Characterizing the Gut Microbiota of Obese Cats and Exploring the Association Between Gut Microbiota and Memory in Dogs Using Metagenomic Sequencing

Abstract

The gut microbiota plays a crucial role in the health and physiology of animals, significantly affecting various biological processes and disease mechanisms. However, there are limited studies on the gut microbiota in cats and dogs, especially regarding the specific characteristics of the gut microbiota in obese cats and its relationship to memory performance in dogs. This dissertation aims to address these shortcomings by characterizing the gut microbiota of obese cats and exploring the association between gut microbiota and memory in dogs using metagenomic sequencing. The first part of this study focuses on the importance of employing appropriate fecal sample collection methods to ensure accurate characterization of the gut microbiota in cats. For domestic cats, lubricants are often necessary to obtain an adequate number of samples. We evaluated the impact of mineral oil lubrication during the collection of cat stool samples on subsequent gut microbiome analysis. We also compared the two primary methods of collecting cat fecal samples using a fecal ring versus using a litter box. This study aims to provide valuable insights into the impact of different fecal collection methods and to assist in the development of standardized protocols for collecting fecal samples in feline microbiome studies. In addition, metagenomic analysis of the gut microbiota in obese cats was performed to identify key microbial species and their potential roles in obesity-related metabolic dysregulation. We observed a significant reduction in microbial diversity in obese cat gut microbiota, suggesting potential dysbiosis. A panel of seven significantly altered, highly abundant species can serve as a microbiome indicator of obesity. Our findings in the obese cat microbiome composition, abundance, and functional capacities provide new insights into feline obesity. Finally, this dissertation also explored the potential links between gut microbiota composition and memory performance in dogs. A single bacterial species, Bifidobacterium pseudolongum, was identified and confirmed to be correlated with memory performance in dogs. Using a random forest regression model, we found that the abundance of 17 bacterial taxa in the microbiome exhibited a stronger predictive capacity for memory performance. Our findings offer valuable insights into microbiome underpinnings of mammalian cognitive functions and suggest avenues for developing psychobiotics to enhance canine memory and learning. Overall, this dissertation contributes to a deeper understanding of the gut microbiota in both cats and dogs, highlighting its relevance in veterinary medicine and its potential implications for improving health and treatment strategies in these companion animals.