Dataset Information

Fast and Slow-Growing Management Systems: Characterisation of Broiler Caecal Microbiota Development throughout the Growing Period.

ABSTRACT: Caecal microbiota and its modulation play an important role in poultry health, productivity and disease control. Moreover, due to the emergence of antimicrobial-resistant bacteria, society is pressing for a reduction in antibiotic administration by finding effective alternatives at farm level, such as less intensified production systems. Hence, the aim of this study was to characterise the caecal microbiota in two different broiler management systems, fast and slow-growing, using 16S rRNA sequencing analysis. To this end 576 broilers were reared in two different management systems (fast and slow-growing). Results showed that Firmicutes represented the dominant phylum for both systems. At the onset, Proteobacteria was the second prevalent phylum for fast and slow-growing breeds, outnumbering the Bacteroidetes. However, during the rest of the production cycle, Bacteroidetes was more abundant than Proteobacteria in both groups. Finally, regardless of the management system, the most predominant genera identified were Oscillospira spp., Ruminococcus spp., Coprococcus spp., Lactobacillus spp. and Bacteroides spp. In conclusion, fast and slow-growing broiler microbiota are in constant development throughout rearing, being relatively stable at 21 days of age. Regarding the genus, it should be noted that the three most abundant groups for both systems, Ruminococcus spp., Lactobacillus spp. and Bacteroides spp., are related to better productive performance and intestinal health.

SUBMITTER: Montoro-Dasi L

PROVIDER: S-EPMC7459849 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Fast and Slow-Growing Management Systems: Characterisation of Broiler Caecal Microbiota Development throughout the Growing Period.

Montoro-Dasi Laura L Villagra Arantxa A de Toro María M Pérez-Gracia María Teresa MT Vega Santiago S Marin Clara C

Animals : an open access journal from MDPI 20200812 8

Caecal microbiota and its modulation play an important role in poultry health, productivity and disease control. Moreover, due to the emergence of antimicrobial-resistant bacteria, society is pressing for a reduction in antibiotic administration by finding effective alternatives at farm level, such as less intensified production systems. Hence, the aim of this study was to characterise the caecal microbiota in two different broiler management systems, fast and slow-growing, using 16S rRNA sequen ...[more]

PMID: 32806542

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Project description:The development of the caecal microbiota plays a role in the metabolism and immune competence of chickens. A detailed understanding of normal succession in the caecal microbiota can inform the use of probiotics and other interventions to optimize the caecal microbiota. The development of the microbiota in caecal mucus and lumen samples from three breeds of broiler chicken (Cobb 500, n = 36; Hubbard JA87, n = 38; and Ross 308, n = 36) was observed between 0 and 42 days post hatch. Chicks were housed in the same room of a climate-controlled, biosecure chicken housing unit. Between 0 and 14 days post hatch, chicks were kept in brooder pens ensuring a mixture of breeds in each brooder. From 22 days post hatch, chicks were removed from the brooders and kept in the same room. DNA was extracted from a pooled sample of caecal mucus and luminal contents from five birds of each breed at 0, 3, 7, 14, 21, 28, and 42 days post hatch. High-throughput Illumina sequencing was performed for the V4 hypervariable region of the 16S rRNA gene. The early caecal microbiota was characterized by poor diversity and dominance by one or two bacterial species. Early colonizers of the caecum included Bifidobacteriaceae, Lachnospiraceae, Bacteroidaceae and Burkholderiaceae with some amplicon sequence variants (ASVs) assigned to Ruminococcaceae. Later colonizers of the caecal microbiota were most apparent from 14 d.p.h and included Ruminococcaceae, Clostridiales vadin BB60 group, Christensenellaceae and Bacillaceae. The caecal microbiota continued to change until 42 d.p.h when the microbiota was characterized by a high abundance of Bacteroidaceae, Lachnospiraceae and Ruminococcaceae. The lumen microbiota was significantly different to the mucus with some ASVs assigned to Lachnospiraceae, Ruminococcaceae, Christensenellaceae and Bacillaceae showing increased abundance in the mucus. ASVs assigned to Bacteroidaceae, Lactobacillaceae and Burkholderiaceae showed a preference for the lumen. Analysis of five caecal mucus samples from each breed at 42 days post hatch showed differences in microbiota composition between Ross and Cobb as well as between Ross and Hubbard. Since performance data was not collected no functional inferences as to the significance of this finding can be made.

Project description:BACKGROUND:Diverse microbial communities colonizing the intestine of fish contribute to their growth, digestion, nutrition, and immune function. We hypothesized that fecal samples representing the gut microbiota of rainbow trout could be associated with differential growth rates observed in fish breeding programs. If true, harnessing the functionality of this microbiota can improve the profitability of aquaculture. The first objective of this study was to test this hypothesis if gut microbiota is associated with fish growth rate (body weight). Four full-sibling families were stocked in the same tank and fed an identical diet. Two fast-growing and two slow-growing fish were selected from each family for 16S rRNA microbiota profiling. Microbiota diversity varies with different DNA extraction methods. The second objective of this study was to compare the effects of five commonly used DNA extraction methods on the microbiota profiling and to determine the most appropriate extraction method for this study. These methods were Promega-Maxwell, Phenol-chloroform, MO-BIO, Qiagen-Blood/Tissue, and Qiagen-Stool. Methods were compared according to DNA integrity, cost, feasibility and inter-sample variation based on non-metric multidimensional scaling ordination (nMDS) clusters. RESULTS:Differences in DNA extraction methods resulted in significant variation in the identification of bacteria that compose the gut microbiota. Promega-Maxwell had the lowest inter-sample variation and was therefore used for the subsequent analyses. Beta diversity of the bacterial communities showed significant variation between breeding families but not between the fast- and slow-growing fish. However, an indicator analysis determined that cellulose, amylose degrading and amino acid fermenting bacteria (Clostridium, Leptotrichia, and Peptostreptococcus) are indicator taxa of the fast-growing fish. In contrary, pathogenic bacteria (Corynebacterium and Paeniclostridium) were identified as indicator taxa for the slow-growing fish. CONCLUSION:DNA extraction methodology should be carefully considered for accurate profiling of the gut microbiota. Although the microbiota was not significantly different between the fast- and slow-growing fish groups, some bacterial taxa with functional implications were indicative of fish growth rate. Further studies are warranted to explore how bacteria are transmitted and potential usage of the indicator bacteria of fast-growing fish for development of probiotics that may improve fish health and growth.

Project description:High temperature is one of the prominent environmental factors causing economic losses to the poultry industry as it negatively affects growth and production performance in broiler chickens. We used One Step TaqMan real time RT-PCR (reverse transcription polymerase chain reaction) technology to study the effects of chronic heat stress on the expression of genes codifying for the antioxidative enzymes superoxide dismutase (SOD), and catalase (CAT), as well as for heat shock protein (HSP) 70, HSP90, glucocorticoid receptor (NR3C1), and caspase 6 (CASP6) in the liver of two different broiler genetic strains: Red JA Cou Nu Hubbard (CN) and Ross 508 Aviagen (RO). CN is a naked neck slow growing broiler intended for the free range and/or organic markets, whereas RO is selected for fast growing. We also analysed the effect of chronic heat stress on productive performances, and plasma corticosterone levels as well as the association between transcriptomic response and specific SNPs (single nucleotide polymorphisms) in each genetic strain of broiler chickens. RO and CN broilers, 4 weeks of age, were maintained for 4 weeks at either 34 °C or 22 °C. The results demonstrated that there was a genotype and a temperature main effect on the broilers' growth from the 4th to the 8th week of age, but the interaction effect between genotype and temperature resulted not statistically significant. By considering the genotype effect, fast growing broilers (RO) grew more than the slow growing ones (CN), whereas by considering the temperature effect, broilers in unheated conditions grew more than the heat stressed ones. Corticosterone levels increased significantly in the blood of heat stressed broilers, due to the activation of the HPA (hypothalamic-pituitary-adrenocortical axis). Carcass yield at slaughter was of similar values in the 4 cohorts (genotype/temperature combinations or treatment groups), ranging from 86.5 to 88.6%, whereas carcass weight was negatively influenced by heat stress in both broiler strains. Heat stress affected gene expression by downregulating CASP6 and upregulating CAT transcript levels. HSPs, SOD and NR3C1 mRNA levels remained unaffected by heat stress. The differences found in the mRNA copies of CASP6 gene could be partly explained by SNPs.

Project description:IntroductionGrowth traits are important in poultry production, however, little is known for its regulatory mechanism at epigenetic level. Therefore, in this study, we aim to compare DNA methylation profiles between fast- and slow-growing broilers in order to identify candidate genes for chicken growth. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) was used to investigate the genome-wide DNA methylation pattern in high and low tails of Recessive White Rock (WRR(h); WRR(l)) and that of Xinhua Chickens (XH(h); XH(l)) at 7 weeks of age. The results showed that the average methylation density was the lowest in CGIs followed by promoters. Within the gene body, the methylation density of introns was higher than that of UTRs and exons. Moreover, different methylation levels were observed in different repeat types with the highest in LINE/CR1. Methylated CGIs were prominently distributed in the intergenic regions and were enriched in the size ranging 200-300 bp. In total 13,294 methylated genes were found in four samples, including 4,085 differentially methylated genes of WRR(h) Vs. WRR(l), 5,599 of XH(h) Vs. XH(l), 4,204 of WRR(h) Vs. XH(h), as well as 7,301 of WRR(l) Vs. XH(l). Moreover, 132 differentially methylated genes related to growth and metabolism were observed in both inner contrasts (WRR(h) Vs. WRR(l) and XH(h) Vs. XH(l)), whereas 129 differentially methylated genes related to growth and metabolism were found in both across-breed contrasts (WRR(h) Vs. XH(h) and WRR(l) Vs. XH(l)). Further analysis showed that overall 75 genes exhibited altered DNA methylation in all four contrasts, which included some well-known growth factors of IGF1R, FGF12, FGF14, FGF18, FGFR2, and FGFR3. In addition, we validate the MeDIP-seq results by bisulfite sequencing in some regions.ConclusionsThis study revealed the global DNA methylation pattern of chicken muscle, and identified candidate genes that potentially regulate muscle development at 7 weeks of age at methylation level.

Project description:Chicken growth traits are important in poultry production, however, little is known for its regulatory mechanism at epigenetic level. Therefore, this study aims to compare DNA methylation profiles between fast- and slow-growing broilers in order to identify candidate genes underlying chicken growth. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) was used to investigate the genome-wide DNA methylation pattern in high and low tails of Recessive White Rock (WRRh, WRRl) and that of Xinhua Chickens (XHh, XHl). The results showed that the average of methylation density was the lowest in CGIs followed by promoters. Within the gene body, the methylation density of introns was higher than UTRs and exons. Moreover, different methylation levels were observed in different repeat types with the highest in LINE/CR1. Methylated CGIs were prominently distributed in the intergenic regions and were enriched in the size range of 200-300 bp. In total 13,294 methylated genes were found in four samples, including 4,085 differentially methylated genes between WRRh and WRRl, 5,599 between XHh and XHl, 4,204 between WRRh and XHh, as well as 7,301 between WRRl and XHl. Moreover, 132 differentially methylated genes related to growth and metabolism were observed in both inner contrasts (WRRh Vs. WRRl and XHh Vs. XHl), whereas 129 differentially methylated genes related to growth and metabolism were found in both across-breed contrasts (WRRh Vs. XHh and WRRl Vs. XHl). Further analysis showed that overall 75 genes exhibited altered DNA methylation in all four contrasts, which included some well-known growth factors of IGF1R, FGF12, FGF14, FGF18, FGFR2, and FGFR3. In addition, we further validate the MeDIP-seq results by bisulfite sequencing in some regions. 12 Breast muscle samples were collected from two breeds of different growth rate, Recessive White Rock (WRR) and Xinhua Chickens (XH). Each breed included low and high-weight groups and 3 samples from each group were pooled equally for methylated DNA immunoprecipitation-sequencing (MeDIP-seq).

Dataset Information

Fast and Slow-Growing Management Systems: Characterisation of Broiler Caecal Microbiota Development throughout the Growing Period.

Publications

Fast and Slow-Growing Management Systems: Characterisation of Broiler Caecal Microbiota Development throughout the Growing Period.

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