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NDT Advance Access originally published online on April 19, 2008
Nephrology Dialysis Transplantation 2008 23(7):2402-2405; doi:10.1093/ndt/gfn212
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© The Author [2008]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org


Proteomic profiling and identification in peritoneal fluid of children treated by peritoneal dialysis

Renske Raaijmakers1, Wendy Pluk2, Cornelis H. Schröder3, Jolein Gloerich2, Elisabeth A.M. Cornelissen1, Hans J.C.T. Wessels4, Johannes L. Willems5, Leo A.H. Monnens1 and Lambert P.W.J. van den Heuvel1,2,4

1 Department of Paediatric Nephrology 2 Laboratory of Paediatrics and Neurology, Nijmegen Proteomics Facility, Radboud University Nijmegen Medical Centre, Nijmegen 3 Department of Paediatric Nephrology, University Medical Centre Utrecht, Utrecht 4 Nijmegen Centre for Mitochondrial Disorders 5 Department of Clinical Chemistry, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

Correspondence and offprint requests to: Renske Raaijmakers, Paediatric Nephrology 833, UMC St Radboud, PO Box 9101, 6500 HB Nijmegen, The Netherlands. Tel: +31-24-3666292; Fax: +31-24-3619348; E-mail: r.raaijmakers{at}cukz.umcn.nl



   Abstract
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 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 Supplementary data
 References
 
Background. Proteomic technologies offer a high-throughput analysis of the expression of proteins in biological samples. The global analysis of the proteins in peritoneal dialysis (PD) fluid will provide a better understanding of the biological processes of the peritoneal membrane.

Methods. The dialysate of nine paediatric PD patients was collected from peritoneal equilibrium tests with 3.86% glucose. Proteins were separated on a 10% SDS–PAGE gel and in-gel digested with trypsin. Peptide mixtures were analysed using nanoLC-MS/MS and results were searched against the NCBI database.

Results. A total number of 189 proteins were identified in the PD fluid of nine patients, with 88 proteins shared by all patients. These 88 proteins accounted for 47% of the identified proteins and >90% of the total protein content in the analysed samples. Proteins were subdivided into eight different classes according to function.

Conclusions. This study gives a representative overview of the proteins present in PD fluid. The proteins in PD fluid reflect plasma proteins as well as local peritoneal processes. Potentially interesting proteins are revealed.

Keywords: mass spectrometry; peritoneal dialysis; proteomics; paediatric



   Introduction
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 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 Supplementary data
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The proteome is the entire set of proteins expressed in a defined biological sample. With the combined techniques of liquid chromatography and mass spectrometry (LC-MS/MS) high-throughput protein profiling and identification can be performed [1,2]. In the field of nephrology the proteomic mapping of human urine [3,4] and the human kidney have been performed [5], as well as more detailed profiling of kidney glomerulus [6] and podocytes [7]. A representative overview of the proteome of peritoneal fluid has not been given so far.



   Subjects and methods
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 Introduction
 Subjects and methods
Results
 Discussion
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Patient samples
The dialysate of nine paediatric patients was collected from 2-h dwells during a peritoneal equilibrium test (PET) and stored at –20°C. None of the patients suffered from peritonitis in the 3 months prior to the collection. Patient and fluid characteristics are shown in Table 1. Experimental procedures and complementary information on the techniques used is available as supplementary material. The protein concentration in the peritoneal dialysis (PD) fluid was measured and from each sample 40-µg protein was taken for analysis. The samples were run on a 10% SDS–PAGE gel, each gel lane was cut into five slices and the proteins were reduced, alkylated and in-gel digested with trypsin overnight. Subsequently, peptides were extracted from the gel with 2% trifluoroacetic acid. For each sample, 5 µl of the peptide mixture was separated on an Agilent 1100 liquid chromatography (LC) system (Agilent, Palo Alto, CA, USA). Bound peptides were eluted from the column using an increasing acetonitrile gradient. Mass spectrometric analyses were performed in a hybrid linear ion trap Fourier transform ion cyclotron resonance mass spectrometer (LIT FT-ICR MS). All samples were measured twice to reduce experimental variation. The mass spectrometry data files were searched against the NCBI database (version 20070212, www.ncbi.nlm.nih.gov) using the Mascot search programme, version 2.1. Protein identifications were validated and clustered using the PROVALT [8] algorithm to achieve a false-discovery rate of <1%. Gene ontology classifications [9] were made with ProteinCenter (www.proxeon.com). To provide an estimation of protein concentration, exponentially modified protein abundance index (emPAI) values were calculated for the identified proteins using the method as described by Ishihama et al. [10] and validated by Yang et al. [11]


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  		Table 1 Characteristics of patients and peritoneal dialysis (PD) fluids used in the present study

 


   Results
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 Subjects and methods
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Discussion
 Supplementary data
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A total number of 189 proteins were identified in the PD fluid of the nine paediatric patients after the measurement of all samples in duplicate, with 88 proteins (47%) shared by all the patients (supplementary Table A). Keratins were excluded. All isoforms and hypothetical alternatives of the observed proteins are listed in supplementary Table B. The 88 shared proteins accounted for >90% of the total protein content, as was calculated by emPAI (Table 2). The proteins were divided according to their physiological cellular localization (Figure 1). The majority of the identified proteins were extracellular matrix proteins, considerably higher than in the plasma proteome (84% versus 11%, respectively). To give more insight into the aetiology and function of the shared proteins they were classified according to their function in eight different classes (Table 3 and supplementary Table A).


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  		Table 2 Distribution of emPAI (exponentially modified protein abundancy index) values (%) between the shared proteins and the other proteins present in the nine patients

 

Figure 1
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  		Fig. 1 Comparison of all identified proteins in the PD fluid from the nine patients according to their physiological cellular localization, based on the gene ontology cellular component annotation. Proteins can be present in more than one component.

 

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  		Table 3 Protein classification according to function of the proteins present in all the patients, relative abundances are given with mean emPAI values

 


   Discussion
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
Supplementary data
 References
 
The proteomic composition of the PD fluid originating from the nine patients is elucidated, giving a representative overview of the total proteome in PD fluid. The common occurrence of 47% of the identified proteins is revealed, accounting for >90% in abundance. The majority of the proteins are extracellular matrix proteins, reflecting the clear relation of PD fluid with the extracellular space. In this study, 1D SDS–PAGE combined with nLC was chosen to pre-fractionate the samples prior to MS analysis. This was preferred over a 2D gel-based approach in order to be able to cover the broad range of proteins and encounter less interference of high-abundant proteins present in PD fluid. With 2D PAGE, proteins might be unable to resolve by their isoelectrical point or to enter the gel effectively [12]. However, it has to be taken into account that 2D gels provide information on the actual mass of proteins and thus can be useful in identifying specific pathophysiological processes like proteolysis. More detailed information on the PD proteome is provided in our analysis of the 88 shared proteins. The proteome of PD, as reported in Table 3 and supplementary Table A, confirms the occurrence of a number of frequently occurring proteins in the dialysate, like acute phase proteins, complement factors, hormones, coagulation factors and apolipoproteins [13–16]. The influence of transport-status on differential expression of individual proteins present in PD fluid was studied by Sritippayawan et al. [17], showing lower values of complement factor 4A and immunoglobulin {kappa} in patients with low-transport status. The proteome of PD fluid reveals some interesting new proteins, for example, gelsolin, intelectin and paraoxonase. Gelsolin has been proposed to protect the organism from deleterious effects of cytoskeletal actin-containing filaments released with tissue injury or cell death and to serve as a possible biomarker for sepsis [18,19]. In peritoneal dialysis gelsolin could play a protective role in mesothelial cell damage and against infections. Intelectin was identified as a new adipocytokine, also named omentin, with a possible role in the defence against intestinal bacterial permeation and against parasites [20,21]. Paraoxonase is a serum enzyme, associated with high-density lipoproteins, protecting lipoproteins from toxic oxidative modifications and exhibiting anti-atherogenic capacities [22]. The possible correlation with early atherosclerotic changes in peritoneal dialysis patients has to be further investigated [23,24].

The proteome of peritoneal fluid has very interesting potential, asking for more functional proteomic research in the near future, to study the influence on this profile of complications such as peritonitis and the effect of different dialysis fluids and prolonged PD.



   Supplementary data
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 Subjects and methods
 Results
 Discussion
 Supplementary data
References
 
Supplementary data is available online at http://ndt.oxfordjournals.org



   Acknowledgments
 
The authors want to thank Ms M. Lelivelt for her assistance in sample collection.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Supplementary data
 References
 

  1. Fliser D, Novak J, Thongboonkerd V, et al. Advances in urinary proteome analysis and biomarker discovery. J Am Soc Nephrol (2007) 18:1057–1071.[Abstract/Free Full Text]
  2. Niwa T. Biomarker discovery for kidney diseases by mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci (2007).
  3. Davis MT, Spahr CS, McGinley MD, et al. Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry: II. Limitations of complex mixture analyses. Proteomics (2001) 1:108–117.[CrossRef][Web of Science][Medline]
  4. Spahr CS, Davis MT, McGinley MD, et al. Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry: I. Profiling an unfractionated tryptic digest. Proteomics (2001) 1:93–107.[CrossRef][Web of Science][Medline]
  5. Sarto C, Marocchi A, Sanchez JC, et al. Renal cell carcinoma and normal kidney protein expression. Electrophoresis (1997) 18:599–604.[CrossRef][Web of Science][Medline]
  6. Miyamoto M, Yoshida Y, Taguchi I, et al. In-depth proteomic profiling of the normal human kidney glomerulus using two-dimensional protein prefractionation in combination with liquid chromatography-tandem mass spectrometry. J Proteome Res (2007) 6:3680–3690.[CrossRef][Web of Science][Medline]
  7. Ransom RF, Vega-Warner V, Smoyer WE, et al. Differential proteomic analysis of proteins induced by glucocorticoids in cultured murine podocytes. Kidney Int (2005) 67:1275–1285.[CrossRef][Web of Science][Medline]
  8. Weatherly DB, Astwood JA III, Minning TA, et al. A heuristic method for assigning a false-discovery rate for protein identifications from Mascot database search results. Mol Cell Proteomics (2005) 4:762–772.[Abstract/Free Full Text]
  9. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet (2000) 25:25–29.[CrossRef][Web of Science][Medline]
  10. Ishihama Y, Oda Y, Tabata T, et al. Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol Cell Proteomics (2005) 4:1265–1272.[Abstract/Free Full Text]
  11. Yang Y, Thannhauser TW, Li L, et al. Development of an integrated approach for evaluation of 2-D gel image analysis: impact of multiple proteins in single spots on comparative proteomics in conventional 2-D gel/MALDI workflow. Electrophoresis (2007) 28:2080–2094.[CrossRef][Web of Science][Medline]
  12. Au CE, Bell AW, Gilchrist A, et al. Organellar proteomics to create the cell map. Curr Opin Cell Biol (2007) 19:376–385.[CrossRef][Web of Science][Medline]
  13. Pecoits-Filho R, Stenvinkel P, Wang AY, et al. Chronic inflammation in peritoneal dialysis: the search for the holy grail? Perit Dial Int (2004) 24:327–339.[Abstract/Free Full Text]
  14. Reddingius RE, Schroder CH, Daha MR, et al. Complement in serum and dialysate in children on continuous ambulatory peritoneal dialysis. Perit Dial Int (1995) 15:49–53.[Abstract/Free Full Text]
  15. Saku K, Sasaki J, Naito S, et al. Lipoprotein and apolipoprotein losses during continuous ambulatory peritoneal dialysis. Nephron (1989) 51:220–224.[Web of Science][Medline]
  16. Van Der Kamp HJ, Otten BJ, Swinkels LM, et al. Influence of peritoneal loss of GHBP, IGF-I and IGFBP-3 on serum levels in children with ESRD. Nephrol Dial Transplant (1999) 14:257–258.[Free Full Text]
  17. Sritippayawan S, Chiangjong W, Semangoen T, et al. Proteomic analysis of peritoneal dialysate fluid in patients with different types of peritoneal membranes. J Proteome Res (2007) 6:4356–4362.[CrossRef][Web of Science][Medline]
  18. Dinubile MJ. Plasma gelsolin: in search of its raison d’etre. Focus on "Modifications of cellular responses to lysophosphatidic acid and platelet-activating factor by plasma gelsolin". Am J Physiol Cell Physiol (2007) 292:C1240–C1242.[Free Full Text]
  19. Lee PS, Waxman AB, Cotich KL, et al. Plasma gelsolin is a marker and therapeutic agent in animal sepsis. Crit Care Med (2007) 35:849–855.[CrossRef][Web of Science][Medline]
  20. Schaffler A, Neumeier M, Herfarth H, et al. Genomic structure of human omentin, a new adipocytokine expressed in omental adipose tissue. Biochim Biophys Acta (2005) 1732:96–102.[Medline]
  21. Datta R, deSchoolmeester ML, et al. Identification of novel genes in intestinal tissue that are regulated after infection with an intestinal nematode parasite. Infect Immun (2005) 73:4025–4033.[Abstract/Free Full Text]
  22. Mackness MI, Mackness B, Durrington PN, et al. Paraoxonase: biochemistry, genetics and relationship to plasma lipoproteins. Curr Opin Lipidol (1996) 7:69–76.[Web of Science][Medline]
  23. Dantoine TF, Debord J, Charmes JP, et al. Decrease of serum paraoxonase activity in chronic renal failure. J Am Soc Nephrol (1998) 9:2082–2088.[Abstract]
  24. Ece A, Atamer Y, Gurkan F, et al. Paraoxonase, anti-oxidant response and oxidative stress in children with chronic renal failure. Pediatr Nephrol (2006) 21:239–245.[CrossRef][Web of Science][Medline]
Received for publication: 5.12.07
Accepted in revised form: 21. 3.08


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