Tuesday, July 31, 2018

Someone decided to make a GOOD mass spec blog!!

If you're here I suspect you like mass spectrometry and/or blogs.

An anonymous person in Germany is actually going out of his/her way to actually write a good one. I highly recommend it!! 

Wait -- that came out kinda wrong. I know there are other good blogs out there. I just meant in reference to the one you are currently visiting!

Monday, July 30, 2018

Great new method for studying lysine acetylation AND succinylation!

I love that we're seeing things other than phosphorylations in the PTM-verse these days! Phosphorylation may be the most studied PTM for a while, but it is only a tiny piece of the post-translational control picture (at least in people -- I don't know about other things).

Having taken a swing recently at acetylation and succinylation -- I can assure you the second has it's name for a reason (..it sucks...)

This paper is awesome. The first thing you see (when you go to the online version -- I can't imagine it works well in the print version) is a VIDEO walking you through the method! From labeling to data processing.  What a great touch!! More people should do this!

If someone says "what about quantitative acetylation and/or succinylation!?!?" this is the paper I'm going to!

Sunday, July 29, 2018

UltraQuant -- Run a scalable MaxQuant on Linux supercomputers!!

There are a lot of similarities between the Ultra series of music festivals and UltraQuant. Actually, there aren't. I was just looking for a cool logo for UltraQuant and this picture from this year's festival in Miami looked too crazy to pass up.

What is UltraQuant? Well -- thanks to Twitter -- I just learned it's a version of MaxQuant that can exist within it's own infinitely scalable container. What's that mean? It means that you can go to this Github thing from the Kentis Research Group and finally make use of those thousands of cores your facility probably has -- but has seemed kind of useless to you....

How long does MaxQuant take to complete a complex run with 18,000 individual threads running...? If I can find a way to test it I'll DEFINITELY post it here!

Saturday, July 28, 2018

AP-MALDI animal brain imaging on a Q Exactive!

Okay -- not proteomics -- but I've got a SERIOUS weakness for imaging mass spectrometry. I've never got to do it myself, but -- holy crud -- it is soooo cool.  When the MALDI-Orbitrap was basically retired (due to the fact only 10 of them or something were ever bought {p.s. I swear there are more of them in Baltimore than any other city in the world -- see? there's more than fentanyl overdoses here!}) it was just a little soul crushing. (Which -- sounds weird after the fentanyl thing I just added...)

However -- there is this weird little company in Columbia, MD that makes MALDI sources that you can put on anything -- including Fusions and Q Exactives.  This has always sounded like a good idea to me, but considering I also don't know anything about MALDI, take this statement with a plate of salt

(Explosm, FTW! No, I do not recommend you ever visit that site -- particularly during "depressing comic week")

What was I rambling about now? Oh yeah!! This new paper!!

This great team here in Baltimore finally gets one of these AP-MALDI things -- and it totally kicks ass. They couple it to a Q Exactive and Orbitrap Velos and at 140,000 resolution (on the QE) it appears to about totally make up for the fact that the pressure at ionization isn't as low as we see on most dedicated imaging MS devices.

The spatial laser and mass resolution of the lipids from these tissues is just incredible. There might be other stuff out there, but this is the first time I've seen something really convincing that says I could get really good imaging data by just buying a second party source -- rather than buying a dedicated imaging mass spectrometer. I don't have real concrete numbers, but the impression I get from a passing offline conversation is that the AP-MALDI source costs about as much as a mid-range HPLC....

Friday, July 27, 2018

PPM or Da -- what to use and when in data processing?

A reader sent me in a suggestion to write this post -- coincidentally, it has been at the forefront of my mind lately cause I'm studying 2 PTMs that differ by less than 0.2 Da -- sound like fun? It TOTALLY IS.

Regardless of what search engine you're using you probably have at least 2 choices for mass tolerance for your engine. There are some smart new software packages that look at your data and select this for you now, but they aren't the norm yet.

Let's look at an example first -- I just updated SearchGUI/PeptideShaker and wanted to take a look at them anyway (best free de novo software ever!!)

Every engine has this somewhere.

Simple answer is this --- for ion traps and TOFs use Da and for FTICR and Orbitrap always use PPM.

End of post!

Not enough? Oh -- and in my videos and screenshots I normally use 10ppm MS1 and 0.02 Da MS/MS for the Orbitrap stuff? Okay -- that's because I'm lazy -- and that was before I started studying some PTMs that suck.

In an ion trap or a quadrupole or a TOF instrument the mass accuracy doesn't change as a function of the size of the ions you are looking at. An ion trap is accurate to the first decimal place as a function of the isolation and ejection speed. An ion trap running really slow (Enhanced mode or super slow mode or Zoom depending on what vendor you're using) is generally accurate to 0.2 and one running fast to 0.6 and one running super fast is probably closer to 0.9.  It doesn't matter if that ion is m/z of 50 or m/z of 1,500 the accuracy is pretty much set.

If you're on a hybrid instrument where you're doing MS1 with high res (like an Orbi or FTICR) and fragments in the ion trap -- these mass cutoffs should apply only to the fragment ions.

Similarly, a really good TOF is accurate to the second decimal place (I'm generalizing here) and it also doesn't care what that mass of the thing it's looking at is -- it's probably +/- 0.05 whether it is at m/z of 50 or m/z of 15,000. In general, the mass doesn't play in. Find the mass accuracy that is within the calibration range of the instrument and run with it.

Orbitraps (and -- I'm pretty sure, but I have VERY limited experience -- FTICRs) are different in this regard. The mass accuracy and resolution of an Orbitrap are affected by the size of the thing they are looking at. This is why we should really always use PPM. For global stuff where we're going to have filters and FDR and stuff -- it probably isn't as important and that is why we can use 0.02 Da for MS/MS tolerance on a QE -- until something weird comes up.

Right after you calibrate a Q Exactive the mass accuracy is going to be within 3ppm -- this is an average. If you run it nonstop for 5 days and then check the calibration it's probably going to have drifted out a few PPM more. I expect to get to 6ppm by the end of the week (MS1). Despite what I've seen claimed a few times -- lower resolution MS/MS scans do have slightly lower mass accuracy (I have proof now, courtesy of MetaMorpheus's recalibration function) it's not much, but it is a little and if you want a boring explanation, I have a very poor animation I could share.

Let's assume 10ppm because the math is easier.
On a 400 m/z ion 10ppm is +/- 0.004 --> that's crazy accurate!
On a 4,000 m/z ion 10ppm is +/-0.04 --> that's 10 times worse. If you have your mass accuracy at 0.02 Da on fragmentation of big ions like LysC digests or glycopeptides, you might miss valuable assignments on the largest ions -- and pick up noise you don't need on the smaller ions. Using PPMs that match the accuracy of your instrument help you avoid that stuff.

I've often ran into workflows that use 0.05 Da mass accuracy on a Q Exactive. This is almost always WAY too loose. On high mass fragment ions, this gives you enough wiggle room to allow the search engine to pick fragment ion M+1 isotopes for fragment confirmation. It'll look like this ---

This is generally not a good thing....and if you're doing something like heavy H+ labeling, this could be disastrous....  (Heavy carbons are evenly distributed across all the carbons in a peptide, there is no reason I can think of where selection of the fragment heavy isotope is ever a good thing)

Was that too many words? Probably. Hope it's helpful -- ping me if it isn't! And I'll tag this to the NewBies section later!

Thursday, July 26, 2018

Epigenetic variability confounds transcriptomics BUT NOT PROTEOMICS, YO!

Google Scholar alert, FTW!

I recently learned about co-regulation/ co-expression analysis -- this is a tool that genomics people use when they don't have nice annotated pathways to go to. In a nutshell, it's the idea that across a bunch of different situations the proteins/genes/transcripts that are all doing similar things are probably linked together in some way. Sounds simple, right? (Especially if you are well informed and have been doing it for like 10 years before I ever heard of it - good for you!)

In case I get all rambly (this is the paper and it is killer!!)

Okay -- so the central dogma leaves out a bunch of stuff. DNA -> (a buttload of stuff, like epigenetics and weirder stuff like transflips) --> RNA --> (tons of stuff we aren't even close to having a handle on like 150 weird nucleotide modifications and end capping and splicing --> Proteins --> (75% of what we can detect with a mass spec that we have no flipping clue what the flip it is) --> Proteoforms

But this paper is about the epigenetic stuff and co-regulation. Turns out that if you try to make sense of the RNA abundance levels or the genetic localization (where the genes are coming from on the chromosomes) and line that up in some way with the epigenetic variability

-- I mean, it doesn't quite line up. However -- if you download proteomic data it isn't nearly as confounded.

This study uses a bunch of fancy R tools and some really nice mouse data from EnCode (rumor is that they know how to do genomics stuff) and the SILAC data from the SILAC mouse study (from a lab I hear is somewhat reputable) and the results look pretty clear cut.

Transcriptomics is still super useful -- don't get me wrong -- for the price of that mass spec (or 20...) you get an awesome instrument that uses a minimum of $1,200 in reagent per sample and will generate at least 220 GigaBytes of noise and as much as 0.1% of it is even useful data!!  -- but when it comes to correlating with epigenetics, it appears that proteomics does a better job.

**Yeah, I made a lot of jokes. Long day -- but please don't think for a second that this isn't a great paper -- we've got a paradigm to shift -- and this study is an important piece of the mounting evidence that proteomics is critical to understanding biology and shouldn't be sitting in distant second place to those guys with the 100x more expensive/sample sequencing instruments**

Wednesday, July 25, 2018

SILAC analysis of differences between 2D and 3D cell cultures!

Yeah!! Okay -- it's pretty clear to everyone that -- while valuable -- taking cells out of an organism and growing them flat in a plate has some limitations. Some of these limitations can be eliminated by growing cells in a somewhat more normal 3D way (come on -- cells are used to being in contact with other cells on ALL sides...that has to affect some stuff...)

In this great new study a SILAC system is used to compare the same cell lines grown as 2D and 3D cultures to see what is changing. I particularly like the fact they use a cancer fibroblast cell line and some non cancerous more normal skin cells so they can get a better feel for what is normal, what isn't and what is shared when good and evil cells are hugging it out (in matrigel).

The proteomics for the 2D is performed on an Orbitrap XL and the 3D is performed on a Q Exactive. Perseus is used to determine significance between sets and my only minor criticism is that I wish the methods would have elaborated a bit on how the normalization was handled between the instruments (intensity scaling is very different between those two devices) but maybe it is just straight-forward in a program as smart as Perseus.

Downstream analysis is mostly handled by STRING and the plots are nice enough that it reminds me I need to default to that program....

Tuesday, July 24, 2018

Wouldn't a quantitative phosphopeptide standard be great!?

I think if you really spent enough time looking you might turn up 50 different ways to enrich phosphopeptides.

If you wanted to assess them or if you're developing your own chemisty --- wouldn't quantitative recovery be an awesome metric? Maybe even better than the elusive # of distinct phosphopeptides?

And that's what this is -- a strategy for building a TMT phosphostandard!! 

Monday, July 23, 2018

Single cell proteomics > Single cell transcriptomics!

Gotta spend time on this when I get caught up -- but it belongs here based on the killer title alone! (...cause...uummm....that is exactly how science is supposed to work, right...?)

....still....I'm leaving it here so I don't forget about it!

EDIT: Having had the chance of finally reading it -- this paper is definitely staying here. These authors have obviously been doing single cell proteomics -- and thinking about what they'll need to really develop the technology to something that will help move biology forward. 100% recommended!

Sunday, July 22, 2018

CPTAC 3 -- First paper already! How the TMT protocol is set up!!

CPTAC3 (might not be the official designation, but that's what I call it) kicked off last year. What I knew about it -- full standardization. All labs have the same LC, same mass spec, use the same columns and chromatography, and they moved up from iTRAQ 4-plex to TMT 10 or 11.

Now we can all know the entire workflow!!

Interesting points? Despite having Orbitrap Lumoses, CPTAC is sticking to MS2 based TMT quan with a super interesting side note ---  they recommend running with Advanced Precursor Determination (APD) off. And suggest that the Q Exactive HF-X shouldn't be used for TMT quan because the APD can not be turned off...?

Interesting, right? But it kinda makes sense, if you are running at a lower resolution at MS1 (60,000 for CPTAC3) maybe you don't resolve as much of the lower abundance peptides that have higher coisolation interference. If APD is helping you to find more lower abundance peptides in the noisier ranges maybe those aren't going to be peptides with good ratios anyway.  I dig the logic. I also dig the 0.7 Da MS/MS isolation window. 

The study also suggests a really high degree of variation in HCD collision energies in their lab's Lumos devices. The actual settings table uses HCD CE of 34, but they emphasize CE optimization.

What kind of results are they looking at? About 10,000 proteins from xenografts with around 7,700 of them coming from human and the rest from mouse cell/protein invasion. They also show some really sharp correlation numbers suggesting their MS2 TMT quan is working just fine for them!

All the RAW and processed data is, of course, available at the CPTAC portal here.  EDIT: 7/23/18 -- I tried to download these files, but they don't appear to be posted yet. 

Saturday, July 21, 2018

EuPA Practical Proteomics Day 5 (late) Recap! Kinase cascades and Crosslinking!!

EuPA Practical proteomics ended with a bang. 

Boris Macek talked about how to study PTMs -- and how to quantify and normalize them -- and then showed an awesome study that is in press right now. I'll be noisy when my Google Scholar alert dings me that it's out.

Then we went into crosslinking for the rest of the day with Juri Rappsilber (with Lutz Fischer for the hands-on section).

What's that above? That's just some crazy amazing crosslinking report I generated in the hands-on workshop on day 5 from some BiorXIV data we pulled down using ---



and the released at the workshop but not quite published yet(?) xiVIEW(!!) All of these tools were developed by the Rappsilber lab and --together -- they're ridiculously powerful.

P.S. This is also the team that developed the xiNET online interface -- which I've been using for downstream interpretation of every crosslinking experiment I've done this year. (If you buy the $500 Xlink nodes for PD 2.2 or 2.3 it will automatically output the data into the xiNET format.

This brings up a very important point about all of these amazing tools this great lab is giving the world for free -- they've also enabled an amazing degree of compatibility. It looks to me like I don't need to use xiSearch at all if I don't want to. It looks like I can take my crosslinked data from any tool that I use and then put it into xiFDR (once i get the format right) and clean up my data with their extremely well-thought-out FDR calculations. Then I can take that data to the next step.

I sat through this workshop in something akin to slack-jawed amazement. And when I did finally say something it was a loud profanity (sorry....). I'm doing a decent amount of crosslinking right now -- pretty much successfully -- but I'm handing off PPTs and Excel sheets to the people who gave me the samples -- these tools get you all the way to the biology and is something we'll be using for sure!

Friday, July 20, 2018







Lecture 3: Boris Macek






EuPA Practical Protoemics DAY 3 (late) recap!!

Okay -- Day 3 is going here but is kinda sparse. I did something stupid (surprise!!! Ben at almost 40 can't hurdle everything he wants to anymore -- {"runner's high" makes me a little crazy in the morning -- seemed like a great idea at the time} and I missed a lot of talks while I focused on remembering how to breathe.  They were from some Apps scientists from Thermo (Sega Ndiaye and Peter Mowlds) they seemed really sharp and like nice people.

Then I took the stage after all the NSIAIDs kicked in and talked about QC/QA and online diagnostics our facility is working on. Slides will be available soon.

Yeah -- I know -- but we vetoed my talk on downstream bioinformatics because Europeans want to talk about QC. I talked about what we're setting up in Frederick which is based on work at the instrument side from Tara Schroeder and Lani Cardasis and data monitoring, which is 100% based on Michael Bereman's work. People in Europe didn't boo me when I wanted to talk about QA and QC!! That's a big deal. I stayed for Ilaria Piazza's talk (covered earlier in the week) and slept 14 hours. Did wonders for my spine and all the weird noises it kept making.

EuPA Practical Proteomics Day 2 (late) Recap!!

EuPA day 2!! PTM day!!! I'll update this post later when the lectures (that will be available) become available!!

Lecture 1: Kris Gevaert (lab link here)

TERMINOME STUDIES!!! Okay -- I know what terminomics is -- and I'm excited that other people do it and I don't have to yet. If you had to do terminomics -- maybe this is enough to give you nightmares. What if you had to do it in plants? What if you had to do proteogenomics and terminomics in plants? Honestly, this might be enough for me to leave the field.

They just published something like this. Everything else has to be easier. Holy cow...mad mad props to this team.

Lecture 2: Glycoproteomics!!!!

More brand new techniques and tools from Dr. Huber. What about advanced statistics in glycan characterization and localization? This paper JUST came out detailing part of this workflow!

What's better than a great new tool in the fastest growing branch of proteomics? Having a great name for it! This tool is called MoFi. And -- just to make sure with 100% certainty that you never forget it. Just once -- picture this legendary actor saying it.

Lecture 3: "Stories on protein biogenesis, acetylation, processing and stabilities". Sound like a great title?  Yeah!  Fingers crossed those slides get made publicly available, cause there is NO way I can do a topic this complex justice

Final talk? Ugh...it was me. Feeling 100% outclassed and not anywhere near accomplished to be sharing a stage with these people.

Lecture 4: BoxCar --> how the method works and why it is important. Give me a couple days, I'm writing something up and I'll have slides available showing how you can probably be doing BoxCar with no special software (if you've got a QE, it looks like we've got it running now, but give us some time to verify. We lost some pump seals on the QEs while I'm at the best meeting ever!!

Today cut a little short because we had the student poster session. I lucked out and got to be head judge. No joke, ya'll, the next generation of young scientists are SCARY. I was like "well...this is smarter than anything I've ever come up with, and -- ummm -- so is this...Mo..Fi..." Almost all of it is work in progress, (set my Google Scholar alerts, for real) but I can point you toward one AWESOME tool that is live now (a lot will come later).

Are you using MSFragger? Wondering what to do with all the data that it kicks out?  What if you could download an awesome Python tool that would statistically rank that noisy output and help you make sense of it?  I mean this in the kindest way possible -- but MSFragger output is kind of imposing -- backing the output up with statistical grouping seems like a GREAT next step!

You fancy smart Python people can check out Julia Bubis's AAStats tool on her bitbucket site here. She's part of the Gorshkov group that recently gave us IdentiPy.

After the poster session we took a tram ride through about 4 million awesome historic buildings in Vienna and then had dinner on the Danube!!!  (Sneaky picture I took of the students and instructors from a distance. It was way nicer than this).

Thursday, July 19, 2018

EuPA School on Practical Proteomics 2018 Day 1 Recap!!







 ....use denial when you can...it makes you feel better than thinking you're wasting loads of peptides with lousy chromatography.....


Wednesday, July 18, 2018

Chemical Proteomics --- I promise you want to check this out!!

I somehow lucked out into getting an invite to the AMAZING EuPA School of Practical Proteomics in Vienna. A lot more will follow as I wrap up what is one of the best meetings I've ever been to.

I've somehow missed this study (this year has been busy...)  I just saw the author speak on it and I promise you want to check it out. I've already sent it to some of my collaborators.

What if we could measure protein-protein communications and protein-metabolite interactions on a global scale -- RIGHT NOW?  No way, right? The technology isn't there yet!

This methodology is sneaky simple elegant and ridiculously powerful...hey...

....who makes these things....
....some picky jerks in some obscure journal called "Call" or something liked it too!

Monday, July 16, 2018

HTRA1 -- The most important protein you never heard of?

Have you ever heard of this HTRA1?!?  If not -- this paper in press at JPR suggests that you (and I) should review the (scant) background literature on it -- or just read this great new study!

What is it? Well....to be certain I'm not sure we knew until now. Seems like the literature goes back a few years showing it's important -- but this study shows it's critical -- and what it's doing in our cells!

What's it linked to?
Little things like
-Macular degeneration

You know, nothing serious...but try Google Scholar digging through and wondering how you never heard of something this important. There is SO little. And this group decided to fix it with --- FLOW CELL SORTED QUANTITATIVE PROTEOMICS!! (Yeah!)

EDIT (7/19/18) -- After spending more time understanding the paper. Flow cytometry is being used to verify the cells are in the correct states in their cell cycle. I don't believe active sorting of populations is in play.

They synchronized 2 cancer cell lines, including a modified version of SW480 where they could finely control the amount of HTRA1 protein expression (didn't check details, but published elsewhere). This is where the model gets cooler. They block the cell cycle (with thymidine) using a really interesting 2 stage blocking technique I haven't seen before.

It looks like they block the cells at one stage (the synchronized cells can't continue about their usual business of dividing. They just stop all that stuff.) Then they wash it out in some cells and block the cells again at the next stage in the cell cycle. Sound hard? Sound like the matrix is getting pretty big? You're right on both counts!!

This great study doesn't stop there. They use another checkpoint inhibitor or two. What they get is a big picture of what different levels of HTRA protein does at different points in normal cell cycle stuff. Because the cells are syncrhonized and stopped all together, they have a big population of cells all doing the same thing. Messing with any protein in this system that is linked to cell cycle progression or maintenance is gonna have effects somewhere!

Wait. What? They also throw in some DNA intercalators? This study is big. Wow. Next time someone has any kind of a serious fundamental question about DNA damage or cell cycle checkpoints pull up this paper and --- boom!

(No joke. Go talk to someone who does Radiation Oncology. They'll be really impressed!)

Once this large matrix of cells at all these checkpoint stops were acquired, proteins were extracted and digested and ran on really really long nanoLC columns? I'll need to check on details. I just talked to someone today with a 200cm nLC column I might try, so maybe 380cm isn't actually that crazy. And all spectra were obtained on an Orbitrap Elite. All processing was MaxQuant LFQ and Perseus.

What do you get out of all this work? What about proof that this protein I never heard of appears to be linked to regulating as much as 1/10 of our proteome? And if you adjust this by a very crude estimate of the proteome coverage vs theoretical proteome -- what if it looks almost half as important as the cell cycle indicators that scream "STOP DIVIDING SOMETHING BAD IS HAPPENING TO OUR DNA". For real.

Elegant experimental design -- really clear output -- mysterious LC conditions? Great paper you should check out!

Sunday, July 15, 2018

QC-ART -- Real time(?) proteomics QC in R?

Credit for this link goes to @UCDProteomics. It's awesome to be mostly done with a QC proteomics talk and then something totally new and amazing pops up in your Twitter feed!

I can not guarantee I get this. I'm also not 100% sure I'm cool with something as wildly open source as R directly interfacing with my mass spectrometer -- but ---

This might really be worth checking out -- particularly if you've got an R BionformaGician around anyway and you haven't instituted a full out QC protocol on all your stuff!

They Shiny App interface looks really super friendly and non-intimidating.  The number of variable assayed may not be any more than what we're currently implementing (sProCoP/AutoQC), and I should probably do some stuff rather than digging through details I probably wouldn't understand anyway, but PNNL has a tendency to make some really good software -- maybe not the most dumb person (me) friendly software, but I bet this is worth taking a look at!

You can download QC-Art here!

Saturday, July 14, 2018

FAIMs is back?!? And putting it on an Orbitrap improves shotgun proteomics!?!?

For just a second I started this paper -- Pierre Thibault -- FAIMS and thought maybe it was 2005 and I had to check a mirror --

Nope -- definitely not 2005 --

You, too, might feel like you've stepped into a time chamber when you see some definite suggestions that FAIMS might finally be back -- and it should be if we can get results like these!

It's in open in press right now!

This paper is really big and deserves more time than I can spend on it this morning and should really be checked out.

Get this -- they do TMT-10 plex (this is FAIMS on a Tribrid). TMT-10 plex can't be done on another ion-mobility proteomics instrument that's getting a lot of attention (despite resolution claims it can't, resolve the reporter even our Orbi XL can) AND -- maybe even better -- it looks like they get better results than SPS-MS3 based TMT quan (less cycle time hit? with FAIMS? what!??! I know!)

Can I get FAIMS now? Doesn't appear so, but maybe soon??

Shoutout @KarlMechtler for tipping me off to this!

Friday, July 13, 2018

A really insightful analysis in paleoproteomics!

I'll be honest, I don't quite understand the paleo part of this study OR the proteomics part! However, my slowly caffeinating brain still realizes that what I do get suggests that this is really cool and has implications for what I do every day!

Besides the obvious WOW factor that this is a proteomics study in an Evolutionary Biology journal(!!) there is still a lot of insight here even past the paleontology part.  Dr. Welker is drawing conclusions from proteomic analysis of both distant relatives and very close ones (humans to chimpanzees) using different search techniques to show where they do and don't have power to make connections.

While most of us aren't doing paleoproteomics, almost all of us are searching proteomics data against protein FASTA files that don't contain the exact sequences of the organism you just lysed and chopped up with trypsin. Individual proteomic variation like single amino acid variants (SAAVs) are undoubtedly having an effect on just about every run we queue up. Maybe error tolerant searches like the ones used here are the temporary fix we need until proteogenomics gets easier (and sequencing gets a little cheaper)!