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Abstract Chronic gastrointestinal (GI) diseases are the most common diseases in captive common marmosets. To understand the role of the microbiome in GI diseases, we characterized the gut microbiome of 91 healthy marmosets (303 samples) and 59 marmosets diagnosed with inflammatory bowel disease (IBD) (200 samples). Healthy marmosets exhibited “humanized,” Bacteroidetes-dominant microbiomes. After up to 2 years of standardized diet, housing and husbandry, marmoset microbiomes could be classified into four distinct marmoset sources based on Prevotella and Bacteroides levels. Using a random forest (RF) model, marmosets were classified by source with an accuracy of 93% with 100% sensitivity and 95% specificity using abundance data from 4 Prevotellaceae amplicon sequence variants (ASVs), as well as single ASVs from Coprobacter, Parabacteroides, Paraprevotella, Phascolarctobacterium, Oribacterium and Fusobacterium. A single dysbiotic IBD state was not found across all marmoset sources, but IBD was associated with lower alpha diversity and a lower Bacteroides:Prevotella copri ratio within each source. IBD was highest in a Prevotella-dominant cohort, and consistent with Prevotella-linked diseases, pro-inflammatory genes in the jejunum were upregulated. RF analysis of serum biomarkers identified serum calcium, hemoglobin and red blood cell (RBC) counts as potential biomarkers for marmoset IBD. This study characterizes the microbiome of healthy captive common marmosets and demonstrates that source-specific microbiomes can be retained despite standardized diets and husbandry practices. Marmosets with IBD had decreased alpha diversity and a shift in the ratio of Bacteroides:Prevotella copri compared to healthy marmosets.

Abstract Chronic gastrointestinal (GI) diseases are the most common diseases in captive common marmosets (Callithrix jacchus). Despite standardized housing, diet and husbandry, a recently described gastrointestinal syndrome characterized by duodenal ulcers and strictures was observed in a subset of marmosets sourced from the New England Primate Research Center. As changes in the gut microbiome have been associated with GI diseases, the gut microbiome of 52 healthy, non-stricture marmosets (153 samples) were compared to the gut microbiome of 21 captive marmosets diagnosed with a duodenal ulcer/stricture (57 samples). No significant changes were observed using alpha diversity metrics, and while the community structure was significantly different when comparing beta diversity between healthy and stricture cases, the results were inconclusive due to differences observed in the dispersion of both datasets. Differences in the abundance of individual taxa using ANCOM, as stricture-associated dysbiosis was characterized by Anaerobiospirillum loss and Clostridium perfringens increases. To identify microbial and serum biomarkers that could help classify stricture cases, we developed models using machine learning algorithms (random forest, classification and regression trees, support vector machines and k-nearest neighbors) to classify microbiome, serum chemistry or complete blood count (CBC) data. Random forest (RF) models were the most accurate models and correctly classified strictures using either 9 ASVs (amplicon sequence variants), 4 serum chemistry tests or 6 CBC tests. Based on the RF model and ANCOM results, C. perfringens was identified as a potential causative agent associated with the development of strictures. Clostridium perfringens was also isolated by microbiological culture in 4 of 9 duodenum samples from marmosets with histologically confirmed strictures. Due to the enrichment of C. perfringens in situ, we analyzed frozen duodenal tissues using both 16S microbiome profiling and RNAseq. Microbiome analysis of the duodenal tissues of 29 marmosets from the MIT colony confirmed an increased abundance of Clostridium in stricture cases. Comparison of the duodenal gene expression from stricture and non-stricture marmosets found enrichment of genes associated with intestinal absorption, and lipid metabolism, localization, and transport in stricture cases. Using machine learning, we identified increased abundance of C. perfringens, as a potential causative agent of GI disease and intestinal strictures in marmosets.