Do you love your standard data dependent experiment, but hate the low level of reproducibility between technical replicates? If you answered "Yes!" then you really should check out this new paper out of Christine Wu's lab at Pitt.
In this study, the authors take a look at the weakness in the standard DDA experiment between technical replicates. Instead of relying only on peptides that were positively ID'ed in each run, they examined the XICs of the identified peptides from each individual run. The high accuracy MS1 and retention time from each identified peptide was compared to those of the other runs, even when sequencing information was not available from the second run.
By running the experiment and interpreting the data in this way, rather than at the level of mutually identified peptide IDs, no loss in peptide IDs are reported. The level of reproducibility between runs, however, increases dramatically.
As you'd expect from the names on this paper, the work is solid, thorough, and innovative. I strongly recommend that everyone doing shotgun proteomics take a look at this, because it isn't often that we get better results without compromising something (or spending more money!)
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