Great (and timely!) review on studying protein-DNA interactions!

 

I suspect that if you've got a mass spec someone is going to come by soon (if they haven't already) and they're gonna be asking about protein-DNA/protein-RNA, glyco-RNA interactions. There is considerable excitement in all of these areas (Thermo is recruiting a postdoc to develop tools for Proteome Discoverer in Bremen, or was...I can't find the link, but it sounded really cool). There is an open postdoc across the street here for that as well.

For a very timely review on the first things in that list, I suggest this very thorough new paper (I hadn't heard of 3/4 of these).

When someone comes by asking about this stuff, nod a lot, pretend you've got another pressing meeting coming up and get back to them after consulting this great paper. 

Two weeks till ASMS Abstract cutoff! And SCP2021 program is up!

 

Hey everybody! Hate to interrrupt your summer breaks, but the ASMS abstract deadline is 2 WEEKS AWAY! Get those abstract in so we can hang out in (not as beautiful as Baltimore, the world's greatest city, but only a short drive away) PHILADELPHIA! 

There aren't hospitality suites.

There is something EVEN better! 

The 4 Seasons LandScaping Company (you can't tell me you don't want to go)!

Relive the peak of incompetence that my neighbors dream to return of (for real, I live near a lot of scary nutjobs).

Before that, though, Single Cell Proteomics 2021! August 18-21!

The schedule just posted! You can check it out here. 

Random walk phosphopeptide data analysis!

 

I've gotten excited more than a few times in the past when I came across what might be a powerful way to make sense of phosphopeptide data. Is this it? If nothing else, the output looks gorgeous (haven't tried it myself yet, but I'm optimistic!). 

The math is intimidating. I felt better about reading the paper from the HTML version so I didn't have to look at letters that make more sense on the front of big houses near college campuses. 

What I do get is that it uses random walk, and I absolutely know what that is. 

All this stuff is made in R and you can get it from Github here! 

Eclipse + FAIMS + 20 nanoliter/minute + NanoPots!

 

I can't remember if I posted on a preprint of this study or if I've just read it so many times that I thought I did. 

How far can you push an Orbitrap Eclipse for direct single cell (no SCoPE-MS or boost or DIA) just DDA? This might be a good answer! 

One normal-sized human cell, prepared with NanoPots, ran at 20 nanoliter/minute (they used a Dionex RSLC 3000 at 250 nL/min and split the flow lower to get it to 20 nL/min). There are some really interesting comparisons here. Eclipse, so ion trap MS/MS or Orbitrap MS/MS? FAIMS on vs FAIMS off? What fill times? What AGC targets? 

The total gradient time appears to be around 150min, so not nearly as bad as I would have assumed to get to a flowrate that low. A custom 50cm column is used, I think, but I forget the details. I don't believe they used match between runs to get to their total numbers. Data processing was in Proteome Discoverer. A great reference for this field of single cell proteomics that is 

(Zoolander quote moratorium is over! I get 4 more before it kicks in again)

Weird Forbes article on proteomics?!?!

 

I go to the beach for a couple of days and come back to what?  Some weird museum mass spectrometer(?) on the front of Forbes?

If you didn't know Forbes appears to be a magazine for business people. You can check out the article here. If Windows has recently updated for you there is probably some new internet browser on your computer called "Edgey" or something and it doesn't have ad blockers installed on it. You can use that to view the article!

Thanks to Twitter, we've also been able to identify the mass spectrometer above. It is a MicroMass (pre-dates me, and I'm hella old) that was set up as above by some genomics researchers to demonstrate that proteomics people are clearly insane and the safe bet is still studying 30,000 human genes or transcripts, despite their general lack of biological relevance. 

To the people outside of proteomics who are increasingly stumbling on this bizarre blog, our instruments are not nightmarish setups of weird wires and magnifying glasses shown above -- our cutting edge stuff is professionally designed, polished, and ready for prime time -- some of the newest examples look like this (the one in the middle is in our lab and sometimes people come by to just look at it, because proteomics stuff used to look like the picture in Forbes and, while the box shouldn't matter, it does suggest that maybe proteomics has grown up and might be worth a second look, particularly if in the 1970s or whatever, Frankenstein's mass spec didn't get them the data they wanted). 

Forbes identifies proteomics as the future of medicine??? HOLY COW. Took freaking long enough for someone to goshdarned figure it out. So much money goes into genomics that they have been muddying the water for years. Lots of scientists don't know that there is basically NO correlation between the abundance of a transcript (as measured by things like RNASeq) and the abundance of the protein that actually does the work in the cell....I should get T-shirts printed....

While I'm super excited by the examples the author brings up, like the incredible work by Bateman Lab and collaborators that can detect Alzheimer's proteins 20 freaking years before symptoms develop, I do find this paragraph puzzling: 

I don't know what slow people they were talking to, but I'd go back to industry or back to washing dishes at Big Frank's if I could only get shreds of protein data in 30 hours. Again, I'm hella old. That's way to slow. For proteomics outsiders, using an instrument released in 2012, we can get high depth proteomics (8,000 or so most abundant human proteins and post-translational modifications) on up to 16 human or patient samples in about 24 hours. The instrument in our lab pictured above? Can do twice that many/day with around 1% of the starting material (not even an exaggeration. underestimation, actually) . At lower depth proteomics TODAY is much much much faster. 

While I'm very excited to see Proteomics get mentioned and to see some really promising new companies get funded, I am also seeing some unproven tech generating alarming amounts of money on very little data. I guess this is how it works, but I'm glad I've got a good seat for the show! 

MONTE -- Prep a tumor for basically everything!

 

....so...what if you were tired of wasting tumor samples and wanted to think reeeeeaaaaally hard about how to do the sample prep so you could really maximize everything you could learn about a single tumor sample? 

Welcome to Monte! 

This one!

 

TMTPro Complementary Ion Search SOFTWARE!!

 

Holy cow, y'all. This paper is super cool. 

However, the coolest part of this might actually be --- 

This frickin' GitHub!! 

An awesome review on why people want us to find HLA peptides!

 

MHC peptides (if you're talking about anything) or HLA peptides (H stands for human) or neo-antigens or whatever the next person will call the awful nontryptic low abundance grossness they want to bring you are really super important.

Why? And what are they again? And how has it changed since the last time you thought you knew what people wanted you to do? 

A bunch of people in Boston got together and assembled pretty figures and a clear breakdown for why you should be inspired to work on these awful things! 

Where did all my scans go? Solving the scan averaging mystery on the TIMSTOFs!

This post has been edited on 7/21/2021 thanks to clarifications from the vendor and new clarifications will be worked into the software (that I've helped with, w00t w00t! to make this more clear in the future). I've also removed some words like "dummy". 

This topic came up (again) for me on a call with an amazing mass spectrometrist who is....ummm... let's go with ....underwhelmed... with a recent TIMSTOF acquisition, so I'll put my solution to this mystery here for other people to reference. 

Mystery: 

I lowered my peptide concentration on column and my number of MS/MS scans dropped dramatically. 

Good example, you're expecting your normal 80 scans/second, but you get...8....

Probably the solution! 

Target intensity and intensity threshold

If you'd previously used a Thermo, SCIEX, Waters, or Agilent instrument for data dependent acquisition (DDA/IDA) you might be under the misconception of something like: 

Target intensity is the ideal intensity of an ion that you'd like to fragment for MS2

and maybe 

Intensity threshold is a cutoff where you wouldn't fragment anything with an intensity below that number. (Edit, 7/21/21, the threshold cutoff does work as a threshold cutoff, but it also has the functionality described below) 

On a TIMSTOF it means something else. 

What does it mean? It's easier if I draw it, but it is a secret formula for how many times you'll average or sum data to get an MS2 spectra! Duh. 

Please note that the estimates I came up with are not entirely accurate. For a tool that will correctly estimate the number of MS2 scans summed, please check out this nice script from Weibke Timm on my Github here. 

The numbers that go in the boxes is the x-axis. The y-axis is how many scans will be averaged to make that one MS2 spectra based on it's intensity. At the intensity threshold (or below) each MS2 is a sum or average of 10 MS2 spectra. 

Imagine that you have an ion with a 4e3 intensity -- the MS2 spectra for that will be the sum of 7 MS2 spectra. If you have an ion at 10,000 counts of above, then it is not averaged. Each MS2 scan is the sum of just one MS2 scan. 

Check out what happens if I change the target intensity to 50,000 (which might be what your default setting is). 

Basically any ion that is under 10,000 counts is averaged at least 8 times!! 

Makes perfect sense, right? 

For very low intensity ions, you sum a bunch of MS2 spectra which boosts their total singal. If you don't know you're doing it, though, you could be thinking you purchased a ceiling disrupting system that isn't as fast as your Q Exactive Classic. Do you need to sum or average 8 scans at 10,000 counts to get one MS2? I guess it depends on the experiment. However, you DEFINITELY don't want to be suprised because you changed a setting you thought was unrelated and drop your number of MS2s by 8-fold! 

Just in case you'd find it useful, I put my TIMSTOFsecretscanaveragingestimatordrawerthing on my Google drive here. It's not anything smart, but if you put your intensity threshold and target intensity in the boxes it will plot across and you can estimate how many scans you are averaging for each ion. I suspect other maths go into it, but I at least find it useful when we're titrating down in the concentration of peptides on column. 

THE method for characterization of small proteoforms by LCMS!

 

I really like this new methods chapter from this group! 

Sure, KRAS is a small protein (17kDa?) but it's got a ton of different isoforms and some really terrible PTMs (and, arguably, the most important region has 74 lysines in the last 41 amino acids (or something). This chapter walks you through ALL the steps to enrich and analyze a little protein and it's important proteoforms. From the complete instrument settings (they use a QE HF + BioPharma, but on a protein this size, you can use just about anything with minor adjustments) through step-by-step analysis with the free ProSite Lite software (and XCalibur), there aren't room for too many questions. 

TMA derivatization (and microwavification) for histones?

 

Moving fast and maybe just leaving this here for myself to actually read later, but this looks kind of crazy/amazing. 

I missed London Proteomics this week, but here are two great studies that were covered!

 

Friday was our first run trying nPoP and which required an early start and missing London Proteomics which was all about super cool drug discovery stuff. Fortunately, the site links to the most relevant papers the speakers covered (though, I assume we missed some top secret new advances.)

LPDG does have a YouTube channel, and there are a bunch of great talks recorded that you can find here. 

This week featured Ilaria Piazza and I've talked about here cool chemoproteomics stuff, the study linked is this recent one. 

The second talk was Patrick Zanon and included words in the title that I didn't know until I pulled up this really cool new preprint. 

It describes going hunting for small molecule covalent inhibitors that don't just mess with cysteines! Before some stupid virus derailed the world, the hottest drugs in the whole world were covalent inhibitors of the "undruggable target" KRAS. (KRAS is messed up in a huge percentage of tumors, and it's generally really bad when it's involved). If you can covalently inhibit a protein this terrible, what could you do with other drugs of this class? 

ASMS 2021 Vendor Wrapup for Proteomics Stuff?

This post has been edited, because I realized later that some of this was me being kind of a jerk and I'm going to blame it on a really dumb injury I got being awesome that derailed my summer. 

Okay, this might take some time, because!! WOW!! what an ASMS hardware rollout! 

If I'm not covering your product, I apologize, its been a long year (and ASMS starts on Halloween!)

There were some seriously big vendor rollouts on the hardware front which got me to thinking ---

 From this Tweet, I learned a few thing. 

1) That there are people out there who didn't realize they were being eccentric with their low signal mediocre resolution data. 😇

2) It was kind of a tie between software and your relationship with your sales and support team. Which...probably doesn't bode well for Thermo since they recently got rid of their subject matter expert sales teams for their products in the US. If you weren't aware, they now sell by geography. So...your local rep who got her/his PhD from the famous proteomics lab? He/she might be selling ICP-OES systems now. Strategery from the company that can't seem to find a way to give up market share in proteomics fast enough to keep their executives happy! 

VENDOR LAUNCH 1: BRUKER! 

Bruker's launch was tied for the longest (3 days, thank goodness for how much time off we get in the USA) and was centered on the "TIMSTOF SCP"

This smaller TIMSTOF was the result of a close collaboration with Matthias Mann's lab and based around the preprint from last May. [Edited jerkness]

Another upside of this event was the TIMSTOF Pro X! This is a new instrument and/or field upgrade for TIMSTOF Pros! The price didn't seem absurd for current users and it's always cool to have a field upgrade for a 10 foot tall 2,000 pound box!

Legit, I think both of these things are totally cool, my job is to be a critic, I think 

ASMS Launch 2 and 2.5

The next week was coinciding launches by Waters and the first of 3 days of Thermo! 

Waters! 

I've been asked by multiple people "wow, you seem really pumped about this one" and I am from a theoretical standpoint. I'm extremely clear in my "mass spec physics taught by a dumb person" slide deck that you can't get above 70,000 resolution on a Time of Flight instrument. The vacuum on the flight tube just becomes far too long to make any sense at all.

Waters has a MALDI/DESI-TOF that can hit 200,000 resolution against the whole goshdarned mass range. Speed? About 10 scans/second. 

If you're thinking "my Orbitrap Fusion/Exploris/can get 480,000 resolution" let's stop for a second

1) How much time does that take? I don't feel like doing math, but it's probably about a second. (You can download my calculator here)

2) What about resolution degradation across a mass range? What? 

Okay, so there are a bunch of secret rules in mass spectrometry vendors that they must stick to. I can't tell you all of them, but:

1) The compounds that you are provided for calibration must be the stupidest thing they can come up with. A peptide that will only singly charge and will rapidly oxidize? PERFECT! A polymer that will stick in your system until the fucking end of goddamned time and will always affect your sensitivity? BINGO! 

2) Vendors can pick any one of these stupid inconvenient molecules and use that for the point where they provide their mass accuracy cutoff. As long as that molecule hurts the end user, it's fair game. 

On Orbitrap instruments, the resolution DECREASES as m/z INCREASES. Thermo, therefore specs their instruments on the lowest molecule they can get away with (which, to be fair, they use 200, if they really wanted to cheat, they'd go to 40 m/z where the resolutions is insane!) 

On TOF instruments they generally spec on that polymer you'll never ever get out of your system (acetone helps) and they aim for 1222 or maybe 922) and resolution slips (but not to the same level) as m/z decreases. 

For real, if you're doing stable isotope labeling (heavy glucose/glutamine incorporation, for example) on an Orbitrap) around 800 m/z you're out of luck. At max resolution (if you aren't running the 1M option) your heavy ATPs are all mixed up because your resolution has fallen off a cliff. You can't tell that heavy N from heavy C. That's a huge deal for metabolism researchers. 

So...200,000 resolution is a big deal to anyone in the medium mass molecule range who needs to resolve nitrogen from carbon isotopes. And 10Hz? That's fast. Yes, right now it's just MALDI and DESI, but how does DESI work? The last 3 letters are ESI! I'd be shocked if Waters doesn't have an LCMS super high resolution TOF out soon. I'd volunteer to test it! 

THERMO!

Ummm....okay...so due to the preprinting time of a really cool study from some ultra marathoning dude with who has great taste in high pressure turbochargers in the Seattle area, I think a lot of people were expecting somethig really super ultra cool for ASMS. 

What did we get? An ultra expensive metabolomics unit and a new FAIMS unit! 

(Again, my job is to be a critic. Who hired me, again? That's right! Nobody! Whassssuppp?)

Jokes aside, the FAIMS is super cool. 

It can do high flow without you having to hack it to do high flow yourself! And it's higher resolution or something. I don't have an instrument that it will go on right now, so I didn't pay attention. Again, anything that will add more capabilities to a currently existing instrument is awesome and there are tons of Thermo boxes out there with the next generation ion source that can get much cleaner data by tacking one of these awesome things on. 

And since this is the Proteomics blog and no one has discovered the hundreds of posts I've made on the Metabolomics blog, I'll move fast on this one. The ID-X (which I love) is a Fusion 1 that has been retarded (not in the insensitive way, in the way tractor trailers slow themselves in the Rockies way) do only do metabolomics, unless you've got 2 minutes and 15 seconds and a basic understanding of how to use a Windows computer to unlock it. The new instrument is based on the Eclipse and I bet it takes longer to release the brakes and make it an Eclipse. There is more intelligent acquisition software for both metabolomics and the small molecule biopharma community.  All of which does seem really impressive. 

SCIEX

You'd be fair if you said I've been "uncharitable" or "an absolute jerk" about SCIEX hardware over the years. For real, I have been. I started my career on ABI/SCIEX instruments and until I used a Q Exactive the 3200/4000 QTrap was my favorite instrument I'd ever used. I don't know what happened because from the 4000 QTrap onward all I ever saw was mediocre improvemetns on those instruments in difference colorss and medium resolution crazy expensive QTOFs and an overpaid marketing department (for real, why aren't they doing the NBA playoffs, not selling analytical instruments. As an aside, during this year's playoffs the NBA will interrupt the actual game to show a commercial about how you should be watching the NBA playoffs [for real, that's continuing to happen].) 

But this is something entirely different. The TIMSTOF is exciting because Bruker figured out how to accumulate ions prior to sending them into a TOF. Bruker has had a TOF for years that can hit QE level proteomic coverage, you just crank up your injections 10-fold. With the TIMS acquisition, you could get speed AND sensitivity. And this is where a ZenoTrap is similar. 

Actually, I think I covered this better in 140 (280?) characters during the event:

The new SCIEX instrument can acquire off the quadrupole (and the quad specs are legit. 0.4Da isolation in high res mode! they do know something about making good quads over there) and the ions can accumulate in the ZenoTrap before being fired into the TOF. Numbers from 4 really good speakers with real data? Looks like 5-20x more signal depending on the molecule.

In addition, there is a collision cell that is two 1 tesla magnets opposed. This (somehow! wtf?) induces a very democratic fragmentation similar to ETD and ECD...with very little decrease in scan speed! Birgit Schilling showed some great PTM fragment spectra to back this up. Think about how slow your ETD or ECD fragmentation is. You've got to inject your reagent and then allow the reaction to proceed, THEN scan your fragments. 50-100 ms reaction time is common. Not including the scan acquisition time, you're at tops 10-20 scans/second. Realistically about 5-10, max. This box can get around 100 EAD fragmentation scans.

I'm out of time so I'm going to just leave this here. I didn't catch the Agilent launch live and I will follow up on that one later, but I think it was small molecule IMS focused. And there were some other launches, but with this out of the way -- HALLOWEEN ASMS IN PHILLY should be just research focused, right?!??

A couple hours until the final ASMS vendor reveal!

 

I don't know anything about anything, of course, but the final big ASMS hardware reveal (that I don't know about) is at 11am EST and....umm....you may not want to miss it. Whatever this top secret thing is might be the thing I'm most excited about. 

Don't be too grossed out about how much they spent on the video editing. There is real substance behind it. 

You can log in here at 11am EST. 

Serum proteomics of a lot of old dudes over a 12 year period!

 

This stats heavy paper takes a look at serum proteome changes correlated with different negative effects of getting older in a population of men 64 and older. 

Stats are ridiculously critical when you're looking at so many variables.

...how are you tossing these awesome outliers...?

I'm not qualified to really evaluate the downstream interpretation, but it seems solid and thoughtful. The upstream, however, was performed by depletion columns and using one of those giant Agilent time of flight instruments that have the ion mobility cell in the middle and the depth of coverage looks solid. 

I'm assuming they'll follow up with an analysis of elderly females shortly. 

Constant levels of KPR4 (at least in Arabidopsis) maintains cellular size!

 

I spend a lot of time these days thinking about how large human cells are and what their relative protein contents are. A great reference, of course, is the original Proteomics Ruler paper. 

I'll be honest, it never occurred to me to ask questions like.why is a human cheek cell 10x wider than a human red blood cell? This group did. 

Even if you hate arabidopsis, I recommend just looking at the pretty pictures in this study. They find a really interesting system where a protein called KPR4 maintains a constant concentration from a cell before and after it divides. It does this by some relationship with histones that I don't fully understand. Being arabidopsis poeple, they of course mess with this gene and can back up their hypotheses! 

glycosylated RNA (glycoRNAs) and tools to help identify them in LCMS data!

 

I was kicking around the idea of submitting a formal review on this topic, but I'm not sure I have enough data for more than a really cool blog post. If you do take this and write up a paper feel free to acknowledge me. I won't object. 

If you haven't seen this paper, you should.  This study presents compelling evidence of an entirely new class of molecules that we had zero idea were even around. The ramifications of this are at the level of text-book-altering. Glycosylated short RNAs sticking on the surface of cells doing -- presumably -- super important things. The initial study only identifies a few and they appear to be annotated as: 

"Non coding RNA" -- which means, they don't appear to make proteins. Why are they there? No idea. Till now. (Kinda).

I just realized that picture above from the PDF cuts off 5 of the author names. Pedro, Benjamin, Alex, Benson and Karim deserve to have their names shown in the PDF. Get your act together, ElfSeverer. Fixed it. 

Without running this out forever, these authors did some really innovative labeling and RNA stuff that I'm sure makes sense to RNA people. And these cool molecules disappear when you treat with something that cleaves RNA or cleaves sugars. They also did some top notch LCMS work. You can find all their RNA data on public repositories, but I can't find the LCMS files. It was obviously something that was secondary to their goals. 

It is not, however, secondary to my goals. And I bet that there are a whole bunch of people weird enough to read a proteomics blog that don't know that there are great tools out there for looking at RNA data by LCMS. There are, in fact, even SEARCH ENGINES and a couple of them are in formats that you already know how to use. 

A couple of things real fast, though. 

1) Nucleotides don't like to ionize in positive mode. Neither do glycans. However at a certain size of a molecule you can pretty much stuff a proton on it somewhere, but the signal might not be great. If you haven't calibrated your instrument in negative mode since installation, you might be operating at a handicap. 

2) Nucleotides LOVE to fragment. No joke. Check this out. 

I highlighted it but it's from this amazing recent study 

See what I highlighted above?  You know what that means, right?!?!?

No, not popcorn time....geez.....it just rhymes....

What it means is that the tools are in the friendly, open, ultrapowerful, free...

OpenMS! I was using 2.4(?) for intact protein work and I had to upgrade to 2.5 in order to use the RNA sequencing tool that this team used in this study (NASE). Honestly, this is probably the best tool for the job today from an automated standpoint, but it definitely isn't the ONLY tool for the job. If you use OpenMS, you're set, though! 

My bias toward using Proteome Discoverer is well established by now. So the first thing I tried was messing with the settings in the OpenMS community nodes RNxPL! You can get those here. 

They're from an older study by the OpenMS team where they used UV to crosslink RNA to proteins and then tryptically digested them to figure out what RNA is interacting with what proteins. Super cool workflow that I have always kept in my back pocket for conversations with people interested in RNA-protein interactions. It's hard to see in the screenshot above, but there are these extra yellow/green lines. What are those? They're nucleotide diagnostic ions!! No joke, this tool is super cool and really easy to use, and it's got amazing visualization capabilities. My only issue with it at all is that the diagnostic ion mass accuracy is a little wide and I can't figure out how to change it.

Please note, it only works in PD 2.0 and PD 2.1. You can always go to the FlexNet and get an older version. They're easy to install and run. 

Want a stand-alone executable with a bunch of power? You should check out RAMM! The RNA Mod Mapper. It is one of many tools for studying RNA by mass spectrometry that you can get here.  You can go down a complete rabbit hole of nucleotide mass spec work from the Limbach group that will run you back to some of the biggest names in mass spec and chemistry that he's worked with over the years. He postdoc'ed with some guy at Utah who's name comes up in undergrad chemistry.  This site is an absolute gold mine. 

What if you just want to do some manual exploration? For example.....wait.....we did some weird shearing experiments of growing cells one time...right...?...I can't remember exactly why but we wanted stuff off the surface of cells without killing them. Still have those RAW files? Just curious if you see an MS/MS spectra with a HexNaC oxonium ion and a nucleotide fragment ion or 6? 

Or...just entirely new to RNAs and what they are or how they might fragment? ARIADNE time! 

Paper link! 

AMAZING Ariadne web resource! 

If you're using Xcalibur, I will warn you that it is a little frustrating looking for multiple diagnostic fragment ions. 

My recommendation is to make multiple overlapping ranges that are just filtered on MS2. (See below)

To do this, activate any MS2 spectra and then delete out the information. Then hit OKAY. It will then activate the filter that it doesn't want to that is only for MS2 spectra. Then you can put in your target ion masses. Once you have one done, you can highlight your first BasePeak (right below "Type") and then if you checkmark another box, then it will copy those settings. All you have to do is repeat and type in multiple diagnostic ion masses. In the example above, the 306.0491 fragment mass is pretty rare, the second ion (I think I used a HexNaC fragment) is much more common, but at 17.01 minutes I've got an MS/MS spectra with each within a 10ppm mass tolerance.

Is it a glycoRNA? No idea, but it might be worth trying copying that spectra out as an MGF and putting it into the RNA ModMapper! 

Ariadne isn't the only web based resource for modified RNA masses. It's just got the best color scheme. Another amazing resource is....

which you can access directly here! 

I can keep going, probably, but I should probably work on other stuff. 

One thing I'm currently hunting is SOS. If nothing else because the interface looks super cool. 

You can read about it here. 

See, I found a ton of cool stuff, but probably not enough for more than a fun 30 minute blog post. And this really does just look like the tip of an iceberg. 

OH! I almost forgot! 

Why am I even thinking about these to begin with? RNA is totally amenable to separation with C-18. Waters has a 90+ page application manual for studying oligonucleotides by LC and LCMS. They use a slightly different BEH C-18 column, and negative mode for most things. A direct download for the Waters PDF manual is here. 

What I'm thinking is that there are lots of situation where we may have already accidentally have acquired data on glycoRNAs or RNAglycans and they're just hanging around in the background of our data. How much of the "proteome dark matter" could be linked to this? A bunch? Who knows?  I don't use nucleases when I prep my shotgun proteomics samples.