title: Viruses roll the dice: the stochastic behavior of viral genome molecules accelerates viral adaptation at the cell and tissue levels.
abstract: Recent studies on evolutionarily distant viral groups have shown that the number of viral genomes that establish cell infection after cell-to-cell transmission is unexpectedly small (1-20 genomes). This aspect of viral infection appears to be important for the adaptation and survival of viruses. To clarify how the number of viral genomes that establish cell infection is determined, we developed a simulation model of cell infection for tomato mosaic virus (ToMV), a positive-strand RNA virus. The model showed that stochastic processes that govern the replication or degradation of individual genomes result in the infection by a small number of genomes, while a large number of infectious genomes are introduced in the cell. It also predicted two interesting characteristics regarding cell infection patterns: stochastic variation among cells in the number of viral genomes that establish infection and stochastic inequality in the accumulation of their progenies in each cell. Both characteristics were validated experimentally by inoculating tobacco cells with a library of nucleotide sequence-tagged ToMV and analyzing the viral genomes that accumulated in each cell using a high-throughput sequencer. An additional simulation model revealed that these two characteristics enhance selection during tissue infection. The cell infection model also predicted a mechanism that enhances selection at the cellular level: a small difference in the replication abilities of coinfected variants results in a large difference in individual accumulation via the multiple-round formation of the replication complex (i.e., the replication machinery). Importantly, this predicted effect was observed in vivo. The cell infection model was robust to changes in the parameter values, suggesting that other viruses could adopt similar adaptation mechanisms. Taken together, these data reveal a comprehensive picture of viral infection processes including replication, cell-to-cell transmission, and evolution, which are based on the stochastic behavior of the viral genome molecules in each cell.
authors.affiliation: Precursory Research for Embryonic Science and Technology (PRESTO), Japan Science and Technology Agency, Kawaguchi, Japan; Plant-Microbe Interactions Research Unit, Division of Plant Sciences, National Institute of Agrobiological Sciences, Tsukuba, Japan.
authors.forename: Shuhei
authors.initials: S
authors.lastname: Miyashita
authors.affiliation: Plant-Microbe Interactions Research Unit, Division of Plant Sciences, National Institute of Agrobiological Sciences, Tsukuba, Japan.
authors.forename: Kazuhiro
authors.initials: K
authors.lastname: Ishibashi
authors.affiliation: Graduate School of Agricultural and Life Sciences, University of Tokyo, Tokyo, Japan.
authors.forename: Hirohisa
authors.initials: H
authors.lastname: Kishino
authors.affiliation: Plant-Microbe Interactions Research Unit, Division of Plant Sciences, National Institute of Agrobiological Sciences, Tsukuba, Japan.
authors.forename: Masayuki
authors.initials: M
authors.lastname: Ishikawa
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics*; D005075:Biological Evolution; D003198:Computer Simulation; D016679:Genome, Viral; D015233:Models, Statistical; D059828:Plant Cells / Q000821:virology; D012367:RNA, Viral / Q000235:genetics*; D012641:Selection, Genetic; D013269:Stochastic Processes; D014026:Nicotiana / Q000821:virology; D017898:Tobamovirus / Q000235:genetics*; D014771:Virion / Q000235:genetics; D014779:Virus Replication / Q000235:genetics
chemical_list: D012367:RNA, Viral