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Transcript
Identification of Disease- and Therapy-Associated Proteome Changes in
the Sera of Patients with Myelodysplastic Syndromes and del(5q)
Changwei Chen PhD1, David T. Bowen MD2, Aristoteles A. N. Giagounidis MD, PhD3,
Brigitte Schlegelberger MD4, Sabine Haase MD3 and Eric G. Wright PhD1
1
Centre for Oncology and Molecular Medicine, Division of Medical Science, College of
Medicine, Dentistry & Nursing, Ninewells Hospital & Medical School, University of
Dundee, Dundee DD1 9SY, Scotland, UK
2
Department of Haematology, St. James’s Institute of Oncology, Bexley Wing, Leeds
LS9 7TF, UK
3
Clinical Research Unit, St. Johannes Hospital, Medizinische Klinik II, An der Abtei 7-
11, 47166 Duisburg, Germany
4
Institute of Cell and Molecular Pathology, Hannover Medical School, Carl-Neuberg-Str.
1, 30625 Hannover, Germany
Running title: Proteomic analysis of serum proteome of myelodysplastic syndromes
Corresponding author: Dr. Changwei Chen, Centre for Oncology and Molecular
Medicine, Division of Medical Science, College of Medicine, Dentistry & Nursing,
Ninewells Hospital & Medical School , University of Dundee, Dundee DD1 9SY,
Scotland, UK; Tel: +44 (0)1382 632663; Fax: +44 (0)1382 633952; Email:
[email protected]
Supplementary Experimental Procedures:
Protein purification and identification
Identification of peaks at m/z 2791, m/z 3274, m/z 3956, m/z 3972, m/z 4282 and m/z
4298
One millilitre of MDS serum was fractionated with ProteinChip spin columns (Bio-Rad
Laboratories Ltd., Hemel Hempstead, UK) according to the manufacturer’s instructions.
Serum fractions were collected and profiled with IMAC30-Cu2+ arrays. The resulting
mass spectra showed that these peaks were mainly present in the flowthrough fraction. To
further enrich these proteins/peptides, a protocol based on reverse phase chromatography
was employed. The flowthrough fraction was mixed with a sample buffer (2% TFA in
20% ACN) at 3:1 and applied to a C18 minicolumn (Amersham Biosciences, Little
Chalfont, England) which had been activated and equilibrated according to the
manufacturer’s instructions. After washing the column with a solution containing 0.5%
TFA and 5% ACN, the bound proteins were sequentially eluted with 20%, 30%, 40%,
50%, 60% and 70% ACN. The eluates were analyzed and two fractions, i.e. eluates with
60% and 70% ACN containing the proteins/peptides were concentrated in a SpeedVac
evaporator (Savant) and then processed for liquid chromatography–tandem mass
spectrometry (LC-MS-MS). Briefly the LC-MS-MS was performed with an Ultimate
3000 nano-HPLC system (Dionex) connected to a LTQ Orbitrap ion trap mass
spectrometer (Thermo Fisher Scientific). Samples were loaded to a 75 m15 cm
PepMap C18 reverse phase column (Dionex) that was equilibrated with 30% solvent B
(90% ACN in 0.08% formic acid) and 60% solvent A (0.01% formic acid in Milli-Q
2
H2O) and run at 300 nl/min. Separated peptides were eluted with a gradient of 30–90%
solvent B over 21 min. The ion trap was set to detect positively charged ions using a
spray voltage of 2 kV and an automated data dependent MS-MS analysis performed on
the top 5 most abundant ions from each MS scan before another full MS scan was
performed. Peptides were analyzed once then excluded for 90 seconds. A Mascot generic
data file was generated from the MS-MS data using RAW2MSM1 prior to database
searching with the Mascot search engine2 against the International Protein Index (IPI)
human database3. The searching parameters were: enzyme: none; fixed modification:
carbamidomethyl (C); variable modifications: acetyl (N-term), oxidation (M); mass
value: monoisotopic; protein mass: unrestricted; peptide mass tolerance: ± 10 ppm; max
missed cleavages: 2. Peptides above the Mascot significance threshold were considered
as positive assignments.
As shown in Supplementary Table 2, the peptides at m/z 3274 and m/z 3972 were
identified as fragments of inter-alpha (globulin) inhibitor H4. We noticed that the
peptides at m/z 4282 and m/z 4298 have the same sequence. As these two peptides have a
mass difference of ca.16 Da, the peptide at m/z 4298 may represent an oxidized form of
the peptide at m/z 4282. The attempts to obtain the identities of two other peptides, i.e.
m/z 2791 and m/z 3956 by MS analysis were unsuccessful. Recently a paper4 reports the
sequence of a same peptide at m/z 3956 which is exactly the same as that of the peak at
m/z 3972 in our study. Another paper5reports the sequence of a peak at m/z 3953 which
is largely the same except a few amino acid residues as that of the peptide at m/z 3972 in
our study. These data indicate that the peptide at m/z 3956 may be a truncated or
3
modified form of the peptide at m/z 3972, which is supported by the array data showing
that these two peaks are closely neighbouring to each other.
Identification of peaks at m/z 7765, m/z 13737, m/z 13810, m/z 15089, m/z 15826 and
m/z 79186
Serum samples were fractionated as described previously and the resulting fractions
containing these proteins were determined by IMAC30-Cu2+ (m/z 7765 and m/z 79186)
or Q10 profiling (m/z 13737, m/z 13810, m/z 15089 and m/z 15826). Proteins were then
separated in a centrifugal filtering device with a 30 kDa cut-off membrane (Millipore,
Watford, UK). The filtrate and the retenate containing proteins with molecular weight
<30 kDa and >30 kDa respectively were dialyzed and concentrated in centrifugal filter
devices with a 3 kDa cut-off membrane (Millipore, Watford, UK). Proteins with
molecular weight <30 kDa were further separated by electrophoresis on 10–20% tricine
gels (Invitrogen, Paisley, UK). To purify the protein at 79186 Da, the retenant was passed
through an affinity column to remove albumin and IgG. The protein was finally purified
by electrophoresis on a 10% glycine gel. After electrophoresis, all the gels were stained
with colloidal Coomassie blue (Invitrogen). Protein bands corresponding to the individual
proteins were excised from the gels and the proteins were in-gel digested with trypsin.
The tryptic digests were analyzed with LC-MS-MS. Briefly the MS analysis was
performed with a QSTAR XL mass spectrometer (Applied Biosystems) connected to an
LC Packings ultimate nano-HPLC system. The resulting MS/MS data were searched
against the IPI Human database using Mascot searching engine. The searching
4
parameters were: enzyme: trypsin; fixed modification: carbamidomethyl (C); variable
modifications: acetyl (N-term), oxidation (M), pyro-glu (N-term Q), sulphone (M); mass
value: monoisotopic; protein mass: unrestricted; peptide mass tolerance: ± 2 Da;
fragment mass tolerance: ± 0.8 Da; max missed cleavages: 2. Peptides above the Mascot
significance threshold were considered as positive assignments.
Database searching identified multiple proteins from the 13 kDa bands, 3 of which i.e.
serum amyloid A protein precursor (IPI00552578), APO C3 13 kDa protein
(IPI00657670), and transthyretin precursor (IPI00022432) have a mass close to 13 kDa.
Based on the published data on serum profiles obtained by other investigators, 68we
suggested that the peaks at m/z 13810 and m/z 13737 would represent the variants of
transthyretin. To test this, we prepared the serum samples depleted of transthyretin and
analyzed them with Q10 array profiling. The two peaks, i.e. m/z 13737 and 13810 along
with another peak at m/z 13851 disappeared from the depleted serum. These peaks were
detected in the eluted sample (Supplementary Figure 1a). This assay demonstrated that
these two peaks were derived from transthyretin. As the mass of the unmodified form of
transthyretin is ca.13760 Da, these two peaks may represent modified forms of
transthyretin. The exact modifications that these two peaks represent need to be clarified.
Four proteins including transthyretin (IPI00022432), haemoglobin subunits 
(IPI00654755), δ (IPI00473011) and  (IPI00410714) were identified from the 15 kDa
gel bands. Based on the published data, 911 we speculated that these two peaks would
represent the haemoglobin  (m/z 15089) and  (m/z 15826) chains. Thus an
immunodepletion assay was carried out to remove haemoglobin from the serum samples.
5
These two peaks disappeared from the depleted serum, and reappeared in the eluted
sample (Supplementary Figure 1b). The assay confirms that these two peaks indeed
represent haemoglobin  and  chain, respectively. The identification of m/z 7765 by MS
analysis was unsuccessful. As several papers report the identification of a few similar
protein peaks as platelet factor 4 (PF-4), 5, 12, 13we employed an immunodepletion assay to
test whether it would be PF-4. The assay showed that the m/z 7765 peak was absent in
the depleted serum, and was detected in the eluted fraction (Supplementary Figure 1c),
which indicates that the peak was indeed derived from PF-4.
6
References
1 Olsen JV, de Godoy L M, Li G, Macek B, Mortensen P, Pesch R et al. Mol Cell
Proteomics 2005; 4: 2010–2021.
2 Perkins DN, Pappin DJ, Creasy DM, Cottrell JS. Probability-based protein
identification by searching sequence databases using mass spectrometry data.
Electrophoresis 1999; 20: 3551–3567.
3 Kersey PJ, Duarte J, Williams A, Karavidopoulou Y, Birney E, Apweiler R. The
International Protein Index: an integrated database for proteomics experiments.
Proteomics 2004; 4: 1985–1988.
4 Song J, Patel M, Rosenzweig CN, Chan-Li Y, Sokoll LJ, Fung ET et al.
Quantification of fragments of human serum inter-alpha-trypsin inhibitor heavy chain
4 by a surface-enhanced laser desorption/ionization-based immunoassay.Clin. Chem.
2006; 52: 1045–1053.
5 Cho WC, Yip TT, Ngan RK, YipTT, Podust VN, Yip C et al. ProteinChip array
profiling for identification of disease- and chemotherapy-associated biomarkers of
nasopharyngeal carcinoma. Clin Chem 2007; 53: 241–250.
6 Escher N, Kaatz M, Melle C, Hipler C, Ziemer M, Driesch D et al. Posttranslational
modifications of transthyretin are serum markers in patients with mycosis fungoides.
Neoplasia 2007; 9: 254–259.
7 Liu L, Liu J, Dai S, Wang X, Wu S, Wang J et al. Reduced transthyretin expression
in sera of lung cancer. Cancer Sci 2007; 98: 1617–1624.
7
8 Miguet L, Bogumil R, Decloquement P, Herbrecht R, Potier N, Mauvieux L et al.
Discovery and identification of potential biomarkers in a prospective study of chronic
lymphoid malignancies using SELDI-TOF-MS. J Proteome Res 2006; 5: 2258–2269.
9 Koomen JM, Shih LN, Coombes KR, Li D, Xiao LC, Fidler IJ et al. Plasma protein
profiling for diagnosis of pancreatic cancer reveals the presence of host response
proteins. Clin Cancer Res 2005; 11: 1110–1118.
10 Kozak KR, Amneus MW, Pusey SM, Su F, Luong MN, Luong SA et al.
Identification of biomarkers for ovarian cancer using strong anion-exchange
ProteinChips: potential use in diagnosis and prognosis. Proc. Natl. Acad. Sci. U S A.
2003; 100: 12343–12348.
11 Woong-Shick A, Sung-Pil P, Su-Mi B, Joon-Mo L, Sung-Eun N, Gye-Hyun N et al.
Identification of hemoglobin-alpha and -beta subunits as potential serum biomarkers
for the diagnosis and prognosis of ovarian cancer. Cancer Sci 2005; 96: 197–201.
12 Vermeulen R, Lan Q, Zhang L, Gunn L, McCarthy D, Woodbury RL et al. Decreased
levels of CXC-chemokines in serum of benzene-exposed workers identified by arraybased proteomics. Proc. Natl. Acad. Sci. U S A. 2005; 102: 17041–17046.
13 Aivado M, Spentzos D, Germing U, Alterovitz G, Meng XY, Grall F et al. Serum
proteome profiling detects myelodysplastic syndromes and identifies CXC chemokine
ligands 4 and 7 as markers for advanced disease. Proc Natl Acad Sci USA 2007; 104:
1307–1312.
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