735 Altered intestinal microbial composition as a potential biomarker of dysregulated immunity in type 1 diabetes mellitus.
Wednesday November 18, 2015 from 11:00 to 12:30
Plenary Room 1

Kenneth L. Brayman, United States

Professor of Surgery, Medicine and Biomedical Engineering

Surgery, Transplant Division

University of Virginia


Altered intestinal microbial composition as a potential biomarker of dysregulated immunity in type 1 diabetes mellitus

Preeti Chhabra1, Anthony Spano2, Tiantian Ren2, Martin Wu2, Michael Timko2, Kenneth Brayman1.

1Department of Surgery, University of Virginia, Charlottesville, VA, United States; 2Department of Biology, University of Virginia, Charlottesville, VA, United States

Goal: Beta-cell destruction results due to a failure of immune-regulation in type 1 diabetes (T1D). We investigated alterations in the intestinal microbiome composition as a potential biomarker for predicting the risk of developing T1D.
Methods: Experiment 1: Female non-obese diabetic (NOD) littermate mice were divided into 3 groups: non-diabetic mice (4-5weeks old, n=5, blood glucose BG 90-160mg/dL); prehyperglycemic mice (≥12 weeks old, n=6; BG 170-250mg/dL) and diabetic mice (15-23 weeks old, n=6, BG≥250mg/dL). Experiment 2: Female NOD littermate mice were divided into a) 4-5wks old non-diabetic mice (n=5, BG 90-160mg/dL); b) 9-12 wks old prehyperglycemic-1 mice  (n=5, BG 90-165mg/dL) that are considered “high-risk, predisposed to diabetes”); ≥13 wks old prehyperglycemic-2 mice (n=5, BG170-250mg/dL, considered new-onset diabetes); and d) ≥13 wks old diabetic mice (n=5, BG≥20mg/dL, established diabetes). QIAamp DNA Stool Mini Kit was used to purify bacterial DNA from cecum contents, followed by further purification with a PCR clean-up kit. 16S rRNA libraries were prepared and deep-sequenced using Illumina platform (Genewiz). Primers targeted the hypervariable V3, V4, and V5 regions of the 16S rRNA gene using next generation amplicon sequencing. Species identification and relative abundance calculation was performed. Principal Coordinate Analysis (PCoA) was used to visualize dissimilarities between the groups (KiNG software).
Results: An increase in Bacteroidetes and a decrease in Firmicutes was observed with progression of T1D development. The genera Bacteroides, Acetivibrio and Butyrivibrio demonstrated significant increase with establishment of T1D. An apparent increase in Anaerostipes, Candidatus azobacteroides, Prevotella and Rosebura was also observed. In contrast, the genera Oscillospora, Anaeroplasma, Eubacterium and Paludibacter were significantly decreased. The PCoA plot comparing differentially abundant bacterial families across the different groups demonstrated clear-cut clusters representing differences between control, prehyperglycemic and diabetic mice groups. Noteworthy, the “high-risk, predisposed to diabetes” prehyperglycemic-1 group had a distinct microbial composition. Age-matched, 'yet to become diabetic' mice fell in the same cluster as the diabetic mice, predicting that these diabetes-prone mice would become diabetic in time. Experiments are currently underway using a larger sample size and a non-diabetes prone mouse model as control for age-associated changes in microbiome.
Conclusions: Our data clearly indicates that the microbiome signature profile of the prehyperglycemic-1, “high-risk, predisposed to diabetes”  NOD mice group can be used potentially as a biomarker for predicting the development of T1D. Also, the microbial composition of the prehyperglycemic-2, “new onset T1D” mice group could be used for diagnosis and that of the diabetic group to study the efficacy of treatments. Thus, the identified changes in the intestinal microbiome composition have significant clinical potential for T1D risk prediction and are extremely relevant in the context of defective immune-regulation in allograft rejection and development of immunologic unresponsiveness.

Focus to Cure Diabetes Foundation.

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