Long-Term Metabolomics Reference Material

Abstract

The use of quality control samples in metabolomics ensures data quality, reproducibility and comparability between studies, analytical platforms and laboratories. Long-term, stable and sustainable reference materials (RMs) are a critical component of the QA/QC system, however, the limited selection of currently available matrix matched RMs reduce their applicability for widespread use. To produce a RM in any context, for any matrix that is robust to changes over the course of time we developed IBAT (Iterative Batch Averaging meThod). To illustrate this method, we generated 11 independently grown E. coli batches and made a RM over the course of 10 IBAT iterations. We measured the variance of these materials by NMR and showed that IBAT produces a stable and sustainable RM over time. This E. coli RM was then used as food source to produce a C. elegans RM for a metabolomics experiment. The metabolite extraction of this material alongside 41 independently grown individual C. elegans samples of the same genotype, allowed to estimate the proportion of sample variation in pre-analytical steps. From the NMR data, we found that 40% of the metabolite variance is due to the metabolite extraction process and analysis and 60% is due to sample-to-sample variance. The availability of RMs in untargeted metabolomics is one of the predominant needs of the metabolomics community that reach beyond quality control practices. IBAT addresses this need by facilitating the production of biologically relevant RMs and increasing their widespread use.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

“…2.2), there is a recognized need for contiguous supply of stable, matrix-specific materials. As an alternative, an iterative batch averaging method (IBAT) (Gouveia et al, 2021) may be used to produce stable in-house RMs over the course of time with relatively low variance. The IBAT process reduces the production and sampling contributions to variance by creating a common source of material from which homogeneous aliquots are produced.…”