I'm just taking screenshots of this stunning paper to make sure you read it before I get a chance to. It's not mass spec multiplexing. It's image multiplexing, but THEN deep visual proteomics!
now also at www.proteomics.rocks
I'm just taking screenshots of this stunning paper to make sure you read it before I get a chance to. It's not mass spec multiplexing. It's image multiplexing, but THEN deep visual proteomics!
Wow. What a blast from the past. A new preprint just dropped that describes the triumphant return of what I've long thought was one of the smartest plasma proteomics methods of all time!
Its called NCTPro, but it is very similar to the old method Promis-Quan, and it gets very similar (amazing!) protein coverage!
This is the original Promis-Quan post (paper here) and here is the new preprint!
Hey you! Have you drugged or poisoned or mutated a mouse or rat so that it induces Parkinson's Disease (PD) or schizophrenia (SC) symptoms in? Do you want to fix it?
Do I ever have a veterinary drug target for you! Check out this new paper!
DISCLAIMERS! DO NOT, DO NOT, DO NOT ATTEMPT TO EXTEND THESE OBSERVATIONS TO HUMANS. That would be silly for the following reasons:
There have been a lot of recent advances to try and take advantage of all these crazy fast instruments.
I'll start with the dumbest analysis possible. That's probably all I have time for anyway.
I reprocessed a small population of large single human cells (TIMSTOF Ultra2 with EvoSep One 40SPD "Whisper Zoom") 41 cells that are EXTREMELY difficult to extract intact out of a cadaver.
No filters, no libraries, just the same library free approach, same FASTA database. Both came back with a little over 7,000 protein groups.
Big difference? On the same PC (an i9 desktop tower purchased last year with a ton of ram put in it before the prices went to the fucking moon) diaTracer wrapped up in about 4 hours from beginning to end. SpectroNaut was close to double that.
The reason this analysis is exciting and not depressing is how the respective softwares name protein groups and genes. SpectroNaut gives you your output as a "Protein Accession; Another protein accession" where multiple proteins could fall in that group. The way I have FragPipe 24 set up I just get a single entry.
I strongly suspect the overlap is better than this.
Besides being fast, I went back and reprocessed both of these datasets looking for PTMs in these big single cells. And diaTracer found over 650 phosphorylation sites! SpectroNaut found ...fewer.... Are they real? I dunno! It would be super cool if they are!
Obviously this is only cool if you're an academic who can use FragPipe, but - hot dog - I'm super excited that FragPipe can 1) process my diaPASEF single cell data and 2) it looks like it's at least very in line with software I've used to process thousands of files and have grown to trust over the years!
Hey you! You have so many options today for doing spatial measurements. You really do. There are at least 10 different options for measuring gene products in different cells. I was at a couple of recent meetins where biologists were talking about how much these things cost, and it's impressive.
Direct quote from a core director "Each slide costs me $7,000 in reagents" for her favorite spatial transcriptomics technology. She owns all the hardware!
I pulled some prices for internal at my University and - wow -
There are now ways to do up to 1,200 antibody probes for proteins in addition to single cell transcriptomics. This appears very new (Bruker's new acquisitions) and I've heard it is in line with the spatial transcriptomics.
Let's break this down for deep visual proteomics (spatial proteomics by microdissection) again this is internal at my University.
For a 10x Visium 2 tissue 11 mm capture for $10,900 you get 50um pixels with 100um center-to-center (according to their website) and adding on proteins is an extra $3,900. Let's call it $15k for 2 images with 100 micron resolution.
This is whole transcript sequencing in most cases so they expect 18,000 gene products theoretically measured across the slide and it looks like 35 protein maximum right now per panel if you add that on.
For $11,000 if you cut out 100um spots by LCMS we could (internal) do between 200 and 400 of those spots with proteomics (you'd have to find someone with an LCM to do it - I know a guy) and unless I'm doing this wrong, 220 100 micron spots (center to center) would be more than one 11 mm capture.
A 50 micron pixel would be somewhere in the 8 cell range so we'd expect a proteomic depth of at least 7,000 proteins per "pixel" not "over the total study" or hypothetical. That's solid depth and could easily be mined for PTMs, etc.,
And....we'd deliver a fully processed visual report in a GUI so the data could be fully mined by the end user.....
Compare that to the Xenium at 5,000 genes and $23,500! Holy shit. Xenium might be far higher resolution, I'm not sure, but if there is a takeaway here -
Spatial proteomics (or deep visual proteomics, if you prefer) is WAY WAY less expensive than spatial transcriptomics.
And....at the end of a deep visual proteomics experiment you don't have to do a western blot to see if any of those gene products actually....you know.....are real at the protein level. Which, depending in how you count the cutoffs, about half of them are actually real.
Maybe this is a rant, but holy shit, I do love spatial transcriptomics and their pretty slides. But when I see 4 slides in a talk now I know they spent $60k - $100k on their n=1 data. And then they did IHC or western blots after. It seems like a misuse of resources.
I've been generally confused about the whole "FragPipe + DIA" thing for a while. What's the DIA-NN node doing there....? Why wouldn't I just run DIA-NN...? (for examples.)
When a new way to process DIA data showed up last year, I had my hands full and just didn't get around to it. I've got SpectroNaut, BPS and automatic command line DIA-NN (academic version). Why would I need anything else?
What if you are an academic and someone set you up a very nice interface where they'll just load you up anything that will run in Linux? And you don't want to type stuff into a command line? And you don't want to convert your Bruker files? And you don't want to pay anything for it? And you don't want to mess around with making spectral libraries yourself?
Need THE crash course in doing shotgun proteomics statistics? Enrollment is open for the upcoming May Institute (I think that is what it is called. Not the month.)
Do you (or your reviewers!) need more than a text file to prove you did some proteomics?
There are some nice DIA-NN tools out there now that make looking at these data at depth easier, and this is seems like a nice new entry.