I am super pumped about this one, y'all! Okay, as you might have noticed I LOVE to talk about mass spectrometry and proteomics. So much so that sometimes on my 45 min to 1.5 hour commute (each way...blech...) sometimes people will just call me and ask me questions and I'll think later to ask who is interrupting my relaxing death metal time. The last 3 years or so it has been things like "what is THE application for single cell proteomics where nothing else exists that can compete with it?"
This is one answer I've kept to myself. (Largely because I've pitched it a bunch of times, including at an epigenetics meeting and the response wasn't encouraging...)
If you are doing single cell proteomics (well) everything has to be perfect. Your sample prep, your instrument, your sample prep, your environmental conditions, and - especially - your sample prep.
But even if you are having an off day with your sample prep and you only get 158 proteins detected per cell - chances are you've got pretty decent coverage of at least 9 histone proteins. That's because they exist in millions of copies per cell. They do sorta suck because they're packed full of basic residues and trypsin cuts them into little bits, and they elute early enough that they may not retain on your trap column well.
But there are people out there that really really really care about histone PTMs in single cells!
Check out this 2023 Nature Biotechnology paper. They successfully measured 2 (TWO!) histone PTMs in single cells! Someone later this year did three, but they can't do 3 simultaneously. They can do a bunch of cells with 2 and then a bunch of cells in the next batch with the third one.
What my paper shows is that even when using relatively high flow nanoLC/microLC with relatively low coverage per method (by today's insane standards!), I can pretty easily pick up 16 different histone PTMs. And as I increase the throughput, as measured in cells per day, those numbers don't change much. We're sampling the histone peptides over and over and over because there are just so many of them!
Now - I did use the TIMSTOF SCP system for this study - and it is blazingly fast even when you've only got like 15 nanograms of peptide load on the system and are running at 1uL/min flow rates or higher. However, I've reprocessed just about every single cell proteomics dataset out there in the world (...which...honestly...isn't all that many...) and deep insight into single cell epigenetics/epiproteomics is available in just about every one of them (with the obvious exception of the non-nucleated cell differentiation studies)
Just because this one is currently open on my desktop - check out the most recent preprint from the Slavov lab (maybe my first post of 2024, on here somewhere) where they did cancer cells that they forced into the epithelial mesenchymal transition with TGF-beta treatment.
This study uses a very very clean Q Exactive Classic running 70k MS1 (100ms fill) and top 7 method with 70k MS/MS with 300ms fill times on a 100 min run-to-run cycle time (90-ish minute active gradient). Translation - this data is beautiful - about 2x the resolution of my stuff (about 4x in the low mass region) at the consequence of about 1/4 the number of spectra/file and about 1/10 the number of spectra per unit time. And here is 100% sequence coverage of a histone acetylation site that is seen in about 60% of the single cells in this study.
Funny thing about K+acetyl is that it makes a BEAUTIFUL and very distinct diagnostic fragment ion that holds onto the proton with extreme veracity. If you don't see it in a peptide your search engine says is "acetylated" your engine might be wrong (or you didn't scan low enough)
And here it is in this Q Exactive file --- clearly distinct from the carrier channel used in this study (the 126 in the TMTPro 18). You can click to zoom, but the 126.09 is K+acetyl!
Cool, right?!? Okay, so who cares, right? I've shown that I can see these histone PTMs in at least 2 accepted papers so far, but what's the application? Honestly, whatever people study histone PTMs for, right? At the genomics thing I went to they were talking about epigenetics in evolution and in heredity and all sorts of other nerdy stuff that I'm sure is important.
What I do, however, is study how drugs work and how cells adapt to drugs. And there is a whole class of drugs out there called "histone deacetylase inhibitors" so I chose one that currently has a limited use authorization from the FDA and has a very promising sounding (see all disclaimers) ongoing clinical trial and I had a new MS student (thanks Tarsh!) dose some cells with the drug, then we pseudo randomized control and treated cells after TMT tagging them and -
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