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Western blots versus parallel reaction monitoring (PRM)!!

This week I visited a lab that has been doing some great validation work with parallel reaction monitoring (PRM). While preparing their work for publication, one of their collaborators began insisting that they "validate" their findings with western blots. I don't know about them, but I felt like I'd been playing Jumanji....

It is 2016 (despite what you've been writing at the top of every page!)!!!  Holy cow. I know I'm typing to my imaginary choir here, but I really want to get this out of my system. Surprisingly, though, no one has really done a head-to-head comparison of PRM versus Western Blots that I can find and I'd like this rant to pop up when I type the two terms into Google. There is, however, a ton of material to pull from to support my rant.

I hereby present: Western blots versus Parallel Reaction monitoring!

In the red corner we have Western Blots. There is a great wikipedia article on this methodology here.

Basically, though, you do this:
1) You run an SDS-PAGE gel
2) You transfer the proteins via more electricity to a membrane (sucks 'em right out and they stick to the membrane
3) You soak the entire membrane in a solution containing a commercial antibody raised against a peptide within your protein of interest. (They do this by injecting a peptide from your protein of interest into a rodent, or camel, or horse. Typically a rodent, though. For this example, lets say its a bunny rabbit.
4) You wash away bunny rabbit antibodies that don't stick to your membrane in a super tight way
5) Then you add a solution to your membrane that has an antibody with a detection region and a region that binds to any bunny rabbit antibodies
6) Then you activate your detection. That detection region might light up (fluorescence) or it typically causes a chemical reaction that makes a dark spot where stuff matches.

Amazing technique when it was developed in the 70s. It is, of course, still super powerful today, but it has weaknesses that have been addressed many times. First of all, it relies on the efficacy and specificity of two commercial antibodies. I know this is ancient history, but in 2008 Lisa Berglund et al., did a high-throughput analysis of commercial antibodies and found that a large number of them did not work at all. In fact, the average success rate of the 1,410 antibodies they tested was an awe-inspring 49%.  I'm sure those numbers have went way way up. However, according to this 2013 article in Nature Methods, the field of antibody production contains over 350 separate producers. Despite this level of competition, the paper appears to recommend returning antibodies as a step in normal lab practices. Hey, no one is perfect, but I'm just throwing these articles out there.

Let us assume that the antibodies you've ordered have been used by tons of groups and that they work just fine. Chances are that you can find a protocol that will give you a good method for step 4 above. If you don't wash away non-specific binding you will just get a blot full of signal. If you use a wash that is too stringent, you get nothing at all. Hopefully someone has done this work for you!  If not, you're on your own. And then you have to wonder...is it the antibody? or is it me? Probably a good idea to run it a few more times. At 4-5 hours a pop with the newest technology and not one single glitch along the way, it might take a few days to optimize a new assay.

I found this nice picture on Google Images, I'd like to share (original source unknown):

Parallel Reaction monitoring!

The figures for PRM are taken from this great recent (open access!) review by Navin Rauniyar.

Here are the steps
1) You start with a pretty good estimate of the mass of some peptides from your protein of interest and you use that for the quadrupole (or ion trap on LTQ-Orbitrap instruments. Yup! You can totally do this on hybrids, but it works better on quadrupole-Orbitraps) isolation. You can easily refine your data acquisition by retention time or by focusing the isolation to reduce background and increase specificity

2) You fragment the ions you select

3) You match the high resolution accurate mass fragment ions to the theoretical (or your previously experimentally observed fragments) within 1 or 2 ppm (really, no reason to ever go above 3 ppm.)

4) Post processing allows you to drop fragment ions that might not be as specific as you'd like and you can use the intensity of your fragment ions cumulatively to score your signal.  Once you have your favorite fragment ions your rerun your PRM method for the samples you'd like to compare.


HEAD to HEAD time!

Category 1: Reproducibility
According to references in this paper from Dan Liebler and Lisa Zimmerman, the CV of a western blotting measurement ranges from 20-40%. In this paper from S. Gallien et al., all PRM measurements in unfractionated human body fluids were found with CVs less than 20%. 5% is common.
Winner?  PRM!

Category 2: Time
There are a bunch of new technologies for western blots including fast transfers and fast blotting and direct signal measurements. If we assume you're using something like that and it takes you 2 hours to normalize, load and run a gel (you are faster than me). You can get this down to 4-5 hours. Now, you can use multiple lanes. But this also involves man hours, where you have to be moving things, transferring things, blah blah blah.
 Winner? In pure time with newest technology? Western blots, maybe. In time (measurements per work day? Definitely PRM.

Category 3: Sensitivity
A chart on this page says you can get sensitivity down to the femto/pico range (in grams.) Since proteins have masses in the kDa range and we measure LC-MS sensitivity on new instruments in the femto and atto-mol range, unless I'm not awake yet, this seems pretty clear.
Winner? PRM by a bunch of zeroes!

Category 4: Specificity
Antibodies are awesomely specific. But they are often raised against one peptide. PRMs of multiple peptides can easily be set up. And you can choose targets AND fragment ions with the level of specificity that you need. Commercial antibody providers will obviously take this stuff into account, but this control is often out of your hands. And its one peptide.  You can see in the blot pictures above that you may often get multiple targets. You can narrow it down by SDS-PAGE determined average mass. OR you can choose multiple peptides that are unique in evolution and you can use the retention time of those peptides and fragments that are unique in evolution, within a few electrons in mass?? This one seems pretty darned clear to me..
Winner? PRM!!!!


Category 5: Cost
Starting from scratch? A full setup to do Western blots is gonna be a lot cheaper than an Orbitrap. But, you know, if you are reading this and you don't have a mass spec you just might have too much time on your hands. If you already have a HRAM LC-MS setup, you don't need anything additional for relative quantification via PRM. For absolute quan you'd want some heavy peptide standards. If you have both the capabilities to do western blots and PRMs in your lab, the antibodies, gels and membranes are additional costs/experiment.
Winner? (If you already have a mass spec that can do PRMs?) PRM!

No ID for your cross-linked peptides? Maybe you aren't looking for the right things.

Cross-linking reagents are such a great idea for studying lots of things. But they can be some cumbersome to work with that a lot of groups just ignore them altogether.  Sven Giese et al., thought it would be worth it to take a deeper look at high resolution CID fragmentation nearly a thousand known cross-linked species to see if we just aren't looking for the correct fragment ion species with our typical techniques.

Turns out that might be exactly what is happening. Taking what they learned from the known peptide high resolution study, they were able to boost the identification rate of their unknowns by 9x over traditional search engines.

Worth noting that they did a lot of this with custom coding in Python, so these tools might not immediately be accessible to all of us, but I bet some smart coder could integrate this info into some user-friendlier tool!

Cause no one ever asked for it! My favorite papers of 2015!

(Picture from PugsAndKisses.Com)

This is definitely my favorite post of the year. This is where I get to go back through this ridiculous hobby of mine and re-read my interpretations about the amazing work you guys are doing out there!  (An added benefit is that I get to fix typos, errors and even delete some of the dumber things I've typed.)

There was SO MUCH great stuff published this year. I know I only read a tiny fraction, but I now have 17 tabs open that I'm trying to narrow down. I'm going to start with the 2 that really stand out in my mind

PROMIS-QUAN -- The most proteins ever ID'ed in a plasma sample isn't some analysis where someone did 2D fractionation and 288 hours of runs? No, its one single LC-MS run?  When friends outside my field ask me how the technology is progressing, I tell them about this paper. I hope hope hope it is real. I feel equally impressed that this group came up with this and equally stupid for not thinking of it, because it is so simple and so so brilliant.

Intelligent acquisition of PRMs -- I really think PRMs are the future of accurate quantification. You get your ion and you know it really is your target because you have basically ever fragment of one species with accurate mass, typically within 1ppm or 2. Problem is they are kinda slow. So these crazies in Luxembourg go and write their own software so that they can intelligently acquire their targets based on the appearance of heavy labeled internal standards? This is a study that is so good, the PI makes this list even though he didn't respond when I asked him for a slide from his HUPO talk. Tie this in with a lot of mounting data that PRMs can be as sensitive or more than QQQ and you start to wonder what routine labs are gonna look like in the near future...

LC-MS can be both reproducible AND accurate -- The genomics/transcriptomics people get to eat our lunch sometimes due to the belief in general science that we aren't very reproducible. So a bunch of smart people get together and show that our biggest problem, as a field, may be that we don't have common sample prep techniques, cause if you prep samples the same way it doesn't seem to matter where your mass spec is or who runs it...

(within reason, of course)

... you can get the same data.

Speaking of sample prep:

How 'bout massively speeding up FASP reactions with mSTERN blotting, iFASP, or change gears entirely with the SMART digest kits?  Which one should you use? I don't know! I'm just a blogger. How 'bout a bunch of you smart people get together and decide which one and lets shake off this whole "proteomics isn't reproducible" bologna and get all the money people are spending on those weird, shiny (and crazy expensive!) RNA boxes. 

Oh yeah!  On the topic of those RNA boxes, PROTEOGENOMICS!

Probably my favorite primary research paper on this topic this year (man, there were some great ones!) I can think of was this gem in Nature. We also saw several great reviews, but this one in Nature Methods was likely the most current and comprehensive one that I spent time on. Is Proteogenomics still really hard to do? Sure! Does it look worth it? Yeah, I still think it does, and it'll get easier at some point!

There were some proteomics papers that transcended our field this year as well. Probably the biggest one was the pancreatic cancer detection from urine that the good people at MSBioWorks were involved in.  Another one I liked a lot was the Proteomics in Forensics out of the Kohlbacher group. Apparently you guys liked it as well, cause my blurb on it was probably my most read post of the year.

  [Previously my opinions on another paper that were a bit negative occupied this spot. I chose to delete a few minutes after posting. Lets keep this positive! Insert Gusto instead!]

Now it gets a little random! Just things that occur to me this morning as really smart.

How 'bout going after non-stoichiometric peptides and PTMs?  When I mention this to people it still seems a little controversial but biologically it makes an awful lot of sense. This year we also either saw a lot more glycoproteomics because that field is advancing on all fronts or I was just more aware of it.  I think its the former, though. A great example was this paper out of Australia.  It was another big year for phosphoproteomics, with new enrichment techniques, incredibly deep coverage studies, reproducibility analyses, applications of quantification and even new tools to analyze all that phospho data!

Another one that sticks out to me was Direct Infusion SIM (DISIM?). If you need to quantify something fast, turns out you can direct infuse the target and you can get some good relative quantification. Makes sense to me, and they have the data to show it works, so why not!?!

Okay, I've been working on this one for way too long. Ending notes: Holy cow, y'all did some awesome stuff in 2015!  THANK YOU!!! I can't wait to see what you've got for us this year!!!!