Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease.

Autor: Visedthorn S; Medical Biochemistry Program, Department of Biochemistry, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.; Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand., Klomkliew P; Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand., Sawaswong V; Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.; Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok 10400, Thailand., Sivapornnukul P; Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand., Chanchaem P; Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand., Saejew T; Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand., Pavatung P; Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand., Kanjanabuch T; Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.; Division of Nephrology, Department of Internal Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.; CAPD Excellence Center, King Chulalongkorn Memorial Hospital, Bangkok 10330, Thailand., Payungporn S; Center of Excellence in Systems Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.; Department of Biochemistry, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand.
Jazyk: angličtina
Zdroj: Biomedical reports [Biomed Rep] 2024 May 14; Vol. 21 (1), pp. 102. Date of Electronic Publication: 2024 May 14 (Print Publication: 2024).
DOI: 10.3892/br.2024.1790
Abstrakt: End-stage kidney disease (ESKD) is the final stage of chronic kidney disease (CKD), in which long-term damage has been caused to the kidneys to the extent that they are no longer able to filter the blood of waste and extra fluid. Peritoneal dialysis (PD) is one of the treatments that remove waste products from the blood through the peritoneum which can improve the quality of life for patients with ESKD. However, PD-associated peritonitis is an important complication that contributes to the mortality of patients, and the detection of bacterial pathogens is associated with a high culture-negative rate. The present study aimed to apply a metagenomic approach for the bacterial identification in the PD effluent (PDE) of patients with CKD based on 16S ribosomal DNA sequencing. As a result of this investigation, five major bacteria species, namely Escherichia coli , Phyllobacterium myrsinacearum , Streptococcus gallolyticus , Staphylococcus epidermidis and Shewanella algae , were observed in PDE samples. Taken together, the findings of the present study have suggested that this metagenomic approach could provide a greater potential for bacterial taxonomic identification compared with traditional culture methods, suggesting that this is a practical and culture-independent alternative approach that will offer a novel preventative infectious strategy in patients with CDK.
Competing Interests: The authors declare that they have no competing interests.
(Copyright: © 2024 Visedthorn et al.)
Databáze: MEDLINE
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