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Determination of the fecal microbiota of healthy, obese and post-slender dogs

Grant number: 19/12861-7
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): July 01, 2019
Effective date (End): June 30, 2020
Field of knowledge:Agronomical Sciences - Veterinary Medicine
Principal researcher:Márcio Antonio Brunetto
Grantee:Matheus Vinícius Macegoza
Home Institution: Faculdade de Medicina Veterinária e Zootecnia (FMVZ). Universidade de São Paulo (USP). São Paulo , SP, Brazil


Obesity is considered a nutritional and metabolic disease more common in veterinary medicine. It is related to metabolic alterations and has been associated with intestinal microbiota dysbiosis. Studies have shown in both genetically obese and diet-induced mice, that a cecal microbiota from obese animals show environmental genetic tags, which encode enzymes involved in the degradation of polysaccharides and simple carbohydrate metabolism. Thus, a microbiota of obese individuals may be more efficient at digesting and metabolizing energy than lean individuals. Thus, the present study aims to characterize the microbiome and to evaluate the effects of microorganisms on the population of obese dogs included in a weight loss program. Ten dogs, females, castrated, aged between 1 and 8 years old, obese, body condition score (ECC) equal to or greater than 8 and with a percentage of body fat greater than 30%, determined from the deuterium isotope dilution method. Fecal samples will be collected at T0 (beginning of the study, obese group) and T20 (after loss of 20% of the initial body weight, lean group) and a control group. The third experimental group (control) consists of ten healthy, female, castrated dogs, aged between 1 and 8 years and ECC 4 or 5 and maximum body fat of 15%. By the end of the study, the total DNA will be extracted from the feces and this genetic material will be sequenced by the Illumina methodology. The observed abundances for each phylum and gender will be analyzed by a generalized linear model, considering binominal distribution and using logit link function. The model will include fixed group effects (control, obese and lean), as well as the random effects of animal and residue. All analyzes will be performed using the PROC GLIMMIX procedure from the Statistical Analysis System, version 9.3 (SAS Institute Inc., Cary, NC, USA).

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