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An evolution-based high-fidelity method of epistasis measurement: Theory and application to influenza.

ABSTRACT: Linkage effects in a multi-locus population strongly influence its evolution. The models based on the traveling wave approach enable us to predict the average speed of evolution and the statistics of phylogeny. However, predicting statistically the evolution of specific sites and pairs of sites in the multi-locus context remains a mathematical challenge. In particular, the effects of epistasis, the interaction of gene regions contributing to phenotype, is difficult to predict theoretically and detect experimentally in sequence data. A large number of false-positive interactions arises from stochastic linkage effects and indirect interactions, which mask true epistatic interactions. Here we develop a proof-of-principle method to filter out false-positive interactions. We start by demonstrating that the averaging of haplotype frequencies over multiple independent populations is necessary but not sufficient for epistatic detection, because it still leaves high numbers of false-positive interactions. To compensate for the residual stochastic noise, we develop a three-way haplotype method isolating true interactions. The fidelity of the method is confirmed analytically and on simulated genetic sequences evolved with a known epistatic network. The method is then applied to a large sequence database of neurominidase protein of influenza A H1N1 obtained from various geographic locations to infer the epistatic network responsible for the difference between the pre-pandemic virus and the pandemic strain of 2009. These results present a simple and reliable technique to measure epistatic interactions of any sign from sequence data.

SUBMITTER: Pedruzzi G

PROVIDER: S-EPMC8248644 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The surface proteins of human influenza A viruses experience positive selection to escape both human immunity and, more recently, antiviral drug treatments. In bacteria and viruses, immune-escape and drug-resistant phenotypes often appear through a combination of several mutations that have epistatic effects on pathogen fitness. However, the extent and structure of epistasis in influenza viral proteins have not been systematically investigated. Here, we develop a novel statistical method to detect positive epistasis between pairs of sites in a protein, based on the observed temporal patterns of sequence evolution. The method rests on the simple idea that a substitution at one site should rapidly follow a substitution at another site if the sites are positively epistatic. We apply this method to the surface proteins hemagglutinin and neuraminidase of influenza A virus subtypes H3N2 and H1N1. Compared to a non-epistatic null distribution, we detect substantial amounts of epistasis and determine the identities of putatively epistatic pairs of sites. In particular, using sequence data alone, our method identifies epistatic interactions between specific sites in neuraminidase that have recently been demonstrated, in vitro, to confer resistance to the drug oseltamivir; these epistatic interactions are responsible for widespread drug resistance among H1N1 viruses circulating today. This experimental validation demonstrates the predictive power of our method to identify epistatic sites of importance for viral adaptation and public health. We conclude that epistasis plays a large role in shaping the molecular evolution of influenza viruses. In particular, sites with , which would normally not be identified as positively selected, can facilitate viral adaptation through epistatic interactions with their partner sites. The knowledge of specific interactions among sites in influenza proteins may help us to predict the course of antigenic evolution and, consequently, to select more appropriate vaccines and drugs.

Project description:Vaccination is considered the most effective preventive means for influenza control. The development of a master virus with high growth and genetic stability, which may be used for the preparation of vaccine viruses by gene reassortment, is crucial for the enhancement of vaccine performance and efficiency of production. Here, we describe the generation of a high-fidelity and high-growth influenza vaccine master virus strain with a single V43I amino acid change in the PB1 polymerase of the high-growth A/Puerto Rico/8/1934 (PR8) master virus. The PB1-V43I mutation was introduced to increase replication fidelity in order to design an H1N1 vaccine strain with a low error rate. The PR8-PB1-V43I virus exhibited good replication compared with that of the parent PR8 virus. In order to compare the efficiency of egg adaptation and the occurrence of gene mutations leading to antigenic alterations, we constructed 6:2 genetic reassortant viruses between the A(H1N1)pdm09 and the PR8-PB1-V43I viruses; hemagglutinin (HA) and neuraminidase (NA) were from the A(H1N1)pdm09 virus, and the other genes were from the PR8 virus. Mutations responsible for egg adaptation mutations occurred in the HA of the PB1-V43I reassortant virus during serial egg passages; however, in contrast, antigenic mutations were introduced into the HA gene of the 6:2 reassortant virus possessing the wild-type PB1. This study shows that the mutant PR8 virus possessing the PB1 polymerase with the V43I substitution may be utilized as a master virus for the generation of high-growth vaccine viruses with high polymerase fidelity, low error rates of gene replication, and reduced antigenic diversity during virus propagation in eggs for vaccine production.IMPORTANCE Vaccination represents the most effective prophylactic option against influenza. The threat of emergence of influenza pandemics necessitates the ability to generate vaccine viruses rapidly. However, as the influenza virus exhibits a high mutation rate, vaccines must be updated to ensure a good match of the HA and NA antigens between the vaccine and the circulating strain. Here, we generated a genetically stable master virus of the A/Puerto Rico/8/1934 (H1N1) backbone encoding an engineered high-fidelity viral polymerase. Importantly, following the application of the high-fidelity PR8 backbone, no mutation resulting in antigenic change was introduced into the HA gene during propagation of the A(H1N1)pdm09 candidate vaccine virus. The low error rate of the present vaccine virus should decrease the risk of generating mutant viruses with increased virulence. Therefore, our findings are expected to be useful for the development of prepandemic vaccines and live attenuated vaccines with higher safety than that of the present candidate vaccines.

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An evolution-based high-fidelity method of epistasis measurement: Theory and application to influenza.

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