Nathalie Legrave and Mariana Silva dos Santos in the Metabolomics STP.

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We specialise in the development and implementation of cutting-edge, tailored metabolomics techniques.

Metabolomics-based projects are designed on a case-by-case basis, depending on the biological system and question. Metabolite profiling, metabolic foot-printing and stable isotope labelling techniques can be employed for the specific needs of a given study.

We have considerable experience in metabolomics project workflows, including study design and development, metabolite extraction techniques, sample preparation, data acquisition and data analysis.

We use bespoke analytical approaches, chemometrics, bioinformatics, and statistical rigour to ensure that the data provided can be interpreted easily and with confidence.


The field of metabolomics is as broad as it is young, and at the Crick we are focused on a number of key areas.

Targeted and untargeted analyses

We specialise in targeted metabolomics, using tailored methods in order to study specific metabolites or metabolic pathway activity. We also perform untargeted analyses, using more global profiling approaches in order to determine the differences between biological samples and the underlying causes of those differences. We are developing methods in order to improve our coverage of metabolite detection.

Stable isotope labelling

Stable isotope labelling is an exceptionally powerful tool that we regularly use. We add an isotopically labelled form of a substrate (often a carbon or nitrogen source, such as 13C-glucose or 15N-glutamine) and trace incorporation into metabolic pathways. This provides invaluable information on the metabolic activity of the cell and enables the delineation of complex metabolic pathways.


Lipidomics is a branch of metabolomics that specifically looks at lipid molecules. Far from simply being a subsection of a broader field, lipidomics covers tens of thousands of molecules with complex structures that can differ in very subtle ways. Detecting and identifying these molecules in a robust manner is a challenge in itself and requires careful consideration. We routinely study fatty acids and sterols, and have implemented and developed techniques in order to measure more complex lipids, such as phospholipids and di- and tri-acylglycerols. We are currently developing further lipidomics techniques in order to broaden the range of lipid classes detectable in our group.

Data analysis

Data analysis is a sophisticated and necessary aspect to metabolomics projects. The methods used can vary considerably depending on the experimental requirements. They range from the initial data extraction (peak-picking, integration, and identification), right through to data processing (quantifications, label incorporation, isotopologue analyses), pattern recognition (principal component analyses, hierarchical cluster analyses, component variability analyses) and statistical approaches (t-tests, ANOVA analyses, Volcano plots, Z-transformations, etc.). We are currently developing further data analysis techniques in order to simplify and shorten this process, which is often the bottleneck in metabolomics projects.

Data analysis examples

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Method development

Metabolomics is still very young and method development is still ongoing for many aspects of this research. Along with methods we are developing in-house, we are also collaborating with some of the world's leading metabolomics groups in order to maintain excellence of operation, while continuing to develop bespoke methodology and integrate cutting-edge techniques into our workflows. This includes sample preparation, statistical rigour and – especially - data analytics and chemometric techniques.