The effect of viral plasticity on the persistence of host-virus systems

Disentangling top-down drivers of mortality underlying diel population dynamics of Prochlorococcus in the North Pacific Subtropical Gyre

Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. We find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics.

Phenotypic flux: The role of physiology in explaining the conundrum of bacterial persistence amid phage attack

Bacteriophages, the viruses of bacteria, have been studied for over a century. They were not only instrumental in laying the foundations of molecular biology, but they are also likely to play crucial roles in shaping our biosphere and may offer a solution to the control of drug-resistant bacterial infections. However, it remains challenging to predict the conditions for bacterial eradication by phage predation, sometimes even under well-defined laboratory conditions, and, most curiously, if the majority of surviving cells are genetically phage-susceptible. Here, I propose that even clonal phage and bacterial populations are generally in a state of continuous 'phenotypic flux', which is caused by transient and nongenetic variation in phage and bacterial physiology. Phenotypic flux can shape phage infection dynamics by reducing the force of infection to an extent that allows for coexistence between phages and susceptible bacteria. Understanding the mechanisms and impact of phenotypic flux may be key to providing a complete picture of phage-bacteria coexistence. I review the empirical evidence for phenotypic variation in phage and bacterial physiology together with the ways they have been modeled and discuss the potential implications of phenotypic flux for ecological and evolutionary dynamics between phages and bacteria, as well as for phage therapy.

Unconstrained coevolution of bacterial size and the latent period of plastic phage

Viruses play critical roles in the dynamics of microbial communities. Lytic viruses, for example, kill significant fractions of autotrophic and heterotrophic microbes daily. The dynamic interplay between viruses and microbes results from an overlap of physiological, ecological, and evolutionary responses: environmental changes trigger host physiological changes, affecting the ecological interactions of host and virus and, ultimately, the evolutionary pressures influencing the two populations. Recent theoretical work studied how the dependence of viral traits on host physiology (viral plasticity) affects the evolutionarily stable host cell size and viral infection time emerging from coevolution. Here, we broaden the scope of the framework to consider any coevolutionary outcome, including potential evolutionary collapses of the system. We used the case study of Escherichia coli and T-like viruses under chemostat conditions, but the framework can be adapted to any microbe-virus system. Oligotrophic conditions led to smaller, lower-quality but more abundant hosts, and infections that were longer but produced a reduced viral offspring. Conversely, eutrophic conditions resulted in fewer but larger higher-quality hosts, and shorter but more productive infections. The virus influenced host evolution decreasing host size more noticeably for low than for high dilution rates, and for high than for low nutrient input concentration. For low dilution rates, the emergent infection time minimized host need/use, but higher dilution led to an opportunistic strategy that shortened the duration of infections. System collapses driven by evolution resulted from host failure to adapt quickly enough to the evolving virus. Our results contribute to understanding the eco-evolutionary dynamics of microbes and virus, and to improving the predictability of current models for host-virus interactions. The large quantitative and qualitative differences observed with respect to a classic description (in which viral traits are assumed to be constant) highlights the importance of including viral plasticity in theories describing short- and long-term host-virus dynamics.

Parameter Estimation in the Age of Degeneracy and Unidentifiability

Parameter estimation from observable or experimental data is a crucial stage in any modeling study. Identifiability refers to one’s ability to uniquely estimate the model parameters from the available data. Structural unidentifiability in dynamic models, the opposite of identifiability, is associated with the notion of degeneracy where multiple parameter sets produce the same pattern. Therefore, the inverse function of determining the model parameters from the data is not well defined. Degeneracy is not only a mathematical property of models, but it has also been reported in biological experiments. Classical studies on structural unidentifiability focused on the notion that one can at most identify combinations of unidentifiable model parameters. We have identified a different type of structural degeneracy/unidentifiability present in a family of models, which we refer to as the Lambda-Omega (Λ-Ω) models. These are an extension of the classical lambda-omega (λ-ω) models that have been used to model biological systems, and display a richer dynamic behavior and waveforms that range from sinusoidal to square wave to spike like. We show that the Λ-Ω models feature infinitely many parameter sets that produce identical stable oscillations, except possible for a phase shift (reflecting the initial phase). These degenerate parameters are not identifiable combinations of unidentifiable parameters as is the case in structural degeneracy. In fact, reducing the number of model parameters in the Λ-Ω models is minimal in the sense that each one controls a different aspect of the model dynamics and the dynamic complexity of the system would be reduced by reducing the number of parameters. We argue that the family of Λ-Ω models serves as a framework for the systematic investigation of degeneracy and identifiability in dynamic models and for the investigation of the interplay between structural and other forms of unidentifiability resulting on the lack of information from the experimental/observational data.

Towards an integrative view of virus phenotypes

Understanding how phenotypes emerge from genotypes is a foundational goal in biology. As challenging as this task is when considering cellular life, it is further complicated in the case of viruses. During replication, a virus as a discrete entity (the virion) disappears and manifests itself as a metabolic amalgam between the virus and the host (the virocell). Identifying traits that unambiguously constitute a virus's phenotype is straightforward for the virion, less so for the virocell. Here, we present a framework for categorizing virus phenotypes that encompasses both virion and virocell stages and considers functional and performance traits of viruses in the context of fitness. Such an integrated view of virus phenotype is necessary for comprehensive interpretation of viral genome sequences and will advance our understanding of viral evolution and ecology.

A Rapid Method for Performing a Multivariate Optimization of Phage Production Using the RCCD Approach

Bacteriophages can be used in various applications, from the classical approach as substitutes for antibiotics (phage therapy) to new biotechnological uses, i.e., as a protein delivery vehicle, a diagnostic tool for specific strains of bacteria (phage typing), or environmental bioremediation. The demand for bacteriophage production increases daily, and studies that improve these production processes are necessary. This study evaluated the production of a T4-like bacteriophage vB_EcoM-UFV09 (an E. coli-infecting phage with high potential for reducing environmental biofilms) in seven types of culture media (Luria-Bertani broth and the M9 minimal medium with six different carbon sources) employing four cultivation variables (temperature, incubation time, agitation, and multiplicity of infection). For this purpose, the rotatable central composite design (RCCD) methodology was used, combining and comparing all parameters to determine the ideal conditions for starting to scale up the production process. We used the RCCD to set up the experimental design by combining the cultivation parameters in a specific and systematic way. Despite the high number of conditions evaluated, the results showed that when specific conditions were utilized, viral production was effective even when using a minimal medium, such as M9/glucose, which is less expensive and can significantly reduce costs during large-scale phage production.

Evolutionarily Stable Coevolution Between a Plastic Lytic Virus and Its Microbial Host

Hosts influence and are influenced by viral replication. Cell size, for example, is a fundamental trait for microbial hosts that can not only alter the probability of viral adsorption, but also constrain the host physiological processes that the virus relies on to replicate. This intrinsic connection can affect the fitness of both host and virus, and therefore their mutual evolution. Here, we study the coevolution of bacterial hosts and their viruses by considering the dependence of viral performance on the host physiological state (viral plasticity). To this end, we modified a standard host-lytic phage model to include viral plasticity, and compared the coevolutionary strategies emerging under different scenarios, including cases in which only the virus or the host evolve. For all cases, we also obtained the evolutionary prediction of the traditional version of the model, which assumes a non-plastic virus. Our results reveal that the presence of the virus leads to an increase in host size and growth rate in the long term, which benefits both interacting populations. Our results also show that viral plasticity and evolution influence the classic host quality-quantity trade-off. Poor nutrient environments lead to abundant low-quality hosts, which tends to increase viral infection time. Conversely, richer nutrient environments lead to fewer but high-quality hosts, which decrease viral infection time. Our results can contribute to advancing our understanding of the microbial response to changing environments. For instance, both cell size and viral-induced mortality are essential factors that determine the structure and dynamics of the marine microbial community, and therefore our study can improve predictions of how marine ecosystems respond to environmental change. Our study can also help devise more reliable strategies to use phage to, for example, fight bacterial infections.