Yevgeniya I. Shurubor

High-Performance Liquid Chromatography Separations Coupled With Coulometric Electrode Array Detectors

Metabolomics is the systematic and theoretically comprehensive study of the small molecules that comprise a biological sample, e.g., sera or plasma. The primary analytical tools used in metabolomics are nuclear magnetic resonance and mass spectroscopy. We here address a different tool, high-performance liquid chromatography (HPLC) separations coupled with coulometric electrode array detection. This system has unique advantages, notably sensitivity and high quantitative precision, but also has unique limitations, such as obtaining little structural information on the metabolites of interest and limited scale-up capacity. The system also only detects redox-active compounds, which can be either a benefit or a detriment, depending on the experimental goals and design. Here, we discuss the characteristics of this HPLC/coulometric electrode array system in the context of metabolomics, and then present the method as practiced in our groups.

Biological variability dominates and influences analytical variance in HPLC-ECD studies of the human plasma metabolome

BackgroundBiomarker-based assessments of biological samples are widespread in clinical, pre-clinical, and epidemiological investigations. We previously developed serum metabolomic profiles assessed by HPLC-separations coupled with coulometric array detection that can accurately identify ad libitum fed and caloric-restricted rats. These profiles are being adapted for human epidemiology studies, given the importance of energy balance in human disease.MethodsHuman plasma samples were biochemically analyzed using HPLC separations coupled with coulometric electrode array detection.ResultsWe identified these markers/metabolites in human plasma, and then used them to determine which human samples represent blinded duplicates with 100% accuracy (N = 30 of 30). At least 47 of 61 metabolites tested were sufficiently stable for use even after 48 hours of exposure to shipping conditions. Stability of some metabolites differed between individuals (N = 10 at 0, 24, and 48 hours), suggesting the influence of some biological factors on parameters normally considered as analytical.ConclusionOverall analytical precision (mean median CV, ~9%) and total between-person variation (median CV, ~50–70%) appear well suited to enable use of metabolomics markers in human clinical trials and epidemiological studies, including studies of the effect of caloric intake and balance on long-term cancer risk.

Relative contribution of specific sources of systematic errors and analytical imprecision to metabolite analysis by HPLC–ECD

Objective interpretation of metabolomics data requires understanding both analytical and biological measurement errors. Here we address analytical measurement errors, the sources of these errors, and how this variability can impact metabolomic profiles. Sources considered include room temperature exposure (which could affect sample stability), spiking with authentic standards, the number of study replicates, the overall temporal design of the experimental series, and the complexity of the biological matrix of the samples (individual or pooled sera). The study focused on the analysis of ∼80 rat sera metabolites by HPLC coupled with coulometric array detectors. Time delay and room temperature exposure had minimal effects on the total relative metabolite concentrations and variability (mean: ∼94–98% of control, CVmedian: ±5–7%), but the concentrations of some specific metabolites were significantly altered. Changes observed in the concentrations of specific metabolites ranged as high as ±7-fold, with changes in variability ranging from 0.3% to 68%. Spiked samples demonstrated more complex behavior when allowed to decay over time than did control samples. The spiking of sera and standards with 43 known metabolites increased variability of the apparent concentrations of metabolites up to ∼24% as opposed to ∼3% in pure sera. Increased variability was metabolite-specific. In both pure and spiked sera, ∼80–95% of metabolites had CVs equivalent to standard analytical CVs for these metabolites. Experimental design, number of replicates, and complexity of the biological matrix had comparable effects. These results suggest that, under carefully controlled conditions, these analytical issues are not significant sources of variability relative to biological variation for most metabolites.

Determination of Coenzyme A and Acetyl-Coenzyme A in Biological Samples Using HPLC with UV Detection

Coenzyme A (CoA) and acetyl-coenzyme A (acetyl-CoA) play essential roles in cell energy metabolism. Dysregulation of the biosynthesis and functioning of both compounds may contribute to various pathological conditions. We describe here a simple and sensitive HPLC-UV based method for simultaneous determination of CoA and acetyl-CoA in a variety of biological samples, including cells in culture, mouse cortex, and rat plasma, liver, kidney, and brain tissues. The limits of detection for CoA and acetyl-CoA are >10-fold lower than those obtained by previously described HPLC procedures, with coefficients of variation <1% for standard solutions, and 1–3% for deproteinized biological samples. Recovery is 95–97% for liver extracts spiked with Co-A and acetyl-CoA. Many factors may influence the tissue concentrations of CoA and acetyl-CoA (e.g., age, fed, or fasted state). Nevertheless, the values obtained by the present HPLC method for the concentration of CoA and acetyl-CoA in selected rodent tissues are in reasonable agreement with literature values. The concentrations of CoA and acetyl-CoA were found to be very low in rat plasma, but easily measurable by the present HPLC method. The method should be useful for studying cellular energy metabolism under normal and pathological conditions, and during targeted drug therapy treatment.