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African Journal of Pig Farming ISSN 2375-0731 Vol. 7 (9), pp. 001-010, September, 2019. Available online at 
www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s) retain the copyright of this article. 

 

Full Length Research Paper 

 

Analysis of pig serum proteins based on shotgun liquid 
chromatography-tandem mass spectrometry 

 
Keshan Zhang, Yongjie Liu, Youjun Shang, Haixue Zheng, Jianhong Guo, 

Hong Tian, Ye Jin, Jijun He and Xiangtao Liu* 

 
State Key Laboratory of Veterinary Etiological Biology, National Foot and Mouth Disease Reference 

Laboratory, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Science, Xujiaping 
No.1, Lanzhou, Gansu, 730046, PR China. 

 
Accepted 12 June, 2019 

 
Recent advances in proteomics technologies have opened up significant opportunities for future applications. We 
used shotgun liquid chromatography, coupled with tandem mass spectrometry (LC-MS/MS) to determine the 
proteome profile of healthy pig serum. Samples of venous blood were collected and subjected to sodium dodecyl 
sulfate-polyacrylamide gel electrophoresis separation and in-gel trypsin digestion. The peptides were then 
processed using shotgun LC-MS/MS. Serum proteins were subjected to protein identification and bioinformatics 
analysis. A total of 392 proteins were identified, and 179 were annotated according to their molecular functions and 
biological processes, excluding 142 hypothetical proteins and 71 immune globulins. To the best of our knowledge, 
this represents the first porcine serum proteomics analysis based on shotgun LC-MS/MS. This method and the 
resulting proteomics information may prove valuable for ensuring good animal welfare practice and for monitoring 
swine health and disease status. 

 

Key words: Analysis, pig serum, shotgun coupled with tandem mass spectrometry (LC-MS/MS). 

 
INTRODUCTION 

 
Serum is a major body fluid. Serum composition thus 
reflects the overall health status of the individual animal 
and is often used to monitor health and disease in farm 
animals (Bendixen et al., 2011; Eckersall et al., 1996). 
Studies of protein distribution characteristics in serum 
may provide significant information to help unravel the 
mechanisms of disease and for the identification of 
biomarkers associated with new drug targets and early 
diagnosis (Issaq et al., 2007; Wan et al., 2006). Human 
serum protein maps have already been established 
(Millioni et al., 2012). Detailed serum protein two-  
 
 

 
*Corresponding author. E-mail: hnxiangtao@hotmail.com. 
 
Abbreviations: LC-MS/MS, Liquid chromatography-tandem  
mass spectrometry; 2-D PAGE, two-dimensional 
polyacrylamide gel electrophoresis; MWs, molecular weights; 
pI, isoelectric point; PRRSV, porcine reproductive and 
respiratory syndrome virus; PCV-2, porcine circovirus-2; PRV, 
pseudorabies virus; HCV, hog cholera virus; FMDV, foot-and-
mouth disease virus. 

 
 
 

 

dimensional gel electrophoresis (2-DE) identification 
maps have been described for healthy pigs, and 27 high-
to-medium-abundance plasma proteins, including some 
examples of infection/inflammation-regulated proteins in 
healthy Landrace × Large white pigs (Miller et al., 2009).  

Proteome analysis is most commonly accomplished 
using a combination of 2-DE to separate and visualize 
proteins and mass spectrometry (MS) for protein identifi-
cation (Gygi et al., 2000a). However, the disadvantages 
of this technique include extensive sample handling, a 
limited dynamic range, and difficulties in resolving low-
abundance proteins with extreme isoelectric points (pIs) 
and molecular weights (MWs), as well as hydrophobic 
proteins such as membrane proteins (Corthals et al., 
2000; Gygi et al., 2000b; Oh-Ishi et al., 2000). Liquid 
chromatography, coupled with tandem mass spectro-
metry (LC−MS/MS), represents a powerful technique for 
the proteomic analysis of complex samples, where 
peptide masses may still overlap, even with a high-
resolution mass spectrometer (Adams and Zubarev, 
2005; Wysocki et al., 2005). LC-MS/MS has been 
increasingly used for the accurate detection of changes in 

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Figure 1. Separation of  
serum proteins by one- 
dimensional SDS-PAGE.  
Samples of 150 g of 
proteins were separated on  
12% bis-Tris gels and 
stained to allow protein  
identification. Four sections 
were excised and  
subsequently used for 
digestion. 

 

 

protein profiles and to infer biological function (Aebersold 
and Mann, 2003; Crockett et al., 2005). The shotgun LC-
MS/MS proteomics method has been used to identify 
thousands of proteins in human body fluids, including 
blood, seminal plasma and tear fluid.  

In the present study, gel-LC-MS/MS and bioinformatics 
analysis methods were used to develop a pig serum 
protein profile. These results are expected to provide 
valuable information to assist in the practice of good 
animal welfare, and for monitoring swine health and 
disease status. 
 

 
MATERIALS AND METHODS 
 
Animals 
 
Four Landrace femal pigs, aged about six months, were bought 
from a local farm and bred in separated rooms. All the pigs were 
free of the following pathogenic agents: porcine reproductive and 
respiratory syndrome virus (PRRSV), porcine circovirus-2 (PCV-2), 
pseudorabies virus (PRV), hog cholera virus (HCV) and foot-and-
mouth disease virus (FMDV), which were detected by polymerase 
chain reaction or reverse transcription-polymerase chain reaction 
(datas not shown). The animal experiments were conducted in 

  
  

 
 

 
accordance with the International Guiding Principles for Biomedical 
Research Involving Animals, issued by the Council for the 
International Organizations of Medical Sciences. 
 
 
Sample preparation and sodium dodecyl sulfate-
polyacrylamide gel electrophoresis separation 
 
Samples of intravenous (iv) blood were collected, they were 
incubated at 37°C for 2 h, then 4°C for 6 h; at last serum were 
separated at 5000 rpm, for 5 min. The serum protein concentration 
was determined by quantitative kit (GE) according to the 
instructions and stored at -80°C until use (Hsieh et al., 2006). Four 

serum samples (150 g) were pooled and denatured at 100°C for 5 
min in an equal volume of 2× protein loading buffer [0.1 M Tris 
buffer, pH 6.8, 4% sodium dodecyl sulfate (SDS), 0.2% mercapto-
ethanol, 40% glycerol, and 0.002% bromophenol blue], and 
subjected to SDS-polyacrylamide gel electrophoresis. Samples 
were separated using 12% homogeneous SDS polyacrylamide slab 
gels and Tris-glycine-SDS buffer (10 mM Tris, 50 mM glycine, 0.1% 
SDS, pH 8.0) using a Bio-Rad mini-protean tera system (Bio-Rad). 
Electrophoresis was carried out at a constant current of 15 mA/gel 
followed by 30 mA for about 1.5 h until the bromophenol blue 
reached the bottom of the gel. The gels were then stained with 
Coomassie brilliant blue G250 (Sigma, USA). Images were 
acquired using a GS-800 densitometer (Bio-Rad, Hercules, CA). 

 

In-gel digestion 
 
The in-gel trypsin digestion of proteins was conducted according to 
Wilm et al. (1996). The protein lane of the stained gel was cut into 
four slices (A, B, C, and D), depending on protein molecular weight 
(MW) (Figure 1). Each slice was diced into 1 × 1 mm pieces and 
subjected to in-gel tryptic digestion. The gel pieces were rinsed 
three times using Milli-Q water and destained with 0.2 ml of 100 mM 
NH4HCO3 in 50% acetonitrile for 45 min at 37°C, until complete 
depigmentation. The gel pieces were then dried in a vacuum 
centrifuge. 10 µl of 10 mM dithiothreitol in 100 mM NH4HCO3, 
sufficient to cover the gel pieces, was added to the proteins at 56°C 
for 1 h. After cooling to room temperature, the dithiothreitol solution 
was replaced with the same volume of 55 mM iodoacetamide in  
100 mM NH4HCO3. After 45 min incubation at room temperature in 

the dark, the gel pieces were washed with 100 L of 100 mM 

NH4HCO3 for 10 min, dehydrated in 100 L of acetonitrile, swollen 

by rehydration in 100 L of 100 mM NH4HCO3, and shrunk again by 
adding the same volume of acetonitrile. The proteins were 

subsequently digested with 20 ng/L porcine trypsin (modified 
proteomics grade, Sigma) overnight at 37°C. Peptides were 
extracted by one change of 20 mM NH4HCO3 and three changes of 
5% formic acid in 50% acetonitrile (20 min for each change) at room 
temperature (Li et al., 2009; Zhang et al., 2007). 

 

 
Shotgun LC-MS/MS analysis 

 
The extracted peptides from each gel piece were analyzed using an 
Ettan MDLC system (GE Healthcare, USA). In this system, samples 
were desalted on RP trap columns (Zorbax 300 SB C18, Agilent 

Technologies, USA), and then separated on an RP column (150 m 
internal diameter, 100 mm long, Column Technology Inc., Fremont, 
CA). Mobile phase A (0.1% formic acid in HPLC-grade water) and 
mobile phase B (0.1% formic acid in acetonitrile) were selected. 20 

g of tryptic peptide mixture was loaded onto the columns and 

separation was carried out at a flow rate of 2 L/min using a linear 
gradient of 4 to 50% B for 120 min. A Finnigan LTQ linear ion trap 
MS (Thermo Electron, USA), equipped with an electrospray 



 
 
 

 
Table 1. Numbers of peptides and proteins identified in porcine serum.  

 
 Parameter Number of protein Percentage (%) 

 Total peptides 5390 100 

 Total proteins 848 15.7 

 Protein groups 392 46.2 

 immune globulin 71 17.1 

 annotated proteins 179 45.7 

 Hypothetical proteins 142 36.2 
 
 
 
interface, was connected to the LC setup to detect the eluted 
peptides. Data-dependent MS/MS spectra were obtained simul-
taneously. Each scan cycle consisted of one full MS scan in profile 
mode, followed by five MS/MS scans in centroid mode with the 
following Dynamic exclusion settings: repeat count 2, repeat 
duration 30 s and exclusion duration 90 s. Each sample was 
analyzed in triplicate. 
 

 
Protein identification and bioinformatics analysis 

 
Peptides and proteins were identified using Biowork 3.2 software 
(Thermo Finnigan, San Jose, CA), which uses the MS and MS/MS 
spectra of peptide ions to search against the Suina protein 
database. MASCOT protein scores (based on combined MS and 
MS/MS spectra) > 72 were considered statistically significant (p ≤ 
0.05). We accepted individual MS/MS spectra with a statistically 
significant (confidence interval ≥ 95%) ion score (based on MS/MS 
spectra). The protein identification and annotation criteria were 
based on Delta CN (≥ 0.1) and Xcorr (one charge ≥ 1.9, two 
charges ≥ 2.2 and three charges ≥ 3.75). Protein classification was  
performed using Gene Ontology Annotation (GOA; 
http://www.ebi.ac.uk/goa/), according to their molecular functions 
and biological processes. The subcellular locations of different 
proteins were predicated with PSORT (http://psort.hgc.jp/). 
 

 

RESULTS 

 

Serum protein SDS-PAGE separation 

 

Serum proteins were separated by one dimensional SDS-
PAGE and the gel was cut into four pieces, according to 
MW, for shotgun LC-MS/MS analysis (Figure 1). 
 

 

Identification of proteins 

 

A total of 5390 peptides were detected by shotgun LC-
MS/MS. A total of 848 proteins were identified, some of 
which belonged to the same peptides groups. Thus, 392 
proteins were finally identified (Table 1). 
 

 

Characterization of protein profile 

 

The molecular mass and pI value distributions of the 392 
identified serum proteins were analyzed. Their molecular 
masses ranged from 3.2 to 360 kDa, with most being 

 
 
 

between 10 and 100 kDa (Figure 2A). The pIs of the 
proteins ranged from 4 to 11.6 (Figure 2B), with most 
being between 5 and 7. The predicted 2-DE distribution 
(Figure 3) showed that the pIs of about 95% of the 
identified proteins were between 4 and 10, representing 
proteins that are usually difficult to separate by 2-DE. 
About 40% of the identified proteins fell outside the 
typical limits of protein resolution obtained by 2-DE. 
Furthermore, about 14 proteins had higher pIs (> 10), 
which are also usually difficult to separate by 2-DE, but 
these proteins were also identified successfully by 
shotgun LC-MS/MS. 
 
 
Bioinformatics analysis 

 

A total of 189 peptides were annotated according to the 
GOA database and were classified on the basis of 
molecular function or biological process. They could be 
divided into about five functional molecular groups 
(Figure 4A): the classical protein group (101, 32.6% of 
189 annotated peptides) and the cellular protein group 
(88, 31.7%) were the most common. The classical serum 
protein group can be further sub-classified into five 
subgroups, based on their specific functions (Figure 4B); 
most proteins were proteases or other enzymes (46, 
47.9%), common circulating blood proteins (19, 19.0%), 
or coagulation and complement factors (18, 18.8%) which 
are important categories of classical serum proteins. The 
cellular protein group is also sub-classified into five 
subgroups according to their function or biological 
process (Figure 4C): signaling channels, hormone 
regulation, the cytoskeleton, the nucleus, and cellular 
metabolic secretions. 
 

 

DISCUSSION 

 
Serum contains many high-abundance proteins that 
perform various housekeeping functions, as well as 
numerous secreted or shed low-abundance proteins that 
are critical for signal transduction and regulatory events. 
During necrosis, apoptosis, and hemolysis, cell contents 
may be released into the serum. In a certain time period, 
the presence, absence or concentration of a specific 
protein from serum may be related with the 

http://www.ebi.ac.uk/goa/
http://psort.hgc.jp/
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Figure 2. Distributions of molecular weights and pI values for proteins identified by LC-MS/MS, (A)  
Distribution of molecular weights. (B) Distribution of pI values.  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Figure 3. Theoretical 2-DE distribution of proteins from porcine serum. The 
theoretical pIs and MWs of the proteins were calculated using compute pI/Mw 

tools according to protein amino acid sequence or ID. 

 



  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
Figure 4. Categorization of 189 serum proteins by molecular functions or biological processes. (A) All identified proteins. (B) Classical 
serum proteins. (C) cellular proteins. 

 

 

 
pathophysiological performance of body, and the 
presence of these components in blood reinforces the 
significance of a proteomic approach to identifying 
biomarkers for disease status. Previous proteomic 
characterizations of pig serum have used two 
dimensional PAGE (Miller et al., 2009). Result shows 
(Figure 3) 40% proteins that are usually difficult to 
separate by 2-DE. This study used the shotgun 
LCMS/MS proteomics technique combined with 
informatics analysis to determine the proteome profile of 
pig serum. This technique represents an efficient strategy 
for swine serum proteomics research, and overcame the 
disadvantage of 2DE that cannot separate polarity 
protein. To reduce the individual differences, serum from 
four pigs were merged together and used for gel 
electrophoresis separation. In order to identify proteins 
according to molecular weight, brand A and B mixed, and 
brand C and D mixed, respectively (Figure 1). In this 
study, given profile of serum protein from porcine, we 
identified a total of 392 proteins (Table 1), of which 189  

(Table 2) were annotated and classified based on their 
molecular function or biological process (Figure 4). As we 
expected, besides immune globulin, albumin, 
apolipoprotein, hemoglobin and actin, which are both 
ubiquitous in the red blood cells were successfully 
identified. These represented the main serum proteins, 
and are involved in the combination and transportation of 
small molecules (Alaupovic, 1996; Bondarenko et al., 
2002). Few coagulation or complement factors 
associated with whole process of blood coagulation were 
identified successfully as well. Sodium channel protein, 
transmembrane channel-like protein related to signaling 
pathways and receptors were identified, with important 
functions in signal transduction (Naren et al., 1997). The 
identified proteins also included 46 kinds of proteases or 
enzymes related to many important biological processes, 
such as biosynthesis, metabolic regulation, nucleotide 
replication, damage repair, transcription and 
posttranslational modification. Fibronectins involved in 
cell adhesion, cell motility, opsonization, wound healing, and 



       
 

Table 2. List of 189 annotated serum proteins.         
 

        
 

Protein name PepCount 
Unique Cover 

MW kD pI 
Accession 

 

PepCount percent number  

    
 

          

Common circulating blood protein 15         
 

Albumin 787 52 74.1 69.4 5.92 gi|833798 
 

Alpha-2-macroglobulin 91 37 32.2 167 5.58 gi|311256211 
 

Ceruloplasmin 71 26 33.7 121.8 5.72 gi|311269519 
 

Apolipoprotein B 31 22 12.3 300 6.19 gi|951375 
 

Apolipoprotein A-I 63 15 52.1 30.3 5.48 gi|461519 
 

Apolipoprotein A-II 8 3 26 11.1 7.73 gi|297747304 
 

Apolipoprotein C-III 4 2 28.1 107 4.76 gi|416627 
 

Hemoglobin subunit beta 33 9 72.1 16.2 7.1 gi|3041678 
 

Porcine hemoglobin 30 9 67.8 16 6.76 gi|5542425 
 

Haptoglobin 22 9 30.8 38.5 6.51 gi|41019122 
 

Hemopexin precursor 37 12 45.3 51.3 6.59 gi|47522736 
 

Apolipoprotein E 12 7 24.6 36.6 5.62 gi|461527 
 

Apolipoprotein D 3 2 13.7 21.5 4.76 gi|311269822 
 

Angiotensinogen-like 3 2 6.3 37.8 8.74 gi|311271188 
 

Spectrin alpha chain 2 2 1.7 284.9 5.2 gi|311246557 
 

Coagulation and complement factor 19         
 

Complement C3 272 55 46.8 186.8 6.09 gi|47522844 
 

Coagulation factor X protein 1 1 2.3 53.1 5.28 gi|113205818 
 

Coagulation factor IX 1 1 2.7 45.5 5.19 gi|60392241 
 

Complement component C3 70 12 60.5 33.4 5.69 gi|295656640 
 

Complement factor B 36 11 22.6 85.9 7.45 gi|162138242 
 

Complement component 4 65 20 19.5 192.5 6.8 gi|158537756 
 

Complement C2 1 1 3 83.3 7.95 gi|156120138 
 

Complement component C5 11 6 5.9 188.6 6.49 gi|37677940 
 

Complement component C6 5 3 5.1 105.3 6.92 gi|148226535 
 

Complement component C7 precursor 1 1 1.5 93.1 6.7 gi|47523630 
 

Complement component C8A 6 4 13.1 66 5.61 gi|147905213 
 

Complement component C8B 7 3 7.4 69.2 8.14 gi|148235410 
 

Component C8G 2 2 10.9 22.3 5.59 gi|148223227 
 

Complement component C9 5 1 3.3 62.3 5.92 gi|148233690 
 

Complement factor I 11 4 11.8 67.1 8.06 gi|311262683 
 

Complement C1 5 2 15.8 26.5 9.43 gi|51491906 
 

Blood coagulation factor XIV 9 4 13.9 51.8 6.23 gi|571399 
 

Coagulation factor XII 1 1 3.6 68 6.98 gi|35039077 
 

Galectin-8 1 1 6.3 36.3 7.86 gi|218664463 
 

Protease inhibitors 7         
 

Serpin A3-1 89 17 36.9 60.9 8.46 gi|311261515 
 

Inter-alpha-trypsin inhibitor 40 15 22.8 102.1 6.42 gi|48374067 
 

Inhibitor of carbonic anhydrase 34 13 26.9 77.6 5.88 gi|47523160 
 

Alpha-1protease inhibitor 16 6 26.8 47.2 5.54 gi|1703026 
 

Clusterin precursor 12 6 20.4 51.7 5.62 gi|47522770 
 

Plasma protease C1 inhibitor 7 2 6.5 54.6 6.77 gi|178056710 
 

Plasminogen activator inhibitor 2 1 4.7 44.8 8.6 gi|311259199  
 



 
        

  Table 2. Count’d.       
         

  Blood transport and binding proteins 9       

  Serotransferrin 258 46 74.7 77 6.93 gi|136192 

  Vitamin D-binding protein 12 6 24.3 24.5 5.02 gi|5186337 

  Hemoglobin subunit alpha 10 6 57.4 150.3 8.76 gi|122465 

  Transthyretin 7 5 48 16.1 6.29 gi|1717817 

  C4b-binding protein alpha chain-like 4 3 8.3 67.4 6.14 gi|311265150 

  Transgelin-2-like 3 2 12.6 54.7 6.04 gi|311254018 

  Polyadenylate-binding protein 4-like 2 1 3.8 70.5 9.33 gi|311258948 

  Polypyrimidine tract-binding protein 1 1 1 5 59.9 9.24 gi|47523538 

  Telethonin binding protein 1 1 9.6 18.9 5.38 gi|224809550 

  Channel and receptor derived proteins 15       
  Voltage-dependent anion-selective       

  Channel protein 1 3 1 6.7 30.7 8.62 gi|7505046 

  Signal sequence receptor, alpha 2 1 5.2 32 4.36 gi|297632426 

  Calreticulin 2 1 7 48.3 4.32 gi|290750002 

  Signal recognition particle 68 kda protein 1 1 2.4 70.4 8.65 gi|311266756 

  Lycine receptor subunit alpha-1 1 1 1.4 50.2 8.93 gi|311274089 

  Sodium channel protein 1 1 0.8 206.8 4.92 gi|311266955 

  Transmembrane channel-like protein 1 1 1.8 92.5 5.91 gi|311245910 

  Phosphoinositide 3-kinase adapter protein 1 1 1 1.6 100.7 5.64 gi|194041783 

  Insulin receptor substrate 4 1 1 2.3 53.1 8.83 gi|258590765 

  Transient receptor potential cation channel 1 1 0.9 236.2 8.54 gi|311245919 

  Sodium channel and clathrin linker 1 1 1 6.4 11 4.98 gi|311262562 

  Mitochondrial import receptor subunit TOM34 1 1 3.1 50.9 9.42 gi|311274903 

  Calmodulin-like 1 1 14.8 16.8 4.09 gi|311252670 

  Syntaxin-3-like 1 1 3.9 48.9 8.44 gi|311247613 

  Protease or other enzymes  44       
  Alpha-1-antichymotrypsin 2 32 9 40.2 46.7 6.28 gi|47523270 

  Plasminogen 18 9 15.8 90.6 7 gi|146345485 

  Fumarate hydratase 20 8 11.8 13.9 6.3 gi|47523636 

  Antithrombin-III 28 7 24.8 52.4 5.84 gi|194018664 

  Prothrombin precursor 19 7 18.8 70.1 5.62 gi|172072659 

  Membrane primary amine oxidase-like 12 6 15.7 78.3 6.61 gi|311267153 

  Glyceraldehyde 3-phosphate dehydrogenase 18 4 29.4 35.8 8.57 gi|2407184 

  Serum paraoxonase/arylesterase 1 8 4 18.8 39.9 5.29 gi|167621416 

  Kininogen-1 isoform 2 5 4 11 43.8 6.64 gi|311269761 

  Plasma kallikrein 8 3 7.9 72.3 7.78 gi|47522962 

  L-lactate dehydrogenase B chain 5 3 17.7 36.6 5.57 gi|1107387 

  Beta-enolase 19 2 9.22 47.1 8.05 gi|113205948 

  Pyruvate kinase isozymes 7 2 5.4 64.9 7.98 gi|311260850 

  ATP synthase subunit alpha, mitochondrial 6 2 7.8 59.7 9.21 gi|297591975 

  ATP-dependent RNA helicase A 1 1 4.5 44.6 5.53 gi|311264941 

  Alpha-1-antichymotrypsin 1 5 2 13.8 24.7 5.22 gi|9968809 

  Transketolase 4 2 9.3 67.8 7.21 gi|162952052 

  Carbonic anhydrase 1 3 2 12.7 29 6.67 gi|194037099 

  Pig muscle 3-phosphoglycerate kinase 3 2 8.5 43.4 8.78 gi|13399644 

  ADP/ATP translocase 1-like isoform 1 3 1 6.7 24.7 10.89 gi|311254417 

  Phosphoglycerate mutase 1-like isoform 2 3 1 10.5 28.9 6.51 gi|194041795 

  Ribose-phosphate pyrophosphokinase 3 1 4.7 34.8 8 gi311276762| 

  Carboxypeptidase B2 2 1 4.3 48.6 6.83 gi|194040626 

  Transmembrane protease serine 4-like 2 1 2.5 64.5 8.22 gi|311264000 



 
        

 Table 2. Count’d.         
         

 Bifunctional aminoacyl-trna synthetase 2 1 1 161.1 1.35 gi|311265228 

 Glucosamine--fructose-6-phosphate 2 1 2.7 59.5 7.01 gi|311249541 

 Aminotransferase 2 1 2.7 59.5 7.01 gi|311249541 

 Polypeptide N-acetylgalactosaminyltransferase 2 1 4.8 64.2 8.63 gi|194042623 

 Threonyl-trna synthetase 1 1 4 37.7 6.28 gi|311273548 

 Nicotinamide N-methyltransferase 1 1 9 29.5 5.63 gi|118573081 

 Phosphoinositide 3-kinase adapter protein 1 1 1.5 107.1 5.78 gi|28860138 

 Mismatch repair endonuclease PMS2 1 1 1.9 94 6.31 gi|311250873 

 Alanyl-trna synthetase, cytoplasmic-like 1 1 23.5 8.6 6.12 gi|311257020 

 Adenylosuccinate synthetase 1 1 2 50.1 8.72 gi|189031714 

 Inorganic pyrophosphatase 1 1 6.6 27.5 5.44 gi|311271315 

 Ubiquitin carboxyl-terminal hydrolase 22-A 1 1 2.2 94.4 7.34 gi|311276293 

 Tyrosine-protein kinase 1 1 1 122.6 6.68 gi|311249266 

 Ubiquitin-conjugating enzyme E2 L3 1 1 16.2 17.9 8.68 gi|297591969 

 Serum paraoxonase/arylesterase 1 7 4 14.3 45.6 6.36 gi|118403912 

 Cholinephosphotransferase 1 1 2.2 42.3 9.05 gi|311262709 

 Serine/threonine-protein kinase 25-like 1 1 3.5 48.7 6.18 gi|311273415 

 Serine/threonine-protein kinase Nek5 1 1 0.1 79 8.67 gi|311266294 

 Rho gtpase-activating protein 23-like 1 1 1 131.8 9.06 gi|311268532 

 Carbonyl reductase [NADPH] 3-like 1 1 6.1 30.7 5.57 gi|311270205 

 Cytokines or homones 1         
 Interleukin enhancer-binding factor 2 3 2 13.1 43.1 5.19 gi|311254260 

 Other extracellular or secreted 55         
 Spreading factor 6 4 10.7 52.6 5.6 gi|1351418 

 Heparin cofactor 2 6 4 11.2 55.8 6.5 gi|194043402 

 Matrin-3-like isoform 1 2 2 5.1 94.7 5.87 gi|311250254 

 Elongation factor 1-alpha 2 6 1 6.3 50.2 9.33 gi|311263706 

 60S ribosomal protein L15 2 1 7.8 17.7 11.6 gi|6174950 

 40S ribosomal protein S5-like isoform 1 2 1 9.8 22.9 9.73 gi|311259613 

 Vitamin K-dependent protein S 2 1 5.9 27.6 5 gi|311270126 

 Leucine-rich alpha-2-glycoprotein 2 1 3.8 29.7 7.02 gi|311248408 

 Macrosialin-like isoform 1 1 1 4.3 42.8 9.29 gi|311261974 

 Fibronectin isoform 3 27 18 13.9 239.7 5.72 gi|311273025 

 Histidine-rich glycoprotein 56 12 25.3 61.5 7.2 gi|311269757 

 Gelsolin 30 11 25.7 84.8 5.93 gi|121118 

 Alpha-1B-glycoprotein 42 10 30.8 54.4 5.99 gi|311259609 

 Alpha-2-HS-glycoprotein 59 8 36.3 38.8 5.5 gi|311269753 

 60 kda heat shock protein 21 8 25.1 60.9 5.7 gi|194044029 

 Actin 50 6 31.2 41.7 5.29 gi|311250866 

 Heat shock cognate 71kda protein 26 5 25.9 50.4 5.41 gi|311264120 

 Heat shock 70 kda protein 1B 18 5 17.5 70.1 5.6 gi|56748897 

 Heat shock cognate protein HSP 90-beta 13 5 12.3 83.2 4.96 gi|31160516 

 Heat shock protein HSP 90-alpha 8 3 7.4 84.7 4.93 gi|47522774 

 T-complex protein 1 subunit alpha-like 13 4 15.4 60.3 5.71 gi|194033404 

 Vimentin-like 13 4 11.5 70.3 6.01 gi|257096532 

 Complex of Bdellastasin With Porcine Trypsin 27 3 22.4 23.4 8 gi|257472074 

 Clathrin heavy chain 7 3 3.8 191.6 5.48 gi|224492556 

 Fetuin-B-like 4 3 15.4 41.2 7.4 gi|31126975 

 Zinc-alpha-2-glycoprotein-like 3 3 17.1 34.4 5.88 gi|311250971 

 Eukaryotic translation initiation factor 3 1 1 16.8 12.6 4.84 gi|311253491 

 Lumican-like 7 2 11.4 38.8 5.82 gi|194037683  



 
        

  Table 2. Count’d.       
         

  Ubiquitin-like modifier-activating enzyme 1 5 2 3.4 114.6 5.54 gi|311276235 

  Elongation factor 1-gamma 5 2 11.4 50 6.15 gi|311247489 

  Fascin  3 2 8.5 54.7 6.07 gi|226372953 

  40S ribosomal protein S15 3 2 28.3 17 10.39 gi|51338618 

  Zinc finger protein 7 1 1 1.9 76.3 9.13 gi|311253237 

  Zinc finger protein AEBP2-like 1 1.4 1.4 54.2 5.13 gi|311250679 

  Zinc finger protein 425-like 1 1 2.6 70.6 9.74 gi|311264767 

  Polyubiquitin-C-like 1 1 1.2 80.8 9.36 gi|31127000 
  Adiponectin 1 1 10.3 15.5 8.94 gi|33694199 
  Troponin T  1 1 6.11 31.2 5.92 gi|66773803 
  Transcription activator BRG1 1 1 1.4 165 8.82 gi|311248656 
  Mitogen-activated protein kinase 9 1 1 4 48.4 5.5 gi|311249537 

  Cytotoxic T-lymphocyte protein 4 1 1 4.5 24.4 5.42 gi|12644505 

  Centromere protein F-like 1 1 0.5 351.5 5.07 gi|311265008 

  Transcription factor AP-2 gamma 1 1 4.9 49.1 7.69 gi|178056536 

  Cell division control protein 42 homolog 1 1 6.8 21.3 5.76 gi122063302 

  94 kda glucose-regulated protein 1 1 2.1 92.5 4.75 gi|17865698 

  Ubiquilin-4-like 1 1 3.3 63.9 5.14 gi|311254132 

  Annexin A5-like 1 1 3.9 42.9 5.16 gi|311262609 

  Apoptosis regulator protein 1-like 1 1 2.2 71.8 5.43 gi|311271288 

  C-reactive protein 1 1 11.3 24.9 5.75 gi|628999899 

  Myosin-9  1 1 1 227 5.51 gi|311255169 

  ADP-ribosylation factor 1-like 1 1 15 20.7 6.31 gi|311249487 

  Golgi membrane protein 1-like 1 1 5.9 27.2 4.51 gi|311265509 

  40S ribosomal protein S28 1 1 17.5 9.1 11.03 gi|45268967 

  78 kda glucose-regulated protein 4 4 9.5 73.8 5.68 gi|194033595 

  Leucine-rich PPR motif-containing protein 1 1 2.1 87 7.55 gi311252711 

  Sytokeleton or nuclear related 24       
  Heterogeneous nuclear ribonucleoprotein A1 10 4 20.9 34.2 9.27 gi|116175259 

  Eukaryotic initiation factor 4A-I 11 3 14.5 46.1 5.32 gi|154147660 

  Tubulin beta chain isoform 1 6 3 14 49.7 4.78 gi|194040122 

  Histone H2A type 2-C-like 7 2 37.2 14 10.9 gi|311254405 

  Plastin-2 isoform 1 3 2 6.4 70.2 5.25 gi|194040624 

  Collagen alpha-3(VI) 1 1 0.8 32.1 7.33 gi|194043712 

  Microtubule-associated protein 4-like 3 1 1.87 116.9 5.03 gi|311268808 

  Heterogeneous nuclear ribonucleoprotein A/B 3 1 6.3 32 8.31 gi|162951821 

  Histone H3.1-like 3 1 23.5 15.4 11.13 gi|311259879 
  RNA-binding protein FUS-like 3 1 6.2 52.5 9.4 gi|311251250 
  Plastin-3 isoform 1 2 1 2.4 63.9 5.73 gi|311276826 

  Heterogeneous nuclear ribonucleoprotein F 2 1 4.1 45.7 5.32 gi|311271228 

  Vinculin  2 1 1.7 123.9 5.62 gi|50403675 

  Heterogeneous nuclear ribonucleoprotein Q 1 1 2.9 69.6 8.68 gi|194035295 

  Actin related protein 1 1 8.3 19.7 8.53 gi|19556223 

  Actin  50 6 31.2 41.7 5.29 gi|311250866 

  Nucleolysin TIAR isoform 2 1 1 4.6 43.4 8.1 gi|311271911 

  Heterogeneous nuclear ribonucleoprotein D0 1 1 9.5 22.9 9.47 gi|311262905 

  Small nuclear ribonucleoprotein E 1 1 27.2 10.8 9.46 gi|147903209 

  Histone H3.2 1 1 23.5 15.4 11.27 gi|311254411 

  Histone h1t-like 1 1 5.2 22.2 11.58 gi194039830 

  Nucleophosmin-like isoform 1 1 1 4.8 32.6 4.61 gi|311273930 

  Nuclear envelope pore membrane protein POM 1 1 7.3 31.2 11.43 gi|311265618 

  Sister chromatid cohesion protein PDS5 1 1 3.6 37.1 7.66 gi|311262027 



 
 
 

 

maintenance of cell shape were identified (Hakkinen et 
al., 2010). Some organellar proteins were found 
(including 40S ribosomal protein S15 and 40S ribosomal 
protein S28), as well as a few eukaryotic translation 
initiation factors. Heat-shock proteins (HSPs) are specific 
proteins that can protect cells and play an important role 
in growth, development, differentiation and other 
physiological activities (Arrigo and Simon, 2010; Burel et 
al., 1992). In a word, this overview map of pig serum 
protein provided a large number of reference information.  

According to function information of proteins, we can 
make a particular study of partially serum protein in some 
aspect of disease. Additionally, as can be seen from the 
sub-cellular localization of identified proteins, these 
proteins distributed mainly in nucleus, cytoplasm, 
extracellular matrix, mitochondrion cytoskeleton, and 
perform their functions in these areas. Therefore, sub-
cellular localization of protein from serum has potential 
values in research on diseases.  

Due to the limited number of pig proteins available in 
the public databases, protein annotation for some of the 
proteins was impossible and a number of peptide mass 
fingerprinting was unmatched effectively. The identifi-
cation of total proteins in pig serum will be achievable as 
soon as the complete and accurately annotated genome 
and protein sequence databases for pig become 
available. 
 

 
ACKNOWLEDGEMENTS 

 
This work was supported by the earmarked fund for 
China Agriculture Research System (CARS-39). The 
authors wish to thank the journal editors and anonymous 
reviewers for their editing and revision of the manuscript. 
 

 
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