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ARS Home » Southeast Area » Little Rock, Arkansas » Arkansas Children's Nutrition Center » Research » Publications at this Location » Publication #348626
Title: Dehydroabietic Acid (DHAA) distinguishes early vs late stages of diabetes and is associated with bacterial species and bacterial metabolic pathways in the UC Davis-Type 2 Diabetes (UCD-T2DM) rat model

Author
item PICCOLO, BRIAN - Arkansas Children'S Nutrition Research Center (ACNC)
item GRAHAM, JAMES - University Of California, Davis
item STANHOPE, KIMBER - University Of California, Davis
item WANKHADE, UMESH - Arkansas Children'S Nutrition Research Center (ACNC)
item NOOKAEW, INTAWAT - University Of Arkansas
item MERCER, KELLY - Arkansas Children'S Nutrition Research Center (ACNC)
item CHINTAPALLI, SREE - Arkansas Children'S Nutrition Research Center (ACNC)
item SHANKAR, KARTIK - Arkansas Children'S Nutrition Research Center (ACNC)
item HAVEL, PETER - University Of California, Davis
item Ferruzzi, Mario

Submitted to: Keystone Symposia
Publication Type: Abstract Only
Publication Acceptance Date: 12/5/2017
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: The gut microbiome is altered in obesity and diabetes, but the molecular signals linking gut microbes and host metabolic regulation have not been established. Our aim was to identify associations between the metagenome and metabolome during the progression of diabetes. Cecal contents were collected from age-matched, chow-fed male UCD-T2DM Rats before the onset of diabetes (pre-diabetic PD, n = 15); 2 wk recently-diabetic (RD, n = 10); 3 mo (D3M n = 11); and 6 mo (D6M n = 7) post-onset of diabetes. Whole-genome shotgun metagenomic analyses of cecal DNA was used to assess microbial species-level taxonomic abundance and functional gene content. Libraries were sequenced using Illumina (~2.5 GB/sample) and processed using in-house and public scripts. Reads were processed using MEGAN6 for taxonomic and functional annotation using the NCBI protein and SEED subsystem databases. Cecal metabolites were identified by GC-QTOF-MS. PLS-DA models performed most accurately in 2-class models predicting early (PD + RD) vs. late (D3M + D6M) stages of diabetes. DHAA had the largest metabolite difference between early and later stages of diabetes (-2.5 log2 fold decrease in later relative to early) and was positively correlated to L vaginalis, while negatively correlated to B timonensis and Clostridium sp. DHAA was also negatively correlated to 23 SEED subpathways related to bacterial carbohydrate metabolism, membrane transport, virulence, and others. In summary, host metabolic status alters the cecal metabolome and metagenome when comparing early and later stages of diabetes UCD-T2DM Rats. DHAA was the strongest metabolite predictor and linked diabetes-specific changes in microbial taxa and functional genetic pathways.