Maximizing yields of virulent phage: The T4/Escherichia coli system as a test case

Aviram, I.; Rabinovitch, A.; Zaritsky, Arieh

doi:10.1016/j.jtbi.2014.09.020

Cited by 2 publications

(2 citation statements)

References 27 publications

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“…On the other hand, optimal (i.e., fitnessmaximizing) latent periods have been estimated using fixed viral traits and/or fixed host concentrations accounting for host quality (Wang et al 1996;Abedon et al 2001), although decoupling host growth rate and density precludes these calculations from predicting the dynamics of the system. Dynamic models have attempted to include plasticity using density-dependent lysis rates instead of latent periods (Weitz and Dushoff 2008), different fixed trait values for different fixed host growth rates (Middelboe 2000), phenomenological expressions (Edwards and Steward 2018), or case-specific effective expressions (Rabinovitch et al 2002) aimed at improving the design of one-step growth experiments (Aviram et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Ecological and Evolutionary Consequences of Viral Plasticity

Choua

Bonachela

2019

The American Naturalist

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Viruses use the host machinery to replicate, and their performance thus depends on the host's physiological state. For bacteriophages, this link between host and viral performance has been characterized empirically and with intracellular theories. Such theories are too detailed to be included in models that study host-phage interactions in the long term, which hinders our understanding of systems that range from pathogens infecting gut bacteria to marine phage shaping the oceans. Here, we combined data and models to study the short-and long-term consequences that host physiology has on bacteriophage performance. We compiled data showing the dependence of lytic-phage traits on host growth rate (referred to as viral phenotypic plasticity) to deduce simple expressions that represent such plasticity. Including these expressions in a standard host-phage model allowed us to understand mechanistically how viral plasticity affects emergent evolutionary strategies and the population dynamics associated with different environmental scenarios including, for example, nutrient pulses or host starvation. Moreover, we show that plasticity on the offspring number drives the phage ecological and evolutionary dynamics by reinforcing feedbacks between host, virus, and environment. Standard models neglect viral plasticity, which therefore handicaps their predictive ability in realistic scenarios. Our results highlight the importance of viral plasticity to unravel host-phage interactions and the need of laboratory and field experiments to characterize viral plastic responses across systems.

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Section: Introductionmentioning

confidence: 99%

Ecological and Evolutionary Consequences of Viral Plasticity

Choua

Bonachela

2019

The American Naturalist

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“…fitness maximizing) latent periods 84 have been estimated using fixed viral traits and/or fixed host concentrations accounting for host quality (Abedon et al, 2001;Wang et al, 1996), although decoupling host growth rate and density precludes these calculations from predicting the dynamics of the system. Dynamic-model attempts 87 to include plasticity used different fixed trait values for different host growth rates (Middelboe, 2000), or case-specific effective expressions (Rabinovitch et al, 2002) aimed to improve the design of one-step growth experiments (Aviram et al, 2015). 90 Therefore, past experiments and theories advanced knowledge on how the host growth rate affects phage development; however, how such a link affects the ecological and evolutionary dynamics of the phage-host system remains largely unknown.…”

Section: Introductionmentioning

confidence: 99%

Ecological and evolutionary consequences of viral plasticity

Choua

Bonachela

2018

Preprint

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Viruses can infect any organism. Because viruses use the host machinery to replicate, their performance depends on the host physiological state. For bacteriophages, this host-viral performance 3 link has been characterized empirically and with intracellular theories. Such theories are too detailed to be included in models that study host-phage interactions in the long term, which hinders our understanding of systems that range from pathogens infecting gut bacteria to marine phage 6 shaping present and future oceans. Here, we combined data and models to study the short-and long-term consequences that host physiology has on bacteriophage performance. We compiled data showing the dependence of lytic-phage traits on host growth rate (viral phenotypic "plasticity") to 9 deduce simple expressions representing such plasticity. We included these expressions in a standard host-phage model, to understand how viral plasticity can break the expected evolutionary trade-off between infection time and viral offspring number. Furthermore, viral plasticity influences dramat-12 ically dynamic scenarios (e.g. sudden nutrient pulses or host starvation). We show that the effect of plasticity on offspring number, not generation time, drives the phage ecological and evolutionary dynamics. Standard models do not account for this plasticity, which handicaps their predictability 15 in realistic environments. Our results highlight the importance of viral plasticity to unravel hostphage interactions, and the need of laboratory and field experiments to characterize viral plastic responses across systems. 182 not peer-reviewed)

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Maximizing yields of virulent phage: The T4/Escherichia coli system as a test case

Cited by 2 publications

References 27 publications

Ecological and Evolutionary Consequences of Viral Plasticity

Ecological and Evolutionary Consequences of Viral Plasticity

Ecological and evolutionary consequences of viral plasticity

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