Friday, September 19, 2014
Finally! A way to normalize peptide levels on the fly! Proteomics Ruler!
I LOVE this paper.
I've been trying to write this blog post for 2 days but hadn't been able to find a second to put it down around 12 hours/day I put into my real job. As it is, this is still going to be really short, cause I gotta hit the road!
Measuring peptide concentrations is tough. Have you looked at the CVs you get from peptide quan when using a nanodrop?
In most cases, its the best that we have and it sucks. Most people resort to tricks like doing the protein concentrations and then assuming that they will always see the same loss in the digestion for every sample. My old method was to oversaturate my desalting tips that had a maximum capacity of 5 ug of peptides and assume that the error bar on that maximum capacity wasn't through the roof. Both techniques are probably valid, but wouldn't it be awesome to know for sure?
This is where the Proteomics Ruler comes in. A trick that genomics people use is cell counts based on DNA concentration. The amount of DNA/cell is reasonably constant. You have X number of chromosomes per cell and X percentage of these cells are dividing at any point in time.
The Proteomics Ruler takes this concept one step further -- histones are proteins that associate with DNA -- at a basically normal concentration....so, if you know your the concentration of your histone peptides, then you should be able to derive how much DNA is there AND how many cell your peptides came from. Brilliant, right?!?!?! And now you basically have an internal control on every cell line.
Here is a screenshot I quickly grabbed from the paper!
As you can imagine, they validate the heck out of this approach. They compare it to one of their complex SILAC spike in experiments and find that once they normalize everything out you can get quan nearly as good with label free as with SILAC.
This paper is currently in press at MCP and open access here. It is one that everyone should read and that I should read more in depth.
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