Bulletin of the American Physical Society
APS March Meeting 2018
Volume 63, Number 1
Monday–Friday, March 5–9, 2018; Los Angeles, California
Session V58: Predicting Viral EvolutionInvited
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Sponsoring Units: DBIO Chair: Ilya Nemenman, Emory Univ Room: LACC Petree Hall C |
Thursday, March 8, 2018 2:30PM - 3:06PM |
V58.00001: Predicting the evolution of influenza virus’s defective interfering genomes Invited Speaker: Katia Koelle Influenza A virus (IAV) rapidly evolves between seasons, enabling the virus to reinfect previously infected hosts. To inform vaccine strain selection, considerable research has therefore focused on predicting the genetic and antigenic evolution of influenza’s hemagglutinin protein, the major target of our immune response. In contrast, little attention has been placed on characterizing the evolutionary dynamics of other components of influenza’s genomic diversity. This genomic diversity encompasses fully-infectious particles, semi-infectious particles that express an incomplete set of essential viral genes, and defective interfering particles (DIPs) that interfere with the replication of the wild-type IAV. Understanding the evolutionary dynamics of DIPs is important given recent work showing that IAV strains can differ in their rates of DIP generation and that these differences affect the severity of infection outcome. Here, we detail recent work from a set of experimental passage studies that addresses the predictability of DIP evolution. Specifically, we statistically interface mechanistic models with data from these passage studies, including deep sequencing data. We find evidence for both selection and drift in driving DIP evolutionary dynamics, with predictable DIP evolution on the largest gene segments emerging from what appears as transitive competitive relationships between the DIPs. Unlike for antigenic phenotypes, where being different is the primary factor impacting fitness, this finding indicates that some DIPs are fitter than others likely as a consequence of either more efficient replication or packaging in coinfected cells. These findings are encouraging for efforts that focus on the development of therapeutic interfering particles for influenza disease control. This is collaborative work between Molly Gallagher/Jeremy Harris/Koelle and Fadi Alnaji/Brigitte Martin/Chris Brooke at UIUC. |
Thursday, March 8, 2018 3:06PM - 3:42PM |
V58.00002: A minimal fitness model for evolutionary predictions Invited Speaker: Marta Luksza Predictions of future evolutionary processes have recently been developed for a number of systems, including the fast-evolving pathogens influenza and HIV. Two key molecular phenotypes have emerged as informative for predictions: protein folding stability and antigenicity, which is determined by interactions with the host’s immune system. A minimal fitness model based on these phenotypes shows time-dependence due to the changing pathogen environment generated by adaptive host immunity. I will show how this model can be used for predictions of antigenic evolution, how the relevant phenotypes can be learned from time-resolved sequence data, and how successful predictions feed back on our understanding of the underlying cell biology. I will use influenza virus and data from cancer patient cohorts as examples. Using these case studies, I will also discuss what are the emerging concepts for predictive analysis of fast-evolving systems. |
Thursday, March 8, 2018 3:42PM - 4:18PM |
V58.00003: Estimation of Vaccine Effectiveness and Early Recognition of Emerging Flu Strain Clusters Invited Speaker: Michael Deem I will discuss evolution of the influenza virus, in the context of the 2017/2018season and historically from 1968 to 2018. Typically a quasispecies of related influenza strains is responsible for the majority of virus in the human population. The virus evolves, however, and this is the reason for the yearly updates to the influenza vaccine. Part of the selection pressure on the virus to evolve arises from immune history in the population due to prior infection or vaccination, which provide protection against closely related strains. This immune protection is well described by the p_epitope theory of vaccine efficacy for both H3N2 and H1N1 influenza. I will discuss this p_epitope theory. As a first application, I will use this theory to explain why the adaptations that occur in the egg-based production lower the effectiveness of the vaccine. In particular, I will show how this theory predicts an effectiveness of 24% for the 2016/2017 vaccine, in comparison to the observed 20%. As a second application, I will discuss interesting recent examples of the emergence of new flu strains, which were not protected against by the vaccine. I will discuss how the emergence of these new strains can be detected and predicted, making use of theory of the immune system. |
Thursday, March 8, 2018 4:18PM - 4:54PM |
V58.00004: Forecasting evolution from the shape of genealogical trees Invited Speaker: Boris Shraiman Given a sample of genome sequences from an asexual population, can one predict its evolutionary future? Under the assumption that evolution proceeds by accumulation of small effect mutations, it can be demonstrated that the branching patterns of reconstructed genealogical trees contains information about the relative fitness of the sampled sequences and that this information can be used to predict successful strains. This approach does not require species specific input and can be applied to any asexual population under persistent selection pressure. The performance of the forecasting method was tested using historical data on seasonal influenza A/H3N2 virus: it identifies the progenitor lineage of the upcoming influenza season with near optimal performance in 30% of cases and makes informative predictions over 80% of the time, overall. The talk will also discuss approaches to improving forecasting with the help of additional, strain specific data. |
Thursday, March 8, 2018 4:54PM - 5:30PM |
V58.00005: Biophysical Walks on Fitness Landscapes Invited Speaker: Eugene Shakhnovich Fitness landscape (FL) is a common metaphoric description of genotype-phenotype relationship (GPR). However its precise nature is not known: ‘’Axes” on the pictorial presentations of FL remain unlabeled. In this talk I will present our theoretical and experimental efforts, to outline FL of viruses and bacteria in terms of biophysical properties of their proteins such as thermodynamic stability, catalytic activity and intracellular abundances as well as functional and non-functional interactions with other proteins. We develop computational multiscale models where link between effect of mutations on molecular properties of proteins and fitness is derived from experiments where rational genetic variation is introduced in ORFs of essential genes dihydrofolate reductase and adenylate kinase. The molecular fingerprints of mutated proteins are then mapped to fitness of strains where mutations are introduced on the chromosome using genomic editing technique. We show how genetic variation introduces major fitness barriers that can be overcome in evolutionary dynamics. Metabolomic, genomic and proteomic comparative analyses of ‘’naïve’’ genomically edited and evolved strains highlights major elements in the relationship between molecular and organismal traits providing a crucial feedback for computational modeling. |
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