You can slow an Astral way down and do TMT on it? I thought you needed MS3?

 

Wow. Okay, so am I ever confused. Since 2012 or so there has been a constant irrefutable message from one of the world's largest science companies. And that message has been something like "the only way to do good multiplexed quantification is by using an exclusive, incredibly slow, and over all low sensitivity method which can only be performed on our most expensive and complex instrumentation." You've seen that, right? This method relies on doing MS2 fragmentation in an ion trap and then (in later iterations on the Fusion instruments) selecting multiple large fragment ions for MS3 based quan in the Orbitrap at high collision energies. So...yeah...slow....

There were some surprising outliers, however. CPTAC - the largest proteomics initiative ever attempted up to that/those times purchased Fusion 2 "Luminati" devices for all participating labs. After a thorough analysis they chose not to use the MS3 based method for heavily fractionated multiplexed samples. Weird. Those data are amazing. Reanalyzing those data with new algorithms has been the backbone of at least 3 companies, and probably a whole lot more. In my mind they're the high water mark of the quality of data you can get with LCMS proteomics and I hope to someday do something as good. (But at a tiny fraction of the cost! The goal in CPTAC was irrefutable quality and that's expensive). 

There were a lot of confused conversations when said gigantic company started showing MS2 based quan for these experiments on their extremely expensive new quadrupole Orbitrap TOF device (Asstral). Some betrayal? Maybe. I know at least one lab where this turnabout made them start to investigate alternative vendors for the first time in the lab's storied history. There are a lot of fast TOFs out there now and some cost like 3x more than the others. 

So...there are places where this new preprint might not go over super well. 

It's a short and easy read and does pack some surprises in it. For one, though, the MS2 based reporter ions look really really good. For real, there isn't much to pick apart in these data aside from the following fine method details. 

We see two different methods employed here. The first is with a 1.2 m/z isolation window. Which probably sounds like an absolutely huge window for an MS2 based multiplexed quan experiment - because it is. That's letting in your peptide of interest and a whole lot of it's friends. It's approaching the size of some DIA windows today. 

To run the TMT HR method you can go down to a much more typical 0.5 m/z window and then use a 50 millisecond accumulation time to get the signal you want. 50 milliseconds? Ouch. Wait. 

I don't know how fast a 120,000 resolution MS1 scan is on this instrument. I'll assume 2x faster than an HF-X so let's put that at 60-ish milliseconds. If you have zero overhead across the board for everything else (which you don't, but we'll pretend) that is almost 19 scans/second on low samples. Right? 1,000 ms - 64ms divided by 50ms? If it perfectly parallelizes MS1 and MS2, which it might, it's impressively smart hardware, maybe the Orbitrap scan doesn't count against you. Even if that's as slow as you can go but most of the time you're not using the whole 50ms fill time that's not the amazing 200 Hz or whatever this thing can get by cutting the ion beam into tiny little windows. So there might be some serious sacrifices here. 19 Hz puts you in "wait. why not use the Orbitrap?" scan speeds. 

Again - these data look great, but don't get it mixed up. You can do MS2 based quan on the Astral, but given the apparent sacrifices you might be better off running it like an Exploris with MS1 and MS2 in the Orbitrap. If you are looking at this thing and you see you can do TMT 32-plex quan and you can do 200 Hz or 300 Hz (whatever it is now) based MS2 with the TOF in parallel, it's important to remember these statements and experiments don't appear to be happening at the same time. 

At the end of the day it's super cool to know that when you get an instrument and your research shifts that you can do a pile of different experiments, and this at least shows you really can do TMT based quan on this box, and those of us doing MS2 based quan should get a little less flack from reviewers in the future for it. (Lolz)

Tandem mass tag (TMT) label on a chip for high throughput labeling!!

Ummm....if this is real it could be enormous for a field or two!

Yesterday I was reading another paper in this issue of Analytical Chemistry that I was excited (and very skeptical about) and I got to the end before I realized there were no files to support some very lofty claims. I was already really mad about some dumb shit my country was up to and I guess the reviewers and editors were just like - meh - whatever, this is going to be super controversial, so we'll just let you push it through without showing any work. That paper will not feature here.

This one will because I've totally got all their RAW files now! (There's only 14! But there is proof they did something!) 

What was it? They built microchannels so they could TMT label single cell digests in a high throughput manner! Does it look like a pain in the butt? Totally. OMG. It totally looks like no fun at all. But have you seen how crazy DropSeq is (how they label cells for single cell RNASeq)? It's crazy. You eventually get flow rate A and flow rate B under a microscope to line up and the bubbles join and then you can do like 10 million of them while you're at lunch or whatever. 

This is a step in the right direction. Now....because I'm a jerk and I do have these files, they do look a little weird. 

This should be 1 cell, 1 cell, 1 cell, 1 cell, 1 cell, 1 cell, 1 cell, 1 cell, blank, 1 cell, 50 cells of each cell type (100 cells). 

I've scanned through few thousand MS/MS spectra and while they look pretty consistent the ratios appear to be off. Good example. 

It's very rare that I land on a spectrum that I expect... one cell is 2e4 and 100 cells is 2e6, by rare, I'm seriously talking about less than 1%. I'll probably queue them up for reprocessing in a second, of course, so I'll have real numbers. There is some level of error intrinsic in just scanning with your finger on the forward arrow key. 

I'm sure the reviewers for such a nice journal looked at this already and were satisfied with it, so I bet I'm missing something. Right now I'm missing the last bit of sunshine to take my trash out to the curb, so I'm can't spend more time on it. Pittsburgh stairs can be steep and dangerous in the dark. Mine are no exception. 

Again, if this is real, it could be really really cool and that's how we should think about every paper we read, right? I'm just personally invested in processes to speed up my single cell labeling and I don't want to get financially invested in something without being super duper skeptical. Please interpret my words and effort implied in this post in that light, because I wouldn't post anything about this paper if I didn't like it. 

Proteomic analysis of postbiotic inhibition of Salmonella typhimurium!

 

Borrowed this picture from the MicroChem website while I was looking up what a Kirby-Bauer Inhibition assay was. Its a microbial zone of inhibition assay! 

Paper link!

What's a postbiotic? It's a metabolic secondary product of "good" bacteria or other microorganisms. So the question was something like "what would inhibit Salmonella typhimurium" and when we see that inhibition, what is causing that?

And since Salmonella is not a fun thing for humans to get, the goal is to find compounds that will inhibit it to limit infections. 

Interestingly the proteomics from these researchers was performed by sending the samples to the University of Copenhagen Chemistry department where they digested them and did peptide mass fingerprinting by MALDI-TOF. I suspect microbiologists are so used to doing everything with lasers that this is due to the contacts they generally have. The authors come up with a solid table of both small molecules identified by GCMS and proteins identified by these methods that may be next line inhibition chemicals for this nasty bacterium.

As an aside I sincerely hope that these authors are safe and continue to remain so in the wake of the blatantly illegal actions of an 800 year old narcoleptic dictator that began a few hours ago. 

Top-down proteomics of....skinned...human....wait. what?

 

Ummm....

Wish I'd seen this before US HUPO, because I clearly had an opportunity to ask some questions this week of the PI! 

(This wasn't me getting mugged for the 3rd time in my life, I'm just never sure what to do with my hands.)

Silliness aside this is a really cool top down proteomics study of proteins extracted from single muscle cells (which can be a lot of material...sometimes these are 10x or 100x the size of the typical human cell) but top-down of a single cell of any size is still super cool.

And there is bigtime variability across single skinned cells across a single donor. This illustrates what a daunting task single...anything... still is. 

Analysis was surprisingly done with a standard Q-TOF (Bruker Impact II) where I definitely expected the use of an FTICR. Protein separation was on a C4 column. Even more suprising, data analysis appears to have been done in Compass Data Analysis rather than the excellent MASH Suite toolkit that you can get from the lab website of these authors. I have never tried this sort of analysis in MASH but it probably doesn't have something in it (yet?) to do this, because MASH is a far better software than Data Analysis. 

Do you still need to do a BCA assay for LCMS proteomics?

 

I haven't had the chance to put time into this, but I want to. The abstract suggests that maybe doing all the BCA quan steps might not be necessary for some experiments. 

US HUPO 2026 Recap?

Okay, so I was going to type something like "I don't know where to start" but that's a lie. I should probably start by apologizing for being such a jerk about the city that hosted US HUPO. I'm pretty pissed off about the state of my country basically all the time. I'm particularly frustrated about watching the news and grinding my teeth last week enough that I had to go to the conference with a broken tooth. And some geographic areas are more at fault for the rapid decline of my country than others. Whining about it doesn't change things, and that's why I am running for a government office in my abundant spare time. But that's not what this is about.

St. Louis was a fantastic venue for US HUPO and I'm leaving here very happy that John Yates invited me to join the advisory board so I couldn't just sit at home being a jerk about the conference location. 

The conference was a little smaller than some previous ones with something around 550 people. Because it is a Conference Solutions organized event - it was very very organized. I'm not throwing shade deliberately at International HUPO, but one of those things is not like the other.

You could literally stumble outside (I'd assume, I didn't stumble much cause had a lot of responsibilities so I was BOOOORRRIIING during this conference), and there you go - the St. Louis Arch. Apparently you can go into it! 

It was a super relaxed conference. ASMS divided by 100. US HUPO Chicago/2 for intensity. 550 people with plenty of room to walk would do that.

Obviously the science on display was nucking futs. 

BIASED Highlights? 

1)There must be 10 different plasma nanoparticle enrichment technologies on display! There is some paradigm shifting shit going on right now. For real, I have to change some slides. Biomarker discovery goes like this 

- Build a statistically valid cohort and get SOLID TISSUE from them. Do amazing proteomics on healthy and not healthy

-Build a validation cohort in SOLID TISSUES

-Get some plasma and find out that you can't see any of those fucking proteins in plasma.

Major conversation I had with some of the best proteomics scientists in the world (that I'm not at all sure why they talk to me) Matt Foster (Duke), Ryan Kelly (BYU), Brett Phinney (UCDavis) have been like this. 

Wait. Can we just do blood? Skip the organs? Speed EVERYTHING up? It might be real. 

2) Blood/serum/plasma proteomes might be stable for decades! 

Okay - so you know how a lot of us have access to these weird repositories of tens or hundreds of thousands of blood/serum/plasma samples? Come on, you have probably stepped back and thought "I bet most of that old stuff is worthless, right? 

The first US HUPO 2026 talk I saw (I spoke at 7:15am, or I probably wouldn't have seen it...) was Jan Muntel showing how they did thousands of proteomes of plasma from a Johns Hopkins / NIA study. Some of those samples were 30 years old! Baltimore is an amazing city, but it doesn't have the most stable power grid, particularly the area around the Hopkins campus. So...if you could get consistent non batchy effecty data from that, then all of these repositories are about a million times more valuable than I ever thought they were. 

This text is making me bored, so here's a photo of some really tall guy and me in a jacket I got for $10 years ago that only fits thanks to an extra 15 pounds (yay!) and Jan! Watch out for a paper from him. I hate asking questions on microphones but totally needed to know if the PTMs had any value. He should know soon! 

Highlight number 3) 

Might be a lowlight. I might be getting old, yo.

Point 1) A researcher I first met when she was a new grad student with Michelle Cilia is now a PI with her own lab and is apparently being a super cool influence on my favorite US HUPO committee (Ed&Out Reach, previously VMO). Keep an eye on Dr. Angela Kruse and her lab. 

Ed&Out is now very focused on making proteomics more approachable! Check out this video!

Point 2) I'm pretty sure I just had my mid-life crisis thing and went back to academia, right? Right? So it's impossible that a High School Student who worked in my academic lab gave a lightning talk and had a ridiculously cool poster. I can claim absolutely zero (not being humble, real life zero) credit for the success of Fatima Sarfraz. She did a summer rotation with an incredible PhD candidate (Dr. Abigail Wheeler) and I had no part in anything but trying to stay out of the way and being positive and encouraging of whatever they were doing. Fatima presented better data at some of our weekly meetings that summer than some of the grad students and postdocs. When I found out she was going to Princeton the very least I could do was alert the impossibly charismatic, and apparently immortal, Ileana Cristae that she was coming. Apparently, that worked out, and clearly biased, but it might have been one of my favorite lighting talks. 

Highlight number 4)

Who am I kidding? I've easily been to 200 conferences by now. 

The US HUPO lightning talks are THE BEST, COOLEST, FUNNIEST thing I've ever seen at any of them. I had two invited talks and the only thing that I get stressed out about is 

SITTING ON STAGE IN A SPARKLY SUIT READING OUT NAMES.

These people have 60 seconds to pitch their research and I could stutter and mess it up. We butcher names. It worries me.

We had rapping, we had juggling, we had the best karaoke I've ever heard, and it was about all the different ways you could do PASEF DIA method. Yes, that won an award. 

The winner of lightning was the same BYU undergrad who won it the last 2 years. 

If you're in marketing in a proteomics company and you don't have a 7 figure multi-year contract ready to offer that young man before he graduates, you're a dumbass. He could sell me SomaScan. He'd have to possibly send the first spreadsheet of data showing that SomaScan works, and then do a Queen tribute to it, but - for real - heads up. 

Highlight number 5)

It only costs $54 to make a life sized cutout of a person who couldn't attend a conference because it's on his/her kid's birthday. I told Mike Washburn when we passed on an escalator - I'm about to set up my favorite joke of the conference.

I put a 6 foot tall, so almost real life sized, cutout of Dr. Benjamin Neely around the conference. Sometimes I'd stop by to make sure no one vandalized him. OMG. Best $50 ever. I did not set this the following photo up. I found him trying to get people to take free conference swag. 

I'd occasionally get random photos and I'm pretty sure he did too. 

Edit - found a few more! 

Somehow related. For real, you had to be here to see how much amazing chaos this was during lightning.

The ultra talented US HUPO President Dr. Ben Garcia, doing a proteomics centric parody of a song from the Barbie movie that is about male fragility was THE FUNNIEST THING EVER.  Except for the first lightning I ever saw with Ileana Cristae. OMG. So funny.

Okay, I have a plane. Later!

Wait. I totally forgot. And my plane is delayed! 

Proteomics people like podcasts! 

At US HUPO honorary Ben, Dr. Renã Robinson and I recorded the 100th episode of THE Proteomics Show! It's out now and it was super fun to interview Dr. Natalie Clark on fine details of the CPTAC initiative and learn about how modern video games work and discuss an animated whale who is super popular with toddlers. 

Yay! 100 podcasts, and some number one the screen the final day said a preposterous number of listens to said podcast. Like e4s of listens. So there you go. We should probably record some more. I just wrote Neely to ask when Season 11 recording starts. I had so much fun at US HUPO I might ask them if they want to partner on another one. We finally found inspiration for one. 

As I'm fixing blatant airport typos this one is cool. 

You can't be an important member of the leadership of US HUPO forever. John Yates gave Ben Garcia a funny president hat as he moves onto some role at some ASMS thing, and some other people passed the torch as well. We're all grateful for the effort they've put into steering the organization to what it is now. 

Single cell proteomics of metabolic liver zonation!

 

While I was at the amazing US HUPO conference in ...Meh...Souri...which was honestly not as bad as I thought it was going to be, Natalie Porat-Shliom spoke on this amazing new paper at MY University! 

Stunning amazing, ridiculously great work that blew up our lab Slack channel thing! 

Top down proteomics takes on liver fibrosis!

 

Wow, there are a lot of liver diseases and we've got decent diagnostics for....well...liver damage.... that's about it. A small panel of liver damage markers finalized around the time Stan Lee and Jack Kirby went on a creative bender and wrote everything from the Fantastic Four, through Spiderman and the X-Man comics. I'm not kidding, there really has been almost zero forward movement in liver diagnostics since the 1960s. The liver protein panel was old when I was running them in the clinic in 2003. And it's still the same thing. 

Could top down proteomics be the answer? 

Given the current limits of top-down it sounds unlikely, but you'll find what appears to be some pretty clear differentials in these small intact proteins (they seem to get up to 38kDa) in this study.

Is it the simplest way forward to getting some modern liver diagnostics out there? Maybe? But for a field that seems to have completely hit a wall 60 f'ing years ago, it's time to try everything! 

Arralyze CellShepherd- Live cell imaging tandem single cell proteomics!! Webinar 2/25!

Timing on this one is a little unfortunate, because everyone has schedules, however, we're getting this science fiction sounding new toy and I'm happy to invite you to this webinar next week! 

Okay, so what if you could do live cell imaging and - not messing around  - dose your cells with a drug and then use machine learning tools to go and pick up the cells that meet your criteria. For example, what if I was growing a population of cells - on the instrument(!!) - in the presence of a KRAS inhibitor and then when that annoying subpopulation of cells I can't seem to catch enough of with random sampling started to demonstrate the EGFR linked adaptation phenotype that no one can seem to figure out--- then the robot pick up that cell and then prep it for proteomics then moved to the other one?  

Science Fiction sounding, right?

I won't have data to show from this at US HUPO, Monday I'm showing the dingle cell workflows that you can get in the amazing Health Sciences Mass Spectrometry core and Wednesday I'll show Cameron and Shelby's work with single cells taken right out of human surgery. I'm biased, but that shit is Musa acuminata.

I'll post a link to the webinar on this the day of the seminar. We had a weird thing where some bored weirdo showed up at one of my writing group meetings and just yelled random bad words. 

You can learn more about Arralyze here. There isn't a lot of proteomics data there yet. Mostly them just showing off how they can observed and mess around with one cell at a time. 

RIPUP histones to rapidly find a new pile of post-translational modifications!

 

This new preprint is so legit. Not only does it identify a pile of histone post-translational modifications I didn't know about, but it does it fast AND it justifies the chemistry that makes it happen. 

What if the reason that some of these PTMs aren't visible is that the modification neutralizes that peptide's ability to pick up a charge? Makes sense. A lot of the more awful PTMs do. 

But what if you could make them visible by adding a boring ol' tandem mass tag? Bonus points for the introduction of an enzyme I didn't know about with an amazing name:

Stop, don't read this. Next line until someone is around and then read it really loud! 

"HEY! Someone order me some ULTRA ARRRRRRGGGG-C!!!!!"

Thermo has embraced Windows 11 on a bunch of software!

If you are like me and you have a PC in your office that your IT security people don't know about (shhh!)  that you just copy your RAW files to in case you need to look at an actual spectrum, do I have great news for you! 

As of a few months ago Thermo started embracing Windows 11! Check out this list! 

A protein organ specificity atlas based on PROTEIN DATA!

 

Leaving this here so I don't lose it for another week because I am incapable of committing any of these author names to memory.

You'd think it would be easy to find something written in the last couple of years that was about tissue-specific proteomics, right? 

You would be very very very wrong. I have 9 tabs open on just the PC I'm standing in front of in my house (wait. why am I here? I have a meeting in Oakland in like 30 minutes...? TYPE FAST!)

In 8 of these papers, the authors who wrote it used the GTEX RNA DATA to determine organ specificity. As you might remember from some of my earlier rantings, GTEX prediction of proteins in organs is better than flipping a coin. Just not by a lot. 

This extremely polite group integrated the GTEX data, but went ahead and did organ specific proteomics (in-gel digestion 6 cut QE HF / QE HF-X) on their own. (Sorry, really truly moving fast, I can't reference the methods.) Then they were extremely polite and constructive and integrate the GTEX findings into their analysis. They go with something like "if 2 out of 3 atlases show a protein is organ specific" then they consider it specific and move on. I don't know the origin of the second (probably RNA atlas) but that's one reason I was super annoyed I misplaced this paper! Now I won't! 

NanoPots + TMTPro 32 >600 tiny single cell proteomes/day!

 

In an interesting recent trend, everyone seems to be emphasizing how small of a cell that they can do single cell proteomics on. 

Do we have a new winner? No, Akos did single E.coli. Even if it was only like 25 proteins, that's clearly the winner for craziest tiny cell idea.

But this group did PBMCs! 

How much protein is in a PBMC? 

14 picograms! (These author's math, not mine). FOURTEEN? 

My group has recently struggled with some human immune cells... and from the TICs I was guessing we were starting with less than 50 picogram. FOURTEEN? Geez.

How'd they get there? 

NanoPots. Ouch. Okay, so something you have to build yourself, but something with incredibly ridiculously low sample loss. 

Then TMT 32plex. 

If they were able to recover all 14 pg, and lets just say that they used 30 channels for actual single cells. To the mass spec, that looks like an MS1 signal of 14 x 30 = 420 picograms. Ouch. That's still not much at all....

The instrument used was a FAIMS (2 voltage) Orbitrap Fusion III (Eclipse). Real time search (ion trap matching) was used to determine was ions to analyze in the Orbitrap for MS/MS. Dual columns and emitters were also used here, and they did have to fabricate a bracket to make that work. 

For samples this low in concentration there was some painstaking optimization, in particular of the "carrier" or (here) "bridge" channel. Sometimes called "boost" or "orgeano" because mass spectrometrists are still a bunch of cantankerous assholes who like to make up new terminology so that we seem as annoying and unapproachable as possible. I'm pretty sure it's just because we all hate research money and being taken seriously and we'd get a lot more of both if we'd quit making up stupid new terminology. 

The bridge channel was kept very very low. The highest tested appears to be 1ng. So...1.4ng on column....

You have to dig for the HPLC stuff in the supplemental but it's about an hour. I'm a little confused about how this version of the dual column parallelization works. It is detailed, but I didn't take time to draw it out, but it looks like each sample is about 60-75 minutes. 60 minutes for 30 cells gives you 720 per day and 75 minutes for 30 cells gives you about 575. The authors report 660 cells/day, so it's somewhere in the right range! They squeeze extra signal out with a ridiculously tiny column. 50um internal diameter and 25cm length. I think this is =>100 nL/min to keep the HPLC from leaving craters where labs used to be. Real time search with spectral libraries made from these samples do some heavy lifting here. And once the authors get it all optimized out they run the system for about 3 days to report data on over 2,000 single cells. 

Really truly impressive work and another great resource that demonstrates we could do high numbers of single cells if we really put the effort in! 

Poor RNA to protein correlations are an artifact of poor proteomics data?

 

I was making slides for a class lecture and went down a long and windy rabbit hole on what we now know about the discrepancies between RNA and protein regulation. I landed on this one from 2022, and while it may seem like I'm rage baiting....I think it should go here anyway..

Despite the title of this blog post we aren't firmly blamed for all the errors. Some error does exist in the mRNA measurements, but it's pretty clear that the disagreement in protein measurements between different studies is something that is worth thinking about. 

Acceleromater correlations to the UK Biobank proteome data!

 

Wooo! Okay, if your reading this in a first world country this won't apply all that much to you. In my country you can now spend $20k USD per year on private health insurance for yourself and if you actually need it someone will be very financially motivated to deny you coverage for pre-exisiting conditions.

What if you could wear an accelerometer (I'm sure my wristwatch has one) and it could predict you might have a pile of different diseases? 

BOOM - pre-existing condition. 100% profit for the most profitable scam in my whole country! 

Science fiction? Or science fact? 

A bunch of people in the UK Biobank agreed to wear an accelerometer for a couple weeks as part of their contribution! And this group remined those data against the O-link proteomics data and the clinical data they could access from these patients.

You accelerate poorly? Dramatic increase in a ton of different diseases! 

Moral of the story? 

Do you need DIA-NN QC? Do you also need retro visualization choices?

 

Okay, we all need more ways to look at the quality of our data, particularly before we send it out to collaborators who may do who-knows-what with it! 

Only one QC tool out there gives you retro visualization options! And it's this one!

https://dia-nn-qc.streamlit.app/

Load a DIA-NN file and choose 80s terminal or 90s webpage or just the boring regular thing. Who says you can't have a creative background while you're making sure you've got the correct number of scans/peak? Not me! 

MuPPE - Serial enrichment of the phospho- and glycoproteome!

 

What a great month for method names already! Introducing the... 

...sequential single pot digestion and then sequential enrichment of the phospho- and glyco- proteome! 

I'm not entirely sure what all the advantages are of the Muppet method. The authors make it seem very streamlined, and I'm guessing that you can get away with less sample and sample loss by keeping things in the tubes, but early in they have to spend a lot of time diluting urea down to functional levels. If you want a lot of the details on how this is performed you'll need to go to page 28 in the Supplemental Info PDF. There you will find that an Orbitrap 480 was used for all analysis with DIA for the peptides and phosphopeptides and DDA for the glycopeptides. So it is still 3 different injections per sample. I am always happy to see something like this, in any paper even if it's on Supplemental page 32. 

I also find this a little concerning

...in Jonathan Pevsner's book (which you can get on Ebay for $12 in first or second edition), he warns that smiling volcano plots can be either a lack of data points, excessive presence/absense, or over-normalization. Since I think they've got a solid pile of data here, it does make me concerned that the data has bene over-normalized. Though...they used Bionic and specify a rather small n-glycopeptide library was used, so it could be the other two. Smiling plots just make me nervous. When I have one I generally find out I did something silly upstream. 

Otherwise this seems like an interesting method, particularly if you're not always doing phosphoproteomics or glycoproteomics and you have to do them. I don't see any reason why you couldn't digest the peptides with a more traditional approach and then put those peptides into this workflow around step 2 or so. 

Target PTMs in single cells with ShtMtPro!

 

YES! Okay, so this is may finally be the smart solution to something we tried (and probably just about everyone else) with the SCoPE-MS/ScoPE2 workflows.

If you have a "carrier" "boost" "basil" or "oregonO" channel, why couldn't you load that thing with phospho-enriched samples (for example) instead of 200 cells or a a diluted perfectly digested pooled sample? The reason appears to be that your coisolated peptide (or junk) background ends up leading to a preposterous number of false discoveries. Remember that in these workflows your complete and total evidence for that peptide being there in single cells is just your single reporter ion. Since most PTM modified peptides are already in a suppressed region of signal to noise - and you only get one measurement of that phosphopeptide - you're already in trouble. (Wait. Is that too many dashes? Don't need y'all thinking some AI wrote this thing. Meh, I'll fix that in a minute). Throw in the contamination of your reporter ion signal with the isotopic impurities and now you've got tons of phosphopeptides and they may not really make sense at all. 

Ready to fix that? I sure am! Except...I don't have this hardware.... hmmm.... okay, but let's do it anyway! Introducing 2026's early entry for best method name......

ShtMtPro!

It's SureQuant with 

Super Heavy Tandem! (Sht) Mass Tags! (Mt) Professional (Pro) version! OMG. 

(Mandatory)

Okay, so the AMAZING name should not, in any way, distract you from how good these data are. Compare the number of PTMs you can pick up using this workflow vs DDA? ShtMtPro crushes it. Even vs PRM, ShtMtPro squeezes out a narrow victory! 

Intelligent - on the fly - targeting of chemically modified peptides IN SINGLE CELLS? Multiplexing so it's super fast?? Incredible idea that I bet no no one tried at all to talk another vendor into for 3 straight years. If you are thinking something dumb like "I can't do single cell proteomics, I just have this old Tribrid..." this is the second paper on this blog this week that should put you on the right track. If, however, someone offered you $75 and a pack of big red for that old Tribrid, I would happily give you twice that for it!

Edit: Okay, apparently they used an Exploris, which I was not aware could do the SureQuant thing. I thought it was a Tribrid exclusive workflow. Good news! There are a bunch of Explorises around!