A touch of sleep: biophysical model of contact-mediated dormancy of archaea by viruses

Abstract

The canonical view of the interactions between viruses and their microbial hosts presumes that changes in host and virus fate requires the initiation of infection of a host by a virus. Infection may lead to the death of the host cell and release of viruses, to the elimination of the viral genome through cellular defence mechanisms or the integration of the viral genome with the host as a chromosomal or extrachromosomal element. Here, we revisit this canonical view, inspired by recent experimental findings in which the majority of target host cells can be induced into a dormant state when exposed to either active or deactivated viruses, even when viruses are present at low relative titre. We propose that both the qualitative phenomena and the quantitative timescales of dormancy induction are consistent with the hypothesis that cellular physiology can be altered by contact on the surface of host cells rather than strictly by infection In order to test this hypothesis, we develop and study a biophysical model of contact-mediated dynamics involving virus particles and target cells. We show how virus particles can catalyse cellular transformations among many cells, even if they ultimately infect only one (or none). We also find that population-scale dormancy is robust to variation in the representation of model dynamics, including cell growth, death and recovery.

Keywords: dormancy; microbes; nonlinear dynamics; viruses.

Figure 1.

Schematic of a biophysical model of virus–host interactions including susceptible microbial cells (S), complexes of a cell with a virus particle (C), cells with viral genomes (I), dormant cells (D) and free viruses (V). All populations are tracked in terms of densities of particles ml⁻¹.

Figure 2.

Dynamics of susceptible hosts, S(t), and free viruses, V(t), for the reduced model in equations (2.3) and (2.4) in three regimes: Ω > 0, Ω = 0 and Ω < 0 (top, middle and bottom, respectively). Common parameters for the dynamics are ϕ = 10⁻⁷ cells/(ml h⁻¹), δ = 4.5 and S₀ = 10⁷ cells ml⁻¹. The initial virus density is V₀ = 1.8 × 10⁵, 1.8 × 10⁶ and 3.5 × 10⁶ viruses ml⁻¹ in the top, middle and bottom panels, respectively.

Figure 3.

Asymptotic fraction of dormant and infected cells resulting from virus–host dynamics. (a) Final dormant cell fraction as a function of the initial ratio of viruses to hosts, V₀/S₀. (b) Final infected cell fraction as a function of the initial ratio of viruses to hosts, V₀/S₀. As shown, the final cell-state fractions depend on δ with qualitatively different responses as a function of the control parameter Ω. The fraction of dormant cells and infected cells increases linearly with V₀/S₀ so long as Ω > 0. When Ω < 0, then the fraction of dormant and infected cells is a constant, irrespective of V₀/S₀. Increases in δ lead to a relative increase in the proportion of dormant versus infected cells. Parameters are otherwise the same as in figure 2. (Online version in colour.)

Figure 4.

Ratio of the concentration of dormant cells at the end of the dynamics to the concentration of viruses at the start of the dynamics. The intensity values denote the ratio, . The solid line demarcates the boundary between ratios that exceed one (upper-left portion) and those that are less than one (remainder). (a) Population dormancy enhancement as a function of the probability of infection given contact, q, and the probability of dormancy-initiation given reversal of contact, p. Here, S₀ = 2.5 × 10⁸ cells ml⁻¹ and V₀ = S₀/100. (b) Population dormancy enhancement as a function of the initial virus–host ratio, V₀/S₀, and the cell fate ratio, δ ≈ p/q. Key point: the number of cells that enter dormancy per virus can be much greater than 1, even if the initial virus–host ratio is much smaller than 1.

Figure 5.

Dormancy induction at the populate scale given host demographic dynamics. (a) Dormant cell density fraction at time t with varying clearance rate γ. (b) Total cell density at time t with clearance (or recovery) rate γ In (a,b), the value of cell death rate μ is fixed as μ = 1/24(≈0.042). (c) The maximum dormant cell fraction with varying clearance rate γ, when μ = 0, 0.0417, 0.0833. Here, MOI is 0.04.

Figure 6.

Maximum dormancy fraction in a model with host demographics and virus decay. (a) The maximum dormancy fraction, is plotted as a function of V₀/S₀ for different values of δ. In each case, the expected domains of behaviour from the asymptotic model are denoted in terms of Ω. (b) Same data as in (a), but plotted with the re-scaled variables versus , where , and . Note that for purposes of visualizing the collapse, only a fraction of simulation results are displayed—all results correspond to the same collapse curve. Here, the parameters of the dynamic simulations are S₀ = 2 × 10⁸, ϕ = 2 × 10⁻⁹, μ = 1/24, γ = 1/72, d = 1/12, r = 0.23, K = 9 × 10⁸, all in units of hours and ml.