ASMS 2020 -- Reboot!

Around the really clever wordplay in all directions, ASMS 2020 is go! You can check on the plans here!

SARS-CoV-2 Protein protein interaction webinar THIS FRIDAY!

Want the inside track on how this huge protein protein interaction study was assembled so rapidly?

Figure out what time it is in London and check out this great talk on Friday!

ALSO -- have you heard about the COVID-19 Mass Spectrometry Coalition?


Sign up and let's kill this stupid virus thing!

FAIMSPro -- More proteins, but where did all the peptides go??

Mystery with a short answer (I think) that took me a while to figure out. However, since it isn't detailed precisely in the study above, I feel a little less unsmart. (1,2,3 negatives in that sentence? Meh.)

When you fire up your FAIMS Pro, you're going to be IMpressed. The background noise is great, the nitrogen consumption....less great..... and you're going to see WAY more protein IDs!

However, there is a cost to this. You're going to get less coverage of those proteins. The authors made this pretty green chart, so I don't have to (borrowed without any permission whatsoever)

Regardless of what FAIMS compensation voltage (CV) you use, you're going to end up with fewer peptides identified. But more proteins!

I'll even go one better with another stolen green plot -- the proteins you'll find will be lower abundance! (Deep HeLa is fractionated).

If you spend less time on albumin, titin and keratin, we all win (unless you're a keratin researcher, and you have your own challenges).

I scratched my head about this and plotted stuff a bunch of different ways. Surprisingly the MS1 isolation interference doesn't seem all that different (but -- keep in mind that this is essentially a normalized measurement)

<---No FAIMS left
FAIMS -75 right -->









However, if you take out all the z=1 peptides and your Signal (S) goes up, you're also raising low abundance peptides that are now contributing to your Noise (N), so probably this is all good stuff.

Okay -- so what is actually different between the files?

The stupid charge state distributions!

 No FAIMS left -- FAIMS -75 right. All the sudden you've got a bunch more +3 peptides (relatively)

Okay -- this gets better, I think, because you know what a lot of search engines assume? They assume that your MS/MS fragments will be +1 charged.

Sure, they'll try to look at more, but as awesome as a 1980s TransAm looks and sounds, it's only got 205 horsepower. With age, it's probably closer to 170 at the wheels without a full rebuild by someone good. You can get faster used hybrids on Craigslist.

Is that a long and unnecessary metaphor/analogy/something or other? Absolutely.

Nearly all of the newer search engines that I'm always going on about start by deconvoluting the MS/MS spectra prior to searching.

As a more controlled experiment (n=1! I'm winning science today) -- let's take the same file and run it through Proteome Discoverer with and without first deconvoluting the MS/MS spectra so all the fragments are +1 (this was in PD 2.1, due to the fact I'm using an older PC today thanks to some weird malware issues that I think are Zoom related)

It's safe to assume in a tryptic digest that you've always got your single basic residue at the terminus. There's one. In a +2 you've got one "mobile proton" so probably +1 fragments make sense, but in a +3?

I'm too bored with this post to dig up some MS/MS spectra. (I went down a rabbit hole reading about Trans Am specs to make sure I was right. My Craigslist hybrid is faster 0-60 than a 1985 Trans Am when the two were brand new. (The Trans Am looks way cooler, though).

CV -75 file number 1. No deconvolution/SeQuest+ Percolator


Same file. Changed nothing except added deconvolution of the MS/MS spectra

FAIMS Pro results may not be exactly what everyone wants. If you're looking for the highest coverage, maybe you want to take it off and run without it. If what you want is the highest number of protein IDs because you are willing to sacrifice some coverage of the higher abundance ones to see some of the lower abundance ones....

----particularly if you're willing to tweak your workflow toward this newish kind of data!

Reminder of #ALSMinePTM Challenge -- and some wiggle room on data submission!

To the amazing people who have signed up for the largest proteomic informatic challenge in the history of the universe -- THANK YOU!

Also -- just a reminder that we were targeting this week for data submissions.

However -- if you've found your life a little bit offset by some virus thing, we think it's fair to move back the due date.

We'll have a portal or something set up soon(?) to start submitting data this week, but we'll continue to accept submissions for the next 2 weeks.

If you're just now hearing about the biggest proteomics informatics challenge in history and want to join in -- there's no better time than right now.

You can find the official site here.

I have something permanently stuck to the front page of this blog over there --> somewhere.

And I have an informal description of what we're doing and why this matters (beyond showing off how good your progam is or what a wizard you are at processing data) here!

Rapid gradient single shot FAIMS-Pro Exploris -- 5000 proteins in 20 min!??!

Did I post this once already? Probably, it was in preprint a while back, but -- wow -- I've reprocessed all the DDA data and it's unreal how good this is.

1) EVOSEP
2) FAIMS Pro
3) Exploris 480

Even conservatively on the 20-ish minutes DDA 500ng HeLa runs I'm getting over 3,800 human proteins on the best runs.

Worth noting, on the DDA runs single FAIMS compensation voltages (CV) are utilized. The authors are very clear that the CV voltages of 70/75 that appear to max out the number of identifications as seen here may be very specific to the instrument being at absolute peak performance (i.e., clean and very lightly used).

I haven't processed the DIA data yet, but it appears to produce better results in their hands.

Huge question here that should be addressed based on TIC alone between some runs I have from EasyNLC vs the signal that I'm seeing here.....do you just naturally get more signal with the EvoSep due to the fact that you're loading directly to your separation column, rather than to a trap as is typical in NanoLC (since you need that column to live a little longer?)

If anyone has that kind of data, I'd love to see it.

Oh yeah! Here is the paper.

COVID-19 AirBnB cancellation policies now extend through ASMS.

I don't know how many people out there do AirBnB for conference travel, but it's my go to for just about any trip. Unsurprisingly, the extension in the US now covers the dates for ASMS Houston. 

I'll undoubtedly use the travel funds for some other trip, so I actually get all my funds back. Woooo! 

Is this the long sought after list of human housekeeping proteins?!?!

A shockingly useful thing in genomics is a list of "housekeeping genes" for each organism. These things are always there and nearly always in uniform abundance for some reasons that make DNA or RNA level sense.

A list of universal "housekeeping proteins" is something I know I've always looked for -- and -- could this newly ASAP Accepted paper at JPR have that list? 

I'm paywalled right this second, so I can't say for sure, so I'm going to leave it here.

Just a reminder, though, if you DID have a list like this you can utilize those proteins in a most workflows, including Proteome Discoverer. I put together an overview of one way you can use a list like that here a couple of years ago (for normalizing between multiple TMT/iTRAQ sets).

Add super accurate and fast quantification to your workflow with FlashLFQ!

Hey!

Do you use a tool that is great for peptide ID but doesn't do quantification -- or only does spectral counting, or does quan in some other dumb way?

BOOM!

(Ignore the fancy Greek words in this title, they are not why this is important -- okay -- if you care about getting better quan, you should read about the erroneous assumptions that we often make in proteomics that makes some things seem super significant when they clearly are not)

What you should do is go get the FlashLFQ GUI here!

 You get all these smart features in a really easy way to use (flexible formats -- including Match Between Runs (MBR) and the Bolognese Nacho Impartial Hat Turkey Carburetor thing that the paper is about!

ASMS 2020 Houston Cancelled -- Online ASMS 2020 details coming soon!

In something that comes as a surprise to no one, we won't be gathering in Houston for my favorite holiday.

An online format is coming. Keep up on details at ASMS.org.

If you're crazy enough that you booked your Airbnb a year in advance, you may be able to get forgiveness for all or a percentage of your stay. May 31, 2020 is the last day currently, but details will be posted here.

Man...a lot can change in the world in 3 weeks. The Skyline team was being proactive about the volunteer speaker pool and I was convinced we'd beat this stupid virus (come on, it's only 10 proteins!) by then.

Great virus proteomics references!

This isn't anywhere near a complete list, but if you're finding yourself motivated to jump into virus proteomics all the sudden for some weird reason or the other, here are some awesome resources.

This review is where everyone (IMHO) should start.

If you're looking for something beyond what the 137 references in that paper can provide, you might need to do some jumping jacks.

However, if you wanted to focus on specifically LCMS methods for virus stuff, a really good next stop would be going to Google Scholar and typing in Virus and Arthur Moseley. That team at Duke has been getting DARPA funding to work on virus detection for years (that's who is acknowledged in at least some of the papers).

In this one they identify host targets using 2D-wait...gels...?...hey, it works and then they build targeted assays for the host biomarkers. 

And this one is my current favorite. In this one they build targeted assays for viral proteins!

The peptides are hunded down with an LC-QTOF and LC-MRM (all Waters instruments) are developed. Stable isotope peptides are used for the MRMs and 30 minute NanoLC gradients.

On the TQ-S they get theoretical LODs in the sub-femptomol range!

AND they show that they can use targets for the variable regions of the nucleocapsids to work out the lineage of the virus.