Epilepsy Research and Treatment

Epilepsy Research and Treatment / 2014 / Article

Research Article | Open Access

Volume 2014 |Article ID 236309 | https://doi.org/10.1155/2014/236309

Guglielmo Lucchese, Jean Pierre Spinosa, Darja Kanduc, "The Peptide Network between Tetanus Toxin and Human Proteins Associated with Epilepsy", Epilepsy Research and Treatment, vol. 2014, Article ID 236309, 11 pages, 2014. https://doi.org/10.1155/2014/236309

The Peptide Network between Tetanus Toxin and Human Proteins Associated with Epilepsy

Academic Editor: A. Vezzani
Received07 Mar 2014
Revised24 Apr 2014
Accepted13 May 2014
Published01 Jun 2014


Sequence matching analyses show that Clostridium tetani neurotoxin shares numerous pentapeptides (68, including multiple occurrences) with 42 human proteins that, when altered, have been associated with epilepsy. Such a peptide sharing is higher than expected, nonstochastic, and involves tetanus toxin-derived epitopes that have been validated as immunopositive in the human host. Of note, an unexpected high level of peptide matching is found in mitogen-activated protein kinase 10 (MK10), a protein selectively expressed in hippocampal areas. On the whole, the data indicate a potential for cross-reactivity between the neurotoxin and specific epilepsy-associated proteins and may help evaluate the potential risk for epilepsy following immune responses induced by tetanus infection. Moreover, this study may contribute to clarifying the etiopathogenesis of the different types of epilepsy.

1. Introduction

The term epilepsy defines a group of disturbances whose only recognized commonality is the paroxysmal synchronous discharging of groups of neurons. Localization and physiological function of the neuronal populations involved determine the clinical picture, so that (1) clinical manifestations can be extremely subtle and the diagnosis can be challenging also in terms of differential definition; (2) epilepsy(ies) can produce extremely multiform clinical pictures with a large degree of overlap [13]. Indeed, epileptic syndromes can also be embedded in larger syndromic clinical pictures, that is, West and Lennox-Gastaut syndromes in tuberous sclerosis complex [4, 5]. This clinical diversity has noteworthy nosological implications. Syndromic or disease status of various forms of epilepsy and the terminology used to define them are indeed still matter of debate [79]. Likewise, the molecular etiopathogenesis of epilepsies has to be better defined at the molecular level. Although genetic alterations [1012], inflammation [13], and viral infections [1416] have been considered and thoroughly studied, nonetheless, the molecular basis and the causal mechanisms of epilepsies are still unclear.

Recently, research on epilepsy has also outlined a neurodevelopmental context [1721]. Spontaneous recurrent seizures have been observed after induction of status epilepticus during the second and third postnatal weeks in rodents, by use of chemoconvulsants such as pilocarpine, kainate, and tetanus toxin (TT) [22]. TT seizures as well as experimental febrile seizures and developmental lithium pilocarpine appear to share a common mechanism for enhancing hippocampal network excitability and promoting epilepsy, possibly through alterations in neurotransmitter receptors or voltage-gated ion channels ([23] and further references therein).

Moreover, numerous reports suggest that immune mechanisms might play a role in processes leading to epileptogenesis [15, 2432]. In fact, antibodies against neural antigens involved in neurotransmission have been detected in epileptic subjects [3339], and, remarkably, epilepsy was shown to respond to immunotherapeutic approaches [38, 40, 41]. Finally, population-based cohort studies have documented that microbial infections during pregnancy may be a risk factor for epilepsy in offspring [4245].

In such a multifaceted scientific-clinical context, here we analyze the peptide commonality between TT, a powerful neurotoxin used in animal models of experimental epilepsy [4650], and human antigens that have been related to epilepsy, searching for possible immunological link(s) that might contribute to epileptogenesis. Indeed, a massive peptide overlap characterizes microbial and human proteomes [5154] and gives grounds for questioning whether immune response(s) to microbial infections might potentially result in cross-reactions against neuronal antigens [5558]. Pathogen versus human immune cross-reactivity might contribute to explaining the association between microbial infections and neurological syndromes [59] and assumes a special significance during pregnancy in light of the consequent possible neurodevelopmental alterations in the fetus and offspring [26, 58].

We report that the tetanus neurotoxin and human epilepsy antigens share an ample pentapeptide platform. The bacterial versus human peptide overlap is not random and, importantly, a search through the Immune Epitope Database (IEDB; http://www.immuneepitope.org/) reveals that the shared pentapeptides are part of TT-derived epitopes. The latter datum is relevant also in light of the role of pentapeptides as minimal functional units in cell biology and immunology [60, 61]. On the whole, the results support the possibility that immune cross-reactions may occur between TT and epilepsy-related proteins.

2. Methods

TT protein sequence, UniProtKB/Swiss-Prot accession number: P04958, 1315aa long, from Clostridium tetani (NCBI Taxonomic identifier: 212717; further details at http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi) was analyzed for pentapeptide sharing with epilepsy-associated proteins as follows. First, a pentapeptide library was constructed by dissecting the TT primary sequence into pentapeptides offset by one residue, that is, MPITI, PITIN, ITINN, TINNF, INNFR, and so forth. Then, each of the final 1311 pentamers was analyzed for instances of the same match within a library consisting of primary sequences of human proteins that, when altered, have been associated with epilepsy. The number of matches and the human proteins sharing matches were recorded.

Epilepsy-associated proteins were randomly retrieved from UniProtKB Database (http://www.uniprot.org/). An unbiased set of proteins that on whatever basis (i.e., differential regulation, protein modification, or mutation) had been involved in or related to epilepsy was obtained utilizing “epilepsy” and “Homo sapiens” as keywords. Only canonical protein sequences were considered. At the time of this study, the keyword-guided search produced a library of 133 human UniProt entries, for a total of 106,022aa. Epilepsy-associated proteins are reported as UniProtKB/Swiss-Prot entry names throughout the paper, unless when discussed in detail. Any pentapeptide occurrence in the set of epilepsy-associated proteins was termed a match.

A set of proteins associated with Down syndrome, a genetic disease in which infectious agents have no role, was retrieved from UniProtKB Database and used as a comparison sample. This set was formed by the following proteins listed according to the aa length, with UniProtKB/Swiss-Prot entries in parentheses: (1) Down syndrome critical region protein 10 (P59022, DSC10), 87aa; (2) Down syndrome critical region protein 8 (Q96T75, DSCR8), 97aa; (3) Down syndrome critical region protein 4 (P56555, DSCR4), 118aa; (4) Down syndrome critical region protein 9 (P59020, DSCR9), 149aa; (5) Down syndrome critical region protein 5 or phosphatidylinositol N-acetylglucosaminyltransferase subunit P (P57054, PIGP), 158aa; (6) Down syndrome critical region protein 6 or protein ripply3 (P57055, DSCR6), 190aa; (7) Down syndrome candidate region 1-like 1 or regulator of calcineurin 2 (Q14206, RCAN2), 197aa; (8) Down syndrome candidate region 1-like protein 2 or regulator of calcineurin 3 (Q9UKA8, RCAN3), 241aa; (9) Down syndrome critical region protein 1 or regulator of calcineurin 1 (P53805, RCAN1), 252aa; (10) Down syndrome critical region protein 2 or proteasome assembly chaperone 1 (O95456, PSMG1), 288aa; and (11) Down syndrome critical region protein 3 (O14972, DSCR3), 297aa.

The Immune Epitope Database (IEDB; http://www.immuneepitope.org/) was used to search for TT-derived B- and/or T-cell epitopes that had been experimentally validated as positive in the human host.

Expected occurrences for pentapeptide sharing between C. tetani neurotoxin and human proteins associated with epilepsy were calculated as follows. First, we considered the number of all possible pentapeptides, . Since each residue can be any of 20aa, the number of all possible pentapeptides is given by . Next, we considered the TT and epilepsy-associated proteins as two sets of pentapeptide size and . That is, is the number of pentapeptides present in the TT protein and is the number of pentapeptides present in the epilepsy-associated protein set. If is the number of times a pentapeptide is selected in the TT protein of size and is the number of times the same pentapeptide is selected in the epilepsy-associated protein set, then and . Assuming that and are independent, . In other words, the expected number of times that one pentapeptide will be selected simultaneously in both TT and epilepsy-related protein set is given by . Neglecting the relative abundance of aa and assuming and , we obtain a formula derived by approximation where the total number of occurrences in a second sample (the epilepsy-related protein set) of pentapeptides occurring in the first sample (TT) is given by .

3. Results and Discussion

3.1. Description of the Pentapeptide Sharing between TT and Epilepsy-Associated Proteins

Peptide sharing between TT and human epilepsy-associated proteins was analyzed using (1) the pentapeptide module as a matching probe and (2) a library consisting of 133 epilepsy-related protein sequences retrieved from UniProt (see under Methods).

We used pentapeptides as scanning probes in sequence similarity analyses since a grouping of five aa residues may represent a minimal unit of immune recognition in cellular and humoral responses. Indeed, scientific literature indicates that an optimal peptide length for T-cell epitopes ranges between 9 and 15 residues, with the central 5–7 aa representing the specific immune recognition contacts and the flanking residues determining the binding potential to the MHC molecules [6266]. De facto, the HFMPT pentapeptide was reported to be a minimal antigenic determinant for MHC class I-restricted T lymphocytes [65], while the KYVKQ pentapeptide was demonstrated to be a minimal antigenic determinant for CD4(+) T-cell clones [66]; in addition, the IEDB describes numerous pentapeptide epitopes capable of binding MHC molecules (e.g., epitope IEDB IDs: 5740, 7948, 11514, 25472, and 33701) and inducing T-cell proliferation (e.g., epitope IEDB IDs: 815, 40168, 47974, 59947, 107725, 107725, and 110376) (reviewed in [61]). Likewise, humoral immune recognition/reactivity unfolds around short aa motifs ([6770]; reviewed in [71]). A representative example is a report by Zeng and colleagues [70], according to which the C-terminal pentapeptide (aa sequence: GLRPG) of luteinizing hormone-releasing hormone is a dominant B-cell epitope able to elicit a strong anti-LHRH antibody response and to discriminate between anti-LHRH antibodies present in fertile and nonfertile mice. That is, the pentapeptide GLRPG has immunogenic and antigenic properties and also discriminates antibody specificities associated with reproductive competence.

The analyzed set of 133 human proteins related to epilepsy is listed in Box 1 according to the aa size (i.e., from IR3IP or immediate early response 3-interacting protein 1, 82aa, to GPR98 or monogenic audiogenic seizure susceptibility protein 1 homolog, 6306aa).

Following matching analyses, we found that 42 out of the 133 epilepsy-associated proteins retrieved at random from UniProt database share 58 pentapeptides (68 including multiple occurrences) with the bacterial toxin. Box 2 lists the epilepsy-related proteins that share pentapeptides with TT and the shared pentapeptides. No TT pentapeptide match was found in the comparison set of proteins associated with Down syndrome.

3.2. Nonstochasticity of the Pentapeptide Sharing between TT and Epilepsy-Associated Proteins

The comparative analysis of Boxes 1 and 2 highlights three main points. Firstly, the 68 TT pentapeptide overlap described in Box 2 exceeds the expected value. As detailed under Methods, the expected number of TT pentapeptides that may occur in the epilepsy-related protein set is given by , where is the number of pentapeptides contained in TT (1,311), is the number of pentapeptides contained in the epilepsy-related protein set (105,490), and is the number of all possible pentapeptides (205). Developing the equation gives 43 as expected number of pentapeptide matches, whereas the observed value is 68 (see Box 2). That is, the pentapeptide overlap between TT and epilepsy-related proteins is 1.58 times higher when compared to the expected one.

A second point of note is that the distribution of the pentapeptide overlap through the epilepsy-related proteins is unexpected. According to equation described above, pentapeptide sharing between two samples is as a quantity directly proportional to the number of pentapeptides in the analyzed samples; that is, it is proportional to the protein aa size. Actually, 91 epilepsy-related proteins are excluded from the pentapeptide matching with TT, independently of their length. For example, SPTN1, 2472aa (see Box 1), has no bacterial matches, while LRRC1, 524aa, shares 3 pentapeptides with TT (Box 2).

In summary, a comparative analysis of Boxes 1 and 2 highlights that 68 TT pentapeptide matches are allocated in 42 out 133 human proteins that have been related, when altered, to epilepsy, and no relationship appears to exist between pentapeptide sharing and the human protein size. Applying the equation described above to the set of 42 epilepsy-related proteins sharing 68 pentapeptides with TT and amounting to 50,254aa, the expected pentapeptide overlap is equal to 20, so that the observed occurrence value is 3, 4 times higher.

Finally, a third punctum saliens is that nonrandomness characterizes also the distribution of the TT pentapeptides among the 42 epilepsy-associated proteins. Box 2 shows that a few TT pentapeptides are repeated in the 42 epilepsy-associated protein set. Indeed, TT pentapeptides EIIPS, SLSIG, and FCKAL recur twice, and TT pentapeptides FGGQD, KEIEK, and TFLRD occur three times (Box 2; see pentapeptides underlined). Box 2 also shows that MK10 (mitogen-activated protein kinase 10; 464aa); CDKL5 (cyclin-dependent kinase-like 5; 1030aa); and KCMA1 (calcium-activated potassium channel subunit alpha-1; 1236aa) share two sequentially overlapping pentapeptides with TT, that is, share the hexapeptides SVDDAL, KNSFSE, and PKEIEK, respectively. The nonrandom TT pentapeptide sharing clearly emerges from Figure 1, where expected and observed occurrence values are graphically compared.

It can be seen that, in conflict with the theoretical trend of the TT pentapeptide matching as a function of epilepsy-related protein length (Figure 1, columns in gray), the observed to expected ratio of pentapeptide matching shows no relationship with the human protein length (Figure 1, columns in black). For example, contrary to mathematical expectations, MK10 (464aa long) has three pentapeptide matches, whereas VP13A (3174aa long) has one match (see Box 2 and Figure 1).

3.3. Immunologic Potential of the Pentapeptide Sharing between TT and Epilepsy-Associated Proteins

Having defined the TT versus epilepsy-associated proteins pentapeptide overlap, it was next tested whether such a sharing has an immunologic potential. To this aim we used IEDB, a database that describes B- and T-cell epitopes for humans, nonhuman primates, rodents, and other animal species, and searched for TT-derived epitopes that had been validated as immunopositive in humans. At the time of the search, we obtained a list of 517 TT-derived epitopes. The pentapeptides common to epilepsy-associated proteins and TT (see Box 2, sequences in italic) were used as probes to scan the 517 TT-derived epitope set in order to define potential cross-reactive peptide sequences. Results are reported in Table 1.

IEDB ID1TT-derived epitope2,3Immune context Epilepsy-associated proteins4

1270 afcpeyvptfdnvieNITSL HLA-Class II, allele undeterminedACHA2
1389 afrnVDGSGLVSklig HLA-Class II, allele undeterminedGPR98 D2HDH EPMIP
1501 agevrqiTFRDLpdkfnaylHLA-Class II, allele undeterminedCLCN2
1929 aihlvnnesseVIVHKamdiHLA-DRB1*04:01CLN5
2219 akkqllefDTQSKnilmqyi HLA-Class II, allele undeterminedSCN8A
3156 amltnliifgpgPVLNKNEVHLA-Class II, allele undeterminedASAH1 LRRC1
3418 anskfigiteLKKLEskinkHLA-DRB1*11:01TSC1
3832 apsyTNGKLniyyrrlyngl HLA-DRB5*01:01, HLA-DRB1*13:01WDR62
7603 danLISIDikndlyektl HLA-DRB1*03:01GPR98
8734 dinndiisdiSGFNSsvity HLA-DRB1*01:01GPR98
8778 diSGFNSsvitypdaqlvpg HLA-DRB1*15:01GPR98
/8903 dkisdvstivpyigPALNIvHLA-DPB1*04:01, HLA-DRB1*15:01NMDE1
9297 dltfiaeKNSFSEepfqdei HLA-DRB1*01:01, HLA-DRB1*04:01CDKL5
9595 DPALLLmheLIHVLhglygB-cell
HLA-DR2; HLA-Class II, allele undetermined
9595 drLSSANlyingvlmgsaeiB-cell
HLA-DR2; HLA-Class II, allele undetermined
10472 DTQSKnilqyikanskfigiteLKKLEski HLA-Class II, allele undeterminedSCN8A TSC1
11980 efDTQSKnilmqyikanskfigitel B-cell SCN8A
13095eLIHVLhglygmqvss B-cell
HLA-DR2; HLA-Class I, allele undetermined
13125 eLKKLEskinkvfstpipfsHLA-Class II, allele undeterminedTSC1
13813 eqdpsgattksamltnliifgpgPVLNKNEVHLA-Class II, allele undeterminedASAH1 LRRC1
15087 eysiessmkkHSLSIGSGwsvsl B-cell PWP2 GCP6 CDKL5 RELN
15411 fdkdsnGQYIVnedkfqily HLA-Class II, allele undeterminedPWP2
16155 fiaeKNSFSEepfqdeivsyntk B-cell CDKL5
17134 fnaylankwvfiTITNDrlsHLA-Class II, allele undeterminedNHLC1
17205 fnnftVSFWLRVPKHLA-Class II, allele undeterminedGBRA1 SCN8A
17207 fnnftVSFWLRVPKVsashleHLA-DRB1*11:01, HLA-DR, HLA-DR1, HLA-DR5, HLA-DR7, HLA-DR11, HLA-DPw4, HLA-Class II, allele undeterminedGBRA1 SCN8A EFHC1
17208 fnnftVSFWLRVPKVsashleqyHLA-DRB1*01:01, HLA-DRB1*04:01, HLA-HLA-DRB1*07:01, HLA-DRB1*11:01GBRA1 SCN8A EFHC1
17487 fqilynSIMYGFTEIelgkk HLA-Class II, allele undeterminedSL9A6 SL9A9 LGI1
18217 fvksGDFIKLyvsynnnehivgy B-cell EFHC2 CNTP2
18356fwLRVPKVsashleqygtne HLA-DRB1*11:01SCN8A EFHC1
19469 gevrqiTFRDLpdkfnaylankw B-cell CLCN2
21599 gpdkeqiadeinnlknKLEEKanB-cell ARHG9
22769 gtneysiissmkkHSLSIGS DQB1*06:02, DRB5*01:01PWP2 GCP6 CDKL5
24238 hLKDKIlgcdwyfvptdegwtnd HLA-Class II, allele undeterminedROGDI
25597 idkisdvstivpyigPALNI HLA-Class II, allele undeterminedNMDE1
25666 idsfvksGDFIKLyvsynnnHLA-DRB1*15:01EFHC2 CNTP2
26808 ikiknedltfiaeKNSFSEe HLA-Class II, allele undeterminedCDKL5
27639 ingkaihlvnnesseVIVHKHLA-Class II, allele undeterminedCLN5
29241 ivdynlqskiTLPNDrttpv HLA-Class II, allele undeterminedGPR98
29331 ivkQGYEGnfigHLA-Class II, allele undeterminedTSEAR
29407 ivpyigPALNIv HLA-Class II, allele undeterminedNMDE1
29408 ivpyigPALNIvkQGYEGnf HLA-DRB1*15:01NMDE1 TSEAR
29843 KAKWLgtvntqfqKRSYQHLA-Class II, allele undeterminedLGI2 WDR62
29891 kamdieyNDMFNnftVSFWLrvpB-cell SCN9A GBRA1
30269 kdVQLKNitdymyltnapsy HLA-DRB1*01:01, HLA-DRB1*04:01GPR98
30572 keqiadeinnlknKLEEKanHLA-Class II, allele undeterminedARHG9
32521 knitdymyltnapsyTNGKL HLA-Class II, allele undeterminedWDR62
32546 knldcwvdneEDIDVilkkstil B-cell GABR1
33527 kstilnldinndiisdiSGFNSs B-cell GPR98
34301 kwievyKLVKAKWLgtvntqHLA-DRB1*01:01ARHGA LGI2
34887 lankwvfiTITNDrLSSANlyinB-cell NHLC1 GPR98
35058 lcikiknedltfiaeKNSFS HLA-DRB1*04:01CDKL5
35566 lekryekwievyKLVKAKWLHLA-Class II, allele undeterminedARHGA LGI2
35993 lftFGGQDanLISIDikndlHLA-Class II, allele undeterminedSCN1A SCN2A SCN8A GPR98
36667 lipvassskdVQLKNitdym HLA-DRB1*11:01GPR98
38977 lqrITMTNSVDDALinstkiHLA-Class II, allele undeterminedVP13A MK10
40770 lygmqvsshEIIPSkqeiym HLA-Class II, allele undeterminedACHA2 ACHA4
41527 mfnnftVSFWLRVPKVsashHLA-DRB1*11:01GBRA1 SCN8A EFHC1
42847 mtnSVDDALinstkiysyfpHLA-DRB1*11:01MK10
43280 napsyTNGKLniyyrrlynglkf B-cell WDR62
43519 ndrLSSANlyingvlmgsaeHLA-Class II, allele undeterminedGPR98
43591 neEDIDVilkkstilnldin HLA-Class II, allele undeterminedGABR1
43939 nftVSFWLRVPKHLA-Class II, allele undeterminedGBRA1 SCN8A
43940 nftVSFWLRVPKVsashleHLA-DRB1*11:01GBRA1 SCN8A EFHC1
44007 ngkaihlvnnesseVIVHKamdiB-cell CLN5
44396 nivkQGYEGnfi HLA-Class II, allele undeterminedTSEAR
44200 niddntiyqylyaqkSPTTL HLA-DRB1*01:01SL9A6
44383 NITSLtigkskyfqDPALLLHLA-ClassII, allele undeterminedACHA2 AFG32 CLN6
44557 NKNEVrgivlrvdnknyfpc HLA-Class II, allele undeterminedLRRC1
44667 nldinndiisdiSGFNSsvi HLA-Class II, allele undeterminedGPR98
45102 nnftVSFWLRVPKVsashleHLA-Class II, allele undeterminedGBRA1 SCN8A EFHC1
46136 ntiyqylyaqkSPTTLqrit HLA-Class II, allele undeterminedSL9A6
46853 PALLLmheLIHVLhglygmqHLA-Class II, allele undeterminedCLN6 WDR62
46855 PALNIvkQGYEGnfigalet HLA-Class II, allele undeterminedNMDE1 TSEAR
48049 PKEIEKlytSYLSITFLRDfHLA-Class II, allele undeterminedGCP6 CSMD3 KCMA1 GTR1
48697 pnrdiliasnwyfnhLKDKIlgc B-cell ROGDI
49984 pvtkGIPYApeyksnaastteihB-cell CBPA6
51254 qkSPTTLqrITMTNSVDDALInsB-cell SL9A6 VP13A MK10
56528 ryekwievyKLVKAKWLgtvntq B-cell ARHGA LGI2
57935 sfvksGDFIKLyvsynnneh HLA-ClassII, allele undeterminedEFHC2 CNTP2
57947 sfwLRVPKVsashle HLA-DR5, HLA-DRB1*11:01SCN8A EFHC1
58527 SIGSGwsvslkgnnliwtlk HLA-DRB1*03:01RELN
59500 SLTDLggelcikikn HLA-Class II, allele undeterminedLRRC1
61214 ssmkkHSLSIGSGwsvslkg HLA-Class II, allele undeterminedPWP2 GCP6 CDKL5 RELN
61354 ssskdVQLKNitdymyltnapsy B-cell GPR98
62073 SVDDALinstkiysyfpsviskvnqGAQGIlHLA-Class II, allele undeterminedMK10
63277 tdymyltnapsyTNGKLniy HLA-DRB1*01:01, HLA-DRB1*04:01WDR62
63450 teLKKLEskinkvfstpipf HLA-DRB1*07:01TSC1
64514 tiyndtEGFNIESKDLksey HLA-Class II, allele undeterminedCSMD3 GPR98
65324 TNGKLniyyrrlynglkfii HLA-Class II, allele undeterminedWDR62
67104 tvntqfqKRSYQmyrsletqvda B-cell WDR62
68104 vdynlqskiTLPNDrttpvt HLA-DQB1*06:02GPR98
69149 VIVHKamdieyNDMFNnftvHLA-Class II, allele undeterminedCLN5 SCN9A
69180 vKAKWLgtvntqfqKRSYQm HLA-DQB1*06:02LGI2 WDR62
70202 vntqfqKRSYQmyrsleyqv HLA-DRB1*07:01WDR62
70165 vnqGAQGIlflqwvrdiiddHLA-Class II, allele undeterminedMK10
70166 vnqGAQGIlflqwvrdiiddftnB-cell MK10
70514 vpyigPALNIvk HLA-Class II, allele undeterminedNMDE1
70982 vsidkfriFCKALnpkHLA-DRB1*11:01LRRC1 SCN8A KCMA1
71155 vstivpyigPALNI HLA-DR, HLA-DR1, HLA-A*02:01NMDE1
71156 vstivpyigPALNIvkQGYEGnf B-cell NMDE1 TSEAR
72784 wLRVPKVsashleqygtneysie B-cell SCN8A EFHC1
76411 yvsidkfriFCKALnPKEIEHLA-Class II, allele undeterminedLRRC1 KCMA15
76537 yylipvassskdVQLKNitd HLA-Class II, allele undeterminedGPR98
79808 eLIHVLhglygmq HLA-DRA*01:01, HLA-DRB1*01:01WDR62 KCMA1
79816 evyKLVKAKWLgt HLA-DRA*01:01, HLA-DRB1*01:01ARHGA LGI2
167585 glygmqvsshEIIPSkqeiy HLA-DRB1*12:01ACHA2 ACHA4
167613 kvnqGAQGIlflqwvrdiidHLA-DRB1*12:01MK10
167626 nLISIDikndlyektlndyk HLA-DRB1*12:01GPR98
167666 shEIIPSkqeiymqhtypis HLA-DRB1*12:01ACHA2 ACHA4

One hundred and sixteen linear TT-derived epitopes that had been found to be immunopositive in the human host were analyzed. Epitope number refers to IEDB ID. Further details and references are reported in the Immune Epitope Database (IEDB; http://www.immuneepitope.org/.
Aa sequences given in one-letter code.
Peptide fragments shared with epilepsy-associated proteins in capital.
Epilepsy-associated proteins reported as UniProt/Swiss-prot entries. For details and references, see http://www.uniprot.org/.
TT-derived epitope ID 76411 shares both pentapeptides FCKAL and PKEIE with human KCMA1 (or calcium-activated potassium channel subunit alpha-1).

In essence, Table 1 shows that all of the 58 pentapeptides common to the 42 epilepsy-associated proteins and TT (Box 2, peptide sequences in parentheses and in italic) are present in 116 TT-derived epitopes that had been established to be immunopositive in humans. This datum indicates a potential vulnerability of the 42 epilepsy-associated proteins to cross-reactions following anti-TT immune responses. Moreover, many TT-derived epitopes share fragments with distinct epilepsy-related proteins and are of particular significance to a multiple cross-reactivity risk, since, for example, an immune response targeting the TT epitope fnnftVSFWLRVPKVsahle (see Table 1, IEDB ID 17207, with shared fragments in capital letter) has the potential to cross-react with the following three crucial proteins related to different forms of epilepsy:(i)GBRA1 or gamma-aminobutyric acid receptor subunit alpha-1, the major inhibitory neurotransmitter in the vertebrate brain that mediates neuronal inhibition by binding to the GABA/benzodiazepine receptor and opening an integral chloride channel [72],(ii)SCN8A or voltage-gated sodium channel subunit alpha Nav1.6, a protein that mediates the voltage-dependent sodium ion permeability of excitable membranes [73],(iii)EFHC1 or myoclonin-1, a protein that may enhance calcium influx through CACNA1E and stimulate programmed cell death [74].

Such a multiple cross-reactivity potential is shown also by other TT-derived epitopes, eg, epitopes IEDB IDs 30436, 48049, 113407, and so forth.

Also, it seems important to highlight that MK10 (mitogen-activated protein kinase 10, also known as stress-activated protein kinase JNK3 or p493F12 kinase), a protein that shows the highest unexpected level of pentapeptide overlap to TT (Figure 1) and also has a high immunologic potential as illustrated in Table 1 (i.e., MK10 pentapeptide(s) are present in 7 TT-derived epitopes), is selectively expressed in a subpopulation of pyramidal neurons in the CA1, CA4, and subiculum regions of the hippocampus, and layers 3 and 5 of the neocortex [75]. That is, there is a potential cross-reactivity risk specifically allocated in brain areas directly linked to epileptogenesis [76, 77].

4. Conclusions

This study describes a vast pentapeptide commonality between TT-derived epitopes and epilepsy-associated proteins. This peptide sharing acquires a relevant pathologic potential in light of the fact that pentapeptide modules have the capacity of inducing immune response(s) and are main players in immune recognition [6171]. Immunologically, two sequences that share a pentapeptide are potentially subject to a cross-reaction [60].

In the disease model examined here, that is, tetanus infection and epilepsy, the ample cross-reactivity platform between TT-derived epitopes and human epilepsy-associated antigens supports the hypothesis of an immune involvement in epilepsy. As a matter of fact, all the 42 epilepsy-related proteins listed in Box 2 are potential targets of cross-reactions (see Table 1). Qualitatively, the peptide overlap occurs in human proteins canonically associated with epilepsy such as gamma-aminobutyric acid receptor subunit alpha-1 (GBRA1), gamma-aminobutyric acid type B receptor subunit 1 (GABR1), sodium channel protein subunits (SCN1A, SCN2A. SCN8A, and SCN9A), and calcium-activated potassium channel subunit alpha-1 (KCMA1) (Table 1). Obviously, an immune attack against such epilepsy-associated proteins may cause alterations to neural structures and functions, especially when the neurodevelopmental intrauterine phase is considered. Being of nonsecondary importance, the nonstochastic character of the peptide overlap between TT and epilepsy-associated proteins (Figure 1) indicates that the potential cross-reactivity extent (and the associated risk of developing epilepsy and neurodevelopmental disorders) will increase with the number of anti-TT immune stimulations.

An additional relevant point is the “antigenic patchwork” shown in Table 1. Indeed, the potential peptide crossreactome involved in different extent and in different combinations of 42 epilepsy-associated proteins might help understand the complex neurobiological network that, once hit and perturbed, may underlie different epileptic forms [19]. Also, it has to be noted that Table 1 includes proteins such as CNTP2 or contactin-associated protein-like 2, RELN or reelin, and TSC1 or tuberous sclerosis 1 protein, which are also landmark antigens for autism and the associated impairment in communication/language skills and behaviors [7881]. Hence, Table 1 may provide a mechanistic framework to allocate the occurrence of epilepsy, intellectual disability, and autism spectrum disorder in patients with tuberous sclerosis complex. Likewise, data from Table 1 might contribute to answering a critical question in neuropsychopathology, that is, the coexistence of patients with combined schizophrenia and epilepsy [8285]. Indeed, Table 1 substantiates the hypothesis according to which the thread joining epilepsy and schizophrenia may reside in neurodevelopmental molecules such as leucine-rich glioma inactivated (LGI) proteins and GPR98, a G protein-coupled receptor, originally known as VLGR1 or very large G protein-coupled receptor [86]. De facto, Table 1 shows that fragments from LGI1, LGI2, and GPR98 are present in 1, 7, and 18 TT-derived epitopes, respectively. In other words, the potential cross-reactivity targeting LGI1, LGI2, and GPR98 following an anti-TT response is high.

Given the caveat that peptide immunoreactivity is influenced by numerous factors, for example, binding affinity [87], cripticity (i.e., determinants embedded in membrane structures do not induce immune responses under physiological conditions) [88], and posttranslational modifications (i.e., citrullination) [89], the present data might contribute to further our understanding of epilepsies. In particular, data from Table 1 might represent a peptide platform to be tested in antibody binding assays using sera from epileptic subjects. Accompanied by parallel immunoassays based on the utilization of epilepsy-related proteins as antigens, such an approach might not only validate the TT-epilepsy link proposed in this study, but also lead to a definition at the molecular level of the repeatedly advanced association between antibodies and epilepsy [3341]. Moreover, of not less importance, immunoassay validation could also represent a prelude to specific therapies based on peptide modules able to block epileptogenic anti-TT autoantibodies [3841, 90]. Immunological research in this direction has been programmed in our lab.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.


Guglielmo Lucchese is supported by Deutscher Akademischer Austauschdienst (DAAD).


  1. C. D. Ferrie, “Idiopathic generalized epilepsies imitating focal epilepsies,” Epilepsia, vol. 46, no. 9, pp. 91–95, 2005. View at: Publisher Site | Google Scholar
  2. E. C. Wirrell, B. R. Grossardt, E. L. So, and K. C. Nickels, “A population-based study of long-term outcomes of cryptogenic focal epilepsy in childhood: cryptogenic epilepsy is NOT probably symptomatic epilepsy,” Epilepsia, vol. 52, no. 4, pp. 738–745, 2011. View at: Google Scholar
  3. A. T. Berg, “Epilepsy, cognition, and behavior: the clinical picture,” Epilepsia, vol. 52, supplement 1, pp. 7–12, 2011. View at: Publisher Site | Google Scholar
  4. U. Stephani, “The natural history of myoclonic astatic epilepsy (Doose syndrome) and Lennox-Gastaut syndrome,” Epilepsia, vol. 47, supplement 2, pp. 53–55, 2006. View at: Publisher Site | Google Scholar
  5. C. J. Chu-Shore, P. Major, S. Camposano, D. Muzykewicz, and E. A. Thiele, “The natural history of epilepsy in tuberous sclerosis complex,” Epilepsia, vol. 51, no. 7, pp. 1236–1241, 2010. View at: Publisher Site | Google Scholar
  6. N. Gaspard and L. J. Hirsch, “Pitfalls in ictal EEG interpretation: critical care and intracranial recordings,” Neurology, vol. 80, supplement 1, pp. S26–S42, 2013. View at: Google Scholar
  7. A. T. Berg, S. F. Berkovic, M. J. Brodie et al., “Revised terminology and concepts for organization of seizures and epilepsies: report of the ILAE Commission on Classification and Terminology, 2005–2009,” Epilepsia, vol. 51, no. 4, pp. 676–685, 2010. View at: Publisher Site | Google Scholar
  8. C. P. Panayiotopoulos, “The new ILAE report on terminology and concepts for the organization of epilepsies: critical review and contribution,” Epilepsia, vol. 53, no. 3, pp. 399–404, 2012. View at: Publisher Site | Google Scholar
  9. G. Avanzini, “A sound conceptual framework for an epilepsy classification is still lacking,” Epilepsia, vol. 51, no. 4, pp. 720–722, 2010. View at: Publisher Site | Google Scholar
  10. R. Ottman, J. F. Annegers, N. Risch, W. A. Hauser, and M. Susser, “Relations of genetic and environmental factors in the etiology of epilepsy,” Annals of Neurology, vol. 39, no. 4, pp. 442–449, 1996. View at: Publisher Site | Google Scholar
  11. X. Wang and Y. Lu, “Genetic etiology of new forms of familial epilepsy,” Frontiers in Bioscience, vol. 13, no. 8, pp. 3159–3167, 2008. View at: Publisher Site | Google Scholar
  12. M. J. Martínez, M. A. López-Aríztegui, N. Puente, I. Rubio, and M. I. Tejada, “CDKL5 gene status in female patients with epilepsy and Rett-like features: two new mutations in the catalytic domain,” BMC Medical Genetics, vol. 13, article 68, 2012. View at: Google Scholar
  13. A. Vezzani, J. French, T. Bartfai, and T. Z. Baram, “The role of inflammation in epilepsy,” Nature Reviews Neurology, vol. 7, no. 1, pp. 31–40, 2011. View at: Publisher Site | Google Scholar
  14. Y. Takahashi, K. Matsuda, Y. Kubota et al., “Vaccination and infection as causative factors in Japanese patients with Rasmussen syndrome: molecular mimicry and HLA class I,” Clinical and Developmental Immunology, vol. 13, no. 2–4, pp. 381–387, 2006. View at: Publisher Site | Google Scholar
  15. W. H. Theodore, L. Epstein, W. D. Gaillard, S. Shinnar, M. S. Wainwright, and S. Jacobson, “Human herpes virus 6B: a possible role in epilepsy?” Epilepsia, vol. 49, no. 11, pp. 1828–1837, 2008. View at: Publisher Site | Google Scholar
  16. J. E. Libbey and R. S. Fujinami, “Neurotropic viral infections leading to epilepsy: focus on Theiler's murine encephalomyelitis virus,” Future Virology, vol. 6, no. 11, pp. 1339–1350, 2011. View at: Publisher Site | Google Scholar
  17. Y. Bozzi, S. Casarosa, and M. Caleo, “Epilepsy as a neurodevelopmental disorder,” Frontiers in Psychiatry, vol. 3, article 19, 2012. View at: Publisher Site | Google Scholar
  18. P. Sgadò, M. Dunleavy, S. Genovesi, G. Provenzano, and Y. Bozzi, “The role of GABAergic system in neurodevelopmental disorders: a focus on autism and epilepsy,” International Journal of Physiology, Pathophysiology and Pharmacology, vol. 3, no. 3, pp. 223–235, 2011. View at: Google Scholar
  19. R. Tuchman and M. Cuccaro, “Epilepsy and autism: neurodevelopmental perspective,” Current Neurology and Neuroscience Reports, vol. 11, no. 4, pp. 428–434, 2011. View at: Publisher Site | Google Scholar
  20. R. J. Hagerman, “Epilepsy drives autism in neurodevelopmental disorders,” Developmental Medicine and Child Neurology, vol. 55, no. 2, pp. 101–102, 2013. View at: Publisher Site | Google Scholar
  21. A. M. van Eeghen, M. B. Pulsifer, V. L. Merker et al., “Understanding relationships between autism, intelligence, and epilepsy: a cross-disorder approach,” Developmental Medicine and Child Neurology, vol. 55, no. 2, pp. 146–153, 2013. View at: Publisher Site | Google Scholar
  22. S. N. Rakhade and F. E. Jensen, “Epileptogenesis in the immature brain: emerging mechanisms,” Nature Reviews Neurology, vol. 5, no. 7, pp. 380–391, 2009. View at: Publisher Site | Google Scholar
  23. C. M. Dubé, A. L. Brewster, C. Richichi, Q. Zha, and T. Z. Baram, “Fever, febrile seizures and epilepsy,” Trends in Neurosciences, vol. 30, no. 10, pp. 490–496, 2007. View at: Publisher Site | Google Scholar
  24. J. Palace and B. Lang, “Epilepsy: an autoimmune disease?” Journal of Neurology Neurosurgery and Psychiatry, vol. 69, no. 6, pp. 711–714, 2000. View at: Publisher Site | Google Scholar
  25. S. Najjar, M. Bernbaum, G. Lai, and O. Devinsky, “Immunology and epilepsy,” Reviews in Neurological Diseases, vol. 5, no. 3, pp. 109–116, 2008. View at: Google Scholar
  26. E. Pineda, D. Shin, S. J. You, S. Auvin, R. Sankar, and A. Mazarati, “Maternal immune activation promotes hippocampal kindling epileptogenesis in mice,” Annals of Neurology, vol. 74, no. 1, pp. 11–19, 2013. View at: Publisher Site | Google Scholar
  27. R. Nabbout, “Autoimmune and inflammatory epilepsies,” Epilepsia, vol. 53, no. 4, pp. 58–62, 2012. View at: Publisher Site | Google Scholar
  28. A. Vincent and P. B. Crino, “Systemic and neurologic autoimmune disorders associated with seizures or epilepsy,” Epilepsia, vol. 52, supplement 3, pp. 12–17, 2011. View at: Publisher Site | Google Scholar
  29. T. Granata, H. Cross, W. Theodore, and G. Avanzini, “Immune-mediated epilepsies,” Epilepsia, vol. 52, supplement 3, pp. 5–11, 2011. View at: Publisher Site | Google Scholar
  30. A. Vezzani and S. Rüegg, “The pivotal role of immunity and inflammatory processes in epilepsy is increasingly recognized: introduction,” Epilepsia, vol. 52, supplement 3, pp. 1–4, 2011. View at: Google Scholar
  31. N. Specchio, L. Fusco, D. Claps, and F. Vigevano, “Epileptic encephalopathy in children possibly related to immune-mediated pathogenesis,” Brain & Development, vol. 32, no. 1, pp. 51–56, 2010. View at: Publisher Site | Google Scholar
  32. K. M. Rodgers, M. R. Hutchinson, A. Northcutt, S. F. Maier, L. R. Watkins, and D. S. Barth, “The cortical innate immune response increases local neuronal excitability leading to seizures,” Brain, vol. 132, no. 9, pp. 2478–2486, 2009. View at: Publisher Site | Google Scholar
  33. H. J. M. Majoie, M. de Baets, W. Renier, B. Lang, and A. Vincent, “Antibodies to voltage-gated potassium and calcium channels in epilepsy,” Epilepsy Research, vol. 71, no. 2-3, pp. 135–141, 2006. View at: Publisher Site | Google Scholar
  34. K. McKnight, Y. Jiang, Y. Hart et al., “Serum antibodies in epilepsy and seizure-associated disorders,” Neurology, vol. 65, no. 11, pp. 1730–1736, 2005. View at: Publisher Site | Google Scholar
  35. C. G. Bien and A. Vincent, “Immune-mediated pediatric epilepsies,” Handbook of Clinical Neurology, vol. 111, pp. 521–531, 2013. View at: Publisher Site | Google Scholar
  36. M. Falip, M. Carreño, J. Miró et al., “Prevalence and immunological spectrum of temporal lobe epilepsy with glutamic acid decarboxylase antibodies,” European Journal of Neurology, vol. 19, no. 6, pp. 827–833, 2012. View at: Publisher Site | Google Scholar
  37. A. Boronat, L. Sabater, A. Saiz, J. Dalmau, and F. Graus, “GABAB receptor antibodies in limbic encephalitis and anti-GAD-associated neurologic disorders,” Neurology, vol. 76, no. 9, pp. 795–800, 2011. View at: Publisher Site | Google Scholar
  38. V. Nociti, G. Frisullo, T. Tartaglione et al., “Refractory generalized seizures and cerebellar ataxia associated with anti-GAD antibodies responsive to immunosuppressive treatment,” European Journal of Neurology, vol. 17, no. 1, p. e5, 2010. View at: Publisher Site | Google Scholar
  39. C. I. Akman, M. C. Patterson, A. Rubinstein, and R. Herzog, “Limbic encephalitis associated with anti-GAD antibody and common variable immune deficiency,” Developmental Medicine and Child Neurology, vol. 51, no. 7, pp. 563–567, 2009. View at: Publisher Site | Google Scholar
  40. E. Krastinova, M. Vigneron, P. Le Bras, J. Gasnault, and C. Goujard, “Treatment of limbic encephalitis with anti-glioma-inactivated 1 (LGI1) antibodies,” Journal of Clinical Neuroscience, vol. 19, no. 11, pp. 1580–1582, 2012. View at: Publisher Site | Google Scholar
  41. A. M. L. Quek, J. W. Britton, A. McKeon et al., “Autoimmune epilepsy: clinical characteristics and response to immunotherapy,” Archives of Neurology, vol. 69, no. 5, pp. 582–593, 2012. View at: Publisher Site | Google Scholar
  42. M. Nørgaard, V. Ehrenstein, R. B. Nielsen, L. S. Bakketeig, and H. T. Sørensen, “Maternal use of antibiotics, hospitalisation for infection during pregnancy, and risk of childhood epilepsy: a population-based cohort study,” PLoS ONE, vol. 7, no. 1, Article ID e30850, 2012. View at: Publisher Site | Google Scholar
  43. J. F. Bale Jr., “Fetal infections and brain development,” Clinics in Perinatology, vol. 36, no. 3, pp. 639–653, 2009. View at: Publisher Site | Google Scholar
  44. C. S. Wu, L. H. Pedersen, J. E. Miller et al., “Risk of cerebral palsy and childhood epilepsy related to infections before or during pregnancy,” PLoS ONE, vol. 8, no. 2, Article ID e57552, 2013. View at: Publisher Site | Google Scholar
  45. Y. Sun, M. Vestergaard, J. Christensen, A. J. Nahmias, and J. Olsen, “Prenatal exposure to maternal infections and epilepsy in childhood: a population-based cohort study,” Pediatrics, vol. 121, no. 5, pp. e1100–e1107, 2008. View at: Publisher Site | Google Scholar
  46. K. E. Nilsen, M. C. Walker, and H. R. Cock, “Characterization of the tetanus toxin model of refractory focal neocortical epilepsy in the rat,” Epilepsia, vol. 46, no. 2, pp. 179–187, 2005. View at: Publisher Site | Google Scholar
  47. M. Mainardi, M. Pietrasanta, E. Vannini, O. Rossetto, and M. Caleo, “Tetanus neurotoxin-induced epilepsy in mouse visual cortex,” Epilepsia, vol. 53, no. 7, pp. e132–e136, 2012. View at: Publisher Site | Google Scholar
  48. R. C. Wykes, J. H. Heeroma, L. Mantoan et al., “Optogenetic and potassium channel gene therapy in a rodent model of focal neocortical epilepsy,” Science Translational Medicine, vol. 4, no. 161, Article ID 161ra152, 2012. View at: Publisher Site | Google Scholar
  49. W. M. Otte, P. Bielefeld, R. M. Dijkhuizen, and K. P. J. Braun, “Focal neocortical epilepsy affects hippocampal volume, shape, and structural integrity: a longitudinal MRI and immunohistochemistry study in a rat model,” Epilepsia, vol. 53, no. 7, pp. 1264–1273, 2012. View at: Publisher Site | Google Scholar
  50. M. Sedigh-Sarvestani, G. I. Thuku, S. Sunderam et al., “Rapid eye movement sleep and hippocampal theta oscillations precede seizure onset in the tetanus toxin model of temporal lobe epilepsy,” The Journal of Neuroscience, vol. 34, no. 4, pp. 1105–1114, 2014. View at: Google Scholar
  51. D. Kanduc, A. Stufano, G. Lucchese, and A. Kusalik, “Massive peptide sharing between viral and human proteomes,” Peptides, vol. 29, no. 10, pp. 1755–1766, 2008. View at: Publisher Site | Google Scholar
  52. G. Lucchese, A. Stufano, M. Calabro, and D. Kanduc, “Charting the peptide crossreactome between HIV-1 and the human proteome,” Frontiers in Bioscience, vol. 3, no. 4, pp. 1385–1400, 2011. View at: Google Scholar
  53. B. Trost, G. Lucchese, A. Stufano, M. Bickis, A. Kusalik, and D. Kanduc, “No human protein is exempt from bacterial motifs, not even one,” Self/Nonself, vol. 1, no. 4, pp. 328–334, 2010. View at: Publisher Site | Google Scholar
  54. G. Lucchese, A. Stufano, and D. Kanduc, “Proposing low-similarity peptide vaccines against mycobacterium tuberculosis,” Journal of Biomedicine and Biotechnology, vol. 2010, Article ID 832341, 8 pages, 2010. View at: Publisher Site | Google Scholar
  55. S. L. Bavaro, M. Calabrò, and D. Kanduc, “Pentapeptide sharing between Corynebacterium diphtheria toxin and the human neural protein network,” Immunopharmacology and Immunotoxicology, vol. 33, no. 2, pp. 360–372, 2011. View at: Publisher Site | Google Scholar
  56. D. Kanduc, “Describing the hexapeptide identity platform between the influenza A H5N1 and Homo sapiens proteomes,” Biologics, vol. 4, pp. 245–261, 2010. View at: Google Scholar
  57. R. Ricco and D. Kanduc, “Hepatitis B virus and homo sapiens proteomewide analysis: a profusion of viral peptide overlaps in neuron-specific human proteins,” Biologics: Targets and Therapy, vol. 4, pp. 75–81, 2010. View at: Google Scholar
  58. G. Lucchese, G. Capone, and D. Kanduc, “Peptide sharing between Influenza A H1N1 hemagglutinin and human axon guidance proteins,” Schizophrenia Bulletin, vol. 40, no. 2, pp. 362–375, 2014. View at: Google Scholar
  59. A. Hoshino, M. Saitoh, A. Oka et al., “Epidemiology of acute encephalopathy in Japan, with emphasis on the association of viruses and syndromes,” Brain & Development, vol. 34, no. 5, pp. 337–343, 2012. View at: Publisher Site | Google Scholar
  60. D. Kanduc, “Homology, similarity, and identity in peptide epitope immunodefinition,” Journal of Peptide Science, vol. 18, no. 8, pp. 487–494, 2012. View at: Publisher Site | Google Scholar
  61. D. Kanduc, “Pentapeptides as minimal functional units in cell biology and immunology,” Current Protein & Peptide Science, vol. 14, no. 2, pp. 111–120, 2013. View at: Publisher Site | Google Scholar
  62. D. B. Sant’Angelo, E. Robinson, C. A. Janeway Jr., and L. K. Denzin, “Recognition of core and flanking amino acids of MHC classII-bound peptides by the T cell receptor,” European Journal of Immunology, vol. 32, no. 9, pp. 2510–2520, 2002. View at: Google Scholar
  63. J. B. Rothbard and M. L. Gefter, “Interactions between immunogenic peptides and MHC proteins,” Annual Review of Immunology, vol. 9, pp. 527–565, 1991. View at: Google Scholar
  64. J. B. Rothbard, R. M. Pemberton, H. C. Bodmer, B. A. Askonas, and W. R. Taylor, “Identification of residues necessary for clonally specific recognition of a cytotoxic T cell determinant,” The EMBO Journal, vol. 8, no. 8, pp. 2321–2328, 1989. View at: Google Scholar
  65. M. J. Reddehase, J. B. Rothbard, and U. H. Koszinowski, “A pentapeptide as minimal antigenic determinant for MHC class I-restricted T lymphocytes,” Nature, vol. 337, no. 6208, pp. 651–653, 1989. View at: Google Scholar
  66. B. Hemmer, T. Kondo, B. Gran et al., “Minimal peptide length requirements for CD4+ T cell clones—implications for molecular mimicry and T cell survival,” International Immunology, vol. 12, no. 3, pp. 375–383, 2000. View at: Google Scholar
  67. K. Landsteiner and J. van der Scheer, “On the serological specificity of peptides. III,” The Journal of Experimental Medicine, vol. 69, no. 5, pp. 705–719, 1939. View at: Google Scholar
  68. R. Tiwari, J. Geliebter, A. Lucchese, A. Mittelman, and D. Kanduc, “Computational peptide dissection of Melan-a/MART-1 oncoprotein antigenicity,” Peptides, vol. 25, no. 11, pp. 1865–1871, 2004. View at: Publisher Site | Google Scholar
  69. S. Tanabe, “Epitope peptides and immunotherapy,” Current Protein & Peptide Science, vol. 8, no. 1, pp. 109–118, 2007. View at: Publisher Site | Google Scholar
  70. W. Zeng, J. Pagnon, and D. C. Jackson, “The C-terminal pentapeptide of LHRH is a dominant B cell epitope with antigenic and biological function,” Molecular Immunology, vol. 44, no. 15, pp. 3724–3731, 2007. View at: Publisher Site | Google Scholar
  71. G. Lucchese, A. Stufano, B. Trost, A. Kusalik, and D. Kanduc, “Peptidology: short amino acid modules in cell biology and immunology,” Amino Acids, vol. 33, no. 4, pp. 703–707, 2007. View at: Publisher Site | Google Scholar
  72. P. Cossette, L. Liu, K. Brisebois et al., “Mutation of GABRA1 in an autosomal dominant form of juvenile myoclonic epilepsy,” Nature Genetics, vol. 31, no. 2, pp. 184–189, 2002. View at: Publisher Site | Google Scholar
  73. K. R. Veeramah, J. E. O'Brien, M. H. Meisler et al., “De novo pathogenic SCN8A mutation identified by whole-genome sequencing of a family quartet affected by infantile epileptic encephalopathy and SUDEP,” American Journal of Human Genetics, vol. 90, no. 3, pp. 502–510, 2012. View at: Publisher Site | Google Scholar
  74. T. Suzuki, A. V. Delgado-Escueta, K. Aguan et al., “Mutations in EFHC1 cause juvenile myoclonic epilepsy,” Nature Genetics, vol. 36, no. 8, pp. 842–849, 2004. View at: Publisher Site | Google Scholar
  75. A. A. Mohit, J. H. Martin, and C. A. Miller, “p493F12 kinase: a novel MAP kinase expressed in a subset of neurons in the human nervous system,” Neuron, vol. 14, no. 1, pp. 67–78, 1995. View at: Google Scholar
  76. C. E. Stafstrom, “The role of the subiculum in epilepsy and epileptogenesis,” Epilepsy Currents, vol. 5, no. 4, pp. 121–129, 2005. View at: Google Scholar
  77. K. Sendrowski and W. Sobaniec, “Hippocampus, hippocampal sclerosis and epilepsy,” Pharmacological Reports, vol. 65, no. 3, pp. 555–565, 2013. View at: Google Scholar
  78. C. Toma, A. Hervás, B. Torrico et al., “Analysis of two language-related genes in Autism: a case-control association study of FOXP2 and CNTNAP2,” Psychiatric Genetics, vol. 23, no. 2, pp. 82–85, 2013. View at: Publisher Site | Google Scholar
  79. T. D. Folsom and S. H. Fatemi, “The involvement of Reelin in neurodevelopmental disorders,” Neuropharmacology, vol. 68, pp. 122–135, 2013. View at: Publisher Site | Google Scholar
  80. E. Romano, C. Michetti, A. Caruso, G. Laviola, and M. L. Scattoni, “Characterization of neonatal vocal and motor repertoire of reelin mutant mice,” PLoS ONE, vol. 8, no. 5, Article ID e64407, 2013. View at: Publisher Site | Google Scholar
  81. S. Jeste, M. Sahin, P. Bolton, G. Ploubidis, and A. Humphrey, “Characterization of autism in young children with tuberous sclerosis complex,” Journal of Child Neurology, vol. 23, no. 5, pp. 520–525, 2008. View at: Publisher Site | Google Scholar
  82. D. C. Taylor, “Schizophrenias and epilepsies: why? When? How?” Epilepsy and Behavior, vol. 4, no. 5, pp. 474–482, 2003. View at: Publisher Site | Google Scholar
  83. P. Qin, H. Xu, T. M. Laursen, M. Vestergaard, and P. B. Mortensen, “Risk for schizophrenia and schizophrenia-like psychosis among patients with epilepsy: population based cohort study,” British Medical Journal, vol. 331, no. 7507, pp. 23–25, 2005. View at: Publisher Site | Google Scholar
  84. Y.-T. Chang, P.-C. Chen, I.-J. Tsai et al., “Bidirectional relation between schizophrenia and epilepsy: a population-based retrospective cohort study,” Epilepsia, vol. 52, no. 11, pp. 2036–2042, 2011. View at: Publisher Site | Google Scholar
  85. M. C. Clarke, A. Tanskanen, M. O. Huttunen, M. Clancy, D. R. Cotter, and M. Cannon, “Evidence for shared susceptibility to epilepsy and psychosis: a population-based family study,” Biological Psychiatry, vol. 71, no. 9, pp. 836–839, 2012. View at: Publisher Site | Google Scholar
  86. N. G. Cascella, D. J. Schretlen, and A. Sawa, “Schizophrenia and epilepsy: is there a shared susceptibility?” Neuroscience Research, vol. 63, no. 4, pp. 227–235, 2009. View at: Publisher Site | Google Scholar
  87. A. Sette, A. Vitiello, B. Reherman et al., “The relationship between class I binding affinity and immunogenicity of potential cytotoxic T cell epitopes,” Journal of Immunology, vol. 153, no. 12, pp. 5586–5592, 1994. View at: Google Scholar
  88. K. D. Moudgil and E. E. Sercarz, “Understanding crypticity is the key to revealing the pathogenesis of autoimmunity,” Trends in Immunology, vol. 26, no. 7, pp. 355–359, 2005. View at: Publisher Site | Google Scholar
  89. P. Eggleton, R. Haigh, and P. G. Winyard, “Consequence of neo-antigenicity of the ‘altered self’,” Rheumatology, vol. 47, no. 5, pp. 567–571, 2008. View at: Publisher Site | Google Scholar
  90. D. Kanduc, “Peptide cross-reactivity: the original sin of vaccines,” Frontiers in Bioscience, vol. 4, pp. 1393–1401, 2012. View at: Google Scholar

Copyright © 2014 Guglielmo Lucchese et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.