scholarly journals HLA-DRB1 Alleles Associated with Lower Leishmaniasis Susceptibility Share Common Amino Acid Polymorphisms and Epitope Binding Repertoires

Vaccines ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 270
Author(s):  
Nicky de Vrij ◽  
Pieter Meysman ◽  
Sofie Gielis ◽  
Wim Adriaensen ◽  
Kris Laukens ◽  
...  
Keyword(s):  
Amino Acid ◽  
Cell Epitope ◽  
Human Leukocyte ◽  
Leishmania Species ◽  
Hla Polymorphism ◽  
Common Amino Acid ◽  
Binding Core ◽  
Epitope Discovery ◽  
Epitope Binding ◽  
The Impact

Susceptibility for leishmaniasis is largely dependent on host genetic and immune factors. Despite the previously described association of human leukocyte antigen (HLA) gene cluster variants as genetic susceptibility factors for leishmaniasis, little is known regarding the mechanisms that underpin these associations. To better understand this underlying functionality, we first collected all known leishmaniasis-associated HLA variants in a thorough literature review. Next, we aligned and compared the protection- and risk-associated HLA-DRB1 allele sequences. This identified several amino acid polymorphisms that distinguish protection- from risk-associated HLA-DRB1 alleles. Subsequently, T cell epitope binding predictions were carried out across these alleles to map the impact of these polymorphisms on the epitope binding repertoires. For these predictions, we used epitopes derived from entire proteomes of multiple Leishmania species. Epitopes binding to protection-associated HLA-DRB1 alleles shared common binding core motifs, mapping to the identified HLA-DRB1 amino acid polymorphisms. These results strongly suggest that HLA polymorphism, resulting in differential antigen presentation, affects the association between HLA and leishmaniasis disease development. Finally, we established a valuable open-access resource of putative epitopes. A set of 14 HLA-unrestricted strong-binding epitopes, conserved across species, was prioritized for further epitope discovery in the search for novel subunit-based vaccines.

scholarly journals Predicted epitope binding core motifs and common amino acid polymorphisms distinguish protective- from susceptibility-associated HLA alleles in leishmaniasis

2021 ◽  
Author(s):  
Nicky de Vrij ◽  
Pieter Meysman ◽  
Sofie Gielis ◽  
Wim Adriaensen ◽  
Kris Laukens ◽  
...  
Keyword(s):  
Amino Acid ◽  
Cell Epitope ◽  
Human Leukocyte ◽  
Common Amino Acid ◽  
Leukocyte Antigen ◽  
Susceptibility Factors ◽  
Binding Core ◽  
Epitope Discovery ◽  
Epitope Binding ◽  
Open Access Resource

AbstractSusceptibility for leishmaniasis is largely dependent on genetic- and immune factors of the host. Despite the previously described association of human leukocyte antigen (HLA) gene cluster variants as genetic susceptibility factors, little is known on the mechanisms that mediate these associations. To characterize the functionality underpinning these associations between HLA and disease, we predicted the epitope binding repertoires for all known leishmaniasis-associated HLA variants collected in a thorough literature review. We identified several amino acid polymorphisms in the HLA sequences that distinguished protective-from risk-associated HLA-DRB1 alleles. Proteome-wide and multi-species T cell epitope binding predictions were carried out across these alleles, enabling us to map the effects on the epitope binding repertoires. The protective-associated HLA-DRB1 alleles were characterized by common binding core motifs, which map to the identified amino acid polymorphisms. These results strongly suggest that polymorphism in the HLA region, resulting in differential antigen presentation, affects the association between HLA and leishmaniasis disease development. Finally, we established a valuable open-access resource of putative epitopes, of which a set of 14 HLA-unrestricted strong-binding epitopes, conserved across species, were prioritized for further epitope discovery in the search for novel subunit-based vaccines.

Assessing the Impact of Secondary Structure and Solvent Accessibility on Protein Evolution

Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 445-458 ◽  
Author(s):  
Nick Goldman ◽  
Jeffrey L Thorne ◽  
David T Jones
Keyword(s):  
Amino Acid ◽  
Secondary Structure ◽  
Protein Evolution ◽  
Solvent Accessibility ◽  
Strong Association ◽  
Length Distribution ◽  
Parametric Bootstrap ◽  
Amino Acid Replacement ◽  
Physical Constraints ◽  
The Impact

Abstract Empirically derived models of amino acid replacement are employed to study the association between various physical features of proteins and evolution. The strengths of these associations are statistically evaluated by applying the models of protein evolution to 11 diverse sets of protein sequences. Parametric bootstrap tests indicate that the solvent accessibility status of a site has a particularly strong association with the process of amino acid replacement that it experiences. Significant association between secondary structure environment and the amino acid replacement process is also observed. Careful description of the length distribution of secondary structure elements and of the organization of secondary structure and solvent accessibility along a protein did not always significantly improve the fit of the evolutionary models to the data sets that were analyzed. As indicated by the strength of the association of both solvent accessibility and secondary structure with amino acid replacement, the process of protein evolution—both above and below the species level—will not be well understood until the physical constraints that affect protein evolution are identified and characterized.

scholarly journals Predicting TCR-Epitope Binding Specificity Using Deep Metric Learning and Multimodal Learning

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 572
Author(s):  
Alan M. Luu ◽  
Jacob R. Leistico ◽  
Tim Miller ◽  
Somang Kim ◽  
Jun S. Song
Keyword(s):  
Neural Network ◽  
Amino Acid ◽  
Cytotoxic T Cells ◽  
Metric Learning ◽  
Binding Specificity ◽  
Class I ◽  
Multimodal Learning ◽  
Binding Prediction ◽  
Deep Metric Learning ◽  
Epitope Binding

Understanding the recognition of specific epitopes by cytotoxic T cells is a central problem in immunology. Although predicting binding between peptides and the class I Major Histocompatibility Complex (MHC) has had success, predicting interactions between T cell receptors (TCRs) and MHC class I-peptide complexes (pMHC) remains elusive. This paper utilizes a convolutional neural network model employing deep metric learning and multimodal learning to perform two critical tasks in TCR-epitope binding prediction: identifying the TCRs that bind a given epitope from a TCR repertoire, and identifying the binding epitope of a given TCR from a list of candidate epitopes. Our model can perform both tasks simultaneously and reveals that inconsistent preprocessing of TCR sequences can confound binding prediction. Applying a neural network interpretation method identifies key amino acid sequence patterns and positions within the TCR, important for binding specificity. Contrary to common assumption, known crystal structures of TCR-pMHC complexes show that the predicted salient amino acid positions are not necessarily the closest to the epitopes, implying that physical proximity may not be a good proxy for importance in determining TCR-epitope specificity. Our work thus provides an insight into the learned predictive features of TCR-epitope binding specificity and advances the associated classification tasks.

scholarly journals Impact of HLA Mismatching on Early Subclinical Inflammation in Low-Immunological-Risk Kidney Transplant Recipients

2021 ◽  
Vol 10 (9) ◽  
pp. 1934
Author(s):  
Domingo Hernández ◽  
Teresa Vázquez ◽  
Juana Alonso-Titos ◽  
Myriam León ◽  
Abelardo Caballero ◽  
...  
Keyword(s):  
Risk Factor ◽  
Kidney Transplant ◽  
Graft Function ◽  
Human Leukocyte ◽  
Subclinical Inflammation ◽  
Kidney Transplant Recipients ◽  
Protocol Biopsy ◽  
Recipient Age ◽  
The Impact ◽  
Hla Mismatches

The impact of human leukocyte antigen (HLA)-mismatching on the early appearance of subclinical inflammation (SCI) in low-immunological-risk kidney transplant (KT) recipients is undetermined. We aimed to assess whether HLA-mismatching (A-B-C-DR-DQ) is a risk factor for early SCI. As part of a clinical trial (Clinicaltrials.gov, number NCT02284464), a total of 105 low-immunological-risk KT patients underwent a protocol biopsy on the third month post-KT. As a result, 54 presented SCI, showing a greater number of total HLA-mismatches (p = 0.008) and worse allograft function compared with the no inflammation group (48.5 ± 13.6 vs. 60 ± 23.4 mL/min; p = 0.003). Multiple logistic regression showed that the only risk factor associated with SCI was the total HLA-mismatch score (OR 1.32, 95%CI 1.06–1.64, p = 0.013) or class II HLA mismatching (OR 1.51; 95%CI 1.04–2.19, p = 0.032) after adjusting for confounder variables (recipient age, delayed graft function, transfusion prior KT, and tacrolimus levels). The ROC curve illustrated that the HLA mismatching of six antigens was the optimal value in terms of sensitivity and specificity for predicting the SCI. Finally, a significantly higher proportion of SCI was seen in patients with >6 vs. ≤6 HLA-mismatches (62.3 vs. 37.7%; p = 0.008). HLA compatibility is an independent risk factor associated with early SCI. Thus, transplant physicians should perhaps be more aware of HLA mismatching to reduce these early harmful lesions.

scholarly journals Design of a companion bioinformatic tool to detect the emergence and geographical distribution of SARS-CoV-2 Spike protein genetic variants

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Alice Massacci ◽  
Eleonora Sperandio ◽  
Lorenzo D’Ambrosio ◽  
Mariano Maffei ◽  
Fabio Palombo ◽  
...  
Keyword(s):  
Receptor Binding ◽  
Consensus Sequence ◽  
Cell Epitope ◽  
Vaccine Design ◽  
Binding Domain ◽  
Spike Protein ◽  
Antibody Activity ◽  
Binding Motif ◽  
Receptor Binding Domain ◽  
The Impact

Abstract Background Tracking the genetic variability of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) is a crucial challenge. Mainly to identify target sequences in order to generate robust vaccines and neutralizing monoclonal antibodies, but also to track viral genetic temporal and geographic evolution and to mine for variants associated with reduced or increased disease severity. Several online tools and bioinformatic phylogenetic analyses have been released, but the main interest lies in the Spike protein, which is the pivotal element of current vaccine design, and in the Receptor Binding Domain, that accounts for most of the neutralizing the antibody activity. Methods Here, we present an open-source bioinformatic protocol, and a web portal focused on SARS-CoV-2 single mutations and minimal consensus sequence building as a companion vaccine design tool. Furthermore, we provide immunogenomic analyses to understand the impact of the most frequent RBD variations. Results Results on the whole GISAID sequence dataset at the time of the writing (October 2020) reveals an emerging mutation, S477N, located on the central part of the Spike protein Receptor Binding Domain, the Receptor Binding Motif. Immunogenomic analyses revealed some variation in mutated epitope MHC compatibility, T-cell recognition, and B-cell epitope probability for most frequent human HLAs. Conclusions This work provides a framework able to track down SARS-CoV-2 genomic variability.

scholarly journals Codon harmonization reduces amino acid misincorporation in bacterially expressed P. falciparum proteins and improves their immunogenicity

AMB Express ◽  
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Neeraja Punde ◽  
Jennifer Kooken ◽  
Dagmar Leary ◽  
Patricia M. Legler ◽  
Evelina Angov
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Codon Usage ◽  
Dna Sequences ◽  
Structural Integrity ◽  
Host Cells ◽  
Loss Of Function ◽  
Species Specific ◽  
And Function ◽  
The Impact

Abstract Codon usage frequency influences protein structure and function. The frequency with which codons are used potentially impacts primary, secondary and tertiary protein structure. Poor expression, loss of function, insolubility, or truncation can result from species-specific differences in codon usage. “Codon harmonization” more closely aligns native codon usage frequencies with those of the expression host particularly within putative inter-domain segments where slower rates of translation may play a role in protein folding. Heterologous expression of Plasmodium falciparum genes in Escherichia coli has been a challenge due to their AT-rich codon bias and the highly repetitive DNA sequences. Here, codon harmonization was applied to the malarial antigen, CelTOS (Cell-traversal protein for ookinetes and sporozoites). CelTOS is a highly conserved P. falciparum protein involved in cellular traversal through mosquito and vertebrate host cells. It reversibly refolds after thermal denaturation making it a desirable malarial vaccine candidate. Protein expressed in E. coli from a codon harmonized sequence of P. falciparum CelTOS (CH-PfCelTOS) was compared with protein expressed from the native codon sequence (N-PfCelTOS) to assess the impact of codon usage on protein expression levels, solubility, yield, stability, structural integrity, recognition with CelTOS-specific mAbs and immunogenicity in mice. While the translated proteins were expected to be identical, the translated products produced from the codon-harmonized sequence differed in helical content and showed a smaller distribution of polypeptides in mass spectra indicating lower heterogeneity of the codon harmonized version and fewer amino acid misincorporations. Substitutions of hydrophobic-to-hydrophobic amino acid were observed more commonly than any other. CH-PfCelTOS induced significantly higher antibody levels compared with N-PfCelTOS; however, no significant differences in either IFN-γ or IL-4 cellular responses were detected between the two antigens.

Sign in / Sign up

Export Citation Format

Share Document