Hello, I am proteomics researcher.
we got stuck in problem detecting immunopeptidome HLA class peptides.
After, enriching peptides, we detect 150 ng/ul concentration of peptide using nanodrop (protein A 280 mode).
and about 750ng of peptides were injected to mass spectrometer. (our mass spectrometer is tims-tof, so if we inject 200ng of HeLa peptide, 40000 peptides can be detected.)
However, 100 peptides were detected in our HLA sample. Furthermore, intensity of peptides signal is low...
why is a large amount of peptides detected in the nanodrops although there seems to be a small amount of peptides in mass spectrometry data?
I heard that A 280 mode in nanodrop detect peptide concentration by measuring tryptophan or tyrosine.
is it possible there are many free tryptophan and tyrosine in the sample, so it make nanodrop conecntration high but not be detected in mass spectrometer?
If you have any idea, please let me know
thank you very much
Hi Jaekwan,
can I ask for the search parameters in the software used for the spectra from your LC-MS analysis. Did you used the same parameters for HLA class peptides and HeLa peptides?
Best,
Murat
Murat Eravci
Mrat, Thanks for reply.
I used the same parameters for HLA class peptides and HeLa peptides.
below is our parameters in the PEAKS 10.5 studio.
The raw files were processed using Peaks 10.5 software and matched to peptide fragment from the homo sapiens protein sequence with a maximum number of allowed missed cleavages of 100 and no enzyme digestion. Mass tolerance was set as 15 ppm and 0.05 Da for precursor and fragment ions respectively. The variable modification included methionine oxidation and N-terminal acetylation. The false discovery rate (FDR) was set at 0.01 for peptide.
Hi Jaekwan,
first thing, If you select the no enzyme digestion mode it doesn't makes sense to set for any missed cleavage, but I don't think that this will have any issue on the number of identified peptides.
If you consider that the statistical calculation of HLA class peptides is much harder than for digested peptides (where both, N-and C-termini of the peptides are known beforehands) I would suggest to increase the number of identifications by changing the FDR from 1% (0.01) to 5% (0.05).
Another thing that you can try is, to set the digestion mode from no enzyme digestion to unspecific digestion since you are searching against homo sapiens DB (if I get this right) istead of using an HLA peptide atlas DB.
Best,
Murat
Murat Eravci
Thank you Murat, your suggestion is acute. I will do what you suggested.
Murat, before LC-MS and data processing, i think there is also sample preparation problem as the number of denovo peptides is very small.
Have you tried HLA peptidome experiment?
If you did, how many peptides were detected?
and what is your database homo sapiens or HLA peptide atlas?
Hi Jaekwon,
yes I have collaborated on some experiments on HLA peptides. My part was the LC-MS analysis of samples provided by collaborators. This was some years ago in a previous position and unfortuneatly I have no access to this data anymore so that I can not provide any info on the number of identified peptides. For this experiments I have analysed all MS raw data with Maxquant against the homo sapiens reference proteome from uniprot with "unspecific" for the digestion mode.
I have never worked with a peptide atlas for HLA peptides but I remeber to read some publications of researchers using that type of databases. Maybe you can search for this via pubmed.
Best,
Murat
Murat Eravci
Thank you for your kind reply.
I will try searching HLA peptide atlas.
Best regards
Jaekwan.
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