Lund, E. M., Armstrong, P. J., Kirk, C. A. & Klausner, J. S. Prevalence and risk factors for obesity in adult dogs from private US veterinary practices. Int. J. Appl. Res. Vet. Med. 4(2), 177 (2006).
German, A. J. The growing problem of obesity in dogs and cats. J. Nutr. 136(7), 1940S-1946S (2006).
Google Scholar
Courcier, E. A., Thomson, R. M., Mellor, D. J. & Yam, P. S. An epidemiological study of environmental factors associated with canine obesity. J. Small Anim. Pract. 51(7), 362–367 (2010).
Google Scholar
Mao, J., Xia, Z., Chen, J. & Yu, J. Prevalence and risk factors for canine obesity surveyed in veterinary practices in Beijing, China. Prev. Vet. Med. 112(3–4), 438–442 (2013).
Google Scholar
Payan-Carreira, R., Sargo, T. & Nascimento, M. M. Canine obesity in Portugal: Perceptions on occurrence and treatment determinants. Acta Vet. Scand. 57(1), 1–1 (2015).
Google Scholar
Chandler, M. et al. Obesity and associated comorbidities in people and companion animals: A one health perspective. J. Comp. Pathol. 156(4), 296–309 (2017).
Google Scholar
Montoya-Alonso, J. A. et al. Prevalence of canine obesity, obesity-related metabolic dysfunction, and relationship with owner obesity in an obesogenic region of Spain. Front. Vet. Sci. 4, 59 (2017).
Google Scholar
Muñoz-Prieto, A. et al. European dog owner perceptions of obesity and factors associated with human and canine obesity. Sci. Rep. 8(1), 1–10 (2018).
Google Scholar
Marshall, W. G., Bockstahler, B. A., Hulse, D. A. & Carmichael, S. A review of osteoarthritis and obesity: Current understanding of the relationship and benefit of obesity treatment and prevention in the dog. Vet. Comp. Orthop. Traumatol. 22(05), 339–345 (2009).
Google Scholar
Zoran, D. L. Obesity in dogs and cats: A metabolic and endocrine disorder. Vet. Clin. N. Am. Small Anim. Pract. 40(2), 221–239 (2010).
Google Scholar
Tvarijonaviciute, A. et al. Obesity-related metabolic dysfunction in dogs: A comparison with human metabolic syndrome. BMC Vet. Res. 8(1), 147 (2012).
Google Scholar
Hoenig, M. Comparative aspects of human, canine, and feline obesity and factors predicting progression to diabetes. Vet. Sci. 1(2), 121–135 (2014).
Google Scholar
Yam, P. S. et al. Impact of canine overweight and obesity on health-related quality of life. Prev. Vet. Med. 127, 64–69 (2016).
Google Scholar
Sandøe, P., Palmer, C., Corr, S., Astrup, A. & Bjørnvad, C. R. Canine and feline obesity: A One Health perspective. Vet. Rec. 175(24), 610–616 (2014).
Google Scholar
Salt, C., Morris, P. J., Wilson, D., Lund, E. M. & German, A. J. Association between life span and body condition in neutered client-owned dogs. J. Vet. Intern. Med. 33(1), 89–99 (2019).
Google Scholar
Switonski, M. & Mankowska, M. Dog obesity—The need for identifying predisposing genetic markers. Res. Vet. Sci. 95(3), 831–836 (2013).
Google Scholar
Mankowska, M. et al. Sequence analysis of three canine adipokine genes revealed an association between TNF polymorphisms and obesity in Labrador dogs. Anim. Genet. 47(2), 245–249 (2016).
Google Scholar
Raffan, E. et al. A deletion in the canine POMC gene is associated with weight and appetite in obesity-prone Labrador retriever dogs. Cell Metab. 23(5), 893–900 (2016).
Google Scholar
Suchodolski, J. S. Intestinal microbiota of dogs and cats: A bigger world than we thought. Anim. Pract. 41(2), 261–272 (2011).
Barko, P. C., McMichael, M. A., Swanson, K. S. & Williams, D. A. The gastrointestinal microbiome: A review. J. Vet. Intern. Med. 32(1), 9–25 (2018).
Google Scholar
Turnbaugh, P. J. et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444(7122), 1027–1031 (2006).
Google Scholar
Bäckhed, F. et al. The gut microbiota as an environmental factor that regulates fat storage. Proc. Natl. Acad. Sci. 101(44), 15718–15723 (2004).
Google Scholar
Ghazalpour, A., Cespedes, I., Bennett, B. J. & Allayee, H. Expanding role of gut microbiota in lipid metabolism. Curr. Opin. Lipidol. 27(2), 141 (2016).
Google Scholar
Losasso, C. et al. Assessing the influence of vegan, vegetarian and omnivore oriented westernized dietary styles on human gut microbiota: A cross sectional study. Front. Microbiol. 9, 317 (2018).
Google Scholar
Pizarroso, N. A., Fuciños, P., Gonçalves, C., Pastrana, L. & Amado, I. R. A Review on the role of food-derived bioactive molecules and the microbiota—Gut–brain axis in satiety regulation. Nutrients 13(2), 632. https://doi.org/10.3390/nu13020632 (2021).
Google Scholar
Boulangé, C. L., Neves, A. L., Chilloux, J., Nicholson, J. K. & Dumas, M. E. Impact of the gut microbiota on inflammation, obesity, and metabolic disease. Genome Med. 8(1), 1–12 (2016).
Google Scholar
Ley, R. E. et al. Obesity alters gut microbial ecology. Proc. Natl. Acad. Sci. USA 102(31), 11070–11075 (2005).
Google Scholar
Ley, R. E., Turnbaugh, P. J., Klein, S. & Gordon, J. I. Human gut microbes associated with obesity. Nature 444(7122), 1022–1023 (2006).
Google Scholar
Zhi, C. et al. Connection between gut microbiome and the development of obesity. Eur. J. Clin. Microbiol. Infect. Dis. 38(11), 1987–1998 (2019).
Google Scholar
Huang, Z., Pan, Z., Yang, R., Bi, Y. & Xiong, X. The canine gastrointestinal microbiota: Early studies and research frontiers. Gut Microbes 11(4), 635–654 (2020).
Google Scholar
Swanson, K. S. et al. Phylogenetic and gene-centric metagenomics of the canine intestinal microbiome reveals similarities with humans and mice. ISME J. 5(4), 639–649 (2011).
Google Scholar
Coelho, L. P. et al. Similarity of the dog and human gut microbiomes in gene content and response to diet. Microbiome 6(1), 1–11 (2018).
Google Scholar
Hand, D., Wallis, C., Colyer, A. & Penn, C. W. Pyrosequencing the canine faecal microbiota: Breadth and depth of biodiversity. PLoS ONE 8(1), e53115 (2013).
Google Scholar
Handl, S. et al. Faecal microbiota in lean and obese dogs. FEMS Microbiol. Ecol. 84(2), 332–343 (2013).
Google Scholar
Park, H. J. et al. Association of obesity with serum leptin, adiponectin, and serotonin and gut microflora in beagle dogs. J. Vet. Intern. Med. 29(1), 43–50 (2015).
Google Scholar
Park, H. J. et al. Fecal microbiota analysis of obese dogs with underlying diseases: A pilot study. Korean J. Vet. Res. 55(3), 205–208 (2015).
Google Scholar
Beloshapka, A. N., Forster, G. M., Holscher, H. D., Swanson, K. S. & Ryan, E. P. Fecal microbial communities of overweight and obese client-owned dogs fed cooked bean powders as assessed by 454-pyrosequencing. J. Vet. Sci. Technol. 7(366), 2 (2016).
Li, Q., Lauber, C. L., Czarnecki-Maulden, G., Pan, Y. & Hannah, S. S. Effects of the dietary protein and carbohydrate ratio on gut microbiomes in dogs of different body conditions. MBio 8(1), e01703-e1716 (2017).
Google Scholar
Kieler, I. N. et al. Gut microbiota composition may relate to weight loss rate in obese pet dogs. Vet. Med. Sci. 3(4), 252–262 (2017).
Google Scholar
Forster, G. M. et al. A comparative study of serum biochemistry, metabolome and microbiome parameters of clinically healthy, normal weight, overweight, and obese companion dogs. Top. Companion Anim. Med. 33(4), 126–135 (2018).
Google Scholar
Salas-Mani, A. et al. Fecal microbiota composition changes after a BW loss diet in beagle dogs. J. Anim. Sci. 96(8), 3102–3111 (2018).
Google Scholar
Alexander, C. et al. Effects of prebiotic inulin-type fructans on blood metabolite and hormone concentrations and faecal microbiota and metabolites in overweight dogs. Br. J. Nutr. 120(6), 711–720 (2018).
Google Scholar
Herstad, K. M. et al. A diet change from dry food to beef induces reversible changes on the faecal microbiota in healthy, adult client-owned dogs. BMC Vet. Res. 13(1), 147 (2017).
Google Scholar
Kim, Y. S., Unno, T., Kim, B. Y. & Park, M. S. Sex differences in gut microbiota. World J. Mens Health 38(1), 48–60 (2020).
Google Scholar
Xu, J. et al. The response of canine faecal microbiota to increased dietary protein is influenced by body condition. BMC Vet. Res. 13(1), 374 (2017).
Google Scholar
Masuoka, H. et al. Transition of the intestinal microbiota of dogs with age. PLoS ONE 12, e0181739 (2016).
Google Scholar
Mizukami, K. et al. Age-related analysis of the gut microbiome in a purebred dog colony. FEMS Microbiol. Lett. 366(8), fnz095 (2019).
Google Scholar
Alessandri, G. et al. Metagenomic dissection of the canine gut microbiota: Insights into taxonomic, metabolic and nutritional features. Environ. Microbiol. 21(4), 1331–1343 (2019).
Google Scholar
Xu, H. et al. Oral administration of compound probiotics improved canine feed intake, weight gain, immunity and intestinal microbiota. Front. Immunol. 10, 666 (2019).
Google Scholar
Reddy, K. E. et al. Impact of breed on the fecal microbiome of dogs under the same dietary condition. J. Microbiol. Biotechnol. 29(12), 1947–1956 (2019).
Google Scholar
O’Neill, D. G., Church, D. B., McGreevy, P. D., Thomson, P. C. & Brodbelt, D. C. Prevalence of disorders recorded in dogs attending primary-care veterinary practices in England. PLoS ONE 9(3), e90501 (2014).
Google Scholar
Vilson, Å. et al. Disentangling factors that shape the gut microbiota in German Shepherd dogs. PLoS ONE 13(3), e0193507 (2018).
Google Scholar
Song, S. J. et al. Cohabiting family members share microbiota with one another and with their dogs. Elife 2, e00458 (2013).
Google Scholar
Guard, B. C. et al. Characterization of the fecal microbiome during neonatal and early pediatric development in puppies. PLoS ONE 12(4), e0175718 (2017).
Google Scholar
Greer, K. A., Canterberry, S. C. & Murphy, K. E. Statistical analysis regarding the effects of height and weight on life span of the domestic dog. Res. Vet. Sci. 82(2), 208–214 (2007).
Google Scholar
Fleming, J. M., Creevy, K. E. & Promislow, D. E. L. Mortality in North American dogs from 1984 to 2004: An investigation into age-, size-, and breed-related causes of death. J. Vet. Int. Med. 25(2), 187–198 (2011).
Google Scholar
Oberbauer, A. M., Belanger, J. & Famula, T. R. A review of the impact of neuter status on expression of inherited conditions in dogs. Front. Vet. Sci. 6, 397 (2019).
Google Scholar
Pilla, R. & Suchodolski, J. S. The role of the canine gut microbiome and metabolome in health and gastrointestinal disease. Front. Vet. Sci. 6, 498 (2020).
Google Scholar
Bermingham, E. N., Maclean, P., Thomas, D. G., Cave, N. J. & Young, W. Key bacterial families (Clostridiaceae, Erysipelotrichaceae and Bacteroidaceae) are related to the digestion of protein and energy in dogs. PeerJ 5, e3019 (2017).
Google Scholar
Kim, J., An, J. U., Kim, W., Lee, S. & Cho, S. Differences in the gut microbiota of dogs (Canis lupus familiaris) fed a natural diet or a commercial feed revealed by the Illumina MiSeq platform. Gut Pathog. 9, 68–68 (2017).
Google Scholar
Mori, A. et al. Comparison of the effects of four commercially available prescription diet regimens on the fecal microbiome in healthy dogs. J. Vet. Med. Sci. 81, 1783–1790 (2019).
Google Scholar
Apper, E. et al. Relationships between gut microbiota, metabolome, body weight, and glucose homeostasis of obese dogs fed with diets differing in prebiotic and protein content. Microorganisms 8(4), 513 (2020).
Google Scholar
Wernimont, S. M. et al. The effects of nutrition on the gastrointestinal microbiome of cats and dogs: Impact on health and disease. Front. Microbiol. https://doi.org/10.3389/fmicb.2020.01266 (2020).
Google Scholar
Schauf, S. et al. Effect of dietary fat to starch content on fecal microbiota composition and activity in dogs. J. Anim. Sci. 96(9), 3684–3698 (2018).
Google Scholar
Bresciani, F. et al. Effect of an extruded animal protein-free diet on fecal microbiota of dogs with food-responsive enteropathy. J. Vet. Intern. Med. 32(6), 1903–1910 (2018).
Google Scholar
Madsen, L., Myrmel, L. S., Fjære, E., Liaset, B. & Kristiansen, K. Links between dietary protein sources, the gut microbiota, and obesity. Front. Physiol. 8, 1047 (2017).
Google Scholar
EU law and publications. Regulation (EC) No 767/2009 of the European parliament and of the council of 13 July 2009 on the placing on the market and use of feed, amending European Parliament and council regulation (EC) No 1831/2003 and repealing council directive 79/373/EEC, commission directive 80/511/EEC, council directives 82/471/EEC, 83/228/EEC, 93/74/EEC, 93/113/EC and 96/25/EC and commission decision 2004/217/EC. OJEC L229, 1–28 (2009).
Paßlack, N. et al. Impact of the dietary inclusion of dried food residues on the apparent nutrient digestibility and the intestinal microbiota of dogs. Arch. Anim. Nutr. 75(4), 311–327 (2021).
Google Scholar
Macedo, H. T. et al. Weight-loss in obese dogs promotes important shifts in fecal microbiota profile to the extent of resembling microbiota of lean dogs. Anim. Microbiome 4(1), 1–13 (2022).
Google Scholar
Zhang, X. et al. Human gut microbiota changes reveal the progression of glucose intolerance. PLoS ONE 8(8), e71108 (2013).
Google Scholar
Remely, M. et al. Microbiota and epigenetic regulation of inflammatory mediators in type 2 diabetes and obesity. Benef. Microbes 5(1), 33–43 (2014).
Google Scholar
Tamanai-Shacoori, Z. et al. Roseburia spp.: A marker of health?. Future Microbiol. 12(2), 157–170 (2017).
Google Scholar
Herrmann, E. et al. RNA-based stable isotope probing suggests Allobaculum spp. as particularly active glucose assimilators in a complex murine microbiota cultured in vitro. BioMed Res. Int. 5, 1. https://doi.org/10.1155/2017/1829685 (2017).
Google Scholar
Wang, J., Wang, P., Li, D., Hu, X. & Chen, F. Beneficial effects of ginger on prevention of obesity through modulation of gut microbiota in mice. Eur. J. Nutr. 59(2), 699–718 (2020).
Google Scholar
Garcia-Mazcorro, J. F., Ivanov, I., Mills, D. A. & Noratto, G. Influence of whole-wheat consumption on fecal microbial community structure of obese diabetic mice. PeerJ 4, e1702 (2016).
Google Scholar
Wang, K. et al. Parabacteroides distasonis alleviates obesity and metabolic dysfunctions via production of succinate and secondary bile acids. Cell Rep. 26(1), 222–235 (2019).
Google Scholar
Wu, T. R. et al. Gut commensal Parabacteroides goldsteinii plays a predominant role in the anti-obesity effects of polysaccharides isolated from Hirsutella sinensis. Gut 68(2), 248–262 (2019).
Google Scholar
Karl, J. P. et al. Effects of psychological, environmental and physical stressors on the gut microbiota. Front. Microbiol. 9, 2013 (2018).
Google Scholar
Gallè, F. et al. Exploring the association between physical activity and gut microbiota composition: a review of current evidence. Ann. Ig. Med. Prev. Comunita 31(6), 582–589 (2019).
Laflamme, D. R. P. C. Development and validation of a body condition score system for dogs. Canine Practice (Santa Barbara, Calif.: 1990, USA) (1997).
FEDIAF. Nutritional Guidelines for Complete and Complementary Pet Food for Cats and Dogs https://fediaf.org/self-regulation/nutrition.html#guidelines (2021).
Klindworth, A. et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 41(1), e1–e1 (2013).
Google Scholar
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7(5), 335–336 (2010).
Google Scholar
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2018).
Lun, A. T., McCarthy, D. J. & Marioni, J. C. A step-by-step workflow for low-level analysis of single-cell RNA-seq data with bioconductor. F1000Research 5, 2122 (2016).
Google Scholar
Gong, W., Kwak, I. Y., Pota, P., Koyano-Nakagawa, N. & Garry, D. J. DrImpute: Imputing dropout events in single cell RNA sequencing data. BMC Bioinform. 19(1), 1–10 (2018).
Google Scholar
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41(D1), D590–D596 (2012).
Google Scholar
Finotello, F., Mastrorilli, E. & Di Camillo, B. Measuring the diversity of the human microbiota with targeted next-generation sequencing. Brief. Bioinform. 19(4), 679–692 (2018).
Google Scholar
Oksanen, J. et al. vegan: Community Ecology Package. Software http://CRAN.R-project.org/package=vegan (2012).
Source: Ecology - nature.com
