Sometime last summer I was sitting here trying to build gene ontology flags for Proteome Discoverer that would flag cell cycle status based on protein expression and hit a wall. This wall wasn't because PD couldn't do what I wanted, it was because -- and you won't believe me until you dig into this some yourself -- we don't actually understand how human cell cycle works. I'm not exaggerating at all. The holes in our knowledge of a fundamental process like this are astounding. And some of the most comprehensive resources on this are transcript abundance based. Cell cycle checkpoints don't work by regulating transcript abundance. That is way way way too slow and the data is largely worse than irrelevant. It is misleading.
I'm not the only one who noticed this amazing gap in our knowledge, but rather than whining about it, this team FIXED IT.
Oh. And this is so smart. Rather than relying on cell cycle "synchronization" (it's a thing and it kind of works) they took a heterogenous population of cells and FACS sorted them with painstaking logic. Don't think about it. Take that method section to your FACS core. They'll get it. The cool thing is that they largely didn't rely on any potentially ambiguous cell cycle markers. The first sorting is on size and shape. There isn't much ambiguity to what a dividing cell looks like, right?
They used multiple biological replicates and cell cultures to get this right. Data was acquired on an Orbitrap Elite and with an HFX(?) and they used high pH offline fractionation to build a library for Match Between Runs. Using a combination of BoxCar(!) and more standard DDA, they end up with nearly 7,000 proteins quantified across all cells and 119 that are clearly quantitatively cell cycle dependent.
This beautiful work has textbook altering ramifications and I sincerely hope that it gets a lot of airplay as such. It deserves to be seen outside of our little community.
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