Do you still need to do a BCA assay for LCMS proteomics?

 

I haven't had the chance to put time into this, but I want to. The abstract suggests that maybe doing all the BCA quan steps might not be necessary for some experiments. 

US HUPO 2026 Recap?

Okay, so I was going to type something like "I don't know where to start" but that's a lie. I should probably start by apologizing for being such a jerk about the city that hosted US HUPO. I'm pretty pissed off about the state of my country basically all the time. I'm particularly frustrated about watching the news and grinding my teeth last week enough that I had to go to the conference with a broken tooth. And some geographic areas are more at fault for the rapid decline of my country than others. Whining about it doesn't change things, and that's why I am running for a government office in my abundant spare time. But that's not what this is about.

St. Louis was a fantastic venue for US HUPO and I'm leaving here very happy that John Yates invited me to join the advisory board so I couldn't just sit at home being a jerk about the conference location. 

The conference was a little smaller than some previous ones with something around 550 people. Because it is a Conference Solutions organized event - it was very very organized. I'm not throwing shade deliberately at International HUPO, but one of those things is not like the other.

You could literally stumble outside (I'd assume, I didn't stumble much cause had a lot of responsibilities so I was BOOOORRRIIING during this conference), and there you go - the St. Louis Arch. Apparently you can go into it! 

It was a super relaxed conference. ASMS divided by 100. US HUPO Chicago/2 for intensity. 550 people with plenty of room to walk would do that.

Obviously the science on display was nucking futs. 

BIASED Highlights? 

1)There must be 10 different plasma nanoparticle enrichment technologies on display! There is some paradigm shifting shit going on right now. For real, I have to change some slides. Biomarker discovery goes like this 

- Build a statistically valid cohort and get SOLID TISSUE from them. Do amazing proteomics on healthy and not healthy

-Build a validation cohort in SOLID TISSUES

-Get some plasma and find out that you can't see any of those fucking proteins in plasma.

Major conversation I had with some of the best proteomics scientists in the world (that I'm not at all sure why they talk to me) Matt Foster (Duke), Ryan Kelly (BYU), Brett Phinney (UCDavis) have been like this. 

Wait. Can we just do blood? Skip the organs? Speed EVERYTHING up? It might be real. 

2) Blood/serum/plasma proteomes might be stable for decades! 

Okay - so you know how a lot of us have access to these weird repositories of tens or hundreds of thousands of blood/serum/plasma samples? Come on, you have probably stepped back and thought "I bet most of that old stuff is worthless, right? 

The first US HUPO 2026 talk I saw (I spoke at 7:15am, or I probably wouldn't have seen it...) was Jan Muntel showing how they did thousands of proteomes of plasma from a Johns Hopkins / NIA study. Some of those samples were 30 years old! Baltimore is an amazing city, but it doesn't have the most stable power grid, particularly the area around the Hopkins campus. So...if you could get consistent non batchy effecty data from that, then all of these repositories are about a million times more valuable than I ever thought they were. 

This text is making me bored, so here's a photo of some really tall guy and me in a jacket I got for $10 years ago that only fits thanks to an extra 15 pounds (yay!) and Jan! Watch out for a paper from him. I hate asking questions on microphones but totally needed to know if the PTMs had any value. He should know soon! 

Highlight number 3) 

Might be a lowlight. I might be getting old, yo.

Point 1) A researcher I first met when she was a new grad student with Michelle Cilia is now a PI with her own lab and is apparently being a super cool influence on my favorite US HUPO committee (Ed&Out Reach, previously VMO). Keep an eye on Dr. Angela Kruse and her lab. 

Ed&Out is now very focused on making proteomics more approachable! Check out this video!

Point 2) I'm pretty sure I just had my mid-life crisis thing and went back to academia, right? Right? So it's impossible that a High School Student who worked in my academic lab gave a lightning talk and had a ridiculously cool poster. I can claim absolutely zero (not being humble, real life zero) credit for the success of Fatima Sarfraz. She did a summer rotation with an incredible PhD candidate (Dr. Abigail Wheeler) and I had no part in anything but trying to stay out of the way and being positive and encouraging of whatever they were doing. Fatima presented better data at some of our weekly meetings that summer than some of the grad students and postdocs. When I found out she was going to Princeton the very least I could do was alert the impossibly charismatic, and apparently immortal, Ileana Cristae that she was coming. Apparently, that worked out, and clearly biased, but it might have been one of my favorite lighting talks. 

Highlight number 4)

Who am I kidding? I've easily been to 200 conferences by now. 

The US HUPO lightning talks are THE BEST, COOLEST, FUNNIEST thing I've ever seen at any of them. I had two invited talks and the only thing that I get stressed out about is 

SITTING ON STAGE IN A SPARKLY SUIT READING OUT NAMES.

These people have 60 seconds to pitch their research and I could stutter and mess it up. We butcher names. It worries me.

We had rapping, we had juggling, we had the best karaoke I've ever heard, and it was about all the different ways you could do PASEF DIA method. Yes, that won an award. 

The winner of lightning was the same BYU undergrad who won it the last 2 years. 

If you're in marketing in a proteomics company and you don't have a 7 figure multi-year contract ready to offer that young man before he graduates, you're a dumbass. He could sell me SomaScan. He'd have to possibly send the first spreadsheet of data showing that SomaScan works, and then do a Queen tribute to it, but - for real - heads up. 

Highlight number 5)

It only costs $54 to make a life sized cutout of a person who couldn't attend a conference because it's on his/her kid's birthday. I told Mike Washburn when we passed on an escalator - I'm about to set up my favorite joke of the conference.

I put a 6 foot tall, so almost real life sized, cutout of Dr. Benjamin Neely around the conference. Sometimes I'd stop by to make sure no one vandalized him. OMG. Best $50 ever. I did not set this the following photo up. I found him trying to get people to take free conference swag. 

I'd occasionally get random photos and I'm pretty sure he did too. 

Edit - found a few more! 

Somehow related. For real, you had to be here to see how much amazing chaos this was during lightning.

The ultra talented US HUPO President Dr. Ben Garcia, doing a proteomics centric parody of a song from the Barbie movie that is about male fragility was THE FUNNIEST THING EVER.  Except for the first lightning I ever saw with Ileana Cristae. OMG. So funny.

Okay, I have a plane. Later!

Wait. I totally forgot. And my plane is delayed! 

Proteomics people like podcasts! 

At US HUPO honorary Ben, Dr. Renã Robinson and I recorded the 100th episode of THE Proteomics Show! It's out now and it was super fun to interview Dr. Natalie Clark on fine details of the CPTAC initiative and learn about how modern video games work and discuss an animated whale who is super popular with toddlers. 

Yay! 100 podcasts, and some number one the screen the final day said a preposterous number of listens to said podcast. Like e4s of listens. So there you go. We should probably record some more. I just wrote Neely to ask when Season 11 recording starts. I had so much fun at US HUPO I might ask them if they want to partner on another one. We finally found inspiration for one. 

As I'm fixing blatant airport typos this one is cool. 

You can't be an important member of the leadership of US HUPO forever. John Yates gave Ben Garcia a funny president hat as he moves onto some role at some ASMS thing, and some other people passed the torch as well. We're all grateful for the effort they've put into steering the organization to what it is now. 

Single cell proteomics of metabolic liver zonation!

 

While I was at the amazing US HUPO conference in ...Meh...Souri...which was honestly not as bad as I thought it was going to be, Natalie Porat-Shliom spoke on this amazing new paper at MY University! 

Stunning amazing, ridiculously great work that blew up our lab Slack channel thing! 

Top down proteomics takes on liver fibrosis!

 

Wow, there are a lot of liver diseases and we've got decent diagnostics for....well...liver damage.... that's about it. A small panel of liver damage markers finalized around the time Stan Lee and Jack Kirby went on a creative bender and wrote everything from the Fantastic Four, through Spiderman and the X-Man comics. I'm not kidding, there really has been almost zero forward movement in liver diagnostics since the 1960s. The liver protein panel was old when I was running them in the clinic in 2003. And it's still the same thing. 

Could top down proteomics be the answer? 

Given the current limits of top-down it sounds unlikely, but you'll find what appears to be some pretty clear differentials in these small intact proteins (they seem to get up to 38kDa) in this study.

Is it the simplest way forward to getting some modern liver diagnostics out there? Maybe? But for a field that seems to have completely hit a wall 60 f'ing years ago, it's time to try everything! 

Arralyze CellShepherd- Live cell imaging tandem single cell proteomics!! Webinar 2/25!

Timing on this one is a little unfortunate, because everyone has schedules, however, we're getting this science fiction sounding new toy and I'm happy to invite you to this webinar next week! 

Okay, so what if you could do live cell imaging and - not messing around  - dose your cells with a drug and then use machine learning tools to go and pick up the cells that meet your criteria. For example, what if I was growing a population of cells - on the instrument(!!) - in the presence of a KRAS inhibitor and then when that annoying subpopulation of cells I can't seem to catch enough of with random sampling started to demonstrate the EGFR linked adaptation phenotype that no one can seem to figure out--- then the robot pick up that cell and then prep it for proteomics then moved to the other one?  

Science Fiction sounding, right?

I won't have data to show from this at US HUPO, Monday I'm showing the dingle cell workflows that you can get in the amazing Health Sciences Mass Spectrometry core and Wednesday I'll show Cameron and Shelby's work with single cells taken right out of human surgery. I'm biased, but that shit is Musa acuminata.

I'll post a link to the webinar on this the day of the seminar. We had a weird thing where some bored weirdo showed up at one of my writing group meetings and just yelled random bad words. 

You can learn more about Arralyze here. There isn't a lot of proteomics data there yet. Mostly them just showing off how they can observed and mess around with one cell at a time. 

RIPUP histones to rapidly find a new pile of post-translational modifications!

 

This new preprint is so legit. Not only does it identify a pile of histone post-translational modifications I didn't know about, but it does it fast AND it justifies the chemistry that makes it happen. 

What if the reason that some of these PTMs aren't visible is that the modification neutralizes that peptide's ability to pick up a charge? Makes sense. A lot of the more awful PTMs do. 

But what if you could make them visible by adding a boring ol' tandem mass tag? Bonus points for the introduction of an enzyme I didn't know about with an amazing name:

Stop, don't read this. Next line until someone is around and then read it really loud! 

"HEY! Someone order me some ULTRA ARRRRRRGGGG-C!!!!!"

Thermo has embraced Windows 11 on a bunch of software!

If you are like me and you have a PC in your office that your IT security people don't know about (shhh!)  that you just copy your RAW files to in case you need to look at an actual spectrum, do I have great news for you! 

As of a few months ago Thermo started embracing Windows 11! Check out this list! 

A protein organ specificity atlas based on PROTEIN DATA!

 

Leaving this here so I don't lose it for another week because I am incapable of committing any of these author names to memory.

You'd think it would be easy to find something written in the last couple of years that was about tissue-specific proteomics, right? 

You would be very very very wrong. I have 9 tabs open on just the PC I'm standing in front of in my house (wait. why am I here? I have a meeting in Oakland in like 30 minutes...? TYPE FAST!)

In 8 of these papers, the authors who wrote it used the GTEX RNA DATA to determine organ specificity. As you might remember from some of my earlier rantings, GTEX prediction of proteins in organs is better than flipping a coin. Just not by a lot. 

This extremely polite group integrated the GTEX data, but went ahead and did organ specific proteomics (in-gel digestion 6 cut QE HF / QE HF-X) on their own. (Sorry, really truly moving fast, I can't reference the methods.) Then they were extremely polite and constructive and integrate the GTEX findings into their analysis. They go with something like "if 2 out of 3 atlases show a protein is organ specific" then they consider it specific and move on. I don't know the origin of the second (probably RNA atlas) but that's one reason I was super annoyed I misplaced this paper! Now I won't! 

NanoPots + TMTPro 32 >600 tiny single cell proteomes/day!

 

In an interesting recent trend, everyone seems to be emphasizing how small of a cell that they can do single cell proteomics on. 

Do we have a new winner? No, Akos did single E.coli. Even if it was only like 25 proteins, that's clearly the winner for craziest tiny cell idea.

But this group did PBMCs! 

How much protein is in a PBMC? 

14 picograms! (These author's math, not mine). FOURTEEN? 

My group has recently struggled with some human immune cells... and from the TICs I was guessing we were starting with less than 50 picogram. FOURTEEN? Geez.

How'd they get there? 

NanoPots. Ouch. Okay, so something you have to build yourself, but something with incredibly ridiculously low sample loss. 

Then TMT 32plex. 

If they were able to recover all 14 pg, and lets just say that they used 30 channels for actual single cells. To the mass spec, that looks like an MS1 signal of 14 x 30 = 420 picograms. Ouch. That's still not much at all....

The instrument used was a FAIMS (2 voltage) Orbitrap Fusion III (Eclipse). Real time search (ion trap matching) was used to determine was ions to analyze in the Orbitrap for MS/MS. Dual columns and emitters were also used here, and they did have to fabricate a bracket to make that work. 

For samples this low in concentration there was some painstaking optimization, in particular of the "carrier" or (here) "bridge" channel. Sometimes called "boost" or "orgeano" because mass spectrometrists are still a bunch of cantankerous assholes who like to make up new terminology so that we seem as annoying and unapproachable as possible. I'm pretty sure it's just because we all hate research money and being taken seriously and we'd get a lot more of both if we'd quit making up stupid new terminology. 

The bridge channel was kept very very low. The highest tested appears to be 1ng. So...1.4ng on column....

You have to dig for the HPLC stuff in the supplemental but it's about an hour. I'm a little confused about how this version of the dual column parallelization works. It is detailed, but I didn't take time to draw it out, but it looks like each sample is about 60-75 minutes. 60 minutes for 30 cells gives you 720 per day and 75 minutes for 30 cells gives you about 575. The authors report 660 cells/day, so it's somewhere in the right range! They squeeze extra signal out with a ridiculously tiny column. 50um internal diameter and 25cm length. I think this is =>100 nL/min to keep the HPLC from leaving craters where labs used to be. Real time search with spectral libraries made from these samples do some heavy lifting here. And once the authors get it all optimized out they run the system for about 3 days to report data on over 2,000 single cells. 

Really truly impressive work and another great resource that demonstrates we could do high numbers of single cells if we really put the effort in! 

Poor RNA to protein correlations are an artifact of poor proteomics data?

 

I was making slides for a class lecture and went down a long and windy rabbit hole on what we now know about the discrepancies between RNA and protein regulation. I landed on this one from 2022, and while it may seem like I'm rage baiting....I think it should go here anyway..

Despite the title of this blog post we aren't firmly blamed for all the errors. Some error does exist in the mRNA measurements, but it's pretty clear that the disagreement in protein measurements between different studies is something that is worth thinking about.