3.1 Determination of F. hepatica based on the morphomolecular characteristics
In the present study, worms with an average length and width of 30×13 mm were identified as F. hepatica (132 liver fluke) and worms with an average length and width of 75×12 mm were considered F. gigantica (53 liver fluke) and excluded from this study. The amplification of the 234 bp fragment of F. hepatica cytochrome c oxidase subunit-1based upon morphological characters.
3.2 Cultivation of F. hepatica eggs and miracidia hatching
Miracidia of F.hepatica developed within 20-17 day’s period as out of 10000 F.hepatica cultured eggs, 48.75% (1425) completely developed into miracidia. On the day 19 after culture, 11.9% (170 miracidia) and on the day 21, 40% (570 miracidia) of eggs were hatched.
3.3 CDNA synthesis and amplification of the HDM-1 gene from eggs, miracidia and adult F. hepatica flukes
The 234bp amplified fragment of COX1 in the synthesized cDNA from total RNA of eggs, miracidia and adult flukes played the role of an internal control .The 153bp amplified fragment of F.hepaticaHDM-1 in the synthesized cDNA of adult flukes could indicate the presence of mRNA and HDM-1 expression in this sample as the lack of amplified fragment in the synthesized cDNA of eggs and miracidia was considered that they could be related to the deficiency of mRNA and HDM-1 expression (Fig. 1). The sequencing result of F.hepaticaHDM-1 adult flukes was registered in the gene bank with access numbers MN786462 and it was translated into amino acid sequences.
3.4 Sequencing and phylogenetic analysis of the F.hepatica HDM-1
The short amplicon-based sequences of HDMs isolates from the global Uniprot with HDM amino acid sequence from our study were aligned (Fig. 2) and the phylogenetic tree of HDM was accordingly generated (Fig. 3), revealed a 100% similarity of our isolate with HDMs of F. hepatica and Fasciola gigantica published in UniProt.HDMs sequences were included in phylogeny analysis that showed separation of sequences into three main clades in the phylogenetic tree along with Fasciola HDMs, Echinostoma, Fasciolopsis, Paragonimus, Clonorchis, Opisthorchis, Trichobilharzia and Schistosoma HDMs(Fig. 3).
3.5 Bioinformatic analysis
PROCHECK was used to assess the stereochemical quality of peptide structures. Ramachandran plot showed relatively good quality of the predicted model (Fig. 4).The protein-sol patches tool was used to calculate patches of charge at pH 6.3 and hydrophobicity of the protein surface, allowing determination of interesting areas on the surface involved in the behavior and stability of structure (Fig. 5). A shows hydrophobic patches for the FhHDM-1, where the ratio of non-polar to polar solvent accessible surface area (NPP ratio) values was given as a scale from low NPP ratio (purple regions) to high NPP ratio (green regions). In Figure 6, picture B it can be visualized charged surface patches from negative charge (color-coded: red regions) to positive charge (color-coded: blue regions). The scaled solubility value was found to be greater than 0.8 by protein-sol patches software, indicating a higher solubility when compared with average soluble E.coli protein.
3.6 Membrane simulation
To determine the reliability of the lipid bilayer simulation results, analyzes were performed at the end of the membrane simulation, the results of which are shown in Figure 7. This figure includes changes in the distance (membrane thickness) between the phosphate atoms of each membrane layer (Fig. 7 a). The electron density of the polar heads of lipid molecules at the two outer surfaces of the membrane can also be observed (Figure 7 d). Another diagram of this figure is related to the density of the phosphate group and the density of water molecules on the outer surface of the two layers of the membrane (Fig. 7c), which clearly shows that the polar heads are located outwards during the simulation and the two outer sides of the membrane have the highest density. These results all confirm the stability of the lipid bilayer membrane and the complete formation of lipid molecules together. Analyzes of the total and partial fluctuations and compaction of the peptide structure during the simulation time indicated the stability of the peptide structure (Fig. 8).
To simulate the peptide in the presence of the membrane, the peptide was placed parallel to and perpendicular to the lipid bilayer membrane by designing a suitable program file using the Gromex program (Fig. 9).
Our results suggest that the peptide can internalized in to the membrane through endocytosis within 1000 nm of simulation (Fig. 9).To prove the entry of the peptide into the membrane, the density of the desired peptide among the hydrocarbon chains of the membrane lipids was calculated during the simulation time. These results indicate that the density of the peptide increased between these chains, indicating the internalization of the peptide into the membrane (Fig. 10).
In the presence of peptide, the thickness and membrane diffusion coefficient increases compared to the pure membrane (Fig. 10). This analysis also indicates the internalization of the peptide into the membrane surface and the gradual entry into the membrane. The distribution of lipid groups and ions around the peptide was calculated for quantifying the position of peptide uptake in biological membranes and understanding of the uptake mechanism. The results showed that most peaks belonged to lipid phosphate groups (Fig. 11a and b). These findings well show that the peptide has moved away from the aqueous environment over time and enters the biological membrane using the polar heads of lipid molecules by creating curvature in the membrane through endocytosis pathways. As the peptide enters the vesicle, we see a decrease in the ion radial distribution function around the peptide (Fig. 11c), which indicates that the peptide is moving away from the aqueous environment. Simultaneously with this decrease, an increase was observed in the distribution of polar groups (8 a-c) around the peptide. Furthermore, the analysis of the distribution function of hydrocarbon tails (hydrophobic) shows well that the density of these groups increases with the distance of the peptide from the aqueous environment and internalization (Fig. 11 d). Thus, our analysis revealed that the peptide can be internalized into the membrane with interaction of polar groups, when is surrounded by hydrocarbon tails of the membrane (Fig. 12). Indeed, negatively charged phosphate groups play a key role in the u and penetration of peptides into membranes. Figure 11 c also shows that the distance between the peptide and the lipid phosphate groups is less than 1 nm (peak position in Fig. 11c), where peptide internalization into the membrane can occur at this distance.
3.7 Prediction of antigenicity and presenting epitopes to T cells
The sequence of FhHMD-1 was predicted antigenic with overall score of 0.5093 (threshold of 0.5). The possible T cell epitopes on the sequence of protein was scanned against a panel of most frequently occurring alleles using the IEDB recommended prediction method (Net MHC pan). The MHC-I epitopes were evaluated based upon the proteasome cleavage score, the TAP score and the MHC binding score. The total score was calculated as the sum of these scores that indicates the ratio of the amount of peptides presented by MHC molecules on the cell surface. The predicted epitopes were screened for the IC50 less than 50 nM as candidates with higher binding affinity (Table 1).
Table 1. Evaluation of the MHC I antigen processing
Allele
|
Position
|
Peptide
|
Proteasome Score
|
TAP * Score
|
MHC Score
|
Total Score
|
IC50 (nM)
|
HLA-A*02:03
HLA-A*02:06
|
16-25
|
KMVKALRDAV
|
0.85
|
0.33
|
-1.13
|
0.05
|
13.5
|
HLA-B*15:01
|
20-29
|
ALRDAVTKAY
|
1.29
|
1.41
|
-1.34
|
1.36
|
21.9
|
HLA-A*30:01
|
31-40
|
KARDRAMAYL
|
1.37
|
0.43
|
-1.24
|
0.57
|
17.2
|
HLA-A*68:01
|
50-59
|
TEVITILLNR
|
1.04
|
0.61
|
-1.29
|
0.37
|
19.4
|
* Transporter associated with antigen processing (TAP)
The top ranked MHC II binding epitopes are presented in Table 2, where the higher value of cleavage probability score and the lower amount of the percentile rank predicts the greater possibility of antigen presenting by MHC II molecules.
Table 2. Evaluation of the MHC II antigen processing
Position
|
Peptide
|
Peptide length
|
Cleavage probability score
|
Cleavage probability percentile rank
|
34-48
|
DRAMAYLAKDNLGEK
|
15
|
0.85345
|
0
|
43-56
|
DNLGEKITEVITIL
|
14
|
0.61552
|
0.18
|
23-35
|
DAVTKAYEKARDR
|
13
|
0.54836
|
0.36
|
23-36
|
DAVTKAYEKARDRA
|
14
|
0.46804
|
0.53
|
42-56
|
KDNLGEKITEVITIL
|
15
|
0.46326
|
0.71
|