Ileal microbial composition in genetically distinct chicken lines reared under normal or high ambient temperatures
Bibliographic record
Abstract
BACKGROUND: Heat stress (HS) has negative effects on poultry productivity, health and welfare resulting in economic losses. Broiler chickens are particularly susceptible to HS due to their high metabolic rate and rapid growth. The commensal intestinal bacterial populations have an important physiological role in the host and could ameliorate the negative effect of HS on the host. Thus, the aim of this study was to compare changes in the ileal (IL) microbiota in four different broiler lines during HS. RESULTS: Day-old broiler chicks from Giant Jungle Fowl (JF), Athens Canadian Random Bred (ACRB), 1995 Random Bred (L1995), and Modern Random Bred (L2015) lines were raised under thermoneutral (TN) conditions until day (d) 28. On d 29 birds were subjected to TN (24 °C) or chronic cyclic HS (8 h/d, 36 °C) condition till d 56. On d 56 two birds per pen were euthanized, and IL luminal content (IL-L) and mucosal scrapings (IL-M) were collected for bacterial DNA isolation. Libraries were constructed using V3-V4 16S rRNA primers and sequenced using MiSeq. DNA sequences were analyzed using QIIME2 platform and SILVA 132 database for alpha and beta diversity, and taxonomic composition, respectively. Functional property of microbiota was predicted using the PICRUSt 2 pipeline and illustrated with STAMP software. Shannon index was significantly elevated in IL-M under HS. β-diversity PCoA plots revealed separation of microbial community of L2015-TN from JF-TN, JF-HS, ACRB-TN, and ACRB-HS in the IL-M. PERMANOVA analysis showed a significant difference between microbial community of L1995-HS compared to ACRB-HS and JF-TN, L1995-TN compared to ACRB-HS and JF-TN, L2015-HS compared to ACRB-HS and ACRB-TN, L2015-HS compared to JF-TN, L2015-TN compared to ACRB-HS and JF-TN, and ACRB-HS compared to JF-TN in the IL-L. The impact of HS on microbial composition of IL-M was more prominent compared to IL-L with 12 and 2 taxa showing significantly different relative abundance, respectively. Furthermore, differences in microbiota due to the genetic line were more prominent in IL-M than IL-L with 18 and 8 taxa showing significantly different relative abundance, respectively. Unlike taxonomy, predicted function of microbiota was not affected by HS. Comparison of L2015 with JF or ACRB showed significant changes in predicted function of microbiota in both, IL-M and IL-L. Differences were most prominent between L2015 and JF; while there was no difference between L2015 and L1995. CONCLUSIONS: These data indicate the genetic line × temperature effect on the diversity and composition of IL microbiota. Moreover, the data showcase the effect of host genetics on the composition of IL microbiota and their predicted function. These data are of critical importance for devising nutritional strategies to maintain GIT microbial balance and alleviate the negative effects of HS on broiler chickens' performance and 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 | 0.001 | 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".