tetano
Editor, Senior Moderator
PLoS One. 2014 May 20;9(5):e97238. doi: 10.1371/journal.pone.0097238. eCollection 2014.
1H NMR-Based Profiling Reveals Differential Immune-Metabolic Networks during Influenza Virus Infection in Obese Mice.
Milner JJ1, Wang J2, Sheridan PA1, Ebbels T2, Beck MA1, Saric J2.
Author information
Abstract
Obese individuals are at greater risk for death from influenza virus infection. Paralleling human evidence, obese mice are also more susceptible to influenza infection mortality. However, the underlying mechanisms driving greater influenza severity in the obese remain unclear. Metabolic profiling has been utilized in infectious disease models to enhance prognostic or diagnostic methods, and to gain insight into disease pathogenesis by providing a more global picture of dynamic infection responses. Herein, metabolic profiling was used to develop a deeper understanding of the complex processes contributing to impaired influenza protection in obese mice and to facilitate generation of new explanatory hypotheses. Diet-induced obese and lean mice were infected with influenza A/Puerto Rico/8/34. 1H nuclear magnetic resonance-based metabolic profiling of urine, feces, lung, liver, mesenteric white adipose tissue, bronchoalveolar lavage fluid and serum revealed distinct metabolic signatures in infected obese mice, including perturbations in nucleotide, vitamin, ketone body, amino acid, carbohydrate, choline and lipid metabolic pathways. Further, metabolic data was integrated with immune analyses to obtain a more comprehensive understanding of potential immune-metabolic interactions. Of interest, uncovered metabolic signatures in urine and feces allowed for discrimination of infection status in both lean and obese mice at an early influenza time point, which holds prognostic and diagnostic implications for this methodology. These results confirm that obesity causes distinct metabolic perturbations during influenza infection and provide a basis for generation of new hypotheses and use of this methodology in detection of putative biomarkers and metabolic patterns to predict influenza infection outcome.
PMID:
24844920
[PubMed - in process]
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/24844920
1H NMR-Based Profiling Reveals Differential Immune-Metabolic Networks during Influenza Virus Infection in Obese Mice.
Milner JJ1, Wang J2, Sheridan PA1, Ebbels T2, Beck MA1, Saric J2.
Author information
Abstract
Obese individuals are at greater risk for death from influenza virus infection. Paralleling human evidence, obese mice are also more susceptible to influenza infection mortality. However, the underlying mechanisms driving greater influenza severity in the obese remain unclear. Metabolic profiling has been utilized in infectious disease models to enhance prognostic or diagnostic methods, and to gain insight into disease pathogenesis by providing a more global picture of dynamic infection responses. Herein, metabolic profiling was used to develop a deeper understanding of the complex processes contributing to impaired influenza protection in obese mice and to facilitate generation of new explanatory hypotheses. Diet-induced obese and lean mice were infected with influenza A/Puerto Rico/8/34. 1H nuclear magnetic resonance-based metabolic profiling of urine, feces, lung, liver, mesenteric white adipose tissue, bronchoalveolar lavage fluid and serum revealed distinct metabolic signatures in infected obese mice, including perturbations in nucleotide, vitamin, ketone body, amino acid, carbohydrate, choline and lipid metabolic pathways. Further, metabolic data was integrated with immune analyses to obtain a more comprehensive understanding of potential immune-metabolic interactions. Of interest, uncovered metabolic signatures in urine and feces allowed for discrimination of infection status in both lean and obese mice at an early influenza time point, which holds prognostic and diagnostic implications for this methodology. These results confirm that obesity causes distinct metabolic perturbations during influenza infection and provide a basis for generation of new hypotheses and use of this methodology in detection of putative biomarkers and metabolic patterns to predict influenza infection outcome.
PMID:
24844920
[PubMed - in process]
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/24844920