Limits...
Determining host metabolic limitations on viral replication via integrated modeling and experimental perturbation.

Birch EW, Ruggero NA, Covert MW - PLoS Comput. Biol. (2012)

Bottom Line: The level of detail of our computational predictions facilitates exploration of the dynamic changes in host metabolic fluxes that result from viral resource consumption, as well as analysis of the limiting processes dictating maximum viral progeny production.For example, although it is commonly assumed that viral infection dynamics are predominantly limited by the amount of protein synthesis machinery in the host, our results suggest that in many cases metabolic limitation is at least as strict.Taken together, these results emphasize the importance of considering viral infections in the context of host metabolism.

View Article: PubMed Central - PubMed

Affiliation: Chemical Engineering, Stanford University, Stanford, CA, USA.

ABSTRACT
Viral replication relies on host metabolic machinery and precursors to produce large numbers of progeny - often very rapidly. A fundamental example is the infection of Escherichia coli by bacteriophage T7. The resource draw imposed by viral replication represents a significant and complex perturbation to the extensive and interconnected network of host metabolic pathways. To better understand this system, we have integrated a set of structured ordinary differential equations quantifying T7 replication and an E. coli flux balance analysis metabolic model. Further, we present here an integrated simulation algorithm enforcing mutual constraint by the models across the entire duration of phage replication. This method enables quantitative dynamic prediction of virion production given only specification of host nutritional environment, and predictions compare favorably to experimental measurements of phage replication in multiple environments. The level of detail of our computational predictions facilitates exploration of the dynamic changes in host metabolic fluxes that result from viral resource consumption, as well as analysis of the limiting processes dictating maximum viral progeny production. For example, although it is commonly assumed that viral infection dynamics are predominantly limited by the amount of protein synthesis machinery in the host, our results suggest that in many cases metabolic limitation is at least as strict. Taken together, these results emphasize the importance of considering viral infections in the context of host metabolism.

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Variation in the limiting factor for phage production across host growth rates.Modeling results overlaid with experimental phage production measurements. The machinery-feasible region represents phage production values from T7 ODEs alone, with the growth rate supplied to correlations for availability of the host replication machinery; phage production values above the machinery-feasible boundary are considered machinery infeasible. The upper boundary of the metabolically feasible region was calculated using the integrated simulation, but with access to excess host replication factors, which we simulated by multiplying the host growth rate from FBA by a factor of 1.25 when it was passed to the T7 ODE host machinery correlations. Growth rate variation for calculating limitation boundaries and integrated simulation was evaluated with a set of modified flux bounds, with most growth rate sampling values simulated with both carbon and oxygen limitation, which produced essentially identical phage production predictions (resulting points lie within width of the line displayed). Error bars are standard deviation of n = 3.
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pcbi-1002746-g007: Variation in the limiting factor for phage production across host growth rates.Modeling results overlaid with experimental phage production measurements. The machinery-feasible region represents phage production values from T7 ODEs alone, with the growth rate supplied to correlations for availability of the host replication machinery; phage production values above the machinery-feasible boundary are considered machinery infeasible. The upper boundary of the metabolically feasible region was calculated using the integrated simulation, but with access to excess host replication factors, which we simulated by multiplying the host growth rate from FBA by a factor of 1.25 when it was passed to the T7 ODE host machinery correlations. Growth rate variation for calculating limitation boundaries and integrated simulation was evaluated with a set of modified flux bounds, with most growth rate sampling values simulated with both carbon and oxygen limitation, which produced essentially identical phage production predictions (resulting points lie within width of the line displayed). Error bars are standard deviation of n = 3.

Mentions: The boundary representing machinery limitations is provided by evaluation of the T7 ODEs alone across varied input growth rates (Figure 7). The region that falls below the model prediction is feasible (dark gray), and everything above is not (light gray). To calculate the bounding metabolic phage production limitation, we simulated the integrated model with the modification that excess host replication machinery components were provided to the ODE model (accomplished by passing a higher host growth rate to the ODEs than that predicted by FBA). This calculation was carried out for carbon- and oxygen-limited growth at each resulting growth rate, which resulted in uniform predictions of phage production at each growth rate. Metabolic feasibility here refers to the supply of small molecule metabolites needed to build phage virions; the metabolic limit increases smoothly with host growth rate because the phage is made of a subset of the metabolites included in the host biomass reaction that represents FBA growth, and a state of host growth maximization is assumed for host supply. This context reveals the integrated model to be slightly mechanistically limited over the range of growth rates between approximately 0.4/hour and 1/hour, and more severely metabolically limited at higher and lower growth rates; however, simulations at very low growth rates do produce empty capsids, reflecting the strong repression of virion DNA production encoded in the ODEs. Metabolic limitation at high and low growth rates explains the better performance of the integrated model than the T7 ODEs alone in predicting phage production on acetate and tryptone media (Figure 3 and 5 respectively).


Determining host metabolic limitations on viral replication via integrated modeling and experimental perturbation.

Birch EW, Ruggero NA, Covert MW - PLoS Comput. Biol. (2012)

Variation in the limiting factor for phage production across host growth rates.Modeling results overlaid with experimental phage production measurements. The machinery-feasible region represents phage production values from T7 ODEs alone, with the growth rate supplied to correlations for availability of the host replication machinery; phage production values above the machinery-feasible boundary are considered machinery infeasible. The upper boundary of the metabolically feasible region was calculated using the integrated simulation, but with access to excess host replication factors, which we simulated by multiplying the host growth rate from FBA by a factor of 1.25 when it was passed to the T7 ODE host machinery correlations. Growth rate variation for calculating limitation boundaries and integrated simulation was evaluated with a set of modified flux bounds, with most growth rate sampling values simulated with both carbon and oxygen limitation, which produced essentially identical phage production predictions (resulting points lie within width of the line displayed). Error bars are standard deviation of n = 3.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475664&req=5

pcbi-1002746-g007: Variation in the limiting factor for phage production across host growth rates.Modeling results overlaid with experimental phage production measurements. The machinery-feasible region represents phage production values from T7 ODEs alone, with the growth rate supplied to correlations for availability of the host replication machinery; phage production values above the machinery-feasible boundary are considered machinery infeasible. The upper boundary of the metabolically feasible region was calculated using the integrated simulation, but with access to excess host replication factors, which we simulated by multiplying the host growth rate from FBA by a factor of 1.25 when it was passed to the T7 ODE host machinery correlations. Growth rate variation for calculating limitation boundaries and integrated simulation was evaluated with a set of modified flux bounds, with most growth rate sampling values simulated with both carbon and oxygen limitation, which produced essentially identical phage production predictions (resulting points lie within width of the line displayed). Error bars are standard deviation of n = 3.
Mentions: The boundary representing machinery limitations is provided by evaluation of the T7 ODEs alone across varied input growth rates (Figure 7). The region that falls below the model prediction is feasible (dark gray), and everything above is not (light gray). To calculate the bounding metabolic phage production limitation, we simulated the integrated model with the modification that excess host replication machinery components were provided to the ODE model (accomplished by passing a higher host growth rate to the ODEs than that predicted by FBA). This calculation was carried out for carbon- and oxygen-limited growth at each resulting growth rate, which resulted in uniform predictions of phage production at each growth rate. Metabolic feasibility here refers to the supply of small molecule metabolites needed to build phage virions; the metabolic limit increases smoothly with host growth rate because the phage is made of a subset of the metabolites included in the host biomass reaction that represents FBA growth, and a state of host growth maximization is assumed for host supply. This context reveals the integrated model to be slightly mechanistically limited over the range of growth rates between approximately 0.4/hour and 1/hour, and more severely metabolically limited at higher and lower growth rates; however, simulations at very low growth rates do produce empty capsids, reflecting the strong repression of virion DNA production encoded in the ODEs. Metabolic limitation at high and low growth rates explains the better performance of the integrated model than the T7 ODEs alone in predicting phage production on acetate and tryptone media (Figure 3 and 5 respectively).

Bottom Line: The level of detail of our computational predictions facilitates exploration of the dynamic changes in host metabolic fluxes that result from viral resource consumption, as well as analysis of the limiting processes dictating maximum viral progeny production.For example, although it is commonly assumed that viral infection dynamics are predominantly limited by the amount of protein synthesis machinery in the host, our results suggest that in many cases metabolic limitation is at least as strict.Taken together, these results emphasize the importance of considering viral infections in the context of host metabolism.

View Article: PubMed Central - PubMed

Affiliation: Chemical Engineering, Stanford University, Stanford, CA, USA.

ABSTRACT
Viral replication relies on host metabolic machinery and precursors to produce large numbers of progeny - often very rapidly. A fundamental example is the infection of Escherichia coli by bacteriophage T7. The resource draw imposed by viral replication represents a significant and complex perturbation to the extensive and interconnected network of host metabolic pathways. To better understand this system, we have integrated a set of structured ordinary differential equations quantifying T7 replication and an E. coli flux balance analysis metabolic model. Further, we present here an integrated simulation algorithm enforcing mutual constraint by the models across the entire duration of phage replication. This method enables quantitative dynamic prediction of virion production given only specification of host nutritional environment, and predictions compare favorably to experimental measurements of phage replication in multiple environments. The level of detail of our computational predictions facilitates exploration of the dynamic changes in host metabolic fluxes that result from viral resource consumption, as well as analysis of the limiting processes dictating maximum viral progeny production. For example, although it is commonly assumed that viral infection dynamics are predominantly limited by the amount of protein synthesis machinery in the host, our results suggest that in many cases metabolic limitation is at least as strict. Taken together, these results emphasize the importance of considering viral infections in the context of host metabolism.

Show MeSH
Related in: MedlinePlus