I have characterized a protein using cDNA cloning of its mRNA. I also have digested the protein using MALDI-TOF mass spec. Ideally I would have like to have done MALDI-TOF tandem MS, but it was not available at the time. So I have basically characterized it at the mRNA level, but I also have all this data of the peptide masses from digestion. Although I know this is not typical for characterization of this protein in other studies, it still provides some sort of confidence that the deduced sequence is valid at the protein level. I am wondering if it hurts more than helps to include these data in my findings or not, especially since a lot of effort and time went into retrieving them.
**I should also mention I was able to match the peptides to sequences using mascot. 100% coverage was achieved after using 3 different enzymes. Using this technique, peptide overlap, and homology with closely related species, I was able to get the same protein sequence as originally deduced.
I honestly think just having the peptide masses does not really help you to any answers. The masses can make you guess it's the right protein, but it does not prove your mRNA-sequence data the slightest. Only a sequence can prove a sequence. In order to get the sequence, you would have to sequence the protein in MS/MS. If you get 60% sequence from one digest, it is a good result, you would need probably 2-3 endoproteases and also would have to separate the peptides via LC first, that's a lot of Maldi spots to measure and analyse and there still is a good chance for missing peptides and half a sequence is as good as none. But be aware, most MS experts do only protein identification via peptide mapping today and no real sequencing anymore. It took me three attempts to find an MS core able to help me with my "very special" proteins, where they could help me and now after some training I will have to analyse the data myself.
If you put these data in a paper, you risk getting it to a Reviewer, who knows enough about MS to request some sequence data and then the work really starts. Trust me, depending on the protein, it can get you into serious trouble, Nobody providing that data before could either mean, it is not relevant for the field or it is the kind of trouble maker, I work on.
You can't publish everything, no matter how much you like it, if it doesn't fit in your papers story, you have to move on.
I should also mention I was able to match the peptides to sequences using mascot. 100% coverage was achieved after using 3 different enzymes.
For problems like that, we typically use different (unspecific) proteases (e.g. Elastase and Thermolysin in addition to Trypsin) to achieve full sequence coverage. NanoLC-MS/MS data can than be analyzed with PEAKS software, which does partially de novo sequencing, searches also for all UniMod modifications and is tolerant to amino acid substitutions. Finally it gives you a graphical alignment of all identified peptides to your protein sequence, which additionally helps you to find out, if parts of a protein are missing.
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