Glycan side chains on naturally presented MHC class II ligands

The molecular characterization of unknown naturally presented major histocompatibility complex (MHC) class II glycopeptides carrying complex glycans has so far not been achieved, reflecting the different fragmentation characteristics of sugars and peptides in mass spectrometric analysis. Human leukocyte antigen (HLA)-DR-bound peptides were isolated by affinity purification, separated via high performance liquid chromatography and analyzed by matrix-assisted laser desorption/ionization and electrospray ionization mass spectrometry. We were able to identify two naturally processed MHC class II ligands, CD53(122-136) and CD53(121-136), carrying complex N-linked glycan side chains by a combination of in-source and collision-induced fragmentation on a quadrupole time-of-flight tandem mass spectrometer.     

Molecular cloning and polymorphism of major histocompatibility complex class I genes from grass carp (Ctenophayngodon idellus)

In order to clarify the molecular sequences,allelic polymorphism and the tertiary structure of grass carp (Ctenophayngodon idellus) MHC class I,and to further study their relationship with disease resistances,grass carp MHC class I gene (Ctid-MHC I) was cloned from a cDNA library and the allelic polymorphism in the population was investigated.The results showed that most of the variations exist in the peptide-binding domain (PBD) and high polymorphism was identified in the Ctid-MHC I allelic genes from 12 individuals.Based on the genetic distance,Ctid-MHC class I can be classified into 6 types (from Ctid-MHC I-UA to Ctid-MHC I-UF) which were subdivided into 9 lineages (from A to I).Comparison of the Ctid-MHC I among animals and humans showed that the key amino acids of the peptide binding sites are conserved.Analysis of the tertiary structure of the PBD between Grass carp and human crystallographic data of HLA-A2,the variation with insertion or deletion was found in eight regions (A～H).The phylogenetic tree of MHC class I indicates the evolution of MHC class I among grass carp,fish,amphibian,birds,higher vertebrates and humans.     

Using random forest to classify T-cell epitopes based on amino acid properties and molecular features

T-lymphocyte (T-cell) is a very important component in human immune system. T-cell epitopes can be used for the accurately monitoring the immune responses which activation by major histocompatibility complex (MHC), and rationally designing vaccines. Therefore, accurate prediction of T-cell epitopes is crucial for vaccine development and clinical immunology. In current study, two types peptide features, i.e., amino acid properties and chemical molecular features were used for the T-cell epitopes peptide representation. Based on these features, random forest (RF) algorithm, a powerful machine learning algorithm, was used to classify T-cell epitopes and non-T-cell epitopes. The classification accuracy, sensitivity, specificity, Matthews correlation coefficient (MCC), and area under the curve (AUC) values for proposed method are 97.54%, 97.22%, 97.60%, 0.9193, and 0.9868, respectively. These results indicate that current method based on the combined features and RF is effective for T-cell epitopes prediction.     

干扰素-γ对母胎界面免疫调控的影响

人类和其他哺乳动物的妊娠过程是自然界中存在的一种同种半异体移植免疫耐受模型，近来的研究发现母胎界面上表达的主要组织相容性复合体（MHC）分子有重要作用，经典的和非经典的MHC I/II类抗原表达在妊娠过程中是时空动态变化的，维持妊娠的正常进行.生理剂量的干扰素-γ（IFNγ）是妊娠必需的细胞因子之一，而超过生理剂量的IFNγ则会直接导致流产.IFNγ影响妊娠的机制是多方面的，主要通过调节母胎界面MHC抗原的表达.与此同时，IFNγ下调在妊娠过程中发挥多种生物学功能的细胞因子IL-1β和TGFβ1的表达；促进母胎界面细胞凋亡水平；抑制孕酮的分泌.超生理剂量IFNγ可通过这些作用最终导致母胎界面局部免疫微环境调控失衡，妊娠失败.文中着重介绍近年来母胎界面免疫调控及IFNγ对其作用机制的研究进展.     

卡托普利和肾切除对肾性高血压大鼠左室心肌MHC基因转录变化的影响

用二肾一夹（２ＫＩＣ）肾性高血压大鼠模型，探讨心肌肥厚发生和逆转以及肌球蛋白重链（ｍｙｏｓｉｎｈｅａｖｙｃｈａｉｎ，ＭＨＣ）基因表达的改变。结果表明：１）２ＫＩＣ肾性高血压大鼠术后第２～１２周，动脉血压持续升高、左室重量／体重（ＬＶＷ／ＢＷ）明显升高、左心室α－ＭＨＣ基因表达明显减弱、β－ＭＨＣ基因表达明显增强；２）在术后第４周给予血管紧张素转换酶抑制剂卡托普利和术后第８周切除肾动脉狭窄侧肾脏可使２ＫＩＣ肾性高血压大鼠动脉血压下降、左心室肥厚发生逆转、抑制左心室α－ＭＨＣ基因表达减弱和β－ＮＨＣ基因表达增强。这些结果提示在２Ｋ１Ｃ肾性高血压中，动脉血压升高是左心室肥厚、左心室肌球蛋白ＭＨＣ基因表型转换的重要因素；肾素———血管紧张素系统可能参与２ＫＩＣ肾性高血压过程中的心肌肥厚和ＭＨＣ基因表型的转移。     

SVM and SVR-based MHC-binding prediction using a mathematical presentation of peptide sequences

At present, there are a number of methods for the prediction of T-cell epitopes and major histocompatibility complex (MHC)-binding peptides. Despite numerous methods for predicting T-cell epitopes, there still exist limitations that affect the reliability of prevailing methods. For this reason, the development of models with high accuracy are crucial. An accurate prediction of the peptides that bind to specific major histocompatibility complex class I and II (MHC-I and MHC-II) molecules is important for an understanding of the functioning of the immune system and the development of peptide-based vaccines. Peptide binding is the most selective step in identifying T-cell epitopes. In this paper, we present a new approach to predicting MHC-binding ligands that takes into account new weighting schemes for position-based amino acid frequencies, BLOSUM and VOGG substitution of amino acids, and the physicochemical and molecular properties of amino acids. We have made models for quantitatively and qualitatively predicting MHC-binding ligands. Our models are based on two machine learning methods support vector machine (SVM) and support vector regression (SVR), where our models have used for feature selection, several different encoding and weighting schemes for peptides. The resulting models showed comparable, and in some cases better, performance than the best existing predictors. The obtained results indicate that the physicochemical and molecular properties of amino acids (AA) contribute significantly to the peptide-binding affinity.     

In silico designing breast cancer peptide vaccine for binding to MHC class I and II: A molecular docking study

Antigenic peptides or cancer peptide vaccines can be directly delivered to cancer patients to produce immunologic responses against cancer cells. Specifically, designed peptides can associate with Major Histocompatibility Complex (MHC) class I or II molecules on the cell surface of antigen presenting cells activating anti-tumor effector mechanisms by triggering helper T cell (Th) or cytotoxic T cells (CTL). In general, high binding to MHCs approximately correlates with in vivo immunogenicity. Consequently, a molecular docking technique was run on a library of novel discontinuous peptides predicted by PEPOP from Human epidermal growth factor receptor 2 (HER2 ECD) subdomain III. This technique is expected to improve the prediction accuracy in order to identify the best MHC class I and II binder peptides. Molecular docking analysis through GOLD identified the peptide 1412 as the best MHC binder peptide to both MHC class I and II molecules used in the study. The GOLD results predicted HLA-DR4, HLA-DP2 and TCR as the most often targeted receptors by the peptide 1412. These findings, based on bioinformatics analyses, can be exploited in further experimental analyses in vaccine design and cancer therapy to find possible proper approaches providing beneficial effects.     

人类及部分实验动物MHC-DRB3.2基因核苷酸序列同源性分析

目的研究人类及部分实验动物DRB3.2基因核苷酸序列的同源性。方法利用PCR技术扩增得到牛的DRB3.2基因片段,并测定其核苷酸序列;从GenBank中下载人类、猕猴、绵羊、山羊、猪的相应基因片段;利用DNAMAN软件进行碱基组成分析、同源性分析和构建分子进化树。结果所分析的物种该基因片段大小为267bp,没有发现碱基的缺失以及插入现象;A、T、G、C四种碱基以及G+C的含量在不同物种之间相差较小。就某种动物来说,G的含量最高,T的含量最低,G+C的含量要明显高于A+T含量;人类与猕猴、绵羊、山羊、牛、猪的同源性分别为91.8%、82.8%、82.4%、81.3%、81.6%。结论不同物种MHC-DRB3.2基因核苷酸序列的同源性都比较高;在研究人类有些疾病时,猕猴是其它实验动物不可替代的;DRB3.2基因是研究生物进化和系统发育分析的一个理想遗传标记。     

脑内免疫炎症的发生机制

中枢神经系统神经元退行性变过程中表达主要组织相容性分子、黏附分子和补体受体,并产生多种细胞因子,从而引发脑内的免疫炎症反应。