Informed DIA allows transcription factor quan in single cells? Also, new Astral?

 

If you've seen me talk about single cell proteomics, I like to point out the proteins I can see (50,000 copies and up) and I make a joke suggesting you come back in a decade if you're interested in transcription factors.

They turn on transcription at your DNA...you only have a couple copies of each gene. In many, most cases, we only expect a few copies of each of those proteins in each cell - certainly not tens of thousands! 

Yes this preprint demonstrates measuring them in global single cell data! 

How? Well...it's complicated. But basically it looks like we've got MS1 - DIA - and then what appears to be heavy isotope triggered wide window PRMs all in one cycle. I *think* the instrument sees the heavy spiked peptides and then moved a PRM window over to where the light should be. 

For you hardware nerds you may be interested in the fact this preprint seems to feature an Orbitrap Eclipse, and Orbitrap Asstral and something called an Orbitrap Astral Zoom, which might suggest we'll see an Asstral 2 at ASMS tomorrow? I guess we'll see! 

The first author will be presenting it as poster WP724 (Wednesday? Poster 724? I think!) if you're in Baltimore! 

pre-ASMS media drops - two new TIMSTOFs confirmed!

 

Hardware is already leaking to the media? Here is the first one - and a surprisingly well-written article with insight from a bunch of early adopters and/or beta testers. 

Oh crap, and my news feed was like "oh, so you like mass spectrometers? First I've ever heard you mention that... here's another! 

Looks like it's a top-down focused instrument with MSn(?) capabilities and some electron transfer thingamabobs, but I'm excited to see what it can do in the area of PTMs in bottom up as well. There area lot of PTMs that are just no fun at all to do with MS2 alone. 

I wonder if they had to get Disney's permission to use the same name or if it's so far from the meaning that there couldn't be confusion and trademarks wouldn't apply? 

 

pre-ASMS drops coming in! Seer system can prep 1,000 plasma proteomics samples/week!

 

Read more here! 

It sure makes the Illumina protein prep 384 samples/week seem even sillier.....

Increase your multiplexing by adding the time dimension (and more nanoLC columns!)

 

My first thought when I saw this new preprint was something like "I've been working on these IRB documents for my clinical trial for waaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaay too many hours, cause I can't figure this out at all." 

I honestly might still not get it, so the less I type the better, but this is probably the best figure for driving the idea home in the preprint. 

I do think it is an interesting idea, and I'm all about getting extra throughput. Multiple samples running with time delays are demonstrated as being deconvolute-able using retention time re-alignments. 

From a practical standpoint - 

Since 2020 I think roughly 30% of my nanoLC columns have arrived in a completely non-functional state. The ones above just weren't glued at the ends so the capillaries just fall right out at the fittings. 

There is a vendor that produces nanoLC columns that have been famously reliable and successful over those few years, but - in my hands- the columns are amazing for about 2 weeks before they overpressure.

The thought of relying on 3 separate nanoLC columns performing properly chronologically seems just about as likely as me winning the big Powerball jackpot thing by buying 3 tickets. I've never gambled in my life, but I'm assured the odds aren't great of that happening. 

Spatial proteomics across laters of skins investigates psoriasis!

 

Okay - so who else was limited in their thoughs of how you could apply spatial proteomics in thinking of slicing being in 2 dimensions? 

This application find altered cholesterol metabolism in psoriasis patients compared to healthy matched controls at different layers of skin with the biggest differences being observed as you go down (?) 

LCM used a Leica 7 and LCMS was EasyNLC 1200 on a TIMSTOF. DIA and DDA(PASEF) were used and at least some of the data was analyzed in FragPipe. 

Really interesting stuff across the board. 

Last minute deadline for HLXMS Travel Awards to ASMS 2025!

 

Applications are still open - UNTIL TOMORROW! 

Chronic alcohol consumption alters acetylation in mice!

 

This is an extremely thorough analysis of the alterations that occur in the metabolome and proteome following chronic ethanol consumption.

On top of the proteomics - which involves both protein turnover analysis and acetylation enrichment multiple assays focus on absolute quantification of different panels of metabolite. Super solid work.  

DIA-BERT - GPU enabled DIA analysis!

 

I can't test this yet, because....ummm.....this is a pretty impressive suggestion for what GPUs you should use.... I honestly didn't know that there were 40GB GPUs! 

But wouldn't it be amazing to do DIA data analysis on GPU?!? Try running DIA-NN by giving it 12 cores, then giving it 24 cores. These tools obviously scale well, right? My old 1080TI in my desktop at home is like 10 years old and has 3,500 cores!

Let's run DIA on GPU!! And this one has a graphic user interface! 

MAP-MS! Get more Orbitrap dynamic range for free!

 

I had to sleep on this one and then find out that the coolest new toy I received for my lab needs to charge before I can try it out --

(not this paper - the fact I have to charge a device that I think will dramatically improve life in my lab and that while charging it I realized it has instructions I'm supposed to read) And now I think I get it. 

Remember BoxCar? I vaguely do, but it worked in sort of a similar way. Both try to take advantage of the fact that ion injection times on MS1 scans are really fast but Orbitraps are 

BoxCar works by chopping up your MS1 into lots of little DIA windows and then alternating between MS1 scans. 

Could you do something very similar but with great big boxes that wouldn't slow anything down at all? And if they were static could it be done with absolutely no obvious consequences? 

That's what MAP-MS appears to be! They study the distribution of trypitic peptides in humans to make their big window cuts and then multiplex their MS1 acquisitions to boost the lower abundance ions, reduce the highest abunance and everything seems to just work. 

On DIA experiments they get 11% more coverage without changing anything else. A lot of people will trade in a proteomics instrument for 11% more IDs, so that's pretty appealing. I do have concerns that maybe not every piece of sofware will love the data, but we won't know until we try it! 

DESI profiling of 165 proteoforms across over 10,000 single rat brain cells!

 

Wow. Okay, so I was a little (lot) less excited about the desciption of this technology when sea slug neurons were being profiled when the technology was first described here. Those sea slug neurons can be really convenient to work with since they can grow out on a plate to be easily 100x larger than typical cells. However - these are rat brain cells and these are going to be biologically relevant to more than just sea slug biology! 

They start with rapidly murdering the rats and getting to their brains and dissocation of the cells with papain. The cell suspension is then allowed to sink down and adhere to plates (fuzzy on this procedure, but it has been detailed in previous studies). Then those cells are fixed(?) in glycerol and some in ethanol (?) on the slides and they're ready for DESI analysis. 

DESI is like MALDI where you're moving spatially across a slide but the ionization is very different - from a mass spectrometrist standpoint the most important part is that you're multiply charging things. Here they can get the charges up enough that proteins are picking up enough charges to be detected in an Orbitrap (Exploris) running single ion methods.

It's a brief read, and a really interesting one. There is a really cool supplementary video and if you want to find what proteoforms were actually detected you'll want Supplemental Data 5.4. All the files are up on MASSIVE, but I suspect given the unique nature of the data it might be tough to make sense of them with the tools that I have.

Intact protein analysis of 10,000 freaking rat brain cells?!?