Insights into the antigenic advancement of influenza A(H3N2) viruses, 2011–2018

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Abstract

Influenza A(H3N2) viruses evade human immunity primarily by acquiring antigenic changes in the haemagglutinin (HA). HA receptor-binding features of contemporary A(H3N2) viruses hinder traditional antigenic characterization using haemagglutination inhibition and promote selection of HA mutants. Thus, alternative approaches are needed to reliably assess antigenic relatedness between circulating viruses and vaccines. We developed a high content imaging-based neutralization test (HINT) to reduce antigenic mischaracterization resulting from virus adaptation to cell culture. Ferret reference antisera were raised using clinical specimens containing viruses representing recent vaccine strains. Analysis of viruses circulating during 2011–2018 showed that gain of an N158-linked glycosylation in HA was a molecular determinant of antigenic distancing between A/Hong Kong/4801/2014-like (clade 3C.2a) and A/Texas/50/2012-like viruses (clade 3C.1), while multiple evolutionary HA F193S substitution were linked to antigenic distancing from A/Switzerland/97152963/2013-like (clade 3C.3a) and further antigenic distancing from A/Texas/50/2012-like viruses. Additionally, a few viruses carrying HA T135K and/or I192T showed reduced neutralization by A/Hong Kong/4801/2014-like antiserum. Notably, this technique elucidated the antigenic characteristics of clinical specimens, enabling direct characterization of viruses produced in vivo, and eliminating in vitro culture, which rapidly alters the genotype/phenotype. HINT is a valuable new antigenic analysis tool for vaccine strain selection.

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Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler

Samuel Shepard, Sarah Meno, Justin Bahl … (2016)

Background Deep sequencing makes it possible to observe low-frequency viral variants and sub-populations with greater accuracy and sensitivity than ever before. Existing platforms can be used to multiplex a large number of samples; however, analysis of the resulting data is complex and involves separating barcoded samples and various read manipulation processes ending in final assembly. Many assembly tools were designed with larger genomes and higher fidelity polymerases in mind and do not perform well with reads derived from highly variable viral genomes. Reference-based assemblers may leave gaps in viral assemblies while de novo assemblers may struggle to assemble unique genomes. Results The IRMA (iterative refinement meta-assembler) pipeline solves the problem of viral variation by the iterative optimization of read gathering and assembly. As with all reference-based assembly, reads are included in assembly when they match consensus template sets; however, IRMA provides for on-the-fly reference editing, correction, and optional elongation without the need for additional reference selection. This increases both read depth and breadth. IRMA also focuses on quality control, error correction, indel reporting, variant calling and variant phasing. In fact, IRMA’s ability to detect and phase minor variants is one of its most distinguishing features. We have built modules for influenza and ebolavirus. We demonstrate usage and provide calibration data from mixture experiments. Methods for variant calling, phasing, and error estimation/correction have been redesigned to meet the needs of viral genomic sequencing. Conclusion IRMA provides a robust next-generation sequencing assembly solution that is adapted to the needs and characteristics of viral genomes. The software solves issues related to the genetic diversity of viruses while providing customized variant calling, phasing, and quality control. IRMA is freely available for non-commercial use on Linux and Mac OS X and has been parallelized for high-throughput computing. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3030-6) contains supplementary material, which is available to authorized users.

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Neuraminidase receptor binding variants of human influenza A(H3N2) viruses resulting from substitution of aspartic acid 151 in the catalytic site: a role in virus attachment?

Victoria Gregory, Stephen Wharton, R. Daniels … (2010)

Changes in the receptor binding characteristics of human H3N2 viruses have been evident from changes in the agglutination of different red blood cells (RBCs) and the reduced growth capacity of recently isolated viruses, particularly in embryonated eggs. An additional peculiarity of viruses circulating in 2005 to 2009 has been the poor inhibition of hemagglutination by postinfection ferret antisera for many viruses isolated in MDCK cells, including homologous reference viruses. This was shown not to be due to an antigenic change in hemagglutinin (HA) but was shown to be the result of a mutation in aspartic acid 151 of neuraminidase (NA) to glycine, asparagine, or alanine, which caused an oseltamivir-sensitive agglutination of RBCs. The D151G substitution was shown to cause a change in the specificity of NA such that it acquired the capacity to bind receptors, which were refractory to enzymatic cleavage, without altering its ability to remove receptors for HA. Thus, the inhibition of NA-dependent agglutination by the inclusion of oseltamivir carboxylate in the assay was effective in restoring the anti-HA specificity of the hemagglutination inhibition (HI) assay for monitoring antigenic changes in HA. Since the NA-dependent binding activity did not affect virus neutralization, and virus populations in clinical specimens possessed, at most, low levels of the "151 mutant," the biological significance of this feature of NA in, for example, immune evasion is unclear. It is apparent, however, that an important role of aspartic acid 151 in the activity of NA may be to restrict the specificity of the NA interaction and its receptor-destroying activity to complement that of HA receptor binding.

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Complete mapping of viral escape from neutralizing antibodies

Michael Doud, Scott E Hensley, Jesse Bloom (2017)

Identifying viral mutations that confer escape from antibodies is crucial for understanding the interplay between immunity and viral evolution. We describe a high-throughput approach to quantify the selection that monoclonal antibodies exert on all single amino-acid mutations to a viral protein. This approach, mutational antigenic profiling, involves creating all replication-competent protein variants of a virus, selecting with antibody, and using deep sequencing to identify enriched mutations. We use mutational antigenic profiling to comprehensively identify mutations that enable influenza virus to escape four monoclonal antibodies targeting hemagglutinin, and validate key findings with neutralization assays. We find remarkable mutation-level idiosyncrasy in antibody escape: for instance, at a single residue targeted by two antibodies, some mutations escape both antibodies while other mutations escape only one or the other. Because mutational antigenic profiling rapidly maps all mutations selected by an antibody, it is useful for elucidating immune specificities and interpreting the antigenic consequences of viral genetic variation.

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Author and article information

Contributors

Larisa V. Gubareva: lqg3@cdc.gov

Journal

Journal ID (nlm-ta): Sci Rep

Journal ID (iso-abbrev): Sci Rep

Title: Scientific Reports

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2045-2322

Publication date (Electronic): 25 February 2019

Publication date PMC-release: 25 February 2019

Publication date Collection: 2019

Volume: 9

Electronic Location Identifier: 2676

Affiliations

[1 ]ISNI 0000 0001 2163 0069, GRID grid.416738.f, Influenza Division, Centers for Disease Control and Prevention (CDC), ; 1600 Clifton Road, Atlanta, GA 30329 USA

[2 ]CNI Advantage, LLC. 17 Executive Park Dr NE, Atlanta, GA 30329 USA

[3 ]ISNI 0000000095689541, GRID grid.27873.39, Battelle Memorial Institute, ; 2987 Clairmont Rd, Suite 450, Atlanta, GA 30329 USA

Article

Publisher ID: 39276

DOI: 10.1038/s41598-019-39276-1

PMC ID: 6389938

PubMed ID: 30804469

SO-VID: 6b963ad3-5e22-46db-844a-499989f5837f

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 16 October 2018

Date accepted : 11 January 2019

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