4.5 Article

Characterizing the gut microbiota in patients with chronic kidney disease

Journal

POSTGRADUATE MEDICINE
Volume 132, Issue 6, Pages 495-505

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/00325481.2020.1744335

Keywords

Chronic kidney disease; gut microbiota; fecal sample; bacterial diversity; 16S rDNA sequencing

Funding

  1. National Natural Science Foundation of China [81770739, 81703592]

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Objectives: Emerging evidence suggests that gut microbiota dysbiosis plays a critical role in chronic kidney disease (CKD). However, the relationship between altered gut microbiome profiles and disease severity remains unclear. In this study, we sought to characterize the gut microbiota in CKD patients compared to healthy controls, and to explore potential relationships between gut microbiota composition and disease severity. Methods: Fecal samples were collected from 95 patients at different stages of CKD (non-dialysis patients from stage 1 to 5) and 20 healthy controls. Bacterial DNA was extracted for 16S ribosomal DNA sequencing targeting the V3-V4 region. The diversity and relative abundance of gut microbiota were analyzed as outcome indicators. Results: Differences were observed in the microbial composition and diversity of fecal samples from CKD patients and healthy controls. Specifically, disease severity was found to alter gut microbiota composition. Compared to that in healthy controls, CKD patients showed an increased abundance of Proteobacteria and decreased Synergistetes, most notably in disease stage 5. Lower levels of butyrate-producing bacteria and higher levels of potential pathogens were also detected in CKD patients. Further, Pyramidobacter and Prevotellaceae_UCG-001 were significantly decreased in the CKD1 group compared with healthy controls. Notably, nine microbial genera, including Escherichia-Shigella, Parabacteroides, Roseburia, rectale_group, Ruminococcaceae_NK4A214_group, Prevotellaceae_UCG.001, Hungatella, Intestinimonas, and Pyramidobacter, identified using a random forest model, distinguished between patients with CKD and healthy controls with high accuracy. Functional analysis also revealed that fatty acid and inositol phosphate metabolism were enriched in the CKD group, while aminoacyl-tRNA biosynthesis, oxidative phosphorylation, phenylalanine, tyrosine, and tryptophan biosynthesis, thiamine metabolism, pantothenate, and CoA biosynthesis, as well as valine, leucine, and isoleucine biosynthesis were enriched in healthy controls. Conclusion: Gut microbiota composition and function are associated with CKD severity. And, specific gut microbes are potentially helpful for CKD early diagnosis and prognosis monitoring.

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