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

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.

Serum Galactomannan: A Predictor of Poor Outcomes in Peritoneal Dialysis Patients With Fungal Peritonitis.

Introduction: The potential value of serum galactomannan index (GMI) in monitoring treatment response in patients with fungal peritonitis who are receiving peritoneal dialysis (PD) was assessed in the present study. Methods: The study included all Thailand fungal PD-related infectious complications surveillance (MycoPDICS) DATA study participants who had timely PD catheter removal and availability of both baseline and ≥2 subsequent serum GMI measurements after starting antifungal therapy (if available). Serum GMI was assessed by direct double-sandwich enzyme-linked immunosorbent assay with reference to positive and negative control samples. Comparisons of categorical variables among groups were analyzed by Fisher's exact test for categorical data and the Wilcoxon rank-sum test for continuous variables. Mortality outcomes were analyzed by survival analyses using Kaplan-Meier curves with Log-rank test. Results: Seventy-six (46%) of 166 participants from 21 PD centers between 2018 and 2022 were included. The median age was 58 (50-65) years, and a half of the patients (50%) had type II diabetes. Nineteen (25%) and 57 (75%) episodes were caused by yeast and mold, respectively. Death occurred in 11 (14%) patients at 3 months, and no differences were observed in demographics, laboratories, treatment characteristics, or in baseline serum GMI between those who died and those who survived. Serum GMI progressively declined over the follow-up period after the completion of treatment. Patients who died had significantly higher posttreatment serum GMI levels and were more likely to have positive GMI after treatment. Conclusion: Serum GMI is an excellent biomarker for risk stratification and treatment response monitoring in patients on PD with fungal peritonitis.

The culture from peritoneal dialysis catheter enhances yield of microorganism identification in peritoneal dialysis-related peritonitis.

An additional yield of culture from the removed peritoneal dialysis (PD) catheter in diagnosis of pathogen causing refractory peritonitis was assessed in 118 eligible patients from 7 PD centers. Peritoneal dialysis fluid (PDF) culture identified organisms in 86 (72.9%) patients, while the catheter culture identified organisms in 55 (46.6%) patients. PD catheter culture could additionally identify organisms in 19 patients whose PDF culture were negative, increasing the positive culture rate to 89%, in other word 16.1% reducing the culture-negative rate. PD catheter culture provided additional yield, especially in fungal and enterococcal infections.

Multiple extracellular vesicle types in peritoneal dialysis effluent are prominent and contain known biomarkers.

Peritoneal dialysis inevitability results in activation of inflammatory processes and its efficiency is highly variable between patients. An improved method to isolate biomarkers and study pathophysiological mechanisms in peritoneal dialysis effluent (PDE) is expected to be of much benefit for the development of this treatment approach and help with patient management. Extracellular vesicles (EVs) are released as part of normal cellular processes. Their proteome is expected to reflect both type and health of their cell of origin. Although there is a significant interest in using EVs for "liquid biopsies", little is reported of their presence or composition in plentiful dialysis waste fluids, including peritoneal dialysis effluent (PDE). Here we determined the presence of EVs in PDE and subsequently characterized their proteome. EVs were first isolated from PDE using differential centrifugation, then a further enrichment using size exclusion chromatography (SEC) was performed. The presence of EVs was demonstrated using transmission electron microscopy, and their particle counts were investigated using nanoparticle tracking analysis and dynamic light scattering. Using tandem mass spectrometry, marker proteins from three types of EVs i.e. apoptotic bodies, ectosomes, and exosomes were identified. The proteomic results demonstrated that the isolation of EVs by differential centrifugation helped enrich for over 2,000 proteins normally masked by abundant proteins in PDE such as albumin and SEC markedly further improved the isolation of low abundant proteins. Gene ontology analysis of all identified proteins showed the marked enrichment of exosome and membrane-associated proteins. Over 3,700 proteins were identified in total, including many proteins with known roles in peritoneal pathophysiology. This study demonstrated the prominence of EVs in PDE and their potential value as a source of biomarkers for peritoneal dialysis patients.