1 research outputs found
Structural Characterization of Plasma Metabolites Detected via LC-Electrochemical Coulometric Array Using LC-UV Fractionation, MS, and NMR
Liquid chromatography (LC) separation combined with electrochemical
coulometric array detection (EC) is a sensitive, reproducible, and
robust technique that can detect hundreds of redox-active metabolites
down to the level of femtograms on column, making it ideal for metabolomics
profiling. EC detection cannot, however, structurally characterize
unknown metabolites that comprise these profiles. Several aspects
of LC-EC methods prevent a direct transfer to other structurally informative
analytical methods, such as LC-MS and NMR. These include system limits
of detection, buffer requirements, and detection mechanisms. To address
these limitations, we developed a workflow based on the concentration
of plasma, metabolite extraction, and offline LC-UV fractionation.
Pooled human plasma was used to provide sufficient material necessary
for multiple sample concentrations and platform analyses. Offline
parallel LC-EC and LC-MS methods were established that correlated
standard metabolites between the LC-EC profiling method and the mass
spectrometer. Peak retention times (RT) from the LC-MS and LC-EC system
were linearly related (<i>r</i><sup>2</sup> = 0.99); thus,
LC-MS RTs could be directly predicted from the LC-EC signals. Subsequent
offline microcoil-NMR analysis of these collected fractions was used
to confirm LC-MS characterizations by providing complementary, structural
data. This work provides a validated workflow that is transferrable
across multiple platforms and provides the unambiguous structural
identifications necessary to move primary mathematically driven LC-EC
biomarker discovery into biological and clinical utility