![]() ![]() These methods have been recognized to be efficient in terms of cost and convenience. Previously, companion dogs have been evaluated for being overweight and obese based on their body weight (BW), body condition score (BCS), and body composition (fat mass and lean body mass) 10, 11, 12. Therefore, the veterinary community is paying increasing attention to the prevention of obesity in dogs. Furthermore, some studies suggest that breed, feed quality, and the owner’s interest in maintaining pet’s health are also possible causes 7, 8, 9. The main cause of obesity in dogs is an imbalance between energy intake and expenditure 6. Among them, canine obesity is considered a major metabolic disease because it can predispose dogs to a variety of disorders, such as cardiovascular disease 2, expiratory airway dysfunction 3, and diabetes mellitus 4, and has detrimental effects on longevity 5. Owing to the growing interest in dog welfare, more people have started to take an interest in the health problems of dogs 1. However, further studies are needed to investigate how specific networks can be interpreted in the context of fermentation characteristics in the lower gut and obesity in dogs. The enriched KEGG modules in the HBCS group enhanced energy efficiency through cross-feeding between auxotrophs and prototrophs. In conclusion, several genera related to short-chain fatty acid production were enriched in the HBCS group. Microbial network analysis revealed distinct co-occurrence and mutually exclusive interactions between the HBCS and NBCS groups. Furthermore, some Kyoto Encyclopedia of Genes and Genomes (KEGG) modules related to amino acid biosynthesis and B vitamins biosynthesis were enriched in the HBCS group ( P < 0.10), whereas those related to carbohydrate metabolism were enriched in the NBCS group ( P < 0.10). The relative abundances of Faecalibacterium, Phascolarctobacterium, Megamonas, Bacteroides, Mucispirillum, and an unclassified genus within Ruminococcaceae were significantly higher in the HBCS group than those in the NBCS group ( P < 0.05). The HBCS group had a significantly higher final BW than the NBCS group ( P < 0.01). In the final week of the experiment, fecal samples were collected directly from the rectum, before breakfast, for analyzing the fecal microbiome using 16S rRNA gene amplicon sequencing. Then, 12 beagle dogs were selected based on body condition score (BCS) and divided into two groups: high BCS group (HBCS BCS range: 7–9, males = 4, females = 2) and normal BCS group (NBCS BCS range: 4–6, males = 4, females = 2). A total of 20 beagle dogs (males = 12, body weight : 10.5 ± 1.08 kg females = 8, BW: 11.3 ± 1.71 kg all 2-year-old) were fed to meet the maintenance energy requirements for 18 weeks. The objective of this study was to investigate the differences in fecal microbiome and specific microbial networks between obese and normal dogs. However, little is known about specific microbial interactions, and how these may be affected by obesity in dogs. The fecal microbiome has been attracting attention because of their impact on energy efficiency and metabolic disorders of host. Canine obesity is a major health concern that predisposes dogs to various disorders.
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