SCPro - Not single cell proteomics, at all, in any way, but still pretty cool!

 

Here, I fixed it for ya! Even though I can clearly see why I also wouldn't have recommended Ben Orsburn as a reviewer for this one, I do actually really like this new study. 

I will, however, complain first. Last week I had a great meeting set up with a potential funder for my program and we got to an impasse that was something like the most important person on the call saying

"-of course we understand that single cell proteomics is not actually a single cell" 

And, while that was not at all unexpected because this was not a dumb group of people. They're up to date and read a lot and obviously they realize that

THE VAST MAJORITY OF "SINGLE CELL PROTEOMICS" PAPERS 

DO NOT

DO PROTEOMICS ON ONE (1) CELL. 

They don't do one cell because it is still hard to do. Believe me, I don't care what hardware you have you really have to be on your A-game with everything planned out and have some luck (no lab floods helps a lot) and a 384 well plate that is slightly mismanufactured so it sits silly in your CellenOne can break some expensive glass and you walk away with nothing at the end of a 14 hour day in the lab when you didn't get to stop for lunch (true story).

So people do things like flow sort 1,000 cells as in the study above or they stain and cut out 10 or 200 cell regions based on cell type specificity markers (as they also did in this study) and to really boost the impact of their paper they put "single cell proteomics" in the title. Or, if they're super on their marketing game they'll name their not-Single-Cell-Proteomics method something like SCPro. Deliberately confusing? 

Again, in this study - which I do seriously like - they do both. The microscopy is nice, the flow sorting looks good. The front end prep on a tip with SCX and C-18 is - in my somewhat professional opinion - probably a whole lot of extra work for very little actual gain over doing something with less steps and places for lower concentration peptides to bind. But the library generation and diaPASEF analysis on a TIMSTOF Pro results in a solid number of IDs. (50 um custom columns, with low flow rates on a nanoElute). When you get down to what looks like to my eye, probably 5-ish cells sliced out, (probably 1ng-ish of protein/peptide) they're getting 500 proteins, which is a solid achievement. At 10-30 cells they're getting above 2k. (maybe 2-6 ng of protein/peptide). Again, nice numbers. 

The downstream analysis is well integrated and the files are publicly available for both the LCMS files (I haven't checked, my office PC has software on it that doesn't like the iPROX access portal sometimes). 

Again, it's a nice study, working with a grand total of 100 nanograms of peptides from 1,000 flow sorted cells does still require some finesse. It is, however, frustrating to spend weeks optimizing the isolation of one (1) single cell at a time and analyzing them one at a time and then hit these new perception hurdles. Like - well, this other lab is doing single cell proteomics (they aren't) or that no one can actually analyze one single cell when we have whole conferences where the admittedly small number of researchers actually doing one cell at a time do speak about it. 

These perception hurdles have always existed, though. I have little scratches in the surface of my relatively new tablet where I've broken the expensive little tips off of the pens that can write on my relatively new tablet when people have said "well, mass spec isn't quantitative." 4 scratches in the last 2 years, for sure. 

This would have been a super positive review (aside from the SCX/C-18 tip) without the title and misleading name for the technique. 

Proteomics of ...spontaneous achilles rupture....

 

I would like to thank these authors and the prestigious Journal of Proteome Research for something new to have nightmares about - 

SPONTANEOUS ACHILLES EXPLOSIONS! 

Proteomics to the rescue! (By the way, there is this whole series of bizarre children's books where there will be some silly problem and it's all COWS TO THE RESCUE or something. It's funny by the 11th page and continues through the 6th book somehow.) 

Obviously, this group wants to understand why sometimes people's achilles up and explode just for fun, and they are able to get samples from patient who end up getting correction surgeries! Obviously, this is yet another place where genomics/transcriptomics of the tissue will probably tell you nothing - so it's proteomics time! 

Interstingly the group breaks out iTRAQ 8-plex and does pooling, offline fractionation (by SCX, I think, but I forget now, did a singing daycare drop between reading it and now) and then analysis of the fractions on a Q Exactive (Classic, I think). All the files are up on PRIDE where they should be. I have no issue with iTRAQ 8-plex here, by the way. They turned up the collision energy, fragmented each target 2x before putting it on the dynamic exclusion list. The 8-plex allows them to run the QE at maximum (vendor permitted) speed with 17,500 resolution at m/z 200. 

What I do have an issue with is the surprising pictures of the operation itself!! I was expecting a calibration or volcano plot and - blech. 

Seriously, though, it is all pretty intersting. There are structural differences in the ruptured tissue that are clearly visible and they go into depth with IHC. They find a panel of targets that might be indicative of potential rupture candidates? It's a super compelling study all around - on something I now get to think about. 

Interestingly...I think this is a dataset that would be a solid candidate for a reanalysis because it looks like this group didn't consider common collagen PTMs. I'm assuming when they considered dynamic oxidations they exclusively mean methionines. Collagens are hyper-modified. In fact, in the BOLT cloud search engine, Amol wrote in a whole crapload of common collagen PTMs in the first pass search because they're just that common. I think he got that idea from the cRAP database guy, whatever his name is. 😇