WOOOOOOOOOO! Man, this paper is a lot of fun to read. I can't spend a ton of time typing here. I've got tons and tons to type elsewhere, but it's just in time to be cited in what I'm writing.
Why would you read it?
1) This demonstrates that terminal cell types that we like to categorize as "cardiomyocytes" that don't really divide and more or less hang around the full extent of your life...
- have different proteomes! Does that make them a different cell type? Does that make them a "sub-cell-type"? I'm not the person to answer that question, but it sure does throw questions in a lot of places.
Really interesting methods in play here as well. Dual Trap Single Column loading with short little columns allowing some really fast cell-to-cell throughput? Pretty statistics stolen directly from the single cell RNASeq people? Not the highest coverage you've ever seen per cell, but a demonstration that if you do a bunch of them you can find really cool stuff to look at. (Maybe 800 proteins/cell average?)
Importantly, they didn't just get cells from hearts they also took some stem cell things and made those into cardiomyocytes and studied how those were the same (and not the same) as the cells from the actual hearts.
Minor gripe - the study is definitely a bunch of different cells from different places (5 types of IPSC derived cells plus some cells from ACTUAL HUMAN BEING ACTUAL HEARTS) but the abstract and conclusion bill it as a very large study. It is 1326 cells. Which is a lot. That's as big as the SCOPE2 study from 2020(?) and we all sort of aim to do more cells than that paper. There are probably 8 studies that have done that many cells or more? Was it a crapload of work? Hell yeah it was, but it'll disappoint your scSeq friends. 😇
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