In silico characterization of multiple genes encoding the GP63 virulence protein from Leishmania braziliensis: identification of sources of variation and putative roles in immune evasion
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The leishmaniasis are parasitic diseases caused by protozoans of the genus Leishmania, highly divergent eukaryotes, characterized by unique biological features. To survive in both the mammalian hosts and insect vectors, these pathogens make use of a number of mechanisms, many of which are associated with parasite specific proteases. The metalloprotease GP63, the major Leishmania surface antigen, has been found to have multiple functions required for the parasite’s survival. GP63 is encoded by multiple genes and their copy numbers vary considerably between different species and are increased in those from the subgenus Viannia, including L. braziliensis.
By comparing multiple sequences from Leishmania and related organisms this study sought to characterize paralogs in silico, evaluating their differences and similarities and the implications for the GP63 function. The Leishmania GP63 genes are encoded on chromosomes 10, 28 and 31, with the genes from the latter two chromosomes more related to genes found in insect or plant parasites. Those from chromosome 10 have experienced independent expansions in numbers in Leishmania, especially in L. braziliensis. These could be clustered in three groups associated with different mRNA 3′ untranslated regions as well as distinct C-terminal ends for the encoded proteins, with presumably distinct expression patterns and subcellular localizations. Sequence variations between the chromosome 10 genes were linked to intragenic recombination events, mapped to the external surface of the proteins and predicted to be immunogenic, implying a role against the host immune response.
Our results suggest a greater role for the sequence variation found among the chromosome 10 GP63 genes, possibly related to the pathogenesis of L. braziliensis and closely related species within the mammalian host. They also indicate different functions associated to genes mapped to different chromosomes. For the chromosome 10 genes, variable subcellular localizations were found to be most likely associated with multiple functions and target substrates for this versatile protease.
KeywordsLeishmania braziliensis GP63 Virulence proteins
Fetal Bovine Serum
Hidden Markov Models
Membrane Attack Complex
Major Surface Protease
Nucleo de Plataformas Tecnológicas
The leishmaniasis are parasitic infectious diseases caused by flagellated protozoa belonging to the genus Leishmania, family Trypanosomatidae, and which are transmitted by sandflies of the genera Phlebotomus or Lutzomyia. These diseases are found as two major clinical forms, named as cutaneous leishmaniasis (CL) and visceral leishmaniasis (VL), with a global incidence for each in the range of hundreds of thousands of cases per year . Multiple Leishmania species are associated with the leishmaniasis and distinct species, closely related or not, are responsible for the disease in different parts of the world. Those belonging to the subgenus Viannia are restricted to the New World (including L. braziliensis and L. guyanensis), have evolved separately from better known species belonging to the subgenus Leishmania (L. major, L. infantum, L. mexicana and others) and are associated with the mucocutaneous leishmaniasis (MCL), a more aggressive variation of CL .
As successful pathogens, the various Leishmania species have developed effective mechanisms to escape the mammalian host immune response and proliferate [3, 4]. Some of these evasion mechanisms are dependent on proteases, which help ensure that the parasites can invade the mammalian tissue, survive, differentiate and multiply . The GP63 protease, also known as leishmanolysin or major surface protease (MSP), was first discovered in 1980 as the major surface antigen of the promastigote form of many species of Leishmania . It was later found to be bound to the cell membrane through a GlycosylPhosphatidylInositol (GPI) anchor and was also identified as an important virulence factor. This is a zinc-dependent metalloproteinase, which belongs to the peptidase family M8 and the metzincin class and includes conserved features such as the motif HEXXHXXGXXH and a pro-peptide located in the protein’s N-terminal region that renders the proenzyme inactive during translation and is removed during its maturation and activation. The GP63 proteins also include an N-terminal signal sequence which directs them to the endoplasmic reticulum and to the Leishmania secretory pathway [7, 8].
GP63 has been found to play multiple roles during Leishmania infection in mammals, starting in the extracellular environment where it acts inactivating the complement cascade, by cleaving C3b into iC3b. This inactivation prevents the formation of the membrane attack complex (MAC), despite allowing the opsonisation of the Leishmania, mediated by iC3b, and facilitating its phagocytosis. GP63 can also facilitate the binding of the parasite to the macrophage through fibronectin receptors, cleaving proteins from the host’s extracellular matrix. Within the macrophages, it also acts to reduce the production of TNF, IL-12 and nitric oxide, which contributes to the protection and survival of the parasite, and provides the Leishmania with a faster entry into the macrophage, through the activation of a host tyrosine phosphatase [7, 9, 10]. GP63 has also been shown to be released through exosomes into the extracellular medium and this may facilitate its uptake by the macrophage even before the internalization of the Leishmania parasite . Lack of GP63 drastically reduces the Leishmania’s ability to establish and maintain an infection, since the hosts are more likely to induce an innate immunity inflammatory response . Within the host cell cytoplasm, GP63 has been shown to cleave the transcriptional factor AP-1, which regulates the production of pro-inflammatory cytokines and nitric oxide by the macrophage [11, 13]. GP63 was also shown to be associated with the inactivation of the mTOR kinase, leading to the inhibition of protein synthesis in the macrophage and providing an ideal environment for the proliferation of the pathogen .
Early studies have shown that GP63 is more abundantly expressed in the promastigote stage of the Leishmania life cycle, the proliferative stage within the insect vector. This expression may peak during metacyclogenesis, when the parasite prepares to infect the mammalian hosts, and is subsequently reduced again upon differentiation into amastigotes, the intracellular stage that multiplies within the mammalian macrophages [7, 15, 16]. The abundant GP63 expression in promastigotes indicates relevant functions also in the insect vector, presumably needed for survival and proliferation. Indeed, a potential involvement in the degradation of protein components that would lead to the adhesion of the parasite in the insect gut epithelium has been shown [17, 18]. Due to its wide substrate specificity, GP63 may also perform a nutritional role for the parasite, acting as an endopeptidase [19, 20], or even protect the Leishmania against the insect defences .
Concerning the GP63 gene organization, there is a noticeable variation in the number of gene copies encoding these proteins among different Leishmania species. In L, major these genes are present in more than one chromosome and multiple copies have been detected arranged in tandem , with the same multi-copy arrangement also found in L. infantum and L. braziliensis . Noteworthy, however, is the substantial increase in the number of gp63 genes reported for L. braziliensis and other species belonging to the subgenus Viannia, when compared with the subgenus Leishmania. This was reported in early studies [23, 24, 25] and has been confirmed more recently by results derived from a screening for cosmids harboring multiple GP63 genes from L. braziliensis , as well as by genome sequencing data for different Leishmania species [27, 28, 29]. No clear biological reasons are known, however, to explain this expansion in the GP63 gene copy number. Here, aiming to contribute further to the understanding of the role of GP63 in Leishmania pathogenesis in general but with a focus on Viannia species, we sought to investigate the GP63 gene expansion further, using a range of in silico tools. We started by better defining the extent of GP63 gene diversity in L. braziliensis, followed by an in-depth analysis of the similarities and differences between different genes from this and related Leishmania species. The GP63 genes were first grouped according to their chromosomal localization followed by phylogenetic comparisons between different trypanosomatid species. Further grouping according to sequence similarities or differences within non-coding and coding elements was also carried out, in order to define putative functional distinctions. Possible mechanisms associated with the gene expansion due to DNA recombination were then investigated and variations in sequence mapped on the GP63 structure and linked with predictions of immunogenic potential. Our results are consistent with a selective expansion of a subset of GP63 genes in L. braziliensis that might be linked to mammalian pathogenesis and might be required for a better protection against the host immune system.
Search for new L. braziliensis GP63 paralogs
The early studies based on hybridization assays [23, 24] had suggested that the total number of GP63 genes found within Leishmania species belonging to the Viannia subgenus is greater than the number of genes available at the TriTrypDB database and identified after the L. braziliensis genome sequencing and annotation. Recent data based on next generation sequencing have also suggested major variations in copy number of GP63 genes between species within the same subgenus, Leishmania or Viannia, that have not yet been included on the annotated genomes [28, 29, 30]. Here, to begin to understand the true diversity of the L. braziliensis GP63 genes, we first sought to reevaluate the available L. braziliensis GP63 gene sequences considering that the automatic annotation methods might have missed further genes. We therefore performed a reanalysis of the L. braziliensis genome sequences and searched for possible new GP63 paralogs that might not have been annotated. To do this we performed a search in the L. braziliensis genome using the Hidden Markov Models (HMMs) methodology , carried out after a grouping of the entire proteome set from different Leishmania species (described in methods). Nine subsets of GP63 sequences were created using the OrthoMCL tool in order to group these sequences and allow the search to be performed, as shown in Additional file 1: Table S1, with the number of genes in each subset varying in size from 56 to only two. All nine subsets were used to build HMMs and these were then applied for the search of new paralogs in the predicted proteome from L. braziliensis 2904. In general, all HMMs were able to find the GP63 sequences assigned to each subset, however no new paralogs were found during the search. The genome of L. braziliensis strain 2904 deposited on TriTrypDB lists 39 GP63 genes and, in total, the HMMs identified the presence of 38 related sequences. A single gene (LbrM.10.1720) was not recovered using these models and indeed its coding sequence did not provide an alignment with a score high enough to be considered as a GP63. The results of the search for each HMM are summarized in Additional file 2: Table S2 and confirm the gene count number for GP63 genes derived from the L. braziliensis genome sequencing, 38 genes, lower than earlier estimates based on the hybridization studies .
Genomic analysis of known Leishmania GP63 genes
In L. braziliensis, based on the available genomic data for the 2904 strain, major differences in the organization of the GP63 genes are observed when they are compared with those found in species from the Leishmania subgenus. First, no GP63 gene is found on chromosome 28, as highlighted before for other Viannia species , despite the presence of orthologues to the same genes flanking the single GP63 sequence from L. major and L. infantum. In contrast, six GP63 genes or gene fragments are found on chromosome 31, again generally flanked by orthologues to the same genes found flanking the GP63 gene found in the L. major and L. infantum chromosome 31. Even more noteworthy, however, are the 33 GP63 genes found clustered on chromosome 10. Again, these are localized to the same region seen harboring the other Leishmania chromosome 10 genes, as confirmed by the presence of neighboring sequences encoding orthologues to those found flanking the L. major and L. infantum GP63 genes from chromosome 10. However, the precise gene organization cannot be properly defined and many of the genes sequenced are assembled in relatively short contigs, as indicated in the scheme from Fig. 2c. Again, this might be due to the high similarity between the gene sequences and the nature of the sequencing strategy which might have prevented a proper assembly of repeated sequences.
The significantly greater number of L. braziliensis GP63 genes from chromosome 10 is supported by our PCR data where primers sets directed to the chromosome 10 genes were able to amplify more genes than the ones originally used for their synthesis. For example, a primer pair designed to amplify the gene LbrM.10.0470 allowed the amplification of eight different gene fragments (G0510B2; G0560B1; G0560B2; G1610B3; G1610B4; G1610B5; G1610B6; G1620B1) and similarly, the primer pair directed to gene LbrM.10.0540 amplified fragments from six different genes (G0510C1; G0510C2; G0540C1; G0560C4; G1640C1; G1640C2). In contrast, two sets of PCR reactions directed to a single GP63 gene from chromosome 31, using the same 5′ primer and two distinct 3′ primers, only led to the amplification of the same gene, LbrM.31.2260 (Additional file 3: Table S3). Indeed, we believe that most of the six GP63 genes annotated from the L. braziliensis chromosome 31 might not exist and in fact are either pseudogenes or derived from genome assembly errors. Only one of those genes (LbrM.31.2260) has GP63-related protein features, such as the propeptide domain (HEXXH), and shares a high similarity (85%) with the L. major and L. infantum chromosome 31 genes. The LbrM.31.2200, LbrM.31.2220, LbrM.31.2230, LbrM.31.2240 and LbrM.31.2250 genes have stop codons in the middle of their sequences and/or in alignments showed identical N-terminal or C-terminal regions to LbrM.31.2260 (data not shown). It is possible that these genes may represent parts of LbrM.31.2260 not properly assembled and this in agreement with our PCR data finding only LbrM.31.2260. Overall these results are consistent with the expansion in the number of GP63 genes in L. braziliensis, and other species belonging to the Viannia subgenus, being mainly directed to the chromosome 10 genes.
GP63 evolutionary analyses
Overall, the gene clusters shown in the tree highlight the higher similarity between the Leishmania sp. genes from chromosomes 28 and 31 with the GP63 genes found in organisms that live in insects only or parasitize plants. For instance, the 38 annotated GP63 genes from Phytomonas are more closely related to the Leishmania chromosome 28 GP63. It is then possible to hypothesize that these genes might me more involved in the insect stage of the parasite life cycle. Genes more closely related to the chromosome 10 GP63 genes can be found in the insect parasites L. pyrrhocoris and C. fasciculate, but in general these genes seem to have suffered a substantial expansion within Leishmania species.
Evaluation of the sequence diversity of the Leishmania GP63 genes from chromosome 10
Identification of functional differences between the various Leishmania GP63 genes from chromosome 10
Leishmania braziliensis GP63 3’ UTR and C-terminal end gene groups. Table showing the Gp63 gene groups from chromosome 10 defined according to the 3’ UTR and C-terminuses sequence similarity
L. braziliensis 3’UTRs
L. braziliensis chromosome 10 GP63 paralogs
LbrM.10.0510, LbrM.10.0530, LbrM.10.0560, LbrM.10.0580, LbrM.10.0600, LbrM.10.0610, LbrM.10.1540, LbrM.10.1580
LbrM.10.0510, LbrM.10.0530, LbrM.10.0550, LbrM.10.0560, LbrM.10.0600, LbrM.10.0610, LbrM.10.1540, LbrM.10.1580
LbrM.10.0470, LbrM.10.0480, LbrM.10.0500, LbrM.10.0520, LbrM.10.0540, LbrM.10.0570, LbrM.10.1570, LbrM.10.1590, LbrM.10.1610, LbrM.10.1620, LbrM.10.1630, LbrM.10.1640, LbrM.10.1650, LbrM.10.0600, LbrM.10.1680
LbrM.10.0470, LbrM.10.0500, LbrM.10.0520, LbrM.10.0540, LbrM.10.0570, LbrM.10.1570, LbrM.10.1590, LbrM.10.1610, LbrM.10.1620, LbrM.10.1630, LbrM.10.1640, LbrM.10.1650, LbrM.10.1660, LbrM.10.1680
Gene recombination in GP63 sequences from chromosome 10
Protein structural modeling, mapping of variable regions and B-cell epitope prediction
Leishmania braziliensis GP63 B-cell epitope prediction. Table showing the distribution of the predicted epitopes along the studied GP63 paralogs
Total Number of Epitopes
Sequence Variation Region
Type of Epitopes
The in-silico analysis carried out here highlights the strong selective pressure for the expansion in copy number of the chromosome 10 GP63 genes within Leishmania species, and in particular in the Viannia and Sauroleishmania subgenera. The increased number of the chromosome 10 GP63 genes in different Leishmania species evolved independently generating a wide range of paralogs, which display sequence variations and may be generated by recombination. This expansion seems to be an ongoing process that might be related to pathogenesis or defense mechanisms directed to the vertebrate host and the parallel expansion in both Viannia and Sauroleishmania species is something that must be taken into account. Such expansion of multiple genes arranged in tandem, originating from duplication and recombination events, demonstrates the adaptability of Leishmania species to the environment, associated with the evolutionary pressure suffered by the GP63 genes . As a result, the presence of these multi-copy arrays may lead to speciation  or indicate the possible need for stage-specific genes . As previously highlighted , an expansion in GP63 sequences also occurred independently in other trypanosomatids, such as T. cruzi and T. brucei, and this led to novel GP63 domains which might be associated with species-specific or group-specific functions. It is likely then that this expansion in Leishmania GP63 genes might be related to novel aspects of the pathogenesis of these parasites to the vertebrate hosts, but this still needs to be better defined. When multiple strains from a single species is considered the overall GP63 diversity might be even greater, as recently evaluated , and this might be associated with possibly different virulence phenotypes and clinical outcomes for the disease. The recent release of a new L. infantum genome based on data using two distinct methodologies of next generation sequencing, and showing a higher copy number of GP63 genes for this species , also highlights the need for better quality genomes in order to properly define the true diversity of these genes for multiple Leishmania and trypanosomatid species.
The expansion observed in the chromosome 10 genes are concentrated in the Group 1 and Group 2 genes and, if we extrapolate the expression for Group 1 based on the data with the L. major and L. infantum genes [15, 25], they are likely to be expressed constitutively with likely functions during the mammalian infection. In contrast, for the Group 3 genes, with only two paralogs, their expression might be restricted to the promastigote stage of the parasite life cycle, therefore with minor or no relevant function in the mammalian host. For all three groups their expression will have to be confirmed but the large sequence variations observed for both Groups 1 and 2 genes, concentrated on potentially immunogenic regions localized on the surface of the GP63 molecules, also imply related expression patterns during the mammalian stage of the Leishmania life cycle. As previously shown in L. major and L. mexicana , these expression patterns should be linked to the mRNA 3’UTRs and sorting out the molecular mechanisms associated will be a major endeavor. An important question that emerges regarding the expression of the genes from Groups 1 and 2 is related to the multiple paralogs. Are multiple genes belonging to the same group expressed simultaneously or some are expressed more efficiently than others or alternatively? This will also need to be investigated further.
Another relevant question remaining deals with the functional roles for the distinct groups and how these might be associated with sequence differences between the paralogs. A possible link with the proteins’ subcellular localization is presumed based on the differences in the C-terminus of the subsets identified and the presence or absence of a typical GPI anchor. These differences regarding the presence or absence of GPI anchor sites have been suggested before based on comparisons between the L. major and L. infantum GP63 sequences . Here, the C-terminal Group 2 of L. braziliensis GP63 sequences lacks the GPI anchor signal entirely, which is consistent with proteins that are directly secreted into the extracellular medium, as previously reported for L. mexicana GP63 . This release into the extracellular environment might contribute at the early stages of infection, due to the ability of GP63 to digest the extracellular matrix proteins, facilitating parasite mobility and invasion . Alternatively, these proteins might be selectively transferred to exosomes and later to the macrophages in order to influence its metabolism and promote Leishmania growth . For the L. braziliensis Group 1 proteins, they all share a C-terminus having a likely transmembrane domain with no clear GPI anchor site. Lack of a typical GPI anchor site however, with a more likely transmembrane domain identified, was also seen in the L. major Group 1 gene, which was nevertheless seen to have a GPI anchor . The distinct C-terminal ends nevertheless clearly suggest critical differences in subcellular localization for the distinct GP63 groups, but these need further experimental confirmation.
In early studies performed with L. guyanensis, it was suggested that new GP63 genes may be generated by events of mosaicism through recombination between 5′ and 3’ UTRs and protein coding regions , and mosaicism in GP63 sequences was subsequently also found in L. braziliensis genes . The data obtained by us corroborate with other studies investigating GP63 recombination that found it to target mainly the N-terminal and C-terminal regions of the gene [37, 38]. The impact of the GP63 sequence variability in its structure has been investigated in a wider scale, comparing Trypanosoma and Leishmania sequences, and found to be associated with variability in its zinc binding site and presumably activity . In a recent study targeting L. braziliensis GP63 sequences, structural differences have also been found to be associated with sequence variability, implying functional differences, such as during substrate binding, which may affect the interaction with the host . Alternatively, the variability in protein structure could mainly affect recognition by the host immune system and promote infection mainly because the host would need to produce different antibodies to neutralize a single group of proteins. Our results, showing variability concentrated on antigenic regions on the protein’s surface, is in agreement with previously reported data based on L. major and L. infantum sequence analysis where regions of GP63 sequence variation were mapped to the surface of the protein and were associated with immunodominant epitopes . However, more studies are needed to better understand the recognition of different GP63 paralogs by the host immune system.
Overall the data presented here highlights novel and relevant aspects related to the expansion of GP63 genes in L. braziliensis and related Viannia species and raises specific issues regarding the role of GP63 in the parasite pathogenesis during the infection in mammals. It is possible that species belonging to the subgenus Viannia may have added a new level of complexity to GP63 function and this may somehow be related to the capacity of some species to cause the more aggressive mucocutaneous form of the disease. The new questions raised here then, when solved, shall provide novel and relevant knowledge regarding the very unique mechanisms of pathogenesis associated with these parasites.
Our results suggest a greater role for the sequence variation found among the chromosome 10 GP63 genes for the pathogenesis of L. braziliensis and closely related species within the mammalian host. The variation in sequence and the expansion in number of these GP63 genes have occurred independently in different Leishmania lineages, is associated with intragenic recombination events and has a likely role against the host immune response. They also indicate different functions associated to genes mapped to different chromosomes and, for the chromosome 10 genes at least, variable subcellular localizations likely associated with multiple functions and target substrates for this versatile protease.
Parasites and culture conditions
In this study, we used Leishmania (Viannia) braziliensis (MHOM/BR/75/M2904) in its promastigote form. This is a reference strain from the Evandro Chagas Institute, Belém, Brazil. The cells were cultured at 26 °C in Schneider (Sigma) pH 7.2 supplemented with 20% fetal bovine serum (FBS), antibiotics (Streptomycin / Penicillin 0.1%) and 0.1% Hemin.
PCR, cloning and sequencing
Approximately, 108 L. braziliensis promastigotes were used for total genomic DNA extraction using DNAzol (Invitrogen) and standard procedures. PCR reactions for the amplification of the GP63 sequences were performed using Phusion® High-Fidelity DNA Polymerase (New England Biolabs), following the manufacturer’s protocol and with the oligonucleotides used as primers listed in the Additional file 5: Table S5. After amplification, cloning and sequencing of the PCR products, a nomenclature was created for the newly generated sequences in order to identify from which set of primers they were derived, whether from those encoding the KDELMAP or GPI regions, and defining which annotated GP63 gene it most closely resembles. The newly generated sequences derived from the PCR amplifications were deposited on the GenBank and all accession numbers are listed in Additional file 3: Table S3.
Search for new GP63 paralogs through hidden Markov models
First, the predicted proteomes of the following organisms were downloaded from TritrypDB in August 25, 2014: L. braziliensis strain 2903 [taxid: 1295825], L. braziliensis strain 2904 [taxid: 420245], L. infantum [taxid: 435258], L. major [taxid: 347515], L. donovani [taxid: 981087], L. mexicana [taxid: 929439] and L. tarentolae [taxid: 5689]. GP63 genes were then identified within the downloaded proteomes, considering only genes annotated as GP63, encoding proteins longer than 30 amino acids and with no more than one stop codon per sequence. All of the protein sequences derived from genes that met these inclusion criteria were submitted to the analysis of the OrthoMCL program , and grouped according to homology using the Markov Cluster algorithm . Protein sequences from each group were aligned using the MAFFT software (default settings)  and the multiple alignments used as input for the hmmbuild, version 3.0, a tool from the HMMER package  to build Hidden Markov Models (HMMs). The models were then used with the hmmsearch tool to search for new paralogs within the L. braziliensis strain 2904 proteome. A cutoff of 0.001 for hit significance (e-value < = 0.001) was applied.
GP63 phylogenetic analysis and detection of recombination events
A phylogenetic tree was built with GP63 protein sequences from genes encoded within chromosomes 10, 28 and 31 from diverse Leishmania species and more distantly related organisms. These include the Phytomonas sp. isolate Hart11 [taxid: 134014], Crithidia fasciculata [taxid: 5656], Leptomonas pyrrhocoris [taxid: 157538], Trypanossoma cruzi [taxid: 353153], Trypanossoma brucei [taxid: 185431], Trypanossoma theileri [taxid: 67003] and Bodo saltans [taxid: 75058]. Another tree was made with selected GP63 sequences used in the previous analyses plus the ones obtained by PCR from L. braziliensis as well as GP63 sequences from Leishmania guyanensis [taxid: 5670]. For all trees, the selected sequences were aligned by MAFFT (default settings) and the alignments automatically edited by Trimal  to keep just phylogenetically informative sites. ProtTest  was then used to predict the best evolutionary model which was subsequently used as a setting to build phylogenetic trees with PhyML, applying the Maximum Likelihood (ML) method , and MrBayes, applying the Bayesian method [55, 56]. The branch support for the ML tree was given by non-parametric bootstrap analysis using 1000 replicates. The Bayesian inferred trees were determined by 5,000,000 chains to check for convergence and a 100% burn-in was discarded. The aligned nucleotide sequences from L. braziliensis, obtained from the TriTrypDB database and through PCR, were analyzed for recombination using the RDP4 program .
Modelling of GP63 homologs and searches for non-conserved regions
Eight of the most variable paralogs from different L. braziliensis C-terminal groups were chosen for the three-dimensional modelling. The modelling was performed for the amino acid sequences previously obtained from TriTrypDB and applying the SWISS MODEL platform . When the models were completed, their qualities were assessed through Procheck . Specific regions of the protein models were then evaluated using the initial alignment information, highlighting the non-conserved regions which were characterized by amino acid exchanges.
B-cell epitope prediction
Linear B-cell epitope predictions were performed for the protein sequences used in the 3D modeling step. The predictions were carried out using the following programs: AAP12 , BCPred12  and BepiPred . Only epitopes predicted by at least two programs, with lengths equal to or greater than 10 amino acids and with scores greater than 0.8 were considered as positive predictions on AAP12 and BCpred12. Epitopes with scores over 0.5 obtained by BepiPred were also included in the analysis.
In addition to the linear prediction, a conformational prediction of epitopes was also performed to evaluate if the protein structures were also able to generate interaction with the immune system. The conformational epitopes were predicted by the CBTOPE web server , where only epitopes with more than 10 amino acids and a score above 4 were considered for this study. After the prediction, an assessment was performed to map the localization of all the epitopes on the modeled proteins.
We thank members of Dr. O. P. de Melo Neto’s laboratory for helpful discussions and support. The authors thank the Nucleo de Plataformas Tecnológicas (NPT) at the Institute Aggeu Magalhães (FIOCRUZ-PE) for the use of its automatic sequencing facility.
The Leishmania work in Dr. de Melo Neto’s lab was more recently funded with grants provided by the Brazilian funding agencies FACEPE (APQ-0239-2.02/12 and APQ-1662-2.02/15), CNPq (480899/2013–4, 313934/2013–4 and 401282/2014–7) and CAPES (23038.007656/2011–92). Studentships for the graduate students (ALCN, and ANALMB) were provided by CAPES and FACEPE.
ALCN – experimental and bioinformatic analysis, writing original draft. ANALMB - experimental and bioinformatic analysis. AMR – bioinformatics experimental design. FBM – results discussions. OPMN – conceptualization, supervision, funding acquisition, writing, review and editing. All authors read and approved the final manuscript.
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