scholarly journals MHC class I allele diversity in cynomolgus macaques of Vietnamese origin

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7941
Author(s):  
Shuting Huang ◽  
Xia Huang ◽  
Shuang Li ◽  
Mingjun Zhu ◽  
Min Zhuo
Keyword(s):  
Mhc Class I ◽  
Binding Sites ◽  
Macaca Fascicularis ◽  
Peptide Binding ◽  
Cynomolgus Macaque ◽  
Class I ◽  
Histocompatibility Complex ◽  
Cynomolgus Macaques ◽  
Mhc Alleles ◽  
Potential Recombination Event

Cynomolgus macaques (Macaca fascicularis, Mafa) have been used as important experimental animal models for carrying out biomedical researches. The results of biomedical experiments strongly depend on the immunogenetic background of animals, especially on the diversity of major histocompatibility complex (MHC) alleles. However, there is much less information available on the polymorphism of MHC class I genes in cynomolgus macaques, than is currently available for humans. In this study, we have identified 40 Mafa-A and 60 Mafa-B exons 2 and 3 sequences from 30 unrelated cynomolgus macaques of Vietnamese origin. Among these alleles, 28 are novel. As for the remaining 72 known alleles, 15 alleles are shared with other cynomolgus macaque populations and 32 are identical to alleles previously reported in other macaque species. A potential recombination event was observed between Mafa-A1*091:02 and Mafa-A1*057:01. In addition, the Mafa-A1 genes were found to be more diverse than human HLA-A and the functional residues for peptide binding sites (PBS) or TCR binding sites (TBS) in Mafa-A1 have greater variability than that for non-PBS or non-TBS regions. Overall, this study provides important information on the diversity of Mafa-A and Mafa-B alleles from Vietnamese origin, which may help researchers to choose the most appropriate animals for their studies.

scholarly journals Major histocompatibility complex haplotyping and long-amplicon allele discovery in cynomolgus macaques from Chinese breeding facilities

2016 ◽  
Author(s):  
Julie A. Karl ◽  
Michael E. Graham ◽  
Roger W. Wiseman ◽  
Katelyn E. Heimbruch ◽  
Samantha M. Gieger ◽  
...  
Keyword(s):  
Major Histocompatibility Complex ◽  
Mhc Class I ◽  
Mhc Class Ii ◽  
Cynomolgus Macaque ◽  
Full Length ◽  
Class I ◽  
Major Histocompatibility ◽  
Histocompatibility Complex ◽  
Cynomolgus Macaques ◽  
Allele Discovery

ABSTRACTVery little is currently known about the major histocompatibility complex (MHC) region of cynomolgus macaques (Macaca fascicularis; Mafa) from Chinese breeding centers. We performed comprehensive MHC class I haplotype analysis of 100 cynomolgus macaques from two different centers, with animals from different reported original geographic origins (Vietnamese, Cambodian, and Cambodian/Indonesian mixed-origin). Many of the samples were of known relation to each other (sire, dam, and progeny sets), making it possible to characterize lineage-level haplotypes in these animals. We identified 52 Mafa-A and 74 Mafa-B haplotypes in this cohort, many of which were restricted to specific sample origins. We also characterized full-length MHC class I transcripts using Pacific Biosciences (PacBio) RS II single-molecule real-time (SMRT) sequencing. This technology allows for complete read-through of unfragmented MHC class I transcripts (~1,100 bp in length), so no assembly is required to unambiguously resolve novel full-length sequences. Overall, we identified 313 total full-length transcripts in a subset of 72 cynomolgus macaques from these Chinese breeding facilities; 131 of these sequences were novel and an additional 116 extended existing short database sequences to span the complete open reading frame. This significantly expands the number of Mafa-A, Mafa-B, and Mafa-I full-length alleles in the official cynomolgus macaque MHC class I database. The PacBio technique described here represents a general method for full-length allele discovery and genotyping that can be extended to other complex immune loci such as MHC class II, killer immunoglobulin-like receptors, and Fc gamma receptors.

scholarly journals Characterization of 100 extended major histocompatibility complex haplotypes in Indonesian cynomolgus macaques

2019 ◽  
Author(s):  
Cecilia G. Shortreed ◽  
Roger W. Wiseman ◽  
Julie A. Karl ◽  
Hailey E. Bussan ◽  
David A. Baker ◽  
...  
Keyword(s):  
Major Histocompatibility Complex ◽  
Mhc Class I ◽  
Macaca Fascicularis ◽  
Class Ii ◽  
Class I ◽  
Major Histocompatibility ◽  
Breeding Colony ◽  
Allelic Variants ◽  
Histocompatibility Complex ◽  
Cynomolgus Macaques

AbstractMany medical advancements – including improvements to anti-rejection therapies in transplantation and vaccine development – rely on pre-clinical studies conducted in cynomolgus macaques (Macaca fascicularis). Major histocompatibility complex (MHC) class I and class II genes of cynomolgus macaques are orthologous to human leukocyte antigen complex (HLA) class I and class II genes, respectively. Both encode cell-surface proteins involved in cell recognition and rejection of non-host tissues. MHC class I and class II genes are highly polymorphic, so comprehensive genotyping requires the development of complete databases of allelic variants. Our group used PacBio circular consensus sequencing of full-length cDNA amplicons to characterize MHC class I and class II transcript sequences for a cohort of 295 Indonesian cynomolgus macaques (ICM) in a large, pedigreed breeding colony. These studies allowed us to expand the existing database of Macaca fascicularis (Mafa) alleles by identifying an additional 141 MHC class I and 61 class II transcript sequences. In addition, we defined co-segregating combinations of allelic variants as regional haplotypes for 70 Mafa-A, 78 Mafa-B and 45 Mafa-DRB gene clusters. Finally, we defined class I and class II transcripts that are associated with 100 extended MHC haplotypes in this breeding colony by combining our genotyping analyses with short tandem repeat (STR) patterns across the MHC region. Our sequencing analyses and haplotype definitions improve the utility of these ICM for transplantation studies as well as infectious disease and vaccine research.

scholarly journals Porcine major histocompatibility complex (MHC) class I molecules and analysis of their peptide-binding specificities

2011 ◽  
Vol 63 (12) ◽  
pp. 821-834 ◽  
Author(s):  
Lasse Eggers Pedersen ◽  
Mikkel Harndahl ◽  
Michael Rasmussen ◽  
Kasper Lamberth ◽  
William T. Golde ◽  
...  
Keyword(s):  
Major Histocompatibility Complex ◽  
Mhc Class I ◽  
Peptide Binding ◽  
Class I ◽  
Major Histocompatibility ◽  
Histocompatibility Complex ◽  
Mhc Class I Molecules

Discovery of novel MHC-class I alleles and haplotypes in Filipino cynomolgus macaques (Macaca fascicularis) by pyrosequencing and Sanger sequencing

2015 ◽  
Vol 67 (10) ◽  
pp. 563-578 ◽  
Author(s):  
Takashi Shiina ◽  
Yukiho Yamada ◽  
Alice Aarnink ◽  
Shingo Suzuki ◽  
Anri Masuya ◽  
...  
Keyword(s):  
Mhc Class I ◽  
Sanger Sequencing ◽  
Macaca Fascicularis ◽  
Class I ◽  
Cynomolgus Macaques

scholarly journals Evaluation of machine learning methods to predict peptide binding to MHC Class I proteins

2017 ◽  
Author(s):  
Rohit Bhattacharya ◽  
Ashok Sivakumar ◽  
Collin Tokheim ◽  
Violeta Beleva Guthrie ◽  
Valsamo Anagnostou ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Amino Acids ◽  
Mhc Class I ◽  
Mhc Class Ii ◽  
Class I ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Histocompatibility Complex ◽  
Mhc Alleles

AbstractBinding of peptides to Major Histocompatibility Complex (MHC) proteins is a critical step in immune response. Peptides bound to MHCs are recognized by CD8+ (MHC Class I) and CD4+ (MHC Class II) T-cells. Successful prediction of which peptides will bind to specific MHC alleles would benefit many cancer immunotherapy appications. Currently, supervised machine learning is the leading computational approach to predict peptide-MHC binding, and a number of methods, trained using results of binding assays, have been published. Many clinical researchers are dissatisfied with the sensitivity and specificity of currently available methods and the limited number of alleles for which they can be applied. We evaluated several recent methods to predict peptide-MHC Class I binding affinities and a new method of our own design (MHCnuggets). We used a high-quality benchmark set of 51 alleles, which has been applied previously. The neural network methods NetMHC, NetMHCpan, MHCflurry, and MHCnuggets achieved similar best-in-class prediction performance in our testing, and of these methods MHCnuggets was significantly faster. MHCnuggets is a gated recurrent neural network, and the only method to our knowledge which can handle peptides of any length, without artificial lengthening and shortening. Seventeen alleles were problematic for all tested methods. Prediction difficulties could be explained by deficiencies in the training and testing examples in the benchmark, suggesting that biological differences in allele-specific binding properties are not as important as previously claimed. Advances in accuracy and speed of computational methods to predict peptide-MHC affinity are urgently needed. These methods will be at the core of pipelines to identify patients who will benefit from immunotherapy, based on tumor-derived somatic mutations. Machine learning methods, such as MHCnuggets, which efficiently handle peptides of any length will be increasingly important for the challenges of predicting immunogenic response for MHC Class II alleles.Author SummaryMachine learning methods are a popular approach for predicting whether a peptide will bind to Major Histocompatibility Complex (MHC) proteins, a critical step in activation of cytotoxic T-cells. The input to these methods is a peptide sequence and an MHC allele of interest, and the output is the predicted binding affinity. MHC Class I and II proteins bind peptides of 8-11 amino acids and 16-26 amino acids respectively. This has been an obstacle for machine learning, because the methods used to date can only handle fixed-length inputs. We show that a recently developed technique known as gated recurrent neural networks can handle peptides of variable length and predict peptide-MHC binding as well or better than existing methods, at substantially faster speeds. Our results have implications for the hundreds of MHC alleles that cannot be predicted with current methods.

scholarly journals An N-Acetylated Natural Ligand of Human Histocompatibility Leukocyte Antigen (Hla)-B39

2000 ◽  
Vol 191 (12) ◽  
pp. 2083-2092 ◽  
Author(s):  
Jesús Yagüe ◽  
Iñaki Alvarez ◽  
Didier Rognan ◽  
Manuel Ramos ◽  
Jesús Vázquez ◽  
...  
Keyword(s):  
Mhc Class I ◽  
Essential Feature ◽  
Peptide Binding ◽  
Class I ◽  
High Yield ◽  
Terminal Sequence ◽  
Leukocyte Antigen ◽  
Aminopeptidase M ◽  
Natural Ligand ◽  
Histocompatibility Complex

Sequence-independent interactions involving the free peptidic NH2 terminus are thought to be an essential feature of peptide binding to classical major histocompatibility complex (MHC) class I proteins. Challenging this paradigm, a natural Nα-acetylated ligand of human histocompatibility leukocyte antigen (HLA)-B39 was identified in this study. It matched the NH2-terminal sequence of two human helicases, was resistant to aminopeptidase M, and was produced with high yield from a synthetic 30 mer with the sequence of the putative parental protein by the 20S proteasome. This is the first reported natural ligand of classical MHC class I antigens that has a blocked NH2 terminus.

Ligand Design for Specific MHC Class I Molecules on the Cell Surface

2020 ◽  
Author(s):  
Xizheng Sun ◽  
Reika Tokunaga ◽  
Yoko Nagai ◽  
Ryo Miyahara ◽  
Akihiro Kishimura ◽  
...  
Keyword(s):  
Cell Surface ◽  
Mhc Class I ◽  
Targeted Delivery ◽  
Peptide Ligands ◽  
Class I ◽  
Class I Mhc ◽  
Mhc I ◽  
Histocompatibility Complex ◽  
High Binding Affinity ◽  
Mhc Class I Molecules

<p><a></a><a></a><a>We have validated that ligand peptides designed from antigen peptides could be used for targeting specific major histocompatibility complex class I (MHC-I)</a> molecules on cell surface. To design the ligand peptides, we used reported antigen peptides for each MHC-I molecule with high binding affinity. From the crystal structure of the peptide/MHC-I complexes, we determined a modifiable residue in the antigen peptides and replaced this residue with a lysine with an ε-amine group modified with functional molecules. The designed ligand peptides successfully bound to cells expressing the corresponding MHC-I molecules via exchange of peptides bound to the MHC-I. We demonstrated that the peptide ligands could be used to transport a protein or a liposome to cells expressing the corresponding MHC-I. The present strategy may be useful for targeted delivery to cells overexpressing MHC-I, which have been observed autoimmune diseases.</p>

Sign in / Sign up

Export Citation Format

Share Document