Get your nanosource camera view on your PC screen

For some of us out there, we have the ability to log into our instruments from home.  Is there anything more comforting than going to bed knowing that you queued everything up properly, the QCs looked fine and the spray stability is awesome?  Or...seeing that something is messed up so you can shut it down and fix it when you get back in?!?

The missing link for most of us these days is the source camera.  If you've got an EasySpray or a nanoFlex ion source your video likely shows up on a little TV screen on top your mass spec.  That isn't too useful if you're using Remote Login.

Well, Sheng Zhang at the Cornell Proteomics Core has a brilliant solution for us!  You can buy Dino-Lite USB controlled microscopes on Amazon and they fit right in where your normal cameras fit into your source!  He has a different one on his Elite and his Fusion and we couldn't find the exact part numbers. The one on the Elite is a little better quality, but both are just awesome.  The little camera even comes with a small program that projects what it sees onto the PC screen. So no extra software necessary.  It doesn't appear to consume many resources at all.

There are tons of options (check this Amazon search page), but one that definitely works with USB 2.0 is this guy for $150!

Process DIA data directly in Proteome Discoverer 2.0 with DIA Umpire

Alright, this DIA stuff is confusing.  There are methods all over the place.  WiSIMDIA on the Fusion, pSMART, multiplex-DIA, and even boring old SWATH.  Software-wise, there is tons of stuff out there.  This weekend I processed some DIA data from a Fusion directly through Proteome Discoverer 2.0...and it looks amazing.

The data in question was ran through the DIA-Umpire to convert the data into a handy-dandy MGF file format.  You can find details on the DIA-Umpire in this Nature Methods paper by Chih-Chiang Tsou et al., out of Alexey Nezvizhskii's lab.  Essentially, it is a (currently) command line driven program that takes your DIA data and "deconvolutes" it down to a format that is friendly to the proteomics processing pipelines we already know and trust.  How does it work?  No idea.  But it works, and the data looks amazing (did I say that once already?)

Here is a random high scoring PSM I grabbed.  Looks pretty incredible, right?  They all do.  And I didn't have to change my workflow at all.  I used SequestHT, target decoy and my normal basic consensus report.  I ended up with a ton of IDs and really nice true FDRs at every level I set them at (PSM, peptide, and protein).

If you are interested in identifying peptides via DIA and you are a little swamped by your software options, you might want to check this out.  I'm tired of learning new software interfaces -- lets put everything in Discoverer!

Another amazing Boston trip!

Yesterday, I somehow suckered around 80 people into spending about a whole day in a big room talking with me about Proteome Discoverer 2.0.  We ran through a lot of different processing ideas and scenarios and I got a ton of feedback to pass on to the Proteome Discoverer team (which I should probably be doing right now rather than blogging this...oh well...it WILL be passed on shortly)

Today was more fun of popping in to see a bunch of different labs and talk about different processing needs and how we can address them with Proteome Discoverer.  Now I've got several cool puzzles to work on (man, everybody is doing something cool in this town!!!).  Anyway, no real news here, just a shout out to the great people of Boston/Cambridge for their time and energy in making this (from my standpoint) a fantastically (that's a word?) productive trip!

Want to take a full intensive course on targeted proteomics online?

This is why I love Twitter for learning stuff!  So much good information out there  -- such as this 21-part course on targeted proteomics put on recently by a ton of experts in targeted proteomics in Zurich.

You can watch all the videos here!

Shoutout to Ben Collins for leading me to this list of all the videos in order!

Outstanding review on the evolution of the Orbitrap

The Orbitrap hasn't been around all that long, yet there are tons of different flavors.  A really fun aspect of my job is that I sometimes get to go into a lab where someone has been running an Orbitrap XL (which is an awesome instrumet, btw!!) and I get to be there when they get to see what their new QE HF is capable of.

Can you still get the same data out of your Orbitrap XL?  In a lot of cases, hell yes you can!  Can you get that same information on the QE HF in...one-quarter or one-tenth the time....sometimes the answer is a resounding yes.

So what are the differences?  For an incredibly thorough (and very pretty) review of where the Orbitrap was, is, and maybe will be next check this paper from Shannon Eliuk and some guy named Makarov?

Its open access and a great read!

Does DMSO addition affect label free quantification?

DMSO as an additive for nanoLC proteomics applications is still pretty polarizing.  If you want my opinion on it, it is: yes, you get more signal and peptide IDs, but you should anticipate requiring more cleaning and maintenance on your instrument.  If you don't mind the downtime and the signal intensity is paramount...well, that's your choice.  For me?  I would run DMSO if I was doing experiments on your instrument, but I wouldn't use it on mine...

To further investigate the affects of DMSO as an additive Dominika Strzelecka et al., checked to see if adding 3% DMSO would affect their label free quantification.  I stole the figure above from the open access paper.  In A, you see the ID'ed peptides.  In B you see the quantified peptides.  In the end they found that DMSO really didn't affect the quality of the quantification, though maybe the increase in signal does help you quantify more.

Me? I'm most interested in the shift in identified peptides!?!  Out of ~2500 peptides ID'ed over 1000 were differentially ID'ed by changing the buffers!

Highly recommended paper that adds more info to a very interesting topic.

Proteomics in negative mode!

Wow!  What is happening in this picture?  Something flat out crazy and awesome.

The paper is in press at MCP here from Nicholas Riley et al., out of some guy named Josh Coon's lab.

What is it?  A hacked LTQ Orbitrap with a new collision source.  They call it the "Multipurpose Dissociation Cell" and it massively improves the signal, speed, and utility of ETD fragmentation.  It improves it to the point that it makes doing proteomics completely in negative mode something that everyone has thought about something that is actually a possibility.

Just last week I spent some time explaining why we don't do negative proteomics for PTMs: poor ionization, fragmentation sucks, there aren't good tools for translating the data, etc.,  Amazing how this field evolves!

To get around poor ionization, this study switched the buffers around.  High pH reverse phase!
To get good fragmentation, they use their awesome new MDC source to perform Acitive Ion Negative ETD (AI-NETD)
To do the data processing, they studied the AI-NETD fragmentation spectra and determined the new charge-reduction loss masses and processed the data to remove these components.  Then they used a modified version of OMSSA that was set to read a(dot) and x fragment ions.

I had to pull the Wikipedia peptide fragmentation chart to figure out where things are coming apart. Wow, right?

This isn't the first run at doing negative proteomics.  It isn't even the first run at doing negative ETD fragmentation.  This is, however, the first time that we've seen this approach produce results on the same scale as we get from positive fragmentation studies.

In one run they broke the 1,000 proteins ID'ed barrier on yeast.
Using multiple enzymes they come close to 100% coverage of the yeast proteome.  How's that for on the right scale!?!

But that isn't really where the power of this approach is needed.  We can get whole proteome shotgun coverage.  We've kind of got that one in the bag.  This opens up a whole new capacity for ions that prefer negative charges.  Like many post translational modifications do.  Heck, this might even open us up for more high throughput analyses of completely different biomolecules like oligonucleotides.

I want to extend a personal thank you to the authors here.  I was trying to come up with reasons to get out of bed early this morning and just when "staying employed" didn't seem like it was enough to tip the scales, I found this in MCP.  Now I'm up, motivated and about to head out the door to see what else all you brilliant people are up to out there!