Integrated metabolomics and lipidomics evaluate the alterations of flavor precursors in chicken breast muscle with white striping symptom

White striping (WS) is the most common myopathy in the broiler chicken industry. To reveal flavor changes of WS meat objectively, flavor precursors of WS breast muscle were evaluated systematically with integrated metabolomics and lipidomics. The results showed that WS could be distinguished from normal controls by E-nose, and four volatile compounds (o-xylene, benzene, 1,3-dimethyl, 2-heptanone and 6-methyl and Acetic acid and ethyl ester) were detected as decreased compounds by gas chromatography-mass spectrometry. Lipidomic analysis showed that WS breast fillets featured increased neutral lipid (83.8%) and decreased phospholipid molecules (33.2%). Targeted metabolomic analysis indicated that 16 hydrophilic metabolites were altered. Thereinto, some water-soluble flavor precursors, such as adenosine monophosphate, GDP-fucose and L-arginine increased significantly, but fructose 1,6-bisphosphate and L-histidine significantly decreased in the WS group. These results provided a systematic evaluation of the flavor precursors profile in the WS meat of broiler chickens

Divergent selection-induced obesity alters the composition and functional pathways of chicken gut microbiota

International audienceAbstractBackgroundThe gastrointestinal tract is populated by a complex and vast microbial network, with a composition that reflects the relationships of the symbiosis, co-metabolism, and co-evolution of these microorganisms with their host. The mechanism that underlies such interactions between the genetics of the host and gut microbiota remains elusive.ResultsTo understand how genetic variation of the host shapes the gut microbiota and interacts with it to affect the metabolic phenotype of the host, we compared the abundance of microbial taxa and their functional performance between two lines of chickens (fat and lean) that had undergone long-term divergent selection for abdominal fat pad weight, which resulted in a 4.5-fold increase in the fat line compared to the lean line. Our analysis revealed that the proportions of Fusobacteria and Proteobacteria differed significantly between the two lines (8 vs. 18% and 33 vs. 24%, respectively) at the phylum level. Eight bacterial genera and 11 species were also substantially influenced by the host genotype. Differences between the two lines in the frequency of host alleles at loci that influence accumulation of abdominal fat were associated with differences in the abundance and composition of the gut microbiota. Moreover, microbial genome functional analysis showed that the gut microbiota was involved in pathways that are associated with fat metabolism such as lipid and glycan biosynthesis, as well as amino acid and energy metabolism. Interestingly, citrate cycle and peroxisome proliferator activated receptor (PPAR) signaling pathways that play important roles in lipid storage and metabolism were more prevalent in the fat line than in the lean line.ConclusionsOur study demonstrates that long-term divergent selection not only alters the composition of the gut microbiota, but also influences its functional performance by enriching its relative abundance in microbial taxa. These results support the hypothesis that the host and gut microbiota interact at the genetic level and that these interactions result in their co-evolution

Combined effect of microbially derived cecal SCFA and host genetics on feed efficiency in broiler chickens

Abstract Background Improving feed efficiency is the most important goal for modern animal production. The regulatory mechanisms of controlling feed efficiency traits are extremely complex and include the functions related to host genetics and gut microbiota. Short-chain fatty acids (SCFAs), as significant metabolites of microbiota, could be used to refine the combined effect of host genetics and gut microbiota. However, the association of SCFAs with the gut microbiota and host genetics for regulating feed efficiency is far from understood. Results In this study, 464 broilers were housed for RFI measuring and examining the host genome sequence. And 300 broilers were examined for cecal microbial data and SCFA concentration. Genome-wide association studies (GWAS) showed that four out of seven SCFAs had significant associations with genome variants. One locus (chr4: 29414391–29417189), located near or inside the genes MAML3, SETD7, and MGST2, was significantly associated with propionate and had a modest effect on feed efficiency traits and the microbiota. The genetic effect of the top SNP explained 8.43% variance of propionate. Individuals with genotype AA had significantly different propionate concentrations (0.074 vs. 0.131 μg/mg), feed efficiency (FCR: 1.658 vs. 1.685), and relative abundance of 14 taxa compared to those with the GG genotype. Christensenellaceae and Christensenellaceae_R-7_group were associated with feed efficiency, propionate concentration, the top SNP genotypes, and lipid metabolism. Individuals with a higher cecal abundance of these taxa showed better feed efficiency and lower concentrations of caecal SCFAs. Conclusion Our study provides strong evidence of the pathway that host genome variants affect the cecal SCFA by influencing caecal microbiota and then regulating feed efficiency. The cecal taxa Christensenellaceae and Christensenellaceae_R-7_group were identified as representative taxa contributing to the combined effect of host genetics and SCFAs on chicken feed efficiency. These findings provided strong evidence of the combined effect of host genetics and gut microbial SCFAs in regulating feed efficiency traits. Video Abstrac

Body Weight Selection Affects Quantitative Genetic Correlated Responses in Gut Microbiota

<div><p>The abundance of gut microbiota can be viewed as a quantitative trait, which is affected by the genetics and environment of the host. To quantify the effects of host genetics, we calculated the heritability of abundance of specific microorganisms and genetic correlations among them in the gut microbiota of two lines of chickens maintained under the same husbandry and dietary regimes. The lines, which originated from a common founder population, had undergone >50 generations of selection for high (HW) or low (LW) 56-day body weight and now differ by more than 10-fold in body weight at selection age. We identified families of <i>Paenibacillaceae</i>, <i>Streptococcaceae</i>, <i>Helicobacteraceae</i>, and <i>Burkholderiaceae</i> that had moderate heritabilities. Although there were no obvious phenotypic correlations among gut microbiota, significant genetic correlations were observed. Moreover, the effects were modified by genetic selection for body weight, which altered the quantitative genetic background of the host. Heritabilities for <i>Bacillaceae</i>, <i>Flavobacteriaceae</i>, <i>Helicobacteraceae</i>, <i>Comamonadaceae</i>, <i>Enterococcaceae</i>, and <i>Streptococcaceae</i> were moderate in LW line and little to zero in the HW line. These results suggest that loci associated with these microbiota families, while exhibiting genetic variation in LW, have been fixed in HW line. Also, long term selection for body weight has altered the genetic correlations among gut microbiota. No microbiota families had significant heritabilities in both the LW and HW lines suggesting that the presence and/or absence of a particular microbiota family either has a strong growth promoting or inhibiting effect, but not both. These results demonstrate that the quantitative genetics of the host have considerable influence on the gut microbiota.</p></div

Large-scale genomic and transcriptomic analyses elucidate the genetic basis of high meat yield in chickens

Introduction: Investigating the genetic markers and genomic signatures related to chicken meat production by combing multi-omics methods could provide new insights into modern chicken breeding technology systems. Object: Chicken is one of the most efficient and environmentally friendly livestock, especially the fast-growing white-feathered chicken (broiler), which is well known for high meat yield, but the underlying genetic basis is poorly understood. Method: We generated whole-genome resequencing of three purebred broilers (n = 748) and six local breeds/lines (n = 114), and sequencing data of twelve chicken breeds (n = 199) were obtained from the NCBI database. Additionally, transcriptome sequencing of six tissues from two chicken breeds (n = 129) at two developmental stages was performed. A genome-wide association study combined with cis-eQTL mapping and the Mendelian randomization was applied. Result: We identified > 17 million high-quality SNPs, of which 21.74% were newly identified, based on 21 chicken breeds/lines. A total of 163 protein-coding genes underwent positive selection in purebred broilers, and 83 genes were differentially expressed between purebred broilers and local chickens. Notably, muscle development was proven to be the major difference between purebred broilers and local chickens, or ancestors, based on genomic and transcriptomic evidence from multiple tissues and stages. The MYH1 gene family showed the top selection signatures and muscle-specific expression in purebred broilers. Furthermore, we found that the causal gene SOX6 influenced breast muscle yield and also related to myopathy occurrences. A refined haplotype was provided, which had a significant effect on SOX6 expression and phenotypic changes. Conclusion: Our study provides a comprehensive atlas comprising the typical genomic variants and transcriptional characteristics for muscle development and suggests a new regulatory target (SOX6–MYH1s axis) for breast muscle yield and myopathy, which could aid in the development of genome-scale selective breeding aimed at high meat yield in broiler chickens

Genetic and phenotypic correlations for lines pooled.

<p>upper side triangle are phenotypic correlations, lower side triangle are genetic correlations with heritabilities on the diagonal.</p><p>*: p<0.05,</p><p>**: P<0.01.</p

<b>Table 1.</b> Heritabilities by line and pooled.

<p>*: p<0.05,</p><p>**: p<0.01.</p

An Automated Colourimetric Test by Computational Chromaticity Analysis: A Case Study of Tuberculosis Test

This paper presents an investigation into a novel approach for an automated universal colourimetric test by chromaticity analysis. This work particularly focuses on how a well-adjusted harmony between computational complexity and biochemical analysis can reduce the associated cost and unlock the limit on conventional chemical practice. The proposed research goal encompasses the potential to the criteria- anytime anywhere access, low cost, rapid detection, better sensitivity, specificity and accuracy. Our method includes obtaining the amount of colour change for each instance by delta E calculation. The system can provide the result in any ambient condition from the trajectory of colour change using Euclidean distance in LAB colour space. The strategy is verified on plasmonic ELISA based diagnosis of tuberculosis (TB). TB detection by plasmonic ELISA is a challenging, demanding and a time-consuming diagnosis. Completing the computation in real time, we circumvent the obstacle liberating the TB diagnosis in less than 15 min

The Dynamic Distribution of Porcine Microbiota across Different Ages and Gastrointestinal Tract Segments

<div><p>Metagenome of gut microbes has been implicated in metabolism, immunity, and health maintenance of its host. However, in most of previous studies, the microbiota was sampled from feces instead of gastrointestinal (GI) tract. In this study, we compared the microbial populations from feces at four different developmental stages and contents of four intestinal segments at maturity to examine the dynamic shift of microbiota in pigs and investigated whether adult porcine fecal samples could be used to represent samples of the GI tract. Analysis results revealed that the ratio of <i>Firmicutes</i> to <i>Bacteroidetes</i> from the feces of the older pigs (2-, 3-, 6- month) were 10 times higher compared to those from piglets (1-month). As the pigs matured, so did it seem that the composition of microbiome became more stable in feces. In adult pigs, there were significant differences in microbial profiles between the contents of the small intestine and large intestine. The dominant genera in the small intestine belonged to aerobe or facultative anaerobe categories, whereas the main genera in the large intestine were all anaerobes. Compared to the GI tract, the composition of microbiome was quite different in feces. The microbial profile in large intestine was more similar to feces than those in the small intestine, with the similarity of 0.75 and 0.38 on average, respectively. Microbial functions, predicted by metagenome profiles, showed the enrichment associated with metabolism pathway and metabolic disease in large intestine and feces while higher abundance of infectious disease, immune function disease, and cancer in small intestine. Fecal microbes also showed enriched function in metabolic pathways compared to microbes from pooled gut contents. Our study extended the understanding of dynamic shift of gut microbes during pig growth and also characterized the profiles of bacterial communities across GI tracts of mature pigs.</p></div