Transcriptomics and spatial proteomics by IHC for missing proteins in the human ovary!

Hey! This is all RNASeq, single cell seq and boring old immunohistochemistry! And, you know, what? It's an impressively constructed argument that adds about 20 proteins to the human ovary that we didn't have any protein level evidence for before! 

BTW, does anyone know of a snipping tool equivalent for MacIntosh? This whole "make a super high res screenshot and upload it to google thing" slows me down a lot more than it should. What was I....oh it uploaded! 

So the human protein atlas (www.proteinatlas.org) obtained new material from ovary/oocytes across a range of ages and they did RNASeq and came up with a bunch of transcripts for things that there is no protein level evidence for. They did "high resolution" IHC (which is basically fixing thin tissue sections to slides, fixing with formaldehyde or something similar, permeating [been a long time, I forget the order you do this stuff] binding with antibodies and then doing microscopy). It's high resolution if you've got a better microscope than those bums down the hallway. When they upgrade to something better than yours, then it's ULTRA HIGH RES, and then you're on your own to come up with a name for it when you get that S10 to get something even better. However...actually....you could listen to PowerMan 5000 for inspiration, I guess. 

Worth noting, there is lots of meta-analysis of the existing human protein atlas (HPA) in this paper - also worth noting, a lot of the "protein expression" in the HPA is based on transcript abundance with correlation to IHC. That's why when you get a visualization of the expression of a human protein across various organs you get Starbucks terms. Which one is bigger, Vente, Grande, or Impreza? Sometimes helpful, though, but caution is advised. 

What is cool in this study is that there are rarer cell types here and expression of proteins in these cells were previously below the limits of detection in the HPA. This study employs single cell RNASeq, which I presume is done by extracting the nuclei (which is an awful lot of scSeq on humans, btw). When they correlate their high resolution IHC which can visualize the antibody binding at a single cell level, it matches up well with the single cell seq. 

I'm fuzzy on how they got their antibodies, and I already typed too much today, but this is a short read on proteomics techniques that are really easy to do if you've got a decent microscope and some patience.