Fat deposition is the key factor affecting the efficiency of animal husbandry production. There are many factors affecting fat deposition, in which the gastrointestinal microbiota plays an important role. Therefore, the body mass index (BMI) was introduced into the evaluation of sheep fat deposition, and the different microbiota and functional pathways of the sheep gastrointestinal tract in different BMI groups were analyzed. We selected 5% of individuals with the highest and lowest BMI from a feed test population (357 in whole group). Microorganisms in 10 sites of the gastrointestinal tract in 36 individuals (18 in each group) were evaluated by 16S rRNA V3−V4 region sequencing. There were differences (p < 0.05) in fat deposition traits between different BMI groups. In the 10 parts of the gastrointestinal tract, the diversity and richness of cecal microflora in the high-BMI group were higher than those in low-BMI Hu sheep (p < 0.05). Principal coordinate analysis (PCoA) showed that there was separation of the cecum between groups, and there were differences in the cecal microbial community. Linear discriminant analysis effect size (LEfSe) showed that most biomarkers were in the cecum. On the basis of an indepth study of cecal microorganisms, 26 different bacterial genera were obtained (p < 0.05). Correlation analysis between them and the characteristics of fat deposition in sheep showed that Colidextribacter, Alloprevotella, and Succenivibrio were positively correlated with fat deposition, while Lachnospiraceae_ND3007_Group was negatively correlated (p < 0.05). The above results show that the cecum may be an important part leading to the difference of BMI in sheep, and its microorganisms may affect the level of fat deposition.
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http://dx.doi.org/10.3390/ani12070880 | DOI Listing |
Tissue Eng Regen Med
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Department of Plastic Surgery, Hand Surgery-Burn Center, University Hospital RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
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View Article and Find Full Text PDFSci China Life Sci
January 2025
Laboratory of Animal Nutritional Physiology and Metabolic Process, Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, 410125, China.
Metabolites and metabolism-related gene expression profiles in skeletal muscle change dramatically under obesity, aging and metabolic disease. Since obese and lean pigs are ideal models for metabolic research. Here, we compared metabolome and transcriptome of Longissimus dorsi (LD) muscle between Taoyuan black (TB, obese) and Duroc (lean) pigs at different ages.
View Article and Find Full Text PDFJ Obes Metab Syndr
January 2025
Research Center, University Institute of Cardiology and Pneumology of Quebec-Laval University, Québec, QC, Canada.
The worldwide prevalence of obesity is a key factor involved in the epidemic proportions reached by chronic societal diseases. A revolution in the study of obesity has been the development of imaging techniques for the measurement of its regional distribution. These imaging studies have consistently reported that individuals with an excess of visceral adipose tissue (VAT) were those characterized by the highest cardiometabolic risk.
View Article and Find Full Text PDFNan Fang Yi Ke Da Xue Xue Bao
January 2025
Department of Gastroenterology, Affiliated Hospital of Guizhou Medical University, Guiyang 550000, China.
Objectives: To investigate the regulatory role of nucleotide-bound oligomerized domain-like receptor containing pyrin-domain protein 6 (NLRP6) in liver lipid metabolism and non-alcoholic fatty liver disease (NAFLD).
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Phys Med Biol
January 2025
North Carolina State University, Fitts Woolard Hall, Raleigh, North Carolina, 27695-7908, UNITED STATES.
Motivated by elastography that utilizes tissue mechanical properties as biomarkers for liver disease, with the eventual objective of quantitatively linking histopathology and bulk mechanical properties, we develop a micromechanical modeling approach to capture the effects of fat and collagen deposition in the liver. Specifically, we utilize computational homogenization to convert the microstructural changes in hepatic lobule to the effective viscoelastic modulus of the liver tissue, i.e.
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