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. 2017 Jul 14;14:313–319. doi: 10.1016/j.dib.2017.07.025

Data on the impact of the blood sample collection methods on blood protein profiling studies

Maria Ilies a,b, Cristina Adela Iuga a,c, Felicia Loghin d, Vishnu Mukund Dhople b, Thomas Thiele e, Uwe Völker b,f, Elke Hammer b,f,
PMCID: PMC5544472  PMID: 28808673

Abstract

Complete blood protein profiles of 4 different blood sample collection methods (EDTA-, heparin- and citrate plasma and serum) were investigated and the data presented herein is an extension of the research article in Ilies et al. [1]. Specimens were depleted of 6 highly abundant proteins and protein profiling was assessed by nano-LC UDMSE. Exhaustive protein sets and protein abundances before and after depletion are presented in tables and figures. Also, the core protein set and the unique proteins for each sample collection method previously described [1] are disclosed.

Keywords: LC-MSE method data, Proteomics, Plasma, Serum, Proteomics


Specifications Table

Subject area Proteomics
More specific subject area Clinical chemistry, Biomarker analysis, Blood proteome profiling
Type of data Tables, figures (PDF file format)
How data was acquired nano liquid chromatography (AQUITY UPLC M-CLASS, Waters Corporation) tandem mass spectrometry (Synapt G2Si mass spectrometer, WATERS Corporation)
UDMSEdata acquisition
Data format Analyzed and processed data
Experimental factors 24 blood samples were drawn from 6 healthy young volunteers in serum tubes and plasma tubes containing EDTA, heparin, and citrate.
Experimental features Serum and plasma was obtained after tube manufacturer's instructions and aliquots were stored at -80  °C until analysis. Protein profiles were analyzed before and after samples depletion of 6 high abundant proteins using a commercial MARS6 (Agilent Technologies) immunoaffinity based column. Prior to the mass spectrometric analysis, proteins were digested by trypsin and peptides were further analyzed and protein profiles investigated with respect to the sample collection method influence.
Data source location Greifswald, Germany
Data accessibility Data is with article

Value of the data

  • Data shows a comprehensive evaluation of the different blood sample collection methods on 6 high abundant proteins and their depletion efficiency using immunoaffinity MARS6 column which can be used for future investigations on blood high abundant proteins and depleted fractions.

  • Individual protein abundances, their presence and variance in the samples collected with different methods after depletion are of potential value to determine which sampling method to be used for proteomics investigations.

  • Data presents an all-inclusive set of information on the methods applied to evaluate the impact of different blood sample collection methods on protein profiling studies and can be used as benchmark for future blood protein profiling studies.

1. Data

In this Data in Brief article we provide detailed information on blood protein profiling as an extension of the results reported in Ref. [1], 24 blood specimens were collected from 6 healthy and young volunteers in different sample collection tubes for serum and plasma. Tubes characteristics and the subsequent sample preparation are presented in Table 1. For the blood protein profiling a nanoLC-UDMSE method and standard search parameters were employed. Detailed description of methods can be found in Ref. [1] and its supplementary methods. 6 highly abundant blood proteins, namely serum albumin, immunoglobulin gamma, immunoglobulin alpha, serotransferrin, haptoglobin, and alpha-1-antitrypsin, were depleted by using a commercially available immunoaffinity depletion column. A detailed overview on depletion efficiency based on protein abundances for all sample collection methods is presented in Table 2. The distribution of the high abundant proteins before and after depletion is presented in Fig. 1 and more specific, fibrinogen coverage is shown in Fig. 2. Data regarding number of identified peptides and relatively quantified proteins for all sample types after depletion is shown in Fig. 3. Also, a top 10 list of the most abundant unique proteins for each of the EDTA-, heparin-, citrate plasma and serum samples is given in Table 3. The complete list of all relatively quantified proteins over all samples including their occurrence in the protein core set or as unique proteins interpreted in detail previously [1], can be found in the Supplementary material with data on individual sample abundance, mean abundance for each sample collection method and the abundance based coefficient of variation after depletion.

Table 1.

Blood sample collection tubes characteristics.

Blood product Serum Plasma
Tube type Plastic SST™ II Advance Plastic K2EDTA Glass Citrate Glass sodium heparin
Cat. No./NHS code 367954/KFK114 367873/KFK286 367691/KFK186 367876/KFK279
Additive (concentration) Silica (clot activator)/gel Potassium EDTA Buffered sodium citrate (0,105 M) Sodium heparin (17 IU/mL blood)
Volume (mL) 5 6 4.5 6
Mixing recommendation Gently inverted 180° and back Gently inverted 180° and back Gently inverted 180° and back Gently inverted 180° and back
5–6 times 8–10 times 3–4 times 8–10 times

Table 2.

Summary of depletion efficiency.

Mean protein abundance EDTA plasma
Heparin plasma
Citrate plasma
Serum
Before depletion After depletion Before depletion After depletion Before depletion After depletion Before depletion After depletion
All proteins 40568018.74 44741390.04 35119594.07 52949084.17 40671622.40 69872,370.90 54995897.89 45191163.47
α-1-antitrypsin 757196.34 14259.97 584561.17 23153.90 764890.57 22854.17 1006489.65 29692.67
Haptoglobin 631767.39 18029.34 487822.58 41219.67 596917.79 56161.72 689948.19 41259.85
Ig A 429327.89 44422.15 380247.33 23957.12 431941.12 51775.29 550978.46 18885.19
Ig G 1–4 2013660.86 91452.63 1677118.63 101491.82 2145431.99 168092.78 2856603.51 124679.28
Serotransferrin 2369837.17 213742.01 2096978.58 183333.16 2651548.54 364344.32 3224215.08 202618.47
Serum albumin 15235797.33 2056072.75 12925303.83 1866019.81 15394810.67 3600066.33 22315530.67 2807855.77
Other proteins 19130431.76 42303411.19 16967561.94 50709908.69 18686081.72 65609076.29 24352132.33 41966172.25
Total fibrinogen 1839721.65 7325737.50 1108301.52 6370617.46 1657777.20 9817167.88 0.00 71699.88

Fig. 1.

Fig. 1

HAP abundance before and after depletion.

Fig. 2.

Fig. 2

Total fibrinogen abundance before and after depletion of HAP.

Fig. 3.

Fig. 3

Global overview on the identified peptides and quantified proteins.

Table 3.

TOP 10 abundant proteins exclusively identified per sampling method.

Accession Entry name TOP10_EDTA plasma Protein names Secreted/ leakage EDTA 1 EDTA2 EDTA3 EDTA4 EDTA5 EDTA6 Mean CV
O75410 TACC1 Transforming acidic coiled-coil-containing protein 1 Leakage 49174 65077 109984 54229 65833 39035 63889 0.39
Q9P2D6 F135A Protein FAM135A Not specified 47425 51140 9049 33084 57915 46010 40770 0.43
Q99683 M3K5 Mitogen-activated protein kinase kinase kinase 5 leakage 37558 44893 34790 36856 52333 37776 40701 0.16
Q9P0W8 SPAT7 Spermatogenesis-associated protein 7 Leakage 21640 32866 28811 17938 32732 19729 25619 0.26
Q9BYW2 SETD2 Histone-lysine N-methyltransferase SETD2 Leakage 22027 26583 21030 22561 30931 20783 23986 0.17
Q15573 TAF1A TATA box-binding protein-associated factor RNA polymerase I subunit A Leakage 14671 20078 22199 21065 27359 18243 20603 0.21
P15813 CD1D Antigen-presenting glycoprotein CD1d Leakage 13395 17280 13398 14071 20923 15275 15724 0.19
O14950 ML12B Myosin regulatory light chain 12B Not specified 10508 9974 11784 13291 8753 9291 10600 0.16
Q5TBE3 CI153 Uncharacterized protein C9orf153 Not specified 6183 7639 8439 7543 11014 7128 7991 0.21
Q8N4P6 LRC71 Leucine-rich repeat-containing protein 71 Not specified 10463 8450 5703 7123 6758 6869 7561 0.22
Accession Entry name TOP10_heparin plasma Protein names Secreted/ leakage Heparin1 Heparin2 Heparin3 Heparin4 Heparin5 Heparin6 Mean CV

Q8WUY3 PRUN2 Protein prune homolog 2 Leakage 160723 206288 192573 306294 247158 283487 232754 0.24
Q15811 ITSN1 Intersectin-1 Leakage 50959 63100 53081 48220 90431 34339 56688 0.33
Q00610 CLH1 Clathrin heavy chain 1 Leakage 15586 14728 18562 20815 22935 20262 18815 0.17
P24043 LAMA2 Laminin subunit alpha-2 Secreted 11392 12288 14534 17688 16610 15376 14648 0.17
Q96RE9 ZN300 Zinc finger protein 300 Leakage 7134 11365 11937 20051 15033 15472 13499 0.33
Q9P0W5 SCHI1 Schwannomin-interacting protein 1 Leakage 17022 10273 10231 14051 10710 10656 12157 0.23
Q5RL73 RBM48 RNA-binding protein 48 Not specified 5454 8424 11531 14460 8906 21118 11649 0.48
Q9P219 DAPLE Protein Daple Leakage 7162 10200 14709 10857 11183 10820 10822 0.22
Q8N3R3 TCAIM T-cell activation inhibitor, mitochondrial Leakage 13138 11101 8965 8622 9601 8057 9914 0.19
Q7LG56 RIR2B Ribonucleoside-diphosphate reductase subunit M2 B Leakage 5452 8109 8708 10250 8552 9235 8384 0.19
Accession Entry name TOP10_citrate plasma Protein names Secreted/ leakage Citrate1 Citrate2 Citrate3 Citrate4 Citrate5 Citrate6 Mean CV
Q9P2M7 CING Cingulin Leakage 25422 20003 21886 23546 30961 24534 24392 0.15
P12259 FA5 Coagulation factor V Secreted 23814 17933 19660 25752 18389 25697 21874 0.17
Q9P2F6 RHG20 Rho GTPase-activating protein 20 Not specified 23589 22007 16027 12855 27896 20017 20398 0.26
Q8N4C7 STX19 Syntaxin-19 Leakage 28854 20451 15902 13099 22999 13806 19185 0.32
P01036 CYTS Cystatin-S secreted 11101 15659 13394 13586 12003 13467 13201 0.12
Q9UHR6 ZNHI2 Zinc finger HIT domain-containing protein 2 Not specified 19443 16822 4967 3913 10581 11941 11278 0.55
Q96RG2 PASK PAS domain-containing serine/threonine-protein kinase Leakage 6479 5955 8749 6906 9560 7207 7476 0.19
P82970 HMGN5 High mobility group nucleosome-binding domain-containing protein 5 Leakage 9548 8133 7295 6810 7588 5103 7413 0.20
Q9Y275 TN13B Tumor necrosis factor ligand superfamily member 13B Secreted 7560 5901 9552 8230 5887 5013 7024 0.24
Q8TBF8 FA81A Protein FAM81A Not specified 2397 14042 4879 6685 5055 6287 6558 0.60
Accession Entry name TOP10_serum Protein names Secreted/ leakage Serum 1 Serum2 Serum3 Serum4 Serum5 Serum6 Mean CV

P04275 VWF von Willebrand factor Secreted 171296 202739 192598 166870 183833 187044 184063 0.07
O95602 RPA1 DNA-directed RNA polymerase I subunit RPA1 Leakage 118817 176926 184007 192232 145288 177692 165827 0.17
Q9ULI0 ATD2B ATPase family AAA domain-containing protein 2B Leakage 51935 64557 22306 53282 62255 57282 51936 0.30
Q96HQ0 ZN419 Zinc finger protein 419 Leakage 36426 50320 48458 36400 54318 39176 44183 0.18
P07996 TSP1 Thrombospondin-1 Leakage 44367 39433 21407 42369 47867 37343 38797 0.24
Q9BS31 ZN649 Zinc finger protein 649 Leakage 23893 41507 27030 51443 37056 43081 37335 0.28
A6NET4 OR5K3 Olfactory receptor 5K3 Leakage 38230 37448 43819 30573 25303 33517 34815 0.19
Q8WXX0 DYH7 Dynein heavy chain 7, axonemal Leakage 19153 26320 19664 22016 33037 19816 23334 0.23
Q7Z443 PK1L3 Polycystic kidney disease protein 1-like 3 Leakage 12597 7542 19654 27879 14351 4420 14407 0.59
P98196 AT11A Probable phospholipid-transporting ATPase IH Leakage 15647 10307 12192 15634 14152 17414 14224 0.18

2. Experimental design, materials and methods

Experimental design and the materials and methods have been reported previously [1].

Acknowledgements

We would like to thank to the European Social Found, Human Resources Development Operational Programme 2007–2013 [Project no. POSDRU/159/1.5/136893], the Deutscher Akademischer Austauschdienst (German Academic Exchange Service) [Programme ID 57130104, Personal number: 91558112], the ERASMUS + Traineeship [Contract no. 06/24/08/2016] and the Iuliu Hațieganu University of Medicine and Pharmacy, Cluj-Napoca Romania [Grant no. 7690/57/2016] for the research grants awarded to Maria Ilies.

Footnotes

Transparency document

Transparency data associated with this article can be found in the online version at 10.1016/j.dib.2017.07.025.

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.dib.2017.07.025.

Contributor Information

Maria Ilies, Email: ilies.maria@umfcluj.ro.

Cristina Adela Iuga, Email: iugac@umfcluj.ro.

Felicia Loghin, Email: floghin@umfcluj.ro.

Vishnu Mukund Dhople, Email: dhoplevm@uni-greifswald.de.

Thomas Thiele, Email: thielet@uni-greifswald.de.

Uwe Völker, Email: voelker@uni-greifswald.de.

Elke Hammer, Email: hammer@uni-greifswald.de.

Transparency document. Supporting information

Supplementary material

mmc2.docx (12.6KB, docx)

.

Appendix A. Supplementary material

Overview on all sample collection methods relatively quantified proteins after depletion.

mmc1.pdf (262.3KB, pdf)

Reference

  • 1.Ilies M., Iuga C.A., Loghin F. Impact of blood sample collection methods on blood protein profiling studies. Clin. Chim. Acta. 2017;471:128–134. doi: 10.1016/j.cca.2017.05.030. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary material

mmc2.docx (12.6KB, docx)

Overview on all sample collection methods relatively quantified proteins after depletion.

mmc1.pdf (262.3KB, pdf)

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