The 2026 list of techniques for deep plasma proteomics by LCMS?

 

This post is probably not actually about this great new review. I'm just leaving a link about it here because I'm reasonably sure one of the peer reviewers put this team through the wringer. Is that a thing? Why would it be related? I don't know, but it's a great and valuable review! 👮

This post is about ALLLLLLLL the ways we can now go way way beyond those top 300-800 most abundant proteins in human circulating blood liquids. Definitely not all, I can't keep up! Edit: Definitely not all. Geez. The last paper cited below mentions 4 other ones! Okay, maybe later edits will mean adding to this and not just correcting. 

For anyone who has never ran human plasma or serum and is excited to do this by LCMS, do I have some crazy stuff to tell you. If you put that on an S-Trap or something else where you're used to getting 4,000 - 10,000 proteins, you'll probably get about 500 protein groups on your first try. If you've got today's most badass $1M thingamabob you might get 1,000. Maybe. Probably 800 is your max. And that's it. Shameless plug, for the Equalizer plasma proteomic standard, we had a poster at US HUPO where 8 labs contributed data. An Astral Zoom running a 45 minute gradient won't get you 2x more proteins (620) than an LTQ Velos from 2011. The dynamic range is just 

for mass spectrometry. Thanks to the Great Meme Reset I can use this one for the first time in 8 years!

However...if you use new magic techniques that not one single person on planet earth can explain to any other person without the made up concept of a "protein corona" (I blame the Broad for this made up terminology -it's not worse than "the mobile proton model"), you can now dig deeper following chemical or physical enrichments.

Let's count the ways! I'm currently aware of these - 

SEER Proteograph

SP3

Ceres

Mag-Net

PCA and PCA-N 

...which is already a lot....

Geez, and there is a new one I don't think anyone has published on yet. P2 from Biognosys. I may lump it in with SP3 based below until I find out I'm totally wrong. 

Let's inaccurately compare all of them! 

SEER - possibly the originator of this whole field, however, it appears that most attempts to claim this legally as something they've developed haven't gone super well. Some may still be in progress, but at least 2 have been initially thrown out of court.

Pros - probably the best data out of anything we've seen. It is one thing if 50 of the best mass spectrometrists in the country at Cedars Sinai can get 6,000 proteins in plasma. However, I'm hearing that anyone who buys the Proteograph system and reagents for their own lab and runs it is getting comparable results.

Cons - Expensive. O-Link expensive? No. Illumina Protein Prep expensive? Absolutely not. Is the data far more valuable than either of those technologies? Yes, and particulary in the case of the Illumina solution. In my opinion, there is no greater misuse of funds in 2026 than running the Illumina Protein Prep for more money if you could run the SEER Proteograph and get actual quantification data. The fact that O-Link is quantitative and can theoretically scale to far higher levels and eventually be cheaper is a little more defensible. However, in the context of what people are used to paying for LCMS it is a lot of money for a sample prep, and that has allowed other technologies to propagate.

SP3 based - these are a magnetic bead based prep that appears to have a solid number of users. It looks less expensive than the proteograph, but I think all 5 of the published comparisons have found it to have inferior results. It should also be noted that this prep requires that your soluble blood proteins (plasma/serum, whatever) is prepared by the clinicians or phlebotomists in a very specific way. If you DO NOT have control over this, you should very very carefully read those instructions. You can't just put any blood plasma/serum thing in it from any old biobank into this workflow and expect success. It should also be noted that I have heard from 4 separate people that sometimes you end up with magnetic beads clogging weird things in your nanoLCs. There is a moderately expensive and otherwise indestructible porcelain needle on the EvoSeps and you should have spares on hand when using these magnetic beads. 

The one I've heard most about is the PreOmics one which is called iST-BC3 (which, to be fair is the one that has the very specific limitations on what fluids it is fully compatible with) but I suspect that the new Biognosys P2 one is closely related to this. I think they're both largely or entirely owned by the same company now? It would be smart to consolidate methods if that is the ase. 

Pros - mid-tier cost? Commercial support kits still mean commercial support teams (people to complain to and get help from!) My impression is that you're talking 1/2 to 1/3 the price of a Proteograph prep. So if SEER is $300-$400 or something, this is closer to $100? I'm sure it all depends on scale, etc,.

Cons? - Might not be compatible with every type of human derived blood proteins. 

Ceres - is some sort of a porous thing amabob and they're making a splash on the scene right now by being willing to send you a free kit to get going. If you're struggling I hear you can get an applications scientist on site to walk you through it. Our first attempt with a kit involved going away from the established workflow and the results were still an improvement, but below the expectations of Ceres and I think someone is coming to help us out later this summer. Ceres got a big endorsement from one of the best proteomics core labs in the country. The total plasma proteomics workflow - including enrichment and analysis - is advertised as considerably less than an enrichment by Proteograph. That seems to indicate a very cost-effective enrichment. They aren't advertising Proteograph level depth, but expecting 3k proteins in plasma was science fiction a couple of years ago. 

Pros - Solid endorsement and good numbers, and US based support team. Sounds very affordable. Tens of dollars? 

Cons - Might not be the best numbers out there yet, and there isn't nearly as much published data for it out there. 

Mag-Net - wow, this one is confusing and controversial for one reason or another that I don't want to go into. I've heard that it might be due to how one group prepared the plasma without following the published instructions. Here is a good comparison. 

Ugh. This paper points out 3 other enrichment kits that I didn't even know about! Okay, maybe I need to add to this one later. Okay, well, that's where there is a link here. These authors (who I think are completely unrelated to the Mag-Net inventors) report 4500 protein groups from plasma at "a remarkably low total cost of just a few dollars per sample" 

Their words, not mine. 

Pros - Very low cost, depending on how you do it. One core facility said you're talking about $5 -$10 in beads depending on where you get them and scale. 

Cons - Might still be some controversy on it, but an increasing body of work suggests that it works just fine. If you do want to get some support on the workflow, this might be the central workflow endorsed by EvoSep. Maybe they'll have kits? 

Perchloric acid (PC / PCA / PCA-N) 

If you want to avoid particles entirely and just want a quick step with a weird acid or two, this is interesting. I've personally tried PCA-N and I found the results kind of -meh, but I have rarely done a great job of a new sample prep in my first attempt. PCA-N is the easier one of the two, you don't need a filter thing. You neutralize out the acid with NaOH or something and then you go right into your workflow. Perchloric acid is cheap and NaOH is virtually free at the amounts used here. It is worth noting, I think, that a group has recently reported no significant increase in the proteome when plasma was depleted of platelets with high speed centrifugation, so the method might be more controversial than you'd guess. 

Pros - Almost no cost or time addition to prep. Add acid, pellet, neutralize. Filter if you're doing the original prep (with reusable filter things I don't fully understand). 

Cons - Probably the least improvement in coverage. I think in the inventor's own studies neat plasma came in at 500-800 proteins per sample and PC and PCA-N got you to 1,000 - 1,500 protein groups. An improvement? Yes. Fast? Yes. Competitive with all the other stuff in terms of coverage? Doesn't sound like it. But a PCA-N study is coming that is 50,000 samples...so even a $20 prep kit is a lot of money. Is that $1M?? Extra on top of everything else? Ouch. So if you get some acid and NaOH from a pool store and it's virtually $0 to do that step? 1,500 proteins for no additional cost or $1M for 3,000 proteins will make a difference in a lot of studies. 

Okay, this was helpful for me to type out. And then arranging them the way I did by descending cost, which does, with possibly the exception of Mag-Net, depending on which paper you believe, seems to also lead to decreasing relative coverage. 

If there is a take-away here, every single one of these will give you more coverage than a neat digest of human plasma. You're looking at doubling proteins at an absolute minimum (probably) to getting 10x or 20x more protein groups. Every single one of them will provide quantitative data. Which is something you can not get from Illumina Protein Prep or SomaScan. If you actually want to know how much of each protein is present, then that's a no brainer, and every one is less expensive than that technology. Depending on which O-Link kit, etc., that you use, your scaling, etc., it's probably close to the cost of doing SEER, and I think that Proteograph will be - in almost every possible situation - the less expensive option than O-Link deep unbiased stuff. Sure, maybe if you're doing a million samples Thermo will cut you a break, but you still aren't getting those million samples back for a year or four, I don't care where you send it. Although new preps are rumored that might be able to get up into the 1e5 samples per year if nothing breaks and you run a prep every single calendar day. Nothing is going to get you to 1e6 without buildings full of robots. Who has that much (good) plasma anyway? 

Finding long "non-coding" RNA microproteins for diagnostics!

 

I wish I had more time to spend on this one, but I've got to get out the door.

The best I can tell, no new data was generated for the study. What it did was leverage riboSeq data in public repositories in tandem with well-curated proteomics data. Looks like CPTAC and another study of hepatocarcinoma. What they're looking for is sections of RNA that were protected by the ribosome, and are therefore likely in the process of being translated to protein.

Then they take those sequences, make a FASTA database and go back through the proteomics data looking for them. Ultimately, this approach probably has applications well beyond "just" looking for microproteins, you could leverage this to look for challenging sequence based isoform/proteoform descrimination as well. Looking for microproteins, though, opens up a whole new aspect of the proteome. Given the complete lack of useful diagnostics and drugs (only 30% of these patients respond to best in care therapies today....) microproteins is a fantastic place to look for things. I expect I'll end up reading this one more than once in the very near future. 

Someone bought Ignite for $150M dollars!

 

Yesterday I really wanted to play basketball and I walked onto a court even though there were high school kids on it. Every ice pack in our home has been in use since, so I was feeling pretty dumb. 

Wow, do I feel better now. Someone bought IGNITE Proteomics for $150,000,000.00 dollars. 

If you aren't familiar, Ignite is a reverse protein array. Their only current product that I'm aware of is a 32 protein panel that costs $2,200 per sample. I think that I might limp into work and see if my team can measure those same 32 proteins in human blood or serum with a mass spectrometer far more accurately than any protein array could. Then we can all go back to what we were doing after lunch. 

The proteomics industry is alive and well today! And investors are still out there making the same decisions! 

Read more about this topic at GenomeWeb here!

Two new preprints on differentiating single cells!

Yo, these are both SO cool. I'm very very jealous. I've been trying to find collaborators who can differentiate out some cells for me for over a year now. 

I'm lumping them together now becaus I'm still trying to dig my inbox out. 

One is cardiomyocytes! 

And they use the AIP! Apparently these can only be obtained in certain countries, btw. In Austria, they'll sell you the upgrade, but you can't get it installed. 

And this one is differentiation out to motor neurons! So cool.

If you were a total jerk you could point out that this is differentiating big cells out to massive cells so there is a lot to work with (respectively) in both cases. If you were someone who does work in liver cells - which are also gigantic and have exceptionally friendly copy number distributions (600-ish proteins make up like 85% of the hepatocyte proteome and they're probably the proteins you care about in the liver), it would be better to delete this whole paragraph. Or....try to insert a GIF from a Mac and fail again! 

Ultra-high speed high resolution LCMS shows we're still underestimating proteomic complexity!

Wow, there are so many great ASMS week preprints, I can't even read all the ones from Jenny van Eyk's lab. This one, however, needs to jump the queue, just a little.

The topic of the paper is well detailed in the title. It's a comparison of Asstral DDA vs DIA. There are some gems in it, including the statement "DDA isn't dead yet". But what is really really super interesting is the relatively low degree in overlap when they run the same samples with DIA, small window DIA and DDA methods. Which leads the authors to type out this really really cool paragraph. 

Okay...so why do I love this so much? Let's go back in time 12 years or something to this paper I ranted about a second or third time here. 

In 2014 or so, these authors used an Orbitrap Elite and ran some long (by today's standard) gradients and just counted the peaks that they saw. Using a D20 let's call it "low field" to differentiate it from the next generation of D20 Orbitraps, a system with an approximately 2 order intrascan linear dynamic range - they could count over 100,000 peptides. 

This is funny today because people are routinely identifying more than 100,000 peptides in their single shot samples, but at the time it was a benchmark. We were only fragmenting 15,000 things with DDA approaches then. It demonstrated how much further we needed to go for complete proteomes. 

Now with today's fastest stuff, these authors - on one instrument just keep finding new stuff. Just by running the same sample with a different method. It should be humbling and exciting to see just how far we still need to go to actually "-ome (ALL the things) the proteome. Or frustrating, I guess, depending on who you are. Lots and lots of gold in this preprint. 

Scone - printing tiny ESI emitters for dramatic signal increases!

Could the next advance in LCMS sensitivity actually be --- 

 -- is this the most perfect gif ever for...

This new study? Is it the most practical thing ever? I'm going to guess probably not, but the sensitivity gain math is large enough to think about it for at least a minute or two, if you haven't already. 

GPT-Rosalind! Purpose built LLM for Life Sciences!

 

If you've been on this "science" blog: 1) I apologize and 2) you might know I'm very skeptical of teaching bitcoin miners how to put words together into LLMs (I'm pretty sure this stands for lazy lama math).

However, when I saw the above plot on this site for an incredibly absurdly overvalued company and their made up metrics for the performance of their tool, I had to think about it twice. 

Please note that I did edit the plot above because you can't have an axis without units labeled. As a reviewer and editor, I feel that I applied the correct units to this plot and consider it a service to the nameless person who made it. I'd send it to them if there was a name on it. It might be billions of gallons of water and trillions of watts of electricity turned into dollar bills for the crypto bros who do this lama stuff now? But I think I probably labeled it accurately. 

Waters ASMS releases - wait. is Waters thinking about proteomics again?

 

This post is a little delayed because I needed to do a check of what I know vs what I'm allowed to talk about. 😇  I'll select a random date to reinsert this. 

What is Waters doing on a proteomics blog? I guess I mentioned them last 2 years ago when they rolled out the reflectron thing. That thing was doing 100 Hz at 100,000 resolution. Which would be insane at any other point in history but is sort of normal today. 

But they had talks on DIA proteomics this year! 

And they had a new box that, according to this weird site...

Wait. So 2x faster ...is that 200 Hz?? Or are we doing less passes to get there (which would decrease the resolution)? It's funny that this sort of ran under the radar. 

SCIEX ASMS 2026 focus - efficiency and affordability?

 

Another company at ASMS is also thinking in a new direction. SCIEX rolled out just one piece of hardware, the novus55 QQQ/QTrap system.

This cute little box is focused on being space, energy and temperature efficient, while still being screaming fast. There is an example 20 min method where something crazy like 500+ pesticides are measured. It might be 800. I forget, maybe that was transitions. Still, I've never built anything above 130 MRM targets (<200 transitions, for sure)  and that didn't fit in 20 minutes.

But here was the big takeaway. SCIEX thinks that the 8600 and 7600+ systems are ready for prime time proteomics right now. And they're ready to put their money where their...mouths...are...? Is that a saying? 

I don't think these numbers were shared with me because they're secret. Normally people make me sign things if they have secrets. I was told academic pricing on an 8600 is $500k with $25k/year academic service deals. To put that in perspective -- I have a quote on my desktop for a new TIMSTOF Flex system. It has a MALDI2, but otherwise it's the exact same system we bought in 2020. Great system and I'm still writing up papers from data from it. 

Would I rather have another TIMSTOF Flex? Or 4 (FOUR. QUATTRO.)? 8600 systems? Or 2 and a half Asstral 1 systems? I think my best Asstral 1 system quote was $1.2M without an LC and stuff. This was during my lab setup and I know that prices change all the time. Actually...

As a reminder - just a couple years ago these systems were >$1M. 

I signed up for a demo for whenever they can squeeze in some time for me.  Because scientific funding isn't getting better here.  And I literally don't even know how you fund a system over $1.2M USD? Like...how.... for real...actually asking.... I told everyone at SCIEX I don't actually have $500k either, but I'm willing to wait in line because the odds of me finding a project that is really cool and important and could be done with a $500k instrument is about 4 times better than me finding....$2,000,000 USD.

They also rolled out software updates for the whole ZenoTOF line that should be coming close to 1Da SWATH windows with pulsing enabled. I think they were previously getting closer to 3 or 4Da. I really enjoy reprocessing the 2Da DIA window data from the Asstral. Could I get half the coisolation interference for less than half the price? 

Bruker ASMS! No new releases and hopefully a refocusing on support?

 

Edit #3 (6/8/2026): 

This original and then second post generated way too much traffic and too many messages. I've got 2 proposals I'm working on and don't have time for it. So...I took it down and took a little break...

Actual Bruker release at ASMS didn't feature new hardware, which I was very excited about. There is a new diaPASEF variant and some improvements to the PASER/BPS thing. They just rolled out the AIP and TIMSOmi last year and this year was focused on applications of these devices. Cool stuff across the board. Hoping this means a focus on supporting the stuff that is already being sold - that is probably better than we know - because people just haven't had a chance to really pressure test it yet. 

Let's see if I can recapture my original impressions and sentiments without the emotions from what has recently been a bumpy road as a customer of the company. Said rough road from my perspective is that I keep seeing new instruments absolutely everywhere and I have not seen anything approaching a proportional increase in the number of people to support said instruments, at least in my geography. This goes for both field service engineers (the ones that install and fix the stuff) or application specialists (the people who troubleshoot and/or develop new methods). In the latter case I feel like there is actually a decrease and can cite specific examples of emails that now bounce, including to some of the most experienced TIMSTOF support scientists in the country. 

Don't get this mixed up - good, well-trained, qualified people are still out there. But if you go from selling 1 instrument every 3 years in the United States to selling 3 instruments in each decent sized city per year, support should scale. In addition, I've personally seen a rapid escalation in the prices of the instruments and service contracts. Escalation that could and should more than make up for global inflation. It's tough to not be frustrated when you see a company increasing prices, decreasing support and buying every silly looking company in sight.