Bioinformatics technologies for the analysis of antigenic evolution of influenza viruses

Human influenza viruses mutate from time to time, causing annual epidemics worldwide. The strong immune pressure in the human population selects a new variant every year, and the antigenic change is one of the primary reasons why vaccination is not a perfect measure to control seasonal influenza. Thus prediction of antigenic change of influenza A virus has been one of the major public health goals. In this review bioinformatics technologies that have been developed to achieve this goal were summarized.     

The evolutionary dynamics of receptor binding avidity in influenza A: a mathematical model for a new antigenic drift hypothesis

The most salient feature of influenza evolution in humans is its antigenic drift. This process is characterized by structural changes in the virus''s B-cell epitopes and ultimately results in the ability of the virus to evade immune recognition and thereby reinfect previously infected hosts. Until recently, amino acid substitutions in epitope regions of the viral haemagglutinin were thought to be positively selected for their ability to reduce antibody binding and therefore were thought to be responsible for driving antigenic drift. However, a recent hypothesis put forward by Hensley and co-workers posits that cellular receptor binding avidity is the dominant phenotype under selection, with antigenic drift being a side effect of these binding avidity changes. Here, we present a mathematical formulation of this new antigenic drift model and use it to show how rates of antigenic drift depend on epidemiological parameters. We further use the model to evaluate how two different vaccination strategies can impact antigenic drift rates and ultimately disease incidence levels. Finally, we discuss the assumptions present in the model formulation, predictions of the model, and future work that needs to be done to determine the consistency of this hypothesis with known patterns of influenza''s genetic and antigenic evolution.     

Evidence for N-glycan shielding of antigenic sites during evolution of human influenza A virus hemagglutinin

After the emergence of influenza A viruses in the human population, the number of N-glycosylation sites (NGS) in the globular head region of hemagglutinin (HA) has increased continuously for several decades. It has been speculated that the addition of NGS to the globular head region of HA has conferred selective advantages to the virus by preventing the binding of antibodies (Ab) to antigenic sites (AS). Here, the effect of N-glycosylation on the binding of Ab to AS in human influenza A virus subtype H3N2 (A/H3N2) was examined by inferring natural selection at AS and other sites (NAS) that are located close to and distantly from the NGS in the three-dimensional structure of HA through a comparison of the rates of synonymous (d(S)) and nonsynonymous (d(N)) substitutions. When positions 63, 122, 126, 133, 144, and 246 in the globular head region of HA were non-NGS, the d(N)/d(S) was >1 and positive selection was detected at the AS located near these positions. However, the d(N)/d(S) value decreased and the evidence of positive selection disappeared when these positions became NGS. In contrast, d(N)/d(S) at the AS distantly located from the positions mentioned above and at the NAS of any location were generally <1 and did not decrease when these positions changed from non-NGS to NGS. These results suggest that the attachment of N-glycans to the NGS in the globular head region of HA prevented the binding of Ab to AS in the evolutionary history of human A/H3N2 virus.     

Subtype- and antigenic site-specific differences in biophysical influences on evolution of influenza virus hemagglutinin

ABSTRACT: BACKGROUND: Influenza virus undergoes rapid evolution by both antigenic shift and antigenic drift. Antibodies, particularly those binding near the receptor-binding site of hemagglutinin (HA) or the neuraminidase (NA) active site, are thought to be the primary defense against influenza infection, and mutations in antibody binding sites can reduce or eliminate antibody binding. The binding of antibodies to their cognate antigens is governed by such biophysical properties of the interacting surfaces as shape, non-polar and polar surface area, and charge. Methods: To understand forces shaping evolution of influenza virus, we have examined HA sequences of human influenza A and B viruses, assigning each amino acid values reflecting total accessible surface area, non-polar and polar surface area, and net charge due to the side chain. Changes in each of these values between neighboring sequences were calculated for each residue and mapped onto the crystal structures. Results: Areas of HA showing the highest frequency of changes agreed well with previously identified antigenic sites in H3 and H1 HAs, and allowed us to propose more detailed antigenic maps and novel antigenic sites for H1 and influenza B HA. Changes in biophysical properties differed between HAs of different subtypes, and between different antigenic sites of the same HA. For H1, statistically significant differences in several biophysical quantities compared to residues lying outside antigenic sites were seen for some antigenic sites but not others. Influenza B antigenic sites all show statistically significant differences in biophysical quantities for all antigenic sites, whereas no statistically significant differences in biophysical quantities were seen for any antigenic site is seen for H3. In many cases, residues previously shown to be under positive selection at the genetic level also undergo rapid change in biophysical properties. Conclusions: The biophysical consequences of amino acid changes introduced by antigenic drift vary from subtype to subtype, and between different antigenic sites. This suggests that the significance of antibody binding in selecting new variants may also be variable for different antigenic sites and influenza subtypes.     

A computational framework for influenza antigenic cartography

Influenza viruses have been responsible for large losses of lives around the world and continue to present a great public health challenge. Antigenic characterization based on hemagglutination inhibition (HI) assay is one of the routine procedures for influenza vaccine strain selection. However, HI assay is only a crude experiment reflecting the antigenic correlations among testing antigens (viruses) and reference antisera (antibodies). Moreover, antigenic characterization is usually based on more than one HI dataset. The combination of multiple datasets results in an incomplete HI matrix with many unobserved entries. This paper proposes a new computational framework for constructing an influenza antigenic cartography from this incomplete matrix, which we refer to as Matrix Completion-Multidimensional Scaling (MC-MDS). In this approach, we first reconstruct the HI matrices with viruses and antibodies using low-rank matrix completion, and then generate the two-dimensional antigenic cartography using multidimensional scaling. Moreover, for influenza HI tables with herd immunity effect (such as those from Human influenza viruses), we propose a temporal model to reduce the inherent temporal bias of HI tables caused by herd immunity. By applying our method in HI datasets containing H3N2 influenza A viruses isolated from 1968 to 2003, we identified eleven clusters of antigenic variants, representing all major antigenic drift events in these 36 years. Our results showed that both the completed HI matrix and the antigenic cartography obtained via MC-MDS are useful in identifying influenza antigenic variants and thus can be used to facilitate influenza vaccine strain selection. The webserver is available at http://sysbio.cvm.msstate.edu/AntigenMap.     

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.     

Molecular epidemiology of A/H3N2 and A/H1N1 influenza virus during a single epidemic season in the United States

To determine the spatial and temporal dynamics of influenza A virus during a single epidemic, we examined whole-genome sequences of 284 A/H1N1 and 69 A/H3N2 viruses collected across the continental United States during the 2006-2007 influenza season, representing the largest study of its kind undertaken to date. A phylogenetic analysis revealed that multiple clades of both A/H1N1 and A/H3N2 entered and co-circulated in the United States during this season, even in localities that are distant from major metropolitan areas, and with no clear pattern of spatial spread. In addition, co-circulating clades of the same subtype exchanged genome segments through reassortment, producing both a minor clade of A/H3N2 viruses that appears to have re-acquired sensitivity to the adamantane class of antiviral drugs, as well as a likely antigenically distinct A/H1N1 clade that became globally dominant following this season. Overall, the co-circulation of multiple viral clades during the 2006-2007 epidemic season revealed patterns of spatial spread that are far more complex than observed previously, and suggests a major role for both migration and reassortment in shaping the epidemiological dynamics of human influenza A virus.     

Polymorphism and evolution of influenza A virus genes

The nucleotide sequences of four genes of the influenza A virus(nonstructural protein, matrix protein, and a few subtypes of hemagglutininand neuraminidase) are compiled for a large number of strains isolated fromvarious locations and years, and the evolutionary relationship of thesequences is investigated. It is shown that all of these genes or subtypesare highly polymorphic and that the polymorphic sequences (alleles) aresubject to rapid turnover in the population, their average age being muchless than that of higher organisms. Phylogenetic analysis suggests thatmost polymorphic sequences within a subtype or a gene appeared during thelast 80 years and that the divergence among the subtypes of hemagglutiningenes might have occurred during the last 300 years. The high degree ofpolymorphism in this RNA virus is caused by an extremely high rate ofmutation, estimated to be 0.01/nucleotide site/year. Despite the high rateof mutation, most influenza virus genes are apparently subject to purifyingselection, and the rate of nucleotide substitution is substantially lowerthan the mutation rate. There is considerable variation in the substitutionrate among different genes, and the rate seems to be lower in nonhumanviral strains than in human strains. The difference might be responsiblefor the so-called freezing effect in some viral strains.     

Directionality in the evolution of influenza A haemagglutinin

The evolution of haemagglutinin (HA), an important influenza virus antigen, has been the subject of intensive research for more than two decades. Many characteristics of HA's sequence evolution are captured by standard Markov chain substitution models. Such models assign equal fitness to all accessible amino acids at a site. We show, however, that such models strongly underestimate the number of homoplastic amino acid substitutions during the course of HA's evolution, i.e. substitutions that repeatedly give rise to the same amino acid at a site. We develop statistics to detect individual homoplastic events and find that they preferentially occur at positively selected epitopic sites. Our results suggest that the evolution of the influenza A HA, including evolution by positive selection, is strongly affected by the long-term site-specific preferences for individual amino acids.     

Understanding original antigenic sin in influenza with a dynamical system

Original antigenic sin is the phenomenon in which prior exposure to an antigen leads to a subsequent suboptimal immune response to a related antigen. Immune memory normally allows for an improved and rapid response to antigens previously seen and is the mechanism by which vaccination works. I here develop a dynamical system model of the mechanism of original antigenic sin in influenza, clarifying and explaining the detailed spin-glass treatment of original antigenic sin. The dynamical system describes the viral load, the quantities of healthy and infected epithelial cells, the concentrations of naïve and memory antibodies, and the affinities of naïve and memory antibodies. I give explicit correspondences between the microscopic variables of the spin-glass model and those of the present dynamical system model. The dynamical system model reproduces the phenomenon of original antigenic sin and describes how a competition between different types of B cells compromises the overall effect of immune response. I illustrate the competition between the naïve and the memory antibodies as a function of the antigenic distance between the initial and subsequent antigens. The suboptimal immune response caused by original antigenic sin is observed when the host is exposed to an antigen which has intermediate antigenic distance to a second antigen previously recognized by the host''s immune system.     

Compensatory evolution of net-charge in influenza A virus hemagglutinin

The propagation of influenza A virus depends on the balance between the activities of hemagglutinin (HA) for binding to host cells and neuraminidase (NA) for releasing from infected cells (HA-NA balance). Since the host cell membrane and the sialic acid receptor are negatively charged, the amino acid substitutions increasing (charge+) and decreasing (charge-) the positive charge of HA subunit 1 (HA1) enhance and reduce, respectively, the binding avidity and affinity. The positive charge of HA1 in human influenza A virus bearing subtype H3N2 (A/H3N2 virus) was observed to have increased during evolution, but the evolutionary mechanism for this observation was unclear because this may disrupt the HA-NA balance. Here we show, from the phylogenetic analysis of HA for human A/H3N2 and A/H1N1 viruses, that the relative frequencies of charge+ and charge- substitutions were elevated on the branches where the number of N-glycosylation sites (NGS) increased and decreased, respectively, compared to those where the number of NGS did not change. On the latter branches, the net-charge of HA1 appeared to have been largely maintained to preserve its structure and function. Since the charge+ and charge- substitutions in HA1 have opposite effects to the gain and loss of NGS on the binding and release of the virus, the net-charge of HA1 may have evolved to compensate for the effect of the gain and loss of NGS, probably through changing the avidity. Apparently, the relative frequency of charge- substitutions in HA1 of A/H3N2 virus was elevated after the introduction of oseltamivir, and that of charge+ substitutions in HA1 of A/H1N1 virus was elevated after the spread of oseltamivir resistance. These observations may also be explained by the compensatory effect of the net-charge in HA1 on the NA activity for keeping the HA-NA balance.     

A deterministic model for influenza infection with multiple strains and antigenic drift

We describe a multiple strain Susceptible Infected Recovered deterministic model for the spread of an influenza subtype within a population. The model incorporates appearance of new strains due to antigenic drift, and partial immunity to reinfection with related circulating strains. It also includes optional seasonal forcing of the transmission rate of the virus, which allows for comparison between temperate zones and the tropics. Our model is capable of reproducing observed qualitative patterns such as the overall annual outbreaks in the temperate region, a reduced magnitude and an increased frequency of outbreaks in the tropics, and the herald wave phenomenon. Our approach to modelling antigenic drift is novel and further modifications of this model may help improve the understanding of complex influenza dynamics.     

Origins and evolution of antigenic diversity in malaria parasites

Each year, malaria parasites cause more than 500 million infections and 0.5-3 million deaths worldwide, mostly among children under five living in sub-Saharan Africa. In contrast with several viral and bacterial pathogens, which elicit long-lived immunity after a primary infection, these parasites require several years of continuous exposure to confer partial, usually non-sterilizing immune protection. One of the main obstacles to the acquisition of antimalarial immunity is the high degree of antigenic diversity in potential target antigens, which enables parasites to evade immune responses elicited by past exposure to variant forms of the same antigen. Allelic polymorphism, the existence of genetically stable alternative forms of antigen-coding genes, originates from nucleotide replacement mutations and intragenic recombination. In addition, malaria parasites display antigenic variation, whereby a clonal lineage of parasites expresses successively alternate forms of an antigen without changes in genotype. This review focuses on molecular and evolutionary processes that promote allelic polymorphism and antigenic variation in natural malaria parasite populations and their implications for naturally acquired immunity and vaccine development.     

A simple influenza model with complicated dynamics

We propose and analyse a model for the dynamics of a single strain of an influenza-like infection. The model incorporates waning acquired immunity to infection and punctuated antigenic drift of the virus, employing a set of differential equations within a season and a discrete map between seasons. We show that the between-season map displays a variety of qualitatively different dynamics: fixed points, periodic solutions, or more complicated behaviour suggestive of chaos. For some example parameters we demonstrate the existence of two distinct basins of attraction, that is the initial conditions determine the long term dynamics. Our results suggest that there is no reason to expect influenza dynamics to be regular, or to expect past epidemics to give a clear indication of future seasons’ behaviour.