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

  • Authors:
    • Suthida Visedthorn
    • Pavit Klomkliew
    • Vorthon Sawaswong
    • Pavaret Sivapornnukul
    • Prangwalai Chanchaem
    • Thunvarat Saejew
    • Preeyarat Pavatung
    • Talerngsak Kanjanabuch
    • Sunchai Payungporn
  • View Affiliations / Copyright

    Affiliations: 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, Center of Excellence in Kidney Metabolic Disorders, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
    Copyright: © Visedthorn et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 102
    |
    Published online on: May 14, 2024
       https://doi.org/10.3892/br.2024.1790
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Abstract

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.
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Copy and paste a formatted citation
Spandidos Publications style
Visedthorn S, Klomkliew P, Sawaswong V, Sivapornnukul P, Chanchaem P, Saejew T, Pavatung P, Kanjanabuch T and Payungporn S: Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease. Biomed Rep 21: 102, 2024.
APA
Visedthorn, S., Klomkliew, P., Sawaswong, V., Sivapornnukul, P., Chanchaem, P., Saejew, T. ... Payungporn, S. (2024). Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease. Biomedical Reports, 21, 102. https://doi.org/10.3892/br.2024.1790
MLA
Visedthorn, S., Klomkliew, P., Sawaswong, V., Sivapornnukul, P., Chanchaem, P., Saejew, T., Pavatung, P., Kanjanabuch, T., Payungporn, S."Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease". Biomedical Reports 21.1 (2024): 102.
Chicago
Visedthorn, S., Klomkliew, P., Sawaswong, V., Sivapornnukul, P., Chanchaem, P., Saejew, T., Pavatung, P., Kanjanabuch, T., Payungporn, S."Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease". Biomedical Reports 21, no. 1 (2024): 102. https://doi.org/10.3892/br.2024.1790
Copy and paste a formatted citation
x
Spandidos Publications style
Visedthorn S, Klomkliew P, Sawaswong V, Sivapornnukul P, Chanchaem P, Saejew T, Pavatung P, Kanjanabuch T and Payungporn S: Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease. Biomed Rep 21: 102, 2024.
APA
Visedthorn, S., Klomkliew, P., Sawaswong, V., Sivapornnukul, P., Chanchaem, P., Saejew, T. ... Payungporn, S. (2024). Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease. Biomedical Reports, 21, 102. https://doi.org/10.3892/br.2024.1790
MLA
Visedthorn, S., Klomkliew, P., Sawaswong, V., Sivapornnukul, P., Chanchaem, P., Saejew, T., Pavatung, P., Kanjanabuch, T., Payungporn, S."Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease". Biomedical Reports 21.1 (2024): 102.
Chicago
Visedthorn, S., Klomkliew, P., Sawaswong, V., Sivapornnukul, P., Chanchaem, P., Saejew, T., Pavatung, P., Kanjanabuch, T., Payungporn, S."Bacterial classification based on metagenomic analysis in peritoneal dialysis effluent of patients with chronic kidney disease". Biomedical Reports 21, no. 1 (2024): 102. https://doi.org/10.3892/br.2024.1790
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