nextflu: real-time tracking of seasonal influenza virus evolution in humans

Sequence amplification via cell passaging creates spurious signals of positive adaptation in influenza virus H3N2 hemagglutinin

Clinical influenza A virus isolates are frequently not sequenced directly. Instead, a majority of these isolates (~70% in 2015) are first subjected to passaging for amplification, most commonly in non-human cell culture. Here, we find that this passaging leaves distinct signals of adaptation, which can confound evolutionary analyses of the viral sequences. We find distinct patterns of adaptation to Madin-Darby (MDCK) and monkey cell culture absent from unpassaged hemagglutinin sequences. These patterns also dominate pooled datasets not separated by passaging type, and they increase in proportion to the number of passages performed. By contrast, MDCK-SIAT1 passaged sequences seem mostly (but not entirely) free of passaging adaptations. Contrary to previous studies, we find that using only internal branches of influenza virus phylogenetic trees is insufficient to correct for passaging artifacts. These artifacts can only be safely avoided by excluding passaged sequences entirely from subsequent analysis. We conclude that future influenza virus evolutionary analyses should appropriately control for potentially confounding effects of passaging adaptations.

Selection of antigenically advanced variants of seasonal influenza viruses

Influenza viruses mutate frequently, necessitating constant updates of vaccine viruses. To establish experimental approaches that may complement the current vaccine strain selection process, we selected antigenic variants from human H1N1 and H3N2 influenza virus libraries possessing random mutations in the globular head of the haemagglutinin protein (which includes the antigenic sites) by incubating them with human and/or ferret convalescent sera to human H1N1 and H3N2 viruses. We also selected antigenic escape variants from human viruses treated with convalescent sera and from mice that had been previously immunized against human influenza viruses. Our pilot studies with past influenza viruses identified escape mutants that were antigenically similar to variants that emerged in nature, establishing the feasibility of our approach. Our studies with contemporary human influenza viruses identified escape mutants before they caused an epidemic in 2014-2015. This approach may aid in the prediction of potential antigenic escape variants and the selection of future vaccine candidates before they become widespread in nature.

Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses

Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny.

Deep Sequencing Reveals Potential Antigenic Variants at Low Frequencies in Influenza A Virus-Infected Humans

Influenza vaccines must be frequently reformulated to account for antigenic changes in the viral envelope protein, hemagglutinin (HA). The rapid evolution of influenza virus under immune pressure is likely enhanced by the virus's genetic diversity within a host, although antigenic change has rarely been investigated on the level of individual infected humans. We used deep sequencing to characterize the between- and within-host genetic diversity of influenza viruses in a cohort of patients that included individuals who were vaccinated and then infected in the same season. We characterized influenza HA segments from the predominant circulating influenza A subtypes during the 2012-2013 (H3N2) and 2013-2014 (pandemic H1N1; H1N1pdm) flu seasons. We found that HA consensus sequences were similar in nonvaccinated and vaccinated subjects. In both groups, purifying selection was the dominant force shaping HA genetic diversity. Interestingly, viruses from multiple individuals harbored low-frequency mutations encoding amino acid substitutions in HA antigenic sites at or near the receptor-binding domain. These mutations included two substitutions in H1N1pdm viruses, G158K and N159K, which were recently found to confer escape from virus-specific antibodies. These findings raise the possibility that influenza antigenic diversity can be generated within individual human hosts but may not become fixed in the viral population even when they would be expected to have a strong fitness advantage. Understanding constraints on influenza antigenic evolution within individual hosts may elucidate potential future pathways of antigenic evolution at the population level.

IMPORTANCE

Influenza vaccines must be frequently reformulated due to the virus's rapid evolution rate. We know that influenza viruses exist within each infected host as a "swarm" of genetically distinct viruses, but the role of this within-host diversity in the antigenic evolution of influenza has been unclear. We characterized here the genetic and potential antigenic diversity of influenza viruses infecting humans, some of whom became infected despite recent vaccination. Influenza virus between- and within-host genetic diversity was not significantly different in nonvaccinated and vaccinated humans, suggesting that vaccine-induced immunity does not exert strong selective pressure on viruses replicating in individual people. We found low-frequency mutations, below the detection threshold of traditional surveillance methods, in nonvaccinated and vaccinated humans that were recently associated with antibody escape. Interestingly, these potential antigenic variants did not reach fixation in infected people, suggesting that other evolutionary factors may be hindering their emergence in individual humans.

Genome-Wide Analysis of Evolutionary Markers of Human Influenza A(H1N1)pdm09 and A(H3N2) Viruses May Guide Selection of Vaccine Strain Candidates

Here we analyzed whole-genome sequences of 3,969 influenza A(H1N1)pdm09 and 4,774 A(H3N2) strains that circulated during 2009–2015 in the world. The analysis revealed changes at 481 and 533 amino acid sites in proteins of influenza A(H1N1)pdm09 and A(H3N2) strains, respectively. Many of these changes were introduced as a result of random drift. However, there were 61 and 68 changes that were present in relatively large number of A(H1N1)pdm09 and A(H3N2) strains, respectively, that circulated during relatively long time. We named these amino acid substitutions evolutionary markers, as they seemed to contain valuable information regarding the viral evolution. Interestingly, influenza A(H1N1)pdm09 and A(H3N2) viruses acquired non-overlapping sets of evolutionary markers. We next analyzed these characteristic markers in vaccine strains recommended by the World Health Organization for the past five years. Our analysis revealed that vaccine strains carried only few evolutionary markers at antigenic sites of viral hemagglutinin (HA) and neuraminidase (NA). The absence of these markers at antigenic sites could affect the recognition of HA and NA by human antibodies generated in response to vaccinations. This could, in part, explain moderate efficacy of influenza vaccines during 2009–2014. Finally, we identified influenza A(H1N1)pdm09 and A(H3N2) strains, which contain all the evolutionary markers of influenza A strains circulated in 2015, and which could be used as vaccine candidates for the 2015/2016 season. Thus, genome-wide analysis of evolutionary markers of influenza A(H1N1)pdm09 and A(H3N2) viruses may guide selection of vaccine strain candidates.

Use of computational and recombinant technologies for developing novel influenza vaccines

Influenza vaccine design has changed considerably with advancements in bioinformatics and computational biology. Improved surveillance efforts provide up-to-date information about influenza sequence diversity and assist with monitoring the spread of epidemics and vaccine efficacy rates. The advent of next-generation sequencing, epitope scanning and high-throughput analysis all help decipher influenza-associated protein interactions as well as predict immune responsiveness based on host genetic diversity. Computational approaches are utilized in nearly all aspects of vaccine design, from modeling, compatibility predictions, and optimization of antigens in various platforms. This overview discusses how computational techniques strengthen vaccine efforts against highly diverse influenza species.

Real-time digital pathogen surveillance - the time is now

It is time to shake up public health surveillance. New technologies for sequencing, aided by friction-free approaches to data sharing, could have an impact on public health efforts.