Intacts and top downs and bears!

What did we do without the Internet and all these resources?

Currently, intact and top down proteomics is a big focus for me.  I'm trying to dig up some primary research to get a better handle on it and everything and there are resources all over the place!

The winner (so far) for aesthetics?  TopDownProteomics.org

An extremely nice site with all sorts of tutorials, video resources, software descriptions, new papers, etc., etc.,

If you haven't seen it, head directly over to it here.

Sorry, I lied about the bear.  And I meant to post date this one to show up later in the week....oh well....

While I'm editing, I might as well add a bear...

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QE Plus intact antibodies

I get distracted sometimes.  Months ago, I promised to show some more data on what the QE Plus can do with intact proteins, and here it is, finally!

This is the 0.1 ug of the Waters antibody standard injected onto a C4 column running at 300uL/min.  The S/N is >100:1.

Post-deconvolution, we are looking at sub-10ppm mass accuracy.  I ran this, btw, not some intact expert!

Punch line?  This is without gas optimization.  This is also without enabling "protein mode" on the QE Plus. This was without desalting the notoriously gross Waters mAB standard!  This was a test to make sure the instrument was working correctly.  Could I have adjusted gas pressures, optimized (thrown in a nice high lock mass?) and employed Protein mode to improve this data?  Of course!  Is 1000:1 S/N possible on a QE Plus on an intact (and not desalted, LOL!) antibody?  I don't know, but if this is what one can do right out of the box, imagining what someone who knows what they're doing and takes the time to really optimize everything is a pretty exciting prospect!

In case you are interested, the method file is now up on the Orbitrap methods database.

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RNAseq plus Proteomics. It's coming!

RNAseq "next gen sequencing" data is becoming more and more common every day.  The instruments are getting better, cheaper and faster all the time.  From what I'm seeing and hearing, I'm expecting to see a ton of posters and papers out there where shotgun LC-MS/MS data is searched against RNAseq data.

The big problem?  The size of the two datasets.  Especially the RNAseq data.  It's pretty tough to search against a 500GB genomics file with our LC-MS/MS data.

Sunghee Woo et. al.,  to the rescue!  In the paper "Proteogenomic Database Construction Driven from Large Scale RNAseq Data", this team from UCSD (with some help from Mike MacCoss) demonstrates how to efficiently use the two technologies synchronously.

They start by dramatically reducing the RNAseq data from a 400GB output down to a 400MB FASTA file, by a stepwise removal of redundancy and less useful data.  The logic is clearly defined and seems really smart.

Next they compare the two datasets, the LC-MS/MS data and the new FASTA in such a way that they end up complementing each other.  So, not only do you they get better matches for their proteomics data than they would with a fully annotated FASTA (what most of us want to use this for), but they also improve the annotation of their genomics data.  That's right.  They use the proteomics to correct the genomics data.  Cause the proteomics data can give you single amino acid substitution and splice variants and improve the understanding of the genome.

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Get your LC method out of your Thermo raw data files

Shoutout to my friend Dave who suggested I write this.  Then I forgot.  Then I remembered again!  Have you ever looked through your RAW data and really wanted to know more about your LC conditions (by more, I really mean anything?)
 Open your RAW data file in Xcalibur.
 Right click on your specra (after thumbtacking it)
 Open your Instrument method
 Hit the right arrow.

BOOM!!!!  Your LC method appears in the box!

READ MORE - Get your LC method out of your Thermo raw data files

JPR special issue on the C-CHP

I love when stuff is open source!  And this is hands-down, one of my very favorite projects out there.  You guys working on the HPP get all sorts of love from me.  The C-CHP, especially, since the common theme seemes to be high resolution accurate mass spectrometry and every study so far seems like it could be subtitled "how to get extremely deep proteome coverage with an Orbitrap".

Want to see how this is going right now?  Want to see how effectively scientists can work together all over the world to answer basic science questions?  Check out this special issue at JPR!

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Protein Deconvolution tutorial videos

I like this banner.  I don't know where its from, and I'm probably not allowed to use it, but Google Images gave me it instead of what I was looking for.

Anywho!  One of my spare time projects the last couple weeks has been making new tutorial videos for you guys.

These aren't officially branded things.  These are rough drafts.  But maybe one day they will be a real thing.  Anyway -- check out the sidebar.  There is a new category.  Protein Deconvolution tutorial videos.  There are only 2 right now, but there will (probably) be more later.

So far there are two videos:

How to manually deconvolute a single intact antibody LC-MS file:  https://vimeo.com/85852770

How to batch deconvolute a series of intact antibody LC-MS runs:  https://vimeo.com/85855510

I have no idea why the font just changed there.  Anyway, the links probably don't work yet, but there is also a link to download the monoclonal antibody LC-MS RAW files I used for these analyses.

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Reddit proteomics!

Almost a week since my last post!  I have been busy...  I promise what I've been working on is really cool and, with any luck, should appear on the side bar in the next couple of weeks.

Time to get back in it.  What happens when you combine 2 of my very favorite things in this world?  Not Pugs and Porsches.  (Though...you can't get much cooler than a pug in a Porsche...)

What about Reddit and Proteomics?  If you aren't familiar with Reddit: "The front page of the Internet" you probably shouldn't check it out.  But if you are already addicted to the fastest way to get news and awesome content about whatever it is in the world that interests you, then you should add www.reddit.com/r/proteomics

Right now there isn't much on there, but that's the joy of Reddit, the more people that get on and participate the better it gets.  Plus, if you are on #612 in your personal newsfeed, it wouldn't hurt if a couple of things in there were cool Proteomics links, right?

Oh, and if you have no idea what I'm talking about at all, check out this awesome video entitled "what is reddit?"

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