They say you learn something new every day. This is especially true for me a few weeks ago; I went on a course for something about which I knew almost nothing: a subject called metabolomics.
OK, first thing: -omics. We have genomics, proteomics, microbiomics, transcriptomics, biomics…and at this point I start making them up. -Omics refers to ALL OF IT. ALL OF THE THINGS IN AN ORGANISM. COLLECTIVELY. Or something. Genome refers to all of the genes in an organism. Therefore, metabolome is all of the metabolites in a organism – it includes amino acids (the building blocks of proteins), fatty acids, lipids, alcohols and sugars. Pretty much any smallish molecule involved in the biological reactions that keep living things alive. Larger molecules, such as proteins are not included.
Metabolomics can be broken down into a number of stages. So you’ve got your thing that you want to measure – what’s the difference between me before eating and me after eating? Let’s say we collect some of my blood before I eat and then some more after I eat. We want to compare them; see what chemicals increase and what goes down. Collection methods are important – we don’t want any of the chemicals to degrade or go through further biological reactions between collecting the samples and testing the samples to see what’s in them. Probably the best way to do this is to freeze the samples in liquid nitrogen. It’s not just for mucking about freezing carrots.
The second stage is identifying all the metabolites in there. This can be done in two ways; if you want to see everything that changes – you can do a quantitative, focussed method targeting a group of compounds using gas chromatography – mass spectrometry (GCMS – complicated chemistry thing I’d forgotten since 1st year undergrad) or a more broad, less quantitative method of seeing everything at a basic level.
Identifying chemicals from this involves looking at a series of wibbly lines to see how much there is, how much it weighs (molecular weight), and what kind of chemical bonds it has. Generally – you compare the wibbly lines to wibbly lines of known chemicals.
The next stage is comparing a bunch of these metatbolites that you have identified in you two different samples, be they from me before and after food, or patients with and without a metabolic disorder to improve treatment. This can be done with statistics – one such test being principal component analysis. It looks like a cluster****, but it is very good at finding the things in the two samples that are most different from each other.
The final stage is looking at your metabolites that are the most different between your two different samples, and figure out what biological processes it is involved. Look at the enzymes involved in its generation and its break down, and identified the genes associated with it.
Why is this important?
This information could be useful in deciding which genes to target in genetic modification of plants, looking at disease markers in plants, evolutionary differences between plants and animals, biomarkers for disease, markers resulting from medicinal drug intervention and environmental stress. And potentially in the growing field of personalised medicine.