I've written about this before, and I'm still shocked to see that it hasn't caught on.
SprayQC is a free program from Max Planck that monitors your spray stability and your LC conditions and stops your runs AND SENDS YOU AN EMAIL detailing the problem when something has gone awry.
It's been out for a couple of years now. The instructions are real easy to follow and now it supports all sorts of sources thanks to an active community of developers.
Normally I'm pretty angry when I get scooped. Not this time! I've wanted a GUI for PepNovo+ so bad that last summer I hired a programmer in Indianapolis with my own money to help me wrap up the VB script that I wrote. Unfortunately the project was dropped when my programmer obtained a real job, saving me some cash! So I kept on running PepNovo+ from the command prompt when I needed to.
AND somebody else wrote it! And its super easy to install and networks perfectly with my Proteome Discoverer de novo workflow that is described in this video!
I guess I kicked up a little bit of a controversy today, as I've gotten a couple of emails already about this (the previous entry).
I've got a lot going on today so I don't want to go into the true differences between Uniprot TREMBL, Uniprot Swissprot, and the IPI databases, I'm just going to show you some real data.
I ran some HeLa digest a while back on an Orbitrap (Velos, I think). I used a high-high mode (60k, 15k) which is relatively slow on that instrument in comparison to the QE or the Elite or Fusion. I think this was for a limits of detection study or something. It doesn't matter. The experiment will illustrate the point.
I downloaded the IPI Human database and I set this to run over lunch. Same file, same everything, all I changed was the database, IPI or Swissprot. I didn't search with any mods except carbamidomethylation on C.
Want the screenshots? Email me. Want the file and the XML copies of the methods? You can have those as well. Let me know.
Why the big difference?
For one, look at our IPI Human database: 50MB, vs our Uniprot database at 13MB. Why so much bigger?
Cause the IPI database is full of putative crap. Putative 22kDa protein? Super useful, right? This is why very few people use the IPI database. The Uniprot/Swissprot has real proteins with annotations that can help you arrive at a biological conclusion. Could that 22kDa protein be super useful later? Sure, but we have no idea what it is right now!
Thanks for all the comments, guys! I'm going to try and reflect these comments.
I've been hearing about ion mobility for years, but I haven't committed anything to long term memory. But I'm going to. Cause this shit seems pretty awesome.
FAIMS (pronounced fAmeZ) is a way of focusing ions as they enter your mass spectrometer. One proponent described it to me as almost a 3rd dimension of separation. Essentially, it appears that you apply an electrical current to the ions at the entrance to the mass spectrometer allowing you to focus the ions into a particular packet (i.e., z=2 at voltage x, and z=2 at voltage x + 1)
This can open a whole realm of possibilities. How awesome would your ion statistics be if you could tell your search engine that this group of ions were doubly charged, while this second group were all triply charged? It opens up a whole realm of possibilities.
How powerful is this technology? Just to put it in perspective, if it is employed properly it can make a Xevo Synapt actually do something other than MS1! No kidding!
In this new paper in Nature Methods from Ute Distler et al.,these researchers describe the use of a similar technology to FAIMS, called TWIMS (traveling wave ion MS) in conjunction with MSe and use it to crank up the number of peptides and proteins hits on a HeLa database. The energy used in the MSe fragmentation are directly affected by the FAIMS settings in order to optimize the energy range according to the charge states of the ions making it into the instrument.
The results are out of this world! On a 300ng HeLa digest using nanoUPLC on 180 minute gradients, the group reports that they can reproducibly obtain around 3,800 unique proteins when using the IPI database. This is almost up to the level of what I'd expect on an Orbitrap Velos running in standard high low in a data dependent experiment when searching against this same database. For the Synapt this represents a huge increase in peptide/protein coverage (2 to 3 fold!) over a standard MSe run.
This makes me really excited because can you even imagine what FAIMS might do it it were coupled to the front of a mass spectrometer that could get already get that kind of coverage, or better? If a Q Exactive under these conditions was obtaining 4,500 IPI proteins per run, could FAIMS double that? Great days are ahead!
For more on how IPI can inflate your results, click here!
The FAIMS + MSe paper is entitled: Drift time-specific collision energies enable deep coverage data-independent acquisition proteomics
Again, thanks for the comments. I plan to read more about ion mobility (found a great review or 7, I'm sure one or more is open access). I'll follow up later!
Due to my second flight delay today I got through all the stuff I was supposed to read and got distracted again.
This handy simplification above came by way of @attilacsordas and makes me really happy. The mysterious central equation in the most cited paper in history (is that still true? I don't know) simplified into one sentence and color coded? Fantastic!
I need access to RAW data. Lots of it. There are so many cool papers out there right now with new studies and new techniques, some of which are so fantastic that they defy my beliefs in the current capabilities of instruments and methods. Unfortunately, I (and if I believe what I've been told out there, you as well!) have a lot of trouble getting ahold of these results.
It's weird. It used to be easy. You'd pull up a paper, you'd go to the last page to figure out whether they put it on Tranche or ProteomeCommons or whatever and you'd download that data. Super easy. Check the RAW results, get the method they used for every file and you could replicate the study lickity-split.
Then things changed. The data files got too big. The databases could no longer hold all the data that we generated. The turning point? February 22, 2011. This was the day that MCP no longer required the uploading of data before considering an article for publication.
While this simplified the publication process for the authors, it sure made reproducing the studies out there a whole lot harder for everyone else. Ultimately, this is slowing down the progress in the field.
Solution? We need to require the public repository of proteomics data. And I think we have the tools now. The solution I propose?
I wrote about the Chorus project last summer as my favorite thing to come out of ASMS. And this was exactly what I was thinking we need it for. A cloud based (HUGE storage) site for uploading data. And you don't have to download the data once its there, you can search it and view it and interrogate it all on the cloud. So when the next amazing paper pops up demonstrating 2,800 proteins quantified in 10 minutes on an old triplequad we can find out that we really are looking at the next revolution in proteomics (or the other thing...) by seeing the data with our own eyes.
Currently the Chorus website states that the site is still in beta mode. However, I talked to Nate Yates and Mike MacCoss and that beta level should be off soon. Lets all get behind Chorus and start moving forward!
I've made this argument before. One day these mass spectrometers are going to get sensitive enough that we won't have to monkey around with nanoflow. We'll be able to microflow, get better and more reproducible chromatography and live happily ever after. Some groups believe these days are already here. If you aren't sample limited, just inject more peptide, right?
This application note came by way of a LinkedIn feed (see, it is good for something!) and talks about the use and application of microflowrates in validation on a triple quad. While the primary focus of the note is demonstrating the increase in sensitivity of microflow over higher flow rates, it brings up the limitations of nanoflow in terms of robustness and relative high maintenance. Absolutely worth a thought!
First proteomics paper to read in 2014? Looked around, then:
Decision made. Proper on so many levels.
Anyway! Bacillus anthracis is pretty much Bacillus cereus with an extra plasmid or two depending on the strain and other complicated factors. Problem is that we want to really identify anthracis and not identify extremely related (and extremely common) spore forming organisms when we're assessing biological threats. Of particular interest are pXO1 and pXO2 plasmids that can be indicative of super virulent (or even militarized strains).
So what can we do to tell extremely related things apart? Crank up the resolution! In this case, these researchers used an LTQ Orbitrap Discovery and looked for differences in a bottom-up approach between various strains of anthracis and cereus until they found a nice set of unique peptides belonging to the nasty strains. Then they validated their new differential markers by moving their discovery results over to SRMs on a TSQ Quantum Ultra. They show that even in extremely complex mixtures, their new markers are specific enough and sensitive enough to clearly differentiate virulent anthracis from its closest relatives.
Good paper for you microbiologists who are interested in proteomics, as well as a good example of moving your discovery results over to a standardized validation assay. Also a great example of an Orbitrap Discovery out there and still doing some great science!
The paper is open access for the time being and you can find it here.
If you happen to have popped over to MCP over the holidays you might be surprised to see a drawing of a Hippopotamus (not to be confused with a Hiphopopotamus) under some constellations. A little investigation will lead you to a paper about the Human Hippo pathway. Unfortunately, the paper isn't open access, but it looks really good and I think the authors must have a good sense of humor!
2013 is over finally! I can't tell you how much I've been looking forward to saying that! While I'm sitting here I figured I'd wrap up what I think was another awesome year for our field. What were the big developments from the perspective of this biased guy?
When I start at the top, the first thing that really hits me is the native analysis of ovalbumin. I'm sorry, I'm still floored by that one. Just when we start to think that we've got a handle on all the awesome things that evolution has produced in biological systems, to think that a new tool can just blow the doors open and make us realize how little we really know? Big favorite.
Quality control in proteomics! This was a huge year for it. Dr. Mechtler's lab gave us new free software for evaluating the QC of RAW data (SympatiQCo), MRM proteomics released serum peptide standards, and people all over the place are using the PRTC standard. I expect and hope that this is just the tip of the iceberg for QC! Let's all do it!
2013 was also the launch for the Orbitrap Fusion, something I think is best highlighted by the Coon lab one hour yeast proteome paper. Gosh damn that thing is fast. I can't wait to see what people do with it this year now that there are a bunch of them out there in good hands!
Another star of 2013 has been the TMT 10 plex. Isobaric tagging with no loss in coverage? It is so great to see reagents evolving along with our instruments. If I haven't said this enough: Are you running iTRAQ 8 plex? Do yourself a favor, call a sales rep and get a trial of the TMT 10 plex. Its been almost 6 months and I still haven't talked to a single person who tried 10 plex and didn't stop doing iTRAQ 8 plex. Night and day....
The completion of the SRM yeast library is a pretty big deal. This opens up the real option of doing DIA on yeast! With more libraries on the way (and easier ways of making them), I think we're going to start seeing spectral library searches and targeted quan moving closer to center stage.
I know I'm skipping over a bunch of things. This year was huge for all of us. And I may add things as they pop into my head. End thought, though: DMSO! Holy cow! I love this one! What other awesome stuff is right underneath our noses?
I'm going to post this now. And I'm real excited for what y'all are going to do in 2014! If you can't tell, I'm a big big fan of this field and I can't wait for the next paper that totally blows my mind!
