Very cool - glad to see folks picking up from libraries like that. We will be sharing more of our libraries soon linked to an upcoming publication, hopefully they will be equally useful for folks. Our approach in inSeqAPI is a bit complicated, but very customizable.
I am curious, are you writing your own IAPI program? Or using one of the (few) options out there?
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I suppose that could be true. But having spent a large amount of time over the past 1.5+ years trying to understand DIA data and its analysis, the thought of adding in time multiplexing seems ambitious. We already see wild variations between softwares and versions with the “simple” data we have now.
What’s interesting to me is that more than one group is taking this approach. I’m still skeptical, you are spreading out the impact your high abundant peptides across the run, impacting low level peptides. Not to mention peptides unique to a sample. But interested to see where this approach goes!
There was a Marto Lab paper using something similar to do PRM in 2021. As far as I know it is not widely available - but would be worth checking in again probably.
Marto lab paper: pubmed.ncbi.nlm.nih.gov/34606255/
As of now the only way to remove 126 is to take reporter ions to ion trap and isolate there. We did that in our Nature Methods paper, but you lose some 127. Other way would be to raise RF amplitude enough to create a low mass cutoff. Interesting idea, but would require some instrumentation changes.
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I imagine the coverage penalty will be pretty severe. For single cell, Trypsin peaks alone will cause significant issues when you spread them out (which you will with a tag solution). Also forgot to mention with mDIA you also have the challenge of mixing different cell types together like in TMT.
Yeah Astral would be good for this. NeuCode would be an attractive approach. You would need to make the tag version of the NeuCode amino acids. We had those at some point in the Coon Lab but I don’t think it was commercialized.
You could use NeuCode type of isotopolouges, but that requires very high resolution MS1 scans - which would take longer to acquire. 6-plex needed 1 million resolution. 4-plex needed 500 thousand resolution. So 0.5 to 1 second per MS1 in the Orbitrap.
Proteome depth will be a challenge because of this. Also, you adding back the complexity of labeling that is a major downside of multiplexed single cell (assuming this is the context). Like I said though, happy to be proven wrong, but I think the max is more realistically < 10 (likely 5 or 6).
Always happy to be proven wrong, but I don’t see how 100+ DIA will work. If each peptide was separated by 4 m/z a single peptide would cover a range of 400 m/z in the MS1. Even with fast instruments and narrow windows, you will struggle to sequence more than the most abundant peptides.
It is DIA. Targeted experiments (PRM) focus the center of the isolation window on the peptide of interest, use higher injection times, and peptide specific the CE. All of those improve sensitivity and selectivity. DIA is more generalized -isolation and the CE are not tailored to one specific peptide
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Not entirely unexpected - but still shocking to see! Mass spec folks may not have noticed, but non-mass spec based proteomics techniques are quite popular already and trending up. Thermo clearly saw this.
The challenge is always maintaining that trust. If you give back 20 hits and only 1 pans out…they might be slow to trust you in the future. But it all depend son how you approach it with them. It’s great l these discussions are happening! Hopefully you are enjoying your time down on the Cali coast!
Yeah, for sure. We tend to just be up front about the confidence of findings - at times we can work w/ collaborators to go into data that may not pass traditional FDR thresholds. But when we do that we are clear we are wading into dangerous territory and hopefully have some biology to justify it.
I agree with the last point…within reason. If the false positives are too high you will spend a lot of time and resources following up on false hits. If you are doing the follow up - maybe not a big deal. If others are doing follow up they might not appreciate it.
If I only had MS2 I probably would have been exploring DIA earlier than we are now because for a 10 fold ratio - getting a 4 fold ratio with MS2 is a lot more painful for me than getting 8 fold with MS3. I can with with a little ratio compression for the benefits of multiplexing.
It does take a while to optimize, once you have it dialed in it works well. I would say that TMT takes more effort on the front end (sample prep and acquisition) but data analysis on the back end is easier (unless you are crossing plexes).
You also have to make sure you get enough signal. We probably inject more ions than others but the quant will be better with more ions. MS3 methods became a lot easier with the real time search, it makes up a lot of the speed and allows you to get more accurate quant…wish they would add it to Lumos
Even with MS3 you have to be careful about how you make the methods. For example on the Lumos we always set very narrow ITMS2 windows (0.5 m/z) and then expanded to a charge dependent window for MS3. We narrowed the SPS isolation width and excluded certain parts of the MS2 range around the precursor
We almost always run MS3…except for single cell where with narrow isolations our single cell MS2 data and MS3 data correlate well, just with more compression in MS2. With the right real time search there isn’t much reason to do MS2. If you only have an Exploris, then yeah I would be careful.
We don’t optimize TMT kits as we should. I also haven’t done - rigorous cost comparison. If I did I would also need to factor in the costs of switching methods - retraining and added costs of data analysis. TMT data is very easy to analyze. Most of our workflows are are automated at this point
I have been looking at DIA papers and data and it appears common to have the first bar of identified proteins and a second bar of quantified proteins, but there doesn’t seem to be consensus on how that second bar is generated. Some folks use CV but that is potentially impacted by chemical noise.
The hardest thing to wrap my head around in DIA is when did you actually “quantify” something. For TMT it is a simple signal threshold for reporter ions. I haven’t seen data yet that makes me believe for 18 samples you can reach the same depth as TMT with DIA - but maybe I don’t know where to look.
Agreed! With the current trajectory it is clear that TMT will be losing out to some applications in the near future (although not completely gone). Hopefully the vendors see that too and the competition will drive some innovation on their part.
I still like what we can do with real-time search today. We have our own IAPI algorithms with custom protein closeout (limiting peptides per protein across runs), protein prioritization (e.g. preferentially sequencing mitochondrial proteins), and we have a preprint out on fixing hyperplexing.
It’s expensive…can’t argue with that. It is a great tool for the right situations, but I completely understand if some folks are priced out and cost is a non starter. Label free DDA and DIA is going to be hard to beat on sample prep cost.