TMT phospho was on my mind all day yesterday thanks to hanging around with a TMT and phospho expert for 12 hours or so.
For a really elegant example of a study that worked for this methodology, check out this open access study from Yi Fang et al.,. The figure above really kinda sums up this work. What they're interested in is the early effects of a chemotherapeutic in "triple negative" breast cancer cell lines.
What I like about this study is -- it is very straight-forward, simple and totally works. It shows how far we've gotten technically with both phospho-enrichment, isobaric tagging, and data processing. An Orbi Velos does the heavy lifting and MaxQuant is used to compile the data with the whole peptide quan in some channels and the phospho in others.
You could argue that there are better ways of looking at the quantification output than just saying that anything above or below 1.5 fold is significant, but when you end up with ~240 nice phosphopeptides that fall into a downstream analysis like this....
....where these are known DNA damage pathway phosphorylation events!!!....I am not going to argue that you should have drawn your cutoff with some fancy-pants statistical cutoff thing that I don't know how to do myself anyway. (Sorry about the resolution, the paper is open access and this isn't even the best figure in this nice paper! You should check it out yourself!)
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