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Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism.

Vital-Lopez FG, Reifman J, Wallqvist A - PLoS Comput. Biol. (2015)

Bottom Line: Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules.Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants.Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm metabolism.

View Article: PubMed Central - PubMed

Affiliation: Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.

ABSTRACT
A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm-based infections that are difficult to eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic cells. Developing treatments against biofilms requires an understanding of bacterial biofilm-specific physiological traits. Research efforts have started to elucidate the intricate mechanisms underlying biofilm development. However, many aspects of these mechanisms are still poorly understood. Here, we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles. Specifically, we computed metabolite concentration differences between known mutants with altered biofilm formation and the wild-type strain to predict drug targets against P. aeruginosa biofilms. We also simulated the altered metabolism driven by gene expression changes between biofilm and stationary growth-phase planktonic cultures. Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we investigated why mutants defective in anthranilate degradation have an impaired ability to form biofilms. Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants. Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm metabolism. Our simulation results showed that plausible, non-intuitive explanations of difficult-to-interpret experimental observations could be generated by integrating genome-scale kinetic models with gene expression profiles.

No MeSH data available.


Related in: MedlinePlus

Coordinated regulation of Psl synthesis.(A) Sketch of the metabolic pathways involved in the increase of Psl and Pel production rates in our simulations. The figure shows the genes associated with the nine reactions that had the highest effect on Psl production. The number to the left of each gene name denotes the rank of the corresponding reaction. The number in parentheses denotes the overall gene expression ratio between the biofilm and the stationary cultures. The numbers to the left and right of the vertical bar denote the median flux ratios of the reactions associated with the genes in simulation with or without the gene expression ratios of the genes accABCD, fabD, purADF, pgl, edd, gcd, and rmlA. Only psl, pel, and those genes whose regulation contributes to increasing Psl and Pel production are shown. (B) Correlation between the expression of the genes that contribute to increasing Psl production and the psl operon genes for biofilm and stationary cultures. Solid and dashed arrows indicate single and multiple reaction steps in the model, respectively.
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pcbi.1004452.g003: Coordinated regulation of Psl synthesis.(A) Sketch of the metabolic pathways involved in the increase of Psl and Pel production rates in our simulations. The figure shows the genes associated with the nine reactions that had the highest effect on Psl production. The number to the left of each gene name denotes the rank of the corresponding reaction. The number in parentheses denotes the overall gene expression ratio between the biofilm and the stationary cultures. The numbers to the left and right of the vertical bar denote the median flux ratios of the reactions associated with the genes in simulation with or without the gene expression ratios of the genes accABCD, fabD, purADF, pgl, edd, gcd, and rmlA. Only psl, pel, and those genes whose regulation contributes to increasing Psl and Pel production are shown. (B) Correlation between the expression of the genes that contribute to increasing Psl production and the psl operon genes for biofilm and stationary cultures. Solid and dashed arrows indicate single and multiple reaction steps in the model, respectively.

Mentions: Fig 2 also shows that the expression of the genes involved in the synthesis of Psl (psl genes) and Pel (pel genes), the two major exopolysaccharides forming the extracellular matrix in biofilms of the PAO1 strain [34], was correlated with the biofilm age, although with opposing signs. This is consistent with the observation that P. aeruginosa strains produce predominantly one polysaccharide at any given time [35]. But unexpectedly, the psl and pel genes were not up-regulated in the biofilm compared with the stationary culture in the study by Costaglioli et al. [11]. A possible explanation for this observation could be that most of the nutrients in the medium have been consumed after 24 h and the synthesis of exopolysaccharides has been stalled in both cultures. Nonetheless, our simulations predicted that there was an increase in the synthesis rate of Psl (median flux ratio = 2.87, minimum flux ratio = 1.22) in the biofilm with respect to the stationary culture. There was also an increase, although small, in the Pel synthesis (median flux ratio = 1.53, minimum flux ratio = 1.32). To understand what caused this result in our simulations, we evaluated the effect of the overall gene expression change of each reaction on the predicted Psl synthesis rate (see Materials and Methods). We found that the increase in Psl synthesis was mainly caused by the down-regulation of a few reactions in pathways competing for Psl precursors. Fig 3A shows a sketch of the pathways associated with the increase in the synthesis of Psl. This figure also shows the genes associated with the nine reactions that had the highest effect on Psl production (the addition of more reactions did not have a significant effect), as well as the predicted median flux ratios in simulations with or without the gene expression changes of all of these genes. Psl production was increased by down-regulating the genes of seven of these reactions (although only two of them, purD and purF, by more than two-fold) and the other two reactions had a gene expression ratio only slightly higher than 1.0 (gcd and rmlA). Interestingly, the sensitivity of the nine reactions coincided with the correlation between their gene expression and the expression of the Psl pathway genes in the datasets obtained from the GEO database (Fig 3B). In other words, the gene expression of the reactions whose down-regulation increased Psl synthesis had a negative correlation with the gene expression of the Psl pathway, whereas the reactions whose up-regulation increased Psl synthesis had a positive correlation. Notably, with the exception of gcd (PA2290), the opposite was observed in planktonic cultures: the gene expression of the reactions whose down-regulation increased Psl synthesis had a positive correlation with the gene expression of the Psl pathway, whereas the reactions whose up-regulation increased Psl synthesis had a negative correlation (Fig 3B). This result led to the hypothesis that P. aeruginosa may increase the production of Psl (and possibly Pel) by not only regulating the genes in their synthesis pathways, but by down-regulating pathways competing for Psl precursors in a biofilm-specific manner.


Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism.

Vital-Lopez FG, Reifman J, Wallqvist A - PLoS Comput. Biol. (2015)

Coordinated regulation of Psl synthesis.(A) Sketch of the metabolic pathways involved in the increase of Psl and Pel production rates in our simulations. The figure shows the genes associated with the nine reactions that had the highest effect on Psl production. The number to the left of each gene name denotes the rank of the corresponding reaction. The number in parentheses denotes the overall gene expression ratio between the biofilm and the stationary cultures. The numbers to the left and right of the vertical bar denote the median flux ratios of the reactions associated with the genes in simulation with or without the gene expression ratios of the genes accABCD, fabD, purADF, pgl, edd, gcd, and rmlA. Only psl, pel, and those genes whose regulation contributes to increasing Psl and Pel production are shown. (B) Correlation between the expression of the genes that contribute to increasing Psl production and the psl operon genes for biofilm and stationary cultures. Solid and dashed arrows indicate single and multiple reaction steps in the model, respectively.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4592021&req=5

pcbi.1004452.g003: Coordinated regulation of Psl synthesis.(A) Sketch of the metabolic pathways involved in the increase of Psl and Pel production rates in our simulations. The figure shows the genes associated with the nine reactions that had the highest effect on Psl production. The number to the left of each gene name denotes the rank of the corresponding reaction. The number in parentheses denotes the overall gene expression ratio between the biofilm and the stationary cultures. The numbers to the left and right of the vertical bar denote the median flux ratios of the reactions associated with the genes in simulation with or without the gene expression ratios of the genes accABCD, fabD, purADF, pgl, edd, gcd, and rmlA. Only psl, pel, and those genes whose regulation contributes to increasing Psl and Pel production are shown. (B) Correlation between the expression of the genes that contribute to increasing Psl production and the psl operon genes for biofilm and stationary cultures. Solid and dashed arrows indicate single and multiple reaction steps in the model, respectively.
Mentions: Fig 2 also shows that the expression of the genes involved in the synthesis of Psl (psl genes) and Pel (pel genes), the two major exopolysaccharides forming the extracellular matrix in biofilms of the PAO1 strain [34], was correlated with the biofilm age, although with opposing signs. This is consistent with the observation that P. aeruginosa strains produce predominantly one polysaccharide at any given time [35]. But unexpectedly, the psl and pel genes were not up-regulated in the biofilm compared with the stationary culture in the study by Costaglioli et al. [11]. A possible explanation for this observation could be that most of the nutrients in the medium have been consumed after 24 h and the synthesis of exopolysaccharides has been stalled in both cultures. Nonetheless, our simulations predicted that there was an increase in the synthesis rate of Psl (median flux ratio = 2.87, minimum flux ratio = 1.22) in the biofilm with respect to the stationary culture. There was also an increase, although small, in the Pel synthesis (median flux ratio = 1.53, minimum flux ratio = 1.32). To understand what caused this result in our simulations, we evaluated the effect of the overall gene expression change of each reaction on the predicted Psl synthesis rate (see Materials and Methods). We found that the increase in Psl synthesis was mainly caused by the down-regulation of a few reactions in pathways competing for Psl precursors. Fig 3A shows a sketch of the pathways associated with the increase in the synthesis of Psl. This figure also shows the genes associated with the nine reactions that had the highest effect on Psl production (the addition of more reactions did not have a significant effect), as well as the predicted median flux ratios in simulations with or without the gene expression changes of all of these genes. Psl production was increased by down-regulating the genes of seven of these reactions (although only two of them, purD and purF, by more than two-fold) and the other two reactions had a gene expression ratio only slightly higher than 1.0 (gcd and rmlA). Interestingly, the sensitivity of the nine reactions coincided with the correlation between their gene expression and the expression of the Psl pathway genes in the datasets obtained from the GEO database (Fig 3B). In other words, the gene expression of the reactions whose down-regulation increased Psl synthesis had a negative correlation with the gene expression of the Psl pathway, whereas the reactions whose up-regulation increased Psl synthesis had a positive correlation. Notably, with the exception of gcd (PA2290), the opposite was observed in planktonic cultures: the gene expression of the reactions whose down-regulation increased Psl synthesis had a positive correlation with the gene expression of the Psl pathway, whereas the reactions whose up-regulation increased Psl synthesis had a negative correlation (Fig 3B). This result led to the hypothesis that P. aeruginosa may increase the production of Psl (and possibly Pel) by not only regulating the genes in their synthesis pathways, but by down-regulating pathways competing for Psl precursors in a biofilm-specific manner.

Bottom Line: Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules.Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants.Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm metabolism.

View Article: PubMed Central - PubMed

Affiliation: Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America.

ABSTRACT
A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm-based infections that are difficult to eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic cells. Developing treatments against biofilms requires an understanding of bacterial biofilm-specific physiological traits. Research efforts have started to elucidate the intricate mechanisms underlying biofilm development. However, many aspects of these mechanisms are still poorly understood. Here, we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles. Specifically, we computed metabolite concentration differences between known mutants with altered biofilm formation and the wild-type strain to predict drug targets against P. aeruginosa biofilms. We also simulated the altered metabolism driven by gene expression changes between biofilm and stationary growth-phase planktonic cultures. Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we investigated why mutants defective in anthranilate degradation have an impaired ability to form biofilms. Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants. Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm metabolism. Our simulation results showed that plausible, non-intuitive explanations of difficult-to-interpret experimental observations could be generated by integrating genome-scale kinetic models with gene expression profiles.

No MeSH data available.


Related in: MedlinePlus