Enabling metabolomics based biomarker discovery studies using molecular phenotyping of exosome-like vesicles

Tatiana Altadill, Irene Campoy, Lucia Lanau, Kirandeep Gill, Marina Rigau, Antonio Gil-Moreno, Jaume Reventos, Stephen Byers, Eva Colas, Amrita K. Cheema

Research output: Contribution to journalArticleResearchpeer-review

43 Citations (Scopus)

Abstract

© 2016 Altadill et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Identification of sensitive and specific biomarkers with clinical and translational utility will require smart experimental strategies that would augment expanding the breadth and depth of molecular measurements within the constraints of currently available technologies. Exosomes represent an information rich matrix to discern novel disease mechanisms that are thought to contribute to pathologies such as dementia and cancer. Although proteomics and transcriptomic studies have been reported using Exosomes-Like Vesicles (ELVs) from different sources, exosomal metabolome characterization and its modulation in health and disease remains to be elucidated. Here we describe methodologies for UPLC-ESI-MS based small molecule profiling of ELVs from human plasma and cell culture media. In this study, we present evidence that indeed ELVs carry a rich metabolome that could not only augment the discovery of low abundance biomarkers but may also help explain the molecular basis of disease progression. This approach could be easily translated to other studies seeking to develop predictive biomarkers that can subsequently be used with simplified targeted approaches.
Original languageEnglish
Article numbere0151339
JournalPLoS ONE
Volume11
Issue number3
DOIs
Publication statusPublished - 1 Mar 2016

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