Nature's Method of the Year 2024 is Spatial Proteomics!

 

WOOOOOOOOOHOOOOOO! 

Editorial here! 

Last year it was long read sequencing or something (they forgot to include it in the 2014 issue, I'm pretty sure).

Check out this special virtual issue (click on the references!) highlighting a bunch of cool people in our field and their work!

Improve your false discovery in your match between runs with PIP-ECHO!

For an old and probably inaccurate description of match between runs (MBR) you can check out this old post. 

Also, you probably shouldn't go past Fengchao and Sarah's paper here. Link might be the preprint.

Quick breakdown, though -

Imagine you run 50 LCMS runs on different patient samples.

In 35 of those runs you fragment and successfully identify PEPTIIIIDEK, it's pretty much 100% +2 charged and 634.3608 and comes off at 15.6 minutes 

In the other 15 runs you see a +2 peptide at 15.6 minutes but you don't fragment it or don't get good enough sequence quality for a positive ID. 

Match Between Runs (MBR) to the rescue! It donates that identification to the runs where it was not identified. 

Perfect idea, right? What's the problem? There are crapload of peptides in any tryptic digest and they coelute a lot. And as the dynamic range of our instruments keeps going up we see lower abundance peptides that we might not have before. 

Compound this with shorter LC gradients

And the fact that every mass analyzer has a +/- mass error

And the retention time on nanoLC, which everyone is pretty much using for some reason no one can justify, is probably more accurately, in those 35 runs, that peptide is coming off somewhere between 14.5 and 16.5 minutes - and now you might be quantifying the wrong peptide. 

The top link above is to IonQuant which works in FragPipe. 

Could you take that idea and build something even better? Maybe! Just do this! 

The comparisons look good, though! And there is some serious nerd power on the preprint. 

I checked the updates and it doesn't look like it's live on MetaMorpheus yet, though something that was driving me absolutely crazy a while back is! (Thank you! I thought my brain had broken (the diagnostic ion is wrong a lot of places - including in software from my group. ) 

Knowing these people we'll PIP-ECHO it in one of the upcoming builds. Fingers crossed it will work outside of the Orbi domain! 

BlueSky is tracked by Altmetric. Twitter is finally dead to science!

Well...that was a run! I was on Twitter for 11(?) years and Tweeted over 10,000 times. 

Mandatory, obviously. 

It's done, though. Biorxiv won't link your Tweets and I don't see a tab on Altmetric. That increasingly bizarre drug addict killed what was at one time the best device for rapidly disseminating scientific advances I'd ever seen. 

BLUESKY is going to be better, I think. The expertise density is legit and some people are starting to figure out some of the cool features that I haven't yet. 

And!  BLUESKY IS TRACKED BY ALTMETRIC, JUST LIKE THIS WEIRD BLOG!  Wait. What? Sure is! And has been for almost a decade. I don't know why, I just type things here with my nice ergonomic keyboard and my broken brain filters. 

SCPro - Not single cell proteomics, at all, in any way, but still pretty cool!

 

Here, I fixed it for ya! Even though I can clearly see why I also wouldn't have recommended Ben Orsburn as a reviewer for this one, I do actually really like this new study. 

I will, however, complain first. Last week I had a great meeting set up with a potential funder for my program and we got to an impasse that was something like the most important person on the call saying

"-of course we understand that single cell proteomics is not actually a single cell" 

And, while that was not at all unexpected because this was not a dumb group of people. They're up to date and read a lot and obviously they realize that

THE VAST MAJORITY OF "SINGLE CELL PROTEOMICS" PAPERS 

DO NOT

DO PROTEOMICS ON ONE (1) CELL. 

They don't do one cell because it is still hard to do. Believe me, I don't care what hardware you have you really have to be on your A-game with everything planned out and have some luck (no lab floods helps a lot) and a 384 well plate that is slightly mismanufactured so it sits silly in your CellenOne can break some expensive glass and you walk away with nothing at the end of a 14 hour day in the lab when you didn't get to stop for lunch (true story).

So people do things like flow sort 1,000 cells as in the study above or they stain and cut out 10 or 200 cell regions based on cell type specificity markers (as they also did in this study) and to really boost the impact of their paper they put "single cell proteomics" in the title. Or, if they're super on their marketing game they'll name their not-Single-Cell-Proteomics method something like SCPro. Deliberately confusing? 

Again, in this study - which I do seriously like - they do both. The microscopy is nice, the flow sorting looks good. The front end prep on a tip with SCX and C-18 is - in my somewhat professional opinion - probably a whole lot of extra work for very little actual gain over doing something with less steps and places for lower concentration peptides to bind. But the library generation and diaPASEF analysis on a TIMSTOF Pro results in a solid number of IDs. (50 um custom columns, with low flow rates on a nanoElute). When you get down to what looks like to my eye, probably 5-ish cells sliced out, (probably 1ng-ish of protein/peptide) they're getting 500 proteins, which is a solid achievement. At 10-30 cells they're getting above 2k. (maybe 2-6 ng of protein/peptide). Again, nice numbers. 

The downstream analysis is well integrated and the files are publicly available for both the LCMS files (I haven't checked, my office PC has software on it that doesn't like the iPROX access portal sometimes). 

Again, it's a nice study, working with a grand total of 100 nanograms of peptides from 1,000 flow sorted cells does still require some finesse. It is, however, frustrating to spend weeks optimizing the isolation of one (1) single cell at a time and analyzing them one at a time and then hit these new perception hurdles. Like - well, this other lab is doing single cell proteomics (they aren't) or that no one can actually analyze one single cell when we have whole conferences where the admittedly small number of researchers actually doing one cell at a time do speak about it. 

These perception hurdles have always existed, though. I have little scratches in the surface of my relatively new tablet where I've broken the expensive little tips off of the pens that can write on my relatively new tablet when people have said "well, mass spec isn't quantitative." 4 scratches in the last 2 years, for sure. 

This would have been a super positive review (aside from the SCX/C-18 tip) without the title and misleading name for the technique. 

Proteomics of ...spontaneous achilles rupture....

 

I would like to thank these authors and the prestigious Journal of Proteome Research for something new to have nightmares about - 

SPONTANEOUS ACHILLES EXPLOSIONS! 

Proteomics to the rescue! (By the way, there is this whole series of bizarre children's books where there will be some silly problem and it's all COWS TO THE RESCUE or something. It's funny by the 11th page and continues through the 6th book somehow.) 

Obviously, this group wants to understand why sometimes people's achilles up and explode just for fun, and they are able to get samples from patient who end up getting correction surgeries! Obviously, this is yet another place where genomics/transcriptomics of the tissue will probably tell you nothing - so it's proteomics time! 

Interstingly the group breaks out iTRAQ 8-plex and does pooling, offline fractionation (by SCX, I think, but I forget now, did a singing daycare drop between reading it and now) and then analysis of the fractions on a Q Exactive (Classic, I think). All the files are up on PRIDE where they should be. I have no issue with iTRAQ 8-plex here, by the way. They turned up the collision energy, fragmented each target 2x before putting it on the dynamic exclusion list. The 8-plex allows them to run the QE at maximum (vendor permitted) speed with 17,500 resolution at m/z 200. 

What I do have an issue with is the surprising pictures of the operation itself!! I was expecting a calibration or volcano plot and - blech. 

Seriously, though, it is all pretty intersting. There are structural differences in the ruptured tissue that are clearly visible and they go into depth with IHC. They find a panel of targets that might be indicative of potential rupture candidates? It's a super compelling study all around - on something I now get to think about. 

Interestingly...I think this is a dataset that would be a solid candidate for a reanalysis because it looks like this group didn't consider common collagen PTMs. I'm assuming when they considered dynamic oxidations they exclusively mean methionines. Collagens are hyper-modified. In fact, in the BOLT cloud search engine, Amol wrote in a whole crapload of common collagen PTMs in the first pass search because they're just that common. I think he got that idea from the cRAP database guy, whatever his name is. 😇

New Hats!

 

It'll take me a while to update everything on all the internet things but we can finally wear these new hats openly.

We'll get used to the colors, though orange and maroon will likely always be my favorite combo.

We're moving so I can get started as Assistant Professor in the Department of Pharmacology and Cellular Biology (through the new institute I don't know if I can talk about yet -soon!). I'll also be helping out Stacy Gelhaus as an Associate Director in the phenomenal Health Sciences Mass Spectrometry center. 

I JUST ORDERED SUPER EXPENSIVE BIG HEAVY THINGS and saw pictures of crates with MY name on them. Not someone else's. My name. Weird. Normally "care of" would be expected.  Huge shoutout to my friends at Bruker Daltronic for helping an Assistant Professor's money stretch out enough to cover what I need to start 

Find what proteins are being made RIGHT now with DADPS!

 

This new paper is an improvement over a super cool already existing technology that I had NO IDEA EXISTED AT ALL. 

Did you know that you could dump in something that cells would mistake for normal methionine that you could selectively pull down, so that you knew what proteins were being made at that point in time? I did not. 

I bet the nerds pulling down ribosomes and cutting the attached DNA with nucleases, then busting up the ribosomes and sequencing what didn't get digested (RiboSeq, definitely not convoluted at all) don't either. Sure, RiboSeq is cool - and programs like ProteoFormer have been around for a while combine RiboSeq and proteomics data output. 

But I don't know how to do RiboSeq. I'd have to go back to a grant application that wasn't funded a while back to figure out who on our team was the expert on that part to even know who to start asking dumb questions about the technology. OR I could just do this? And have an output I understand that says "your drug is causing the cell to start making proteins A/B/C right now?" 

Again, this is an optimization, but the authors use the original long acronym thing you don't need to commit to memory (because theirs is better) and demonstrate that is can also be used with TMT, it seems to work best with SPS/MS3 based TMT quan. 

Cognitive impairment at high altitude? Proteomics (and metabolomics) to the rescue!

 

I don't know about you, but I'm waaaaaay dumber than usual when I'm at really high elevations. Not only dumb, but also lazy and tired and 2 glasses of wine and I might just fall right off of a ski lift. 

I went to a wine convention thing in Colorado at a Ski resort years ago and found out all of these things. 

This study tried to get to the bottom of this by collecting proteomic and metabolomic samples from people who went to work in high elevations for 6 months. Holy crap. Some of this work was at 4,800 meters in elevation. There isn't anything in Colorado that tall. The highest lift I fell off of wasn't even 4,000 meters. I'd be useless up there. 

These authors compared serum proteomics (TIMSTOF Pro with....ummm....I'm not sure I understand what else. SDS-PAGE fractionation? Online? At high pH? And an Ultimate 3000 was used on the TIMSTOF but no details seem to be here for the column, flow rate, gradient length) and the data was processed by ....umm....magic....? No software was mentioned that made the PSM/Peptide or Protein Assignments.  I suspect the person doing the actual proteomics was not consulted by the authors on that section. Or they're author 7 and they're like "f' you guys, figure it out yourself" which I've heard sometimes happens. 

The metabolomics was done on a Q Exactive and there are details. Waters BEH 2.1mm x 10 cm column at 350uL/min for a completely secret gradient length. It literally says "over time" and if you want to know about how they ran the Q Exactive - you did not come to the right authors. No joke, check this out. 

We optimized it for best performance and we will never ever tell you what that was and it's weird you'd want to know. The reviewers were not on top of their game for this one. Weird to see something like this in JPR. Nature something or other? Sure. Not JPR or MCP. Meh. 

The data does appear to be publicly available if you're all nosy and want to know or...you know...if you thought this was cool and you wanted to reproduce this work.

The plots are really nice, though. MSStats was used for the super secret proteomics data and an R wizard was onboard who tells you what packages he/she/they used. Hmm...no version info - but AHA there is a github and it is populated. The biology looks cool and I really dig some of the graphs, so Imma post it. The authors could put the complete mass spec methods in the Github later since it doesn't appear to be published to Zenodo or something that will lock it from alterations. 

The single cell proteomics/mass spec meeting schedule for 2025!

 

Image from my kid's very favorite thing to fall asleep looking at - NIH Bioart! 

When Single Cell Mass Spectrometry is announced, I'll add it here. Please ping me if there are others. I have no idea how I missed that Asilomar thing a couple of years ago, but I still feel dumb about not even knowing that I should be there. 

Here are the first two! 

Single Cell Proteomics (US/Boston/NorthEastern) May 27-May 28

European Single Cell Proteomics (I love this one and it crushed me to miss 2024 in one of my all time favorite cities) Vienna! August 26-27! 

SomaScan - 7k vs 11k - seem to largely agree with one another...

 

I'm leaving this here largely for me to check if I can find plasma proteomics by LCMS that I can confidently link back to this same cohort. There is a lot of LCMS proteomics data from these authors, though all I have actively worked with has been muscle biopsies.

However - people are going to want to use the 11k SomaScan assay that is now out there, and it is nice to see that these authors find - after proper normalization  and a lot of batch effect analysis - that data from these two technologies are aligned.

It should be noted that the precision of SomaScan has been shown to be solid. In 8 years of watching for it, I still haven't seen any evidence that the system produces results that are an accurate reflection of the amount of protein present. 

With the growth of this technology - including the use by some of the best groups in the world, such as this one - I hope hope hope hope that it is actually accurate and one day we'll see proof of it.