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Metabolic investigation of host/pathogen interaction using MS2-infected Escherichia coli.

Jain R, Srivastava R - BMC Syst Biol (2009)

Bottom Line: Also, no changes were predicted in the glycolytic pathway.These studies may provide insight into how to design better drugs.They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Chemical, Materials and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. jainr@ornl.gov

ABSTRACT

Background: RNA viruses are responsible for a variety of illnesses among people, including but not limited to the common cold, the flu, HIV, and ebola. Developing new drugs and new strategies for treating diseases caused by these viruses can be an expensive and time-consuming process. Mathematical modeling may be used to elucidate host-pathogen interactions and highlight potential targets for drug development, as well providing the basis for optimizing patient treatment strategies. The purpose of this work was to determine whether a genome-scale modeling approach could be used to understand how metabolism is impacted by the host-pathogen interaction during a viral infection. Escherichia coli/MS2 was used as the host-pathogen model system as MS2 is easy to work with, harmless to humans, but shares many features with eukaryotic viruses. In addition, the genome-scale metabolic model of E. coli is the most comprehensive model at this time.

Results: Employing a metabolic modeling strategy known as "flux balance analysis" coupled with experimental studies, we were able to predict how viral infection would alter bacterial metabolism. Based on our simulations, we predicted that cell growth and biosynthesis of the cell wall would be halted. Furthermore, we predicted a substantial increase in metabolic activity of the pentose phosphate pathway as a means to enhance viral biosynthesis, while a break down in the citric acid cycle was predicted. Also, no changes were predicted in the glycolytic pathway.

Conclusions: Through our approach, we have developed a technique of modeling virus-infected host metabolism and have investigated the metabolic effects of viral infection. These studies may provide insight into how to design better drugs. They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.

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Comparison of the biosynthesis of amino acids in a MS2 phage-infected Escherichia coli cell with an uninfected Escherichia coli cell. Little change to a five-fold increase was seen although aspartate (D), glutamine (Q), glycine (G) and serine (S) biosynthesis rates decreased by as much as two-fold. The x-axis labels represent the single letter amino acid abbreviations, a key for which is available at http://en.wikipedia.org/wiki/Amino_acid. Figure legend text.
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Figure 1: Comparison of the biosynthesis of amino acids in a MS2 phage-infected Escherichia coli cell with an uninfected Escherichia coli cell. Little change to a five-fold increase was seen although aspartate (D), glutamine (Q), glycine (G) and serine (S) biosynthesis rates decreased by as much as two-fold. The x-axis labels represent the single letter amino acid abbreviations, a key for which is available at http://en.wikipedia.org/wiki/Amino_acid. Figure legend text.

Mentions: All metabolic resources were diverted to the biosynthesis of amino acids in the infected cells instead of the production of biomass as in the uninfected cells. Overall, there was anywhere from little change to a five-fold increase in the biosynthesis of amino acids except for aspartate (D), glutamine (Q), glycine (G) and serine (S) synthesis rates as shown in Figure 1. Biosynthesis of aspartate, glutamine, glycine and serine was downregulated as, in addition to protein synthesis, these amino acids also took part in the ATP biosynthesis that by itself was downregulated as a result of change in the objective of the metabolic network. Also, the pentose phosphate pathway was upregulated from anywhere between two-fold to 100-fold as shown in Figure 2.


Metabolic investigation of host/pathogen interaction using MS2-infected Escherichia coli.

Jain R, Srivastava R - BMC Syst Biol (2009)

Comparison of the biosynthesis of amino acids in a MS2 phage-infected Escherichia coli cell with an uninfected Escherichia coli cell. Little change to a five-fold increase was seen although aspartate (D), glutamine (Q), glycine (G) and serine (S) biosynthesis rates decreased by as much as two-fold. The x-axis labels represent the single letter amino acid abbreviations, a key for which is available at http://en.wikipedia.org/wiki/Amino_acid. Figure legend text.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2813233&req=5

Figure 1: Comparison of the biosynthesis of amino acids in a MS2 phage-infected Escherichia coli cell with an uninfected Escherichia coli cell. Little change to a five-fold increase was seen although aspartate (D), glutamine (Q), glycine (G) and serine (S) biosynthesis rates decreased by as much as two-fold. The x-axis labels represent the single letter amino acid abbreviations, a key for which is available at http://en.wikipedia.org/wiki/Amino_acid. Figure legend text.
Mentions: All metabolic resources were diverted to the biosynthesis of amino acids in the infected cells instead of the production of biomass as in the uninfected cells. Overall, there was anywhere from little change to a five-fold increase in the biosynthesis of amino acids except for aspartate (D), glutamine (Q), glycine (G) and serine (S) synthesis rates as shown in Figure 1. Biosynthesis of aspartate, glutamine, glycine and serine was downregulated as, in addition to protein synthesis, these amino acids also took part in the ATP biosynthesis that by itself was downregulated as a result of change in the objective of the metabolic network. Also, the pentose phosphate pathway was upregulated from anywhere between two-fold to 100-fold as shown in Figure 2.

Bottom Line: Also, no changes were predicted in the glycolytic pathway.These studies may provide insight into how to design better drugs.They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Chemical, Materials and Biomolecular Engineering, University of Connecticut, Storrs, CT 06269, USA. jainr@ornl.gov

ABSTRACT

Background: RNA viruses are responsible for a variety of illnesses among people, including but not limited to the common cold, the flu, HIV, and ebola. Developing new drugs and new strategies for treating diseases caused by these viruses can be an expensive and time-consuming process. Mathematical modeling may be used to elucidate host-pathogen interactions and highlight potential targets for drug development, as well providing the basis for optimizing patient treatment strategies. The purpose of this work was to determine whether a genome-scale modeling approach could be used to understand how metabolism is impacted by the host-pathogen interaction during a viral infection. Escherichia coli/MS2 was used as the host-pathogen model system as MS2 is easy to work with, harmless to humans, but shares many features with eukaryotic viruses. In addition, the genome-scale metabolic model of E. coli is the most comprehensive model at this time.

Results: Employing a metabolic modeling strategy known as "flux balance analysis" coupled with experimental studies, we were able to predict how viral infection would alter bacterial metabolism. Based on our simulations, we predicted that cell growth and biosynthesis of the cell wall would be halted. Furthermore, we predicted a substantial increase in metabolic activity of the pentose phosphate pathway as a means to enhance viral biosynthesis, while a break down in the citric acid cycle was predicted. Also, no changes were predicted in the glycolytic pathway.

Conclusions: Through our approach, we have developed a technique of modeling virus-infected host metabolism and have investigated the metabolic effects of viral infection. These studies may provide insight into how to design better drugs. They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.

Show MeSH
Related in: MedlinePlus