A hypothetical question. I have two closely related plants. One is suspected to lack a certain protein present in the other. How difficult is it to discover this difference in the following situations:
A.) I know the exact amino acid sequence of the protein that should be lacking
B.) I have no idea which protein is lacking, I do not know its sequence
The task needs to be completed without the use of transcriptome or DNA analysis, only by the means of proteomics (Mass spectometry, Protein Electrophoresis, Western blot e.t.c)
Which methods should I use? How reliable are they? How long will it take?
In what case will this task be the most difficult to accomplish?
if you have a good antibody to the protein, western blotting should be sufficient to give you the answer you're looking for.
Mass spectrometry should work too, if you know the sequence of the protein - all you have to do is look for the presence or absence of unique peptides.
For case B - this seems very random; I'm not sure what exactly you mean. Does the protein exist at all (i.e. is it in databases / ORF translations) or are you merely speculating? If your protein is in standard databases like UniProt (even if there is no experimental evidence that the protein exists), you can use mass spectrometry to tell you if it is absent in your sample relative to another sample.
if you have a good antibody to the protein, western blotting should be sufficient to give you the answer you're looking for.
Mass spectrometry should work too, if you know the sequence of the protein - all you have to do is look for the presence or absence of unique peptides.
For case B - this seems very random; I'm not sure what exactly you mean. Does the protein exist at all (i.e. is it in databases / ORF translations) or are you merely speculating? If your protein is in standard databases like UniProt (even if there is no experimental evidence that the protein exists), you can use mass spectrometry to tell you if it is absent in your sample relative to another sample.
I think in the case A you could use the increasingly popular targeted proteomics (http://www.nature.com/nmeth/journal/v10/n1/full/nmeth.2285.html). Especially since you know the protein quite well in that context.
Case B is a little bit more tricky, but still feasible. If you want to have an easy, fast way of getting an idea of what's missing in your sample, you could do a proteomics analysis and a database search on both, then use a simple spectral count (maybe only on unique peptides to avoid having to deal with protein inference) to determine the differences between both. It's not perfect, but it can help you along the way of detecting "markers" for your abscent proteins.
SearchGUI (https://code.google.com/p/searchgui/) and PeptideShaker (https://code.google.com/p/peptide-shaker/) are a very powerful tandem that can form a pipeline to handle this. Contact me if you want more information on how to do this.
Cheers and good luck,
Kenneth
you can use quantitative proteomics to analysis the protein samples from these two plants, I suggest you to use the label free method, this is easy and fast. And a lot of research centers provide this service. Hope this helps
I thank everyone for their responses. Vikram, case B was indeed speculative and more theoretical than practical. We are not sure if an extra protein exists in the sample, and if it does - we are not sure what the protein is, but we want to check for it anyway. For example, if want to use proteomics (not genomics) to detect an event of random lateral gene transfer from an unknown source. Genome analysis would be simpler in most cases, but as i said my question is more theoretical. I just wanted to know what are the current capabilities of modern proteomics in this aspect.
Regarding the case B, I suggest you differential proteome analysis using 2D-DIGE. Briefly, by this method samples to be compared are labeled by CyDye (Cy 3 or 5) and Cy 2 CyDye DIGE fluor is employed to label a pooled sample comprising equal amounts of each of the samples (acting as internal standards). This approach may allow you the measurement of subtle protein expressional differences among your samples with a good statistical confidence.
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