM + 0% BSFL, T2: 25% BSFL + 75% FM; T3: 50% BSFL + 50% FM; T4: 75% BSFL + 25% FM, and T5: 100% BSFL + 0% FM. Sampling was done from the eight major regions including oesophagus, crop, proventriculus, gizzard, duodenum, ileum, large intestines and ceca. Out of the 400,064 classified reads analyzed, the most dominant phyla identified across the feed treatments were Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria. The diet treatment with 100% inclusion levels of BSFL showed the highest intra-species alpha diversity and richness according to Chao1 and Shannon index. Intra-species beta diversity assessment revealed that the diet types significantly influenced the abundance of the microbiota, but differences between most abundant taxa were similar. There was increase in abundance of potentially beneficial bacteria (Lactobacillus, Bacteroides and Enterococcus) with increased inclusion levels of BSFLF in layer pullets diets. Across the different gut segments, Lactobacillus dominated all the eight regions and the ceca was the most diverse segment. Our findings unravel complex gut microbial shift in laying hen fed BSFLF and therefore underpins the potential roles of beneficial bacteria as promising prebiotics and probiotics in reshaping of the gut microbiota to maintain good gut health.
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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 | 0.001 |
| 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".