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The addition of QCs on a sample plate throughout an experimental run
The intermittent analysis of QCs during an experiment

The application of quality control samples

Quality assurance and quality control provides a mechanism to ensure that a scientific process meets the predefined criteria.

In metabolomics the application of quality control samples and their use in the quality assurance procedure provides a mechanism to judge the quality and assess the analytical variance of the data. The quality control (QC) sample should qualitatively and quantitatively representative the entire collection of samples included in the study, providing an average of all of the metabolomes analysed in the study. The QC samples are analysed intermittently for the duration of the analytical study to assess the variance observed in the data throughout the sample preparation, data acquisition and data pre-processing steps. Replicate injections should provide identical data for each injection, however in reality analytical variance will be observed and the replicate QC injections can be used to measure this variance across the analytical study.

In untargeted metabolomics QCs are applied to assess and ensure the analytical process is performed appropriately and meets the predefined criteria. There are different types of QC samples. The ideal QC sample is a pooled QC sample in which a small aliquot of each biological sample in the study set are mixed together. The pooled QC represents both the sample matrix and metabolite composition of the samples. The pooled QC mixture is used to produce multiple QC samples that can be used for the duration of the analytical study.

If it is not possible to create a pooled QC sample due to limited sample amounts or if the study involves thousands of samples to be collected over several months or years, then an alternative QC sample should be used. If in a large study set (with greater than 500 samples) the QC may be prepared from the first batch of samples collected. However, the recruitment of subjects should be randomised and the samples should be representative of the entire study group. Alternatively a commercially available QC sample may be used, for example human serum can be purchased from commercial suppliers. Preparation of the QCs should follow the same sample procedure performed in the preparation of the study biological samples, and the number of freeze-thaw cycles should be standardised between the QC and study biological samples.

If neither a pooled QC nor a commercial alternative is available for example in samples with low volumes such as tears or bile then a synthetic substitute may be used. The synthetic substitute should comprise a metabolite cocktail that includes multiple representatives from each class of metabolites expected in the study samples and the synthetic QC should be prepared under identical conditions to the study samples.

The data from the QC samples is used to monitor drift, separate high- and low-quality data, equilibrate the analytical platform, correct for drift in the signal and allow the integration of multiple analytical experiments. The data analysis technique principal component analysis (this will be described in week 4 of the course) can be used to quickly assess the reproducibility of the QC samples in an analytical run. The QC samples are used to determine the variance of a metabolite feature. If the variance is deemed to be too high (ie, 20% for LC-MS data) then the feature is removed from the analysis. This processing step is performed at the start of the data analysis process.

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This article is from the free online course:

Metabolomics: Understanding Metabolism in the 21st Century

University of Birmingham