scholarly journals Galactooligosaccharides and Xylo-oligosaccharides Altering the Caecal Microbiome, Metabolome, and Transcriptome of Chickens Revealed by a Multi-Omics Analysis

2021 ◽  
Author(s):  
Chaowu Yang ◽  
Mohan Qiu ◽  
Chunlin Yu ◽  
Han Peng ◽  
Xiaoyan Song ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Meat Quality ◽  
Myristic Acid ◽  
Transcriptome Sequencing ◽  
Underlying Mechanism ◽  
Gut Contents ◽  
Chicken Breast ◽  
Gut Content ◽  
Flavor Compound ◽  
Different Levels

Abstract Backgroud Studies have shown that prebiotics could affect meat quality, but the underlying mechanism are poorly understood. This study aimed to investigate whether prebiotics affect chicken’s meat quality through gut microbiome and metabolome. Methods The gut content were collected from chickens fed with or without prebiotics (galactooligosaccharides or xylo-oligosaccharides) and subjected to microbiome and metabolome analyses, and chicken breast was performed transcriptome sequencing. Results The prebiotics altered proportions of microbiota in gut contents at different levels, especially microbiota in the phylum of Bacteroidetes and Firmicutes, such as genus of Alistipes, Bacteroides, and Faecalibacterium. The prebiotics also altered contents of caecal metabolites such as lysophosphatidylcholine (lysoPC), intramuscular fat and flavor compound (Benzaldehyde and myristic acid). Differentially expressed genes (DEGs) induced by prebiotics were significantly involved in regulation of lipolysis inadipocytes and adipocytokine signaling pathway. Changes in gut microbiota and metabolites were remarkably correlated such as Bacteroidetes and Firmicutes was respectively positively and negatively correlated with lysoPC. DEGs were also interacted with caecal metabolites. Conclusion These findings integrated and incorporated link among gut microbiota, metabolites and transcriptome, which proposed prebiotics may affect meat quality and flavor of chickens.

scholarly journals Analysis of metagenome-assembled genomes from the mouse gut microbiota reveals distinctive strain-level characteristics

2020 ◽  
Author(s):  
Shenghui Li ◽  
Siyi Zhang ◽  
Bo Li ◽  
Shanshan Sha ◽  
Jian Kang ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Ribosomal Rna ◽  
Strain Level ◽  
Gut Contents ◽  
Gut Content ◽  
Gut Flora ◽  
Human Gut ◽  
Gene Catalogue ◽  
Taxonomic Characterization ◽  
Mouse Gut Microbiota

AbstractThe laboratorial mouse harbors a unique gut microbiota with potential value for human microbiota-associated studies. Mouse gut microbiota has been explored at the genus and species levels, but features rarely been showed at the strain level. The identification of 833,051 and 658,438 nonredundant genes of faeces and gut content samples from the laboratorial C57/BL mice showed over half of these genes were newly found compared to the previous mouse gut microbial gene catalogue. Metagenome-assembled genomes (MAGs) was used to reconstruct 46 nonredundant MAGs belonging to uncultured specieses. These MAGs included members across all phyla in mouse gut (i.e. Firmicutes, Bacteroidetes, Proteobacteria, Deferribacteres, Verrucomicrobia, and Tenericutes) and allowed a strain-level delineating of the mouse gut microbiota. Comparison of MAGs with human gut colonies revealed distinctive genomic and functional characteristics of mouse’s Bacteroidetes and Firmicutes strains. Genomic characteristics of rare phyla in mouse gut microbiota were demonstrated by MAG approach, including strains of Mucispirillum schaedleri, Parasutterella excrementihominis, Helicobacter typhlonius, and Akkermansia muciniphila.ImportanceThe identification of nonredundant genes suggested the existence of unknown microbes in the mouse gut samples. The metagenome-assembled genomes (MAGs) instantiated the specificity of mouse gut species and revealed an intestinal microbial correlation between mouse and human. The cultivation of faeces and gut contents sample validated the existence of MAGs and estimate their accuracy. Full-length 16S ribosomal RNA gene sequencing enabled taxonomic characterization. This study highlighted a unique ecosystem in the gut of laboratorial mice that obviously differed with the human gut flora at the strain level. The outcomes may be beneficial to researches based on laboratorial mouse models.

scholarly journals Assessment of chicken breast shelf life based on bench-top and portable NIR spectroscopy tools coupled with chemometrics

2020 ◽  
Author(s):  
Ilaria Lanza ◽  
Daniele Conficoni ◽  
Stefania Balzan ◽  
Marco Cullere ◽  
Luca Fasolato ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Shelf Life ◽  
Meat Quality ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Life Assessment ◽  
Chicken Breast ◽  
Portable Devices ◽  
Physicochemical Processes ◽  
Insight Into

Abstract Near-infrared (NIR) spectroscopy is a rapid technique able to assess meat quality even if its capability to determine the shelf life of chicken fresh cuts is still debated, especially for portable devices. The aim of the study was to compare bench-top and portable NIR instruments in discriminating between four chicken breast refrigeration times (RT), coupled with multivariate classifier models. Ninety-six samples were analysed by both NIR tools at 2, 6, 10 and 14 days post-mortem. NIR data were subsequently submitted to partial least squares discriminant analysis (PLS-DA) and canonical discriminant analysis (CDA). The latter was preceded by double feature selection based on Boruta and Stepwise procedures. PLS-DA sorted moderate separation of RT theses, while shelf life assessment was more accurate on application of Stepwise-CDA. Bench-top tool had better performance than portable one, probably because it captured more informative spectral data as shown by the variable importance in projection (VIP) and restricted pool of Stepwise-CDA predictive scores (SPS). NIR tools coupled with a multivariate model provide deep insight into the physicochemical processes occurring during storage. Spectroscopy showed reliable effectiveness to recognise a 7-day shelf life threshold of breasts, suitable for routine at-line application for screening of meat quality.

scholarly journals Aflatoxin B1 alters meat quality associated with oxidative stress, inflammation, and gut-microbiota in sheep

2021 ◽  
Vol 225 ◽  
pp. 112754
Author(s):  
Qin-qin Cao ◽  
Lu-xi Lin ◽  
Ting-ting Xu ◽  
Ying Lu ◽  
Chao-dong Zhang ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Gut Microbiota ◽  
Meat Quality ◽  
Aflatoxin B1

Modulation of gut microbiota and intestinal barrier function during alleviation of antibiotic-associated diarrhea with Rhizoma Zingiber officinale (Ginger) extract

2020 ◽  
Vol 11 (12) ◽  
pp. 10839-10851
Author(s):  
Zhi-jie Ma ◽  
Huan-jun Wang ◽  
Xiao-jing Ma ◽  
Yue Li ◽  
Hong-jun Yang ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Barrier Function ◽  
Intestinal Barrier ◽  
Zingiber Officinale ◽  
Underlying Mechanism ◽  
Intestinal Barrier Function ◽  
Ginger Extract ◽  
Beneficial Effects ◽  
Antibiotic Associated Diarrhea

Ginger extract showed beneficial effects on rats with antibiotic-associated diarrhea, and the underlying mechanism might be associated with the recovery of gut microbiota and intestinal barrier function.

scholarly journals Comprehensive Proteomic Characterization of the Pectoralis Major at Three Chronological Ages in Beijing-You Chicken

2021 ◽  
Vol 12 ◽  
Author(s):  
Jian Zhang ◽  
Jing Cao ◽  
Ailian Geng ◽  
Haihong Wang ◽  
Qin Chu ◽  
...  
Keyword(s):  
Meat Quality ◽  
Muscle Development ◽  
Expression Profiles ◽  
Pectoralis Major ◽  
Breast Muscle ◽  
Differentially Expressed ◽  
Chronological Age ◽  
Chicken Breast ◽  
Group 13 ◽  
Oocyte Meiosis

Chronological age is one of the important factors influencing muscle development and meat quality in chickens. To evaluate the protein expression profiles during skeletal muscle development, we performed a tandem mass tag (TMT)-based quantitative proteomic strategy in pectoralis major (breast muscle) of Beijing-You chicken (BYC) at the chronological age of 90, 120, and 150 days. Each chronological age contained 3 pooling samples or 15 birds (five birds per pooling sample). A total of 1,413 proteins were identified in chicken breast muscle with FDR < 1% and 197 of them were differentially expressed (fold change ≥1.2 or ≤0.83 and p < 0.05). There were 110 up- and 71 down-regulated proteins in 120 d vs 90 d group, 13 up- and 10 down-regulated proteins in 150 d vs 120 d group. The proteomic profiles of BYC at 120 d were very similar to those at 150 d and highly different from those at 90 d, suggesting that 120 d might be an important chronological age for BYC. Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that these differentially expressed proteins were mainly involved in the pathway of glycolysis/gluconeogenesis, adrenergic signaling in cardiomyocytes, focal adhesion, oocyte meiosis and phagosome. Furthermore, some DEPs were quantified using parallel reaction monitoring (PRM) to validate the results from TMT analysis. In summary, these results provided some candidate protein-coding genes for further functional validation and contribute to a comprehensive understanding of muscle development and age-dependent meat quality regulation by proteins in chickens.

scholarly journals Altered Fecal Metabolites and Colonic Glycerophospholipids Were Associated With Abnormal Composition of Gut Microbiota in a Depression Model of Mice

2021 ◽  
Vol 15 ◽  
Author(s):  
Xue Gong ◽  
Cheng Huang ◽  
Xun Yang ◽  
Jianjun Chen ◽  
Juncai Pu ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Gut Microbiota ◽  
16S Rrna Gene Sequencing ◽  
Underlying Mechanism ◽  
Rrna Gene ◽  
Mice Model ◽  
Microbial Composition ◽  
Gas And Liquid Chromatography ◽  
Correlation Analysis Method ◽  
Rrna Gene Sequencing

The microbiota–gut–brain axis has been considered to play an important role in the development of depression, but the underlying mechanism remains unclear. The gastrointestinal tract is home to trillions of microbiota and the colon is considered an important site for the interaction between microbiota and host, but few studies have been conducted to evaluate the alterations in the colon. Accordingly, in this study, we established a chronic social defeated stress (CSDS) mice model of depression. We applied 16S rRNA gene sequencing to assess the gut microbial composition and gas and liquid chromatography–mass spectroscopy to identify fecal metabolites and colonic lipids, respectively. Meanwhile, we used Spearman’s correlation analysis method to evaluate the associations between the gut microbiota, fecal metabolites, colonic lipids, and behavioral index. In total, there were 20 bacterial taxa and 18 bacterial taxa significantly increased and decreased, respectively, in the CSDS mice. Further, microbial functional prediction demonstrated a disturbance of lipid, carbohydrate, and amino acid metabolism in the CSDS mice. We also found 20 differential fecal metabolites and 36 differential colonic lipids (in the category of glycerolipids, glycerophospholipids, and sphingolipids) in the CSDS mice. Moreover, correlation analysis showed that fecal metabolomic signature was associated with the alterations in the gut microbiota composition and colonic lipidomic profile. Of note, three lipids [PC(16:0/20:4), PG(22:6/22:6), and PI(18:0/20:3), all in the category of glycerophospholipids] were significantly associated with anxiety- and depression-like phenotypes in mice. Taken together, our results indicated that the gut microbiota might be involved in the pathogenesis of depression via influencing fecal metabolites and colonic glycerophospholipid metabolism.

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