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Gram-negative and Gram-positive bacterial infections give rise to a different metabolic response in a mouse model.

Hoerr V, Zbytnuik L, Leger C, Tam PP, Kubes P, Vogel HJ - J. Proteome Res. (2012)

Bottom Line: In an attempt to develop a better understanding of the process of pathogenesis and the associated host response we have used a quantitative (1)H NMR approach to study the metabolic response to different bacterial infections.Multivariate statistical analysis revealed correlations between metabolic, cytokine and physiological responses.Since Gram-positive and Gram-negative bacteria activate different receptor pathways in the host, our results suggest that it may become possible in the future to use a metabolomics approach to improve on current clinical microbiology diagnostic methods.

View Article: PubMed Central - PubMed

Affiliation: Biochemistry Research Group, Department of Biological Sciences, ‡Department of Physiology and Biophysics, Snyder Institute, University of Calgary , Calgary, Alberta T2N 1N4, Canada.

ABSTRACT
Metabolomics has become an important tool to study host-pathogen interactions and to discover potential novel therapeutic targets. In an attempt to develop a better understanding of the process of pathogenesis and the associated host response we have used a quantitative (1)H NMR approach to study the metabolic response to different bacterial infections. Here we describe that metabolic changes found in serum of mice that were infected with Staphylococcus aureus, Streptococcus pneumoniae, Escherichia coli and Pseudomonas aeruginosa can distinguish between infections caused by Gram-positive and Gram-negative bacterial strains. By combining the results of the mouse study with those of bacterial footprinting culture experiments, bacterially secreted metabolites could be identified as potential bacterium-specific biomarkers for P. aeruginosa infections but not for the other strains. Multivariate statistical analysis revealed correlations between metabolic, cytokine and physiological responses. In TLR4 and TLR2 knockout mice, host-response pathway correlated metabolites could be identified and allowed us for the first time to distinguish between bacterial- and host-induced metabolic changes. Since Gram-positive and Gram-negative bacteria activate different receptor pathways in the host, our results suggest that it may become possible in the future to use a metabolomics approach to improve on current clinical microbiology diagnostic methods.

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Covariationbetween metabolic, physiological, and cytokine responses.Correlation circle (biplot, three components, R2 = 0.72, Q2 = 0.52)of the four bacterial infections (S. aureus, S. pneumoniae, E. coli, P. aeruginosa) in C57BL/6 wild-type mice, their metabolites (x-variables), as well as their physiological and immunological parameters(y-variables).
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fig8: Covariationbetween metabolic, physiological, and cytokine responses.Correlation circle (biplot, three components, R2 = 0.72, Q2 = 0.52)of the four bacterial infections (S. aureus, S. pneumoniae, E. coli, P. aeruginosa) in C57BL/6 wild-type mice, their metabolites (x-variables), as well as their physiological and immunological parameters(y-variables).

Mentions: To further investigate the covariation betweenmetabolite levels and host response, PLS regression analysis of allfour bacterial infections was performed using the physiological/immunologicalcharacteristics as y variables and metabolite concentrationsas x variables (three components, R2 = 0.72, Q2 =0.52). Several statistically significant correlations between physiologicaland immunological parameters and corresponding metabolite profilescould be derived (Figure 8). Besides well-knownpositive correlations between neutrophils and taurine41,42 and weight loss and ketone bodies, correlations were also foundbetween some cytokines and serum metabolites. For example, a positivecorrelation was found between IL6 and serum concentrations of acetone,formate, creatine, and 2-hydroxybutyrate. Similar positive relationshipswere identified for TNFa, G-CSF, and KC, while most of the cytokinesand chemokines were negatively correlated with choline, glucose, aswell as the TCA cycle intermediates citrate and 2-oxoglutarate.


Gram-negative and Gram-positive bacterial infections give rise to a different metabolic response in a mouse model.

Hoerr V, Zbytnuik L, Leger C, Tam PP, Kubes P, Vogel HJ - J. Proteome Res. (2012)

Covariationbetween metabolic, physiological, and cytokine responses.Correlation circle (biplot, three components, R2 = 0.72, Q2 = 0.52)of the four bacterial infections (S. aureus, S. pneumoniae, E. coli, P. aeruginosa) in C57BL/6 wild-type mice, their metabolites (x-variables), as well as their physiological and immunological parameters(y-variables).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3368387&req=5

fig8: Covariationbetween metabolic, physiological, and cytokine responses.Correlation circle (biplot, three components, R2 = 0.72, Q2 = 0.52)of the four bacterial infections (S. aureus, S. pneumoniae, E. coli, P. aeruginosa) in C57BL/6 wild-type mice, their metabolites (x-variables), as well as their physiological and immunological parameters(y-variables).
Mentions: To further investigate the covariation betweenmetabolite levels and host response, PLS regression analysis of allfour bacterial infections was performed using the physiological/immunologicalcharacteristics as y variables and metabolite concentrationsas x variables (three components, R2 = 0.72, Q2 =0.52). Several statistically significant correlations between physiologicaland immunological parameters and corresponding metabolite profilescould be derived (Figure 8). Besides well-knownpositive correlations between neutrophils and taurine41,42 and weight loss and ketone bodies, correlations were also foundbetween some cytokines and serum metabolites. For example, a positivecorrelation was found between IL6 and serum concentrations of acetone,formate, creatine, and 2-hydroxybutyrate. Similar positive relationshipswere identified for TNFa, G-CSF, and KC, while most of the cytokinesand chemokines were negatively correlated with choline, glucose, aswell as the TCA cycle intermediates citrate and 2-oxoglutarate.

Bottom Line: In an attempt to develop a better understanding of the process of pathogenesis and the associated host response we have used a quantitative (1)H NMR approach to study the metabolic response to different bacterial infections.Multivariate statistical analysis revealed correlations between metabolic, cytokine and physiological responses.Since Gram-positive and Gram-negative bacteria activate different receptor pathways in the host, our results suggest that it may become possible in the future to use a metabolomics approach to improve on current clinical microbiology diagnostic methods.

View Article: PubMed Central - PubMed

Affiliation: Biochemistry Research Group, Department of Biological Sciences, ‡Department of Physiology and Biophysics, Snyder Institute, University of Calgary , Calgary, Alberta T2N 1N4, Canada.

ABSTRACT
Metabolomics has become an important tool to study host-pathogen interactions and to discover potential novel therapeutic targets. In an attempt to develop a better understanding of the process of pathogenesis and the associated host response we have used a quantitative (1)H NMR approach to study the metabolic response to different bacterial infections. Here we describe that metabolic changes found in serum of mice that were infected with Staphylococcus aureus, Streptococcus pneumoniae, Escherichia coli and Pseudomonas aeruginosa can distinguish between infections caused by Gram-positive and Gram-negative bacterial strains. By combining the results of the mouse study with those of bacterial footprinting culture experiments, bacterially secreted metabolites could be identified as potential bacterium-specific biomarkers for P. aeruginosa infections but not for the other strains. Multivariate statistical analysis revealed correlations between metabolic, cytokine and physiological responses. In TLR4 and TLR2 knockout mice, host-response pathway correlated metabolites could be identified and allowed us for the first time to distinguish between bacterial- and host-induced metabolic changes. Since Gram-positive and Gram-negative bacteria activate different receptor pathways in the host, our results suggest that it may become possible in the future to use a metabolomics approach to improve on current clinical microbiology diagnostic methods.

Show MeSH
Related in: MedlinePlus