Saturday, February 27, 2021

Cranking up Thermal Proteome Profiling for Drug Mechanisms with TMTPro!

Thermal Proteome Profiling is one of the awesomely powerful new(-ish) methods for rapidly working out how a drug works in a cell. 

I've rambled about it here and there, but it was way too slow for me to suggest it to anyone around me until people started multiplexing it. (PISA blog post here that will link you to older posts/papers).

Basic idea -- proteins have a natural way of unfolding. If a drug is stuck to them or messing with them in some way, that natural way of unfolding is going to be disturbed. 

Why not get the whole experiment over with fast by using TMTPro? 

Interesting from a very boring level, the authors are using a Tribrid system and they don't change their fragmentation parameters for the TMT11-plex to the TMTPro. In every paper I've seen so far, people are using a little less energy, particularly for the Q Exactive family of instruments. There is some wiggle room in HCD for fragmentation on everything. At a purely anecdotal level, it has seemed to me that the HCD/IRM assembly on the Fusion isn't as particular about HCD energy as the terminal HCD on the Q Exactives. I can't back that up with any data, but at a big core where multiple users accessed each instrument, the Fusion HCD seemed less annoyed by users who used slightly different fragmentation settings. Maybe that plays in here?

Friday, February 26, 2021

Death to nanoLC -- 50uL/min proteomics, 38,000 samples and counting!

Hey you! 

What's your record for number of samples on that EasySpray column? Have you ever gotten 6 weeks out of one? I did once because I took the thing apart and put a new emitter in it after it clogged. (I should show you people how to do that! It doesn't work great, and it kind of negates the whole point of buying an EasySpray if you're going to make a crappy junction on the inside of one....but in an emergency.)

That plot above is the performance of proteomics columns with a time scale that isn't DAYS. It's over a 2 year period. Check it out here! 

How are they doing this? 50uL/min. 

The proteomics data quality doesn't suck, at all. 

The Lumos and HF-X systems with the big opening in the front do appear to be necessary to hit the kind of coverage this group does, particularly with the short gradient lengths employed.  In our hands we can get great data on the Q Exactive Classic, but we can't get away with 30 minute gradients and we have to use much larger injection volumes. (Preprint here I keep forgetting to submit somewhere so nice proteomics people can reject it.) 

High flow proteomics is coming and hopefully we'll see the Nanoflow HPLC start to die out. Your collaborators are prepping MILLIgrams of protein most of the time. You need nanoflow for nanograms of material. 

Wednesday, February 24, 2021

Sunday, February 7, 2021

ABRF 2019 DIA Study Preprint is out!

 Are you one of the 45 labs that submitted data for the 2019 ABRF DIA study? Well, the results are out!'ve got a spare hard drive and just want to see what this group of volunteers can download the 1.7 TERABYTES of data acquired for the study at MASSIVE. 

Or you could check out the summary at BioRXIV here! 

On that topic, the virtual ABRF 2021 Abstract Deadline is 2/15. Which sounded far away until I was about to schedule this post to submit and my calendar stated that it is currently February of 2021. If I'd had to guess, it wouldn't have been my first one. So...coming up fast! 

Tuesday, February 2, 2021

Ethics in clinical proteomics!

Whoa! Almost 2 months without a blog post?  That might be the longest space in a decade, but we started a new project this year and he's kind of time consuming. (Thanks, Dr. Rinas for the great books!) 

If I'm writing the first post of the year, I figured it should be a really awful one. 

Let's talk about ethical principles and constraints in proteomics. Ugh. 
(Yes, I deliberately used the page that would have the Elfseverer logo on it, because that is the global stamp of ethical behavior.) 

This study is mostly a literature search about the stuff that we've gotten away without thinking about (ethics stuff) that the genetics people have to worry about. Wait. Why do we have to think about this all of a sudden? 

This shouldn't come as a surprise to anyone, right? If you've got access to a mass spec and you haven't ran your own blood and some dog poo that looked funny through it, you're the weirdo, not me. Somewhere I've got slides from a lecture where I show that it looks like I'm lacking some important protein in my blood. In reality (from my whole genome sequencing data) I know I've got several single amino acid substitutions in that protein that subs in some Rs and the alternative cleavage events make them look downregulated since those variants aren't in uniprot. Impute the missing peptide and whoa, super downregulated. In this study they show how they can tell participants from past studies apart, and what info they can also extract on them. Fun! 

And...I guess if you're in a group where you've published more than one method section over the years with a statement like this....

....leading the charge on the ethical use of that information is a great idea! 

See...everyone does it! 

(Side note: This paper is quite old and I doubt with the coverage at the time that this is nearly as big of a deal, but I really thought that this was funny)