Metabolomics Applied to the Study of Extracellular Vesicles

Abstract

Cell-secreted extracellular vesicles (EVs) have rapidly gained prominence as sources of biomarkers for non-invasive biopsies, owing to their ubiquity across human biofluids and physiological stability. There are many characterisation studies directed towards their protein, nucleic acid, lipid and glycan content, but more recently the metabolomic analysis of EV content has also gained traction. Several EV metabolite biomarker candidates have been identified across a range of diseases, including liver disease and cancers of the prostate and pancreas. Beyond clinical applications, metabolomics has also elucidated possible mechanisms of action underlying EV function, such as the arginase-mediated relaxation of pulmonary arteries or the delivery of nutrients to tumours by vesicles. However, whilst the value of EV metabolomics is clear, there are challenges inherent to working with these entities-particularly in relation to sample production and preparation. The biomolecular composition of EVs is known to change drastically depending on the isolation method used, and recent evidence has demonstrated that changes in cell culture systems impact upon the metabolome of the resulting EVs. This review aims to collect recent advances in the EV metabolomics field whilst also introducing researchers interested in this area to practical pitfalls in applying metabolomics to EV studies.

Keywords: biomarkers; diagnostics; exosomes; extracellular vesicles; metabolic pathways; microvesicles.

Figure 1

Key stages of the metabolomic analysis workflow for extracellular vesicle (EV) samples. Methodologies of EV isolation can impact the metabolome and should be carefully considered when comparing results from different studies. (CCM, cell conditioned medium; SEC, size exclusion chromatography; GC, gas chromatography; HILIC, hydrophilic interaction chromatography; RP, reversed-phase chromatography; Targeted analysis, detailed analysis of a predefined subset of the metabolome; Non-targeted analysis, maximum metabolite coverage).