Metabolomics - non-polar metabolites
Metabolomics is the comprehensive study of the metabolome, the complete set of metabolites within a biological system. Metabolomics provides a detailed snapshot of biochemical activity in cells, tissues, and fluids by identifying, quantifying, and analyzing these small molecules. Metabolites, which include compounds like amino acids, carbohydrates, and vitamins, are crucial for maintaining cellular function and homeostasis. Disruptions in their patterns can lead to diseases, making metabolomics essential for discovering biomarkers, understanding metabolic pathways, and exploring the effects of interventions on metabolic health. Human Metabolome Database lists over 220,000 metabolites, offering valuable insights into human health and disease.
Untargeted metabolomics
The reversed phase is ideal for separating and analyzing non-polar to moderately polar metabolites, such as lipids, fatty acids, certain amino acids, and hormones.
We use ultrahigh-performance liquid chromatography (UPLC) in the separation mode of reversed-phase LC coupled with high-resolution (70,000 FWHM) Orbitrap mass spectrometry. Up to 10,000 metabolite features in typical biological samples (serum, plasma, CSF) are relatively quantified in positive detection mode. QC samples are injected throughout the analysis to monitor instrument stability (platform variability, retention time shift, and mass shift) and sample stability to ensure high-quality datasets. QC data is evaluated for each data set with multivariate statistics. Identification of metabolites is performed in silico and with a library of standard substances of >900 metabolites in stock.
Platform strengths
The assay has high reproducibility and compatibility with various metabolite classes, particularly non-polar compounds. The method provides relative quantitation of hydrophilic to lipophilic metabolites and lipids by untargeted metabolomics analysis combined with database searching and putative metabolite IDs based on accurate masses.
Metabolite identification
Tier 3 is provided as optional (upon request) by using accurately measured masses (errors ≤5 ppm) to query metabolome databases for preliminary metabolite assignments with putative identities. Tier 1 and Tier 2 are provided to identify and structurally confirm statistics relevant metabolite biomarkers by combining metabolome/lipidome database searching, LC-MS, and LC-MS/MS spectral matching and interpretation, with the aid of an in-house library consisting of >900 authentic metabolite compounds. Upon request, we can perform additional LC-MS and LC-MS/MS runs and acquire new standards (if available) to confirm the identity of novel metabolites that are not currently in our library.
Example data
Serum: In 120 samples, 8,404 metabolite and lipid features were found across all samples (allowing 10% missing values). In a set of 1,860 samples, 4,544 metabolite and lipid features were found across all samples (allowing 10% missing values).