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SUMMARY:Designed Biofluid Mixtures Allow Feature-Wise Evaluation Of Metabo
 lic Profiling Analytical Platforms - Athersuch\, T (Imperial College Londo
 n)
DTSTART:20110830T160000Z
DTEND:20110830T163000Z
UID:TALK32568@talks.cam.ac.uk
CONTACT:Mustapha Amrani
DESCRIPTION:The development of spectral analysis platforms for targeted me
 tabolic profiling may help streamline quantification and will undoubtedly 
 facilitate biological interpretation of metabolomics/metabonomics datasets
 . A general method for evaluating the performance\, coverage and applicabi
 lity of analytical methods in metabolic profiling is much needed to aid bi
 omarker assessment. \n\nThe substantial variation in spectral and composit
 ional background that exist in samples generated by real biofluid studies 
 are often not capture by traditional evaluations of analytical performance
  that use compounds addition (spikes). Such approaches may therefore under
 estimate the contribution of matrix effects to the measurement of major me
 tabolites and confound analysis. \n\nWe illustrate how a strategy of mixin
 g intact biofluids in a predetermined experimental design can be used to e
 valuate\, compare and optimise the performance of quantitative spectral an
 alysis tools in conditions that better approximate a real metabolic profil
 ing experiment. \n\nResults of preliminary experiments on two commonly-use
 d profiling platforms (high-resolution 1D 1H nuclear magnetic resonance (N
 MR) spectroscopy and ultra high performance liquid chromatography-mass spe
 ctrometry (UPLC-MS)) are discussed. Use of multivariate regression allowed
  feature-wise statistics to be generated as a summary of the overall perfo
 rmance of each platform. \n\nThe use of designed biofluid mixtures as a ba
 sis of evaluating the feature-wise variation in instrument response provid
 es a rational basis for exploiting information from several samples simult
 aneously\, in contrast to spectral deconvolution\, which is typically appl
 ied to one spectrum at a time.\n
LOCATION:Seminar Room 1\, Newton Institute
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