Convert protein sequences into text and use language models to reveal all their secrets!

 

Wow. I'm completely blown away by this one. If you've got VERY GOOD AD BLOCKERS INSTALLED, you can find the popsci article here. Don't click it if you don't. Hot dog, the little counter on the corner of my screen rang up 74 ads and trackers in just a second. And the banner at the top warned me of "consequences" of blocking those 74 ads. 

The article is sort of about this new PNAS paper! Click this instead. My school doesn't subscribe to PNAS? Weird. Maybe my ad blockers are too good. 

Okay, but here is the thing. What if you could convert protein sequences to text? For real, hear me out here. You could, in theory, assign each amino acid IN ORDER an alphabetical letter. Then you could take all the complexity of a protein sequences - even one with hundreds of amino acids! - and make it just a short paragraph! 

See where I'm going with this? I bet some of you super saavy scientists do. Good for you! Then you could use that text input into - you guessed it - these amazing LLM things! 

I suspect this group at the NIH did a far better job than me when I just tried it with the LLMs I have access to, but I swear I think I just found an interesting pattern in my proteomics data with a similar approach. I have this output I haven't ever seen before. 

Serine-Histidine-(Leucine, or Isoleucine, but likely the latter)-Threonine-Threonine-Tyrosine-Serine-Histidine-(Leucine, or Isoleucine, but likely the latter)-Threonine-Threonine-Tyrosine-Serine-Histidine-(Leucine, or Isoleucine, but likely the latter)-Threonine-Serine-Histidine-(Leucine, or Isoleucine, but likely the latter)-Threonine

Have I discovered an entirely new and obviously important protein motif? It seems worth investigating for potential phosphorylation sites alone! 

MSCards - An educational game to learn mass spectrometry hardware!

 

This is so clever! And I absolutely want a deck! (In English, probably, but I'd take the French ones for sure!)

If there is an opportunity missed in this EXCELLENT paper...

 (For real, this is such a great read from authors who understand both mass spectrometry and educational concepts. Neurons from my long ago training to be a teacher stood up and tried to do things when I read words like "pedagogy"). 

...I would have ABSOLUTELY, WITHOUT A DOUBT, cited a paper by Kenneth J. Rodgers first. 

It's a preprint, there is still time! Maybe this one? 

Scientist Exchange Program Award! Deadline September 11, 2026!

Are you a trainee of some kind in the US? 

Would you like to go to some US HUPO member lab and LEARN A NEW SKILL?

AND Win a fancy award for your CV? Check this shit out. 

I'm not saying this is what you should do, but here is a scenario. Imagine you wanted to do some single cell proteomics. You could totally come to Pittsburgh and get trained by my amazing team and do some badass single cell proteomics. And US HUPO would help pay for that experience and present you with an award or something.

You could obviously go to some other US HUPO lab and learn something else, but I'm just listing what I'd personally consider the coolest possible option. 

....

 

Optimize your low-load EvoSep loading!

 

Whoa. Okay, so someone else was wondering how to minimize low concentration sample prep to EvoTip loading. Turns out one of the culprits can be the lyophilization/speed vac'ing step! 

Worth checking out, for real.

Have an AI design your lab layout!

This weekend while watching too much stuff indoors because it was 40C (>100F) outside I kept seeing ads for using AI to "design your space".

We have a single lab bay not counting my office and the awesome open space for the TIMSTOF and EvoSep, but we do have to think hard when students rotate about where to put them. 

Maybe if I give an AI all the details of the lab and the dimensions it could......

....make me think this isn't the dumbest fad in all of human.....history.... 

MCP did a whole special issue on Don Hunt!

 

I'm not sure when this special issue actually published this year, but I ran into it while editing a review. And I do love this paper in it. It's all about boring old validation of a high resolution LCMS (!!!!) proteomics assay. 

Only want to identify proteins (but not quantify them) use any column you want!

 

Proteomics is in such an interesting place right now! There is so much new interest that I hear people talking about proteins in my day-to-day than genes. Maybe that's environment, but it's definitely the first time ever.

Now, you've kind of got two groups of people in proteomics. 

You've got the nitpicky nerds who aren't just satisfied by knowing what proteins are present. These jerks want to know how much of each protein is there. For no reason at all I'm going to call them "Medical doctors and good scientists". Purely, and only, because I randomly referred to them first in this list. 

Then you've got the people who don't care at all how much of each protein is around. They just want to identify a protein is there. It could be one molecule or it could be 90% of the total seven kilograms of protein present. I'm going to call them "Not the other thing", again, I need to come up with two lists with these categories and they had to be in some order. 

Now, the second group generally uses aptamers (SomaScan, Illumina Protein Prep). But if you want to use a mass spectrometer improperly, you can absolutely do this without aptamers and this has been very popular recently. I've seen LCMS data where people are measuring 1-2 scans across peaks. Which might honestly be able to generate "quantitative data" as bad as Illumina's proteomics solution if you hit the peak wrong a couple of times and don't have too many peptides per protein.

This is absolutely not what this new MCP paper is about. 

These authors probably generally fall into the first group, but I think they were just asking the hypothetical question for this second group of scientists "IF you only cared about peptide identification numbers and you didn't care about quantifying proteins, does it matter what chromatography you use?" And, surprisingly, the answer really does appear to be no. This Astral is so fast that any "chromatography" that can get you a 3 second wide (FWHM) peak can get you a whole ton of identified proteins. 

The authors also show that if you run serial dilutions against each other you can see that the lower dilutions seem to have lower protein levels. I'm a little surprised by this because I figured DIA-NN would normalize protein levels by default, but that doesn't appear to be the case. Actually, I just looked and cross-run is enabled by default, so wouldn't that scale the 0.1ng up in intensity to as close as it could get to the 50ng? They probably just turned it off. 

Either way - it's pretty impressive you can pack just about whatever you want into an HPLC column and run 3ng fill time narrow window DIA on an Asstral and identify a whole ton of proteins. I'd love to have seen this study with a spike in experiment to know what you could quantify with each one, but I hope I almost always fall into that first group.... 

Safeguarding the bioeconomy - a super great book about how science works and grows

 

This isn't proteomics, but damn, I love this book. 2020 joint publication by 3 National Academies. I stumbled on it while working on a paper that I hope is going out the door shortly and it's a goldmine of insights about how the science works and grows. 

If you dig around even a little I think you can get it free. I went through my library but it led me around to what appears to be a fully free pdf to download. 

DigestedProteinDB - Handy new proteomics tools to ID weird peptides!

 

Have you ever just ran into a funny differential peptide that seems really interested and thought ".....awesome...where do I even start to figure out what that is....?" I sure have! And before you try to figure out if you can export that single spectrum for de novo (eek!) or hand sequencing with a calculator (double eek!) what if you could just have a starting point? 

Check out this clever little thing! 

Don't feel like reading? Check out this hosted web instance of it here! 

You just type in your m/z or mass and give it a mass tolerance window and it pulls up all of the peptides in UniProt that could match. Obviously, better mass accuracy ends up with a smaller list, but what if it's up- in one condition by like 5x and the first hit is another protein from your results that is also up 5x? Mystery solved! Maybe you're not that lucky, but what a neat and helpful new tool to help you get going. It has other powers, but this is the one I liked the most when playing with it. You can also download it locally where you can change the databases and stuff.