Saturday, May 12, 2018
IonStar -- Global proteomics with reproducibility as #1 priority!
Okay, ya'll. This is going to look a little self-serving, because I've been lucky enough to contribute in some small way to this amazing project, but I'm on a mission.
This mission is to prove that:
1) Proteomics CAN be reproducible
2) Proteomics CAN contribute to clinical studies
3) Proteomics CAN be part of what we use to diagnose patients -- to find out when they're sick before it's too late and to help pick the drugs that they need to use to get better the fastest.
4) If proteomics focuses on what it can do to COMPLEMENT genomics and transcriptomics, rather than trying to beat them all the time (an exome sequencing is under $350, y'all, and a full 30-50x transcriptome might drop under $1k really really soon) at things they can do better and cheaper -- we can do great amazing things together. Do we really want to try and compete with that -- when they can't do any PTMs and have basically no ability to do proteoforms!?!?
I think an awful lot of people in our field are on this same mission -- but sometimes it doesn't seem like it -- because we can't don't seem to be able to stop messing around with the settings on our instruments and settle on methods that will make our experiment not only impactful for us for singular studies -- but also impactful for anyone who wants to go to ProteomeXchange and look at our data and compare those to other datasets.
I'm guilty of the same thing. Why have 112 settings I can change on my Fusion IF I DON'T TRY EVERY COMBINATION OF THEM!?!?!?! I stayed up basically all night last night trying to make a QE HF do BoxCar (follow-up post coming -- I think I got it)
Jun Qu is also on this same mission. To prove it, his lab pretty much stopped changing their sample prep and mass spec methods a couple years ago -- and it's reaping some amazing dividends (more papers published -- just since 2017 -- than I've published in my career...). So I'm going to present yet another great IonStar paper here.
7,000 proteins ID'ed quantified in mammal cell lysates with no missing values
Introduces IonStaR Stats which can be downloaded here so you, too, can have all the tools shown in this paper.
The suggestion of -- you know what?!?! if we just do great chromatography and ultra-high resolution MS1 scans -- maybe that triply charge peptide that we've got at 104 +/- 0.5min with 1ppm mass accuracy is the same peptide from run1 to run 8,412. Maybe we can use MS1 libraries (not presented here -- but it sure sounds like it might work)...
Another advantage -- and maybe just because I'm a little bit of a funk because of some disappointment the last 2 days -- if you've got a TriBrid you're good to go. You don't have to hack your instrument or anything like that. The vendor's software -- a seriously nice column (Jun's lab uses 100cm columns), in limited experiments at my facility with 50cm and 75cm EasySprays -- the performance doesn't looks that far off. The bit I lose, I'd trade for the ease of NanoViper. I'm lazy -- sue me. The important part is 1) picking a sample prep method, best you can, and follow it exactly 2) Run the same exact instrument method. As much as you want to try that higher AGC target --DON'T. 3) And consider that if you are just using peak finding (match between runs) that there is a certain number of false discoveries that will occur -- use some method of FADR to control it a little!
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