Journal of Current Biomedical Reports jcbior.com Volume 1, Number 1, 2020 1 Original research Immunogenicity, antigenicity and epitope mapping of Salmonella InvH protein: An in silico study Behzad Dehghani1,*, Tayebeh Hashempour1, Zahra Hasanshahia, Iraj Rasooli2,3 1 Shiraz HIV/AIDS Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran 2 Department of Biology, Shahed University, Tehran, Iran 3Molecular Microbiology Research Center, Shahed University, Tehran, Iran Abstract InvH is an indispensable part of T3SS-I and has a significant role in SPI-I mediated effector protein translocation. The InvH mutations have significant effects including reduced secretory and inflamma- tory responses that result from preventing the normal secretion of several proteins. Our team previous studies showed the capable ability of InvH to induce the humoral immune system to prevent almost all Salmonella strains infections. The current study aimed to determine all aspects of this protein using several bioinformatics tools and find the differences among all Salmonella strains. This data could pave the way for further studies about InvH protein and the production of an effective vaccine against Sal- monella infections. InvH sequences for all Salmonella strains were obtained from GenBank and ana- lyzed to determine physicochemical properties, B-Cell and T-Cell epitopes, and reliable structures. Re- sults showed some minimal differences among Salmonella strains. B-Cell and T-Cell epitopes predicted by numerous software approved the ability of this protein to induce both humoral and cellular immune systems remarkably. This study provided a comprehensive data to determine all features of InvH pro- tein and our results showed the ability of this protein to design a capable vaccine and the effect of amino acid changes on structure and physicochemical properties, and epitopes. Keywords: InvH, Salmonella, Bioinformatics, SPI-I, Vaccine 1. Introduction Each year 1.3 million cases of salmonellosis occur globally. Salmonella enterica (S. enterica) includes many foodborne pathogens causing sal- monellosis in developing or developed countries. Patterns of salmonellosis in humans include en- teric fever, gastroenteritis, bacteremia, and chronic carries. Typhoid fever is caused by Sal- monella enterica serovar Typhi (S. Typhi), and * Corresponding author: Behzad Dehghani, MSc 2nd floor, Voluntary Counseling and Testing Center, Lavan Ave, Delavaran-e Basij Blvd, Khatoun Sq, Shiraz, Fars, Iran Tel/Fax: +98 71 37386272 Email: deghanibehzad@gmail.com https://orcid.org/0000-0002-4895-9419 Received: May, 31, 2020 Accepted: June, 10, 2020 paratyphoid fever is caused by Salmonella para- typhi (S. paratyphi) A, B, and C. Infection is spread by contaminated food or water. Salmo- nella Typhimurium (S. Typhimurium) and Sal- monella enterica serovar Enteritidis (S. Enter- itidis) cause gastroenteritis via contaminated food or water by animal waste. Bacteremia is a se- rious infection associated with invasive sero- https://jcbior.com/ https://orcid.org/0000-0002-4895-9419 Dehghani et al. 2 types, Salmonella cholearaesuis (S. cholearae- suis), and Salmonella Dublin (S. Dublin). Chronic carriers are major factors to spread Sal- monellosis in the word [1]. Many Gram-nega- tive bacteria have a type III secretion system. The type-III secretion system-I (T3SS-I) of S. enterica is necessary for invasion and translocation effec- tors proteins from bacteria into host cells. Two Salmonella pathogenicity islands of SPI1 and SPI2 encode structural components, effec- tors, and regulators of T3SS1 [2, 3]. InvH, a main part of T3SS-I, is necessary for the effective per- formance of Salmonella invasion of epithelial cells [4, 5]. Deletion of invH gene is related to re- duce the invasion efficiency of the bacterium compared to the wild-type [5]. Genetic analysis has shown the presentation of InvH in many Sal- monella strains [6]. Immunization with recombi- nant InvH against S. Enteritidis and S. Typhi in animal models has shown its potential as a vac- cine candidate [7, 8]. Many bioinformatics tools have been employed to analyze the properties and features of different bacterial and viral genes [9- 13]. This study aimed to compare experimental and bioinformatics data to find epitopes, modifi- cation sites, and structure analysis that can pro- vide much useful information on immunogenicity and antigenicity of InvH protein. 2. Material and Methods 2.1. invH sequence analysis For bioinformatics analysis, 6 sequences (full length: 444 bp, 148 amino acids) were obtained from GenBank (http://www.ncbi.nlm.nih.gov). The sequences included were accession number: CP009102.1 (S. Typhimurium), accession num- ber: AOYF01000046.1 (S. Paratyphi B), acces- sion number: AL513382.1 (S. Typhi), accession number: NC_006511.1 (S. Paratyphi A), acces- sion number: CP000857.1 (S. Paratyphi C), and accession number: AM933172.1 (S. Enteritidis). 2.2. Amino acid changing and Phylogenetic trees All sequences were translated, edited, and aligned using CLC sequence viewer version Beta (QIAGEN). Phylogenic trees were determined by neighbor-joining (NJ) methods 1000 times to confirm the reliability of phylogenetic trees. Sig- nal peptide and signal peptide cleavage sites for Gram-negative bacteria were determined using "SignalP 4.1” at (http://www.cbs.dtu.dk/ser- vices/SignalP/) [14], "Predisi" (http://www.pre- disi.de/predisi/startprediction) [15], and "Signal- BLAST” (http://sigpep.ser- vices.came.sbg.ac.at/signalblast.html) [16]. 2.3. InvH physicochemical properties "Expasy’s ProtParam" (http://expasy.org/ tools/protparam.html) was used to determine theoretical isoelectric point (pI), instability index, aliphatic index, and grand average hydropathy (GRAVY) [17-19]. 2.4. Immuno-informatic prediction "Immuneepitope" (http://tools.immuneep- itope.org/tools/bcell/iedb_input) was employed to determine B-Cell epitopes positions. Chou and Fasman method was used to predict Beta-Turns, Karplus and Schulz for predicting the flexibility; Emini method was used for surface accessibility prediction, and Parker method for hydrophilicity evaluation and Bepipred method to define B-cell epitopes using crystal structures. B-cell epitopes prediction was based on hydrophilic, flexibility, surface accessibility, B-turns, antigenic, exposed surface, and Polarity scale methods using BceP- red software at (http://www.imtech.res.in/raghava/bcepred) [20], and ABCpred software (http://www.imtech.res.in/raghava/abcpred/) [21]. T-cell epitope prediction was done by "SYFPEITHI" (http://www.syfpei- thi.de/bin/MHCServer.dll/EpitopePredic- tion.htm) [22], and "immuneepitope" (http://tools.immuneepitope.org/main/tcell/) [23]. Antigenicity probability was estimated (http://www.ddg-pharmfac.net/vaxijen/Vaxi- Jen/VaxiJen.html) using VaxiJen software [24]. Prediction of IgE epitopes was carried out by Al- gPred at (http://www.imtech.res.in/raghava/al- gpred/submission.html) [25]. 2.5. Disulfide bond prediction Disulfide bonds position was predicted using DiANNA [26] (http://cla- vius.bc.edu/~clotelab/DiANNA) and SCRATCH [27] (http://scratch.proteomics.ics.uci.edu/). 2.6. Secondary structure prediction Secondary structure was predicted and con- firmed by SOPMA (http://npsa-pbil.ibcp.fr/cgi- bin/npsa_automat.pl?page=npsa_sopma.html), http://www.cbs.dtu.dk/services/SignalP/ http://www.cbs.dtu.dk/services/SignalP/ http://tools.immuneepitope.org/main/tcell/ http://scratch.proteomics.ics.uci.edu/ http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html Dehghani et al. 3 Phyre server (http://www.sbg.bio.ic.ac.uk/phyre) [28]. 2.7. Prediction and validation of tertiary structure I-TASSER (http://zhanglab.ccmb.med.umich.edu/I- TASSER) [29-32], Phyre2server (http://www.sbg.bio.ic.ac.uk/~phyre) [28], and (PS)2 Server [33] (http://ps2v2.life.nctu.edu.tw) were employed to build 3D structures the stereo- chemistry and quality of the 3D structures mod- els were evaluated by Qmean [34, 35] (http://swissmodel.expasy.org/qmean/cgi/in- dex.cgi) and Ramachandran plots were mapped by Rampage (http://mor- dred.bioc.cam.ac.uk/~rapper/rampage.php). 3. Results 3.1. Sequences analysis and Phylogenetic trees The alignment of all sequences is shown in Figure 1. Phylogenetic tree for 6 sequences by NJ method: two main clades were shown in the tree, upper clade is divided into two clusters; in the first cluster Paratyphi A and Typhi (with 95 boot- strap score); in the second cluster Paratyphi C and Typhimurium are very close (with 83 boot- strap score). A clade contains Enteritidis and Paratyphi B (Figure 2). Signal peptide prediction of each software was similar for all sequences. 3.2. Amino acid changing A comparison of the sequences with S. Typhi revealed only 4 amino acid residue changes. Changes at positions 36 (K-Q) and 139 (A-S) in S. Paratyphi C, amino acid 67 (Q-H) in S. Typhi- murium, position 146 (A-S) in S. Enteritidis. 3.3. Protparam results Almost the results were similar for all se- quences except for pI of S. Paratyphi C (Table 1). 3.4. Immuno-informatics Immuneepitopes by Beta-Turn methods de- termined three positions of 65-72, 70-76 and 126- 132 as B-cell epitopes regions. Surface Accessi- bility method showed two regions (87-92 and 109-114) and flexibility method showed three re- gions of 124-131, 87-95 and 106-114, antigenicity method indicated region 6-16, hydrophilicity method revealed a region (107-114), Bepipred (threshold:1) method determined three regions. The regions were similar in all sequences. Seven parameters of hydrophilicity, flexibility, surface accessibility, beta turs, surface exposure and po- larity were almost similar according to BcePred results (Table 2). ABCpred results revealed a start position of 16 meric B-cell epitopes of 97, 46, 89, and 29 were similar for all sequences. Prediction of protective antigens by "VaxiJen" program was around 0.34 and was probable non-antigen for all sequences. Prediction by mapping of IgE epitopes using "Al- gPred" software revealed as non-allergen for all sequences. HLA-E and HLA B27-5 T-cell epitopes results are shown in Table 3. HLA-E epitopes in all sequences were similar and HLA-B27-5 epitope regions were similar in all sequences ex- cept for S. Paratyphi C in which region 27 in HLA-B*27:05 was absent. The 8-14 meric epitopes were similar in all sequences except for S. Paratyphi C in which region 27 in HLA- B*27:05 was absent. 3.5. Disulfide bond prediction Three disulfide positions (7, 48, and 85) were predicted by "DiANNA" and 4 positions (7, 16, 48, and 85) by "scratch". Positions 7, 16, 48, and 85 were conserved for disulfide bonds. 3.6. Secondary and tertiary structures predic- tion Percentages of secondary structures by "SOPMA" are given in Table 4. The results were almost similar in all sequences. The secondary structures are shown in Figure 3. We could not construct a valid structure for InvH protein using all programs. 4. Discussion Cloning and molecular characterization of InvH were performed in 1993 [6]. The role of this protein in adherence and invasion to epithelial cell culture was determined in previous studies [6]. InvH is necessary for intestinal secretory and inflammatory responses, bovine macrophages ly- sis, and secretion of Salmonella effecter proteins by type III secretion system (TTSS). InvH is an important part of the needle complex of TTSS and is required for efficient assembly of the organelle. InvH is present in all Salmonella strains ex- cept Salmonella Heidelberg (S. Heidelberg) and Salmonella enterica subspecies arizonae (S. arizonae). InvH is highly conserved in all strains. http://www.sbg.bio.ic.ac.uk/phyre http://zhanglab.ccmb.med.umich.edu/I-TASSER http://zhanglab.ccmb.med.umich.edu/I-TASSER http://www.sbg.bio.ic.ac.uk/~phyre2/html http://swissmodel.expasy.org/qmean/cgi/index.cgi http://swissmodel.expasy.org/qmean/cgi/index.cgi http://mordred.bioc.cam.ac.uk/~rapper/rampage.php http://mordred.bioc.cam.ac.uk/~rapper/rampage.php Dehghani et al. 4 Figure 1. The alignment of all used sequences Figure 2. Phylogenic tree for all sequences by Neigh- bor-Joining method with 100 bootstrap score Dehghani et al. 5 Table 4. Percentages of the secondary structures for all sequence Sequences Percentages of alpha helix, extended strand, beta turn, random coil Typhi- murium 50.34, 4.76, 2.72, 42.18 Paratyphi B 51.02, 4.76, 2.72, 41.50 Typhi 51.02, 4.76, 2.72, 41.50 Paratyphi A 51.02, 4.76, 2.72, 41.50 Paratyphi C 51.02, 4.76, 2.72, 41.50 Enteritidis 51.02, 4.76, 2.72, 41.50 Table 1. Physico-chemical properties of the selected sequences. Sequences Theoretical pI half- life (hours) Instability in- dex Instability clas- sifies Aliphatic in- dex Hydropathi- city Typhi- murium 7.65 >10 59.76 unstable 78.37 -0.490 Paratyphi B 7.63 >10 57.64 unstable 78.37 -0.493 Typhi 7.63 >10 57.64 unstable 78.37 -0.493 Paratyphi A 7.63 >10 57.64 unstable 78.37 -0.493 Paratyphi C 6.72 >10 60.26 unstable 77.69 -0.507 Enteritidis 7.63 >10 60.63 unstable 77.69 -0.510 Table 2. BcePred analysis of all sequences Se- quences Hydrophilic Flexibility Surface accessibility Β- turns Antigenic Exposed surface Polarity Typhi- murium 33-35, 68-75, 89-92, 109-112 22-23, 60-62, 70-72, 106-109, 125-127, 29-30, 33-39, 58-65, 68-69, 72-75, 87-94, 102-115, 127- 128 65-71 5-13, 21-28, 50-55, 121-125, 134-135 1-2, 87-92, 106-112 86-92, 107- 115, 140-144 Paratyphi B 33-35, 68-75, 89-92, 109-113 22-23, 60-62, 70-72, 106-109, 125-127, 29-30, 33-39, 58-65, 67-70, 72-75, 87-94, 102-115, 127- 128 66-71 5-13, 21-28, 50-55, 121-125, 134-135 1-2, 87-92, 106-112 86-92, 107- 115, 140-144 Typhi 33-35, 68-75, 89-92, 109-114 22-23, 60-62, 70-72, 106-109, 125-127, 29-30, 33-39, 58-65, 67-70, 72-75, 87-94, 102-115, 127- 129 66-71 5-13, 21-28, 50-55, 121-125, 134-135 1-2, 87-92, 106-112 86-92, 107- 115, 140-144 Paratyphi A 33-35, 68-75, 89-92, 109-115 22-23, 60-62, 70-72, 106-109, 125-127, 29-30, 33-39, 58-65, 67-70, 72-75, 87-94, 102-115, 127- 130 66-71 5-13, 21-28, 50-55, 121-125, 134-135 1-2, 87-92, 106-112 86-92, 107- 115, 140-144 Paratyphi C 33-35, 68-75, 89-92, 109-116 22-23, 60-62, 70-72, 106-109, 125-127, 29-30, 33-35, 58-65, 67-70, 72-75, 87-94, 102-115, 127- 131 66-71 5-13, 21-28, 50-55, 121-125, 134-136 1-2, 87-92, 106-112 86-92, 107- 115, 140-144 Enteritidis 33-35, 68-75, 89-92, 109-117 22-23, 60-62, 70-72, 106-109, 125-127, 29-30, 33-39, 58-65, 67-70, 72-75, 87-94, 102-115, 127- 130 66-71 5-13, 21-28, 50-55, 121-125, 134-135 1-2, 87-92, 106-112 86-92, 107- 115, 140-144 Table 3. HLA-E*01:01, HLA-B*27:05 T-cell epitope regions in selected Sequences HLA Start Length Sequences HLA-E*01:01 35 8 QKEQLANA HLA-E*01:01 66 8 HPQYMRSK HLA-E*01:01 102 9 PVFLLIGCA HLA-E*01:01 9 10 NANSIDECQS HLA-E*01:01 41 10 EKYKQTKEQA HLA-E*01:01 86 10 HPQYMRSKED HLA-E*01:01 102 11 HPQYMRSKEDE HLA-E*01:01 102 12 QPGAQKEQLANA HLA-E*01:01 31 12 HPQYMRSKEDEE HLA-E*01:01 102 13 NKSLSNQNADNSA HLA-E*01:01 61 13 HPQYMRSKEDEEQ HLA-E*01:01 66 14 DECQSLPYVPSDLA HLA-E*01:01 102 8 QKEQLANA HLA-E*01:01 46 8 HPQYMRSK HLA-E*01:01 55 9 PVFLLIGCA HLA-B*27:05 106 10 M R S K E D E E Q L HLA-B*27:05 2 10 K K F Y S C L P V F HLA-B*27:05 129 10 K N L S I Y Q T L L HLA-B*27:05 12 10 L L I G C A Q V P L HLA-B*27:05 27 10 K P V Q Q P G A Q K HLA-B*27:05 89 10 K Q T K E Q A L T F HLA-B*27:05 3 9 K F Y S C L P V F HLA-B*27:05 19 9 V P L P S S V S K HLA-B*27:05 121 9 K V L L E P G S K Dehghani et al. 6 Three residual changes were determined be- tween S. typhimurium and S. choleraesuis [6]. In this study, we found 4 residual changes and the phylogenic tree showed high similarity between 6 sequences because of the similarity in InvH se- quences. S. Typhimurium, S. Paratyphi A, S. Para- typhi B, S. Paratyphi C, S. Typhi, and S. Enter- itidis are important in foodborne diseases. In our previous studies, the presentation of InvH on bacterial surface and antibody interaction with this protein was validated. Theoretical pI for all sequences was 7.63 ex- cept for S. Paratyphi C, which was 6.72. This could be attributed to a change in acidic amino acid to a basic one (lysine to glutamine 36). Instability index provided estimated protein stability of 77.7 to 78.3 in a test tube that showed this protein is an unstable protein (Instability in- dex of <40 is regarded). The aliphatic index was 78 for all sequences which is a positive factor for the thermostability of globular proteins and depends on aliphatic side chains (alanine, valine, isoleucine, and leucine). The aliphatic index of a protein is defined as the relative volume occupied by aliphatic side chains (alanine, valine, isoleucine, and leucine) and it may be regarded as a positive factor for the increase of the thermostability of globular pro- teins. The aliphatic index of a protein is calcu- lated according to the following formula: Ali- phatic index = X(Ala) + a * X(Val) + b * ( X(Ile) + X(Leu) ) where X(Ala), X(Val), X(Ile), and X(Leu) are mole percent (100 X mole fraction) of alanine, valine, isoleucine, and leucine. The coefficients a and b are the relative volume of valine side chain (a = 2.9) and of Leu/Ile side chains (b = 3.9) to the side chain of alanine. Hydropathicity index was around -0.6 for all sequences shows hydrophilicity of the protein. Hydrophilicity of protein parts is a positive patent for immune proteins because these parts are al- most exposed and have the potential of interac- tion with immunoglobulins. Signal peptide cleavage sites and signal pep- tide region prediction by three programs shows three (19, 26, and 15) different sites. "Predisi" re- sults were more reliable and similar to experi- mental results. The mutation in nucleotide 106 (A to C) brought about amino acid change (K-Q 36) in S. Paratyphi C, nucleotide 199 (G to T) brought about amino acid change (Q-H 67) in S. Typhi- murium. The mutation in nucleotide 415 (G to T) changed the amino acid 139 from A-S in S. Para- typhi C, and that in nucleotide 436 (G to T) changed the amino acid 67 (Q-H) in S. Enter- itidis. B-cell epitopes prediction by "Immuneep- itope" and six other methods showed some potent similar regions. A combination of the results of all methods showed four potent B-cell regions (65- Figure 3. Secondary struc- tures of all sequences pre- dicted and validated by "SOMPA". Blue: helix, Red: strand, Purple: coil and Green: beta turn. A: Typhimurium, B: Paratyphi B, C: Typhi, D: Paratyphi A, E: Paratyphi C, F: Enter- itidis Dehghani et al. 7 76, 87-95, 106-114, and 124-132). B-cell epitopes by BcePred showed similar regions in all se- quences. ABCpred regions (29-45, 46-62, 89-105, and 97-113) were similar in all sequences. Im- muneepitope, BcePred, and ABCpred showed the most potent B-cell epitope of 86-115 for InvH pro- tein. Region 86-115 contains the best potential in terms of hydrophilicity, flexibility, surface acces- sibility, surface exposed position, polarity, and linear B-cell epitopes prediction. This region con- tains almost alpha helix and random coil struc- tures. Immunization of mice by recombinant InvH showed a significant rise of IgG and humoral re- sponse and protective immunization against S. Typhi and S. Enteritidis [7, 8] confirming our im- mune-informatics analysis. "VaxiJen" showed InvH protein as probable non-antigen. AlgPred determined InvH as non-allergen. HLA-E binds nonamer peptides derived from bacterial proteins and triggers CD8-mediated ly- sis and IFN- production when exposed to infected targets, raising the possibility that this novel ef- fector mechanism might contribute to host de- fense against intracellular bacterial infections. Salmonella OMP peptides binding to HLA- B*27:05 were identified to modulate the host-mi- crobe interaction and HLA-B27 confers a very strong genetic predisposition to the development of reactive arthritis after infection by bacteria such as S. Typhimurium [36]. Our results showed 9 HLA-B*27:05 and 15 HLA-E T-cell epitopes regions. We, however, found two 9 meric T-cell epitopes (102-111 and 55-64) that indicated a good potential of InvH to stimulate cell-mediated immune system. Disulfide bonds are important in determining the functional linkages and stability of proteins. SS bonds were analyzed using two reliable pro- grams. Four cysteine amino acids making two di- sulfide bonds in InvH contributed to protein sta- bility. Amino acid 16, 48 were located on coil structure, 7 on strand structure, and 58 was on helix structure and any of them were not located on selected B-cell epitope region (86-115). Secondary structure in InvH protein con- tained almost alpha helix and random coil. Re- sults of all the sequences were similar except for S. Typhimurium in which region 60-80 helix was changed to random coil because of the change in amino acid (Q-H 67). We, however, could not achieve a proper 3D model for InvH, in spite of using three popular and reliable programs. The limited number of sequences and the number of bioinformatics software employed are the main limitation of the present study. In addi- tion, other Salmonella strains can be added for further studies. To sum up, it can be concluded that the find- ings of the present study provided valuable data about InvH protein which can be used to design a novel vaccine against all Salmonella strains as well as all physicochemical features of this pro- tein were defined which can be useful to express this protein in available hosts. Acknowledgements The authors wish to thank Farahnaz Dehghani for her kind support. Author Contributions Conception or design of the work: BD and IR; Data collection: ZH, TH; Data analysis and inter- pretation: BD, ZH; Drafting the article: BD, IR; Critical revision of the article: BD, TH, all authors read and approved the final version of manu- script. Conflict of Interests Authors declare there is no conflict of inter- est. Ethical declarations Not applicable Funding resource None References 1. Pui C, Wong W, Chai L, Tunung R, Jeyaletchumi P, Hidayah N, et al. Salmonella: A foodborne pathogen. Int. Food Res. J. 2011; 18(2):465-473. 2. Coburn B, Sekirov I, Finlay BB. 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