RT Journal Article
SR Electronic
T1 METASPACE: A community-populated knowledge base of spatial metabolomes in health and disease
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 539478
DO 10.1101/539478
A1 Theodore Alexandrov
A1 Katja Ovchinnikova
A1 Andrew Palmer
A1 Vitaly Kovalev
A1 Artem Tarasov
A1 Lachlan Stuart
A1 Renat Nigmetzianov
A1 Dominik Fay
A1 Key METASPACE contributors
A1 Mathieu Gaudin
A1 Cristina Gonzalez Lopez
A1 Marina Vetter
A1 John Swales
A1 Mark Bokhart
A1 Mario Kompauer
A1 James McKenzie
A1 Luca Rappez
A1 Dusan Velickovic
A1 Regis Lavigne
A1 Guanshi Zhang
A1 Dinaiz Thinagaran
A1 Elisa Ruhland
A1 Marta Sans
A1 Sergio Triana
A1 Denis Abu Sammour
A1 Sarah Aboulmagd
A1 Charlotte Bagger
A1 Nicole Strittmatter
A1 Angelos Rigopoulos
A1 Erin Gemperline
A1 Asta Maria Joensen
A1 Benedikt Geier
A1 Christine Quiason
A1 Eric Weaver
A1 Mridula Prasad
A1 Benjamin Balluff
A1 Konstantin Nagornov
A1 Lingjun Li
A1 Michael Linscheid
A1 Carsten Hopf
A1 Dimitri Heintz
A1 Manuel Liebeke
A1 Bernhard Spengler
A1 Berin Boughton
A1 Christian Janfelt
A1 Kumar Sharma
A1 Charles Pineau
A1 Christopher Anderton
A1 Shane Ellis
A1 Michael Becker
A1 József Pánczél
A1 Georges Da Violante
A1 David Muddiman
A1 Richard Goodwin
A1 Livia Eberlin
A1 Zoltan Takats
A1 Sheerin Shahidi-Latham
YR 2019
UL http://biorxiv.org/content/early/2019/02/03/539478.abstract
AB Metabolites, lipids, and other small molecules are key constituents of tissues supporting cellular programs in health and disease. Here, we present METASPACE, a community-populated knowledge base of spatial metabolomes from imaging mass spectrometry data. METASPACE is enabled by a high-performance engine for metabolite annotation in a confidence-controlled way that makes results comparable between experiments and laboratories. By sharing their results publicly, engine users continuously populate a knowledge base of annotated spatial metabolomes in tissues currently including over 3000 datasets from human cancer cohorts, whole-body sections of animal models, and various organs. The spatial metabolomes can be visualized, explored and shared using a web app as well as accessed programmatically for large-scale analysis. By using novel computational methods inspired by natural language processing, we illustrate that METASPACE provides molecular coverage beyond the capacity of any individual laboratory and opens avenues towards comprehensive metabolite atlases on the levels of tissues and organs.