In Silico Vaccine Strain Prediction for Human Influenza Viruses

Klingen, Thorsten R.; Reimering, Susanne; Guzmán, Carlos A.; McHardy, Alice C.

doi:10.1016/j.tim.2017.09.001

Cited by 53 publications

(54 citation statements)

References 86 publications

(95 reference statements)

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“…Improvements on the understanding of viral dynamics and the correlation between antigenic and genetic changes in influenza viruses have facilitated the selection of virus strains to be included in upcoming seasonal vaccines (35–37). To better understand viral dynamics of GII.4 noroviruses, we performed selection analyses including all variants reported for over four decades.…”

Section: Discussionmentioning

confidence: 99%

Population Genomics of GII.4 Noroviruses Reveal Complex Diversification and New Antigenic Sites Involved in the Emergence of Pandemic Strains

Tohma

Lepore

Gao

et al. 2019

Preprint

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(max 250) 14Word count in Importance: 110 (max 150) 15 Word count in Main Text: 5698 16Abstract 25 26 GII.4 noroviruses are a major cause of acute gastroenteritis. Their dominance has been partially 27 explained by the continuous emergence of antigenically distinct variants. To gain insights on the 28 mechanisms of viral emergence and population dynamics of GII.4 noroviruses, we performed 29 large-scale genomics, structural, and mutational analyses of the viral capsid protein (VP1). GII.4 30 noroviruses exhibited a periodic replacement of predominant variants with accumulation of 31 amino acid substitutions. Genomic analyses revealed (i) a large number (87%) of conserved 32 residues; (ii) variable residues that map on the previously determined antigenic sites; and (iii) 33 variable residues that map outside of the antigenic sites. Residues from the third pattern formed 34 motifs on the surface of VP1, which suggested extensions of previously predicted and new 35 uncharacterized antigenic sites. The role of two motifs (C and G) in the antigenic make-up of the 36 GII.4 capsid protein was confirmed with monoclonal antibodies and carbohydrate blocking 37 assays. Amino acid profiles from antigenic sites (A, C, D, E, and G) correlated with the 38 circulation patterns of GII.4 variants, with two of them (C and G) containing residues (352, 357, 39 378) linked with the emergence of new GII.4 variants. Notably, the emergence of each variant 40 was followed by a stochastic diversification with minimal changes at the antigenic sites that did 41 not progress towards the next variant. This study provides a methodological framework for 42 antigenic characterization of viruses, and expands our understanding of the dynamics of GII.4 43 noroviruses that could facilitate the design of cross-reactive vaccines. 44 3 Importance 45 46 Noroviruses are an important cause of viral gastroenteritis around the world. An obstacle 47delaying the development of norovirus vaccines is an inadequate understanding of the role of 48 norovirus diversity in immunity. Using a population genomics approach, we identified new 49 residues on the viral capsid protein (VP1) from GII.4 noroviruses, the predominant genotype, 50 that appear to be involved in the emergence and antigenic topology of GII.4 variants. Careful 51 monitoring of the substitutions in those residues involved in the diversification and emergence of 52 new viruses could help in the early detection of future novel variants with pandemic potential. 53Therefore, this novel information on the antigenic diversification could facilitate GII.4 norovirus 54 vaccine design. 55 56

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Section: Discussionmentioning

confidence: 99%

Population Genomics of GII.4 Noroviruses Reveal Complex Diversification and New Antigenic Sites Involved in the Emergence of Pandemic Strains

Tohma

Lepore

Gao

et al. 2019

Preprint

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“…Retrospective analysis of historical data should be con-ducted to quantify the degree to which reassortment events give rise to successful genotypes [15,18,20]. Results from such analysis can then inform predictive modeling efforts to anticipate composition of future influenza virus populations [7,33,36,37]. In addition to paramount importance for public health, the wealth of genomic longitudinal data with high spatiotemporal resolution make influenza viruses an ideal system to address general questions of evolutionary biology on epistasis, reassortment, and recombination.…”

Section: Discussionmentioning

confidence: 99%

Evolution and rapid spread of a reassortant A(H3N2) virus that predominated the 2017-2018 influenza season

Potter

Garten

Hadfield

et al. 2019

Preprint

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The 2017-2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the virus's North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70% of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, HI assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016-2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.

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“…For example, in outbreak investigations, host risk behaviour and transmission patterns are not usually observed and must be inferred. It is not known a priori which clades are more or less likely to expand in the future, although there is active research addressing this problem, such as to predict the emergence of strains of influenza A virus (Klingen et al 2018) or the forecast the effect of antibiotic usage policies on the prevalence of resistant variants (Whittles et al 2017).…”

Section: Figurementioning

confidence: 99%

Identification of hidden population structure in time-scaled phylogenies

Volz

Wiuf

Grad

et al. 2019

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17Population structure influences genealogical patterns, however data 18 pertaining to how populations are structured are often unavailable or 19 not directly observable. Inference of population structure is highly 20 important in molecular epidemiology where pathogen phylogenetics is 21 increasingly used to infer transmission patterns and detect outbreaks. 22 Discrepancies between observed and idealised genealogies, such as those 23 generated by the coalescent process, can be quantified, and where 24 significant differences occur, may reveal the action of natural selection, 25 host population structure, or other demographic and epidemiological 26 heterogeneities. We have developed a fast non-parametric statistical test 27 for detection of cryptic population structure in time-scaled phylogenetic 28 trees. The test is based on contrasting estimated phylogenies with the 29 theoretically expected phylodynamic ordering of common ancestors in 30 two clades within a coalescent framework. These statistical tests have 31 also motivated the development of algorithms which can be used to 32 quickly screen a phylogenetic tree for clades which are likely to share a 33 distinct demographic or epidemiological history. Epidemiological 34 applications include identification of outbreaks in vulnerable host 35 populations or rapid expansion of genotypes with a fitness advantage.36To demonstrate the utility of these methods for outbreak detection, we 37 applied the new methods to large phylogenies reconstructed from 38 thousands of HIV-1 partial pol sequences. This revealed the presence of 39 clades which had grown rapidly in the recent past, and was significantly 40 concentrated in young men, suggesting recent and rapid transmission in 41 that group. Furthermore, to demonstrate the utility of these methods 42 for the study of antimicrobial resistance, we applied the new methods to 43 a large phylogeny reconstructed from whole genome Neisseria 44 gonorrhoeae sequences. We find that population structure detected 45 using these methods closely overlaps with the appearance and expansion 46 of mutations conferring antimicrobial resistance. 48 diversity is a longstanding problem in population genetics. When information 49 about how lineages are sampled is available, primarily geographic location, a 50 variety of statistics are available for describing the magnitude and role of 51 population structure (Hartl et al. 1997). In pathogen phylogenetics, such 52 geographic 'meta-data' has been instrumental in enabling the inference of 53 transmission rates over space (Dudas et al. 2017), host species (Lam et al. 54 2015), and even individual hosts (De Maio et al. 2018). Population structure 55 shapes genetic diversity, but can the existence of structure be inferred directly 56 from genetic data in the absence of structural covariates associated with each 57 lineage, such as if the geographic location or host species of a lineage is 58 unknown? 59 The problem of detecting and quantifying such 'cryptic' population 60 structure has become a pr...

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In Silico Vaccine Strain Prediction for Human Influenza Viruses

Cited by 53 publications

References 86 publications

Population Genomics of GII.4 Noroviruses Reveal Complex Diversification and New Antigenic Sites Involved in the Emergence of Pandemic Strains

Population Genomics of GII.4 Noroviruses Reveal Complex Diversification and New Antigenic Sites Involved in the Emergence of Pandemic Strains

Evolution and rapid spread of a reassortant A(H3N2) virus that predominated the 2017-2018 influenza season

Identification of hidden population structure in time-scaled phylogenies

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