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Untargeted, semi-targeted and targeted analytical approaches

There are three analytical chemistry strategies applied in metabolomics – untargeted, semi-targeted and targeted.

Both untargeted and semi-targeted approaches are applied in hypothesis-generating studies, while targeted assays are usually applied in validation and for the translation of the novel discoveries after an initial hypothesis-generating study. The major differences between untargeted, semi-targeted and targeted studies are the level of sample preparation required, the number of metabolites detected and the level of quantification of the metabolites. The objectives of a study define which of the three analytical strategies are applied.

Untargeted approaches

Untargeted approaches provide the most appropriate route to detect unexpected changes in metabolite concentrations; the aim is to maximise the number of metabolites detected and therefore provide the opportunity to observe unexpected changes. Hundreds to thousands of metabolites can typically be measured. However one single analytical method cannot detect all of the metabolites in a biological system. It’s therefore desirable to combine multiple analytical approaches to maximise the number of metabolites detected and increase coverage of the metabolome.

Sample preparation in untargeted studies is typically the extraction of the biological sample in to a solvent with no further separation of the metabolites. The peak area of each metabolite is used as the parameter in the statistical analysis to define the concentration differences between the different biological samples being measured. This is referred to as relative quantification as there is no comparison to calibration curves constructed with chemical standards, which are required for full quantification. The biological importance of each metabolite is determined during data analysis and metabolite identification, and biological interpretation is performed at the end of the experimental pipeline. This approach does not know the chemical identity of each metabolite before data is acquired – data acquired during data acquisition is applied to identify metabolites after data acquisition.

Currently, one of the major limitations in untargeted approaches is the identification of metabolites. It may not be possible to identify the metabolites highlighted in the statistical analysis as significantly changing between the biological classes in the study. Metabolite identification is currently one of the hot topics in metabolomics.

Targeted approaches

Targeted studies analyse a relatively small and specific number of metabolites, typically up to twenty metabolites. These metabolites are chemically characterised and biochemically annotated with established biological importance at the start of the study before data acquisition is performed. Targeted methods have a greater selectivity and sensitivity than untargeted methods. Quantification of the metabolites is performed through the use of internal standards and authentic chemical standards to construction calibration curves for each of the metabolite.

A targeted study cannot be performed unless an authentic chemical standard of the metabolite is available. The sample preparation in targeted studies applies methods that can be optimised to retain the metabolites of interest and to remove other biological species and analytical artefacts which are not carried through to the downstream analysis, simplifying the analysis of the data and interpretation of the biological significance.

Semi-targeted approaches

Semi-targeted methods fall in the middle between untargeted and targeted approaches. This approach aims to quantify hundreds of metabolites whose identity is known before data acquisition. The method typically applies one calibration curve for a set of metabolites of similar chemical structure, rather than apply a single calibration curve for each metabolite.

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This article is from the free online course:

Metabolomics: Understanding Metabolism in the 21st Century

University of Birmingham

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