Proteomics of organoids IN OUTER SPACE!!

Y'all know what organoids are, right? 

Some people got together like 20-ish years ago and were like "yo, I wonder if it actually makes sense that all these human cells are growing in 2 dimensions...?" For real, like, they don't grow like that inside a human being, outside of perhaps Lady Cassandra....

So they make cells grow in little balls instead. Still...not...like normal...but if you give people a dose of a drug and measure a response and you work out that same dose for cells growing in 2 dimensions vs growing in the little balls of cells (organoids) the latter is closer to the human.

SO.

What if. 

You (not you, but some NASA affiliated people, unless that IS you. Then you, obviously!)

PUT ORGANOID IN OUTER SPACE???

 (They did single organoid, so I assume it's singular when referencing them?) Sounds funnier, at the very least. 

We send way dumber shit than that to outer space all the time. A ketamine addict who runs a racist social media platform keeps failing to get rockets into space that probably just have pictures he colored of himself inside them. Who knows? Certainly not ol' Space Ketamine Karen.

What was I typing abou...THIS STUDY THAT I SAW PREVIEWED BY ALINE AT US HUPO! 

To make this even more spacy! They ran the organoids on - you guessed it - an Orbitral Trap tandem Time of Flight Mass Spectrometer that we know as the Asstral! 

A massively paralleled ion trap inspired by nature!

 

Okay, so maybe what we actually need is 500 parallel ion traps within our instruments!!! 

This is just an early proof of concept of teeny tiny ion traps operating under the control of individual (or individual clusters?) of GPU (CUDA-type?) cores. I've never seen anything at all like this so it jumped the queue of things I meant to type about this week. 

Higher throughput and coverage than O-Link or Illumina Protein Prep - on a SCIEX?

 

Yikes. Okay, so if there is legitimate instrument competition across the board, I think there should be some seriously competitive pricing in the LCMS space this year. If you're not seeing it, demo something else and let them know about it because - holy cow...

I had a super early version of the 7600. I had it before it could do ZenoPulsing/ ZenoTrapping in DIA. It was a nice instrument and super ridiculoulsy great at targeted proteomics. That PRM thing (mRmHR?) loved Skyline and it processed data super fast. But it wasn't up there with my TIMSTOFs. Not really. You could doulble the gradient length and increase the amount you loaded on column by 2-4x and get the same coverage as the TIMSTOF Flex with the XR catrdidge. 

You sure as hell couldn't get 4,700 protein groups at 500 SPD from 200ng of K562! Make no mistake thsi is far higher throughput than the "next gen" proteomics solutions out there. This is more than 10x more samples/day than Illumina's new protein prep - AND this thing can QUANTIFY proteins. Friendly reminder that Illumina Protein Prep only detects proteins. It does NOT QUANTIFY proteins in any meaningful way. O-Link can provide meaningful quantitative responses, but on a single instrument setup 500 SPD is going to be 2x - 4x the throughput (though I've heard this is improving with 1536 well plate preps or something). 

Something weird on the 7600 was that it had a lot of the optics from the earlier generation QQQs. The 8600 doesn't. It's got the new stuff and on top of the speed they're showing off, this thing can hit solid coverage at single cell equivalents. They even prep single HeLa cells in 1 cell, 3 cell, 10 cell and stuff and it looks good. Also there is some 3 proteome digest stuff that looks pretty solid - obviously better quantitative accuracy at the lower speeds. CVs look decent. If you could nitpick these results you could say that the ion mobility equipped instruments do get cleaner spectra and tighter CVs but - for real - SCIEX seems to have a legitimate competitor for the other company flagships. I was about to make a bunch of highlander jokes following some recent software company acquisitions but it looks like there is still legitimate competition out there in the world! 

Pepyrus - User defined HLA (MHC) peptide libraries!

 

...well...this is frustratingly brilliant....

So why we're all messing around trying to figure out how to do a better job deep learning endogenous peptides, this group decided to just cut out the middle of the plan completely.

This system relies on using E.coli to generate the peptides that you think are there which can be directly informed from your genomics data - to actually make the endogenous peptides that you might be able to see - if they are there. Double dash! 

Then you can have the real spectral libraries for that mutant form that would be really super amazingly cool to see on the surface of that cancer cell. If it is there you see it by mass spec and then you can design a CAR(R)-T thingamabob or immunotherapeutic whatchamacallit to those cells.

For real, just intimidatingly shockingly clever, because it really seems super obvious once you get 3 pages into it. Not that I could have pulled it off (please see thingamabobs above and genetic expressoin in little poop bacteria seems like weird magic these days), but it does seem like someone should have thought of it.

Site specific glycoproteomics of hepatocarcinoma!

 

This is a solid new study with a noteworthy method combination.

The global proteomics was done one a TIMSTOF with diaPASEF and analysis in SpectroNaut. The glycoproteomics was done following some sort of chemical enrichment thing followed by TMT proteomics. It's a big 'ol pile of files.

I was looking for how they would normalize the glycopeptides against the whole protein concentrations and they actually include that part in the method section! Our puppy just scratched our kid, sounds minor, but I've got to stop typing here even though I haven't got to how they used some combination of ETD and HCD to do the glycan and TMT based quan. Worth checking out though! 

Charge detection mass spectrometry of intact HIV Envelope Proteins - with Glycoform information!?!

...well...I didn't know that you could do this....

And - wow - has ChemRXIV gotten a glow up! It used to be the ugliest duckling of the preprinting world, but now it's totally modern and legible! 

For this study something called a Q Exactive HUMR with charge detection was used to work out these assembled protein complexes. Flipping everything I know about Orbitrap intact protein work on it's head, this group ran the charge detection thingy at 200,000 resolution with direct nanoinfusion for possibly as long as 30 minutes. 

I've done a lot of intact mAB work, somehow almost always out of the goodness of my heart. Actually - advice to younger scientists who might be way too nice and willing to help people - If anyone wants you to get a good intact mass of an mAB - especially if they are a startup - payment up front every single time. And if they said they worked with me, definitely reach out so I can tell you about how I took work from a nice CRO or three and got $0.00 for it and I'll suggest you charge them 100x what you're thinking. 

Wait. What was I typing about? OH YEAH!

Okay, so on mABs on a regular Orbitrap I generally run 15,000 resolution, when KRAS will look great at 70,000. Intact mABs are 10x larger than KRAS and those spare molecules in the Orbitrap wreak havoc on something that large. On an Exactive EMR, the biggest thing I ever did was maybe 250kDa and I had to run it at 7,000 resolution or something to get it to resolve

So whatever this charge thingy flips that upside down! 200,000 resolution! That's crazy! And they step through collision energies to get data on this heavily glycosylated complex! Super cool work.  

Could you profile snake evolution by proteomics of their venom?!?

 

I missed this recent study and it's ridiculously cool! 

I'm going to start by just stealing this line in the conclusions by the authors: 

"...From an ecological-evolutionary perspective, a post-transcriptional mechanism that modulates rapid variation of the venom phenotype can potentially confer adaptive advantages in response to environmental changes...."

...right??? because of course it would. 'Cause if you're a snake and you want to spread across a mountainous region where some of your 94th cousins live close to the ocean and you live at 3,000 meters you and your cousins have different things that you need to need to defend your self from, or prepare for lunch, right? 

And is the fastest way to do that adaptation waiting 140,000 years and 220,0000 generations for your DNA to make those changes? Or could post-transciptional mechanisms lead you to make a toxin that can KILL THE MOUNTAIN THINGS IN YOUR WAY? 

Sounds to me like one of those things is more energetically favorable than the others.

This group does some awesome stuff - first looking at the intact protein profiles of the snake venoms they got from different elevations - and they look different by eye, for sure. They also....have different lethalities on different animals...which.... yo, you wouldn't know until you checked, right? 

Bottom up proteomics is done with SDS-PAGE, in-gel digestion and analysis on a Q Exactive Plus.

All the data is up on MASSIVE accessioned as MSV000096598 if you want to take a look at it. 

I tell you what, I get to do a lot of cool stuff in a medical school with some sky bridges to where the operating rooms and MDs are, but I'll never get tired of looking at someone using the same tools we have to do things like question basic evolutionary paradigms with weird stuff like poisons they squeezed out of a snake. Okay, I do get bored when people have the same tools but do a half-assed job and get away with it because they completely invaluable samples, but that's not what you'll find here. 

NIFty -Never Impute Features (thank you)!

 

This was the first poster I hunted down after Day 2 Lightening Talks at US HUPO 2026, and now I can share it with you guys! It's great because another SCP Biorxiv preprint came out this week and my opinions on that that one definitely have to stay in my drafts folder. This is a place for positive commentary, mostly! 

Proteomics has a very strange relationship sometimes with the concept of zero. I get it, dividing by zero is not allowed in Excel, and that's probably a significant part of the problem, so there are piles of smart-ish ways to not have a zero. Realistically, single cells are still at the limits of our detection limits and zeroes are pervasive. Everyone's heard this a million times, but the first good scSeq dataset I got on a drug I was studying was a little more than 90% zeroes. There were a couple transcripts that were detected in less than 10 cells out of 7,000 cells so...for that transcript, in that study it was more than 99.875% zeroes. 

SCP also has batch effect problems that primarily effect lower abundance proteins. Those high abundance proteins can look pretty great from study to study. 

This is me rambling about what I understand about NIFty, which tries to solve both problems by 1) using zero values as if they mean things and 2) looking for classifying data using the proteins that are less variable between batches.

And then there are a bunch of things like this, which an AI just informed me indicates that you are supposed to read the formula in a snobby British accent. Which....makes me think I've pushed the Chipotle support bot a little too hard today. 

You might just want me to stop typing and post the Github so you can check this awesome thing out yourself! 

https://github.com/PayneLab/nifty

Can't tell what species it is peptide level data? Enter PEPTONIZER 2000!

 

Given the sheer multiplicity of peptide level data, we're probably approaching a point where just trying to do metagenomics classification seems silly compared to the metaproteomics stuff, right? 

The way I think of it - 

Yo, is this species A or species B?  I've got 20 bases of relatively fragile oligonucleotides, so  4 bases ^20 is what I'm working off of to make that species ID. That's a big number. Something in the e12s according to some extremely sleepy Excel thing that took 11 seconds and might not be right at all. 

Or. I've got some collagen which can have a half life of over 70 years....and I've got 20 amino acids from that. so...it's 20^20-ish. Change the 4 to 20 in that same excel spreadsheet and now you've got something that could occure by chance in the e26 times. 

Okay, but I know how to get good sequencing data of peptides....what's the next step?

PEPTONIZER 2000! 

Here come the LLM Search Engines, introducing ChatDIA!

 

Okay, so everyone else should be really embarrassed they didn't put together a preprint and get credit for "ChatDIA". I just submitted a one paragraph "paper" to Biorxiv on my lunch break, so ChatDDA is mine in the next 72 hours or so.

That's not to say that this doesn't have merit. This thing appears to fare well against DIA-NN! 

SAINTexpress portal- Good pull-down proteomic data analysis in your web browser!

 

You know what proteomics needs more of? Accessible data interrogation and interpretation tools, like the new SAINTexpress portal!  For some people they just really need tools online because it takes them 6 months to get permission to install things. Not me, I hang out with the IT Director whenever I can. 

SAINT (Significance Analysis of INTeractome) (whoa. my font went all funny, that's what I get for copy/pasting. Come on, Ben you can absolutely spell Sigifnivcance on the first try. Wait. Maybe not.) is a great way to take your immunoaffinity, affinity enrichment, pull-down, IP-MS, AE-MS (wait, maybe thats what one of the longer things stands for) data and make sense of it. And now you've got a webportal! 

Infinite multiplexing by attaching ...giant peptides....to...your...peptides...?

 

Okay, so I went back and forth on posting this one for a while, but I might honestly be missing something. 

I'm certainly missing the RAW data files, because those weren't deposited... but the initial idea seems clever...until you try to design something that can multiplex more than 3 samples at a time....

The basic idea is something like "why swap isotopes around when you could SWAP AMINO ACIDS AROUND?"

As shown in figure 1 - if you had INFINITELY LARGE PEPTIDE LINKED TAGS! 

...attached to your tryptic peptides.... 

(wait. what?)

 ...you could have INFINITE MULTIPLEXING! 

Y'all don't line up immediately to add a 2,000 Da multiplexing tag to your all of your peptides so you can have the equivalent of a TMT 16 plex experiment. I think you should definitely contact the authors first to ask to see these .raw files because there aren't enough details in the method section ....of a paper accepted in ...Analytical Chemistry ... to reproduce the experiment. You can guess some of the settings, though. TopN? Guess. Ion injection time? Guess again! Can you employ normal dynamic exclusion?  What is the mass of the tags that were searched in MaxQuant? If you want to know, you need to do the math yourself. Really, just a disappointment to see something slide by an editor and reviewers, particularly when something seems - on the surface  - unlikely to work...? 

The OpenLC project! Build an autosampler out of an old OpenTrons?

 

Our library doesn't subscribe to this journal, and I don't have $50 to spend on one paper, so it sure was handy for the authors to put links in the abstract to the -

OpenLC Github! 

There is a repository with .STL files you'll need to print adapters and the code you can use to over-write the original OpenTrons one.

There are a couple of related papers that I can access as well, such as this one that can probably provide a starting point on useful details like this.

What's the point of these super fast LCMS methods if your HPLC only has room for 1 or 3 plates? You can't even go on a weekend trip. But if you have an OT2 autosampler could you have room for 12 plates???

Sure looks like it to me! Totally worth thinking about....

JASMS pulled together an amazing piece on the passing of Amina Woods

 

I didn't know Dr. Amina Woods as well as you'd guess considering the 20+ years we were doing mass spectometry stuff in the same city. We'd spoken a few times, most recently maybe two or three years ago and I was always a fan of her work and presentations of it. 

What a person she must have been to have inspired such a touching piece from the nitpicky chemistry nerds at JASMS. It's a legitimately nice read and maybe being good and interesting enough to inspire such a thing is something we should all aspire to. 

Somebody went all out on diaPASEF peptidomics exploration - analyzing baby formula!

 

I was initially a little appalled by the amount of optimization of diaPASEF windows in this paper, but I read more of it while walking a mean little dog in the rain and there is a lot here. 

Food science is very different that your run-of-the-mill proteomics samples. Often the thing you're worried about is the allergenic peptidome, and those sure don't look like tryptic peptides. It's likely that this team ran some baby formula using the default methods on the instrument and they didn't see a single thing of interest.

They had to go back to the drawing board do wide IMS window DDA and build their windows for their targets iteratively until they had a good method.

Even in this context, I have to admit there are just too many purple DIA windows to make this more than a useful reference for the next time we have to look at something singly charged and 10-50 amino acids long. I certainly don't want to read the whole thing until that happens, but I'm glad to know it's out there! 

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.