Some peptides suuuuuuuuuuuuck. They don't have basic residues, or they have too many or they have too little and too many in all the wrong places. Sure, alternative enzymes help, but not if you end up with no way to charge the stupid things.
What's an APCI source? It's in the translator over there somewhere, but it is something about chemical ionization, and you should try it if nothing else because it looks really cool.
APPI is something similar, and basically if you have APCI you do something slightly different and you have the other. APCI is great for fluorinated compounds or other things that you're just about to give up on getting signal for (a lot of pesticides look great on APCI, particularly things that are Fluorinated or extra Chlorinated. I've never done APPI and it was looking probably that I wouldn't have time to with what is left in my career.
However, if I can pick up more GluC peptides with APPI than with electrospray -- because I fragment the + acetyl adduct(!) then maybe I'll dig in a drawer until I find one!
One nasty little secret in LCMS is that we're only getting about 1% of the molecules from the liquid phase into the charged gas phase. We can do all sorts of great things inside the instruments (and have) to improve the efficiency of those gas phase ions, but even at 100% efficiency internally (which we don't have, I don't care what anyone says, and you shouldn't either) there are big dividends on the outside.
It reminds me of something, I can't think of what, but if these numbers are real (those are log intensity values in C!) I think it's time to visit the machining shop down the street!
You've got plenty of search engines to choose from these days for different applications. If you're interested in single cell proteomics, that's your fault, but you might be interested to know how different tools perform.
My setup uses MSFragger, MSAmanda 2.0, MSPepSearch and SequestHT and Percolator to sort it all out at the end, so maybe my solo quest to do meaningful SCP here is on the right track in at least one regard.
I like that this group digs deep into the PTMs they can detect in single cells. It wasn't all that long ago that was a super controversial thing to say you were seeing. Are they the most convenient PTMs possible on the highest copy number proteins that are there? Yes and yes. Still there, though!
Nice little paper, and I always appreciate a good clear UpSetR plot.
Kidneys that might be considered...suboptimal...for a number of reasons are sometimes subjected to something called NMP that is in the blog title and I doubt i can type it correctly again.
As you might guess, having human kidneys in a machine to keep them going for a transplant imparts a lot of changes. Knowing what ones might help us predict which will work, which won't, and how to preserve them longer!
I can't figure out what instrument was used for this. Since the MS1 resolution is 120,000, it is probably a high field Orbitrap, and I suspect we're operating in DDA mode. The biology is the star here and the details on how the proteomics was performed doesn't fit within the page limits. That's still okay, because of how interesting the biology is.
If you actually want to know, the RAW files are up on ProteomeXchange here as PXD036432.
For some weird reason this was the second most viewed post on this blog in all of 2022 (after #1, when I responsibly (and extremely legally, cleared by EVERYONE) released the details of the Orbitrap Assend).
I honestly don't know whether the post was popular because literally no one knew we had a Proteomics Standards Initiative, or if they thought one was a good idea.
LMAO!! I know that literally no one at all cared that it existed OR thought one was a good idea. The evidence speaks for itself.
However, just for fun, I have an inside agent who is (I'm not even kidding) actually going to attend it this year. For real and I'm going to leak the location and details for fake internet points.
It is in Gasselterboerveenshemond, in the Netherlands. The organizers, tired of being ignored, found the easiest to find city in all of Europe. The name is short -- and phonetic -- it is pronounced exactly as it is spelled.
You have no excuse for missing the riveting discussions at the PSI meeting with the easiest to type city in Europe for your GPS program of choice and literally everyone in the world will know exactly what train station you are aiming for.
I think most mass spec or proteomics or -omics studies go 1 or 2 main ways. You're focused on understanding a biological system at some important granular level or you are building a resource for people who are.
ImmPRes is a really beautiful new(?) [they've been working on it for 8 years, but the web portal is new to me, so I think that counts as new(?)] example of the latter, born from years of experiments in the former.
http://immpres.co.uk/ let's anyone interested in the proteomes of immune cells to easily dig through data on all sorts of cells associated with the human/mammalian systems.
For example, say you're interested in just CD4 cells --
BOOOOOOM.
Now....I know that we're supposed to do hypothesis driven research...but how often does that come up in explorative -omics? I'm impressed when it does, but most is "how the fuck does this system work?" and I really think that is where most of us operate these days. If you can get to a point where you've got a resource easy enough for anyone to dig through, you've done something good for the world in my clearly exceptionally biased opinion.
on a drug that I've been messing with for a little over a year and in every single cell line I've dosed with the drug, I've seen a decreased abundance of the ERK protein of 2-5 fold.
By DDA, by DIA, whatever, there is always less of this protein when I dose my ATCC cell lines with this drug.
Sure doesn't look like the case by Western blot.... The 2-fold doesn't surprise me, what I tell students is that if you see it 5-fold different by LCMS, you can "validate" that by Western. I haven't used these cell lines, but I'm curious now and will get them.
Here is the thing, though, if you go through this study almost every figure and result in this study focuses on whether ERK and/or phospho-ERK are altered by single/double drug/ siRNA, whatever, treatment.
What does this do to the rest of a very nice study if there really is a significant alteration in your protein levels/abundances and you just can't see it? If I go through this paper and assume every time they see ERK unaltered, it actually is, then EVERY conclusion of this nice looking (and obviously difficult) study needs questioned, if not completely thrown out.
Considering this might be the single most promising drug ever developed for pancreatic cancer, I'd really prefer if the measurements were a little more accurate.
A lot of the newer direct drug-target stuff uses different temperatures for unfolding the proteins prior to digestion and we've seen how valuable multiplexing can be for those.
This study breaks out a lot of newer technology, including phase constraint, but the first thing that stands out is the use of isobaric carrier channels. By having that secondary carrier (which is referred to as SIILCC, here) this group shows a dramatic improvement in data quality. Normally we're using that to boost our signal for incredibly low abundance things, and we know the limitations for those. Here, however, they could realistically just add more material, they aren't incredibly limited.
Where this really truly shines is in the increase in data completeness. Having this higher abundance pool in the carrier channel reduces the number of missing values and makes the data a whole lot easier ot work with.
In a case where you're trying to determine "did this drug alter the melting point/thermal stability of protein X" NOT TRIGGERING an MS2 on a peptide of interest can make that whole LCMS run pretty much useless.
Altogether this is just a really clever way to leverage an isobaric carrier channel in a new-ish way to improve the data in really tough and extremely valuable experiments.
Please note, the previous title: "Get IonOpticks columns from a US vendor instead of from sketchy Australians" was a joke based on whatever parameters our purchasing department uses to audit vendors for direct purchase approval. Whatever those parameters are, I can't purchase directly from a number of foreign vendors and this has zero bearing on the company itself, it probably is some tax thing. If I thought these people really were sketchy, I wouldn't...send them lots of money and use their products to run precious -- often invaluable -- human samples. ....
This probably doesn't count as something that should be here, but I'm really tired and this is a big deal for me.
I really like the IonOpticks columns for the TIMSTOFs. A little expensive? Sure, but the main reason that we don't use them all the time is that they can't get approval at our university as a vendor. I've met multiple people from their company and they seemed okay, which makes me worry even more about my ability to judge people. *Checks notes* Yup! Loads and loads of reasons to be concerned about my judgment!
Well, whether or not the people who tell me how to spend money with my name on it like these Australians, they make nice columns. And you can now purchase them from a far less sketchy American company! (..again...this is a joke....sigh.....I think I rarely "sigh" and when I do I suspect you can tell I was raised by a teenage mother in a trailer in a West Virginia. It's more of a growling sound that sounds suspiciously like a whole lot of f-words, but not suspiciously enough that a pastor would catch it.)
Yesterday was the last day of the NBA regular season with loads of playoff implications for all teams with places 5-9 in the western conference decided in 1 day!
Stick with me here, because the proof that proteomics is BIG DATA and can do BIG COHORTS are starting to drop and I think there is similarity here.
We probably can't stop the "next gen" proteomics tools that are coming. They have too much inertia and too much money, and even when there isn't a lot of proof they work yet, we'll either have it soon -- or we won't.
In the meantime, they're resetting the expectations for our field. Worst case scenario -- it turns out that things like O-link and Somascan and WhateverIt'sCalled suck and we forget about them 5 years from now -- they've done one major thing.
They've proven, without a doubt, that medical researchers and biologists all want big cohort proteomics data. They appreciate the value, they just don't think LCMS can do it.
Now, you could argue that worst-case scenario is that these new technologies are amazing and they displace us, but the season ain't over yet. Want proof?
>2,000 plasma proteome samples. It took some work to find out the throughput, but based on the references and the fact this paper used EvoSep 60, I think that is what it is, so not counting controls and libraries, that's 1 month for one Exploris (DIA).
That's great and everything, right? This isn't the coolest part for me. It's the pQTLs.
Quantitative Trait Loci (QTLs) are a big deal for bioinformaticians. There are entire fields of researchers looking at the genome/transcriptome/proteome in a different way than we are. They aren't just isolating this one thing that we think is a distinct protein and trying to figure out if it is linked to things. QTLs focus on phenotypes -- in humans, that's going to be the clinical information -- and then look at what quantitative changes exist when that phenotype is present. It sounds like what we do, but the subtleties and the direction at which you look at it are very different.
800 HLA peptides from 1e6 cells is a crazy number to begin with (good job little Exploris!)
3,000 HLA peptides from the same amount of material is ridiculous.
AND they did this with Spectrum Mill! Imagine what they might get if they used a good search engine
(with all respect to Dr. Clauser, I know that the Broad Spectrum Mill is some super amazing custom job, operated/optimized by the guy who designed it, but I couldn't resist).
Well....it's finally happened...you send back one person HLA data that makes sense and now people are figuring out the secret way to get into our basement (elevators were shut down because they are very very very unsafe) to offer us projects.
I saw a real science blogger talk and she mentioned revisiting things that you think are really important that might get lost in the months or years of content you generated.
RawBeans is a tool that I tell people about and forward all the time.
"Why did I get less peptides than expected in this run?"
RawBeans time!
Chromatography information, fill time vs AGC information, you name it, it is in here (some features like AGC might not work well for an instrument that doesn't have AGC, etc.,) but you get the point.
1,300 proteins in plasma at 60 samples/day sounds pretty freaking impressive to me. Especially with a method that doesn't rely on a super expensive and slow depletion column and looks extremely amenable to automation.
Somebody put this up on r/proteomics to start a conversation about it if that's a format of social media you use. I'm thinking about this big plasma cohort I was on the fence about taking on and whether this simplifies it and gets the cost down to where I could do it?
