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Evidence shows urine specimens from different women have different populations of bacteria. The co-occurrence of hypertension and hyperlipidemia in those with diabetes may alter the composition of urine and the microenviroment of the bladder in which bacteria live. The aim of this study was to characterize the urinary microbiota in women with type 2 diabetes mellitus only and those with diabetes plus hypertension and/or hyperlipidemia, and to explore whether the composition of the urinary microbiota is affected by fasting blood glucose, blood pressure, and blood lipids. We enrolled 28 individuals with diabetes only, 24 with diabetes plus hypertension, 7 with diabetes plus hyperlipidemia, and 11 with diabetes plus both hypertension and hyperlipidemia. Modified midstream urine collection technique was designed to obtain urine specimens. Bacterial genomic DNA was isolated using magnetic beads and the urinary microbiota was analyzed using the Illumina MiSeq Sequencing System based on the V3-V4 hypervariable regions of the 16S rRNA gene. Among the four cohorts, the diabetes plus hypertension cohort had the highest relative abundance of Proteobacteria. In contrast, the diabetes plus hyperlipidemia cohort had the lowest relative abundance of Proteobacteria. In addition, Escherichia and Gardnerella were not found in the diabetes plus hyperlipidemia cohort but they were found in all of the other cohorts. Cetobacterium was only present in the diabetes plus hypertension cohort. The most abundant bacteria in the diabetes only and diabetes plus hyperlipidemia cohorts was Lactobacillus, while Prevotella was the most abundant bacteria in the diabetes plus hypertension and diabetes plus hypertension and hyperlipidemia cohorts. Moreover, the relative abundance of Lactobacillus was significantly lower in the diabetes plus hypertension cohort than in the diabetes only and diabetes plus hyperlipidemia cohorts. Several bacteria were correlated with the participants' fasting blood glucose, blood pressure, and blood lipids. In conclusion, hypertension and/or hyperlipidemia and other patient factors can affect the composition of the urinary microbiota in those with diabetes. The insights from this study could be used to develop microbiota-based treatment for comorbid conditions, including urinary tract infections, in those with diabetes.
Pubmed ID: 28316574
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Database of biological data related to a single initiative, originating from a single organization or from a consortium. A BioProject record provides users a single place to find links to the diverse data types generated for that project. It is a searchable collection of complete and incomplete (in-progress) large-scale sequencing, assembly, annotation, and mapping projects for cellular organisms. Submissions are supported by a web-based Submission Portal. The database facilitates organization and classification of project data submitted to NCBI, EBI and DDBJ databases that captures descriptive information about research projects that result in high volume submissions to archival databases, ties together related data across multiple archives and serves as a central portal by which to inform users of data availability. BioProject records link to corresponding data stored in archival repositories. The BioProject resource is a redesigned, expanded, replacement of the NCBI Genome Project resource. The redesign adds tracking of several data elements including more precise information about a project''''s scope, material, and objectives. Genome Project identifiers are retained in the BioProject as the ID value for a record, and an Accession number has been added. Database content is exchanged with other members of the International Nucleotide Sequence Database Collaboration (INSDC). BioProject is accessible via FTP.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.
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