Mapping the Evolutionary Potential of RNA Viruses

Dolan, Patrick; Whitfield, Zachary J.; Andino, Raul

doi:10.1016/j.chom.2018.03.012

Cited by 90 publications

(89 citation statements)

References 124 publications

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“…The evolutionary pathways traversed by RNA viruses are shaped by natural selection, which will favor some evolutionary trajectories more than others based on whether mutations are beneficial, deleterious, or neutral (2). Predicting the likely results of RNA virus evolution is an important step for anticipating viral emergence and for developing escape-resistant antiviral drugs and vaccines (3,4).…”

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confidence: 99%

Fitness Barriers Limit Reversion of a Proofreading-Deficient Coronavirus

Graepel

Agostini

et al. 2019

J Virol

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The 3=-to-5= exoribonuclease in coronavirus (CoV) nonstructural protein 14 (nsp14-ExoN) mediates RNA proofreading during genome replication. ExoN catalytic residues are arranged in three motifs: I (DE), II (E), and III (D). Alanine replacement of the motif I residues (AA-E-D; four nucleotide substitutions) in murine hepatitis virus (MHV) and severe acute respiratory syndrome (SARS)-CoV yields viable mutants with impaired replication and fitness, increased mutation rates, and attenuated virulence in vivo. Despite these impairments, MHV-and SARS-CoV ExoN motif I AA mutants (ExoN-AA) have not reverted at motif I in diverse in vitro and in vivo environments, suggesting that profound fitness barriers prevent motif I reversion. To test this hypothesis, we engineered MHV-ExoN-AA with 1, 2, or 3 nucleotide mutations along genetic pathways to AA-to-DE reversion. We show that engineered intermediate revertants were viable but had no increased replication or competitive fitness compared to that of MHV-ExoN-AA. In contrast, a low-passage-number (passage 10 [P10]) MHV-ExoN-AA showed increased replication and competitive fitness without reversion of ExoN-AA. Finally, engineered reversion of ExoN-AA to ExoN-DE in the presence of ExoN-AA passage-adaptive mutations resulted in significant fitness loss. These results demonstrate that while reversion is possible, at least one alternative adaptive pathway is more rapidly advantageous than intermediate revertants and may alter the genetic background to render reversion detrimental to fitness. Our results provide an evolutionary rationale for lack of ExoN-AA reversion, illuminate potential multiprotein replicase interactions and coevolution, and support future studies aimed at stabilizing attenuated CoV ExoN-AA mutants. IMPORTANCE Coronaviruses encode an exoribonuclease (ExoN) that is important for viral replication, fitness, and virulence, yet coronaviruses with a defective ExoN (ExoN-AA) have not reverted under diverse experimental conditions. In this study, we identify multiple impediments to MHV-ExoN-AA reversion. We show that ExoN-AA reversion is possible but evolutionarily unfavorable. Instead, compensatory mutations outside ExoN-AA motif I are more accessible and beneficial than partial reversion. We also show that coevolution between replicase proteins over long-term passage partially compensates for ExoN-AA motif I but renders the virus inhospitable to a reverted ExoN. Our results reveal the evolutionary basis for the genetic stability of ExoN-inactivating mutations, illuminate complex functional and evolutionary relationships between coronavirus replicase proteins, and identify potential mechanisms for stabilization of ExoN-AA coronavirus mutants.

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confidence: 99%

Fitness Barriers Limit Reversion of a Proofreading-Deficient Coronavirus

Graepel

Agostini

et al. 2019

J Virol

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“…In either case, our results strongly suggest that the MAX protease's sequence position affects its genotypic PI resistance profile. Synonymous codons differ in their propensity to mutate, and as previously suggested (25,32,43), this differential access to the protein sequence space may affect adaptive pathways.…”

Section: Discussionmentioning

confidence: 80%

“…Moreover, synonymous virus genome recoding involves the introduction of hundreds or thousands of nucleotide substitutions, which minimizes the risk of phenotypic reversion via point mutations or through recombination with homologous sequences in circulating strains. This is particularly important with regard to RNA viruses, since viral RNA polymerases lack error correction mechanisms (25)(26)(27). The high genetic variability of RNA viruses is a critical limitation in designing novel antiviral strategies.…”

Section: Abstract Evolutionary Biology Human Immunodeficiency Virusmentioning

confidence: 99%

“…Like those of other RNA viruses, HIV-1 populations comprise closely related mutant spectra or mutant clouds termed viral quasispecies (34,35). Mutant cloud composition can affect virus evolvability, fitness, and virulence (25)(26)(27). One unexplored aspect of HIV-1 genetic architecture is how codon choice influences population diversity and evolvability.…”

Section: Abstract Evolutionary Biology Human Immunodeficiency Virusmentioning

confidence: 99%

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HIV-1 Protease Evolvability Is Affected by Synonymous Nucleotide Recoding

Nevot

Jordan-Paiz

Martrus

et al. 2018

J Virol

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One unexplored aspect of HIV-1 genetic architecture is how codon choice influences population diversity and evolvability. Here we compared the levels of development of HIV-1 resistance to protease inhibitors (PIs) between wild-type (WT) virus and a synthetic virus (MAX) carrying a codon-pair-reengineered protease sequence including 38 (13%) synonymous mutations. The WT and MAX viruses showed indistinguishable replication in MT-4 cells or peripheral blood mononuclear cells (PBMCs). Both viruses were subjected to serial passages in MT-4 cells, with selective pressure from the PIs atazanavir (ATV) and darunavir (DRV). After 32 successive passages, both the WT and MAX viruses developed phenotypic resistance to PIs (50% inhibitory concentrations [ICs] of 14.6 ± 5.3 and 21.2 ± 9 nM, respectively, for ATV and 5.9 ± 1.0 and 9.3 ± 1.9, respectively, for DRV). Ultradeep sequence clonal analysis revealed that both viruses harbored previously described mutations conferring resistance to ATV and DRV. However, the WT and MAX virus proteases showed different resistance variant repertoires, with the G16E and V77I substitutions observed only in the WT and the L33F, S37P, G48L, Q58E/K, and L89I substitutions detected only in the MAX virus. Remarkably, the G48L and L89I substitutions are rarely found in PI-treated patients. The MAX virus showed significantly higher nucleotide and amino acid diversity of the propagated viruses with and without PIs ( < 0.0001), suggesting a higher selective pressure for change in this recoded virus. Our results indicate that the HIV-1 protease position in sequence space delineates the evolution of its mutant spectrum. Nevertheless, the investigated synonymously recoded variant showed mutational robustness and evolvability similar to those of the WT virus. Large-scale synonymous recoding of virus genomes is a new tool for exploring various aspects of virus biology. Synonymous virus genome recoding can be used to investigate how a virus's position in sequence space defines its mutant spectrum, evolutionary trajectory, and pathogenesis. In this study, we evaluated how synonymous recoding of the human immunodeficiency virus type 1 (HIV-1) protease affects the development of protease inhibitor (PI) resistance. HIV-1 protease is a main target of current antiretroviral therapies. Our present results demonstrate that the wild-type (WT) virus and a virus with recoded protease exhibited different patterns of resistance mutations after PI treatment. Nevertheless, the developed PI resistance phenotypes were indistinguishable between the recoded virus and the WT virus, suggesting that the HIV-1 strain with synonymously recoded protease and the WT virus are equally robust and evolvable.

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“…In Wright's vivid words, the interaction of selection and variation enables populations to "continually find their way from lower to higher peaks" [4], thereby providing a universal mechanism for open-ended evolution [5]. Thanks to the explosive development of sequencing technologies, fitness landscapes have now been measured in a variety of real molecular [6], viral [7] or microbial [8] systems. As a result, the goal of predicting evolution no longer appears wholly out of reach [8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Effective potential reveals evolutionary trajectories in complex fitness landscapes

Smerlak¹

2019

Preprint

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Growing efforts to measure fitness landscapes in molecular and microbial systems are premised on a tight relationship between landscape topography and evolutionary trajectories. This relationship, however, is far from being straightforward: depending on their mutation rate, Darwinian populations can climb the closest fitness peak (survival of the fittest), settle in lower regions with higher mutational robustness (survival of the flattest), or fail to adapt altogether (error catastrophes). These bifurcations highlight that evolution does not necessarily drive populations "from lower peak to higher peak", as Wright imagined. The problem therefore remains: how exactly does a complex landscape topography constrain evolution, and can we predict where it will go next?Here I introduce a generalization of quasispecies theory which identifies metastable evolutionary states as minima of an effective potential. From this representation I derive a coarse-grained, Markov state model of evolution, which in turn forms a basis for evolutionary predictions across a wide range of mutation rates. Because the effective potential is related to the ground state of a quantum Hamiltonian, my approach could stimulate fruitful interactions between evolutionary dynamics and quantum many-body theory. SIGNIFICANCE STATEMENTThe course of evolution is determined by the relationship between heritable types and their adaptive values, the fitness landscape. Thanks to the explosive development of sequencing technologies, fitness landscapes have now been measured in a diversity of systems from molecules to micro-organisms. How can we turn these data into evolutionary predictions? I show that preferred evolutionary trajectories are revealed when the effects of selection and mutations are blended in a single effective evolutionary force. With this reformulation, the dynamics of selection and mutation becomes Markovian, bringing a wealth of classical visualization and analysis tools to bear on evolutionary dynamics. Among these is a coarse-graining of evolutionary dynamics along its metastable states which greatly reduces the complexity of the prediction problem.

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Mapping the Evolutionary Potential of RNA Viruses

Cited by 90 publications

References 124 publications

Fitness Barriers Limit Reversion of a Proofreading-Deficient Coronavirus

Fitness Barriers Limit Reversion of a Proofreading-Deficient Coronavirus

HIV-1 Protease Evolvability Is Affected by Synonymous Nucleotide Recoding

Effective potential reveals evolutionary trajectories in complex fitness landscapes

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