Designed Biofluid Mixtures Allow Feature-Wise Evaluation Of Metabolic Profiling Analytical Platforms
Seminar Room 1, Newton Institute
The development of spectral analysis platforms for targeted metabolic profiling may help streamline quantification and will undoubtedly facilitate biological interpretation of metabolomics/metabonomics datasets. A general method for evaluating the performance, coverage and applicability of analytical methods in metabolic profiling is much needed to aid biomarker assessment.
The substantial variation in spectral and compositional 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 underestimate the contribution of matrix effects to the measurement of major metabolites and confound analysis.
We illustrate how a strategy of mixing intact biofluids in a predetermined experimental design can be used to evaluate, compare and optimise the performance of quantitative spectral analysis tools in conditions that better approximate a real metabolic profiling experiment.
Results of preliminary experiments on two commonly-used profiling platforms (high-resolution 1D 1H nuclear magnetic resonance (NMR) spectroscopy and ultra high performance liquid chromatography-mass spectrometry (UPLC-MS)) are discussed. Use of multivariate regression allowed feature-wise statistics to be generated as a summary of the overall performance of each platform.
The use of designed biofluid mixtures as a basis of evaluating the feature-wise variation in instrument response provides a rational basis for exploiting information from several samples simultaneously, in contrast to spectral deconvolution, which is typically applied to one spectrum at a time.