Sweep Dynamics (SD) plots: Computational identification of selective sweeps to monitor the adaptation of influenza A viruses

Klingen, Thorsten R.; Reimering, Susanne; Loers, Jens Uwe; Mooren, Kyra; Klawonn, Frank; Krey, Thomas; Gabriel, Gülşah; McHardy, Alice C.

doi:10.1038/s41598-017-18791-z

Cited by 17 publications

(54 citation statements)

References 71 publications

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“…Of the seven key antigenic sites by Koel et al (2013), sites 155, 156 and 189 were excluded from a patch. These findings underline that antigenic alterations cannot exclusively explain positive selection 14,16 .…”

Section: Adaptive Immune Evolutionmentioning

confidence: 63%

“…Subsequent studies refined key regions or sites responsible for antigenic drift in HA1 14,23,52,53 . Thus, we also compared H3N2 patch sites with "antigenic patch" sites 23 , "adapatch" sites 22 , key antigenic sites 52 , sweep-related sites 16 and TCE sites 33 ( Figure 1A). Eight of twenty-three antigenic patch sites are included in patches ( ).…”

Section: Adaptive Immune Evolutionmentioning

confidence: 99%

“…In turn, thirty ( ) sites were newly clustered into patches, mostly due to inclusion of both exposed and, newly, also buried protein sites in patches. Half of the sweep-related sites from 16 Figure 2B). For pH1N1/HA1 we observe almost identical overlaps of patch sites with TCE sites ( ) and BCE sites ( ).…”

Section: Adaptive Immune Evolutionmentioning

confidence: 99%

“…Human influenza A viruses are the prime example of a rapidly evolving pathogen engaging in a co-evolutionary arms race with the host adaptive immune defenses. Due to their rapid evolution, the antigenic change of the major antigen to the humoral (B-cell) immune response, the surface protein HA, is monitored across the years 2,[12][13][14][15][16] . Every couple of years, as susceptibility of the population becomes low due to prior infection or vaccinations, antigenically novel strains emerge and predominate in seasonal epidemics 17 .…”

Section: Introductionmentioning

confidence: 99%

“…Evolutionary processes such as adaptation to specific environmental conditions can be studied on the level of genes, individual sites or even protein regions 15,16,[22][23][24][25][26][27][28][29] . A widely used method determines the rates of non-synonymous to synonymous changes ( ratio) in a phylogeny 13,30 .…”

Section: Introductionmentioning

confidence: 99%

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Structures and functions linked to genome-wide adaptation of human influenza A viruses

Klingen

Loers

Stanelle-Bertram

et al. 2018

Preprint

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Human influenza A viruses elicit short-term respiratory infections with considerable mortality and morbidity. While H3N2 viruses circulate since almost 50 years, the recent introduction of pH1N1 viruses presents an excellent opportunity for a comparative analysis of the genome-wide evolutionary forces acting on both subtypes. Here, we inferred patches of sites relevant for adaptation, i.e. being under positive selection, on eleven viral protein structures, from all available data since 1968 and correlated these with known functional properties. Overall, pH1N1 had more patches than H3N2 viruses, especially in the viral polymerase complex, while antigenic evolution is more apparent for H3N2 viruses. In both subtypes, NS1 had the highest patch and patch site frequency, indicating that NS1-mediated viral attenuation of host inflammatory responses is a continuously intensifying process, elevated even in the longtimecirculating subtype H3N2. We confirmed the resistance-causing effects of two pH1N1 changes against oseltamivir in NA activity assays, demonstrating the value of the resource for discovering functionally relevant changes. Our results represent an atlas of protein regions and sites with links to host adaptation, antiviral drug resistances and immune evasion for both subtypes for further study.

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Section: Adaptive Immune Evolutionmentioning

confidence: 63%

Section: Adaptive Immune Evolutionmentioning

confidence: 99%

Section: Adaptive Immune Evolutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Structures and functions linked to genome-wide adaptation of human influenza A viruses

Klingen

Loers

Stanelle-Bertram

et al. 2018

Preprint

Self Cite

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Software for Characterizing the Antigenic and Genetic Evolution of Human Influenza Viruses

Reimering

McHardy

2018

Methods in Molecular Biology

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Influenza viruses are rapidly evolving pathogens causing annual epidemics and occasional pandemics. The accumulation of amino acid substitutions allows the virus to adapt to changing environments like novel host species or to escape the acquired immunity of the host population. Especially substitutions in the epitope regions of the surface protein HA lead to antigenic change, facilitating the evasion of the host's immune response by the virus and making frequent updates of the vaccine composition necessary. Through the global monitoring of circulating influenza viruses, large amounts of sequence data are generated. Computational biology offers a quick and easy way to analyze these to characterize the genetic and antigenic evolution of influenza viruses. Using sequence data together with antigenic information provided by hemagglutination inhibition (HI) assays and structural information, bioinformatics methods can elucidate evolutionary relationships between isolates, infer amino acid sites or regions of the protein under positive selection, and identify amino acid changes relevant for the antigenic evolution. We here describe a selection of programs used to generate hypotheses about functionally or antigenically important amino acid changes, protein regions, or individual sites that can subsequently be tested in wet-lab experiments or have value for predicting the future evolution of seasonal influenza A viruses.

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Antigenic characterization of influenza and SARS-CoV-2 viruses

2021

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Antigenic characterization of emerging and re-emerging viruses is necessary for the prevention of and response to outbreaks, evaluation of infection mechanisms, understanding of virus evolution, and selection of strains for vaccine development. Primary analytic methods, including enzyme-linked immunosorbent/lectin assays, hemagglutination inhibition, neuraminidase inhibition, micro-neutralization assays, and antigenic cartography, have been widely used in the field of influenza research. These techniques have been improved upon over time for increased analytical capacity, and some have been mobilized for the rapid characterization of the SARS-CoV-2 virus as well as its variants, facilitating the development of highly effective vaccines within 1 year of the initially reported outbreak. While great strides have been made for evaluating the antigenic properties of these viruses, multiple challenges prevent efficient vaccine strain selection and accurate assessment. For influenza, these barriers include the requirement for a large virus quantity to perform the assays, more than what can typically be provided by the clinical samples alone, cell- or egg-adapted mutations that can cause antigenic mismatch between the vaccine strain and circulating viruses, and up to a 6-month duration of vaccine development after vaccine strain selection, which allows viruses to continue evolving with potential for antigenic drift and, thus, antigenic mismatch between the vaccine strain and the emerging epidemic strain. SARS-CoV-2 characterization has faced similar challenges with the additional barrier of the need for facilities with high biosafety levels due to its infectious nature. In this study, we review the primary analytic methods used for antigenic characterization of influenza and SARS-CoV-2 and discuss the barriers of these methods and current developments for addressing these challenges.

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Sweep Dynamics (SD) plots: Computational identification of selective sweeps to monitor the adaptation of influenza A viruses

Cited by 17 publications

References 71 publications

Structures and functions linked to genome-wide adaptation of human influenza A viruses

Structures and functions linked to genome-wide adaptation of human influenza A viruses

Software for Characterizing the Antigenic and Genetic Evolution of Human Influenza Viruses

Antigenic characterization of influenza and SARS-CoV-2 viruses

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