Differences in cecal microbiome of selected high and low feather-pecking laying hens

Birkl, Patrick; Bharwani, Aadil; Kjaer, Joergen; Kunze, Wolfgang; McBride, Peter; Forsythe, Paul; Harlander-Matauschek, Alexandra

doi:10.3382/ps/pey167

Cited by 40 publications

(47 citation statements)

References 38 publications

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“…Comparisons of the cecal microbiomes between layer lines divergently selected for FP or with different actual FP behavior revealed apparent differences [11][12][13]. It is difficult to determine, whether these differences are a cause for FP or just a consequence of feather consumption.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the brain transcriptome in lines of laying hens divergently selected for feather pecking

et al. 2020

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Background: Feather pecking (FP) in laying hens reduces animal welfare and leads to economic losses for the layer industry. FP is considered a heritable condition that is influenced by dysregulation of neurotransmitter homeostasis, the gut microbiome, and the immune system. To identify genes and biological pathways responsible for FP behavior we compared the brain transcriptomes of 48 hens divergently selected for FP. In addition, we tested if high feather peckers (HFP) and low feather peckers (LFP) respond differently to light since light has been shown to trigger FP behavior. Results: Of approximately 48 million reads/sample an average of 98.4% were mapped to the chicken genome (GRCg6a). We found 13,070 expressed genes in the analyzed brains of which 423 showed differential expression between HFP and LFP. Genes of uncertain function and non-coding RNAs were overrepresented among those transcripts. Functional analyses revealed the involvement of cholinergic signaling, postsynaptic activity, membrane channels, and the immune system. After the light stimulus, 28 genes were found to be differentially expressed. These included an interaction cluster of core components of the circadian clock. However, differences in the response to light between HFP and LFP were not detectable. Conclusions: Genes involved in cholinergic signaling, channel activity, synaptic transmission, and immune response were found to be involved in FP behavior. We propose a model in which the gut microbiota modulates the immune system, which in turn affects cholinergic signaling. This might have an influence on monoamine signaling with possible involvement of GABA or glutamate signaling.

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Section: Introductionmentioning

confidence: 99%

Analysis of the brain transcriptome in lines of laying hens divergently selected for feather pecking

et al. 2020

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“…Even if studies on livestock are still uncommon, they have all implicated the gut microbiota in host behavior (109)(110)(111)(112)(113). In hens, the aggressive damaging behavior of feather pecking was associated higher relative abundances of Clostridiales and a lower relative abundance of Lactobacillus in the luminal microbiota composition of ileum, caecum and colon sections combined (114,115). In humans, Parashar and Udayabanu (94) have reviewed the relationships between specific bacteria populations and both stress and anxiety.…”

Section: Streptococcus D14mentioning

confidence: 99%

Effects of Three Distinct 2-Week Long Diet Strategies After Transport on Weaned Pigs' Short and Long-Term Welfare Markers, Behaviors, and Microbiota

et al. 2020

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Alternative feed supplements have shown promising effects in terms of performance, but their effects on welfare have had little evaluation. In the present study, we aimed at evaluating the effect of diet supplementation on welfare indicators. A total of 246 piglets were weaned and transported for 12 h. After transport, they were assigned to one of 3 diets for a 14-day period: A-an antibiotic diet including chlortetracycline and tiamulin, NA-a control diet without any antibiotic or feed supplement, GLN-a diet including 0.20% L-glutamine. After the 14-day period, all piglets were fed the same diet. Tear staining was measured 11 times post-weaning (from d0 to 147). Skin lesions were counted before and after weaning (d-2, 2, and 36). Novel object tests (NOT) were done in groups 4 times post-weaning (d17, 47, 85, 111). Samples for 16S rRNA gene composition were collected prior to transport (d0), following the 14-day period (d14) and at the conclusion of the nursery phase (d34). The NA pigs appeared less interested in novel objects. On d17, they avoided the object less than A pigs (P < 0.05). They spent less time exploring the object on d85 and took longer to interact with the object on d111 than A and GLN pigs (P < 0.05). NA pigs also appeared more sensitive to environment and management. They had larger tear stains than GLN pigs on d84 and 110 (P < 0.05). On d2, NA pigs had more lesions than A and GLN (P < 0.01). In terms of microbiota composition, GLN had higher α-diversity than A and NA (P < 0.001). Differences between dietary treatments were absent at d0, were demonstrated at d14 and disappeared at d34. Pearson correlations between aggression, stress and anxiety indicators and bacterial populations were medium to high from 0.31 to 0.69. The results demonstrate that short-term feeding strategy can have both short-and long-term effects on behavior and welfare, that may partly be explained by changes in gut microbiota composition. Supplementation with GLN appears to confer similar benefits to dietary antibiotics and thus could be a viable alternative.

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“…Overall, it seems both host genetic variations and intestinal microbiota composition could explain variations in individual Salmonella Enteritidis carriage in chicken. Furthermore, genetic studies on other phenotypic traits, such as digestive e ciency [22], body weight [23] or feather-pecking in laying hens [24] showed that host genetic variations in uence the intestinal microbiota composition in chicken. In these studies, authors identi ed several QTLs and single nucleotide polymorphisms (SNPs) associated with speci c bacterial species that may explain the phenotype and calculated heritabilities of these bacteria abundances.…”

Section: Introductionmentioning

confidence: 99%

Impact of Host Genetics on Caecal Microbiota Composition and on Salmonella Carriage in Chicken

Cazals¹,

Estellé²,

Bruneau³

et al. 2020

Preprint

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Background Salmonella Enteritidis (SE) is one of the major causes of human foodborne intoxication through the consumption of contaminated poultry products. Genetic selection of animals more resistant to Salmonella carriage and the modulation of gut microbiota are two promising ways of decreasing individual Salmonella carriage. This study aims to identify the main genetic and microbial factors controlling the individual levels of Salmonella carriage in chickens (Gallus gallus) in controlled experimental conditions. Two-hundred and forty animals from the White Leghorn inbred lines, N and 61, were infected by SE at 7 days of age. After infection, animals were kept in isolators to reduce the recontamination of birds by Salmonella. Caecal contents were sampled at 12 days post-infection and used for DNA extraction. Microbiota DNA was used to measure individual counts of SE by digital PCR and to determine the bacterial taxonomic composition through a 16S rRNA gene high-throughput sequencing approach. Results Results confirmed that the N line is more resistant to Salmonella carriage than the 61 line, and that intra-line variability is higher for the 61 line. Furthermore, the 16S analysis showed strong significant differences in microbiota taxonomic composition between the two lines. Out of 617 Operational Taxonomic Units (OTUs), over 390 were differentially abundant between the two lines. Furthermore, within the 61 line, we found a difference in the microbiota taxonomic composition between high and low Salmonella carriers, with 39 differentially abundant OTUs. Finally, via metagenome functional prediction based on 16S data, we identified several metabolic pathways potentially associated to microbiota taxonomic differences (e.g. butyrate metabolism) between high and low carriers. Conclusions Overall, this study demonstrates that the caecal microbiota composition of the N and 61 lines is influenced by the host genetics, which could be one of the reasons why these lines differ for their Salmonella carriage in experimental infection conditions.

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Differences in cecal microbiome of selected high and low feather-pecking laying hens

Cited by 40 publications

References 38 publications

Analysis of the brain transcriptome in lines of laying hens divergently selected for feather pecking

Analysis of the brain transcriptome in lines of laying hens divergently selected for feather pecking

Effects of Three Distinct 2-Week Long Diet Strategies After Transport on Weaned Pigs' Short and Long-Term Welfare Markers, Behaviors, and Microbiota

Impact of Host Genetics on Caecal Microbiota Composition and on Salmonella Carriage in Chicken

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