More improvements for MSAmanda -- for all operating systems!

MSAmanda has continued to improve, and if you haven't takend a look at this free search tool in a while now might be the time to take another look. Check out a short summary here!

For people using Macintoshes there aren't exactly a ton of options for proteomics. You can say the same for Linux probably unless you are adept at pulling tools from Github and figuring out what steps the developer thought you were smart enough to know about without them telling you. 

Other highlights include more compatibility with file types recommended by the Proteomics Standards Initiative which must be composed of the most tolerant people who have ever lived on earth. Most normal people after 1 year of trying to get proteomics to standardize anything: 

They've been coming up with ideas for almost 20 years! 

Proteomics needs more spectral library formats!

 At both the conveniently overlapping USHUPO and ABRF a couple weeks ago a big story was the emerging new alternative proteomics techniques. Illumina is getting into the game and is chasing the SOMASCAM technology to see who can be the fastest to accurately quantify 1,500 proteins in human samples. 

Four new companies launched last year alone raising huge amounts of money with basically the same pitch "we want to be the Illumina of proteomics", which probably led to Illumina wondering why it couldn't be the "Illumina of proteomics" too. Google the term in quotation marks. You'll find them and their huge successful investment raises.

The outside world is excited and ready to invest in proteomics and it's becoming readily apparent that LCMS is not part of the conversation. Could someone raise anywhere near that kind of investment capital on a pitch based on LCMS? No way. If you take a step outside our little community spin around in place 3 times and look back in you can probably see why the scientific community is fatigued with us and all the dumb shit we spend our time on. 

For example: I think that a substantial percentage of people in the field right now are spending their time trying to come up with completely new and completely incompatible spectral library formats. Is that what you're planning to do today?

Why do we need a tool like EncyclopeDIA to have to converters for 7 different spectral library formats? Why is that not even enough?

I downloaded the files from a new study from a single word journal this morning to see the results for myself and I'm absolutely fucking thrilled to see a new spectral library format this morning. Even Pinnacle, which can natively load practically any format of MS data and has options for accepting a scrollable list of input formats (did you know that some ultralarge biopharma companies have their own internal spectral library formats? they do, because we've all absorbed too much acetonitrile through our skin and it has done something awful to our brains. I know because Pinnacle has the option to accept those as well on it's pulldown list of options for input) just closes when I try to feed it this amazing new spectral library format. I'm sure that OptyTech could fix that for me today, but why should they have to? 

When you apply for your next grant and you're beaten by the genomics core across town because they can now use their NovaSeq to quantify 1,500 proteins, don't be bitter. 

Go back to your lab and get back to working on a completely new and unnecessary way to extract proteins from your cell types that we already have 15 ways to effectively work with. Alternate between 100mM TEAB for resuspending your trypsin today and swap over to 50mM AmBiC on Friday, heck, mess with the ratios of protein to trypsin while you're at it. Tinker with that gradient to get that one extra albumin peptide you've always wanted to see in your global runs, you know you want to. Hell, put a grad student on making an entirely new spectral library format. We probably don't have enough anyway. 

Just keep in mind that every step along the way we have done basically everything we could think of to make proteomics inaccessible to the greater scientific community and make it as challenging to reproduce our results as we possibly could. If Illumina pulls off 3,000 protein identifications in their next generation of technology as they have promised, we'll be lucky if LCMS proteomics exists anywhere outside of Cambridge and Munich, because by and large the scientific community is tired of our circular tail-biting craziness. And they should be. 

Mesh -- select and fragment multiple charge states of intact proteins -- in real time!

 And the winner for understated study so far for 2022 goes to.....

Man, this is why I'm still here doing this stuff, I guess. From the title and abstract alone, I bet you probably didn't want to read this. Why would you? 

Well, you can get a program developed for this study from Github here that will allow you to operate your Q Exactive system with some new super powers! 

MetaDrive? What's that do? Well, it's nothing to yell about really, it allows you to look at intact proteins on the fly and deconvolute them and then it selects multiple precursors for your intact protein (like targeted multiplex quantification) and will hit them with stepped CE allowing you to get massively more signal on your intact proteins. That's all. 

When you do intact proteins on an Orbitrap and select an ion for fragmentation the best case scenario is that it looks like this and you selected that one charge state for your MS/MS fragmentation. 

You're only getting a fraction of the total protein signal for fragmentation. It's a large part of the reason that MS/MS scans of proteins look so lousy. 

What if when this signal came off your QE, there was a program sitting there that was smart enough to deconvolute that protein and recognize multiple intense charge states? Keep in mind that the example above is a pure myoglobin standard. Top down doesn't look like that normally because you'll have multiple protein envelopes overlapping. 

Just imagine if you were able to select even these three below? You've effectively tripled your protein signal for fragmentation! 

Even better, since the Orbitrap is by far the slowest part of this process, there may be effectively no increase in the amount of time each cycle takes (like BoxCar, you're accumulating multiple isolated ion windows, holding them and then scanning, but here you can fragment them!) 

You know, not a big deal. The authors might have understated how freaking cool this is because they do note that the real time calculations are a little slow. They're working on implementing the screaming fast FlashDeconV program into this to help alleviate the bottleneck. 

The files are up on PRIDE, but still locked. I already put in a request to open them up if you want them! 

MS2Go Reports for MSFragger open search results!

 I had a couple of Zoomie Team things this week where the conversations landed on MSFragger. Part of that is due to the fact that it is currently the only free way to process a big TIMMYTOF file in reasonable time. (As an aside we had OmicsPCs build us a new box with a water cooled Ryzen 5950X for this purpose. When we ordered it in December I think it was the fastest desktop CPU in the world. Probably isn't now, but we're getting MSFragger searches completed in about 1/3 the time this paper described.)

If you're using FragPipe much, you're probably familiar with this box.

And if you get distracted because, for example, you have an abnormally large 10 week old human who just discovered he has hands and his favorite thing to do when you look away for 10 seconds is punch himself in his own eyeballs, you might forget which peptide.tsv you have open. In this example you should close them all and go try and show him the dozens of frogs that just came out of hibernation that are having a loud jumping and splashing party. Oh. Punching yourself in the face is more interesting than frogs climbing up an 8 foot rock wall just to jump off into a little pond? Cool. 

Okay, but the real challenge people point out is that it can be a little challenging to get from your protein to the peptide and PSM level evidence with all the sheets FragPipe generates. 

Would a single output sheet like this help? 

A single sheet with the proteins....

...and coverage map...

....and your open search reports all hyperlinked together and sorted out with premade filters? 

There are some steps to this, but nothing that will cost you any money and you won't get all the superpowers that FragPipe has, but if you're just searching DDA data with MSFragger in Open or Closed search you probably won't notice (if you've got something other than .RAW you'll need to convert it to a universal format first.)

You'll need PD or a PD demo version.

I'll do it on this one. 

And you'll need MS2Go (it says it only works in versions up to PD 2.3, but it totally works in 2.4, so I assume 2.5 will be just fine as well.) 

I made a tutorial for installing MSFragger in PD a while back you can find that here and I think I put in links to better instructions from their lab somewhere there as well.

MS2Go is super simple. Just point it at your .pdresult file.

And export your condensed report. If you didn't use Feature based quan you'll see this warning that it couldn't find it. 

Obviously, this isn't a solution for everyone or every project, but if you or people you work with are used to seeing this kind of a condensed output it will save you a ton of time over assembling this from the FragPipe output yourself! 

Want to learn the annoying field of single cell proteomics?

Are you tired of hearing the words "single cell"? 

Not yet? Okay, so you should totally try getting a single cell into the bottom of a 96-well plate, or floating on the surface of a tiny droplet on a glass slide (NAnOPot) for yourself, and then successfully digest that cell and get it into a mass spec.

Don't know how? There are 2 great meetings coming up! 

Chronologically, the first one is only 1 month away!  

Busy in April? 

ASMS has been moved to the fall, so what about the Boston meeting in June? 

Our field lost a great scientist -- and an even better person.

Wow, is this one hard to write. If you weren't aware, Michael Bereman of NC State passed away last week. As an ASMS member you might remember Michael receiving one of the awards that are given to extraordinary young researchers just a few years ago (2015). He was brilliant and far too young for me to be writing this.

Michael's stuff has been on this blog a lot. AutoQC, SProCoP and other tools and we reused the amazing CSF proteomics files that his lab generated for #ALSMinePTMs, partly because I wanted to make sure the files we used for reanalysis were generated by a real expert. 

A GoFundMe page just went up for Michael's family that you can find here, with additional info on this great guy that we'll all miss.

CIDer -- Account for the differences between CID and HCD!

Were you comfortably just sitting there pretending that CID and HCD fragmentation were the same until someone worked it out for you? So was I! Shame on both of us.

Well, they clearly are not the same. Yes, they both predominantly result in b/y ion fragmentations when hitting nice unmodified tryptic peptides, but you don't have to go too far off those friendly ions before it is clear they are very different.

I'm comfortable saying this now because these nice people worked it out. 

MS1-only proteomics is back with some machine learning boosts!

 

How much evidence do you need to make a peptide identification? 

If you're using match between runs, if your identification is by "Match only" you are relying on your aligned retention time, mass and your isotopes to make that identification.

Is that enough? 

MS1-only proteomics says черт возьми it is! (Google said that is how you say "hell yeah" in Moscow)

What if you had aligned retention time, and mass and some ion mobility hardware as well? Is that enough to make an identification? 

Is that enough? It's certainly more. 

What if you then toss in some sophisticated FDR based on machine learning? 

Some of the work is performed on a FAIMS equipped Fusion Lumos, and some other files are from a QE HF. 

This is one of an increasing number of studies that are questioning the foundations of "what makes a confident peptide identification?" and is definitely worth thinking about. 

Downloads for ReCal Offline and other old FTPrograms!

Are you looking for RecalOffline? For some reason it can be hard to find. 

Some person I ran into at this week's conferences has a link set up for downloading three separate versions. 

If you aren't aware, this allows you to take data acquired on a Thermo FTICR or Orbitrap and apply a recalibration factor. It can be quite slow for today's files, but sometimes it's a lifesaver.

Our mysterious benefactor put up separate links for:

 FTPrograms 4.0

 FTPrograms 3.0

 FTPrograms 2.0

Happy recalibrating! 

Effects of column and gradient lengths on proteomics!

 

I spent time on a lot of references, and eventually found the absolute worst one as a follow-up from some ramblings from this weekend. 

Want to ruin your lunch break reading about stuff you don't want to think about? I recommend this one. 

We convert biological molecules into ionized gases and move them around however we want -- even blowing them to bits -- in vacuum chambers with increasingly sophisticated tools --- and if I don't think about peptide solubility I can't maximize my results?  BORING. However, that's how it works. 

I dislike this paper the most because it makes it seem so simple. 

I strongly recommend you don't read this paper or my main takeaways.

Takeaway #1) When using a 10cm column there is basically no difference in the number of peptides identified when increasing from 60 to 90 minute gradient. Too much time, too little chromatography material.

Takeaway #2) When looking at gradients of up to 90 minutes in total length, there was basically no difference in the number of peptide IDs when moving from a 40cm to a 60cm column. You've got more chromatography material, but to really take advantage of that you'll need a longer gradient. 

This one I'm not sure would reproduce the same way today. An LTQ FT Ultra system was used and we're talking about probably 5 MS/MS scans acquired per second? I've never actually ran one of those myself, but I thought it was comparable to the Orbi XL. I'd expect if your instrument was 10x faster that you'd see a difference here, but at 90 minutes it might not be a pronounced one. 

Hopefully this is the last I have to discuss this for a while, because it's booooring, but it's stuff we do have to consider. I've seen a couple of great studies recently with important samples and expensive instruments and a fraction of the #PSMs/peptides/proteins that I'd expect. It's such a bummer to pull down the RAW files and see that something as boring as chromatography held the whole thing back.