The Role of Genomics in Tracking the Evolution of Influenza A Virus

Influenza A virus causes annual epidemics and occasional pandemics of short-term respiratory infections associated with considerable morbidity and mortality. The pandemics occur when new human-transmissible viruses that have the major surface protein of influenza A viruses from other host species are introduced into the human population. Between such rare events, the evolution of influenza is shaped by antigenic drift: the accumulation of mutations that result in changes in exposed regions of the viral surface proteins. Antigenic drift makes the virus less susceptible to immediate neutralization by the immune system in individuals who have had a previous influenza infection or vaccination. A biannual reevaluation of the vaccine composition is essential to maintain its effectiveness due to this immune escape. The study of influenza genomes is key to this endeavor, increasing our understanding of antigenic drift and enhancing the accuracy of vaccine strain selection. Recent large-scale genome sequencing and antigenic typing has considerably improved our understanding of influenza evolution: epidemics around the globe are seeded from a reservoir in East-Southeast Asia with year-round prevalence of influenza viruses; antigenically similar strains predominate in epidemics worldwide for several years before being replaced by a new antigenic cluster of strains. Future in-depth studies of the influenza reservoir, along with large-scale data mining of genomic resources and the integration of epidemiological, genomic, and antigenic data, should enhance our understanding of antigenic drift and improve the detection and control of antigenically novel emerging strains

Inference of Genotype–Phenotype Relationships in the Antigenic Evolution of Human Influenza A (H3N2) Viruses

Distinguishing mutations that determine an organism's phenotype from (near-) neutral ‘hitchhikers’ is a fundamental challenge in genome research, and is relevant for numerous medical and biotechnological applications. For human influenza viruses, recognizing changes in the antigenic phenotype and a strains' capability to evade pre-existing host immunity is important for the production of efficient vaccines. We have developed a method for inferring ‘antigenic trees’ for the major viral surface protein hemagglutinin. In the antigenic tree, antigenic weights are assigned to all tree branches, which allows us to resolve the antigenic impact of the associated amino acid changes. Our technique predicted antigenic distances with comparable accuracy to antigenic cartography. Additionally, it identified both known and novel sites, and amino acid changes with antigenic impact in the evolution of influenza A (H3N2) viruses from 1968 to 2003. The technique can also be applied for inference of ‘phenotype trees’ and genotype–phenotype relationships from other types of pairwise phenotype distances

The impact of seasonal and year-round transmission regimes on the evolution of influenza A virus

Punctuated antigenic change is believed to be a key element in the evolution of influenza A; clusters of antigenically similar strains predominate worldwide for several years until an antigenically distant mutant emerges and instigates a selective sweep. It is thought that a region of East–Southeast Asia with year-round transmission acts as a source of antigenic diversity for influenza A and seasonal epidemics in temperate regions make little contribution to antigenic evolution. We use a mathematical model to examine how different transmission regimes affect the evolutionary dynamics of influenza over the lifespan of an antigenic cluster. Our model indicates that, in non-seasonal regions, mutants that cause significant outbreaks appear before the peak of the wild-type epidemic. A relatively large proportion of these mutants spread globally. In seasonal regions, mutants that cause significant local outbreaks appear each year before the seasonal peak of the wild-type epidemic, but only a small proportion spread globally. The potential for global spread is strongly influenced by the intensity of non-seasonal circulation and coupling between non-seasonal and seasonal regions. Results are similar if mutations are neutral, or confer a weak to moderate antigenic advantage. However, there is a threshold antigenic advantage, depending on the non-seasonal transmission intensity, beyond which mutants can escape herd immunity in the non-seasonal region and there is a global explosion in diversity. We conclude that non-seasonal transmission regions are fundamental to the generation and maintenance of influenza diversity owing to their epidemiology. More extensive sampling of viral diversity in such regions could facilitate earlier identification of antigenically novel strains and extend the critical window for vaccine development

The PhyloPythiaS Web Server for Taxonomic Assignment of Metagenome Sequences

Metagenome sequencing is becoming common and there is an increasing need for easily accessible tools for data analysis. An essential step is the taxonomic classification of sequence fragments. We describe a web server for the taxonomic assignment of metagenome sequences with PhyloPythiaS. PhyloPythiaS is a fast and accurate sequence composition-based classifier that utilizes the hierarchical relationships between clades. Taxonomic assignments with the web server can be made with a generic model, or with sample-specific models that users can specify and create. Several interactive visualization modes and multiple download formats allow quick and convenient analysis and downstream processing of taxonomic assignments. Here, we demonstrate usage of our web server by taxonomic assignment of metagenome samples from an acidophilic biofilm community of an acid mine and of a microbial community from cow rumen

Allele dynamics plots for the study of evolutionary dynamics in viral populations

Phylodynamic techniques combine epidemiological and genetic information to analyze the evolutionary and spatiotemporal dynamics of rapidly evolving pathogens, such as influenza A or human immunodeficiency viruses. We introduce ‘allele dynamics plots’ (AD plots) as a method for visualizing the evolutionary dynamics of a gene in a population. Using AD plots, we propose how to identify the alleles that are likely to be subject to directional selection. We analyze the method’s merits with a detailed study of the evolutionary dynamics of seasonal influenza A viruses. AD plots for the major surface protein of seasonal influenza A (H3N2) and the 2009 swine-origin influenza A (H1N1) viruses show the succession of substitutions that became fixed in the evolution of the two viral populations. They also allow the early identification of those viral strains that later rise to predominance, which is important for the problem of vaccine strain selection. In summary, we describe a technique that reveals the evolutionary dynamics of a rapidly evolving population and allows us to identify alleles and associated genetic changes that might be under directional selection. The method can be applied for the study of influenza A viruses and other rapidly evolving species or viruses

Gene finding and the evaluation of synonymous codon usage features in microbial genomes

McHardy AC. Gene finding and the evaluation of synonymous codon usage features in microbial genomes. Bielefeld (Germany): Bielefeld University; 2004.Diese Arbeit befasst sich mit der Vorhersage von Genen, von Genexpressionsraten und der Detektion und Charakterisierung von horizontal transferierten Genregionen in mikrobiellen Genomen. Diese Themen sind sowohl für die Annotation als auch für weiterführende, experimentelle Analysen eines Organismus von Bedeutung. Teile der Arbeit wurden bereits in verschiedenen Fachzeitschriften veröffentlicht. Der Inhalt von Kapitel 1 wird in diesem Jahr in Bioinformatics erscheinen, Kapitel 3 wurde in der ersten Ausgabe von Proteomics in 2004 veröffentlicht. Die Implementierung einer Genvorhersagekomponente für das Annotationssystem GenDB wird in der Veröffentlichung über das Annotationssystem in Nucleic Acids Research (April 2003) beschrieben. Im Folgenden werden die Ziele und Themen dieser Arbeit genauer beschrieben. Im ersten Kapitel wird die Entwicklung von Genvorhersage-Strategien für mikrobielle Genome, basierend auf den häufig verwendeten Programmen Glimmer und Critica, beschrieben. Aufgrund der Vielzahl von laufenden Genomprojekten verschiedener Organismen wird es zunehmend wichtiger, ein performantes Verfahren für diese Aufgabe zu haben. Hierzu wurde ursprünglich die Performanz der beiden Programme auf einem Datensatz von 114 prokaryotischen Genomsequenzen evaluiert. Anschließend wurden kombinierte Vorhersagestrategien entwickelt, die eine signifikante Performanz-Verbesserung aufweisen. Dies ist besonders für GC-reiche Genome der Fall. Die Methoden werden zur Zeit bereits in mehreren mikrobiellen Genomprojekten angewandt. Der zweite Teil der Arbeit beschäftigt sich mit der Evaluierung des synonymen Codongebrauchs in den Kodierregionen prokaryotischer Genome. Zur Klassifikation anhand von Eigenschaften des Codongebrauchs wird ein neues, auf log-odds ratio scores basierendes Verfahren eingeführt, welches einige vorteilhafte Eigenschaften besitzt. In Kapitel 2 wird das Verfahren und dessen Implementierung in dem Program CoBias beschrieben. In Kapitel 3 wird das Verfahren angewendet, um Genexpressionsraten anhand von Expressionlevel-abhängigen Eigenschaften des Codongebrauchs vorherzusagen. Durch einen Vergleich mit Daten aus zwei Proteomstudien wird die implizite Annahme der Vorgehensweise untersucht und bestätigt. Es wird gezeigt, wie die Ergebnisse der Methode sich verwenden lassen, um die 'in silico' Simulation von 2-dimensionalen Gelelektrophoreseexperimenten zu verbessern. Im vierten Kapitel wird das Verfahren angewendet, um, basierend auf Unterschieden im synonymen Codongebrauch zwischen mikrobiellen Genomen, horizontal transferierte Gene zu erkennen und einen möglichen Donor für diese vorherzusagen. Die Vorhersage eines Donors ist eine Neuerung gegenüber anderen Methoden, die horizontal transferierte Gene anhand ihrer atypischen Sequenz-Zusammensetzung detektierten. Eine Evaluation des Ansatzes wird für das Genom des hyperthermophilen Bakteriums Thermotoga maritima durchgeführt, welches Genregionen von vermutlich archaebakteriellem Ursprung enthält. Die mit der neuen Methode gefundenen Ergebnisse stehen im Einklang mit den Ergebnissen von früheren phylogenetischen und strukturellen Analysen des Genomes und liefern weiteres, unabhängiges Beweismaterial für den archaebakteriellen Ursprung von Teilen des T. maritima Genoms.This work deals with the prediction of genes, gene expression rates and the detection and characterization of horizontally aquired gene regions in microbial genomes. These topics are of relevance for genome annotation and for further experimental studies of the organism. The content of chapter 1 will appear in Bionformatics later this year, chapter 3 has been published in the first issue of Proteomics in 2004. The implementation of the gene prediction component of the GenDB genome annotation system (chapter 5) is described in the publication on GenDB which appeared in Nucleic Acids Research in April, 2003. In the following, the aims and topics of this work are explained in more detail. Chapter 1 describes the development of joint gene finding strategies for microbial genomes which combine the strengths of the commonly used Glimmer and Critica programs. A large number of genome projects have either recently been finished or are currently underway, and it is becoming increasingly important to have performant methods for this task. Initially, the gene finding performance of the two programs was evaluated for a data set of 114 prokaryotic genome sequences belonging to a wide variety of microbial organisms. Subsequently, joint application strategies were optimized in performance, using different parameters with relevance to the gene finding problem. The resulting combined methods are significantly improved in performance, especially for GC-rich genomes. They are already being applied in several microbial genome projects. The second part focuses on the evaluation of synonymous codon usage features of prokaryotic coding sequences. For classification based on such features, a novel method of log-odds ratio scoring is introduced, which has several favorable properties. Chapter 2 contains a description of the method and its implementation in the CoBias program. In chapter 3, the novel method is applied to the prediction of highly expressed genes and for estimation of gene expression levels. The implicit assumption is that expression level-dependent features in codon usage can be taken as estimates of protein expression rates. This is supported by a comparison with data on protein abundance from the Escherichia coli and Bacillus subtilis exponential growth phase. It is finally demonstrated how the results can be used for 'predictive proteomics' - to improve the in silico simulation of 2-dimensional gel electrophoretic experiments. In chapter 4, the method is used for the detection of horizontally transferred genes contained in contemporary microbial genomes and the inference of a putative donor species. The method allows the inference of a potential donor genome based on genome-specific sequence properties, which is an innovation compared to existing methods. An in detail evaluation is performed for the genome of bacterial hyperthermophile Thermotoga maritima, which presumably contains regions of archaebacterial origin. The results found with the new method agree well with the results of previous phylogenetic and structural analyses of the genome and give additional, independent support for the archaebacterial origin of parts of the T. maritima genome

Generation of genetic diversity and antigenic drift in the evolution of human influenza A viruses.

<p>Blue and yellow viruses depict two antigenically similar strains of the same subtype circulating in the human population. The genetic diversity of the circulating viral population increases through mutation and reasssortment. Single white arrows indicate relationships between ancestral and descendant viruses. White marks on the segments indicate neutral mutations and red marks indicate mutations that affect the antigenic regions of the surface proteins. Incoming pairs of orange arrows indicate the generation of reassortants with segments from two different ancestral viruses. As these viruses continue to circulate, immunity against them builds up in the host population, represented here by the narrowing of the bottleneck. In parallel, viruses with mutations affecting the antigenic regions of the surface proteins accumulate in the viral population. At some point a novel antigenic drift variant, indicated by a red colored virus, which is less affected by immunity in the human population, is generated. This variant is able to cause widespread infection and founds a new cluster of antigenically similar strains.</p

Schematic drawing demonstrating the up/down tree concept.

<p>For the two taxa <i>t₂</i> and <i>t₄</i>, no antiserum is present, and thus, <i>b₃</i> and <i>b₆</i> only have up-weights. A path from <i>t₁</i> to <i>t₃</i> would use the up-weights of branch <i>b₁</i> and <i>b₂</i>, and the down-weights of branch <i>b₄</i> and b₅. Similarly, the path from <i>t₂</i> to <i>t₁</i> would use the up-weight of branch <i>b₃</i> and the down-weight of branch <i>b₂</i>. Notably, the path from <i>t₁</i> to <i>t₁</i>, namely the antigenic distance from antigen <i>t₁</i> to the antiserum raised against strain <i>t₁</i>, would use the up-weight and the down-weight of branch <i>b₁</i>.</p

Internal branches with high average antigenic weights (≥1.0 antigenic units) and according antigenic types in comparison to antigenic clusters identified by antigenic cartography (branches leading to three or less isolates are excluded).

<p>Branch amino acid changes indicate the corresponding branches, where changes in bold were also found by Smith <i>et al.</i> (2004), and weights give the respective up, down and average branch weights. Multiple branches that can be mapped to a single antigenic type are separated by dashed lines. Additional amino acid changes indicate branches that carry further mutations found to be cluster transition substitutions by Smith <i>et al.</i> (2004). For some branches, the down-weight was not defined, as no antiserum was in the respective subtree. Branches that can be mapped to multiple type transitions are shown at the first mapping only. Smith <i>et al.</i> (2004) present average distances between consecutive antigenic clusters, whereas average antigenic branch weights give a minimum distance between consecutive antigenic types. Note that on branches with multiple changes not all changes have to contribute to the antigenic weight, though their individual impacts could not be resolved with the dataset (unsampled viral isolates).</p