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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Host population and phage population time courses.(A) Dynamic time courses of experimental host population data uninfected (line is mean of n = 2) and infected cultures (line is mean of n = 3); an immediate drop in population density occurs when the solution of phage is added at , due to dilution. Initial infection multiplicity was 0.1. (B) Measured and simulated phage production per infected host in tryptone broth media (circles are mean, error bars shown are the standard deviation, n = 3). Simulation presented for the integrated model and T7 ODEs alone simulated at . (C) Expanded comparison of the simulated concentrations of critical phage replication machinery and phage virion components compared to T7 ODEs alone. Gene Product 1 is the T7 RNA polymerase; Gene product 10A is the major capsid protein.
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pcbi-1002746-g003: Host population and phage population time courses.(A) Dynamic time courses of experimental host population data uninfected (line is mean of n = 2) and infected cultures (line is mean of n = 3); an immediate drop in population density occurs when the solution of phage is added at , due to dilution. Initial infection multiplicity was 0.1. (B) Measured and simulated phage production per infected host in tryptone broth media (circles are mean, error bars shown are the standard deviation, n = 3). Simulation presented for the integrated model and T7 ODEs alone simulated at . (C) Expanded comparison of the simulated concentrations of critical phage replication machinery and phage virion components compared to T7 ODEs alone. Gene Product 1 is the T7 RNA polymerase; Gene product 10A is the major capsid protein.

Mentions: To validate the ability of the model to predict infection phenotypes, we observed E. coli infection by T7 during growth on tryptone broth. We first measured the growth of E. coli cultures in the presence and absence of T7 (Figure 3A). The culture is cleared within 35 minutes, representing approximately two infection cycles at .


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

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

Host population and phage population time courses.(A) Dynamic time courses of experimental host population data uninfected (line is mean of n = 2) and infected cultures (line is mean of n = 3); an immediate drop in population density occurs when the solution of phage is added at , due to dilution. Initial infection multiplicity was 0.1. (B) Measured and simulated phage production per infected host in tryptone broth media (circles are mean, error bars shown are the standard deviation, n = 3). Simulation presented for the integrated model and T7 ODEs alone simulated at . (C) Expanded comparison of the simulated concentrations of critical phage replication machinery and phage virion components compared to T7 ODEs alone. Gene Product 1 is the T7 RNA polymerase; Gene product 10A is the major capsid protein.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1002746-g003: Host population and phage population time courses.(A) Dynamic time courses of experimental host population data uninfected (line is mean of n = 2) and infected cultures (line is mean of n = 3); an immediate drop in population density occurs when the solution of phage is added at , due to dilution. Initial infection multiplicity was 0.1. (B) Measured and simulated phage production per infected host in tryptone broth media (circles are mean, error bars shown are the standard deviation, n = 3). Simulation presented for the integrated model and T7 ODEs alone simulated at . (C) Expanded comparison of the simulated concentrations of critical phage replication machinery and phage virion components compared to T7 ODEs alone. Gene Product 1 is the T7 RNA polymerase; Gene product 10A is the major capsid protein.
Mentions: To validate the ability of the model to predict infection phenotypes, we observed E. coli infection by T7 during growth on tryptone broth. We first measured the growth of E. coli cultures in the presence and absence of T7 (Figure 3A). The culture is cleared within 35 minutes, representing approximately two infection cycles at .

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