抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

/pdf/initial-sequencing-and-comparative-analysis-of-the-mouse-5a9n62pifj.pdf

Initial sequencing and comparative analysis of the mouse genome.

Immune checkpoint inhibitors, which unleash a patient’s own T cells to kill tumors, are revolutionizing cancer treatment. To unravel the genomic determinants of response to this therapy, we used whole-exome sequencing of non–small cell lung cancers treated with pembrolizumab, an antibody targeting programmed cell death-1 (PD-1). In two independent cohorts, higher nonsynonymous mutation burden in tumors was associated with improved objective response, durable clinical benefit, and progression-free survival. Efficacy also correlated with the molecular smoking signature, higher neoantigen burden, and DNA repair pathway mutations; each factor was also associated with mutation burden. In one responder, neoantigen-specific CD8+ T cell responses paralleled tumor regression, suggesting that anti–PD-1 therapy enhances neoantigen-specific T cell reactivity. Our results suggest that the genomic landscape of lung cancers shapes response to anti–PD-1 therapy.

https://science.sciencemag.org/content/sci/early/2015/03/11/science.aaa1348.full.pdf

Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

/pdf/identification-and-analysis-of-functional-elements-in-1-of-2o640l8ikl.pdf

Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project

“Outcomes Research” in molecular immunology is driven by faster, cheaper and increasingly sophisticated methods such as miniaturisation, automation, and data integration. The latter is a prerequisite for efficient information analysis, knowledge discovery, and eventually research planning. The data warehousing approach has been successfully applied for managing clinical data [1], but rarely in exploratory biological research. In order to clarify aspects of data warehousing in molecular immunology we constructed a small model database of swine major histocompatibility antigens (swine MHC or SLA) using warehousing principles.

SLAD-An Integrated Swine MHC Database:A Case Study of Data Warehousing in Molecular Immunology

Biological research frequently requires specialist databases to support in-depth analysis about specific subjects. With the rapid growth of biological sequences in public domain data sources, it is difficult to keep these databases current with the sources. Simple queries formulated to retrieve relevant sequences typically return a large number of false matches and thus demanding manual filtration. In this paper, we propose a novel methodology that can support automatic incremental updating of specialist databases. Complex queries for incremental updating of relevant sequences are learned using Association Rule Mining (ARM), resulting in a significant reduction in false positive matches. This is the first time ARM is used in formulating descriptive queries for the purpose of incremental maintenance of specialised biological databases. We have implemented and tested our methodology on two real-world databases. Our experiments conclusively show that the methodology guarantees an F-score of up to 80% in detecting new sequences for these two databases.

Incremental maintenance of biological databases using association rule mining

/pdf/editorial-immune-system-modeling-and-related-pathologies-nugopb55gx.pdf

Editorial Immune System Modeling and Related Pathologies

Computational vaccinology is a developing discipline. To become a standard component in vaccine development, it requires accurate and broadly applicable models of wet-lab experiments. We developed prediction models based on a novel data representation of peptide/MHC interaction and support vector machines (SVM) for prediction of peptides that promiscuously bind to multiple human leukocyte antigen (HLA) alleles belonging to HLA-B7 supertype. 10-fold cross-validation results showed that the area under the receiver operating curve (Aroc) of SVM models is above 0.90. Blind testing results showed that the average Aroc of SVM models is 0.84. A learning approach based on information theory, termed Information Learning Approach, was used for feature selection. Several amino acid positions with high information content have been identified in input 9mer peptides and HLA alleles and were used as input features to SVM. They are position 1, 2, 4, 5, 7, 8, 9 in 9mer peptides and position 45 and 97 in HLA-B7 molecules. Prediction accuracy was improved after feature selection. These positions cover the anchor positions of HLA-B7 alleles, which have important biological roles for successful biding of relevant peptides.

Computational Models for Identifying Promiscuous HLA-B7 Binders based on Information Theory and Support Vector Machine

Identification of T-cell epitopes (parts of antigenic proteins to which the T-cells receptor respond) is important in the development of vaccines and immunotherapeutics. We developed MULTIPRED1 (http://antigen.i2r.a-star.edu.sg/multipred1/), a Web-based computational system for prediction of peptides (protein fragments) that bind multiple related human leukocyte antigen (HLA) molecules (the human major histocompatibility complex - MHC molecules). In this paper, the performance of MULTIPRED1 in predicting individual 9-mer binders to HLA-A2 and A3 molecules was compared with five other publicly available prediction tools, SFYPEITHI, BIMAS, SMM, RANKPEP and SVMHC. The results show that MULTIPRED1 is both sensitive and specific for prediction of binders to individual HLA alleles and demonstrates comparable accuracy as those of other prediction tools. Majority voting was applied to combine the strength of the three prediction models of MULTIPRED1 and results indicate that better prediction performance can be achieved. MULTIPRED1 is useful in the selection of key antigenic regions to minimize the number of experiments required for mapping of promiscuous T-cell epitopes.

Vladimir Brusic

Papers

SLAD-An Integrated Swine MHC Database:A Case Study of Data Warehousing in Molecular Immunology

Incremental maintenance of biological databases using association rule mining

Editorial Immune System Modeling and Related Pathologies

Computational Models for Identifying Promiscuous HLA-B7 Binders based on Information Theory and Support Vector Machine

Performance Evaluation of MULTIEPD1 on Prediction of MHC Class I Binders