NIH Director's Pioneer Award: Antigenic Cartography

NIH 主任先锋奖：抗原制图

• 批准号: 7683825
• 负责人: Derek James Smith
• 金额: $ 52.73万
• 依托单位: UNIVERSITY OF CAMBRIDGE
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-30 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7683825
• 关键词: Affect; Antigenic Diversity; Antigens; Applied Research; Award; Binding; Bioinformatics; Biological Assay; Data; Enzyme-Linked Immunosorbent Assay; Epidemic; Epidemiology; Escape Mutant; Evolution; Eye; Hemagglutination; Hepatitis C virus; Human; Immune Sera; Immune response; Immunity; Infection; Influenza; Intervention; Laboratories; Methods; Phenotype; Population; Procedures; Property; Series; Signal Transduction; Time; United States National Institutes of Health; Update; Vaccination; Vaccines; Viral; Virus; base; genetic analysis; influenza virus vaccine; influenzavirus; novel; pandemic influenza; pathogen; pressure; success

Influenza viruses are classic examples of antigenically variable pathogens, and have a seemingly endless capacity to evade the immune response. For example, since the influenza A(H3N2) subtype entered the human population circa 1968 the vaccine against it has had to be updated 24 times to track the evolution of the viral quasispecies and to remain effective. Most of the bioinformatics methods for analyzing viral evolution are based on genetic analyses; however, it is the phenotypic (antigenic) properties of the virus that determine its success at escaping prior immunity and causing infection. Indeed, the antigenic data are the primary criteria for selecting the virus strain used in the influenza vaccine, and which are important for much basic and applied research on influenza. However, there is no reliable method to determine quantitatively antigenic differences. Antigenic differences are typically determined using some form of binding assay (for influenza virus, the hemagglutination inhibition assay, for other pathogens a neutralization assay, ELISA, etc.). In such assays, typically a panel of antisera is titrated against a series of antigens and the data are organized in tabular form and analyzed by eye. This has been the procedure for over 50 years. These data are difficult to interpret quantitatively, and sometimes even for experts give an inconsistent picture. The primary reason for this difficulty is that the data contain irregularities, or paradoxes. On such irregularity is that one antiserum might detect a difference between two antigens, while another will not. Another irregularity is that heterologous titers are sometimes higher than homologous titers. Furthermore, it is often difficult to compare data from different laboratories. These, along with other irregularities result in binding assay data only being considered reliable enough to judge large antigenic differences?in the case of influenza virus differences of sufficient magnitude that they necessitate an update of the vaccine strain. By only being able to judge gross differences among the thousands of influenza strains characterized each year, one misses opportunities to optimize the vaccine strain choice, to detect signals in the evolution of the viral quasispecies that could give advance warning of the necessity to update the vaccine, to understand the epidemiology of influenza, to judge how vaccination affects the viral evolution, and to devise novel intervention strategies which have the potential to fundamentally change our options to control epidemic and pandemic influenza. Influenza virus is one example of an antigencially variable pathogen; others include human immunodifficiency virus and hepatitis C virus. The degree of antigenic diversity will increase as interventions increase selection pressure to generate escape mutants, and the characterization of these phenotype differences will thus only increase in importance.

流感病毒是经典的 抗原可变病原体的例子，并且具有看似无限的能力 逃避免疫反应。例如，由于流感A（H3N2）亚型输入 大约1968年的人口，反对它的疫苗必须更新24次 跟踪病毒式准特性的演变并保持有效。大多数 用于分析病毒进化的生物信息学方法基于遗传分析。 但是，病毒的表型（抗原）特性决定了其成功 逃脱先前的免疫力并引起感染。确实，抗原数据是 选择流感疫苗中使用的病毒菌株的主要标准，它们是 对于有关流感的许多基本和应用研究很重要。但是，没有 确定定量抗原差异的可靠方法。 通常使用某种形式的结合测定法确定抗原差异（对于 其他病原体A的流感病毒，血凝抑制测定法 中和测定，ELISA等）。在这样的测定中，通常会滴定一个反塞拉 针对一系列抗原和数据以表格形式组织，并通过 眼睛。这是50多年来的程序。这些数据很难解释 定量，有时甚至对于专家而言，都会不一致。主要 造成这种困难的原因是数据包含不规则性或悖论。关于 不规则性是一种抗血清可能检测到两种抗原之间的差异，而 另一个不会。另一个不规则是异源滴度有时更高 而不是同源滴度。此外，通常很难比较来自不同的数据 实验室。这些，以及其他不规则性导致约束性测定数据仅为 被认为足够可靠以判断大抗原差异吗？ 足够大小的病毒差异，需要对疫苗进行更新 拉紧。仅仅能够判断成千上万的流感中的总体差异 每年都有特征的菌株，一个人错过了优化疫苗应变的机会 选择，检测病毒式准特性演变中的信号 警告更新疫苗，了解流感流行病学的必要性，以判断疫苗接种如何影响病毒进化并设计新颖 干预策略有可能从根本上改变我们的选择 控制流行性和大流行性流感。 流感病毒是抗本质可变病原体的一个例子。其他包括 人免疫缺陷病毒和丙型肝炎病毒。抗原多样性的程度 随着干预措施增加选择压力以产生逃生突变体，并且会增加 因此，这些表型差异的表征只会增加重要性。

项目成果

Antibody landscapes after influenza virus infection or vaccination.

• DOI: 10.1126/science.1256427
• 发表时间: 2014-11-21
• 期刊: Science (New York, N.Y.)
• 作者: Fonville JM;Wilks SH;James SL;Fox A;Ventresca M;Aban M;Xue L;Jones TC;Le NMH;Pham QT;Tran ND;Wong Y;Mosterin A;Katzelnick LC;Labonte D;Le TT;van der Net G;Skepner E;Russell CA;Kaplan TD;Rimmelzwaan GF;Masurel N;de Jong JC;Palache A;Beyer WEP;Le QM;Nguyen TH;Wertheim HFL;Hurt AC;Osterhaus ADME;Barr IG;Fouchier RAM;Horby PW;Smith DJ
• 通讯作者: Smith DJ

Antigenic and genetic characteristics of swine-origin 2009 A(H1N1) influenza viruses circulating in humans.

• DOI: 10.1126/science.1176225
• 发表时间: 2009-07-10
• 期刊: Science (New York, N.Y.)
• 作者: Garten RJ;Davis CT;Russell CA;Shu B;Lindstrom S;Balish A;Sessions WM;Xu X;Skepner E;Deyde V;Okomo-Adhiambo M;Gubareva L;Barnes J;Smith CB;Emery SL;Hillman MJ;Rivailler P;Smagala J;de Graaf M;Burke DF;Fouchier RA;Pappas C;Alpuche-Aranda CM;López-Gatell H;Olivera H;López I;Myers CA;Faix D;Blair PJ;Yu C;Keene KM;Dotson PD Jr;Boxrud D;Sambol AR;Abid SH;St George K;Bannerman T;Moore AL;Stringer DJ;Blevins P;Demmler-Harrison GJ;Ginsberg M;Kriner P;Waterman S;Smole S;Guevara HF;Belongia EA;Clark PA;Beatrice ST;Donis R;Katz J;Finelli L;Bridges CB;Shaw M;Jernigan DB;Uyeki TM;Smith DJ;Klimov AI;Cox NJ
• 通讯作者: Cox NJ