Proteomic analysis of porcine saliva

The Veterinary Journal 187 (2011) 356–362

Contents lists available at ScienceDirect

The Veterinary Journal journal homepage: www.elsevier.com/locate/tvjl

Proteomic analysis of porcine saliva A.M. Gutiérrez a, I. Miller b,*, K. Hummel c, K. Nöbauer c, S. Martínez-Subiela a, E. Razzazi-Fazeli c, M. Gemeiner b, J.J. Cerón a a

Department of Animal Medicine and Surgery, University of Murcia, 30100 Espinardo, Murcia, Spain Department of Biomedical Sciences, University of Veterinary Medicine Vienna, Veterinaerplatz 1, A-1210 Vienna, Austria c VetOMICS Core Facility for Research, University of Veterinary Medicine Vienna, Veterinaerplatz 1, A-1210 Vienna, Austria b

a r t i c l e

i n f o

Article history: Accepted 22 December 2009

Keywords: Proteome Saliva Porcine Two-dimensional electrophoresis Mass spectrometry Immunoblotting Biomarkers

a b s t r a c t Saliva contains a number of proteins that may be useful as biomarkers of health and disease and can be easily obtained from large numbers of animals in a non-invasive, stress-free way. The objective of this study was to explore the protein composition of porcine saliva from 10 specific pathogen free pigs using first one-dimensional SDS–PAGE and then two-dimensional electrophoresis and mass spectrometry. A reference proteome pattern for porcine saliva was established with the identification of 13 different, mainly saliva-specific, proteins. These reference data will facilitate the investigation of salivary proteins potentially altered in disease and could serve as novel diagnostic biomarkers. Ó 2009 Elsevier Ltd. All rights reserved.

Introduction Proteomics is the large-scale characterisation of proteins expressed by a genome (Conrad et al., 2008). This form of analysis has been facilitated by the development of three key technologies: (1) multi-dimensional protein separation; (2) mass spectrometry (MS) to identify the separated proteins; and (3) bioinformatics to analyse large protein databases (Rudney et al., 2009). By using proteomic methodology, up- and down-regulation as well as modification of proteins associated with specific diseases can be revealed (Hogarth et al., 2004) and both have potential as diagnostic biomarkers (Deutsch et al., 2008). An advantage of this approach is that a panel of proteins (rather than a single protein biomarker) is identified and tends to correlate more reliably with specific conditions, such as Alzheimer’s disease and rheumatoid arthritis (Xiao et al., 2005; Papale et al., 2008). Although most salivary proteins originate in the salivary glands (Tabak, 2001), saliva also contains serum-derived proteins, which may have potential as biomarkers (Papale et al., 2008) as alterations in the human salivary protein profile have been associated with disease (Huang, 2004; Wong, 2006). As a diagnostic sample, saliva has a number of advantages: the collection procedure is simple, stress-free and non-invasive and large numbers of patients can

* Corresponding author. Tel.: +431 25077 4224; fax: +431 25077 4290. E-mail address: [email protected] (I. Miller). 1090-0233/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.tvjl.2009.12.020

be individually and repeatedly sampled within a short period of time (Kaufman and Lamster, 2002). Characterisation of the salivary proteome is essential to the development and validation of salivary-based diagnostics (Hu et al., 2005; Guo et al., 2006; Sondej et al., 2009). To date, such analysis of porcine saliva has not been carried out, although use of a serum protein-map, to illustrate differences between healthy pigs and pigs with post-weaning multisystemic wasting syndrome (PMWS) has been published recently (Miller et al., 2009). The present study used one- and two-dimensional electrophoresis (2-DE), MALDI-TOF/TOF MS and Western blotting to obtain the profile of salivary proteins in healthy pigs and to compare it with those sub-clinically infected with porcine circovirus type-2 (PCV-2), Mycoplasma hyopneumoniae and porcine respiratory and reproductive syndrome (PRRS) virus.

Materials and methods Animal selection All procedures were approved by the Murcia University Ethical Committee. Saliva samples were collected from male, Duroc-(Landrace-Large White) crossbred animals at the beginning of the fattening period (average age 120 days), from two premises in South-east Spain. All of the pigs were clinically normal and were divided into two groups of 10 according to the health status of the farm. Group one came from a specific pathogen free (SPF) unit and group two animals from a farm that had experienced both PCV-2 infection and PRRS during the fattening period.

A.M. Gutiérrez et al. / The Veterinary Journal 187 (2011) 356–362 Sample collection Saliva samples were collected using Salivette tubes (Sarstedt) and a sponge, as previously described (Gutiérrez et al., 2009b). In brief, animals were allowed to chew on the sponge until it was thoroughly moistened. The sponges were then placed in the tubes and centrifuged for 10 min at 3000 g to obtain approximately 0.5–1 mL saliva/sponge. Blood samples were collected from the jugular vein into Vacutainers and were allowed to clot for 1 h at room temperature prior to centrifugation (2000 g for 15 min) to obtain serum. Serum and saliva samples were stored at 20 °C until analysed. Serological and biochemical analysis Animal disease status was assessed using serology and acute phase protein (APP) estimations of C-reactive protein (CRP) and haptoglobin (Hp) in saliva. Serum samples were analysed for specific antibodies to the following pathogens by ELISA according to the manufacturer’s instructions: PCV-2 (Ingenasa); pseudorabies virus (Hipra laboratories); M. hyopneumoniae (Hipra Laboratories); and PRRS virus (IDEXX Laboratories). Serum was also assessed for PRRS virus using PCR (Roche). Concentrations of CRP and Hp were measured using time-resolved immunofluorimetric assays (TR-IFMAs) (Gutiérrez et al., 2009a,b). The limit of detection (LOD) was 0.52 ng/mL and 0.47 ng/mL for Hp and CRP, respectively, and the coefficients of variation for intra- and inter-assay precision were <12% for both assays. Using TR-IFMAs, serum and salivary APP concentrations have previously been found to highly correlate with coefficients of correlation (r) of 0.70 and 0.79 for CRP and Hp, respectively (Gutiérrez et al., 2009a,b). SDS–polyacrylamide gel electrophoresis One-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE) was used to separate the major components in the saliva of the healthy and sub-clinically infected animals. After determination of the total protein content of the sample (Bradford, 1976), electrophoresis was performed according to the method of Laemmli (1970). Briefly, appropriately diluted samples were reduced with dithiothreitol (DTT) at 95 °C and separated on 140  140  1.5 mm gradient gels (10–15% T, 2.7% C) in a Hoefer SE 600 vertical electrophoresis chamber (Hoefer Scientific Instruments). Gels were silver-stained to visualise the protein patterns (Miller and Gemeiner, 1992). Two-dimensional electrophoresis An immobilised pH gradients (IPG)-DALT system was used to carry out 2-DE, using home-made gels for both dimensions according to standard protocols1 with modifications (Miller et al., 2004). First-dimensional IPGs were run under reducing and denaturing conditions in a Multiphor II electrophoresis chamber (GE Healthcare Life Sciences) in non-linear gradients (pH 4–10) (Gianazza et al., 1985) of 11 cm in length. Equilibration of the strips with DTT and iodoacetamide (Bjellqvist et al., 1993) was followed by SDS–PAGE as described above. Gels were silver-stained, either for analysis (Miller and Gemeiner, 1992), or for MS where the use of aldehyde was omitted in a number of steps (Miller et al., 2004). Protein identification by Western blot Immunoblotting was performed after 2-DE to detect specific proteins. The proteins were transferred onto nitrocellulose (GE Healthcare) by semi-dry blotting (Hoefer Semi-Phor TE 70, Hoefer Scientific Instruments) and tested using appropriate primary and horseradish peroxidase (HRPO)-conjugated secondary antibodies. The primary antibodies used were anti-human immunoglobulin (Ig) G (Fc-specific, Dako), anti-human IgA (a-chain specific, Sigma), and anti-human kappa and lambda Ig light chains (Sigma). All antibodies used had been previously assessed for cross-reactivity with the corresponding porcine Ig (Miller et al., 2009). Immunoglobulin M was detected using an anti-porcine IgM (l-chain specific, Bethyl Laboratories). Secondary antibodies used were HRPO-conjugated anti-goat (Accurate Chemicals) or anti-rabbit (Sigma) IgG followed by application of a chromogen (4chloro-1-naphthol) (Miller and Gemeiner, 1992) or ECL (enhanced chemiluminescence) detection (GE Healthcare). Mass spectrometry using MALDI-TOF/TOF Sample preparation Prominent 2-DE ‘spots’ were excised, washed, reduced with DTT, alkylated with iodoacetamide and in-gel digestion with trypsin (Trypsin Gold, Mass Spectrometry Grade, Promega) was carried out (Shevchenko et al., 1996). In order to enhance peptide ionisation and the sensitivity of MS, dried peptides were de-salted using ZipTips C18 (microbed) (Millipore) according to the manufacturer’s instructions.

Derivatisation for de novo sequencing In order to enhance the quality of tandem mass spectrometry (MS/MS) spectra for de novo sequencing, N-terminal chemical modification using 4-sulfophenyl isothiocyanate (SPITC) was carried out with some modifications (Wang et al., 2004; Zhang et al., 2008). The remaining de-salted peptide solution was used for derivatisation with SPITC (4 lL of 5 mg/mL SPITC in 20 mM ammonium bicarbonate buffer [pH 8.5]) for 1 h at 56 °C. Following evaporation of the derivatisation solution, the remaining peptides were de-salted using ZipTips C18 (microbed). Spotting and mass spectrometry De-salted peptides (0.5 lL) were spotted onto a disposable AnchorChip MALDI target plate pre-spotted with a-cyano-4-hydroxycinnamic acid (PAC target, Bruker Daltonics). Data were acquired on a Matrix Assisted Laser Desorption Ionisation Tandem Time-of-Flight (MALDI-TOF/TOF) mass spectrometer (Ultraflex II, Bruker Daltonics) in MS and MS/MS modes. Spectra processing and peak annotation were carried out using FlexAnalysis and Biotools (Bruker Daltonics). Data analysis and de novo peptide sequencing For standard database searches, processed spectra were searched via Mascot2 in the Swiss-Prot database (release 56.5) or in NCBInr (20090314) using the following search parameters: taxonomy mammalian; global modifications carbamido-methylation on cysteine; variable modifications oxidation on methionine; MS tolerance 100– 150 ppm; MS/MS tolerance 1 Da; one missed cleavage allowed. Identifications were considered statistically significant where a < 5%. Peptide sequencing was carried out manually using FlexAnalysis. These sequences were then used for a homology search using MS-BLAST,3 FASTS4 and MShomology.5

Results On serological and APP analysis, differences between healthy and infected animals were identified. On serology, group one control SPF pigs were seronegative for PCV-2 and PRRS virus and to M. hyopneumoniae while each of the group two animals was seropositive to each of the above pathogens. All animals were seronegative for pseudorabies virus. The median concentrations of CRP were 25– 50 ng/mL for group one and 62 ng/mL for sub-clinically infected group two pigs. Medians of 1.4 lg/mL and 5 lg/mL were found for Hp for group one and two animals, respectively. The concentrations of salivary Hp and CRP in sub-clinically infected animals were significantly higher than in the controls (P < 0.05) (Fig. 1). The average total protein concentration in saliva was 0.68 mg/mL and 2.4 mg/mL for group one and group two animals, respectively. Using SDS–PAGE a complex banding pattern was obtained for the saliva samples, with protein bands in the range <10– >100 kDa (Fig. 2). Electrophoresis under reducing conditions revealed mainly quantitative changes in the protein composition of samples from the same group, but also of samples between the two groups. Typically, an increase in the intensity of proteins of approximate molecular weight 67, 40, 25 and 19 kDa was obtained in group one SPF relative to group two infected pigs (Fig. 2) (supplementary material, Table 3). Other changes were not consistent within or between the groups. As it was assumed that there would be overlap of proteins of similar molecular weight, we proceeded with 2-DE, as this provides a more detailed pattern because the proteins are separated according to their isoelectric points (pI) in the first dimension. A typical 2-DE pattern from the saliva from a group one control animal is shown in Fig. 3, and represents the same sample in lane 7 in the one-dimensional SDS–PAGE (Fig. 2). A further saliva sample is illustrated in Fig. 5. The 2-DE gel images indicated that there are multiple spot chains or clusters in different parts of the gel, in some cases with different pI, but of overlapping molecular weight. Thus, 2-DE facilitated the visualisation of proteins not clearly sep2 3 4

1

SWISS-2DPAGE database. See: http://us.expasy.org/ch2d/protocols.

357

5

See: See: See: See:

www.matrixscience.com. http://dove.embl-heidelberg.de/Blast2/msblast.html. http://fasta.bioch.virginia.edu/fasta_www2/fasta_www.cgi?rm=select. http://prospector.ucsf.edu.

358

A.M. Gutiérrez et al. / The Veterinary Journal 187 (2011) 356–362

Fig. 1. C-reactive protein (CRP, A) and haptoglobin (Hp, B) concentrations in saliva samples from healthy SPF (n = 10) and sub-clinically infected (n = 10) pigs, as determined by time-resolved immunofluorimetric assays. The plot shows the median (line within box), 25th and 75th percentiles (box), 5th and 95th percentiles (whiskers) and outliers (°). Differences statistically significant where P < 0.05 () and P < 0.005 ().

Healthy

Mr [kD]

Sub-clinically infected

94 67 43

30

20 14

1

2

3

4

5

6

7

8

9 10 11

1

2

3

4

5

6

7

8

9 10 11

Fig. 2. SDS–PAGE according to Laemmli on polyacrylamide gels (size: 140  140  1.5 mm [10–15% T, 2.7% C]). Proteins (2.5 lg according to protein determination) were reduced and applied per lane. After the electrophoretic separation, protein bands were detected by silver-staining. Lane 1 represents the molecular weight marker LMW. Lanes 2–11 on left and right gels represent saliva samples from 10 healthy SPF and 10 sub-clinically infected pigs, respectively. Mr, molecular weight. Main band differences outlined by boxes.

arated in one-dimensional patterns. Spots for MS identification were selected because of their abundance (medium to high) and their frequent occurrence in samples from the controls. In general, only one characteristic spot of a spot chain was subjected to MS, assuming that the identification obtained was valid for the whole spot chain. All of the proteins that could be identified by MALDI-TOF/TOF are illustrated in Fig 3. Twenty-four different spots were successfully analysed by MS, resulting in the identification of 10 different proteins in the gel. Due to the conditions used for protein separation in 2-DE, proteins appear as single spots, spot chains (with spots of different pI but approximately similar molecular weight) or several spot chains (sub-units). Therefore, several spots belonging to the same protein may be found on the gel, either in close proximity to each other (in

case of modifications) or in different parts of the gel (sub-units, breakdown products). This is illustrated for salivary lipocalin (Fig. 3) and for immunoglobulins (Figs. 4 and 5). Given that current databases do not contain all the protein-related data for pigs to reliably identify proteins based on their tryptic peptide pattern (peptide mass fingerprinting), de novo sequencing was applied (Tables 1 and 2). Comparing the 2-DE patterns obtained from our saliva samples with the published pig serum protein-map revealed similarities, particularly in regions where immunoglobulins are located (Miller et al., 2009). In total, 13 proteins could be reliably identified in the salivary 2-DE pattern, these included IgA heavy and light chains (Fig. 4) and the heavy chains of IgG and IgM (Fig. 5). In samples from group two, sub-clinically infected animals, immunoglobulin levels were higher.

359

A.M. Gutiérrez et al. / The Veterinary Journal 187 (2011) 356–362

Mr [kD]

Mr [kD]

94

μ

94 1

67

67 2

43

3

α

43

γ

4 5 6 7

30

L

30

9 8 10

20

14

16

15

17 18

14

19

20

11 12

13

21 20

14

22 23 24

pI 4

pI 4

Fig. 3. Protein spots successfully identified by MALDI-TOF/TOF from sample from a healthy animal (corresponding to lane 7 of left gel in Fig. 2) marked with circles (numbering corresponds with data in Tables 1 and 2). (1) Serum albumin precursor, (2) adenosine deaminase, (3) alpha-amylase I precursor, (4–7, 11) carbonic anhydrase, (8–10, 12, 20) salivary lipocalin precursor, (13, 14, 18, 19) prolactin– inducible protein homologue precursor, (15–17) lipocalin 1 precursor, (21–22) double-headed protease inhibitor from sub-mandibular salivary gland, (23) cystatin B and (24) calgranulin C. Mr, molecular weight.

Mr[kD]

94 67

IgA α-chain

43 30

Ig light chains

20

pI

10

10

4

10

Fig. 4. Two-dimensional electrophoresis on sample from same healthy animal featured in Fig. 3 with blotting onto nitrocellulose and probing with anti-humanIgA (upper half) and anti-human kappa and lambda chain (lower half) immunoglobulins (Ig). Mr, molecular weight.

The heavy chain of IgG appeared at a molecular weight of approximately 50 kDa, while those of IgM and IgA were found around 80 and 55–60 kDa, respectively. Light chains of immunoglobulins were detected between 26 and 30 kDa.

Discussion In order to identify potential biomarkers of health and disease in saliva, a complete profile of the proteins detectable, such as that provided by proteomic methods, is required (Hu et al., 2005; Guo

Fig. 5. Two-dimensional electrophoresis on sample from a sub-clinically infected animal (corresponds to lane 7 of the right gel in Fig. 2) and identification of immunoglobulin chains. Positions of immunoglobulin heavy (a, c, l) and light (L) chains outlined (determined by Western blotting in Fig. 4). Mr, molecular weight.

et al., 2006; Sondej et al., 2009). In this study, we assessed the potential of 1- and 2-DE to separate porcine salivary proteins. The serological findings in the two groups of animals was in line with their infection status and similarly the median salivary APP concentrations from control pigs were lower than those from the sub-clinically infected animals (Gutiérrez et al., 2009c). Onedimensional electrophoresis was carried out to compare the overall protein banding pattern in saliva, based on molecular weight, between the sub-clinically infected and control pigs. The main differences in SDS–PAGE were quantitative in nature. Two-DE was used to obtain higher protein resolution and thus avoid the overlap of proteins of similar molecular weight and revealed a highly complex pattern of single spots, spot chains and clusters of several spots. Immunoblotting and MS facilitate the identification of electrophoretically separated proteins in 2-DE gels and have been successfully used in the establishment of a 2-DE pig serum protein-map (Miller et al., 2009). However, given the paucity of commercially available antibodies against porcine, or even human, salivary proteins, protein identification relied on the use of MALDI-TOF/TOF. The use of algorithms, such as MASCOT (Perkins et al., 1999), to identify pig salivary proteins resulted in successful identification in only half of the searches performed. Although this percentage improved when MS/MS was used, almost one-third of the spots remained unidentified. To achieve significant levels of identification using this approach either the porcine protein must be present in the database, or the structural identity of the peptides with a homologous protein of a different species is needed. Where proteins from a species with little sequence information are being assessed, de novo sequencing and homology-tolerant database searches are required (Shevchenko et al., 2001; Mackey et al., 2002; Kayser et al., 2004). When the identification results of all three search algorithms in our study were compared, there were consistent ‘hits’ for every search query, although in some cases there were species differences between search engines. Furthermore, in MS BLAST and FASTS, which provide information on the statistical significance of the hits, all proved statistically significant, underlining the validity of our homology identifications. Immunoblotting was used to identify the different Ig chains as

360

A.M. Gutiérrez et al. / The Veterinary Journal 187 (2011) 356–362

Table 1 Proteins in porcine saliva identified by database search following two-dimensional electrophoresis and MALDI-TOF/TOF mass spectrometry. Spot number

Protein

Accession number

Identification method

MASCOT score (PMF/MSMS)

Peptides matched

Sequence coverage (%)

Expected molecular weight (Da)

Expected isoelectric point

1 2 3

Serum albumin precursor (ALBU_PIG) Adenosine deaminase (ADA_MOUSE) Pancreatic alpha-amylase precursor (AMYP_PIG) Carbonic anhydrase VI (Sus scrofa) Carbonic anhydrase VI (Sus scrofa) Carbonic anhydrase VI (Sus scrofa) Carbonic anhydrase VI (Sus scrofa) Salivary lipocalin precursor (SAL_PIG) Salivary lipocalin precursor (SAL_PIG) Salivary lipocalin precursor (SAL_PIG) Carbonic anhydrase VI (Sus scrofa) Salivary lipocalin precursor (SAL_PIG)

P08835 P03958 P00690

PMF/MSMSa MSMSa, de novoc PMF/MSMSa

102*/224** –/46** 92*/174**

16/4 –/1 18/4

22/9% –/3% 33/11%

71,643 40,251 57,791

6.08 5.48 6.52

gi|221136928 gi|221136928 gi|221136928 gi|221136928 P81608 P81608 P81608 gi|221136928 P81608

PMF/MSMSb PMF/MSMSb PMF/MSMSb PMF/MSMSb MSMSa, de novoc PMF/MSMSa PMF/MSMSa MSMSb, de novoc MSMSb de novoc MSMSa, de novoc

98*/407** 119*/236** 81*/185** 70*/170** –/142** 92*/242** 94*/356** –/111** –/172**

10/4 12/4 11/3 7/3 –/2 11/5 10/5 –/4 –/2

39/22% 33/13% 22/7% 18/9% –/10% 42/25% 45/23% –/11% –/14%

36,402 36,402 36,402 36,402 21,859 21,859 21,859 36,402 21,859

6.15 6.15 6.15 6.15 5.19 5.19 5.19 6.15 5.19

–/76**

–/1

–/7%

17,145

5.84

**

–/1

–/7%

17,145

5.84

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Prolactin-inducible protein homologue precursor (PIP_RABIT) Prolactin-inducible protein homologue precursor (PIP_RABIT) Lipocalin-1 (precursor) (LCN1_PIG) Lipocalin-1 (precursor) (LCN1_PIG) Lipocalin-1 (precursor) (LCN1_PIG) Prolactin-inducible protein homologue precursor (PIP_RABIT) Prolactin-inducible protein homologue precursor (PIP_RABIT) Salivary lipocalin precursor (SAL_PIG)

P60990

Double-headed protease inhibitor, submandibular gland (IPSG_MARMT) Double-headed protease inhibitor, submandibular gland (IPSG_MARMT) Cystatin-B (CYTB_PIG) Protein S100-A12, calgranulin C (S10AC_PIG)

P81482

a

c

P60990

MSMS , de novo

–/93

P53715 P53715 P53715 P60990

PMF/MSMSa PMF/MSMSa PMF/MSMSa MSMSa, de novoc

72*/224** 52/163** 126*/398** –/91**

5/3 6/2 9/4 –/1

42/19% 31/19% 42/39% –/7%

19,511 19,511 19,352 17,145

5.00 5.00 5.00 5.84

P60990

MSMSa, de novoc

–/89**

–/1

–/7%

17,145

5.84

P81608

MSMSb de novoc de novoc

–/189**

–/2

–/14%

21,859

5.19

13,444

6.96

13444

6.96

11,181 10,739

5.19 5.67

c

P81482

de novo

Q29290 P80310

MSMSa PMF/MSMSa

44/281** 79*/352**

3/3 5/5

42/42% 57/57%

PMF, identified by peptide mass fingerprint; MSMS, identified by tandem mass spectrometry. a Database SWISSPROT. b Database NCBInr. c De novo. Details in Table 2. * Statistically significant identification in PMF P < 0.05. ** Statistically significant identification by MSMS P < 0.05.

Table 2 Proteins in porcine saliva identified by a homology search after de novo sequencing. Spot number 2 8 11

12 13 14 18 19 20 21 22 a b c

a

MS BLAST

M[I|L][I|L]T[I|L]EDEA[I|L]YTR DMGFTEEEFKR VEHIR VGDGVYTVAYY WTYSDGELDEAHWSR SVQYNPA[I|L]R PVTEVHVVHYNSF VGDGVYTVAYYGENKFR TF[Q|K][I|L]MEFYGR YTSCLCDDYPR [K|Q][I|L]G[I|L]CP[K|Q]D[K|Q]AV[I|L]P[I|L]AANR YTSCLCDDYPR PND[K|Q]AV[I|L]P[I|L]AANR YTSCLCDDYPR PND[K|Q]AV[I|L]P[I|L]AANR YTSCLCDDYPR PND[K|Q]AV[I|L] VGDGVYTVAYYGENKFR TF[Q|K][I|L]MEFYGR TYSSEC[I|L]FCF[I|L]S[Q|K]E EW[I|L]P[I|L]CGGD GASVACTR TYSSEC[I|L]FCF[I|L]S[Q|K]E

Adenosine deaminase

ADA_HUMAN 153* SAL_PIG 131* CAH6_SHEEP 211*

ADA_MOUSE 3.5 e 9* SAL_PIG 1.7 e 10* CAH6_SHEEP 1.9 e 15*

ADA_MOUSE 97 SAL_PIG 86 CAH6_SHEEP 153

Prolactin-inducible protein homologue precursor

SAL_PIG 207* PIP_RABIT 161*

Prolactin-inducible protein homologue precursor

PIP_RABIT 138*

Prolactin-inducible protein homologue precursor

PIP_RABIT 138*

Prolactin-inducible protein homologue precursor

PIP_CAVPO 105* SAL_PIG 207* IPSG_MARMT 108* IPSG_MARMT 104*

SAL_PIG 1 e 24* PIP_RABIT 8.5 e 16* PIP_RABIT 7.3 e 13* PIP_RABIT 7.3 e 13* PIP_RABIT 2.2 e 9* SAL_PIG 1 e 24* IPSG_MARMT 2.4 e 9* IPSG_MARMT 5.3 e 8*

SAL_PIG 147 PIP_CAVPO 129 PIP_CAVPO 111 PIP_CAVPO 111 PIP_CAVPO 89 SAL_PIG 147 IPSG_MARMT 101 IPSG_MARMT 88

Carbonic anhydrase VI

Salivary lipocalin precursor

Salivary lipocalin precursor Double-headed protease inhibitor, sub-mandibular salivary gland Double-headed protease inhibitor, sub-mandibular salivary gland

MS BLAST search: database sp_nrdb; scoring matrix PAM30MS; *scores statistically significant according to software. FASTS search: database Swissprot; scoring matrix BLOSUM 62; *scores <1 e 4 statistically significant. MS homology search: database Swissprot; scoring matrix BLOSUM 62; 70% homology; no threshold scores for significance available.

MS homology

c

Protein

Salivary lipocalin precursor

FASTS

b

Peptide sequence searched

A.M. Gutiérrez et al. / The Veterinary Journal 187 (2011) 356–362

antibodies against the porcine or human forms of these proteins were available and the identification of these proteins by MS is difficult because of their highly variable regions. In total, 13 different proteins were identified, in addition to Hp and CRP detected by TR-IFMA. The latter two proteins were not found in the 2-DE pattern, most likely because their concentrations, even in the sub-clinically infected animals, were below the detection limit of this method. A previous study also reported difficulties identifying APP by MS in bovine milk (Hogarth et al., 2004). In general, the detection of such low-abundance proteins using this method would require pre-fractionation of the samples to remove the highly abundant proteins (Hu et al., 2005). There has been little 2-DE analysis of the proteins in the saliva of humans (Ghafouri et al., 2003; Huang, 2004; Hu et al., 2005; Wong, 2006; Sondej et al., 2009), the only species investigated. Using a fluorescent staining method, Ghafouri et al. (2003) established a 2-DE protein-map of approximately 600 spots, of which 101 were successfully identified by MS, resulting in the identification of 20 unique proteins. Multiple spots of proteins occur due to fragmentation, bacterial degradation, endogenous truncation, glycosylation (Sondej et al., 2009), and phosphorylation. Alphaamylase, albumin, IgA and IgG, carbonic anhydrase VI, prolactininducible protein, lipocalin-1 and cystatins, identified in human saliva, were also found in our samples, although at slightly different or multiple gel positions. In addition to detecting saliva-specific proteins, we also identified serum-derived proteins as described by Giusti et al. (2007). Most of the proteins identified are involved in the immune response or modulate anti-inflammatory activity including Ig, carbonic anhydrase VI (Kivelä et al., 1999; Vitorino et al., 2004), cystatin B (Giusti et al., 2007), and lipocalin (Vitorino et al., 2004). Carbonic anhydrase VI is involved in the prevention of dental caries (Kivelä et al., 1999), cystatins have antimicrobial activities and lipocalin may act as a scavenger of pro-inflammatory lipids (Vitorino et al., 2004), or in pigs, as a pheromonebinding protein (Guiraudie et al., 2003). Adenosine deaminase regulates lymphocyte proliferation (Charlab et al., 2001) and may have potential as a tumour biomarker (Schmalstieg et al., 1977). De novo sequencing identified spots 21 and 22 as the double-headed protease inhibitor secreted by the sub-mandibular salivary gland (see Supplementary material, Fig. 6). This protein is composed of two homologous actively inhibiting halves, which can inhibit trypsin and elastase.6 To the authors’ knowledge this is the first time that this protein has been identified in a biological fluid using proteomics. Its function in the pig remains unclear. Some of the bands in the 1-DE banding pattern may be attributed to albumin (at 67 kD), to the heavy chains of IgM (at 80 kD), IgG and IgA (between 55 and 60 kD) and to Ig light chains (between 26 and 30 kD). The considerable overlap of proteins noticed in 2-DE, especially at molecular weights <30 kD, suggests that use of one-dimensional SDS–PAGE in such an analysis is limited.

Conclusions Thirteen medium- to high-abundance proteins have been identified in porcine saliva using proteomic methods. A number of these saliva-specific proteins, as well as other serum-derived proteins, may have potential as biomarkers of health and disease in the pig and further research is required to elucidate their specific functions. 6

UniProtKB/Swiss-Prot. See: http://www.uniprot.org/uniprot/P81482.

361

Conflict of interest statement None of the authors of this paper has a financial or personal relationship with other people or organisations that could inappropriately influence or bias the content of the paper. Acknowledgements This study has been possible thanks to Integrated Action (HA2008-0016) between the Department of Animal Medicine and Surgery of The University of Murcia, Spain and the Department of Biomedical Sciences, The University of Veterinary Medicine, Vienna, Austria and a grant from the Spanish Ministry of Education and Science (AGL 2006-05701). Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.tvjl.2009.12.020. References Bjellqvist, B., Pasquali, C., Ravier, F., Sánchez, J.-C., Hochstrasser, D.F., 1993. A nonlinear wide-range immobilized pH gradient for two dimensional electrophoresis and its definition in a relevant pH scale. Electrophoresis 14, 1357–1365. Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Analytical Biochemistry 72, 248–254. Charlab, R., Valenzuela, J.G., Andersen, J., Ribeiro, J.M., 2001. The invertebrate growth factor/CECR1 subfamily of adenosine deaminase proteins. Gene 267, 13–22. Conrad, D.H., Goyette, J., Thomas, P.S., 2008. Proteomics as a method for early detection of cancer: a review of proteomics, exhaled breath condensate, and lung cancer screening. Journal of General Internal Medicine 23, 78–84. Deutsch, O., Fleissig, Y., Zaks, B., Krief, G., Aframian, D.J., Palmon, A., 2008. An approach to remove alpha amylase for proteomic analysis of low abundance biomarkers in human saliva. Electrophoresis 29, 4150–4157. Ghafouri, B., Tagesson, C., Lindhal, M., 2003. Mapping of proteins in human saliva using two-dimensional gel electrophoresis and peptide mass fingerprinting. Proteomics 3, 1003–1015. Gianazza, E., Giacon, P., Sahlin, B., Righetti, P.G., 1985. Non-linear pH courses with immobilized pH gradients. Electrophoresis 6, 53–56. Giusti, L., Baldini, C., Bazzichi, L., Ciregia, F., Tonazzini, I., Mascia, G., Giannaccini, G., Bombardieri, S., Lucacchini, A., 2007. Proteome analysis of whole saliva: a new tool for rheumatic diseases-the example of Sjögren’s syndrome. Proteomics 7, 1634–1643. Guiraudie, G., Pageat, P., Cain, A.H., Madec, I., Nagnan-Le Meillour, P., 2003. Functional characterization of olfactory binding proteins for appeasing compounds and molecular cloning in the vomeronasal organ of pre-pubertal pigs. Chemical Senses 28, 609–619. Guo, T., Rudnick, P.A., Wang, W., Lee, C.S., Devoe, D.L., Balgley, B.M., 2006. Characterization of the human salivary proteome by capillary isoelectric focusing/nanoreversed-phase liquid chromatography coupled with ESItandem MS. Journal of Proteome Research 5, 1469–1478. Gutiérrez, A.M., Martínez-Subiela, S., Cerón, J.J., 2009a. Evaluation of an immunoassay for determination of haptoglobin in various biological specimens from swine. American Journal of Veterinary Research 70, 691–696. Gutiérrez, A.M., Martínez-Subiela, S., Eckersall, P.D., Cerón, J.J., 2009b. C-reactive protein quantification in porcine saliva: a minimally invasive test for pig health monitoring. The Veterinary Journal 181, 261–265. Gutiérrez, A.M., Martínez-Subiela, S., Soler, L., Pallarés, F.J., Cerón, J.J., 2009c. Use of saliva for haptoglobin and C-reactive protein quantifications in porcine respiratory and reproductive affected pigs in field conditions. Veterinary Immunology and Immunopathology 132, 218–223. Hogarth, C.J., Fitzpatrick, J.L., Nolan, A.M., Young, F.J., Pitt, A., Eckersall, P.D., 2004. Differential protein composition of bovine whey: a comparison of whey from healthy animals from those with clinical mastitis. Proteomics 4, 2094–2100. Hu, S., Xie, Y., Ramachandran, P., Loo, R.R.O., Li, Y., Loo, J.A., Wong, D.T., 2005. Largescale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry. Proteomics 5, 1714–1728. Huang, C., 2004. Comparative proteomic analysis of human whole saliva. Archives of Oral Biology 49, 951–962. Kaufman, E., Lamster, I.B., 2002. Diagnostic applications of saliva. A review. Critical Reviews in Oral Biology and Medicine 13, 197–212. Kayser, J.P., Vallet, J.L., Cerny, R.L., 2004. Defining parameters for homology-tolerant database searching. Journal of Biomolecular Techniques 15, 285–295. Kivelä, J., Parkkila, S., Parkkila, A., Leinonen, J., Rajaniemi, H., 1999. Salivary carbonic anhydrase isoenzyme VI. Journal of Physiology 520, 315–320.

362

A.M. Gutiérrez et al. / The Veterinary Journal 187 (2011) 356–362

Laemmli, U.K., 1970. Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature 222, 680–685. Mackey, A.J., Haystead, T.A.J., Pearson, W.R., 2002. Getting more from less – algorithms for rapid protein identification with multiple short peptide sequences. Molecular and Cellular Proteomics 1, 139–147. Miller, I., Gemeiner, M., 1992. Two-dimensional electrophoresis of cat sera: protein identification by cross reacting antibodies against human serum proteins. Electrophoresis 13, 450–453. Miller, I., Friedlein, A., Tsangaris, G., Maris, A., Fountoulakis, M., Gemeiner, M., 2004. The serum proteome of Equus caballus. Proteomics 4, 3227–3234. Miller, I., Wait, R., Sipos, W., Gemeiner, M., 2009. A proteomic reference map for pig serum proteins as a prerequisite for diagnostic applications. Research in Veterinary Science 86, 362–367. Papale, M., Pedicillo, M.C., Di Paolo, S., Thatcher, B.J., Lo Muzio, L., Bufo, P., Rocchetti, T., Centra, M., Ranieri, E., Gesualto, L., 2008. Saliva analysis by surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF/MS): from sample collection to data analysis. Clinical Chemistry and Laboratory Medicine 46, 89–99. Perkins, D.N., Pappin, D.J.C., Creasy, D.M., Cottrell, J.S., 1999. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567. Rudney, J.D., Staikov, R.K., Johnson, J.D., 2009. Potential biomarkers of human salivary function: a modified proteomic approach. Archives in Oral Biology 54, 91–100. Schmalstieg, F.C., Nelson, J.A., Mills, G.C., Monahan, T.M., Goldman, A.S., Goldblum, R.M., 1977. Increased purine nucleotides in adenosine deaminase-deficient lymphocytes. Journal of Pediatrics 91, 48–51.

Shevchenko, A., Sunjaev, S., Loboda, A., Shevchenko, A., Bork, P., Ens, W., Standing, K.G., 2001. Charting the proteomes of organisms with unsequenced genomes by MALDI-quadruple time-of-flight mass spectrometry and BLAST homology searching. Analytical Chemistry 73, 1917–1926. Shevchenko, A., Wilm, M., Vorm, O., Mann, M., 1996. Mass spectrometric sequencing of proteins from silver-stained polyacrylamide gels. Analytical Chemistry 68, 850–858. Sondej, M., Denny, P.A., Xie, Y., Ramachandran, P., Si, Y., Takashima, J., Shi, W., Wong, D.T., Loo, J.A., Denny, P.C., 2009. Glycoprofiling of the human salivary proteome. Clinical Proteomics 5, 52–68. Tabak, L.A., 2001. A revolution in biomedical assessment: the development of salivary diagnostics. Journal of Dental Education 65, 1335–1339. Vitorino, R., Lobo, M.C.J., Ferrer-Correira, A.J., Dubin, J.R., Tomer, K.B., Domingues, P.M., Amado, F.M.J., 2004. Identification of human whole saliva protein components using proteomics. Proteomics 4, 1109–1115. Wang, D., Kalb, S.R., Cotter, R.J., 2004. Improved procedures for N-terminal sulfonation of peptides for matrix-assisted laser desorption/ionization postsource decay peptide sequencing. Rapid Communications in Mass Spectrometry 18, 96–102. Wong, D.T., 2006. Salivary diagnostics powered by nanotechnologies, proteomics and genomics. Journal of the American Dental Association 137, 313–321. Xiao, Z., Prieto, D., Conrads, T.P., Veenstra, T.D., Issaq, A.J., 2005. Proteomic patterns: their potential for disease diagnosis. Molecular and Cellular Endocrinology 230, 95–106. Zhang, X., Rogowska-Wrzesinska, A., Roepstorff, P., 2008. On-target sample preparation of 4-sulfophenyl isothiocyanate-derivatized peptides using AnchorChip targets. Journal of Mass Spectrometry 43, 346–359.