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\begin{document}

\title{Bioinformatics analysis and immunogenicity assessment of the novel
multi-stage DNA vaccine W541 against Mycobacterium tuberculosis}



\author[1]{Yourong Yang}%
\author[1]{Yan Liang}%
\author[1]{Yong Xue}%
\author[2]{Xiaoou Wang}%
\author[1]{Lan Wang}%
\author[3]{Jie Wang}%
\author[2]{Junxian Zhang}%
\author[1]{Xueqiong Wu}%
\affil[1]{Chinese PLA General Hospital}%
\affil[2]{The Eighth Medical Center of Chinese PLA General Hospital}%
\affil[3]{Tuberculosis Prevention and Control Key Laboratory, Beijing Key Laboratory of Ne beijing, Beijing, CN 100091}%


\vspace{-1em}



  
  \date{May 24, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Background: Vaccination is one of the effective measures to prevent
latent tuberculosis infection (LTBI) from developing into active
tuberculosis (TB). Applying bioinformatics methods to pre-evaluate the
biological characteristics and immunogenicity of vaccines can improve
the efficiency of vaccine development. Objectives: To evaluate the
immunogenicity of tuberculosis vaccine W541 and explore the application
of bioinformatics technology in tuberculosis vaccine research. Methods:
This study concatenated the immunodominant sequences of Ag85A, Ag85B,
Rv3407, and Rv1733c to construct the W541 DNA vaccine. Then,
bioinformatics methods were used to analyze the physicochemical
properties, antigenicity, allergenicity, toxicity, and population
coverage of the vaccine, identify its epitopes, and perform molecular
docking with MHC alleles and Toll-like receptor 4 (TLR4) of the host.
Finally, the immunogenicity of the vaccine was evaluated through animal
experiments. Results: the W541 vaccine protein is a soluble cytoplasmic
protein with a half-life of 1.1 hours in vivo and an instability index
of 45.37. It has good antigenicity and wide population coverage without
allergenicity and toxicity. It contains 138 HTL epitopes, 73 CTL
epitopes, 8 linear and 14 discontinuous epitopes of B cells, and a
strong affinity for TLR4. Immune simulations showed it could effectively
stimulate innate and adaptive immune responses. Animal experiments have
confirmed that the W541 DNA vaccine could effectively activate the Th1-
and Th17-type immune responses, producing high levels of IFN-\selectlanguage{greek}γ \selectlanguage{english}and
IL-17A, but could not significantly increase antibody levels.
Conclusion: the W541 DNA vaccine can induce strong cellular immune
responses. However, further optimization of the vaccine design is needed
to make the expressed protein more stable in vivo. Bioinformatics
analysis could reveal vaccines' physicochemical and immunological
information, which is critical for guiding vaccine design and
development.%
\end{abstract}%



\sloppy


Bioinformatics analysis and immunogenicity assessment of the novel
multi-stage DNA vaccine W541 against \emph{Mycobacterium tuberculosis}

Yourong Yang+,Yan~Liang+,Yong Xue, Xiaoou Wang, Lan Wang, Jie Wang,
Junxian Zhang, Yinping Liu,Xueqiong Wu*

Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and
Treatment, Institute of Tuberculosis Research, Senior Department of
Tuberculosis, the Eighth Medical Center of PLA General Hospital, Beijing
100091, China

+These authors contributed equally to this study.

*Corresponding author.E-mail:xueqiongwu@139.com.

\textbf{Running title} : Analysis and Verification of DNA vaccine

\textbf{Abstract}

\textbf{Background:}Vaccination is one of the effective measures to
prevent latent tuberculosis infection (LTBI) from developing into active
tuberculosis (TB). Applying bioinformatics methods to pre-evaluate the
biological characteristics and immunogenicity of vaccines can improve
the efficiency of vaccine development. \textbf{Objectives:} To evaluate
the immunogenicity of tuberculosis vaccine W541 and explore the
application of bioinformatics technology in tuberculosis vaccine
research.\textbf{Methods:} This study concatenated the immunodominant
sequences of Ag85A, Ag85B, \emph{Rv3407} , and \emph{Rv1733c} to
construct the W541 DNA vaccine. Then, bioinformatics methods were used
to analyze the physicochemical properties, antigenicity, allergenicity,
toxicity, and population coverage of the vaccine, identify its epitopes,
and perform molecular docking with MHC alleles and Toll-like receptor 4
(TLR4) of the host. Finally, the immunogenicity of the vaccine was
evaluated through animal experiments.\textbf{Results:}the W541 vaccine
protein is a soluble cytoplasmic protein with a half-life of 1.1 hours
in vivo and an instability index of 45.37. It has good antigenicity and
wide population coverage without allergenicity and toxicity. It contains
138 HTL epitopes, 73 CTL epitopes, 8 linear and 14 discontinuous
epitopes of B cells, and a strong affinity for TLR4. Immune simulations
showed it could effectively stimulate innate and adaptive immune
responses. Animal experiments have confirmed that the W541 DNA vaccine
could effectively activate the Th1- and Th17-type immune responses,
producing high levels of IFN-\selectlanguage{greek}γ \selectlanguage{english}and IL-17A, but could not significantly
increase antibody levels. \textbf{Conclusion:} the W541 DNA vaccine can
induce strong cellular immune responses. However, further optimization
of the vaccine design is needed to make the expressed protein more
stable in vivo. Bioinformatics analysis could reveal vaccines'
physicochemical and immunological information, which is critical for
guiding vaccine design and development.

\textbf{Keywords:} Tuberculosis; DNA vaccine; Bioinformatic analysis;
Simulated immunization; Immunogenicity

1. Introduction

Latent tuberculosis infection (LTBI) is characterized by the presence of
specific immune responses to \emph{Mycobacterium
tuberculosis}(\emph{M.tb} ) previously infected without clinical
evidence of active tuberculosis (TB)(1). Currently, about 23\% of the
world's population is in an LTBI state, in which 5-15\% of those with
LTBI may develop into active TB in their lifetime; LTBI has become an
essential source of active TB(2). According to the 2015 WHO Guidelines
for the Management of Latent Tuberculosis Infection, individuals with
LTBI can take anti-TB drugs to avoid developing active TB(2).
Considering that LTBI has no clinical symptoms, it appears that
vaccination-based preventive treatment is more acceptable than
chemotherapy. However, the Bacillus Calmette-Gu\selectlanguage{ngerman}érin (BCG) vaccine,
widely used for tuberculosis prevention, has a poor preventive effect on
LTBI(3). M72/AS01E, which was in phase IIb clinical trial and developed
by GlaxoSmithKline Plc., has only a 54.0\% protective efficacy against
LTBI developing into active pulmonary TB(4). The phase III clinical
trial of the \emph{M.vaccae} vaccine produced by Anhui ZhiFeiLongKeMa
Biopharmaceutical Co., Ltd showed a protective efficacy of 54.7\%
against LTBI(5). These data suggest that developing an effective LTBI
preventive and therapeutic vaccine has broad prospects.

According to research reports, the Ag85 complex is the main secretory
protein of\emph{M.tb} , consisting of three proteins: Ag85A, Ag85B, and
Ag85C. It accounts for 30\% of the total secreted protein In the
\emph{M.tb} \emph{H37Rv} strain and can be isolated from early cultures.
It has mycobacterial acid transferase activity, allowing trehalose to
transfer and deposit on the cell wall of\emph{M.tb} , playing an
essential role in the final stage of \emph{M.tb}cell wall synthesis(6,
7). Ag85A and Ag85B contain multiple human T-cell epitopes, and
CD4\textsuperscript{+} T cells from TB patients could respond to the
whole Ag85A or Ag85B polypeptides to produce interferon-gamma
(IFN-\selectlanguage{greek}γ\selectlanguage{english})(8). Our previous animal experimental studies(9-13)and the
clinical trials reported(8, 13-25) have shown that Ag85A and Ag85B had
high immunogenicity, could induce Th1-type responses and cytotoxic T
lymphocytes, reduce bacterial loads in lung and other tissues, alleviate
lung lesions, and had better protective or therapeutic effects on TB or
mouse model with latent tuberculosis infection (LTBI). At present, many
new TB vaccines internationally chose Ag85A and/or Ag85B protein as
vaccine antigens(15, 16), among which multiple vaccines have entered
clinical trials, such as AERAS-402 (including Ag85A, Ag85B, and
TB10.4)(17), MVA85A \textbackslash{} Ad5Ag85A \textbackslash{} ChAdOx1
85A (all including Ag85A)(8, 13-20), TB/FLU-04L (including Ag85A and
ESAT6)(21), GamTBvac (including Ag85A, ESAT6, and CFP10)(22), H1/IC31
(including Ag85B and ESAT6)(23), H4: IC31 (including Ag85B and TB10.4)
{[}{]}, H56: IC31 (including Ag85B, ESAT6, and \emph{Rv2660c} )(24),
AEC/BC02 (including Ag85B, ESAT6, and CFP10)(25).

\emph{Rv3407} is a protein consisting of 99 amino acids, specifically
expressed during the \emph{M.tb} transition from dormancy to
reactivation. It may be a kind of antitoxin, only slightly expressed
in\emph{M.tb} virulent strains and not expressed in BCG strains(26-28).
Schuck D et al. have revealed that the \emph{Rv3407} protein could
induce abundant IFN-\selectlanguage{greek}γ \selectlanguage{english}and robust Th1-type cell-mediated immune responses
in individuals with LTBI and was notably deficient in active TB
patients, indicating that the \emph{Rv3407}protein may confer
significant protection against dormant \emph{M.tb}infection in
susceptible populations(29). Reece et al. engineered the\emph{rv3407}
gene into the BCG vaccine and immunized mice with the recombinant BCG
vaccine, and found that this modified BCG vaccine stimulated high levels
of IFN-\selectlanguage{greek}γ \selectlanguage{english}production in mice and markedly enhanced protection against
TB(30).~Our research group also found through animal experiments that
the mice immunized with the \emph{rv3407} DNA vaccine could produce
higher levels of antigen-specific IFN-\selectlanguage{greek}γ \selectlanguage{english}in the culture supernatant of
splenic lymphocytes, had more Th1 cells and an increased Th1/Th2 cells
ratio in the whole blood, could reduce the bacterial load in the lungs
of mouse models with acute infection or LTBI, and alleviate the degree
of lung lesions(31, 32).

\emph{Rv1733c}is a major dormancy antigen highly expressed by
latent\emph{M.tb}and can be well recognized by T cells from individuals
with LTBI(33). Zhang W et al. immunized mice with a DNA vaccine encoding
\emph{Rv1733c}and exhibited higher splenocyte stimulation index and
IFN-\selectlanguage{greek}γ, \selectlanguage{english}IL-2, and IL-4 levels than those injected with saline(34). Our
research group used animal experiments to compare the preventive and
therapeutic effects of MTB ag85ab and 7 types of LTBI DNA vaccines on a
mouse LTBI model, and it showed that the ag85ab, \emph{rv2659c} ,
and\emph{rv1733c} DNA vaccines reduced the bacterial load and degree of
lung lesions in the mouse LTBI model(32). Additionally, Coppola M et al.
immunized mice with synthetic \emph{Rv1733c} long peptides (28 amino
acid sequences located at positions 57-84, IPFAAAAGTAVQDSRSHVYAHQAQTRHP)
and exhibited significantly increased expression of IFN-\selectlanguage{greek}γ, \selectlanguage{english}TNF-\selectlanguage{greek}α, \selectlanguage{english}and
specific antibody, and reduced the pulmonary\emph{M.tb} load. The
findings suggest that \emph{Rv1733c} has the potential for the
prevention or treatment of TB(33).

Based on this, we chose the full-length amino acid sequence of Ag85A and
308 amino acids of Ag85B as the vaccine backbone, added 51 amino acids
of\emph{Rv3407} protein (including 15 amino acids at positions 16-30 and
36 amino acids at positions 61-96) and 28 amino acids of
\emph{Rv1733c}protein (located at positions 57-84), and then
concatenated them to construct a new TB DNA vaccine, named W541 based on
the number of recombinant plasmids been constructed by our research
group over the years, aiming to elicit synergistic protective immunity
on TB and LTBI.

The development of bioinformatics and the application of big data
analytics have provided convenient conditions for the design and
development of vaccines, allowing researchers to have the opportunity to
understand vaccine-related information in advance, thereby gaining a
deeper understanding of vaccine characteristics and making corresponding
optimizations to improve the efficiency of vaccine development (35-38).
In this study, we used bioinformatics techniques to analyze various
physicochemical properties and immunological characteristics of the W541
DNA vaccine. Then, we verified the immunogenicity of the W541 vaccine
through animal experiments, exploring the feasibility of employing
bioinformatics analysis methods as a means of preliminary assessment
during tuberculosis vaccine development to aid vaccine research.

\textbf{Material and method}

The flow chart of the study design was shown in figure 1.

\textbf{2.1 Bioinformatics analysis}

\textbf{2.1.1Servers and Databases}

The bioinformatics analysis servers and databases used in this study are
shown in Table 1.

\textbf{2.1.2 The amino acid sequence of the W541 vaccine protein}

The W541 vaccine protein contains immunodominant sequences of four
antigens: ag85A, ag85B, \emph{Rv3407} , and \emph{Rv1733c} . The amino
acid sequence of the vaccine protein is shown in figure 2.

\textbf{2.1.3 The physicochemical and basic biological characteristics
of the W541vaccine protein}

The physicochemical properties of the vaccine proteins, including amino
acid composition, molecular weight, theoretical isoelectric point (pI),
instability index (II), aliphatic index (AI), and grand average of
hydropathicity (GRAVY), were predicted using the ProtParam server(39).
The SignaIP 4.1 server (40), MHMM 2.0 server, and Cell-PLoc 2.0
server(41) were used to predict the presence of signal peptide
sequences, transmembrane regions, and subcellular localization of the
vaccine proteins after expression within host cells, respectively. The
antigenicity, allergenicity, and toxicity of the vaccine proteins were
predicted using the VaxiJen server(42), AllerTop server(39), and
ToxinPred server(43), respectively. Human homology analysis on the
vaccine proteins was performed using the BLAST server(44).

\textbf{2.1.4 The spatial structure analyses of W541 vaccine protein and
molecular docking with Toll-like receptor (TLR)4~}

Using the SOPMA serve predicted the secondary structure of the W541
vaccine protein (45). Utilize the bKunyun supercomputing platform to
execute the AlphaFold2(46)to predict the tertiary structure of W541,
which was then authenticated using the Prosa server(47).

The GRAMM server can systematically assess a series of docking postures
between proteins and ligands and predict the most stable docking
conformation(48). Firstly, the PDB files of TLR4 were downloaded from
the PDB database(49) and uploaded to the GRAMM server along with the
W541 PDB files predicted by AlphaFold to predict the docking status
between the TLR4 and W541 vaccine. Finally, the PDBePISA server (50) was
used to calculate the detailed docking data of the docking complexes,
such as the interaction surface areas and binding energies.

\textbf{2.1.5} \textbf{Prediction of B-cell epitopes in the W541
vaccineprotein~}

The linear and discontinuous B-cell epitopes of W541 vaccine proteins
were predicted using the ElliPro server(51) with default parameters by
uploading the AlphaFold-predicted W541 PDB file.

\textbf{2.1.6} \textbf{Prediction of HTL and CTL epitopes in the W541
vaccine protein}

The helper T lymphocytes (HTL) epitopes were predicted by the MHC-II
Binding Predictions server(52) using the ``IEDB recommended method''
specified for the Full HLA reference set with default parameters, which
can predict all the 15 amino acid residues in the W541 vaccine protein.
Later the epitopes(excluding epitopes containing linker amino acids)
with IC50 values below 500 nM were further analyzed by the VaxiJen
server with a threshold of 0.4, the IFN epitope server(53), IL4pred
server (54), IL6pred server(55), and IL-10pred server (56) to predict
their antigenicity, the abilities to stimulate IFN-\selectlanguage{greek}γ, \selectlanguage{english}IL-4, IL-6, and
IL-10 secretion with default parameters.~

The cytotoxic T lymphocytes (CTL) epitopes were predicted by the MHC-I
Binding Predictions server(57) using the ``recommended epitope
predictor'' specified for the default HLA allele reference set, which
can predict all the 9 and 10 amino acid residues CTL epitopes of the
vaccine. Further, the epitopes (excluding epitopes containing linker
amino acids) with IC50 values below 500 nM were analyzed using the Class
I Immunogenicity server with default parameters to predict their
immunogenicity (58)and using the VaxiJen server to predict their
antigenicity with default parameters.

At last, all the HTL and CTL epitopes of the W541 vaccine protein were
submitted to AllerTOP v. 2.0 serve and ToxinPred serve to predict their
allergenicity and toxicity with default parameters.

\textbf{2.1.7} \textbf{Analysis of population coverage and molecular
docking of T-cell epitopes with MHC molecules for the W541 vaccine}

The population coverage of the vaccine was predicted by the IEDB
Population Coverage tool(59). The molecular docking between the vaccine
epitopes and MHC molecules was performed using the GRAMM docking server.
Firstly, the PDB files of the MHC molecules were downloaded from the
RCSB PDB database and processed with Pymol software 2.0 (an open-source
tool) to remove unnecessary ligands. Meanwhile, the structures of all
docking epitopes were predicted using the PEP-FOLD 3.5 server (60). The
PDB files of MHC molecules and corresponding epitope structures were
then submitted to the GRAMM docking server using the ''free docking''
mode. The docking results were analyzed using the PDBePISA server.

\textbf{2.1.8 Immune simulation in silico}

The immune responses to the W541 vaccine were simulated using the
C-ImmSim server(61). In this study, we performed three rounds of in
silico immunization with the W541 vaccine at 0, 14, and 28 days to
simulate the immune effects of the W541 vaccine.

\textbf{2.2 Experiment validation}

\textbf{2.2.1Preparation and characterization of W541 DNA vaccine and
its corresponding recombinant protein W540.}

According to the genetic code rules, the amino acid sequence of the W541
vaccine protein was translated into a DNA sequence. The DNA sequence was
then codon-optimized to generate sequences specifically suited for
eukaryotic and prokaryotic expression. The optimized eukaryotic
expression DNA sequence and the pVAX1 vector plasmid were digested with
restriction enzymes NheI and EcoRI, respectively. The two fragments were
ligated using DNA ligase to construct the recombinant plasmid. The
recombinant plasmid was then transformed into Escherichia coli (\emph{E.
coli} ) DH5\selectlanguage{greek}α \selectlanguage{english}competent cells. Subsequently, the transformed \emph{E.
coli} DH5\selectlanguage{greek}α \selectlanguage{english}cells were cultured in the LB medium. After culturing, the
W541 recombinant plasmid was isolated and purified using the plasmid
extraction kit (Qiagen, Germany). Similarly, the optimized prokaryotic
expression DNA sequence and the pET28a vector plasmid were digested with
restriction enzymes NheI and EcoRI, respectively. Then, the obtained
fragments were ligated using DNA ligase to construct the W540
recombinant protein plasmid and transformed into \emph{E. coli}BL21(DE3)
competent cells. The transformed E.coli BL21(DE3) cells were cultured on
LB medium and induced by 0.1 mM IPTG at 37 for 3 hours before purifying
the recombinant fusion protein(62). The W541 recombinant plasmid was
identified by sequencing and enzyme digestion. The W540 recombinant
plasmid was identified by sequencing, and the protein expression of
transformed \emph{E.coli} BL21(DE3)was identified by sodium dodecyl
sulfate-polyacrylamide gel~electrophoresis (SDS-PAGE) (63).

\textbf{2.2.2 Experimental animals}

Female BALB/c mice aged 56-62 days and weighing 18-20g were obtained
from Vital River Laboratory Animal Technology Co. Ltd (Beijing, China).
The animal experiments were conducted following the Regulations on
Management of Experimental Animals formulated by the Ministry of Science
and Technology of China. The Animal Ethics Committee of the Eighth
Medical Center of PLA General Hospital has approved the experimental
plan.

\textbf{2.2.3} \textbf{Immunization of the Animals}

Mice were divided into three groups (8 mice per group) and treated as
follows: 1) Control group: each mouse was injected intramuscularly with
100 \selectlanguage{greek}μ\selectlanguage{english}l of saline; 2) pVAX1 group: each mouse was injected
intramuscularly with 100 \selectlanguage{greek}μ\selectlanguage{english}g pVAX1 plasmid diluted in 100 \selectlanguage{greek}μ\selectlanguage{english}l saline; 3)
Vaccine group: each mouse was injected intramuscularly with 100 \selectlanguage{greek}μ\selectlanguage{english}g W541
DNA vaccine diluted in 100 \selectlanguage{greek}μ\selectlanguage{english}l saline (32). Mice received injections
every two weeks for a total of 3 injections. At five weeks after the
last immunization, the mice were euthanized. Blood samples were
collected in heparin lithium anticoagulant tubes, and then the plasma
was separated. The spleens of the mice were also harvested.

\textbf{2.2.4 Detection of specific antibodies against W540}

The blood sample of each mouse was separated from the plasma and stored
at -20. The enzyme-linked immunosorbent assay (ELISA) was employed to
individually detect specific antibodies IgG and its subtypes IgG1 and
IgG2a against W540 protein in the plasma samples obtained from all 24
mice in 3 groups. The method is briefly described as follows: The ELISA
plate (Costar, China) was coated with 100 \selectlanguage{greek}μ\selectlanguage{english}l of 10 \selectlanguage{greek}μ\selectlanguage{english}g/ml W540 protein in
the coating buffer (0.05M NaHCO\textsubscript{3}, pH 9.6) and incubated
overnight at 4. The plate was then washed with PBS-T
(1\selectlanguage{ngerman}×Phosphate-Buffered Saline, pH7.4, containing 0.05\% Tween-20) and
blocked with 200 \selectlanguage{greek}μ\selectlanguage{english}l/well of 2\% (w/v) ovalbumin (Coolaber, China) in PBS
buffer and incubated for 3 hours at 37. Plasma samples were diluted
1:100 in assay buffer (1\% w/v BSA in PBS-T) and added in duplicate at
100 \selectlanguage{greek}μ\selectlanguage{english}l/well, followed by incubation for 2 hours at 37. The coating
buffer without W540 protein was added to each plate as a negative
control. Goat anti-mouse IgG, IgG1, and IgG2a conjugated to horseradish
peroxidase (HRP) (Abcam, England) diluted 1:10,000 in assay buffer was
added at 100 \selectlanguage{greek}μ\selectlanguage{english}l/well and incubated for 1 hour at 37. After washing, 100
\selectlanguage{greek}μ\selectlanguage{english}l of 3,3',5,5'-Tetramethylbenzidine(TMB) substrate (BD, America) was
added to each well, and plates were incubated in the dark at room
temperature for 5 minutes. The enzymatic reaction was stopped by adding
50 \selectlanguage{greek}μ\selectlanguage{english}l of 1M H\textsubscript{2}SO\textsubscript{4}, and then the
absorbance at 450nm was measured using a microplate reader (Thermo,
America).

\selectlanguage{greek}\textbf{2.2.5 Detect the number of mouse splenocytes secreting IFN-γ by
enzyme-linked Immunospot assay (ELISPOT)}\selectlanguage{english}

Equal amounts of mice spleen cells from the same group were mixed to
reduce individual variations, and 3 independent experiments were
subsequently conducted with the Mouse IFN-\selectlanguage{greek}γ \selectlanguage{english}ELISpotPLUS (HRP) assay kit
(MABTECH AB, Sweden)to assess the immune response of mouse splenocytes
to the W540 protein. The detailed process follows:
3\selectlanguage{ngerman}×10\textsuperscript{5}mixed cells were seeded in each well of the
filter membrane plate pre-packaged with IFN-\selectlanguage{greek}γ \selectlanguage{english}capturing antibody
(MABTECH AB, Sweden). The negative control wells were added with RPMI
1640 complete medium, while the positive control wells were added
phytohemagglutinin (PHA) (Sigma, USA) at a final concentration of
20mg/ml. Following the kit's instructions, the number of splenocytes
secreting IFN-\selectlanguage{greek}γ \selectlanguage{english}was measured after stimulation with W540 protein at a
concentration of 30\selectlanguage{greek}µ\selectlanguage{english}g/ml in a CO\textsubscript{2} incubator at 37 for
20 hours. The number of spots in each well was detected using CTL
ImmunoSpot\selectlanguage{ngerman}®S5 Micro equipment (Cellular Technology, America).

\textbf{2.2.6 Cytokine analysis}

Spleen cell suspensions from each group of mice were mixed in equal
proportion to reduce individual variations, and then 3 repeated
experiments were conducted. The mixed spleen cell concentration was
adjusted to 3×10\textsuperscript{6} cells/ml. After stimulation with
W540 protein at a final concentration of 30\selectlanguage{greek}µ\selectlanguage{english}g/ml for 24h, the
supernatant from spleen cell cultures was subjected to analyze the
expression levels of cytokine IFN-\selectlanguage{greek}γ, \selectlanguage{english}IL-2, IL-4, IL-6, IL-10, and IL-17A
using the CBA assay kit (BD Biosciences, USA) following the instructions
provided. The measurements were performed in triplicate.

\textbf{2.2.7 Statistical analysis}

The antibody detection, ELISPOT assay, and cytokine detection data were
analyzed using GraphPad Prism 8 software. Quantitative data of normal
distribution were analyzed using one-way analysis of variance (ANOVA),
and pairwise comparisons were conducted using Tukey\textbf{'} s multiple
comparisons test. The results were presented as mean\selectlanguage{ngerman}±standard error, and
a p-value of less than 0.05 was considered a statistically significant
difference.

\textbf{3 Results}

\textbf{3.1 Bioinformatics analysis results}

\textbf{3.1.1 Physicochemical characteristics and basic biological
characteristics of W541vaccine protein}

The W541 vaccine protein sequence contains 704 amino acid residues with
a molecular weight of 74.6 kDa and a theoretical isoelectric point of
6.29. It exhibits an average hydrophobicity of -0.294, an aliphatic
index of 68.85, an instability index of 45.37, and possesses 57
phosphorylation sites and 7 glycosylation sites. The expressed vaccine
protein lacks signal peptide and transmembrane domains. Upon expression
in human cells, it localizes to lysosomes and the cytoplasm. It had a
half-life of 1.1 hours in mammalian reticulocytes, 3 minutes in yeast,
and 2 minutes in \emph{E. coli} . These data indicate that the W541
vaccine protein is a relatively large soluble protein prone to
degradation. The W541 vaccine protein also displays commendable
antigenicity, non-allergenicity, non-toxicity, and no homology with
human proteins (Table 2).

\textbf{3.1.2 The spatial structures of the W541 vaccine protein and
docking with TLR4}

According to the analysis conducted by the SOPMA server, the secondary
structure of the W541 protein exhibited a distribution of \selectlanguage{greek}α-\selectlanguage{english}helices,
\selectlanguage{greek}β-\selectlanguage{english}sheet, \selectlanguage{greek}β-\selectlanguage{english}turns, and random coils, accounting for 26.99\%, 19.03\%,
11.51\%, and 42.47\% of the total sequence, respectively. These four
secondary structures were arranged alternately throughout the overall
structure but had one distinct feature: the \selectlanguage{greek}α-\selectlanguage{english}helices primarily exist in
the central and posterior parts of the protein (figure 3A). Due to their
inherently flexible nature, the random coils and \selectlanguage{greek}β-\selectlanguage{english}turns tend to be
situated on the protein surface, showcasing a prominent structure. This
region is usually enriched with epitopes that are advantageous for
B-cell recognition.

For the W541 vaccine protein, AlphaFold2 predicted five possible
tertiary structures exhibiting high similarities. Both Ag85A and Ag85B
sequences were folded separately, while the three C-terminal epitopes
exist independently as \selectlanguage{greek}α-\selectlanguage{english}helices and random coils. The Prosa server
scored respectively the five predicted structures as -10.99, -10.96,
-10.65, -10.60, and -10.97, which fall within the expected range of the
server's protein model database. This result indicates a high
reliability of the predicted results (figure 3B).

The top-ranking W541 vaccine protein A structure was selected to study
the interaction with TLR4 to evaluate the immune system activation
effect of the vaccine. The central region of the W541 vaccine protein
showed a remarkable docking affinity with the B chain of TLR4, with a
binding energy of -10.7 kcal/mol and an interface area of 2209.7\selectlanguage{ngerman}Å²
(figure 3C). The lower the binding energy indicates the closer
vaccine-TLR binding, the more likely it is to activate TLR4 and induce
the production of cytokines and chemokines to enhance immune responses.

\textbf{3.1.3 B-cell epitopes of W541 vaccine protein}

B-cell epitopes can bind to B cell receptors (BCRs), activating
downstream signaling cascades that regulate B-cell activation and
antibody production. Activated B cells can also act as
antigen-presenting cells. The prediction results from the ElliPro server
showed that the W541 vaccine protein had 15 linear epitopes with
prediction scores ranging from 0.511 to 0.755 and 11 discontinuous
epitopes with predicted scores ranging from 0.543 to 0.987 (shown in
Supplementary Table 1).

\textbf{3.1.4 HTL and CTL epitopes of W541 vaccine protein}

Based on the selection criteria, the W541 vaccine protein contained a
total of 138 HTL epitopes (Supplementary Table 2) and 73 CTL epitopes
(Supplementary Table 3), in which 101, 63, 3, and 19 HTL epitopes could
induce IFN-\selectlanguage{greek}γ, \selectlanguage{english}IL-4, IL-6, and IL-10, respectively. The W541 protein
contained 10 HTL toxic epitopes and 6 CTL toxic epitopes. These toxic
epitopes were concentrated within two discreet regions of the amino acid
chain, totaling 21 residues (Supplementary Table 4).

\textbf{3.1.5 Population coverage analysis and molecular docking of T
lymphocyte epitopes with MHC for W541 vaccine protein}

The population coverage analyses on the HTL and CTL epitopes of the W541
vaccine protein and their corresponding MHCs were performed using the
Population Coverage server. The results revealed that the population
coverage rates of HTL and CTL epitopes were 99.68\% and 98.36\%,
respectively. 138 HTL epitopes that stimulate IFN-\selectlanguage{greek}γ \selectlanguage{english}secretion
(Supplementary Table 2) and 73 CTL epitopes (Supplementary Table 3)
could recognize 24 MHC class II molecules and 26 MHC class I molecules,
respectively. Some of these epitopes had a binding affinity for a single
MHC molecule, while others could bind to multiple MHC molecules. From
this epitope library, 18 HTL epitopes (antigenicity threshold
\textgreater{} 0.8, inducing only IFN, IC50 \textless{} 500) and
corresponding MHC molecules are displayed in Table 3A; 27 CTL epitopes
(antigenicity threshold \textgreater{} 0.8, class I immunogenicity
\textgreater{} 0.1, IC50 \textless{} 500) and corresponding MHC
molecules are shown in Table 3B. Molecular docking results of two
selected T-cell epitopes with their corresponding MHC molecules are
shown in figure 4.

\textbf{3.1.} \textbf{6 Immune simulation in silico}

\textbf{3.1.6.1 Activation of innate immune cells by}

\textbf{the W541 DNA vaccine}

Macrophages and dendritic cells are crucial to the body's innate immune
responses. The C-ImmSim server provides a simulation immune platform for
evaluating the immune response after vaccination. After the first
immunization, the number of activated macrophages significantly
increased. Each subsequent injection further enhanced macrophage
activation, and the macrophage count declined around day 50 until it
returned to pre-immunization levels on day 70 (figure 5A). Dendritic
cells were activated after the first immunization, and the number of
dendritic cells in the presenting state increased after each
immunization until it returned to pre-immunization levels on day 90
(figure 5B). The simulation results indicate a significant activation of
macrophages and dendritic cells after three immunizations of the W541
DNA vaccine.

\textbf{3.1.6.2 Activation of adaptive immune cells by theW541 DNA
vaccine}

The adaptive immune cells mainly include TH, TC, and B cells, which play
a crucial role in anti-TB immunity. After the initial vaccination, TH,
TC, and B cells were activated. With each subsequent immunization, their
activation was enhanced and reached their peaks on day 35, day 50, and
day 30, respectively. It is worth noting that the activation levels of
the TH and B cells decreased before the subsequent immunization, while
the TC cells remained in a sustained activated state (figure 5C-E).
Following the first vaccination, IFN-\selectlanguage{greek}γ \selectlanguage{english}levels rapidly increased. With
the second immunization, IFN-\selectlanguage{greek}γ \selectlanguage{english}levels were further elevated. After the
third immunization, the IFN-\selectlanguage{greek}γ \selectlanguage{english}levels remained relatively stable compared
to the second immunization and then rapidly declined, eventually
returning to pre-immunization levels around day 50 (figure 5F). A slight
increase in IgG and IgM was observed after the initial immunization.
After the second immunization, the expression of IgG and IgM increased
rapidly and further increased after the third immunization. IgM peaked
around day 40, followed by a decline, and dropped to the plateau phase
around day 90. IgG peaked around day 50, followed by a similar decline,
eventually entering a steady phase around day 150 (figure 5G).
Simulation results demonstrated that the W541 DNA vaccine could
effectively activate TH, TC, and B cells, leading to elevated levels of
corresponding cytokines such as IFN-\selectlanguage{greek}γ \selectlanguage{english}and antibodies IgG and IgM.

\textbf{3.2 Experimental validation results}

\textbf{3.2.1 Identification of W541 DNA vaccine and W540 recombinant
protein}

The sequencing findings indicate that the DNA sequences inserted in the
W541 vaccine and W540 plasmid are congruent with the design. Upon
induction with IPTG, the transformed \emph{E. coli} BL21(DE3) with W540
plasmid expressed protein with an approximate molecular weight of 70kDa
on SDS-PAGE (figure 6).

\textbf{3.2.2 Antibody production induced by W541 DNA vaccine}

After three immunizations, there was no significant difference in the
antibody IgG, IgG1, and IgG2a levels among the W541 vaccine group,
Control group, and pVAX1 group (P\textgreater{}0.05) (figure 7).

\selectlanguage{greek}\textbf{3.2.3Detect number of splenocytessecreting IFN-γ using ELISPOT
assay}\selectlanguage{english}

The ELISPOT assay results showed that the number of spots produced by
splenocytes secreting IFN-\selectlanguage{greek}γ \selectlanguage{english}in the vaccine group (26\selectlanguage{ngerman}±10) was
significantly higher than that in the normal control group (1.2±0.6,
P\textless{}0.01) and the pVAX1 vector control group (2±1,
P\textless{}0.01) (figure 8). These findings indicate that the W541 DNA
vaccine effectively activated the splenic lymphocytes in mice; upon
stimulation with the W540 protein, the activated splenocytes exhibited a
rapid and powerful secondary immune response.

\textbf{3.2.4 Analyses of Th1, Th2, and Th17 cytokines in splenocyte
culture supernatants of mice in each group}

For Th1-type and Th17-type cytokines, the IFN-\selectlanguage{greek}γ \selectlanguage{english}and IL17 levels were
significantly higher in the supernatants of splenocyte cultures from
mice immunized with the W541 DNA vaccine compared to the normal control
and pVAX1 vector groups (P\textless{}0.05, figure 9A\&F). However, there
were no significant differences in IL-2 levels among the vaccine and
control groups (P\textgreater{}0.05, figure 9B). For Th2-type cytokines,
comparing the W541 vaccine group to the normal control group revealed
that the W541 vaccine decreased expression of IL-4 and IL-6 by murine
splenocytes (P\textless{}0.05, figure 9C\&D). There were no significant
differences in IL-10 expression among the three
groups(P\textgreater{}0.05, figure 9E). These results demonstrate that
the W541 DNA vaccine effectively activated a Th1-type immune response in
the host.

\textbf{4. Discussion}

In recent years, the rapid development of bioinformatics methods and the
application of Internet databases have provided practical approaches for
selecting protein-dominant epitopes and the pre-evaluation of vaccines
(64-66), accelerating the vaccine research and development process. In
this study, we employed bioinformatic methods to analyze the
physicochemical properties, structure, safety, and immunological
functions of a multi-stage DNA vaccine W541 constructed by tandem
immunodominant sequences of ag85A, ag85B, \emph{Rv1733c} ,
and\emph{Rv3407} antigens. Furthermore, we evaluated its immunogenicity
through a murine model to verify the results of bioinformatics analysis
and lay a foundation for further optimization of the vaccine.

The bioinformatic analysis revealed that the W541 vaccine protein was a
soluble protein with a molecular weight of 74 kDa, which exhibited
excellent antigenicity and broad population coverage without
allergenicity or toxicity. These fundamental data strongly support the
suitability of W541 as a vaccine candidate based on the essential
criteria.

There is a close relationship between the secondary structure of a
protein and B-cell epitopes. The structures of irregular coiling and
\selectlanguage{greek}β-\selectlanguage{english}turns, being more loosely arranged, are prone to distortion and
spiralization, leading to their exposure to the protein surface. These
regions typically harbor a greater abundance of B-cell epitopes. The
predictive analysis revealed that within the W541 vaccine protein, the
sequence length of irregular coiling and \selectlanguage{greek}β-\selectlanguage{english}turns constitutes 53.98\% of
the total sequence length, most located on the surface of protein
molecules. Furthermore, the protein harbors 8 linear B-cell epitopes and
14 discontinuous epitopes. These structures and epitopes provide the
foundation for eliciting effective humoral immune responses in the host.
The immune stimulation in silico revealed that the W541 vaccine protein
could induce a heightened antibody response. However, in animal
experiments, most mice in the W541 DNA vaccine group did not exhibit a
significant increase in antibody levels. This phenomenon may be
attributed to the subcellular localization (in the cytoplasm and
lysosomes) and poor stability of the W541 protein, which consequently
affects the vaccine's efficacy in eliciting a robust humoral immune
response. The W541 vaccine protein expressed in the cytoplasm and
lysosomes lost the opportunity to bind to BCR. In addition, it had a
short half-life and poor stability, indicating that the vaccine protein
is prone to degradation, leading to loss of conformational epitopes,
which is detrimental to B cell activation and antibody production(65).
Emerging evidence suggests that B cells and humoral immunity can
regulate various immune responses of the intracellular pathogen \emph{M.
tuberculosis} (67). In addition, unstable proteins may undergo
degradation before being captured by macrophages and DC cells,
compromising their antigen presentation effectiveness. Ultimately, this
could also impact the activation of TH cells (66). Therefore, optimizing
the vaccine by increasing signal peptides to alter the subcellular
localization of vaccine proteins or optimizing sequences to enhance
their stability may help improve the immunogenicity of the vaccine
(68-70). Studies have shown that lysine residues exposed on protein
surfaces can bind to ubiquitin and promote protein degradation by
proteases~(71, 72). Additionally, the glycine, lysine, arginine, and
cysteine residues at the N-terminus and middle portion of proteins have
marked effects on protein stability~(73). In the future, we will focus
on fine-tuning the structure of the W541 vaccine to enhance the
immunogenicity of the vaccine protein.

TLRs play a crucial role in activating the anti-TB immune responses, and
TLR agonists are considered a promising class of vaccine adjuvants. TLR4
is an essential receptor involved in MTB recognition within cells,
expressed in both immune and non-immune cells, and its structure
includes the extracellular domain, transmembrane domain, and
intracellular domain(74). TLR4 forms homodimers to recognize
pathogen-associated molecular patterns such as lipopolysaccharides
(LPS), lipoteichoic acid (LTA), dsRNA, etc. After TLR4 activation, it
can initiate innate immune responses and regulate the migration,
maturation, and function of antigen-presenting cells while facilitating
adaptive immune responses(75, 76).\emph{M.tb}dormancy-related proteins
\emph{Rv2659c} and \emph{Rv1738} can mediate the production of
inflammatory cytokines through the TLR4 pathways(77). Furthermore, the
activated TLR4 can limit the survival of \emph{M.tb} by inducing
cellular autophagy(78). These studies demonstrate the beneficial
inclusion of TLR4 agonists in the design of TB vaccines. The relatively
stable binding between TLR and ligand is fundamental for TLR activation.
Molecular docking simulations in this study have demonstrated that the
expressed W541 protein in cells can establish stable interactions with
TLR4, thereby possessing the potential to activate TLRs. Simulation
immune results also proved that the W541 vaccine can effectively trigger
the body's innate immune responses.

The prominent immune characteristics of TB patients include impaired Th1
cell-mediated immune function or imbalanced Th1/Th2 cell immune
responses, which represent the primary risk factors of TB(79, 80).
Hence, effectively activating the host's Th1-type cell-mediated immune
response is essential for TB vaccines to exert their protective effects
against \emph{M.tb} (81). IFN-\selectlanguage{greek}γ \selectlanguage{english}plays a crucial role in the defense
against \emph{M.tb} infection by promoting the proliferation and
differentiation of Th0 cells into Th1 cells and activating
macrophages(82). The bioinformatics analysis of this study showed that
the W541 vaccine protein was an antigen with a majority of T-cell
epitopes, containing a total of 138 HTL epitopes, in which 101 HTL
epitopes could induce the production of IFN-\selectlanguage{greek}γ. \selectlanguage{english}In addition, it also
included a smaller number of HTL epitopes that could induce the
production of IL-4, IL-6, and IL-10. The simulated immunization with the
W541 vaccine demonstrated that the W541 DNA vaccine could effectively
activate TH cells and elicit a robust release of IFN-\selectlanguage{greek}γ \selectlanguage{english}and small amounts
of TGF-\selectlanguage{greek}β, \selectlanguage{english}IL-10, and IL-12 brief secretion. In contrast, the secretion
of other cytokines (including IL-4 and IL-6) was not observed. Animal
experiments have confirmed that mice in the vaccine group exhibited
significantly higher levels of IFN-\selectlanguage{greek}γ \selectlanguage{english}secretion in spleen cells compared
to the control group, and there was no significant increase in the
secretion levels of Th2-type cytokines (IL-4, IL-6, and IL-10). These
results collectively validate the consistency between most of the
immunoinformatics analysis results and animal experimentation results of
the vaccine, demonstrating a favorable structure-function
relationship.IL2 is also a representative multifunctional cytokine
mainly secreted by CD4\textsuperscript{+} T cells in the Th1-type
immunity, which can activate T cells and promote cytokine production,
activate macrophages, enhance the killing activity of NK cells, and
promote the production of immunoglobulins by B cells, playing an
essential role in the body's anti-TB immunity. In this study,
immunoinformatics prediction showed a significant increase in IL2, but
animal experiments exhibited that the W541 immunization could not
effectively induce the production of IL2. The possible reasons for this
are: (1) W541 immunization expressed high levels of antigens in mice,
mainly inducing effector memory T cells (TEM) and producing predominant
high IFN- \selectlanguage{greek}γ/ \selectlanguage{english}low IL-2 reaction. After weakened vaccine expression, it
may mainly induce central memory T cells (TCM), possibly with a
predominant low IFN- \selectlanguage{greek}γ/ \selectlanguage{english}high IL2 reaction. (2) It may also be because
mouse spleen cells were stimulated by the specific antigen W540 for a
shorter time (24 hours), which generally requires culture for 72 hours
to induce high levels of IL2 production(83). In addition, the experiment
results showed that the level of IL-17A in the vaccine group was
significantly higher compared to the control group. IL-17A was produced
by activated T cells and mediated the production of inflammatory
molecules, chemokines, antimicrobial peptides, and remodeling proteins
(84), playing an essential role in the immune response to \emph{M.tb}
(85). The W541 vaccine protein contains 138 CTL epitopes, which can
effectively activate cytotoxic T cells, confirmed in immune simulations.
Cytotoxic T cells are crucial in clearing\emph{M.tb}infection by
promoting target cell apoptosis or clearing infected target cells and
persisting bacteria through the perforin-granzyme pathway(86-89).
Numerous HTL and CTL epitopes within the W541 vaccine protein have been
experimentally validated. For instance, KLIANNTRV has been identified as
an HLA-A2-specific CD8\textsuperscript{+} immunodominant antigen
peptide~(90), PBMCs from TB patients exhibit a strongly proliferative
response to a peptide (DQSGLSVVMPVGGQSSFY) derived from Ag85(91).

5. Conclusions

In summary, although the results of bioinformatics analysis may not
encompass all biological effects elicited by vaccines in vivo, the
results of the existing analysis showed a strong positive correlation
with animal experiments. The research findings indicate that the W541
DNA vaccine composed of antigen Ag85A, Ag85B, \emph{Rv3407} ,
and\emph{Rv1733c} sequences contains a large number of HTL and CTL
epitopes, which can activate TH cells and TC cells, mainly inducing Th1
and Th17 immune responses of the body. However, the protein expressed by
the vaccine in vivo was not stable and could not effectively induce
humoral immune responses. Therefore, we will optimize the vaccine design
to address the issues with W541 and further evaluate the immunogenicity
and protective efficacy of the vaccine in a mouse LTBI model.

\textbf{Funding:} This study was supported by a grant from the National
Key R\&D Program of China (2022YFA1303500-003).

\textbf{Institutional Review Board Statement:} The animal study was
reviewed and approved by The Animal Ethical Committee of the Eighth
Medical Center of the Chinese PLA General Hospital (Approved Number:
309202108250973).

\textbf{Data Availability Statement:}The original contributions
presented in the study are included in the article and Supplementary
Material. Further inquiries can be directed to the corresponding author.

\textbf{Conflict of interest:} The authors declare that the research was
conducted without any commercial or financial relationships that could
be construed as a potential conflict of interest.

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Table 1. The servers and databases of bioinformatics analysis used in
this study\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
Servers/databases & Website\tabularnewline
\midrule
\endhead
ProtParam & https://web.expasy.org/protparam/\tabularnewline
VaxiJen &
http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html\tabularnewline
AllerTop & http://www.ddg-pharmfac.net/AllerTOP\tabularnewline
ToxinPred &
https://webs.iiitd.edu.in/raghava/toxinpred/multi\_submit.php\tabularnewline
Blastp &
https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE=Proteins\tabularnewline
SignaIP 4.1 &
https://services.healthtech.dtu.dk/service.php?SignalP-4.1\tabularnewline
TMHMM 2.0 &
https://services.healthtech.dtu.dk/service.php?TMHMM-2.0\tabularnewline
Cell-PLoc 2.0 &
http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc-2/\tabularnewline
NetPhos &
https://services.healthtech.dtu.dk/services/NetPhos-3.1\tabularnewline
NetNGlyc &
https://services.healthtech.dtu.dk/services/NetNGlyc-1.0\tabularnewline
YinOYang &
https://services.healthtech.dtu.dk/services/YinOYang-1.2\tabularnewline
SOPMA &
https://npsa-prabi.ibcp.fr/cgi-bin/npsa\_automat.pl?page=/NPSA/npsa\_sopma.html\tabularnewline
bkuyun & https://www.bkunyun.com\tabularnewline
Prosa & https://prosa.services.came.sbg.ac.at/prosa.php\tabularnewline
GRAMM & https://gramm.compbio.ku.edu/gramm\tabularnewline
PDB & https://www.rcsb.org/\tabularnewline
PDBePISA & https://www.ebi.ac.uk/pdbe/pisa/\tabularnewline
ElliPro & http://tools.iedb.org/ellipro/\tabularnewline
MHC-I Binding Predictions & http://tools.iedb.org/mhci/\tabularnewline
Class I Immunogenicity &
http://tools.iedb.org/immunogenicity/\tabularnewline
MHC-II Binding Predictions & http://tools.iedb.org/mhcii/\tabularnewline
CD4 T cell immunogenicity prediction &
http://tools.iedb.org/CD4episcore/\tabularnewline
IFNepitope &
http://crdd.osdd.net/raghava/ifnepitope/predict.php\tabularnewline
IL4pred &
https://webs.iiitd.edu.in/raghava/il4pred/predict.php\tabularnewline
IL6pred &
https://webs.iiitd.edu.in/raghava/il6pred/predict3.php\tabularnewline
IL-10pred &
https://webs.iiitd.edu.in/raghava/il10pred/predict3.php\tabularnewline
Population Coverage & http://tools.iedb.org/population/\tabularnewline
PEP-FOLD 3.5 server &
https://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py\#forms::PEP-FOLD3\tabularnewline
C-ImmSim & http://150.146.2.1/C-IMMSIM/index.php\tabularnewline
\bottomrule
\end{longtable}

Table 2. Physicochemical and biological properties of the protein
encoded by W541 DNA vaccine\selectlanguage{english}
\begin{longtable}[]{@{}ll@{}}
\toprule
\begin{minipage}[b]{0.47\columnwidth}\raggedright\strut
Properties\strut
\end{minipage} & \begin{minipage}[b]{0.47\columnwidth}\raggedright\strut
Results predicted\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Total number of amino acids\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
704\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Molecular weight\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
74644.63\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Formula\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
C3329H5035N923O993S24\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Theoretical pI\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
6.29\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Total number of negatively charged residues (Asp+Glu)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
52\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Total number of positively charged residues (Arg+Lys)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
48\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Total number of atoms\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
10304\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Number of phosphorylation sites\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
57\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Number of glycosylation sites\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
7\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
Estimated half-life\strut
\end{minipage} & \begin{minipage}[t]{0.48\columnwidth}\raggedright\strut
1.1 hours (mammalian reticulocytes, in vitro). 3 min (yeast, in vivo). 2
min (Escherichia coli, in vivo).\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Instability index (II)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
45.37(unstable)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Aliphatic index (AI)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
68.85\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Grand average of hydropathicity (GRAVY)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
-0.294\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Antigenicity\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
0.6527(ANTIGEN )\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Allergenicity\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Non-allergenicity\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Toxicity\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Non-toxin\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Signal peptide\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
No\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
TMHMM result\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Outside\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Subcellular localization (Cell-PLoc, Gram-positive bacterial)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Extracell\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Subcellular localization (Cell-PLoc, Hum-mPLoc)\strut
\end{minipage} & \begin{minipage}[t]{0.47\columnwidth}\raggedright\strut
Cytoplasm, lysosome\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\par\null

Table 3A. Docking results of selected HTL epitopes with corresponding
MHC alleles\selectlanguage{english}
\begin{longtable}[]{@{}llllllllll@{}}
\toprule
Antigens & Peptides & Alleles & Start & End &
Antigenicity\textgreater{}0.8 & IFN induce & IL4 induce & IL6 induce &
IL10 induce\tabularnewline
\midrule
\endhead
Ag85A & EYLQVPSPSMGRDIK &
HLA-DRB1*04:01,HLA-DRB1*04:01,HLA-DRB1*01:01,HLA-DRB1*01:01,HLA-DRB1*04:05,HLA-DRB1*04:05,HLA-DRB1*07:01,HLA-DRB1*07:01,HLA-DRB1*09:01,HLA-DRB1*09:01,HLA-DRB5*01:01,HLA-DRB5*01:01,HLA-DRB3*01:01,HLA-DRB3*01:01
& 9 & 23 & 0.9509 & + & - & - & -\tabularnewline
& YLQVPSPSMGRDIKV &
HLA-DRB1*04:01,HLA-DRB1*04:01,HLA-DRB1*01:01,HLA-DRB1*01:01,HLA-DRB1*07:01,HLA-DRB1*07:01,HLA-DRB5*01:01,HLA-DRB5*01:01
& 10 & 24 & 1.5272 & + & - & - & -\tabularnewline
& QVPSPSMGRDIKVQF &
HLA-DRB1*03:01,HLA-DRB1*03:01,HLA-DRB4*01:01,HLA-DRB4*01:01 & 12 & 26 &
1.595 & + & - & - & -\tabularnewline
& VPSPSMGRDIKVQFQ &
HLA-DRB1*03:01,HLA-DRB1*03:01,HLA-DRB4*01:01,HLA-DRB4*01:01 & 13 & 27 &
1.6767 & + & - & - & -\tabularnewline
& PSPSMGRDIKVQFQS &
HLA-DRB1*03:01,HLA-DRB1*03:01,HLA-DRB4*01:01,HLA-DRB4*01:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DQA1*01:02/DQB1*06:02
& 14 & 28 & 1.483 & + & - & - & -\tabularnewline
& DIKVQFQSGGANSPA &
HLA-DRB1*04:01,HLA-DQA1*05:01/DQB1*03:01,HLA-DRB4*01:01,HLA-DRB1*15:01,HLA-DRB1*01:01
& 21 & 35 & 1.5849 & + & - & - & -\tabularnewline
& TGSAVVGLSMAASSA &
HLA-DQA1*01:02/DQB1*06:02,HLA-DQA1*05:01/DQB1*03:01,HLA-DRB1*01:01,HLA-DRB1*08:02,HLA-DRB1*04:01,HLA-DRB1*09:01
& 118 & 132 & 0.9493 & + & - & - & -\tabularnewline
& VGLSMAASSALTLAI &
HLA-DRB1*09:01,HLA-DQA1*05:01/DQB1*03:01,HLA-DRB1*07:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DRB3*02:02,HLA-DPA1*01:03/DPB1*02:01,HLA-DRB1*01:01,HLA-DRB1*13:02,HLA-DPA1*02:01/DPB1*01:01,HLA-DRB1*03:01,HLA-DRB1*04:01,HLA-DRB1*04:05,HLA-DRB1*15:01,HLA-DRB5*01:01,HLA-DRB4*01:01,HLA-DPA1*03:01/DPB1*04:02
& 123 & 137 & 0.8465 & + & - & - & -\tabularnewline
& WVYCGNGKPSDLGGN & HLA-DQA1*05:01/DQB1*03:01 & 208 & 222 & 1.4613 & + &
- & - & -\tabularnewline
Ag85B & PGLVGLAGGAATAGA &
HLA-DQA1*05:01/DQB1*03:01,HLA-DRB1*01:01,HLA-DRB1*15:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DRB1*09:01
& 317 & 331 & 0.8938 & + & - & - & -\tabularnewline
& LRAQDDYNGWDINTP & HLA-DQA1*01:01/DQB1*05:01 & 373 & 387 & 1.2208 & + &
- & - & -\tabularnewline
& KPTGSAAIGLSMAGS &
HLA-DQA1*05:01/DQB1*03:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DRB1*01:01,HLA-DRB1*09:01
& 447 & 461 & 0.9162 & + & - & - & -\tabularnewline
& PTGSAAIGLSMAGSS &
HLA-DQA1*05:01/DQB1*03:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DRB1*09:01,HLA-DRB1*01:01
& 448 & 462 & 1.0429 & + & - & - & -\tabularnewline
& TGSAAIGLSMAGSSA &
HLA-DQA1*05:01/DQB1*03:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DRB1*01:01,HLA-DRB1*09:01
& 449 & 463 & 1.2409 & + & - & - & -\tabularnewline
& GSAAIGLSMAGSSAM &
HLA-DQA1*05:01/DQB1*03:01,HLA-DRB1*09:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DRB1*01:01,HLA-DRB1*07:01,HLA-DRB1*04:01
& 450 & 464 & 0.9638 & + & - & - & -\tabularnewline
& SAAIGLSMAGSSAMI &
HLA-DQA1*05:01/DQB1*03:01,HLA-DRB1*09:01,HLA-DQA1*01:02/DQB1*06:02,HLA-DRB1*01:01,HLA-DRB1*07:01,HLA-DRB1*04:01,HLA-DRB5*01:01
& 451 & 465 & 0.863 & + & - & - & -\tabularnewline
& SMAGSSAMILAAYHP &
HLA-DQA1*01:02/DQB1*06:02,HLA-DQA1*05:01/DQB1*03:01,HLA-DRB1*15:01,HLA-DRB1*12:01,HLA-DRB1*07:01,HLA-DRB1*01:01,HLA-DRB1*09:01,HLA-DRB5*01:01
& 457 & 471 & 0.8015 & + & - & - & -\tabularnewline
& DPSQGMGPSLIGLAM &
HLA-DQA1*05:01/DQB1*03:01,HLA-DRB1*09:01,HLA-DRB1*01:01 & 485 & 499 &
0.9049 & + & - & - & -\tabularnewline
\bottomrule
\end{longtable}

Table 3B. Docking results of selected CTL epitopes with corresponding
MHC alleles\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
Antigens & Peptides & Alleles & Start & End & Length &
Antigenicity\textgreater{}0.8 & Class I
Immunogenicity\textgreater{}0.1\tabularnewline
\midrule
\endhead
Ag85A & FSGWDINTPA & HLA-A*02:06,HLA-A*02:01,HLA-A*68:02,HLA-A*02:03 &
48 & 57 & 10 & 0.9887 & 0.40528\tabularnewline
& SGWDINTPA & HLA-A*02:06 & 49 & 57 & 9 & 1.4382 &
0.24401\tabularnewline
& SGWDINTPAF & HLA-A*23:01,HLA-B*15:01 & 49 & 58 & 10 & 1.5629 &
0.26756\tabularnewline
& NTPAFEWYD & HLA-A*68:02 & 54 & 62 & 9 & 0.927 & 0.4288\tabularnewline
& ALTLAIYHP & HLA-A*02:03 & 132 & 140 & 9 & 1.0436 &
0.1806\tabularnewline
& FQDAYNAGGG & HLA-A*02:06,HLA-A*02:03,HLA-A*68:02 & 240 & 249 & 10 &
1.4901 & 0.1219\tabularnewline
& YNAGGGHNGV & HLA-A*68:02,HLA-A*02:06,HLA-A*02:03 & 244 & 253 & 10 &
2.4651 & 0.15759\tabularnewline
& NAGGGHNGV & HLA-A*68:02 & 245 & 253 & 9 & 3.0386 &
0.12289\tabularnewline
& WEYWGAQLN & HLA-B*40:01,HLA-B*40:01 & 264 & 272 & 9 & 0.904 &
0.18728\tabularnewline
& RALGATPNTG & HLA-A*02:06 & 280 & 289 & 10 & 0.8506 &
0.11318\tabularnewline
Ag85B & GTAAAVVLP & HLA-A*68:02 & 309 & 317 & 9 & 0.9815 &
0.15739\tabularnewline
& VGLAGGAATA & HLA-A*02:03 & 320 & 329 & 10 & 1.0136 &
0.1943\tabularnewline
& GLAGGAATA & HLA-A*02:03,HLA-A*02:01,HLA-A*02:06 & 321 & 329 & 9 &
1.3338 & 0.17233\tabularnewline
& AGGAATAGAF & HLA-B*15:01 & 323 & 332 & 10 & 1.1862 &
0.21456\tabularnewline
& GGAATAGAF & HLA-B*15:01 & 324 & 332 & 9 & 1.0961 &
0.17816\tabularnewline
& GSAAIGLSM & HLA-B*58:01,HLA-B*15:01 & 450 & 458 & 9 & 1.2027 &
0.10755\tabularnewline
& RLWVYCGNGT & HLA-A*02:03 & 537 & 546 & 10 & 0.8136 &
0.10358\tabularnewline
& TPNELGGAN & HLA-B*35:01 & 546 & 554 & 9 & 1.3143 &
0.17121\tabularnewline
& TPNELGGANI & HLA-B*07:02 & 546 & 555 & 10 & 1.2042 &
0.18199\tabularnewline
& ELGGANIPA & HLA-A*68:02 & 549 & 557 & 9 & 0.8819 &
0.18295\tabularnewline
& AYNAAGGHNA & HLA-A*24:02 & 574 & 583 & 10 & 1.5728 &
0.16379\tabularnewline
& YNAAGGHNAV & HLA-A*68:02,HLA-A*02:03,HLA-A*02:06 & 575 & 584 & 10 &
1.6111 & 0.16592\tabularnewline
& NAAGGHNAV & HLA-A*68:02,HLA-B*35:01,HLA-A*02:06,HLA-A*02:03 & 576 &
584 & 9 & 1.9957 & 0.12765\tabularnewline
& NAAGGHNAVF & HLA-B*15:01,HLA-B*35:01 & 576 & 585 & 10 & 1.4758 &
0.16235\tabularnewline
& AAGGHNAVF & HLA-B*15:01,HLA-B*35:01 & 577 & 585 & 9 & 1.1841 &
0.12765\tabularnewline
& AVFNFPPNG & HLA-A*30:01 & 583 & 591 & 9 & 0.9399 &
0.12191\tabularnewline
Rv1733c & FAAAAGTAVQ & HLA-B*15:01 & 679 & 688 & 10 & 0.8588 &
0.21685\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
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\includegraphics[width=0.70\columnwidth]{figures/Figure-1-The-flow-chart-of-the-study/Figure-1-The-flow-chart-of-the-study}

\end{center}
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\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2/Figure-2}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-3/Figure-3}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-6/Figure-6}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-7/Figure-7}

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\includegraphics[width=0.70\columnwidth]{figures/Figure-8/Figure-8}

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\includegraphics[width=0.70\columnwidth]{figures/fig-9/fig-9}

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