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
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