Abstract
Liquid-chromatography mass spectrometry is commonly used to identify and quantify metabolites from biological samples to gain insight into human physiology and pathology. Metabolites and their abundance in biological samples are labile and sensitive to variations in collection conditions, handling and processing. Variations in sample handling could influence metabolite levels in ways not related to biology, ultimately leading to the misinterpretation of results. For example, anticoagulants and preservatives modulate enzyme activity and metabolite oxidization. Temperature may alter both enzymatic and non-enzymatic chemistry. The potential for variation induced by collection conditions is particularly important when samples are collected in remote locations without immediate access to specimen processing. Data are needed regarding the variation introduced by clinical sample collection processes to avoid introducing artifact biases. In this study, we used metabolomics and lipidomics approaches paired with univariate and multivariate statistical analyses to assess the effects of anticoagulant, temperature, and time on healthy human plasma samples collected to provide guidelines on sample collection, handling, and processing for vaccinology. Principal component analyses demonstrated clustering by sample collection procedure and that anticoagulant type had the greatest effect on sample metabolite variation. Lipids such as glycerophospholipids, acylcarnitines, sphingolipids, diacylglycerols, triacylglycerols, and cholesteryl esters are significantly affected by anticoagulant type as are amino acids such as aspartate, histidine, and glutamine. Most plasma metabolites and lipids were unaffected by storage time and temperature. Based on this study, we recommend samples be collected using a single anticoagulant (preferably EDTA) with sample processing at <24 h at 4 °C.
Highlights
Recent advancements in sensitive analytical technologies such as liquid-chromatography mass spectrometry (LC-MS) have enabled the identification and quantification of polar and non-polar metabolites in biological samples
The K2 EDTA-containing plasma samples were stored at 4 ◦ C or room temperature (22 ◦ C) and the sodium-citrate-containing plasma samples were stored at room temperature (Refer to Figure 1 for detail analytical strategy for metabolomics and lipidomics data)
Statistical treatment was undertaken for five donors separately to determine the effect of storage time and anticoagulants in the plasma lipid profile
Summary
Recent advancements in sensitive analytical technologies such as liquid-chromatography mass spectrometry (LC-MS) have enabled the identification and quantification of polar and non-polar metabolites in biological samples. Metabolomics refers to measuring the complete set of metabolites that change according to the physiological, developmental, or pathological state of the cell, tissue, organ, or organism [2]. Metabolomics and lipidomics approaches employ high-resolution mass spectrometry to profile thousands of chemical components in an array of biological samples, making it one of the most powerful technologies to investigate metabolic perturbations in normal biology, disease or other exogenous or endogenous factors. Cellular metabolic activities can be studied by quantifying changes in lipids at the class, subclass, and molecular species level and discerning the differential metabolites between normal and abnormal cells [12]. Change in the normal concentrations of these metabolites and lipids often relates to disease and differential physiological states [13–15]
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