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!