Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery

<div><p>Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens’ pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.</p></div

Additional file 1 of Identification of predictive biomarkers for endometrial cancer diagnosis and treatment response monitoring using plasma metabolome profiling

Additional file 1: Table S1. List of all metabolites measured in this study. Table S2. Significantly increased metabolites in the plasma of patients with endometrial cancer compared to healthy controls. Table S3. Significantly decreased metabolites in the plasma of patients with endometrial cancer compared to healthy controls

Quality markers identified in this study for the evaluation of pre-analytical conditions.

<p>Quality markers identified in this study for the evaluation of pre-analytical conditions.</p

Changes in the metabolomic profiles caused by the storage of EDTA blood are visualized by PCA (score plot) based on the chemical features in the plasma samples as detected by the HILICpos assay.

<p>Sample storage conditions are represented by symbols colour-coded blue and red for 4°C and 25°C, respectively; dots, squares, triangles, crosses, and circles represent 3, 6, 12, 24, and 48 h, respectively. Control and SQC samples are represented by black dots and diagonal crosses, respectively.</p

Global metabolomics protocol.

<p>Study samples (1–88) were set at well positions from A1 to H11, and an RQC was set at A12 from sample tubes using a robotic system. The SQC (study quality control) is a mixture of 30 μL of each study sample collected from the 96-well plate after automated sample processing and is introduced into B12, whereas d<i>x</i>QC is a <i>x</i>-fold dilution of SQC (<i>x</i> = 2, 4, 8, or 16) with 50% methanol (water/methanol = 50/50, v/v %) containing 0.1% formic acid and is introduced into C12-F12. BK indicates a blank sample (50% methanol containing 0.1% formic acid) introduced into H12. *All study samples were diluted 8-fold; a 150 μL of methanol containing 0.1% formic acid was added to the 50 μL volume of plasma sample. After mixing, homogenization, and centrifugation, a 100 μL volume of the supernatant was transferred, and 100 μL of water containing 0.1% formic acid was added to the sample.</p