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Anal Chem. 2018 Jul 17;90(14):8396-8403. doi: 10.1021/acs.analchem.8b00875. Epub 2018 Jun 28.

Autonomous Multimodal Metabolomics Data Integration for Comprehensive Pathway Analysis and Systems Biology.

Author information

1
Metabolomics Platform, Faculty of Biology and Medicine , University of Lausanne , CH-1005 Lausanne , Switzerland.
2
Department of Molecular Medicine and Surgery , Karolinska Institute , 171 77 Stockholm , Sweden.
3
Department of Food Chemistry and Toxicology, Faculty of Chemistry and Vienna Metabolomics Center (VIME) , University of Vienna , Währingerstrasse 38 , 1090 Vienna , Austria.

Abstract

Comprehensive metabolomic data can be achieved using multiple orthogonal separation and mass spectrometry (MS) analytical techniques. However, drawing biologically relevant conclusions from this data and combining it with additional layers of information collected by other omic technologies present a significant bioinformatic challenge. To address this, a data processing approach was designed to automate the comprehensive prediction of dysregulated metabolic pathways/networks from multiple data sources. The platform autonomously integrates multiple MS-based metabolomics data types without constraints due to different sample preparation/extraction, chromatographic separation, or MS detection method. This multimodal analysis streamlines the extraction of biological information from the metabolomics data as well as the contextualization within proteomics and transcriptomics data sets. As a proof of concept, this multimodal analysis approach was applied to a colorectal cancer (CRC) study, in which complementary liquid chromatography-mass spectrometry (LC-MS) data were combined with proteomic and transcriptomic data. Our approach provided a highly resolved overview of colon cancer metabolic dysregulation, with an average 17% increase of detected dysregulated metabolites per pathway and an increase in metabolic pathway prediction confidence. Moreover, 95% of the altered metabolic pathways matched with the dysregulated genes and proteins, providing additional validation at a systems level. The analysis platform is currently available via the XCMS Online ( XCMSOnline.scripps.edu ).

PMID:
29893550
DOI:
10.1021/acs.analchem.8b00875
[Indexed for MEDLINE]

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