Wednesday, September 13, 2023

What a difference 3 years makes in single cell proteomics!


Has this been on here already? I forget. If not, you should check it out. 

There was this sortof secret race going on behind the scenes the last 8 months or so as at least 3 different groups were all trying to publish wide window acquisition for single cells at the same time. Maybe there were more, but I was only a top secret peer reviewer for 3 of them and they all concluded that single cell doesn't work the same way as unlimited protein material in that wider windows really are better, but that's not the moral of this story.

What I want to talk about is what a jump this is in such a short period of time from this one -- 

it says 2021 but these fancy monarchy people take forever to construct a PDF. This was accepted in June or 2020, so it's been right at 3 years. 

I've got a paper due to an editor like yesterday or something and as part of said paper, I've been really looking at these data. 

Check out the copy number distribution shift. Sure - they got more proteins per HeLa cell with 3 years of improvements - and - I guess this might seem silly and obvious, but the shift toward the lower copy number proteins is even more striking to me, because most of the cool proteins can be found on the left side of the plot. 

This was plotted with my Shiny App I made a couple years ago, btw. It took me a month to make overlapping histograms work right in R and I'm going to use this skill like Naruto with the whole shadow clone thing (if you aren't familiar, it took him forever to figure out a simple trick everyone else easily mastered and he basically just used it for everything for a comic book that ran for at least 10 years? I was very surprised to see costumes for characters from this ancient comic book in a local halloween store a few days ago, so I guess it's still around? 

Even more impressive (about the progress that is supposedly the topic of this post? The number of unique peptides per protein went from 4.6 to 8.4! Using basically the same hardware and sample prep. Sure, some tweaks but this is mostly instrument method and informatics. 

Super impressive progress in the left direction! 

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