Abstract: FR-PO969
Metagenomic Analysis of Microbial Nanovesicle in Blood of Maintenance Hemodialysis Patients
Session Information
- Bioengineering and Informatics
November 03, 2017 | Location: Hall H, Morial Convention Center
Abstract Time: 10:00 AM - 10:00 AM
Category: Bioengineering and Informatics
- 101 Bioengineering and Informatics
Authors
- Jeon, Un Sil, Sheikh Khalifa Specialty Hospital, Ras Al Khaimah, United Arab Emirates
- Yang, Jinho, MD Healthcare Inc., Seoul, Korea (the Republic of)
- Yang, Seung Hee, Kidney Research Institute, Seoul National University, Seoul, Korea (the Republic of)
- Kim, Yoon-Keun, MD Healthcare Inc., Seoul, Korea (the Republic of)
Background
Gut dysbiosis in uremic patients is known to contribute to progression and complications of chronic kidney disease (CKD). Extracellular vesicles (EVs) excreted from bacteria contain not only bacterial DNA and RNA, but also endotoxins and other virulent proteins. EVs can enter systemic circulation through intestinal mucosal membrane freely and be key communication messengers in host-microbe communication in human diseases.
Methods
We performed metagenomic analysis of bacteria-derived EVs in blood of 20 maintenance hemodialysis (HD) patients (10 diabetic and 10 non-diabetic) and 20 healthy controls. EVs in human serum were isolated using the differential centrifugation method as described previously (Proteomics 2007;7:3143–3153). DNA was extracted from 1 ug of serum EVs, and 16S ribosomal RNA (16S rRNA) gene sequencing was performed using high-throughput 454 pyrosequencing after amplification of the V1–V3 region of the 16S rDNA. Taxonomy assignment was carried out by using UCLUST and QIIME against the 16sRNA sequence database in GreenGenes.
Results
The value of alpha-diversity was lower in HD patients than in healthy controls, which means HD patients had a lower diversity of microbiome than healthy controls. The value of beta-diversity was significantly different between HD patients and controls. At the level of Phylum, HD patients had a significant higher level of Acidobacteria EVs than controls, but a lower level of Proteobacteria EVs. At the level of Genus, we found 37 biomarkers which revealed different levels between HD patients and controls (29 elevated and 18 decreased EVs in HD patients). Streptococcus., Koribacteraceae(f), Ellin6513(o), and Burkholderia spp. EVs were higher in HD patients than in controls, and Enterobacteriaceae(f), Acinetobacter, Pseudomonas, Akkermansia, Proteus and Lactobacillus spp. EVs were lower in HD patients. However, there were no differences between diabetic and non-diabetic HD patients.
Conclusion
In conclusion, we observed significant differences in the composition and amounts of bacteria-derived EVs in blood between HD patients and healthy controls using metagenomic analysis. Metagenomic analysis of bacteria-derived EVs could be a useful tool to investigate microbial dysbiosis and biomarkers in CKD patients.