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Introduction to Metabolomics


last_modification Last modification: Jul 26, 2021


.pull-left[An archaic image of a large wheel with substances.] .pull-right[A cartoon of genes pointing to a genome, mRNA to a transcriptome, proteins to a proteome, and metabolites to a metabolome. All of these are connected by various lines, and finally point to function at the bottom.]

«Quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification » (Nicholson, 1999)



.pull-left[ Metabolo l omics .left[ Metabolic ‘fingerprints’ (unique for each type of cell or tissue) based on comprehensive quantification

i.e. comprehensive and simultaneous systematic determination of metabolite levels in a biological system (cell, tissue, fluid) ]]

.pull-right[ Metabolo n omics .left[ Description of metabolic changes

i.e. detection of disrupted metabolic pathways ]]

Metabolomics : the world of small molecules

.pull-left[ Physico-chemical diversity

.pull-right[ Molecular mass range Histogram comparing E. coli and S. cerevisiae and their molecular weight ranges and frequency. 80% of metabolites with mol. mass ≤ 600 (E. coli, S. cerevisiae) ]

Analytical challenge

Large pathway map with text over it reading: targeted/global, sensitity coverage. Great number of metabolites, 2.5k to 15k. Chemical diversity of metabolites, mass, pKa, polarity, volatiity. Variable concentrations. NMR vs MS. Universality, Sensitivity, Can get both structural and quantitative information. And in red in the center: The metabolome analysis relies on combinations of approaches.

Complementary analytical tools

For metabolome investigation

MS produces m/z masses, and ms/ms structure. NMR produces other spectra. A stacked bar chart compares use of ms only, nmr only, or both across years of publications.

Strategy: untargeted metabolomics

or metabolic fingerprinting

A chart shows an exposed and control group, different tissues being extracted and analysed with NMR, MS, etc. The spectra is processed to reduce the data, and multivariate statistics are done to identify metabolites like glucose, taurine, glycine, etc.

Strategy: targeted metabolomics

Qualitative and quantitative analysis

Samples are extracted, run through GC(-MS) and LC(-MS) to produce metabolome coverage and lists of classes like lipids, polar metabolites, xenobiotics, and other classes.

Thank you!

This material is the result of a collaborative work. Thanks to the Galaxy Training Network and all the contributors! Galaxy Training Network This material is licensed under the Creative Commons Attribution 4.0 International License.