Skip to main content
Journal of Biomolecular Techniques : JBT logoLink to Journal of Biomolecular Techniques : JBT
. 2009 Apr;20(2):101–108.

A Depletion Strategy for Improved Detection of Human Proteins from Urine

Mark M Kushnir 1, Peter Mrozinski 2, Alan L Rockwood 3, David K Crockett 1,
PMCID: PMC2685607  PMID: 19503621

Abstract

With rapidly growing interest in the urine proteome, methods for reducing sample complexity are becoming increasingly important. Depletion strategies for removal of high-abundance proteins from human urine have not been reported. A commercial kit designed for depletion of abundant proteins from plasma was evaluated for removing top proteins from urine of patients with proteinuria. The number of low-abundance proteins identified in urine after depletion increased nearly 2.5-fold.

Keywords: affinity chromatography, protein depletion, proteinuria, proteomics, urine

INTRODUCTION

The detection and identification of trace amounts of proteins in complex samples is a major challenge in bio-markers discovery and validation. Depletion of proteins present in high concentrations is one common approach for improved detection of low-abundance proteins, which may serve as potential biomarkers.13 The depletion strategy often employs antibody affinity chemistry using commercially available kits.4,5

Samples of interest for detection of protein biomarkers are typically serum or plasma. Thus, commercial kits for the depletion of abundant proteins are generally developed and optimized for plasma or serum samples. However, with the rapidly growing interest in the human urine proteome, methods for reducing the complexity of urine samples are needed.68 To date, depletion strategies for removal of high-abundance proteins from human urine have not been reported.

Fractionation of samples has been recognized as one common approach for reducing complexity and making the samples amenable for instrumental analysis. One of the most efficient methods for reduction of sample complexity is affinity capture of abundant proteins followed by analysis of the remaining fraction.1,4,9

Because of the simplicity and noninvasiveness of collection, urine is an attractive sample type for many diagnostic tests. Furthermore, urine contains a relatively small number of proteins typically present at low concentrations, and thus a simpler matrix for detecting proteins as compared to serum or plasma. However, in some human diseases excess protein is found in the urine, as can occur in patients with compromised kidney function. As a result, many of the proteins normally present in blood will also be excreted into the urine. This condition, known as proteinuria, is often observed in acute inflammation, acute urinary tract infection, amyloidosis, diabetic nephropathy, kidney failure, multiple myeloma, nephrotic syndrome, and severe yeast infections. 1014

When searching for diagnostic markers of the above diseases and conditions, plasma proteins present at high concentrations in urine samples can hinder the ability to detect potential protein biomarkers present at low concentrations. Depletion of high-abundance plasma proteins from urine is one approach that would simplify sample complexity and improve the chances of finding potential biomarkers. In this study we report the use of a commercially manufactured protein depletion kit for the removal of the six most abundant human plasma proteins from urine samples.

EXPERIMENTAL PROCEDURES

To evaluate the commercial protein depletion kit, human serum samples were prepared and processed according to the manufacturer’s instructions. Test samples of pooled human urine were then prepared. A protein-containing urine pool was collected from the urine of patients with proteinuria. For the negative control, pooled urine samples from healthy individuals were used. All samples were de-identified in accordance with a University of Utah Institutional Review Board approved protocol.

The multiple affinity removal (MARS) column for the depletion of 6 high-abundant proteins (Agilent Technologies, Santa Clara, CA, Part #5185–5984) contains affinity binders for the depletion of albumin, transferrin, haptoglobin, IgG, IgA, and alpha-1 antitrypsin. Samples were prepared by ultrafiltration (Amicon Ultra-4 filters, 5 kDa cutoff, Millipore, Billerica, MA), then processed with the recommended column run cycle consisting of loading the sample (serum or urine), collecting the flow-through (depleted fraction) proteins, washing, and eluting bound proteins.

The efficiency of the depletion of the proteins from urine was confirmed using SDS-PAGE. Where possible, equal loading of total protein onto the depletion column and for gel analysis was employed. After electrophoresis, the gel was silver stained (Invitrogen, Carlsbad, CA) and imaged.

Samples were processed by alkylating cysteine residues with iodoacetamide, then either in-gel or in-solution tryptic digest for 18 h at 37°C. The samples were then analyzed on the Agilent 6510 Q-TOF (Agilent Technologies, Santa Clara, CA) equipped with a ChipCube (G2240A) and an Agilent 1200 nano-HPLC system using a 30-min acetonitrile gradient (5%–40%) and C18 reversed-phase separation. Data acquisition (2 GHz extended dynamic range) was performed with MassHunter Q-TOF Acquisition software B.01.03 with an acquisition rate of 3 scans/s followed by tandem mass spectrometry (MS/MS) scans of the three most intense ions using the acquisition rate of 2 scans/s. Exclusion was set for 12 s after two consecutive MS/MS scans of a precursor ion. The time-of-flight (TOF) analyzer was tuned to a resolution of 12,000 and calibrated prior to each experiment for a mass accuracy < 2 ppm.

The acquired MS/MS spectra were searched using Spectrum Mill MS Proteomics Workbench Rev A.03.03.075 (Agilent) against the SwissProt human database (v 13.2–53,541 entries). Mass tolerance was set to 20 ppm for precursor ions and 50 ppm for fragment ions. An enzyme-specific search (trypsin) was used with two missed cleavages allowed. Variable carbamidomethylation (Da 57.0214) was also included for peptide scoring during the database search. Search results were filtered to approximately 5% error using Spectrum Mill’s autovalidation tool, with an individual peptide score threshold of 10 or summed score of 15.

RESULTS

High-abundance proteins were removed from human serum using the Agilent MARS column. The depletion was performed according to the method recommended by the manufacturer for serum samples. Figure 1 shows the silver-stained SDS gel of the control serum sample (lane 1), flow-through of the depletion column (lane 2), and the eluted fraction of serum proteins retained by the column (lane 3).

FIGURE 1.

FIGURE 1

Depletion of high-abundance proteins from serum (lanes 1–3) and urine (lanes 4–9) samples. Lane 1: Serum control; lane 2: depletion column flow-through; lane 3: column elution of the bound serum proteins. Lane 4: normal urine control; lane 5: column flow-through; lane 6: column elution. Lane 7: proteinuria control; lane 8: flow-through fraction; lane 9: column elution of the bound protein fraction.

Performance of the depletion kit was also compared between serum and urine samples. The pool of urine samples collected from healthy individuals contained traces of proteins (lane 4), which were removed in the flow-through fraction (lane 5) and accounted for in the eluted fraction (lane 6). The gel analysis of proteinuria samples contained large amounts of proteins (lane 7), which were removed in the flow-through fraction (lane 8) and seen in the eluted fraction (lane 9).

To further evaluate the performance of depletion in urine, the total number of proteins identified by liquid chromatography (LC)-MS/MS analysis of urine samples was compared. While only 29 proteins were identified in urine from healthy individuals (Fig. 1, lane 4 and Table 1), some 60 proteins were identified in urine from patients with proteinuria (Fig. 1, lane 7 and Table 2). However, after depletion of high-abundance proteins, 142 proteins were identified (Fig. 1, lane 8 and Table 3). Table 4 summarizes these findings.

TABLE 1.

Human Proteins Identified in Urine of Healthy Individuals

Group No. No. Spectra No. Unique PEPs % Coverage Unique Score Accession Protein
1 20 10 20 147.9 P02768 Serum albumin precursor
2 18 7 65 117.5 P62988 Ubiquitin
3 4 3 2 41.8 P02452 Collagen alpha-1(I) chain precursor
4 3 2 8 38.7 P10645 Chromogranin-A precursor
5 3 3 12 29.9 P11684 Uteroglobin precursor
6 4 3 12 29.6 P01009 Alpha-1-antitrypsin precursor
7 3 2 4 28.5 P04080 Cystatin-B
8 13 4 33 27.2 P01834 Ig kappa chain C region
9 2 2 31 21.6 Q9UGM3 Deleted in malignant brain tumors 1 protein precursor
10 5 2 1 21.4 P01344 Insulin-like growth factor II precursor
11 2 2 4 21.2 P02814 Submaxillary gland androgen-regulated protein 3 homolog B
12 7 2 39 20.7 P68133 Actin, alpha skeletal muscle
13 2 3 2 20.4 P68363 Tubulin alpha-1B chain
14 2 2 3 20.3 P36578 60S ribosomal protein L4
15 2 2 4 19.7 P18135 Ig kappa chain V-III region HAH precursor
16 2 2 6 19.7 P02750 Leucine-rich alpha-2-glycoprotein precursor
17 2 2 2 19.0 P02760 AMBP protein precursor (contains alpha-1-microglobulin)
18 2 2 4 18.9 P00738 Haptoglobin precursor (contains haptoglobin alpha chain)
19 2 2 1 18.9 P01602 Ig kappa chain V-I region HK102 precursor
20 2 2 13 18.4 P10153 Nonsecretory ribonuclease precursor
21 2 2 9 18.2 P01842 Ig lambda chain C regions
22 2 2 27 17.0 P02753 Plasma retinol-binding protein precursor
23 2 2 4 16.8 P07602 Proactivator polypeptide precursor (contains Saposin-A)
24 2 2 2 16.8 P01703 Ig lambda chain V-I region NEWM
25 2 2 10 16.1 Q12907 Vesicular integral-membrane protein VIP36 precursor
26 4 2 2 15.3 P01857 Ig gamma-1 chain C region
27 3 2 3 15.1 P19971 Thymidine phosphorylase precursor
28 2 2 2 15.0 Q99459 Cell division cycle 5-like protein
29 3 2 2 15.0 P80748 Ig lambda chain V-III region LOI

TABLE 2.

Human Proteins Identified in Urine of Individuals with Proteinuria

Group No. No. Spectra No. Unique PEPs % Coverage Unique Score Accession Protein
1 42 12 17 218.0 P02768 Serum albumin precursor
2 28 6 9 107.8 P07911 Uromodulin precursor
3 11 5 1 98.0 P98160 Basement membrane-specific heparan sulfate proteoglycan core protein
4 11 4 4 75.4 P01133 Pro-epidermal growth factor precursor
5 7 3 7 58.9 P19961 Alpha-amylase 2B precursor
6 6 3 8 56.5 P10909 Clusterin precursor
7 6 3 5 56.3 Q6EMK4 Vasorin precursor
8 7 3 5 52.5 P01042 Kininogen-1 precursor
9 15 4 16 52.3 P05090 Apolipoprotein D precursor
10 4 2 3 40.3 P55290 Cadherin-13 precursor
11 6 2 5 37.6 P01876 Ig alpha-1 chain C region
12 7 2 9 37.0 P10451 Osteopontin precursor
13 6 2 3 36.1 Q14624 Inter-alpha-trypsin inhibitor heavy chain H4 precursor
14 6 2 3 34.0 Q08380 Galectin-3-binding protein precursor
15 4 2 3 33.4 P01833 Polymeric-immunoglobulin receptor precursor
16 3 2 4 32.0 P68871 Hemoglobin subunit beta
17 2 2 9 27.2 P01009 Alpha-1-antitrypsin precursor
18 4 2 4 25.2 P10153 Nonsecretory ribonuclease precursor
19 2 2 18 25.1 P07288 Prostate-specific antigen precursor
20 3 3 8 24.9 P01834 Ig kappa chain C region
21 2 2 1 24.6 Q7Z5L0 Vitelline membrane outer layer protein 1 homolog precursor
22 2 2 2 24.4 P10253 Lysosomal alpha-glucosidase precursor
23 5 2 1 24.0 Q9HCU0 Endosialin precursor
24 4 3 5 23.7 P12109 Collagen alpha-1(VI) chain precursor
25 4 2 8 22.9 P05452 Tetranectin precursor
26 6 2 3 22.5 P41222 Prostaglandin-H2 D-isomerase precursor
27 2 2 4 21.2 P04004 Vitronectin precursor
28 2 2 4 20.7 Q6GTX8 Leukocyte-associated immunoglobulin-like receptor 1 precursor
29 2 2 2 20.6 P02774 Vitamin D-binding protein precursor
30 4 3 9 20.6 P01859 Ig gamma-2 chain C region
31 3 3 2 20.5 P06310 Ig kappa chain V-II region RPMI 6410 precursor
32 2 2 3 20.2 O94919 Endonuclease domain-containing 1 protein precursor
33 4 2 4 20.0 P15309 Prostatic acid phosphatase precursor
34 2 2 4 20.0 P06870 Kallikrein-1 precursor
35 2 2 15 19.9 O75594 Peptidoglycan recognition protein precursor
36 2 2 1 19.4 P01766 Ig heavy chain V-III region BRO
37 4 2 2 19.2 P04264 Keratin, type II cytoskeletal 1
38 2 2 7 19.2 Q12907 Vesicular integral-membrane protein VIP36 precursor
39 2 2 2 19.0 P01781 Ig heavy chain V-III region GAL
40 4 2 2 19.0 O00187 Mannan-binding lectin serine protease 2 precursor
41 3 3 1 18.8 P01871 Ig mu chain C region
42 2 2 5 18.8 P16070 CD44 antigen precursor
43 4 2 2 18.5 P25311 Zinc-alpha-2-glycoprotein precursor
44 2 2 1 18.4 P05155 Plasma protease C1 inhibitor precursor
45 2 2 2 17.4 P14543 Nidogen-1 precursor
46 6 2 1 17.0 Q9GZM5 Protein YIPF3
47 3 2 2 16.9 P35908 Keratin, type II cytoskeletal 2 epidermal
48 2 2 5 16.9 P08571 Monocyte differentiation antigen CD14 precursor
49 2 2 1 16.8 P18827 Syndecan-1 precursor
50 2 2 2 16.6 Q6UVK1 Chondroitin sulfate proteoglycan 4 precursor
51 3 3 1 16.6 P69905 Hemoglobin subunit alpha
52 6 2 1 16.3 P02760 AMBP protein precursor [Contains: Alpha-1-microglobulin]
53 4 2 1 16.1 P06396 Gelsolin precursor
54 2 2 1 15.1 Q6XZF7 Dynamin-binding protein
55 3 3 1 15.1 P02751 Fibronectin precursor
56 2 2 2 15.0 Q00796 Sorbitol dehydrogenase
57 2 2 3 15.0 P12830 Epithelial-cadherin precursor
58 3 2 9 15.0 P02750 Leucine-rich alpha-2-glycoprotein precursor
59 2 2 2 15.0 O75144 ICOS ligand precursor
60 6 2 1 15.0 Q8IZQ5 Selenoprotein H

TABLE 3.

Human Proteins Identified in Urine of Individuals with Proteinuria Using a Depletion Strategy

Group No. No. Spectra No. Unique PEPs % Coverage Unique Score Accession Protein
1 80 14 46 261.1 P25311 Zinc-alpha-2-glycoprotein precursor
2 33 10 11 161.7 P15144 Aminopeptidase N
3 80 8 69 152.5 P62988 Ubiquitin
4 66 6 27 117.2 P02763 Alpha-1-acid glycoprotein 1 precursor
5 47 6 30 114.1 P10451 Osteopontin precursor
6 92 7 21 107.4 P02760 AMBP protein precursor (contains alpha-1-microglobulin)
7 30 6 18 105.7 P80188 Neutrophil gelatinase-associated lipocalin precursor
8 17 6 43 103.3 P27487 Dipeptidyl peptidase 4
9 13 7 7 102.0 P10253 Lysosomal alpha-glucosidase precursor
10 23 6 10 100.8 P08571 Monocyte differentiation antigen CD14 precursor
11 21 5 22 96.7 P15586 N-acetylglucosamine-6-sulfatase precursor
12 42 5 9 89.4 P07602 Proactivator polypeptide precursor (contains saposin-A)
13 12 6 8 88.3 O43451 Maltase-glucoamylase, intestinal (includes maltase)
14 32 6 9 83.3 P07911 Uromodulin precursor
15 15 5 3 81.7 P07339 Cathepsin D precursor
16 13 5 8 81.3 P01011 Alpha-1-antichymotrypsin precursor
17 14 5 15 78.6 P04746 Pancreatic alpha-amylase precursor
18 9 4 15 77.4 Q13228 Selenium-binding protein 1
19 15 5 10 75.1 P01833 Polymeric-immunoglobulin receptor precursor
20 23 4 11 74.7 P02768 Serum albumin precursor
21 20 4 7 73.6 P17900 Ganglioside GM2 activator precursor
22 13 5 23 70.7 P00915 Carbonic anhydrase 1
23 9 5 26 68.9 Q92820 Gamma-glutamyl hydrolase precursor
24 7 3 21 63.5 P02452 Collagen alpha-1(I) chain precursor
25 7 4 2 61.2 Q14624 Inter-alpha-trypsin inhibitor heavy chain H4 precursor
26 7 3 6 60.9 P22352 Glutathione peroxidase 3 precursor
27 10 3 19 59.1 P07686 Beta-hexosaminidase beta chain precursor
28 20 3 5 57.4 P05451 Lithostathine 1 alpha precursor
29 18 2 18 54.2 P01593 Ig kappa chain V-I region AG
30 10 3 30 53.3 Q9Y5Y7 Lymphatic vessel endothelial hyaluronic acid receptor 1 precursor
31 7 3 8 51.8 P09603 Macrophage colony-stimulating factor 1 precursor
32 12 3 7 51.3 O00584 Ribonuclease T2 precursor
33 6 3 10 51.2 P00751 Complement factor B precursor
34 13 3 6 50.9 P01620 Ig kappa chain V-III region SIE
35 25 3 38 50.7 P41222 Prostaglandin-H2 D-isomerase precursor
36 13 3 20 50.3 Q08380 Galectin-3-binding protein precursor
37 15 2 5 48.2 P01834 Ig kappa chain C region
38 8 3 34 47.9 P12830 Epithelial-cadherin precursor
39 12 3 5 45.9 P13473 Lysosome-associated membrane glycoprotein 2 precursor
40 9 3 7 44.8 P05155 Plasma protease C1 inhibitor precursor
41 7 2 5 44.0 P07478 Trypsin-2 precursor
42 6 2 7 43.1 Q13231 Chitotriosidase-1 precursor
43 8 2 5 43.0 Q9h299 SH3 domain-binding glutamic acid-rich-like protein 3
44 6 3 20 42.3 P06865 Beta-hexosaminidase alpha chain precursor
45 11 3 5 42.2 P02753 Plasma retinol-binding protein precursor
46 4 2 24 40.9 O94919 Endonuclease domain-containing 1 protein precursor
47 13 3 5 38.5 P55290 Cadherin-13 precursor
48 6 2 4 37.0 P61769 Beta-2-microglobulin precursor
49 5 2 16 36.7 P11279 Lysosome-associated membrane glycoprotein 1 precursor
50 12 2 4 36.5 P01625 Ig kappa chain V-IV region Len
51 9 2 22 36.1 P35754 Glutaredoxin-1
52 12 2 11 35.6 P19320 Vascular cell adhesion protein 1 precursor
53 7 3 2 35.4 P98160 Basement membrane-specific heparan sulfate proteoglycan core protein
54 4 3 1 35.2 P98164 Low-density lipoprotein receptor-related protein 2 precursor
55 7 2 1 35.1 P10153 Nonsecretory ribonuclease precursor
56 4 3 9 34.7 P02751 Fibronectin precursor
57 3 2 2 34.6 P02774 Vitamin D-binding protein precursor
58 7 3 6 34.1 P04080 Cystatin-B
59 23 3 24 33.9 P00441 Superoxide dismutase [Cu-Zn]
60 8 2 12 33.5 P05090 Apolipoprotein D precursor
61 5 2 12 33.3 Q15828 Cystatin-M precursor
62 6 2 14 33.1 P29966 Myristoylated alanine-rich C-kinase substrate
63 4 2 15 32.0 P31025 Lipocalin-1 precursor
64 4 2 12 31.8 P78324 Tyrosine-protein phosphatase non-receptor type substrate 1 precursor
65 5 2 5 31.7 P06870 Kallikrein-1 precursor
66 9 2 8 31.2 O00468 Agrin precursor
67 4 2 1 29.5 Q07075 Glutamyl aminopeptidase
68 4 2 3 28.7 Q96S96 PEBP family protein precursor
69 4 2 6 28.5 P02765 Alpha-2-HS-glycoprotein precursor
70 5 2 4 28.2 P11684 Uteroglobin precursor
71 6 2 12 27.6 Q6GTX8 Leukocyte-associated immunoglobulin-like receptor 1 precursor
72 4 2 9 26.2 P02766 Transthyretin precursor
73 4 2 8 26.1 P01040 Cystatin-A
74 4 2 21 26.0 O75368 SH3 domain-binding glutamic acid-rich-like protein
75 6 2 20 25.2 P07360 Complement component C8 gamma chain precursor
76 3 2 7 24.2 P01008 Antithrombin-III precursor
77 4 2 4 24.2 Q01459 Di-N-acetylchitobiase precursor
78 6 2 3 24.1 Q13508 Ecto-ADP-ribosyltransferase 3 precursor
79 3 2 2 23.7 Q14019 Coactosin-like protein
80 6 2 16 23.5 P16070 CD44 antigen precursor
81 4 2 1 23.2 P06310 Ig kappa chain V-II region RPMI 6410 precursor
82 3 2 9 23.0 Q9UM22 Mammalian ependymin-related protein 1 precursor
83 3 2 8 22.8 Q14315 Filamin-C
84 2 2 1 22.8 P02735 Serum amyloid A protein precursor
85 11 2 29 22.3 Q02747 Guanylin precursor
86 4 2 16 21.8 P02671 Fibrinogen alpha chain precursor [Contains: Fibrinopeptide A]
87 6 2 2 21.6 Q9NP84 Tumor necrosis factor receptor superfamily member 12A precursor
88 4 2 7 21.6 Q9NQC3 Reticulon-4
89 6 2 1 21.6 P07148 Fatty acid-binding protein, liver
90 2 2 8 21.4 P53634 Dipeptidyl-peptidase 1 precursor
91 4 2 3 21.4 P02788 Lactotransferrin precursor
92 2 2 1 21.2 P10619 Lysosomal protective protein precursor
93 2 2 2 21.1 P08174 Complement decay-accelerating factor precursor
94 4 2 3 20.9 P01871 Ig mu chain C region
95 18 3 2 20.9 P01842 Ig lambda chain C regions
96 2 2 18 20.3 P37173 TGF-beta receptor type-2 precursor
97 2 2 2 20.1 Q03405 Urokinase plasminogen activator surface receptor precursor
98 4 2 3 19.9 P09668 Cathepsin h precursor
99 2 2 3 19.8 P02792 Ferritin light chain
100 2 2 8 19.8 P36957 Dihydrolipoyllysine-residue succinyltransferase, mitochondrial precursor
101 4 2 3 19.7 P01703 Ig lambda chain V-I region NEWM
102 5 2 10 19.6 P10599 Thioredoxin
103 7 2 12 19.0 P81605 Dermcidin precursor
104 4 2 10 19.0 P06396 Gelsolin precursor
105 2 2 1 19.0 P05413 Fatty acid-binding protein, heart
106 6 2 9 18.9 P01034 Cystatin-C precursor
107 2 2 7 18.7 P24855 Deoxyribonuclease-1 precursor
108 3 3 4 18.6 P01700 Ig lambda chain V-I region HA
109 4 2 11 18.3 A0AVF1 Tetratricopeptide repeat protein 26
110 5 2 1 18.1 P05060 Secretogranin-1 precursor
111 2 2 2 18.1 O75223 Uncharacterized protein C7orf24
112 2 2 5 18.1 Q09666 Neuroblast differentiation-associated protein AHNAK
113 6 2 1 17.8 Q9Y624 Junctional adhesion molecule A precursor
114 3 2 3 17.7 P08236 Beta-glucuronidase precursor
115 12 3 1 17.5 O43692 Peptidase inhibitor 15 precursor
116 2 2 3 17.3 P04207 Ig kappa chain V-III region CLL precursor
117 2 2 6 17.3 Q86Y38 Xylosyltransferase 1
118 2 2 1 17.3 Q13201 Multimerin-1 precursor
119 2 2 1 17.2 P15289 Arylsulfatase A precursor
120 2 2 3 17.1 Q16378 Proline-rich protein 4 precursor
121 2 2 11 17.1 P20142 Gastricsin precursor
122 3 2 2 17.0 P52758 Ribonuclease UK114
123 2 2 7 17.0 P04279 Semenogelin-1 precursor
124 11 3 3 16.5 Q9GZM5 Protein YIPF3
125 2 2 2 16.3 Q9Y4L1 Hypoxia up-regulated protein 1 precursor
126 2 2 1 16.2 P07711 Cathepsin L precursor
127 2 2 4 15.7 Q9Y279 V-set and immunoglobulin domain-containing protein 4 precursor
128 2 2 2 15.4 P01857 Ig gamma-1 chain C region
129 2 2 6 15.4 Q9BY77 Polymerase delta-interacting protein 3
130 3 3 3 15.3 P04433 Ig kappa chain V-III region VG precursor
131 2 2 7 15.2 Q9UGM3 Deleted in malignant brain tumors 1 protein precursor
132 2 2 1 15.1 P04430 Ig kappa chain V-I region BAN
133 2 2 8 15.1 O43653 Prostate stem cell antigen precursor
134 4 2 15 15.1 Q9UKL3 CASP8-associated protein 2
135 2 2 1 15.0 Q15149 Plectin-1
136 2 2 1 15.0 Q6UWV6 Ectonucleotide pyrophosphatase/phosphodiesterase family member 7 precursor
137 2 2 2 15.0 Q12830 Nucleosome remodeling factor subunit BPTF
138 2 2 1 15.0 P05543 Thyroxine-binding globulin precursor
139 2 2 2 15.0 P05067 Amyloid beta A4 protein precursor
140 2 2 1 15.0 P01598 Ig kappa chain V-I region EU
141 2 2 15 15.0 Q6EMK4 Vasorin precursor
142 2 2 2 15.0 P02689 Myelin P2 protein

TABLE 4.

Summary of Proteins Identified in Human Urine by LC-MS/MS

Sample Type Depletion Protein IDs Fold
Healthy human urine No 29
Proteinuria human urine No 60 2.1
Proteinuria human urine Yes 142 2.4

DISCUSSION

LC-MS/MS is a powerful technique available for proteomic studies. Depending on the type of separation and detection used, reliable detection range may span three to four orders of magnitude of protein concentration. However, this is insufficient for detection of low-abundance proteins that may be present at concentrations up to 10 orders of magnitude lower than the most abundant proteins of the sample. Although the protein content in urine samples of patients with proteinuria is significantly lower compared to plasma, the samples are still very complex and detection of low-abundance proteins remains a difficult task.

The silver-stained SDS-PAGE (Fig. 1) demonstrated efficient depletion of major proteins from human urine. Performance of the affinity depletion MARS column for urine samples was comparable to the performance observed when the column was used for serum samples. In addition, the protocol for removal of abundant proteins from urine required only slight modification, including the removal of low-molecular-weight components using ultrafiltration. Benefits of the commercial depletion kit included efficient removal of targeted proteins and the ability to reuse the column for multiple samples, thus decreasing processing cost per sample.

Importantly, the proteins targeted by the depletion kit (albumin, transferrin, haptoglobin, immunoglobulin G, immunoglobulin A, and alpha-1 antitrypsin) were noticeably absent or greatly reduced in the depleted data set, thus allowing many more moderate- or low-concentration proteins to be found. For example, serum albumin was identified with the highest score in both normal urine (10 peptides) and proteinuria sample (12 peptides), but was identified 20th on the list (only 4 peptides) in the proteinuria sample after depletion.

The human response to disease or infection often increases the number of proteins in the urine. For proteinuria samples, depletion of six high-abundance proteins allowed two-and-a-half times the number of proteins to be identified in urine from these patients. This study demonstrates that depletion is a useful strategy for reducing the overall complexity of the urine sample.

Acknowledgments

This work was supported by the ARUP Institute for Clinical and Experimental Pathology®.

REFERENCES

  • 1.Echan LA, Tang HY, Ali-Khan N, Lee K, Speicher DW. Depletion of multiple high-abundance proteins improves protein profiling capacities of human serum and plasma. Proteomics. 2005;5:3292–303. doi: 10.1002/pmic.200401228. [DOI] [PubMed] [Google Scholar]
  • 2.Pieper R, Su Q, Gatlin CL, Huang ST, Anderson NL, Steiner S. Multi-component immunoaffinity subtraction chromatography: An innovative step towards a comprehensive survey of the human plasma proteome. Proteomics. 2003;3:422–432. doi: 10.1002/pmic.200390057. [DOI] [PubMed] [Google Scholar]
  • 3.Sigdel TK, Lau K, Schilling J, Sarwal M. Optimizing protein recovery for urinary proteomics, a tool to monitor renal transplantation. Clin Transplant. 2008;22(5):617–623. doi: 10.1111/j.1399-0012.2008.00833.x. [DOI] [PubMed] [Google Scholar]
  • 4.Darde VM, Barderas MG, Vivanco F. Depletion of high-abundance proteins in plasma by immunoaffinity subtraction for two-dimensional difference gel electrophoresis analysis. Methods Mol Biol. 2007;357:351–364. doi: 10.1385/1-59745-214-9:351. [DOI] [PubMed] [Google Scholar]
  • 5.Fu Q, Bovenkamp DE, Van Eyk JE. A rapid, economical, and reproducible method for human serum delipidation and albumin and IgG removal for proteomic analysis. Methods Mol Biol. 2007;357:365–371. doi: 10.1385/1-59745-214-9:365. [DOI] [PubMed] [Google Scholar]
  • 6.Thongboonkerd V, Semangoen T, Chutipongtanate S. Enrichment of the basic/cationic urinary proteome using ion exchange chromatography and batch adsorption. J Proteome Res. 2007;6:1209– 1214. doi: 10.1021/pr0605771. [DOI] [PubMed] [Google Scholar]
  • 7.Righetti PG, Boschetti E, Lomas L, Citterio A. Protein equalizer technology: The quest for a “democratic proteome. Proteomics. 2006;6:3980–3992. doi: 10.1002/pmic.200500904. [DOI] [PubMed] [Google Scholar]
  • 8.Soldi M, Sarto C, Valsecchi C, et al. Proteome profile of human urine with two-dimensional liquid phase fractionation. Proteomics. 2005;5:2641–2647. doi: 10.1002/pmic.200401269. [DOI] [PubMed] [Google Scholar]
  • 9.Chromy BA, Gonzales AD, Perkins J, et al. Proteomic analysis of human serum by two-dimensional differential gel electrophoresis after depletion of high-abundant proteins. J Proteome Res. 2004;3:1120–1127. doi: 10.1021/pr049921p. [DOI] [PubMed] [Google Scholar]
  • 10.Biesenbach G, et al. [“Diabetic” proliferative retinopathy and nodular glomerulosclerosis without diabetes mellitus] Dtsch Med Wochenschr. 1988;113:1968–1971. doi: 10.1055/s-2008-1067921. [DOI] [PubMed] [Google Scholar]
  • 11.Avram MM. Survival in uremia due to systemic diseases. Kidney Int Suppl. 1978:S55–S60. [PubMed] [Google Scholar]
  • 12.Burke DG, Emancipator SN, Smith MC, Salata RA. Histoplasmosis and kidney disease in patients with AIDS. Clin Infect Dis. 1997;25:281–284. doi: 10.1086/514556. [DOI] [PubMed] [Google Scholar]
  • 13.Prakash J, Singh AK, Saxena RK. Usha. Glomerular diseases in the elderly in India. Int Urol Nephrol. 2003;35:283–288. doi: 10.1023/b:urol.0000020429.14190.5b. [DOI] [PubMed] [Google Scholar]
  • 14.van Ypersele de Strihou C, Pirson Y. Indications for dialysis and transplantation in end-stage renal disease. Contrib Nephrol. 1989;71:1104–1110. doi: 10.1159/000417260. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Biomolecular Techniques : JBT are provided here courtesy of The Association of Biomolecular Resource Facilities

RESOURCES