, 15:21 | Cite as

Trial data of the anti-obesity potential of a high resistant starch diet for canines using Dodamssal rice and the identification of discriminating markers in feces for metabolic profiling

  • Ye Jin Kim
  • Jae Geun Kim
  • Wan-Kyu Lee
  • Kyoung Min SoEmail author
  • Jae Kwang KimEmail author
Original Article



Dodamssal rice (Oryza sativa L.) includes high levels of resistant starch (RS), which is a source of dietary fiber. Recently, there has been an increase in the prevalence of obesity in canines; however, the information regarding diet treatments for such a condition is inadequate.


Targeted metabolic profiles in canine feces were performed to identify potential biomarkers of RS and demonstrate the effect and potential use of Dodamssal rice as an anti-obesity treatment.


Study canines were divided into three groups and fed either a regular diet, high-fat diet (HFD), or high-fat diet with Dodamssal rice (DoHFD). Fecal metabolites were analyzed using gas chromatography time-of-flight mass spectrometry and a gas chromatography-flame ionization detector. Multivariate analyses were used to analyze and visualize the obtained data.


A total of 52 metabolites were detected in the canine feces. In addition, HFD group feces contained a significantly low level of C12:0. The DoHFD group feces had higher levels of 4-aminobutyric acid, glucose, and 3-hydroxybutyric acid compared to the other groups (p < 0.05).


For the first time, targeted metabolic profiling in the canine feces in response to three diets was performed. This metabolic profiling approach should be a useful tool to detect discriminating markers as well as assess the effect of diet compositions for anti-obesity treatment of canines. Furthermore, Dodamssal rice may possibly be used not only for canines, but also to treat obesity in other animals and humans.


Anti-obesity treatment Canine feces Dodamssal rice Metabolic profiling Multivariate analysis Resistant starch 


Author contributions

KMS and JKK designed the experiments and analyzed the data. YJK and JGK wrote the manuscript and performed the experiments. W-KL analyzed the data.


This work was carried out with the support of the Incheon National University Research in 2016 and “Cooperative Research Program for Agriculture Science and Technology Development (Project No: PJ01283406)”, Rural Development Administration, Republic of Korea.

Compliance with ethical standards

Conflict of interest

The authors declare to have no financial and non-financial conflict of interest.

Ethical approval

We followed all applicable international, national, and institutional guidelines for the care and use of animals. All procedures performed in the studies that involved animals were in accordance with the ethical standards of the institution in which the studies were conducted.

Supplementary material

11306_2019_1479_MOESM1_ESM.pptx (468 kb)
Supplementary material 1 (PPTX 467 KB)


  1. Allaway, D., Kamlage, B., Gilham, M. S., Hewson-Hughes, A. K., Wiemer, J. C., Colyer, A., et al. (2013). Effects of dietary glucose supplementation on the fasted plasma metabolome in cats and dogs. Metabolomics, 9(5), 1096–1108.CrossRefGoogle Scholar
  2. An, Y., Xu, W., Li, H., Lei, H., Zhang, L., Hao, F., et al. (2013). High-fat diet induces dynamic metabolic alterations in multiple biological matrices of rats. Journal of Proteome Research, 12(8), 3755–3768.PubMedCrossRefGoogle Scholar
  3. Association of American Feed Control Officials (AAFCO). (2011). 2011 Official publication: Association of American Feed Control Officials. Oxford: Association of American Feed Control Officials.Google Scholar
  4. Birkett, A., Muir, J., Phillips, J., Jones, G., & O’Dea, K. (1996). Resistant starch lowers fecal concentrations of ammonia and phenols in humans. The American Journal of Clinical Nutrition, 63(5), 766–772.PubMedCrossRefGoogle Scholar
  5. Brown, I. L., McNaught, K. J., Ganly, R. N., Conway, P. L., Evans, A. J., Topping, D. L., et al. (1996). Probiotic compositions. International Patent WO, 96(08261), A1.Google Scholar
  6. Buettner, R., Parhofer, K. G., Woenckhaus, M., Wrede, C. E., Kunz-Schughart, L. A., Schölmerich, J., et al. (2006). Defining high-fat-diet rat models: Metabolic and molecular effects of different fat types. Journal of molecular endocrinology, 36(3), 485–501.PubMedCrossRefGoogle Scholar
  7. Crawford, P. A., Crowley, J. R., Sambandam, N., Muegge, B. D., Costello, E. K., Hamady, M., et al. (2009). Regulation of myocardial ketone body metabolism by the gut microbiota during nutrient deprivation. Proceedings of the National Academy of Sciences, 106(27), 11276–11281.CrossRefGoogle Scholar
  8. Daniel, H., Gholami, A. M., Berry, D., Desmarchelier, C., Hahne, H., Loh, G., et al. (2014). High-fat diet alters gut microbiota physiology in mice. The ISME Journal, 8(2), 295–308.PubMedCrossRefGoogle Scholar
  9. Forster, G. M., Heuberger, A. L., Broeckling, C. D., Bauer, J. E., & Ryan, E. P. (2015). Consumption of cooked navy bean powders modulate the canine fecal and urine metabolome. Current Metabolomics, 3(2), 90–101.CrossRefGoogle Scholar
  10. Fukao, T., Lopaschuk, G. D., & Mitchell, G. A. (2004). Pathways and control of ketone body metabolism: On the fringe of lipid biochemistry. Prostaglandins, Leukotrienes and Essential Fatty Acids, 70(3), 243–251.CrossRefGoogle Scholar
  11. Higgins, J. A., Higbee, D. R., Donahoo, W. T., Brown, I. L., Bell, M. L., & Bessesen, D. H. (2004). Resistant starch consumption promotes lipid oxidation. Nutrition & Metabolism, 1(1), 8.CrossRefGoogle Scholar
  12. Kleessen, B., Stoof, G., Proll, J., Schmiedl, D., Noack, J., & Blaut, M. (1997). Feeding resistant starch affects fecal and cecal microflora and short-chain fatty acids in rats. Journal of Animal Science, 75(9), 2453–2462.PubMedCrossRefGoogle Scholar
  13. Laffel, L. (1999). Ketone bodies: A review of physiology, pathophysiology and application of monitoring to diabetes. Diabetes/Metabolism Research and Reviews, 15(6), 412–426.PubMedCrossRefGoogle Scholar
  14. Lee, J. Y., Sohn, K. H., Rhee, S. H., & Hwang, D. (2001). Saturated fatty acids, but not unsaturated fatty acids, induce the expression of cyclooxygenase-2 mediated through Toll-like receptor 4. Journal of Biological Chemistry, 276(20), 16683–16689.PubMedCrossRefGoogle Scholar
  15. McGhie, T. K., & Rowan, D. D. (2012). Metabolomics for measuring phytochemicals, and assessing human and animal responses to phytochemicals, in food science. Molecular Nutrition & Food Research, 56(1), 147–158.CrossRefGoogle Scholar
  16. McGreevy, P. D., Thomson, P. C., Pride, C., Fawcett, A., Grassi, T., & Jones, B. (2005). Prevalence of obesity in dogs examined by Australian veterinary practices and the risk factors involved. Veterinary Record-English Edition, 156(22), 695–701.CrossRefGoogle Scholar
  17. Moreira, A. P. B., Texeira, T. F. S., Ferreira, A. B., Peluzio, M. D. C. G., & Alfenas, R. D. C. G. (2012). Influence of a high-fat diet on gut microbiota, intestinal permeability and metabolic endotoxaemia. British Journal of Nutrition, 108(5), 801–809.PubMedCrossRefGoogle Scholar
  18. National Research Council (NRC). (2006). Nutrient requirements of dogs and cats. Washington, DC: National Academies Press.Google Scholar
  19. Park, C. H., Park, S.-Y., Lee, S. Y., Kim, J. K., & Park, S. U. (2018a). Analysis of metabolites in white flowers of Magnolia denudata Desr. and violet flowers of Magnolia liliiflora Desr. Molecules, 23, 1558.PubMedCentralCrossRefGoogle Scholar
  20. Park, J., Lee, S. K., Choi, I., Choi, H. S., Shin, D. S., Park, H. Y., Han, S.-I., & Oh, S.-K. (2018b). Starch content and in vitro hydrolysis index of rice varieties containing resistant starch. The Korean Journal of Crop Science, 63(4), 304–313.Google Scholar
  21. Park, P. W., & Goins, R. E. (1994). In situ preparation of fatty acid methyl esters for analysis of fatty acid composition in foods. Journal of Food Science, 59(6), 1262–1266.CrossRefGoogle Scholar
  22. Penning, M. E. M. (2014). Using first-trimester urinary metabolomics profiling to identify markers of preeclampsia. In Penning, M. E. M. (Ed.), On renal pathophysiology in preeclampsia (pp. 141–144). Leiden: Leiden University Medical Center (LUMC).Google Scholar
  23. Phua, L. C., Koh, P. K., Cheah, P. Y., Ho, H. K., & Chan, E. C. Y. (2013). Global gas chromatography/time-of-flight mass spectrometry (GC/TOFMS)-based metabonomic profiling of lyophilized human feces. Journal of Chromatography B, 937, 103–113.CrossRefGoogle Scholar
  24. Pokusaeva, K., Johnson, C., Luk, B., Uribe, G., Fu, Y., Oezguen, N., et al. (2017). GABA-producing Bifidobacterium dentium modulates visceral sensitivity in the intestine. Neurogastroenterology & Motility, 29(1), e12904.CrossRefGoogle Scholar
  25. Raben, A., Tagliabue, A., Christensen, N. J., Madsen, J., Holst, J. J., & Astrup, A. (1994). Resistant starch: The effect on postprandial glycemia, hormonal response, and satiety. The American Journal of Clinical Nutrition, 60(4), 544–551.PubMedCrossRefGoogle Scholar
  26. Reader, D., Johnson, M. L., Hollander, P., & Franz, M. (1997). Response of resistant starch in a food bar vs. two commercially available bars in persons with type II diabetes mellitus. Diabetes, 46(1), 254A.Google Scholar
  27. Reed, D. R., Tordoff, M. G., & Friedman, M. I. (1991). Enhanced acceptance and metabolism of fats by rats fed a high-fat diet. American Journal of Physiology-Regulatory Integrative and Comparative Physiology, 261(5), R1084–R1088.CrossRefGoogle Scholar
  28. Sadeghi-Bazargani, H., Bangdiwala, S. I., Mohammad, K., Maghsoudi, H., & Mohammadi, R. (2011). Compared application of the new OPLS-DA statistical model versus partial least squares regression to manage large numbers of variables in an injury case-control study. Scientific Research and Essays, 6(20), 4369–4377.CrossRefGoogle Scholar
  29. Sajilata, M. G., Singhal, R. S., & Kulkarni, P. R. (2006). Resistant starch—A review. Comprehensive Reviews in Food Science and Food Safety, 5(1), 1–17.CrossRefGoogle Scholar
  30. Sim, E.-Y., Chung, S.-K., Cho, J.-H., Woo, K. S., Park, H. Y., Kim, H.-J., et al. (2015). Physicochemical properties of high-amylose rice varieties. Food Engineering Progress, 19(4), 392–398.CrossRefGoogle Scholar
  31. Sybille, T., June, Z., Michael, K., Roy, M., & Maria, L. M., (2013). The intestinal microbiota in aged mice is modulated by dietary resistant starch and correlated with improvements in host responses. FEMS Microbiology Ecology, 83(2), 299–309.CrossRefGoogle Scholar
  32. Tian, J., Dang, H. N., Yong, J., Chui, W. S., Dizon, M. P., Yaw, C. K., et al. (2011). Oral treatment with γ-aminobutyric acid improves glucose tolerance and insulin sensitivity by inhibiting inflammation in high fat diet-fed mice. PLoS ONE, 6(9), e25338.PubMedPubMedCentralCrossRefGoogle Scholar
  33. Viant, M. R., Ludwig, C., Rhodes, S., Günther, U. L., & Allaway, D. (2007). Validation of a urine metabolome fingerprint in dog for phenotypic classification. Metabolomics, 3(4), 453–463.CrossRefGoogle Scholar
  34. Viant, M. R., Kurland, I. J., Jones, M. R., & Dunn, W. B. (2017). How close are we to complete annotation of metabolomes? Current Opinion in Chemical Biology, 36, 64–69PubMedPubMedCentralCrossRefGoogle Scholar
  35. Xiao, M., Du, G., Zhong, G., Yan, D., Zeng, H., & Cai, W. (2016). Gas chromatography/mass spectrometry-based metabolomic profiling reveals alterations in mouse plasma and liver in response to Fava Beans. PLoS ONE, 11(3), e0151103.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Division of Life SciencesIncheon National UniversityIncheonRepublic of Korea
  2. 2.College of Veterinary MedicineChungbuk National UniversityCheongjuRepublic of Korea
  3. 3.National Institute of Animal Science, Rural Development AdministrationWanju-gunRepublic of Korea

Personalised recommendations