Dataset Information

Deciphering bacterial community changes in zucker diabetic fatty rats based on 16S rRNA gene sequences analysis.

ABSTRACT: The aim of the present pilot study was deciphering bacterial community changes in Zucker diabetic fatty rats (ZDF rats), a model of type 2 diabetes. Recent studies unmasked that the status of gastrointestinal tract microbiota has a marked impact on nutrition-related syndromes such as obesity and type-2 diabetes (T2D). In this study, samples taken from the gastrointestinal tracts (GI tracts) of ZDF and their lean littermates (ZL rats) were subjected to 16S rRNA gene sequence-based analysis to examine the characteristic bacterial communities, including those located in the stomach, duodenum, jejunum, ileum, cecum and feces. Results revealed that the Firmicutes/Bacteroidetes ratio was increased and greater numbers of Lactobacillus were detected along GI tracts in ZDF rats compared to ZL rats. In conclusion, this work is the first study to systematically characterize bacterial communities along ZDF rat GI tract and provides substantial evidence supporting a prospective strategy to alter the GI microbial communities improving obesity and T2D.

SUBMITTER: Gu C

PROVIDER: S-EPMC5226482 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Deciphering bacterial community changes in zucker diabetic fatty rats based on 16S rRNA gene sequences analysis.

Gu Chunyan C Yang Ye Y Xiang Hong H Li Shu S Liang Lina L Sui Hua H Zhan Libin L Lu Xiaoguang X

Oncotarget 20160801 31

The aim of the present pilot study was deciphering bacterial community changes in Zucker diabetic fatty rats (ZDF rats), a model of type 2 diabetes. Recent studies unmasked that the status of gastrointestinal tract microbiota has a marked impact on nutrition-related syndromes such as obesity and type-2 diabetes (T2D). In this study, samples taken from the gastrointestinal tracts (GI tracts) of ZDF and their lean littermates (ZL rats) were subjected to 16S rRNA gene sequence-based analysis to exa ...[more]

PMID: 27418144

Similar Datasets

Project description:Diabetes is a very strong predictor of chronic systemic vascular diseases and acute cardiovascular events. Recently, associations between metabolic disorders and pulmonary hypertension have also been reported in both humans and animal models. In order to get some further insight into the relationship of pulmonary hypertension with obesity, insulin resistance and hyperglycemia, herein we have used the Zucker diabetic fatty rats (ZDF/clr-lepr fa) at 20 weeks fed a standard diet and compared to their lean Zucker littermates (ZL). ZDF rats were obese, had elevated plasma glucose levels and insulin resistance, i.e. a clinically relevant model of type 2 diabetes. They presented elevated systolic, diastolic and mean pulmonary arterial pressures and a parallel increase in the Fulton index. Systemic arterial pressures were also increased but the left ventricle plus septum weight was similar in both groups and the heart rate was reduced. Wall media thickening was observed in the small pulmonary arteries from the ZDF rats. Isolated pulmonary arteries mounted in a wire myograph showed similar vasoconstrictor responses to phenylephrine and 5-HT and similar responses to the endothelium-dependent vasodilator acetylcholine. However, the iNOS inhibitor 1400W enhanced the vasoconstrictor responses in ZDF but not in ZL rats. The protein expression of eNOS and iNOS was not significantly different in the lungs of the two groups. The lung expression of Bmpr2 mRNA was downregulated. However, the mRNA expression of Kcna5, Kcnk3, Kcnq1, Kcnq4 or Kcnq5, which encode for the potassium channels Kv1.5, TASK-1, Kv7.1, Kv7.4 and Kv7.5, respectively, was similar in ZL and ZDF rats. In conclusion, ZDF rats show increased pulmonary arterial pressure, right ventricular hypertrophy, pulmonary arterial medial thickening and downregulated lung Bmpr2 despite leptin resistance. These changes were mild but are consistent with the view that diabetes is a risk factor for pulmonary hypertension.

Project description:Fermented fruits and vegetables play an important role in safeguarding food security world-wide. Recently, robust sequencing-based microbial community analysis platforms have improved microbial safety assessment. This study aimed to examine the composition of bacteria and evaluate the bacterial safety of fermented fruit products using high-throughput 16S-rRNA metagenomic analysis. The operational taxonomic unit-based taxonomic classification of DNA sequences revealed 53 bacterial genera. However, the amplicon sequencing variant (ASV)-based clustering revealed 43 classifiable bacterial genera. Taxonomic classifications revealed that the abundance of Sphingomonas, which was the predominant genus in the majority of tested samples, was more than 85-90% among the total identified bacterial community in most samples. Among these identified genera, 13 low abundance genera were potential opportunistic pathogens, including Acinetobacter, Bacillus, Staphylococcus, Clostridium, Klebsiella, Mycobacterium, Ochrobactrum, Chryseobacterium, Stenotrophomonas, and Streptococcus. Of these 13 genera, 13 major opportunistic pathogenic species were validated using polymerase chain reaction. The pathogens were not detected in the samples of different stages and the final products of fermentation, except in one sample from the first stage of fermentation in which S. aureus was detected. This finding was consistent with that of ASV-based taxonomic classification according to which S. aureus was detected only in the sample from the first stage of fermentation. However, S. aureus was not significantly correlated with the human disease pathways. These results indicated that fermentation is a reliable and safe process as pathogenic bacteria were not detected in the fermentation products. The hybrid method reported in this study can be used simultaneously to evaluate the bacterial diversity, their functional predictions and safety assessment of novel fermentation products. Additionally, this hybrid method does not involve the random detection of pathogens, which can markedly decrease the time of detection and food safety verification. Furthermore, this hybrid method can be used for the quality control of products and the identification of external contamination.

Dataset Information

Deciphering bacterial community changes in zucker diabetic fatty rats based on 16S rRNA gene sequences analysis.

Publications

Deciphering bacterial community changes in zucker diabetic fatty rats based on 16S rRNA gene sequences analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets