Bidirectional correlation of NMR and capillary electrophoresis fingerprints: a new approach to investigating Schistosoma mansoni infection in a mouse model

We demonstrate the statistical integration of nuclear magnetic resonance (NMR) spectroscopy and capillary electrophoresis (CE) data in order to describe a pathological state caused by Schistosoma mansoni infection in a mouse model based on urinary metabolite profiles. Urine samples from mice 53 days...

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Vydáno v:Analytical chemistry (Washington) Ročník 82; číslo 1; s. 203
Hlavní autoři: Garcia-Perez, I, Couto Alves, A, Angulo, S, Li, J V, Utzinger, J, Ebbels, T M D, Legido-Quigley, C, Nicholson, J K, Holmes, E, Barbas, C
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 01.01.2010
Témata:
Animals
Biomarkers - urine
Electrophoresis, Capillary
Female
Mice
Nuclear Magnetic Resonance, Biomolecular
Schistosoma mansoni - isolation & purification
Schistosomiasis mansoni - diagnosis
Schistosomiasis mansoni - parasitology
Schistosomiasis mansoni - urine
Urine - chemistry
ISSN:1520-6882, 1520-6882
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Shrnutí:We demonstrate the statistical integration of nuclear magnetic resonance (NMR) spectroscopy and capillary electrophoresis (CE) data in order to describe a pathological state caused by Schistosoma mansoni infection in a mouse model based on urinary metabolite profiles. Urine samples from mice 53 days post infection with S. mansoni and matched controls were analyzed via NMR spectroscopy and CE. The two sets of metabolic profiles were first processed and analyzed independently and were subsequently integrated using statistical correlation methods in order to facilitate cross assignment of metabolites. Using this approach, metabolites such as 3-ureidopropionate, p-cresol glucuronide, phenylacetylglycine, indoxyl sulfate, isocitrate, and trimethylamine were identified as differentiating between infected and control animals. These correlation analyses facilitated structural elucidation using the identification power of one technique to enhance and validate the other, but also highlighted the enhanced ability to detect functional correlations between metabolites, thereby providing potential for achieving deeper mechanistic insight into the biological process.
Bibliografie:ObjectType-Article-1
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ISSN:1520-6882
1520-6882
DOI:10.1021/ac901728w