DIA-Umpire V2 -- Full support for Orbitrap data!

Mild confusion when I saw this article on GenomeWeb (original here). Cause I was honestly surprised that anyone had used the DIA Umpire for anything other than Orbitrap data -- but it was totally invented for SWATCH!

So...DIA Umpire V2 is now out and ready and, guess what(!?!?) it seems to be fantastic for Orbitrap data. A description of DIA Umpire V2 can be found in this brand new paper here.

Explain bioinformatics (or proteomics) to your grandmother!

...this paper needs more attention. Cause it is awesome.

Didn't Isaac Asimov say something to the effect of "if you can't explain it you really don't understand it?" I've looked for that quote before and not found it.

Anyway, this paper is awesome. Its a couple years old but it is cool enough to bring up and was bouncing around Twitter this weekend.

While we're on the topic of Atlases -- A great new review on the Human Protein Atlas!

Hey! Don't forget the other Atlas while everyone is talking about the low resolution one!  The Human Protein Atlas is an awesome huge resource that I visit frequently (mostly for cancer cell line data) but it has tons of stuff in it.

I'd never even seen the Mouse Brain Atlas until I went over for that image. Want to see some awesome microscopy? There is some stunning stuff in there -- and it is useful -- not to me, but to somebody for sure!

What was I...oh yeah!  A brand new review on the Human Protein Atlas from Cecilia Lindskog. It is a nice short read, and has a clinical tilt to it. You can read it (open access) here!

Don't give that big 'ol FTICR away just yet. They found some Helium!

Say Good-bye to the Helium shortage and Hello to your favorite 1 Hz FTICR again.  Researchers collaborating with an un-named entity found a huge reserve beneath the country of Tanzania. Hopefully this leads to cheap helium again and some economic gains for one of the world's poorest countries. Wins all around!

BBC article here. Wait. Is it still B-BC? Didn't they change their name or something recently?

SRMAtlas -- Tools to do SRMs on a bunch of human proteins!

Whoa! Finally got the full text.

I humbly present my interpretation of the HumanSRMAtlas that showed up in Cell last week.

Let me get this off my chest first. This thing has been around for at least 5 years, right? Seriously, I thought I'd been taking crazy pills, but then PubMed verified it:

GoogleScholar finds references to it going back even further than PubMed does. And this went into Cell!

With that out of the way!  What is this?

Its a ton more SRM assays!  They painstakingly developed synthetic peptides that would be representative of a large number of human proteins. They obtained MS/MS spectra for these synthetic peptides using some Q-TOFs and used multiple collision energies to assemble good spectra.

Then once they had this big library they picked a pathway that was interesting and they show that they can use triple quads to look at quantification of that pathway in human cells.

Will the SRMs still suffer from the same inherent problems of every low resolution MS/MS experiment ever done? Absolutely! But a lot of work went into minimizing this. Proof? Peptides from 7-20 amino acids long, they could identify with 96% success rate in their tissue (FDR ~4%) bigger peptides were more problematic (21-30 amino acids ~ 83% success rate), but remember this is SRM, you can always do more peptides.

Will interference be a bigger problem in more complex organisms like humans? Sure!

Will the quality of the data vary wildly depending on the body tissue? Of course.

But, this is a seriously comprehensive database. Loads of SRMs. A TON of work went into this and its a free resource out there at SRMAtlas.org!

Ben's biggest questions here -- presumably since this was designed with high resolution MS/MS, I wonder if this resource is PRM compatible for higher certainty, less noise, etc.,

Another awesome UVPD phosphoproteomics study!

I swear I'm almost going to stop reading papers where people have "hacked" their Orbitraps and added UV photo-dissociation to them. Maybe this is the last one.

This is (one of?) Jenny Broadbelt's systems it seemed like everybody at ASMS was talking about and described in this new paper by Michelle Robinson et al.,.

In this case they modify an Orbitrap Fusion (yikes!) and add UVPD to the HCD cell. They IMAC enrich phosphopeptides from cancer cells and alternate HCD/UVPD and investigate both positive and negative modes.

The HCD still wins in terms of most identified peptides (15k resolution MS/MS scans), but the UVPD peptides are highly complimentary to the ones identified via UVPD. The negative stuff looks the least efficient in terms of ID's per time, but identifies even more complimentary phospho peptides identified by the other techniques.

They use PD 1.3 and Sequest for the data processing. Part of me seriously wonders if they could do a lot better with the modified OMSSA Coon Lab has been using, or with the modified Byonic that was described a few weeks ago.

In the end, though, we're looking at another description of UVPD that shows it has enormous power. Unfortunately, no one is discussing commercial release. Looks like some of us here in MD need to buy a laser and a voltmeter and get rewiring. I've got a spare weekend coming up... (P.S., I'm mostly joking)

Masses4Masses.org

Mildly interesting -- and somewhat odd. Masses4Masses.org.

Might be interesting cause its got a pretty nice animation of mass spectrometry history. Might be leaning a little toward a particular set of technologies ---

Interesting perspective, right? If you were an outsider to the field you could scroll through this and think that ion mobility was the biggest technological advance in mass spectrometry for this century so far. Not to say that it isn't cool stuff. But...

...its like looking at a genomics website that breezes over PCR like it was some annoying stepping stone. "In 1995 some guys made unlimited amounts of DNA from virtually no DNA and some weird guys in Norway gave them a prize for it"

Seriously, pretty animations and some interesting videos. But it might be as slanted toward a particular technology as this silly blog is. ;)

Mission Critical -- Why Precision Medicine NEEDS proteomics!

I guess if you read into the image above it might seem like I'm implying something. I'm not. I just couldn't find a cool picture for "Mission Critical". This seemed much cooler!

What am I rambling about now? This cool opinion/review in Human Molecular Genetics. It is called "Mission Critical: The need for proteomics in the era of next-gen sequencing and precision medicine." YEAH!

Who is it written for? The HUGE genomics field and the users of this technology AND kinda for us. It is a great description paper of 1) Our technology 2) Their technology and 3) Why the interplay is critical.

It points out places where we can definitely interact -- such as mass cytometry (enriching and identifying cell populations by mass spec) -- as well as a few places where genomics techniques lack power that our instruments have.

Now...minor criticism of this nicely written paper might be that our current generation sensitivity and power might be downplayed a little. Sure, amplification based DNA/RNA techniques are super sensitive, but some next-gen techniques don't employ amplification. Compare where we are now in terms of the low copy-number proteins vs transcripts each respective field can identify and we're not far off -- and possibly ahead.

Wait, one more. You can tell the authors are coming from the genetics world in that the only times they mention modifications are when they discuss splice variants or single amino acid changes. You could argue that with the importance every study is showing regarding post-translational modifications in every disease we have looked at -- well, this is where mass specs are going to be indispensable in terms of precision medicine. Good luck PCR-amplifying that global shift toward deglycosylation!

Seriously, though. Well written paper with some good arguments for why our field needs to be considered in any initiatives toward precision medicine!

SRMAtlas -- Come on, PubMed, list this thing so I can find a full text copy!

Honestly, just leaving this here so I don't remember to read it once PubMed indexes it. I'm far too  lazy busy to find it in the stacks -- and I ain't paying $53 to read something about triple quads (no offense).  Seriously, though, Twitter has went kinda nuts about this paper, but I'm not sure anyone has read it yet.

When it is indexed I'm gonna say SRM-Atlast!

Proteomics approach finds other dominant virus proteins in Zika+ brains!

You could say that 2016 was the year of the Zika Virus. I'd honestly never heard of it. Friends from areas where it has been around for a long time made it seem like no big deal. Just another tropical virus you get sometimes (!!) -- but it has been implicated in some terrible stuff, including (terrifying!!) microencephaly.

According to this brand new, short report from Fabio Nogueira, et al., Zika virus may not be the only thing at play in the real nefarious stuff.

They got some brain tissue from brains that tested positive for the Zika virus by PCR, digested the protein and ran it out on a Q Exactive and looked for Zika proteins. And didn't find any.

They expanded the search to a much more comprehensive database...and found some highly expressed viral proteins -- from a different virus!! The virus is called the bovine-like viral diarrhea virus (BVDV-like) and they show nice fragmentation spectra in the e5s.

As a minor comment -- I don't think that we could say that the Zika virus proteins aren't there. Brain matter is going to be super complex and separation on a 15cm column for 180minutes is not going to provide ultra-deep proteome coverage, but this is pretty interesting. If we think of lethal viral models that hijack host cells and then produce tons and tons of themselves -- you'd expect the Zika proteins to be at high abundance. Or at least I would. It is at least super weird that another virus appears to be running amuck -- in the brain -- in 3 different individuals!

Seriously interesting and I'm glad this paper appears to be getting a lot of attention!!

Can't get enough Orbitrap physics?

I needed to brush up on my Orbitrap physics recently. This review is EPIC. It is a little older, but..seriously...these authors couldn't make something so daunting any more clear than they have done here.

It is also open access (w00t!) here!

Drug target inspector! Informed info on your tumor from any -omics data set!

Wait? What?  I'm going to put this here cause I don't really have time to sort it out, but I'm really blown away by what I think I'm looking at here.

What it looks like? A brilliant data processing pipeline from a bunch seriously smart researchers in Europe.

There are bunches of those. Big deal.

But this one looks like a pipeline that takes multi-Omics workflows from whatever you can rapidly find out about a patient tumor -- with an output that is treatment recommendations!

Ummm...this is what EVERYONE in cancer has been working on. Right? This is DEFINITELY what we were trying to do at the NCI. This is what a lot of people I know are trying to do right now at the NCI...and JHU...and Sidney Kimmel...and..everywhere...

Why isn't this front page stuff all over the place?

The abstract states that they did several case tests and show that this thing works. Wait. What?

I need to do some digging. But I should probably do a bunch of things first that I'll get paid to do first...

You can find more about Drug Target Inspector at the tutorial resources here!

BioNSI -- FRIENDLY biological network simulator

There are some totally sweet and expensive pathway network tools out there AND there are a bunch of cool R scripts that can do all sorts of pathway and network analysis. The latter has the drawback of....well...being R scripts and the former have the drawback of not being free.

What are you going to do if you're not loaded with funds or free time?

Maybe you need CytoScape and the new BioNSI add-in software!

It is described here in JPR -- brand new this month!

Did I read it? NOOOPE. 1) It is behind a paywall and 2) The link to the software is in the abstract (and here!)

These awesome authors also provide us with some nice tutorials and easy sample data sets.

My recommendation:
1) Go to Java.com and upgrade your Java (chances are yours is out of date)
2) Download CytoScape here. 
3) Run the BioNSI.Jar file and the tool is in there.

Feed it some quantification data and see if it makes any sense out of it!

Set up your Orbitrap for microflow!

I saw an announcement for a seminar in my area next week that is called something like "Take Your Mass Spectrometry to the Ultimate Dimension of Supreme Amazingness with MICROFLOW." I may have exaggerated the title...a little... Then that got me to thinking that maybe everybody doesn't know about microflow? Sure seems like its a revolution to the vendor putting on the talk.  And maybe it is one of those cases where I just think everybody knows about something cause I've been doing it forever, so maybe I should put some resources together so I can reference it later?

What is microflow? That is the grey area between what is clearly nanoflow (nanoliters/minute) and what I've always called analytical flow (the flow level that HPLCs have been able to stably handle since before I was born)..say...50uL/min. Microflow is generally considered a few microliters per minute (1uL - 10uL/min)

I've always been a big fan of microflow rates and not only because I hate nanoLC but primarily cause I hate nanoLC. You get a big boost in sensitivity over analytical flow, but you don't have to do nanoLC!

Best part. Every Thermo mass spec I've ever used has been compatible with microflow LC. You may need to make a source adjustment, but you can go two ways with it.

Option 1: Smaller gauge ESI or HESI needle. If you want to use your orthogonal source (the old ESI or the newer HESI and HESI 2 sources) you can flow 1uL/min or whatever, but the stock needle is a little wide and it is hard to get great spray stability out of it at <10uL/min (proof? calibration! try getting that sucker to tune/calibrate at 1uL/min with the stock needle. You can probably eventually do it in positive mode, but it isn't easy).

The stock needle is 32 gauge. The low flow is 34 gauge

If you have a Fusion/Lumos/Endura or Quantiva, the low flow needle insert is Thermo part number: OPTON-30136

If you have a HESI for any other instrument the low flow needle is. As far as I can tell, this is the same exact needle used in the older ESI source as well: OPTON-53011

In both cases, these needles will set you back less than $500. And they're steel so they last a good long time.

Pop in the smaller needle (there are instructions here: PDF), make sure your LC can do that flow rate (or borrow one that can) and you're microflowing!

Option 2: Convert your nanosource to microflow!

This is easiest with the EasySpray (coincidence?) this set microspray emitter is part number ES792. You can find it online here. Just put on your column and pop it in. Did you know that your EasyNLC 1000 can do microflow rates? Sure can. But you have to use short gradients cause each pump is only 50uL. I'm pretty sure, don't quote me, that you can do up to 12uL/min. At 50/50 -- that is only an 8 minute run.

For the old nanospray source or the flex you'll have to do a little more work. New Objective, for example has steel emitters that go up to 50um at the tip. Since that page says "microflow workhorse" on it, that seems like the product to use these days from them. There used to be a cool worksheet on their page for plumbing things up, but I'd just get mixed up and call them and they'd walk me through any weird setup I was doing -- I bet that hasn't changed.

This link is to the PDF of a poster from Thermo people on doing microflow that shows some of the advantages.

Disclaimer: Ben doesn't really hate nanoLC, but he does dream of the day when sensitivity is high enough that we don't need to use it anymore. With each new generation of instrument he wonders if we've finally made it over that hump...and maybe we have?

DAPPLE 2 -- Homology-based PTM searches!

Some people out there aren't studying lab strains yeast or E.coli or nematodes of even ridiculously inbred mice. These weirdos are studying these things cause they cause diseases or just cause we don't know anything about them. A consequence of this aberrant behavior can be that their organism of interest hasn't been sequence (or...realistically at this point....sequenced, but not annotated). Think it is tough to assign the correct phosphorylation site to yeast? Try assigning it in an extremophile that somebody did a crappy next gen sequencing run on.

DAPPLE 2 is an attempt to help these people out and is a topic of this new paper in JPR. Why is it DAPPLE 2? Maybe cause if you just look for "Dapple" you just get these...

!!!!!  ERMAHGERD!!!!  The 2 is important -- unless you want to waste your pre-work coffee time flipping through puppy pictures rather than blogging...

I didn't finish this?  Actually, DAPPLE is an algorithm that has already existed. DAPPLE 2 is an improvement on this approach. DAPPLE2 draws on post translational motifs from 15 different databases.

Despite drawing on all of these resources it still ends up as FASTER than the original algorithm in their datasets!

If you're thinking "Great...another phosphorylation motif search tool..." I say to you -- ever heard of malonylation? I haven't!  It is one of the many PTM motifs that this tool can search. While most of the data out there is phosphorylation (for good reason) this group didn't forget that it is just one important PTM and there are other ones that might be what's up with your organism!  (Looks like there are at least 20 different PTMs in their table!)

Seriously a nice resource!  Want to check it out directly? Here is the link (did I mention it is web-based?!)
http://saphire.usask.ca/saphire/dapple2/

Concerned about how to search negative ETD spectra?

I realize that currently this is only a useful paper to a small subset of the people out there with mass spectrometers. Specifically, this probably is only useful to people who have hacked their LTQ Orbitraps with ETD and added in a CO2-based laser and wrote custom software for it. Currently.

What if you are one of those labs on the forefront of mass spectrometry with the skill to make these modifications and the intestinal fortitude to deal with your local FSE when there is clearly a

attached to your Orbitrap (I think it goes without saying that this invalidates your warranty), but you've got a bunch of MS/MS spectra you need to search?

HAHA!  Byonic has you covered. In this new paper at JPR which is (surprise!) a collaboration between the Coon lab and Protein Metrics, this group describes how you can apply Byonic to searching negative ETD spectra from such a device!

You know that stuff that is invisible to traditional shotgun proteomics (or even just gross low intensity?) well AI-NETD takes a serious whack at those spectra and returns serious levels of results.

So...about that currently thing....when do the rest of us get laser beams on our Orbitraps? Seems like a lot of people are working on or with such things...soon-ish? Please?

I'd like cytoskeletal remodeling -- ASAP1!

Coincidentally, this paper came up in conversation last week -- I didn't realize it was the paper until I got to the methods section though. Coincidence? Or is Ben reading too many papers?

The paper in question is this one from Pei-Wen Chen et al., in JBC a few months ago and it deals with figuring out what the Art GTPase-activating Protein, ASAP1 does in cytoskeletal remodeling.

Rapid background -- Cancer cells have totally whacked out cytoskeletal stuff. You can do really simple stains of just actin with colloidin or whatever and tell the cancer cells are a mess. People have been trying to figure out a pattern in the madness with all sorts of microscopy and things forever.  Actually, if you are interested this is a super solid open access review on the topic.

Great approaches to the cytoskeletal approach are 2 of my favorite lab things to do -- proteomics! and immunocytochemistry (ICC/IHC)

(thanks Atlas Antibodies for the picture!)

In this paper, they are focued on focal adhesions. This is where a bunch of actin builds up to have a ton of structural strength and is the central point of the remodeling (this can also be the starting point for a cell moving -- construct a focal adhesion and move the cell toward or away from it). Focal adhesions can be modelated by several players.

In this study, this group looks at a relative new player ASAP1 and how the activity of this protein might explain some what appeared to be randomness in this remodeling.

They do this by knocking down ASAP1 and by using fibronectin to drive remodeling with/without the protein. Nice ICC and nice LTQ proteomics confirms the active players. All in all, just a nice study out of the NIH that fills in a gap in the remodeling process that might allow some of the other puzzle pieces to fall into place!

Super in-depth analysis of FASP shows optimization is sample specific

Filter Aided Sample Prep (FASP) has been surprisingly controversial. Groups rapidly started pointing out limitations to the technique. Wow, I just did a quick check and I have posted at least 10 different papers on this blog where people have improved FASP in some way or another.

So...Jacek R. Wisniewski (who knows something about the topic, I've heard) went through two variations of FASP -- regular and MultiEnzyeDigested MED FASP -- and made possibly the definitive guide on the topic.

You can find it at JPR here.

What did he find out? That it might not be something as simple as --"Eureka! This is the perfect FASP protocol"

How well he did with each technique had a lot to do with what he loads and how much. Fortunately for us, however, he did all the work!

Personally, I think these findings are disappointing. We need to standardize our protocols from lab to lab if we're ever going to shake the "proteomics isn't reproducible" bologna that has shot down more than a few of the nice grants y'all are writing.

That's science, though! As much as I don't like these results it sure seems like Jacek has done a thorough job and this is quite convincing. Maybe we can circumvent this by optimizing FASP protocols for the pure discovery work and work on a universal sample prep method for getting this reproducibility monkey off our backs?

Integrins again? Is there anything they aren't involved in?

Man, these stupid integrins. It seems like if you dig deep enough they are involved in everything!

More evidence that these ridiculously complex sensor/activator things are something we should be considering? 

This solid paper that indicates how critical integrinB1 is in the aging process in mice. Normal integrin levels? Mouse that dunks like young Doctor J. Knock out the integrinB1? Mouse that dunks like older Doctor J.

Wait. Bad example.You get it, though. They also restore ItgB1 function (not in the good Doctor -- in an old mouse) and the mouse immediately does a keg stand (or something -- weird. no Google Images of a mouse doing a keg stand? Oh well...).

The paper then diverges off into looking at what ItgB1 is typically activated by (fibronectin) and do a bunch of nice western blots to look at 4 or 5 proteins downstream of ItgB1.  Their conclusions are that they should probably think about other integrins. Hmmm...I wonder how they might go about that....?  Wait!  I know how!

In this awesome paper a few years ago, this group developed a complete model system for studying downstream ItgB1 family signaling. They used SILAC and an Orbitrap Velos, and their heat maps are sick (seriously, the group in the paper I mentioned first have pretty western blots. Someone has either done a million blots in their career or they tried 50 times to get that blot right. Then you look at the heat maps in the Max Planck study....is this even science from the same planet...or century...?)


Seriously, we can EASILY identify/quantify virtually every known protein downstream of ItgB1. With the exception of some phosphorylation sites that are embedded in lysine-rich motifs and some kinases that require cytokine pulldowns this is a problem proteomics solved the crap out of 5 years ago when everyone was developing these awesome techniques (and kits) for applying proteomics to these central pathways --mostly for cancer. Got the tools and (hopefully) and easier problem to solve!

Spiked in controls to adjust TMT quan values!

Could we be overthinking how to adequately compensate for quantification compression in reporter ion quan data?

This study from Erik Ahrne (sorry, I don't know how to make the correct symbols above your name) et al., seems to think so, and they've got a simple solution to tell us about in JPR here!

In this work they take a step back and say...reporter ion quan compression? Maybe we should just recalibrate and compensate for it!  They do this by testing a bunch of different calibration standards -- finally ending up on a nice 6 protein mixture that they dilute out and spike into each channel.

Effectively they now have a calibration standard inside their runs. If they compare the ratios of what they get experimentally to what they know they spiked in -- BOOM!  -- they have an idea of the compression ratio that their mix suffers from.

For example -- If their 4:1 protein comes out of processing at 2.132: 1 then they can do some simple math to readjust their values back out.

It seems to work well, too!  They do some E.coli and a human cancer cell line extract in both cases they pull out evidence that it is helping. They also take a complex set and do an elaborate label free quan work up on the samples and show that adjusting the TMT gets them closer to the LFQ. To make this even more thorough, they show it helps when doing TMT with an Orbitrap Elite and with a QE HF (both of which, I might add, appear to have been ran by someone who knew what they were doing. Nice methods!)

They've already made the package to do these adjustments available in the SafeQuant R package. But they are quick to point out you could do this adjustment yourself in Excel.

Curious how their adjustment scheme compares to yours (you smart variance stabilization people, I'm looking at you...though I'm almost as curious about significance and/or S/N adjustments...) well, this topnotch group already posted this dataset on PRIDE -- it is PXD003346.

Need another reason to study glycans? Huge amount of data showing links with Aging!

Slightly relevant....these 80 YEAR OLD MARATHONERS!!!

There was a cool graph floating around ASMS this year (I suspect @ScientistSaba made it) that showed what people have been doing with their Orbitrap Fusions this year. One of the most common applications? Probably no surprise -- glycoproteomics. Seems like everybody is looking at sugars these days!

While doing my daily Scholar search to see if anyone has cured this aging crap, I happened across this really nice review from Yuri Muira and Tamao Endo that gives a break down of all the evidence that (surprise!) glycomics and glycoproteomics are valuable tools for studying what is going on behind the scenes.

It starts off by really defining glycomics and glycoproteomics but then delves right into evidence that aging work needs to put some time into this field. They review other people's work, but then preview some work they've done with a small cohort of people of ages 30-ish, 70-ish, and 110-ish (seriously!) that indicates some possible striking differences in global plasma glycan composition in the people that make it over 100. Not a cure, but a nice little review!

Combine bottom up and top down to determine protease substrates in mitochondria!

(Original image here, totally Open Commons and awesome!)

In our house there has been a lot of discussions on mitochondria recently. Fact check fail, retry. There has been lots of things said about mitochondria and, believe it or not, I do stop talking once in a while and listen.

Honestly, I forgot that they are there -- and its the one organelle I should know something about, cause they're basically stripped out bacteria that just do electron transport and make ATP. Turns out, though, that their dysfunction is linked to all sorts of different diseases (including maybe some nasty mental ones!)

In this awesome short communication from Alice Di Pierro et al., in this month's EuPA proteomics (wait. it is July already? ugh.)...last month's EuPA proteomics(!) this group demonstrates a really awesome method for determining the substrates of mitochondria.

What they use is a model where dopamine synthesis proceeds normally and one where it is deficient (see? brain stuff!) and they use both bottom up and top down proteomics to determine what is being used by the mitochondria under the 2 conditions.

Present in the top down AND bottom up analysis? Boom! Not a substrate!

Not present in the top down, but you can find peptides in it from bottom-up? The protein is being degraded as a substrate!  Heck, you could even use a de novo approach (they do) and figure out where the degraded proteins are being degraded at.

A nice short paper with a really clever approach to a biological problem. I'm sure there are other systems we could easily apply this smart approach to!  Bravo!

Tracking cancer mutation status in historic proteomic datasets!

(Image stolen from this paper)

p53 (or TP53) is a central regulator of just about everything. It is also mutated like crazy in cancer. There are regions of p53 that are so-called "hot spots" and are much more likely to be modified than others.

A super good review of the protein is this one from Bernard Leroy et al., (it is a couple of years old now).  Why am I rambling about this when it isn't new?  Honestly, I had a conversation the other day and it centered on how much of a cancer cell line's mutational status could be forcibly extracted from historic proteomics datasets.

Wait. I'll back up. In my extremely basic understanding of how cancer works -- A normal cell is going along just fine and it randomly picks up some DNA damage here and there. Normal consequence of life, metabolism and making new DNA. Typically the cell can use the simple doublechecking proteins and make fixes. If it is a big mistake the cell-cycle checkpoint proteins kick in and stop cell division while the damage is repaired. If it can't be repaired, then the cell is destroyed.

Stuff goes crazy when your checkpoint gene/proteins get messed up. p53 is intrinsic in this whole checkpoint thing. p53 gets messed up...and....now DNA damage that is picked up is copied into the next cell and you start seeing mutations all over the place!  The weird part here is that p53 looks pretty easy to mutate.

I made a quick summary from the Leroy paper and from COSMIC

These are cell lines from the NCI-59 panel that I selected almost at random (honestly, cause they were the first ones that finished downloading a few weeks ago). p53 is messed up in all of these lines except for MCF-7 and H460. In all the ones at the bottom, they have the same stupid mutation!

That site in yellow is an R instead of an H.

Enough background and back to the question!

Question:  Can I find out what the mutational status of p53 (and other important proteins, of course!) in a normal shotgun proteomics dataset?

Answer?  Hell yeah I can!! -- with a couple caveats.

Proof? Okay, so let's start out by going to the NCI-59 cell line repository here.  (Quick shoutout to Drs. Kuster, Meng, and Gholami for helping me out with some extra info on this fantastic resource!!!)

The original paper was in Cell a couple years ago here.

For the first run, I just took my normal Uniprot human database (that contained wild-type (WT) p53 and I added the R273H mutation. Cause I'm a resolution snob these days, I only went with the "Deep Proteomes" at first (these are Orbitrap Elite high-high datasets -- 24 fractions, I think, seriously nice dataset!)

This is what I get when I just run MCF-7 and U251 (MCF7 should be WT; U251 - mutant! See? Nice dataset (and I'm being lazy, this is just an old UniProt)

So...even in Uniprot, there are a lot of isoforms of this important protein, but only one peptide that corresponds uniquely to the R273H mutation.  See the weird stuff, though!??!  Where is the wild type?

This threw me for a loop. It isn't there. What? It has to have the WT protein, right?  Yeah, it definitely has to be there.

Probably just something weird, right? So--- let's go to the other WT strain!

Son of a fish.....same thing!

Lets go to the XICs!!!

Well, at least I'm not craaaazy.

That is one peptide that should be carried over from the WT strain and any of the mutations. We'd expect to detect it...unless we don't want the WT protein around either!

Yeah!  There shouldn't be any p53 around unless the cells are under stress (or the protein is mutated). If everything is cool, MdM2 should degrade it almost immediately.  Link to this here.

Man, I read way too many cancer papers tonight working on this.

One last side note, though. Remember the Proteomics Ruler?   If you can't find signal for any of the peptides from a protein -- at the MS1 XIC level ---

You're essentially dividing from zero. That is some loooow level stuff.

Wow. That was WAY too long.
1) Can you determine p53 mutational status? Heck yeah you can!  And I lucked out, cause p53 mutants seem to lead to overexpression and then its really easy to find the mutational site!
2) With the caveat that there is a dynamic range to proteomics, still.   (Hey! Anyone doing MCF-7 proteomics on a Lumos? I'd love to see if you can see these peptides!!)

FTMS booster!

Oookay...so I'm definitely going with a healthy dose of skepticism, but this seems a little awesome. I saw it at ASMS, but didn't get a chance to more than run by one of the posters in-between responsibilities.

This little box is supposed to be able to connect up to an Orbitrap (or LTQ-FT system!) and provide extra processing power(?) and alternate algorithms to convert the transient signal (the frequencies recorded by the Orbitrap) into mass.

The craziest part of the marketing info is this jewel. They show that if they run a Fusion system at 15k resolution and process the data with their device, that they can resolve the TMT10plex N/C reporters.  At 15k resolution.

That is a seriously big deal.

As far as I can tell only one paper has been peer-reviewed so far, and it is a rapid communication on an alternate Fourier transformation. I won't even bother downloading it cause its wouldn't help me, but here it is for you mathy people!

WREGEX -- Cancer mutation prediction!

Quick drop here on a resource I don't 100% have my mind wrapped around yet. Slow brain Saturday!

Wregex is a bioinformatics resource that has been around a couple of years, but didn't make a big splash at first.

Wregex 2.0 launched and showed application of the power of the interface and now people are paying attention!  In this new paper, researchers show that they can go through the COSMIC cancer mutation database and start to make sense of motifs that are changing throughout the proteome.

You can access the Wregex interface directly here!

You'll also find some more pop-sci articles leading you to it with a quick Google search, but I'm not going to link them. The confusion I'm having is partially low coffee levels and partially that the original article I read might have stretched the results a good bit. Neat resource, nonetheless!