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

Visedthorn,Suthida; Klomkliew,Pavit; Sawaswong,Vorthon; Sivapornnukul,Pavaret; Chanchaem,Prangwalai; Saejew,Thunvarat; Pavatung,Preeyarat; Kanjanabuch,Talerngsak; Payungporn,Sunchai

doi:10.3892/br.2024.1790

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
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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
Published online on: May 14, 2024 https://doi.org/10.3892/br.2024.1790
Article Number: 102
Copyright: © Visedthorn et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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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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1	Akchurin OM: Chronic kidney disease and dietary measures to improve outcomes. Pediatr Clin North Am. 66:247–267. 2019.PubMed/NCBI View Article : Google Scholar
2	NIDDK: Peritoneal Dialysis. Journal 1950.
3	Zimmerman AM: Peritoneal dialysis: Increasing global utilization as an option for renal replacement therapy. J Glob Health. 9(020316)2019.PubMed/NCBI View Article : Google Scholar
4	Akoh JA: Peritoneal dialysis associated infections: An update on diagnosis and management. World J Nephrol. 1:106–122. 2012.PubMed/NCBI View Article : Google Scholar
5	Brook NR, White SA, Waller JR and Nicholson ML: The surgical management of peritoneal dialysis catheters. Ann R Coll Surg Engl. 86:190–195. 2004.PubMed/NCBI View Article : Google Scholar
6	Amato D, de Jesus Ventura M, Miranda G, Leaños B, Alcántara G, Hurtado ME and Paniagua R: Staphylococcal peritonitis in continuous ambulatory peritoneal dialysis: Colonization with identical strains at exit site, nose, and hands. Am J Kidney Dis. 37:43–48. 2001.PubMed/NCBI View Article : Google Scholar
7	Deng X, Achari A, Federman S, Yu G, Somasekar S, Bártolo I, Yagi S, Mbala-Kingebeni P, Kapetshi J, Ahuka-Mundeke S, et al: Metagenomic sequencing with spiked primer enrichment for viral diagnostics and genomic surveillance. Nat Microbiol. 5:443–454. 2020.PubMed/NCBI View Article : Google Scholar
8	Simner PJ, Miller S and Carroll KC: Understanding the promises and hurdles of metagenomic next-generation sequencing as a diagnostic tool for infectious diseases. Clin Infect Dis. 66:778–788. 2018.PubMed/NCBI View Article : Google Scholar
9	Rota PA, Oberste MS, Monroe SS, Nix WA, Campagnoli R, Icenogle JP, Peñaranda S, Bankamp B, Maher K, Chen MH, et al: Characterization of a novel coronavirus associated with severe acute respiratory syndrome. Science. 300:1394–1399. 2003.PubMed/NCBI View Article : Google Scholar
10	Greninger AL and Zerr DM: NGSocomial infections: High-Resolution views of hospital-acquired infections through genomic epidemiology. J Pediatric Infect Dis Soc. 10 (Supplement 4):S88–S95. 2021.PubMed/NCBI View Article : Google Scholar
11	Chiu CY and Miller SA: Clinical metagenomics. Nat Rev Genet. 20:341–355. 2019.PubMed/NCBI View Article : Google Scholar
12	Chiu CY: Viral pathogen discovery. Curr Opin Microbiol. 16:468–478. 2013.PubMed/NCBI View Article : Google Scholar
13	Gu W, Deng X, Lee M, Sucu YD, Arevalo S, Stryke D, Federman S, Gopez A, Reyes K, Zorn K, et al: Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids. Nat Med. 27:115–124. 2021.PubMed/NCBI View Article : Google Scholar
14	Greninger AL, Naccache SN, Federman S, Yu G, Mbala P, Bres V, Stryke D, Bouquet J, Somasekar S, Linnen JM, et al: Rapid metagenomic identification of viral pathogens in clinical samples by real-time nanopore sequencing analysis. Genome Med. 7(99)2015.PubMed/NCBI View Article : Google Scholar
15	Nie S, Zhang Q, Chen R, Lin L, Li Z, Sun Y, Huang J, Feng Z, Cao X, Ye K, et al: Rapid detection of pathogens of peritoneal dialysis-related peritonitis, especially in patients who have taken antibiotics, using metagenomic next-generation sequencing: A pilot study. Ren Fail. 45(2284229)2023.PubMed/NCBI View Article : Google Scholar
16	Ye P, Xie C, Wu C, Yu C, Chen Y, Liang Z, Chen Y, Chen Q and Kong Y: The application of metagenomic next-generation sequencing for detection of pathogens from dialysis effluent in peritoneal dialysis-associated peritonitis. Perit Dial Int. 42:585–590. 2022.PubMed/NCBI View Article : Google Scholar
17	Wick RR, Judd LM and Holt KE: Performance of neural network basecalling tools for Oxford Nanopore sequencing. Genome Biol. 20(129)2019.PubMed/NCBI View Article : Google Scholar
18	Lanfear R, Schalamun M, Kainer D, Wang W and Schwessinger B: MinIONQC: Fast and simple quality control for MinION sequencing data. Bioinformatics. 35:523–525. 2019.PubMed/NCBI View Article : Google Scholar
19	Rodriguez-Perez H, Ciuffreda L and Flores C: NanoCLUST: A species-level analysis of 16S rRNA nanopore sequencing data. Bioinformatics. 37:1600–1601. 2021.PubMed/NCBI View Article : Google Scholar
20	Cole JR, Chai B, Marsh TL, Farris RJ, Wang Q, Kulam SA, Chandra S, McGarrell DM, Schmidt TM, Garrity GM, et al: The ribosomal database project (RDP-II): Previewing a new autoaligner that allows regular updates and the new prokaryotic taxonomy. Nucleic Acids Res. 31:442–443. 2003.PubMed/NCBI View Article : Google Scholar
21	Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, et al: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 37:852–857. 2019.PubMed/NCBI View Article : Google Scholar
22	Gu Z, Eils R and Schlesner M: Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 32:2847–2849. 2016.PubMed/NCBI View Article : Google Scholar
23	Bradley CW, Flavell H, Raybould L, McCoy H, Dempster L, Holden E and Garvey MI: Reducing Escherichia coli bacteraemia associated with catheter-associated urinary tract infections in the secondary care setting. J Hosp Infect. 98:236–237. 2018.PubMed/NCBI View Article : Google Scholar
24	Eggimann P, Sax H and Pittet D: Catheter-related infections. Microbes Infect. 6:1033–1042. 2004.PubMed/NCBI View Article : Google Scholar
25	Fu Y, Chen Q, Xiong M, Zhao J, Shen S, Chen L, Pan Y, Li Z and Li Y: Clinical performance of nanopore targeted sequencing for diagnosing infectious diseases. Microbiol Spectr. 10(e0027022)2022.PubMed/NCBI View Article : Google Scholar
26	Midha MK, Wu M and Chiu KP: Long-read sequencing in deciphering human genetics to a greater depth. Hum Genet. 138:1201–1215. 2019.PubMed/NCBI View Article : Google Scholar
27	Matsuo Y, Komiya S, Yasumizu Y, Yasuoka Y, Mizushima K, Takagi T, Kryukov K, Fukuda A, Morimoto Y, Naito Y, et al: Full-length 16S rRNA gene amplicon analysis of human gut microbiota using MinION™ nanopore sequencing confers species-level resolution. BMC Microbiol. 21(35)2021.PubMed/NCBI View Article : Google Scholar
28	D'Andreano S, Cusco A and Francino O: Rapid and real-time identification of fungi up to species level with long amplicon nanopore sequencing from clinical samples. Biol Methods Protoc. 6(bpaa026)2020.PubMed/NCBI View Article : Google Scholar
29	Monger XC, Saucier L, Gilbert AA and Vincent AT: Stabilization of swine faecal samples influences taxonomic and functional results in microbiome analyses. MethodsX. 9(101716)2022.PubMed/NCBI View Article : Google Scholar
30	Menke S, Gillingham MA, Wilhelm K and Sommer S: Home-Made cost effective preservation buffer is a better alternative to commercial preservation methods for microbiome research. Front Microbiol. 8(102)2017.PubMed/NCBI View Article : Google Scholar
31	Jeong J, Yun K, Mun S, Chung WH, Choi SY, Nam YD, Lim MY, Hong CP, Park C, Ahn YJ and Han K: The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology. Sci Rep. 11(1727)2021.PubMed/NCBI View Article : Google Scholar
32	Shi Y, Wang G, Lau HC and Yu J: Metagenomic sequencing for microbial DNA in human samples: Emerging technological advances. Int J Mol Sci. 23(2181)2022.PubMed/NCBI View Article : Google Scholar
33	Simoes-Silva L, Araujo R, Pestana M, Soares-Silva I and Sampaio-Maia B: Peritoneal microbiome in end-stage renal disease patients and the impact of peritoneal dialysis therapy. Microorganisms. 8(173)2020.PubMed/NCBI View Article : Google Scholar
34	Vaziri ND, Wong J, Pahl M, Piceno YM, Yuan J, DeSantis TZ, Ni Z, Nguyen TH and Andersen GL: Chronic kidney disease alters intestinal microbial flora. Kidney Int. 83:308–315. 2013.PubMed/NCBI View Article : Google Scholar
35	Dzekova-Vidimliski P, Nikolov IG, Gjorgjievski N, Selim G, Trajceska L, Stojanoska A, Rambabova-Bushljetik I, Simeonov R and Stojkovski L: Peritoneal dialysis-related peritonitis: Rate, clinical outcomes and patient survival. Pril (Makedon Akad Nauk Umet Odd Med Nauki). 42:47–55. 2021.PubMed/NCBI View Article : Google Scholar
36	Feng X, Yang X, Yi C, Guo Q, Mao H, Jiang Z, Li Z, Chen D, Cui Y and Yu X: Escherichia coli Peritonitis in peritoneal dialysis: The prevalence, antibiotic resistance and clinical outcomes in a South China dialysis center. Perit Dial Int. 34:308–316. 2014.PubMed/NCBI View Article : Google Scholar
37	Chao CT, Lee SY, Yang WS, Chen HW, Fang CC, Yen CJ, Chiang CK, Hung KY and Huang JW: Viridans streptococci in peritoneal dialysis peritonitis: Clinical courses and long-term outcomes. Perit Dial Int. 35:333–341. 2015.PubMed/NCBI View Article : Google Scholar
38	Salzer WL: Peritoneal dialysis-related peritonitis: Challenges and solutions. Int J Nephrol Renovasc Dis. 11:173–186. 2018.PubMed/NCBI View Article : Google Scholar
39	Gadola L, Poggi C, Dominguez P, Poggio MV, Lungo E and Cardozo C: Risk factors and prevention of peritoneal dialysis-related peritonitis. Perit Dial Int. 39:119–125. 2019.PubMed/NCBI View Article : Google Scholar
40	Yan Y, Chai X, Chen Y and Zhang X: The fulminating course of infection caused by shewanella algae: A case report. Infect Drug Resist. 15:1645–1650. 2022.PubMed/NCBI View Article : Google Scholar
41	Hughes G, Pallard C, Chavdab S and Davida MD: The first case report of human infection with Phyllobacterium myrsinacearum causing spondylodiscitis. Clin Infec Pract. 7-8(100029)2020.