Orbitrap Elite

Last month I finally got my hands on an Orbitrap Velos plus ETD.  Faster, more sensitive, and more robust than my old reliable Orbitrap XL.  And now this happens!

The video above is an animation of the new Orbitrap Elite
The Elite has 2.5 times the maximum resolution of my Velos and operates nearly 4 times faster.  It also has a slew of other goodies that make it better than the Velos.  No idea what the price is, but I'm guessing a cool million. Since I changed jobs I missed ASMS where it was unveiled.

Something Bioworks does better than Proteome Discoverer

Proteome Discoverer 1.2 is a great piece of software.  Now that I've got the module thing down, I don't know how I got anything done with Bioworks.  We did, of course, process hundreds of GB of data with Bioworks, but it is so much faster and easier now with Discoverer.
There is, however, one thing that Bioworks does better, much better, than Discoverer.
If you are trying to put together a presentation to show off your SILAC quantification data, would you rather show this:

or

The top is the graphical output for a protein that is ~10 fold down-regulated in the heavy labeled cell line that you would get with Bioworks.
The bottom is an example of the output you get with Discoverer.  Not nearly as pretty, or as sciencey!

Summary:  Bioworks still has value.  Keep an old Windows XP computer around so that you can still run it if you need to!

Quality control in biological mass spectrometry

Just sent of my new book proposal off to Springer:  Quality Control in Biological Mass Spectrometry.  I don't know how long these things take to be reviewed, but I'm assuming it can take a long time.  I still feel that this is an area that doesn't get nearly enough attention and needs to be addressed.

Microarray vs Proteomics

At this point, I believe we have a consensus:  Quantification data from microarrays doesn't replicate very well at the protein level.  The problem is that we don't seem to have an idea how bad the discrepancy is or why this occurs.

Years ago, Dr. Rich Helm, who runs the Mass Spectrometry Consortium at Virginia Tech said that in bacteria, the correlation is less than 0.20.  So, 1 in 5 observations match between the two in an organism that has 1 chromosome and very limited post-translational modifications?

I throw this out there because I recently participated in a study where we did quantitative proteomics and microarrays on two cell lines from mice.  Our correlation?  0.01.  One in one hundred observations matched between the two.

The ridiculous part?  That the two techniques gave us extremely complementary data.  They pointed at exactly the same pathway, with almost no overlap in proteins.  As we construct this paper, I'm sure that I'll continue to search the literature.  Maybe someone has a good explanation, but I've been doing some reading and I sure haven't come upon one yet.

Deep Proteome Coverage without Prefractionation

A good friend forwarded me a great paper that I somehow missed from last summer.  "Deep and Highly Sensitive Proteome Coverage by LC-MS/MS without Prefractionation."  This paper is out of Matthias Mann's lab at Max Planck and Suman Thakur is the lead author.

In a nutshell, the paper describes their attempts at using long (up to 2 meter!!!!!) columns to separate and identify complex peptide samples.  If you are thinking 1 million PSI backpressure, you aren't alone.  They build a custom column heater to keep the backpressure down.  And it works.  Holy cow.  In a 480 minute run they cover 68% of the proteins that they found in the multistage fractionation of yeast extract that they did a few years ago.  68% in 480 minutes.

The kicker here?  Call up your nanospray column manufacturer and ask for a quote on a column even 40cm long!  Lets see if you get as discouraged as I did.  If you know of a company that makes custom columns of this length for less than the price of a Porsche 951, definitely let me know!

New job

With considerable mixed feelings, I accepted a new position today.  Although I sincerely loved my lab and my position in it, when a fantastic opportunity falls in your lab, sometimes you need to grab it.  I will be moving from my postdoctoral position in the Drug Mechanism Group to a full Scientist position in Molecular Pathogenesis and Biomarkers.  The position comes with the newest Orbitrap Velos plus ETD, as well as a considerable increase in both responsibility, freedom, and salary.  I'll miss my group but I am extremely excited to move onward

4G10 antibody for FACE, regular or platinum

As mentioned in a previous post, the antibody of choice for phosphopeptide enrichment via Filter Aided Capture and Elution is the Millipore 4G10 antibody.
Recently, however, Millipore has introduced its new 4G10 platinum antibody.  Due to a slight order mix-up, we ended up with aliquots of both the regular and the platinum antibody.
Instead of having 2 separate antibodies around, the sample was split and enriched by equal aliquots of the two antibodies, with essentially no change in peptide enrichment.
The 4G10 platinum was developed to minimize lot-to-lot variation, but if you are not concerned with variation (i.e., you are doing 1 enrichment), save yourself $120 and just get the old 4G10.  As far as lot variability is concerned, I've never had a problem with a millipore antibody and if they have variation between lots, my guess is that it is going to really affect 1 in 1,000 experiments.

Summary:  4G10 vs 4G10 platinum?  4G10 is cheaper but may vary to a level (I'd guess is imperceptible) between lots.

GeneSpring GX 11

GeneSpring 11 updates are now rolling out.  In order to see what the updates entail, I grabbed a couple sets of microarray files that I have interrogated so thoroughly that I have the heatmaps memorized.

I have only good things to report:
1) The interface is the same.  There are no changes in uploading files or in setting up an experiment
2) The Guided Workflow is no different, except the thumbtack feature when looking at the overall statistics is a little less glitchy.  In GX 9 once I set a thumbtack on the graph I want to see, the program seems to strobe the charts kind of randomly.
3) Big improvement:  In the exporting of your final list of differentially expressed genes --> the orientation no longer changes when you copy to Excel.  GX 9 will show you fold change between the genes up-regulated in condition 1 vs. condition 2.  When you export the data to Excel, the spreadsheet will now be condition 2 vs. condition 1.  This can cause some serious confusion when you don't know your experimental model very well.  At least in this dataset, GX 11 did not have this glitch.
4) Direct link to Ingenuity Pathways Analysis.  This is another nice improvement.  The transition of the results into IPA happens almost automatically.  You don't have to export to Excel, convert your data into tab-delimited text, then import it into IPA.

Summary:  Very nice improvements.  Since the upgrade is free for all Genespring subscribers, You really should download the file.  It won't slow down your experiments, and should only simplify things for you!

New Proteomic Protocols Book

My new book is out!  And you can purchase it at Amazon. Whether or not to make it available for Kindle is still under consideration.  I don't know how useful it would be and whether it would really be worth my time.  The first time I see someone with a tablet in use in a lab, I may go to the effort to make this available in digital format, but I still haven't seen it happen.  Its coming, especially with the iORBI thing.

Big shoutouts got to David Berryhill at Johns Hopkins for critically reviewing this text and to Michael Mullendore for assistance with the sections on protein validation.

Pierce Graphite Columns, do you really get more phosphopeptides than with C-18 Ziptips?

Pierce has been advertising their Graphite spin columns as a more efficient method for desalting and retaining phosphopeptides, but is that really the case?
In this experiment, we took a mixture of phosphopeptides that were enriched by filtered capture and elution (FACE) using the 3G10 antibody as described in this paper from Mathias Mann's group.

The eluted phosphopeptides were split into two equal aliquots.  One aliquot was desalted with the graphite spin columns.  The second was desalted with C-18 ziptips.

The results are pretty clear, although it is interesting that the majority of phosphopeptides pulled out by the C-18 columns were unique to that desalting method.
Our thoughts are to integrate the two techniques, perhaps by desalting the flowthrough from 1 method by the other.  Anything that increases our coverage this easily needs to be jumped on.