Sunday, April 9, 2017

SCoPE-MS -- We can finally do single cell proteomics!!!

I seriously can't wait for ASMS! Yes, I'm normally too enthusiastic about the awesome stuff you guys are doing, but -- wow -- I'm just blown away with the jumps you guys are making right now. MetaMorpheus, Prot-Vista, PTM-Oracle are all game changers in my mind -- and I'm gonna stack SCoPE-MS right on top of this list.

SCoPE-MS stands for Single Cell ProtEomics by Mass Spectrometry and you can read about it in this open access paper here.

The paper hasn't gotten through Peer-Review yet, but it will. This is one of those simple and elegant solutions that will immediately make you think "oh...why the Albert Heck didn't I think of that...?!?!"

Boring/possibly incorrect biological significance stuff: Single cell -omics is a big deal right now. When you are mixing a population of cells, lysing them and reading the signals you are getting averages of the cells there. And we often don't want that -- especially in eukaryotic systems. I have friends at different institutions who use completely different approaches to only study certain cell types within tumors (tumors get crazy complex as they differentiate) and if you lyse cells from them indiscriminately you may lose what is going on. Even if you collect cells by laser microdissection that stain the same or have the same surface markers so you can collect them by flow cytometry or something you are still averaging signal. Having one cell -- that's serious...

...Holy Grail stuff!!

Okay -- but the DNA/RNA people have the polymerase chain reaction (PCR) so they are way way more sensitive than us. They really can get one cell, get the DNA/RNA, amplify it and then sequence it. Even with a Lumos, the limit I think I've seen is a decent proteome with 100 yeast cells, right!?!?(can't find the reference right now)

Back to SCoPE-MS:  This technique effectively multiplies your sensitivity by 200 fold!!!

How?? By taking what is generally considered a weakness of isobaric tagging techniques (like TMT/iTRAQ) and turning it into an advantage!

Let's review the TMT workflow first (TMT is a trademark of Proteome Sciences, btw):

1) We extract peptides from out different conditions
2) We tag them with the TMT reagent -- adding the exact same mass tag to every peptide
3) We combine all the tagged peptides
4) We do normal proteomics
5) In the simplest examples (Q Exactive, for example) we get one MS/MS spectra that can be used for identifying the peptide and we get the tag fragments in the low mass range.

For all intensive purposes, the dynamic range of these tags is somewhere between 2 and 3 orders of magnitude. Most processing software will say that if the ratio between your 2 tags differs by over 100-fold, it will give you the maximum ratio of 100-fold. That is default, and I think there have been cases of studies showing linearity much higher than this. Don't quote me on this (don't quote me on anything!), but I don't think anyone has shown linearity beyond 3 logs, even on targeted TMT. Honestly, however, I doubt anyone has looked into it too far -- if your protein is up-regulated 87-fold or 821.4-fold you probably are going to investigate it!

Wow, I have been working on this too long. Y'all -- it probably looks like I throw these together in like 5 minutes (okay, sometimes I do), I gotta wrap this up...someone looks ready to go kayaking!

In SCoPE-MS these authors divert the "normal" TMT proteomics workflow. Only one channel has a proteome with a realistically detectable amount of cells for obtaining a good proteome ~200 cells. This channel is used for peptide identification. The other channels can have as little as one individual cell!  (Please see figure at the very top of this rambly post which explains this better).

You have 10 TMT channels:

One channel is blank for determining noise levels (you'll need it here)
One channel has peptides extracted from 200 cells (a normal...though still impressively small! amount of cells)
The other 8 channels can ALL be from individual single cells!!

The channel with the 200 cells provides enough material for peptide selection for fragmentation and peptide identifications!

Then you can see in the TMT tagging range the relative quantities of the peptides/proteins in the individual cells. You are below the current dynamic range of peptide identification with the single cell channels, but you are well within the dynamic range of the TMT tags!!

How'd they do?

This is the correlation between proteins they found and the results of RT-PCR -- often considered the most sensitive biological measurement possible. Yeah. That good.

They use an Orbitrap Elite for the TMT LC-MS/MS. They do some seriously thorough optimization and downstream statistics. Data processing appears to be all MaxQuant.

Single cell proteomics is finally a real thing....and it is multiplex-able and quantifiable. What an amazing start to this beautiful day!

EDITS: Dr. Norris was surprised by the apparent level of correlation here between the proteome and RT-PCR. This looks substantially higher than what we've come to expect from most studies in the literature. Fascinating thought here -- what if the variability we've come to expect between RNA and Proteome is because RNA levels are more stable among cell averages than the protein levels from cell to cell? If that is the case, it seriously builds the case for how essential this technique is and will be in the future!

Also replaced some incorrect "your/you're/yer".


  1. You got to know it is still not single cell at all. They still average dozens of cells together.