Whoa. Day 1 kicked off with "you should get another espresso, Ben" this is some heavy stuff. Preprinted here, though!
For you mass spec nerds the method is worth thinking about. What if you spiked each single cell with the same SILAC heavy bulk digest? It looks like it works really well, but what he cares about is intrinsic vs extrinsic noise in -omics datasets.
Damn, what a cool work. They also do metabolic labeling and then single cell proteomics. And I honestly think the preprint contains every detail necessary to reproduce this method and analysis. I wouldn't even know where to start for processing SILAC diaPASEF data in DIA-NN, but - boom - they're all there!
Oh.
Ummmmm.......okay....so...this ISN'T preprinted yet, but I didn't beat 3 other people to basically the same question. So...maybe just watch out for an upcoming Parallel Squared preprint from Dr. Megan Elcheikhali where they succeeded in something that an extremely skilled former postdoc in my lab (and many other great scientists in other labs) have failed to do. I'm dying to know what the trick is. (Likely very very many tricks.)
This happens to me all the time:
Someone kicks in my office door and yells "HEY NERD! I'm here to do single cell proteomics! I've got a bunch of brains or livers in this Yeti cooler in the trunk of my car!" And I have to say "Wait. What? Where do you get all these organs? And why did you freeze the whole thing?? If you froze it, the cell membranes definitely ruptured, so you can't sort them. And if they can't be sorted with an intact membrane, it doesn't work.
So....if what she said is real then....about 9 out of ever 10 collaboration requests I turn down might actually be ....viable.... so.... this was a ridiculously important talk.
Man, I really thought I was going to bug out and work on a proposal I really think is going to define the rest of my career, but - damn this panel talk was lit.
Topics covered -
-Most biologists still don't know single cell proteomics is a thing. But the point was brought up that most biologists don't really know that proteomics is a thing. Not in the way we currently do it.
-Slavov shared some tips for how he's finding all these amazing collaborations. Cutting out as much useless jargon as possible and engaging everyone he can in other fields. The 100 Nature family papers probably doesn't hurt.
-Definite concerns about costs discussed by everyone. No real solution yet. 1,000 single cells from some weird cell line is still going to be expensive.
I had to do some ...work...ugh...and I only half paid attention to the next couple of talks.
This seems like the most recent paper out of one of them. Though you'll find these authors are prolific right now.
I had an alarm set for Ronnie Cutler's talk and it didn't disappoint. I'm not sure what I can share from that one yet. Maybe, what if you really did look at integrating single cell transcriptomics - not the read count data, but the other data you get from it. At a single cell level. With PTMs you can target at those same levels, maybe you can find a depressing (for old people like me) story in it?
It's after 3am when I'm posting whatever I typed in this orange box, because I did get to doing the work ...ugh... stuff I needed to. I did finally get to see a talk on how the AIP works from a guy with an amazing last name. If he was at Thermo, new people would infer that he was critically involved in the development of their long running series of flagships. And Bernard Delanghe found out that no one there wanted to look at mass spectra. I feel like there was another preprint I had in hand, but I forget.
It was yet another amazing meeting in a long string of them.
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