**3.1 Free peptides analysis**

The analyses to investigate the "peptidomic" both in healthy and in pathological samples were accomplished by using a gel-free approach. The peptide component of the eluted fraction was analyzed by tandem mass spectrometry. The stringency of scoring parameters of the MASCOT algorithm minimized the number of false positive identifications. Most MS/MS spectra giving positive hits were derived from doubly and triply charged precursor ions that resulted predominantly in y-ion series.

Triplicate LC-MS/MS analysis of supernatants after ACN precipitation of serum proteins, showed the occurrence of many free peptides in both analyzed sera. As reported in Table 1, the total number of detected and identified peptides was 41. Among these, 9 peptides were unique in the pathologic sample. It should be noted that some peptides were identified in both samples.

A Proteomic Approach to Investigate Myocarditis 355

**m/z RT Sequence Peptide Protein H/M** 

693.06 13.06 SSSYSKQFTSSTSYNRGDSTFESKS (576-600) **P02671** Fibrinogen alpha

733.83 14.48 SSSYSKQFTSSTSYNRGDSTFESKSY (576-601) **P02671** Fibrinogen alpha

619.75 17.89 QGVNDNEEGFF (31-41) **P02675** Fibrinogen beta

663.26 16.54 QGVNDNEEGFFS (31-42) **P02675** Fibrinogen beta

696.28 17.64 QGVNDNEEGFFSA (31-43) **P02675** Fibrinogen beta

851.07 22.22 TLEIPGNSDPNMIPDGDFNSYVR (957-979) **P0C0L4** Complement

489.96 20.26 RHPDYSVVLLLR (169-180) **P02768** Serum Albumin 0.43±0.17 417.91 16.67 KFQNALLVRY (426-435) **P02768** Serum Albumin H: not

547.31 16.25 KVPQVSTPTLVEVSR (438-452) **P02768** Serum Albumin H: not

781.37 17.84 TATSEYQTFFNPR (315-327) **P00734** Prothrombin H: not

803.76 21.14 AATVGSLAGQPLQERAQAWGERL (210-232) **P02649**Apolipoprotein E 0.02 Table 1. List of free peptides identified by LC-MS/MS. Averaged area of chromatographic peaks from healthy(H) and myocarditis (M) ratio, indicates that some of them were differently represented. Peptide sequences were validated by MALDI-TOF/TOF analyses

868.46 25.47 TGIFTDQVLSVLKGEE (86-101) **P02655**Apolipoprotein

572.95 12.91 DALSSVQESQVAQQAR (45-60) **P02656**Apolipoprotein

1447)

R (14-38) **P00488** Coagulation

PR (13-38) **P00488** Coagulation

ELQGVVPR (7-38) **P00488** Coagulation

404.55 18.90 RIHWESASLL (1310-

402.22 14.29 THRIHWESASLLR (1308-

445.25 16.98 SKITHRIHWESASLL (1305-

415.20 7.60 HWESASL (1312-

471.74 16.21 HWESASLL (1312-

1054.53 25.86 DDPDAPLQPVTPLQLFEGR (1429-

868.11 21.57 AVPPNNSNAAEDDLPTVELQGVVP

920.14 21.09 RAVPPNNSNAAEDDLPTVELQGVV

837.93 21.39 TAFGGRRAVPPNNSNAAEDDLPTV

too.

**ratio** 

M: not detected

M: not detected

detected

detected

detected

detected

detected

H: not detected

H: not detected

detected

detected

detected

H: not detected

H: not detected

factor XIII A 2.40±0.84

factor XIII A 23.60±3.61

factor XIII A 91.32±7.39

chain 3.25±0.89

chain 1.97±0.41

chain 2.31±0.53

chain

chain

1319) **P01024** Complement C3 H: not

1320) **P01024** Complement C3 H: not

1319) **P01024** Complement C3 H: not

1318) **P01024** Complement C3 H: not

1319) **P01024** Complement C3 H: not

C4-A

**P0C0L4** Complement C4-A

C-II

C-III


**m/z RT Sequence Peptide Protein H/M** 

AAYHPF (658-687)

<sup>F</sup>(662-687)

FR (662-688)

379.71 0.55 LAEGGGVR (28-35) **P02671** Fibrinogen alpha

453.24 3.65 FLAEGGGVR (27-35) **P02671** Fibrinogen alpha

510.76 11.29 DFLAEGGGVR (26-35) **P02671** Fibrinogen alpha

539.27 11.70 GDFLAEGGGVR (25-35) **P02671** Fibrinogen alpha

597.77 15.59 SGEGDFLAEGGGV (22-34) **P02671** Fibrinogen alpha

603.79 12.57 EGDFLAEGGGVR (24-35) **P02671** Fibrinogen alpha

632.30 13.50 GEGDFLAEGGGVR (23-35) **P02671** Fibrinogen alpha

655.28 16.03 DSGEGDFLAEGGGV (21-34) **P02671** Fibrinogen alpha

675.81 13.67 SGEGDFLAEGGGVR (22-35) **P02671** Fibrinogen alpha

690.80 16.13 ADSGEGDFLAEGGGV (20-34) **P02671** Fibrinogen alpha

733.33 14.04 DSGEGDFLAEGGGVR (21-35) **P02671** Fibrinogen alpha

768.85 14.08 ADSGEGDFLAEGGGVR (20-35) **P02671** Fibrinogen alpha

851.71 13.58 SSSYSKQFTSSTSYNRGDSTFES (576-598) **P02671** Fibrinogen alpha

567.95 17.09 QAGAAGSRMNFRPGVLS (650-666)

513.78 17.70 YYLQGAKIPKPEASFSPR (627-644)

1005.98 22.78 QLGLPGPPDVPDHAAYHPF (669-687)

757.71 19.96 SRQLGLPGPPDVPDHAAYHPF (667-687)

823.17 22.11 MNFRPGVLSSRQLGLPGPPDVPDH

681.85 22.07 PGVLSSRQLGLPGPPDVPDHAAYHP

576.90 20.69 PGVLSSRQLGLPGPPDVPDHAAYHP

**ratio** 

H:not detected

H:not detected

H:not detected

0.68±0.18

0.27±0.09

0.18±0.03

H:not detected

chain 25±3.11

chain 2.48±0.57

chain 1.33±0.76

chain 3.15±1.02

chain 0.85±0.23

chain 2.42±0.63

chain 2.72±0.71

chain 1.23±0.36

chain 2.32±0.58

chain 3.25±0.82

chain 1.59±0.12

chain 6.16±1.01

chain 0.65±0.17

**Q14624** Inter-alphatrypsin inhibitor heavy chain H4

**Q14624** Inter-alphatrypsin inhibitor heavy chain H4

**Q14624** Inter-alphatrypsin inhibitor heavy chain H4

**Q14624** Inter-alphatrypsin inhibitor heavy chain H4

**Q14624** Inter-alphatrypsin inhibitor heavy chain H4

**Q14624** Inter-alphatrypsin inhibitor heavy chain H4

**Q14624** Inter-alphatrypsin inhibitor heavy chain H4


Table 1. List of free peptides identified by LC-MS/MS. Averaged area of chromatographic peaks from healthy(H) and myocarditis (M) ratio, indicates that some of them were differently represented. Peptide sequences were validated by MALDI-TOF/TOF analyses too.

A Proteomic Approach to Investigate Myocarditis 357

Fig. 2. Two-dimensional electrophoresis gels of healthy (A) and myocarditis affected (B) sera proteins. Arrows and numbers in (B) correspond to numbers of identified spots in Table 2. It should be underlined that all the spots we further analysed were taken from the

15 Q14624 Inter-alpha-trypsin inhibitor heavy chain H4

22 P36955 Pigment epithelium-derived factor 23 P36955 Pigment epithelium-derived factor 24 P36955 Pigment epithelium-derived factor Table 2. List of proteins identified by LC-MS/MS of spots excised from two-dimensional

16 P08603 Complement factor H 17 P08603 Complement factor H 18 P03952 Plasma kallikrein 19 P06727 Apolipoprotein A-IV 20 P00738 Haptoglobin 21 P00738 Haptoglobin

(a) (b)

**Spot Accession number Protein** 1 P02790 Hemopexin 2 P02790 Hemopexin 3 P02790 Hemopexin 4 P02790 Hemopexin 5 P02790 Hemopexin 6 P02787 Serotransferrin 7 P01008 Antithrombin III 8 P01008 Antithrombin III 9 P01011 Alpha-1 antichymotrypsin 10 P01024 Complement C3 11 P04196 Histidine rich glycoprotein 12 P01024 Complement C3 13 P00738 Haptoglobin 14 P04196 Histidine rich glycoprotein

pathologic serum and results are summarized in Table 2.

gels of sera taken from myocarditis affected patients.

As a whole, the LC-MS/MS proved to be a very sensitive and reproducible analysis which led to the identification of very weakly present peptides, these data were confirmed by another fragmentation technique, MALDI-TOF/TOF. As Fig. 1 shows, the fragmentation pattern of the peptide –ADSGEGDFLAEGGGVR- (from alpha fibrinogen protein) confirm what we found using LC-MS/MS analysis. Some of these peptides are related to different proteolytic activities on proteins involved in acute phase or inflammatory events, such as myocarditis itself. Among identified peptides, the molecular species , namely, peptide 662- 668 from inter-alpha-trypsin inhibitor heavy chain H4 and peptide 1305-1319 from complement C3 correspond to free bioactive peptides, whose activity might be related again to inflammatory events (van den Broek I et al, 2010, ter Weeme M, et al, 2009). Preliminary qualitative and quantitative differences were detected in the analysis of the peptidomas from healthy and pathological samples. In fact, as reported in the Table 1 , averaged area of each peak of all detected peptides resulted to be different, showing that some of them were differently represented in each sample. The above mentioned peptides from complement C3 and inter-alpha trypsin inhibitor were poorly represented in the healthy serum samples, whereas fibrinogen alpha chain peptides were strongly represented in these sera, as well as coagulation factor XIII A peptides.

Fig. 1. Positive ion mode MALDI-TOF/TOF fragmentation spectrum of m/z 1536.44 corresponding to peptide 20-35 from fibrinogen alpha chain protein from healthy serum.

#### **3.2 The proteins profile from 2D-electrophoresis is different**

After depletion of the most abundant proteins, a two dimensional electrophoretic separation of the two sera samples was performed, thus leading to the construction of 2D protein maps of healthy and myocarditis samples. Each gel was blue comassie stained. Image analysis was performed on the two sets of 2D maps (from healthy control and pathologic sera) clearly showing that the protein profile is quite different, as reported in figure 2. The protein spots which resulted to be differentially expressed in the two samples were then submitted to mass spectral identification. Fig 2 shows all the spots we chose.

As a whole, the LC-MS/MS proved to be a very sensitive and reproducible analysis which led to the identification of very weakly present peptides, these data were confirmed by another fragmentation technique, MALDI-TOF/TOF. As Fig. 1 shows, the fragmentation pattern of the peptide –ADSGEGDFLAEGGGVR- (from alpha fibrinogen protein) confirm what we found using LC-MS/MS analysis. Some of these peptides are related to different proteolytic activities on proteins involved in acute phase or inflammatory events, such as myocarditis itself. Among identified peptides, the molecular species , namely, peptide 662- 668 from inter-alpha-trypsin inhibitor heavy chain H4 and peptide 1305-1319 from complement C3 correspond to free bioactive peptides, whose activity might be related again to inflammatory events (van den Broek I et al, 2010, ter Weeme M, et al, 2009). Preliminary qualitative and quantitative differences were detected in the analysis of the peptidomas from healthy and pathological samples. In fact, as reported in the Table 1 , averaged area of each peak of all detected peptides resulted to be different, showing that some of them were differently represented in each sample. The above mentioned peptides from complement C3 and inter-alpha trypsin inhibitor were poorly represented in the healthy serum samples, whereas fibrinogen alpha chain peptides were strongly represented in these sera, as well as

Fig. 1. Positive ion mode MALDI-TOF/TOF fragmentation spectrum of m/z 1536.44 corresponding to peptide 20-35 from fibrinogen alpha chain protein from healthy serum.

After depletion of the most abundant proteins, a two dimensional electrophoretic separation of the two sera samples was performed, thus leading to the construction of 2D protein maps of healthy and myocarditis samples. Each gel was blue comassie stained. Image analysis was performed on the two sets of 2D maps (from healthy control and pathologic sera) clearly showing that the protein profile is quite different, as reported in figure 2. The protein spots which resulted to be differentially expressed in the two samples were then submitted

**3.2 The proteins profile from 2D-electrophoresis is different** 

to mass spectral identification. Fig 2 shows all the spots we chose.

coagulation factor XIII A peptides.

Fig. 2. Two-dimensional electrophoresis gels of healthy (A) and myocarditis affected (B) sera proteins. Arrows and numbers in (B) correspond to numbers of identified spots in Table 2.

It should be underlined that all the spots we further analysed were taken from the pathologic serum and results are summarized in Table 2.


Table 2. List of proteins identified by LC-MS/MS of spots excised from two-dimensional gels of sera taken from myocarditis affected patients.

al., 2010).

A Proteomic Approach to Investigate Myocarditis 359

easy to handle strategy to give preliminary insights for the comparison of glycoproteomes in healthy and pathological human sera, by using a single Con A affinity chromatography step coupled with mass spectrometry techniques. The strategy led both to the identification of 69 different glycosylation sites within 49 different proteins and to the definition of the glycosylation patterns. Moreover, glycoform distribution in myocarditis and hepatic carcinoma has been reported. The analysis of glycan profiling, once extracted from serum glycopeptides, is essential for comparative studies on different sera samples thus providing a useful tool for the development of screening procedures (Carpentieri A, Giangrande C, et

In this paper, a different simple and rapid procedure to obtain an overview of the glycosylation sites profiling in the two samples was accomplished. This was achieved by enriching for the N-linked glycopeptides resulting from trypsin digestion of sera samples in order to enhance the identification of N-glycosylation sites using LC-MS/MS. The analyses

To reduce the complexity of the whole sample, Boronate affinity purification was rapidly performed in batch after tryptic digestion. Thanks to the vicinal diols binding capacity no discrimination on the basis of the glycan type was performed thus, in a proof of principle, all glycopeptides could be selected. The recovered glycopeptides were then deglycosylated

The analyses were performed on intact serum samples without any pre-purification step or removal of most abundant proteins. The peptide component of the eluted fraction was analysed by tandem mass spectrometry. Similar analyses were carried out on the unbound

The data were then pooled and summarised in Table 3. The results presented here demonstrated that Boronate affinity chromatography on serum tryptic digests is a useful tool to enhance the detection by LC-MS/MS of glycopeptide. Another advantage of the strategy relies on the fact that it was performed on glycopeptides instead of glycoproteins, therefore there were no SDS-PAGE step, no isolation of the individual glycoproteins and no *in situ* digestion. This allowed the detection of less abundant glycopeptides together with the most represented ones, such as those deriving from albumins or immunoglobulins. As shown in Table 3, all the selected peptides still contained the conserved N-glycosylation motif (Asn-X-Ser/Thr), thus indicating that N-glycosylation peptides were isolated with high selectivity. This analysis led both to the localization of the modification sites and

The presence of a putative N-glycosylation site was confirmed by the fact that peptides mass was increase of 1 Da, due to the conversion of Asn into Asp after PNGase F incubation. However, some non-specific peptides, namely non-glycosylated peptides, were detected in the eluted Boronate fraction, and identified as belonging to most abundant proteins like

Spontaneous deamidation seems rather unlikely for generating the results presented, although it cannot be excluded completely. Most MS/MS spectra giving positive hits were derived from doubly charged precursor ions that resulted predominantly in y-ion series. As a whole, using Boronate affinity approach we could confirm the previously identified glycosylation sites based on ConcanavalinA enrichment and 5 more glycosylation sites were identified thus refining previous data (Carpentieri A, Giangrande C, et al., 2010) on

by PNGase F treatment and the peptide mixtures directly analysed by LC-MS/MS.

have been carried out by using healthy sera as control.

identification of glycoproteins.

myocarditis glycoproteome.

albumin.

Boronate fractions, mainly containing non-glycosylated peptides.

Proteins excised from the gel were reduced alkylated and, in situ, digested with trypsin. The resulting peptide mixtures were directly analysed by LC-MS/MS according to the peptide mass fingerprinting procedure. MS and MS-MS obtained data were used to search for a nonredundant sequence using the in-house MASCOT software, taking advantage of the specificity of trypsin and of the taxonomic category of the samples. The number of measured masses that matched within the given mass accuracy of 20 ppm was recorded and the proteins that had the highest number of peptide matches were examined.

Thanks to this approach, we could identify many proteins differently expressed in the two sera. Among identified proteins, hemopexin (Dooley H et al., 2010) , complement C3 (Adamsson Eryd S et al., 2011, Onat A et al., 2011), plasma kallikrein (Kolte D et al.,2011) are undoubtedly related to inflammatory events and most interestingly they resulted clearly over expressed in the pathologic sample.

A preliminary speculation on identified proteins might involve the function of hempopexin. As shown by literature data (Dooley H et al., 2010, : Mauk MR et al., 2011, Larsen R et al.,2010), hemopexin is a serum protein with the very well known function of scavenging the heme released or lost by the turnover of heme proteins such as haemoglobin or by haemolysis caused by parasitic infection, and thus protects the body from the oxidative damage that free heme can cause (Larsen R et al.,2010). Myocarditis itself it's not related to haemolysis phenomena, but some viral infections may cause it, therefore, finding a very high level of hempoxin in a myocarditis affected patient might be a putative marker of the inflammation itself (quite common are in fact viral myocarditis).

Moreover we found some connections between differently expressed proteins in pathologic serum and identified free peptides; in particular we could detect some free peptides some peptides from proteins Complement C3, Inter-alpha-trypsin inhibitor heavy chain H4, Antithrombin III which results over expressed in pathologic serum, (see Tab 1).

#### **3.3 Boronate affinity chromatography**

The third part of this work focus on the investigation of one of the most important posttranslational modification, the glycosylation. The importance of investigation of posttranslational modifications (PTM) is notably increased in the proteomic era, as they play a critical role in cellular functioning and they vary in response to environmental stimuli, signalling modulators or development of diseases (Laurell E et al., 2011). PTMs can affect biological functions thus playing a critical role in cellular functioning. Moreover, they can vary in response to environmental stimuli, thus finely tuning cellular mechanisms and their deregulation might be involved in the development of diseases. A huge number of different types of PTMs have been identified but only a few are reversible and important for regulation of biological processes (Wu C et al. 2011). The pattern of PTMs on proteins constitute a molecular code that dictates protein conformation, cellular location, macromolecular interactions and activities, depending on cell type, tissue and environmental conditions. Understanding this code is the major challenge of proteomics in post-genomic era. Existing methodologies for PTMs identification essentially rely on specific enrichment procedures able to selectively increase the amount of modified peptides. These procedures have to be integrated with sophisticated mass spectrometric experiments to address the identifications of PTMs. The development of a variety of new technologies for exploring the structures of the sugar chains has opened up a new frontier in the glycomics field. Moreover recent progress in mass spectrometry led to new challenges in glycomics, including the development of rapid glycan enrichment. Recently our group introduced an

Proteins excised from the gel were reduced alkylated and, in situ, digested with trypsin. The resulting peptide mixtures were directly analysed by LC-MS/MS according to the peptide mass fingerprinting procedure. MS and MS-MS obtained data were used to search for a nonredundant sequence using the in-house MASCOT software, taking advantage of the specificity of trypsin and of the taxonomic category of the samples. The number of measured masses that matched within the given mass accuracy of 20 ppm was recorded and

Thanks to this approach, we could identify many proteins differently expressed in the two sera. Among identified proteins, hemopexin (Dooley H et al., 2010) , complement C3 (Adamsson Eryd S et al., 2011, Onat A et al., 2011), plasma kallikrein (Kolte D et al.,2011) are undoubtedly related to inflammatory events and most interestingly they resulted clearly

A preliminary speculation on identified proteins might involve the function of hempopexin. As shown by literature data (Dooley H et al., 2010, : Mauk MR et al., 2011, Larsen R et al.,2010), hemopexin is a serum protein with the very well known function of scavenging the heme released or lost by the turnover of heme proteins such as haemoglobin or by haemolysis caused by parasitic infection, and thus protects the body from the oxidative damage that free heme can cause (Larsen R et al.,2010). Myocarditis itself it's not related to haemolysis phenomena, but some viral infections may cause it, therefore, finding a very high level of hempoxin in a myocarditis affected patient might be a putative marker of the

Moreover we found some connections between differently expressed proteins in pathologic serum and identified free peptides; in particular we could detect some free peptides some peptides from proteins Complement C3, Inter-alpha-trypsin inhibitor heavy chain H4,

The third part of this work focus on the investigation of one of the most important posttranslational modification, the glycosylation. The importance of investigation of posttranslational modifications (PTM) is notably increased in the proteomic era, as they play a critical role in cellular functioning and they vary in response to environmental stimuli, signalling modulators or development of diseases (Laurell E et al., 2011). PTMs can affect biological functions thus playing a critical role in cellular functioning. Moreover, they can vary in response to environmental stimuli, thus finely tuning cellular mechanisms and their deregulation might be involved in the development of diseases. A huge number of different types of PTMs have been identified but only a few are reversible and important for regulation of biological processes (Wu C et al. 2011). The pattern of PTMs on proteins constitute a molecular code that dictates protein conformation, cellular location, macromolecular interactions and activities, depending on cell type, tissue and environmental conditions. Understanding this code is the major challenge of proteomics in post-genomic era. Existing methodologies for PTMs identification essentially rely on specific enrichment procedures able to selectively increase the amount of modified peptides. These procedures have to be integrated with sophisticated mass spectrometric experiments to address the identifications of PTMs. The development of a variety of new technologies for exploring the structures of the sugar chains has opened up a new frontier in the glycomics field. Moreover recent progress in mass spectrometry led to new challenges in glycomics, including the development of rapid glycan enrichment. Recently our group introduced an

Antithrombin III which results over expressed in pathologic serum, (see Tab 1).

the proteins that had the highest number of peptide matches were examined.

inflammation itself (quite common are in fact viral myocarditis).

over expressed in the pathologic sample.

**3.3 Boronate affinity chromatography** 

easy to handle strategy to give preliminary insights for the comparison of glycoproteomes in healthy and pathological human sera, by using a single Con A affinity chromatography step coupled with mass spectrometry techniques. The strategy led both to the identification of 69 different glycosylation sites within 49 different proteins and to the definition of the glycosylation patterns. Moreover, glycoform distribution in myocarditis and hepatic carcinoma has been reported. The analysis of glycan profiling, once extracted from serum glycopeptides, is essential for comparative studies on different sera samples thus providing a useful tool for the development of screening procedures (Carpentieri A, Giangrande C, et al., 2010).

In this paper, a different simple and rapid procedure to obtain an overview of the glycosylation sites profiling in the two samples was accomplished. This was achieved by enriching for the N-linked glycopeptides resulting from trypsin digestion of sera samples in order to enhance the identification of N-glycosylation sites using LC-MS/MS. The analyses have been carried out by using healthy sera as control.

To reduce the complexity of the whole sample, Boronate affinity purification was rapidly performed in batch after tryptic digestion. Thanks to the vicinal diols binding capacity no discrimination on the basis of the glycan type was performed thus, in a proof of principle, all glycopeptides could be selected. The recovered glycopeptides were then deglycosylated by PNGase F treatment and the peptide mixtures directly analysed by LC-MS/MS.

The analyses were performed on intact serum samples without any pre-purification step or removal of most abundant proteins. The peptide component of the eluted fraction was analysed by tandem mass spectrometry. Similar analyses were carried out on the unbound Boronate fractions, mainly containing non-glycosylated peptides.

The data were then pooled and summarised in Table 3. The results presented here demonstrated that Boronate affinity chromatography on serum tryptic digests is a useful tool to enhance the detection by LC-MS/MS of glycopeptide. Another advantage of the strategy relies on the fact that it was performed on glycopeptides instead of glycoproteins, therefore there were no SDS-PAGE step, no isolation of the individual glycoproteins and no *in situ* digestion. This allowed the detection of less abundant glycopeptides together with the most represented ones, such as those deriving from albumins or immunoglobulins.

As shown in Table 3, all the selected peptides still contained the conserved N-glycosylation motif (Asn-X-Ser/Thr), thus indicating that N-glycosylation peptides were isolated with high selectivity. This analysis led both to the localization of the modification sites and identification of glycoproteins.

The presence of a putative N-glycosylation site was confirmed by the fact that peptides mass was increase of 1 Da, due to the conversion of Asn into Asp after PNGase F incubation. However, some non-specific peptides, namely non-glycosylated peptides, were detected in the eluted Boronate fraction, and identified as belonging to most abundant proteins like albumin.

Spontaneous deamidation seems rather unlikely for generating the results presented, although it cannot be excluded completely. Most MS/MS spectra giving positive hits were derived from doubly charged precursor ions that resulted predominantly in y-ion series.

As a whole, using Boronate affinity approach we could confirm the previously identified glycosylation sites based on ConcanavalinA enrichment and 5 more glycosylation sites were identified thus refining previous data (Carpentieri A, Giangrande C, et al., 2010) on myocarditis glycoproteome.

A Proteomic Approach to Investigate Myocarditis 361

**P02790** Hemopexin SWPAVGN\*CSSALRH,M

**Q13439** Golgin subfamily A

**P00738** Haptoglobin

**P04196** Histidine rich

**P05155** Plasma protease C1

**P01857** Ig alpha-1 chain C

**P01859** Ig gamma-2 chain C

**P01860** Ig gamma-1 chain C

**P01591** Immunoglobulin J

**P40189** Interleukin-6 receptor

**P11279** 

**Q5VU65** 

**P27169** 

**Q9Y275** 

glycoprotein

region

region

Lysosome-associated membrane glycoprotein 1

Nuclear pore membrane glycoprotein 210-like

Serum paraoxanase/arylester ase1

Tumor necrosis factor ligand superfamily member 13B

**P36955** Pigment epithelium

**P01871** Ig mu chain C region YKN\*NSDISSTRH

**Protein Sequence Peptide** 

member 4 HN\*STLKQLMREFNTQLAQKH 1990-2008

ALPQPQN\*VTSLLGCTHH,M

VVLHPN\*YSQVDIGLIKH,M MVSHHN\*LTTGATLINEQWLLTTAKH ,M NLFLN\*HSEN\*ATAKH,M

VEN\*TTVYYLVLDVQESDCSVLSRH VIDFN\*CTTSSVSSALANTKH,M

LSLHRPALEDLLLGSEAN\*LTCTLTGL

TKPREEQFN\*STFRH TPLTAN\*ITKH

region EEQYN\*STYRH,M 136-144

chain EN\*ISDPTSPLRH,M 48-58

beta QQYFKQN\*CSQHESSPDISHFERM 812-833

GLTFQQN\*ASSMCVPDQDTAIRM

derived factor VTQN\*LTLIEESLTSEFIHDIDRH 282-303

**P56199** Integrin alpha-1 SYFSSLN\*LTIRM 1096-1106 **P29622** Kallistatin DFYVDEN\*TTVRH 232-242 **P01042** Kininogen-1 LNAENN\*ATFYFKH,M 389-400

**Q9HC10** Otoferlin NEMLEIQVFN\*YSKVFSNKH,M 59-76

**Q9Y5E7** Protocadherin beta 2 ETRSEYN\*ITITVTDFGTPRM 414-432

**P49908** Selenoprotein P EGYSN\*ISYIVVNHQGISSRH 79-97

RH 127-153

DPAFKAAN\*GSLRM 314-325

EVVVN\*ASSRH 1551-1559

HAN\*WTLTPLKH 250-259

CIQNMPETLPN\*NSCYSAGIAKM 232-252

inhibitor VGQLQLSHN\*LSLVILVPQNLKH,M 344-364

181-193 447-462

236-251 179-202 203-215

61-83 121-139

168-180 200-208

44-54 204-223


**P01011** Alpha-1-

**P02763** Alpha-1-acid

**P01009** Alpha-1-antitrypsin

**P04114** Apolipoprotein B-100

**O75882** Attractin

**P08603** Complement

**P02748** Complement

**P02765** Alpha-2-HS-

**Q03591** Complement factor H

factor H

glycoprotein

**P01023** Alpha-2-

glycoprotein

macroglobulin

**P43652** Afamin DIENFN\*STQKH,M

**P02749** Apolipoprotein H VYKPSAGN\*NSLYRH

**P00450** Ceruloplasmin EHEGAIYPDN\*TTDFQRH,M

**Q14517** Protocadherin-fat 1 QVYN\*LTVRAKDKM

**P01008** Antithrombin III LGACN\*DTLQQLMEVFKH,M

**P05090** Apolipoprotein D ADGTVNQIEGEATPVN\*LTEPAKM 83-104

**P10909** Clusterin LAN\*LTQGEDQYYLRH,M 372-385 **Q8IWV2** Contactin-4 LN\*GTDVDTGMDFRM 64-76 **P05156** Complement factor 1 FLNN\*GTCTAEGKH,M 100-111 **P01024** Complement C3 TVLTPATNHMGN\*VTFTIPANRH 74-94 **P0C0L4** Complement C4-A GLN\*VTLSSTGRH,M 1326-1336

**Protein Sequence Peptide** 

SVQEIQATFFYFTP**N\***KTEDTIFLRH,M QDQCIY**N\***TTYLNVQRH,M

YLGN\*ATAIFFLPDEGKH,M QLAHQSN\*STNIFFSPVSIATAFAMLSL GTKH ADTHDEILEGLNFN\*LTEIPEAQIHEGF QELLRH,M

SLGNVN\*FTVSAEALESQELCGTEVPS

YAEDKFN\*ETTEKH

SLTFN\*ETYQDISELVYGAKH,M

FN\*SSYLQGTNQITGRH,M FVEGSHN\*STVSLTTKH AEEEMLEN\*VSLVCPKM YDFN\*SSMLYSTAKM

LGN\*WSAMPSCKM

IDSTGN\*VTNELRH,M GPVKMPSQAPTGNFYPQPLLN\*SSMC LEDSRH

EN\*LTAPGSDSAVFFEQGTTRH,M

ISEEN\*ETTCYMGKH MDGASN\*VTCINSRH,M IPCSQPPQIEHGTIN\*SSRM SPDVIN\*GSPISQKH

component C9 AVN\*ITSENLIDDVVSLIRH,M 413-430

related protein 1 LQNNENN\*ISCVERH 120-132

FSMDYKTGALTVQN\*TTQLRSRM

VCQDCPLLAPLN\*DTRH,M AALAAFNAQNN\*GSNFQLEEISRH

VPEHGRKH 864-886

58-81 87-101

268-283 64-93 94-125

28-37 396-407

124-139 183-201

1522-1536 3405-3419 27-41 3462-3474

> 155-167 251-261

411-422 1023-1052

> 129-144 396-414

907-919 1024-1036 868-885 212-224

994-1005 1930-1950

> 145-159 166-187

antichymotrypsin YTGN\*ASALFILPDQDKH,M 268-283


A Proteomic Approach to Investigate Myocarditis 363

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Table 3. LC/MSMS analysis for the identification of glycosylation sites, H indicates peptides deriving from healthy serum and M indicates the ones from myocarditis serum.
