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.
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.
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!
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.
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?
Highlights? 75 Hz in a Tribrid? That's rocket fast. Probably rocking the Excedion Pro's lower resolution Orbitrap scan rates? Unclear, but that would be the safe assumption.
It looks like there will be 4 versions of ApeX aimed at different markets?
There is a long held tradition for this vendor to take a big 'ol dump on the systems that you currently have.....wow, they rolled out a lot of details on these systems.... but there it is....
...a giant jump forward from the venerable Assend....
If this is the one that is boring enough to release several days before the conference, it should be an eventful week!
Wait. There is another one hidden in here as well - The Excedion not Pro. Amateur? Excedion Rec League!
....my brain is off. Obviously it's the
I find it more helpful these days to simply point out the failure rate of transcript level measurements (because just about every wet bench scientist out there has ran into it), it is relatively cheap and easy to get those transcript measurements. (However, I've still never been offered a $100 genome. Have you? I hear it's a thing, but it still seems like $100s plural).
What if it still had some value (besides finding point mutations in variant call files, of course!)?
These authors suggest straight out heresy and suggest implying that you could integrate these data to group those peptide IDs into actual protein data better. Proteoform data thanks to RNA?
Just leaving this here so I can get back to it later in case we have some drug response data with a lot of variables!
While I don't love every aspect of this paper (some insight on what LC gradients were used when seems to be entirely absent from the main manuscript, which makes me question the title which seems to describe a single workflow) there is some gold in here!
In my lab we don't reduce and alkylate the single cell derived proteins. I do this because I'm lazy. And also because I spend a lot of time studying drugs that modify cysteines.
A really nice evaluation of different reduction and alkylation conditions in this study finds optimal conditions and reagents for reducing and alkylating. However, the %CV decreases when doing so under most conditions, probably due to the extra manipulation steps. This section is really well done.
This group also looks at how to digest single cell derived proteins at 37C without those teeny tiny droplets of trypsin evaluating and comes up with a method that works well. They also describe an easy way to get to 100% humidity.
Since they're using a nanoelute they can go between 96 and 384 well plates. Simply moving from the 96 - 384 well plates is enough to give them 300 protein groups!
Multiple cell lines were used here. A549 cancer cells, primary astrocytes grown on poly-lysine, etc., it and the system in use is a TIMSTOF SCP and data was processed in DIA-NN 1.8.2 (?) Even if you ran your first single cells (eek. 8...or 9...? years? ago?) There is probably something to learn or re-learn here. I'm certaily adding it to my lab's Slack channel for literature now!
If you've been on this blog much recently, I am sorry.
Also, you have probably seen me in some level of outrage about some recent studies where people have gotten anywhere from 1-4 measurements of the peptides they are looking at. Is it better than Illumina ProteinCrap? Absolutely. But is it good for mass spectrometry data? No.
Why is it bad? Because some blogging academic says so?
This new preprint looks at the problem in depth and finds that for high abundance proteins in blood, the 1-4 measurements per peak is actually not all that bad. Unfortunately....the cancer biomarker you are looking for is probably not albumin, transferring, or immunoglobulins. For low abundance proteins, getting fewer scans per peak means you miss any changes between healthy and cancer patient blood. So....honestly... what's the fucking point of doing the study anyway?
They say it nicer than this here!
