Label-free quantification of membrane proteins

Measuring expression changes of membrane proteins can be a challenge but they are the source of important molecular processes in disease progression. The group of Marius Ueffing (Department of Protein Science, Helmholtz Zentrum München) have shown that, with the right approach and our quantify then identify workflow, you can generate highly-sensitive, reproducible label-free quantification of membrane proteins. They used this approach to define the proteins and novel pathways involved in equine retinal uveitis (ERU) and the results have just been published in MCP.

Incidentally, this is one of several groups I’ve talked to doing equine based research. It’s a well funded field and, as I’ve learnt, it’s a good animal model with high variability that resembles human patient-to-patient variability.

ERUThe group of Marius Ueffing (Department of Protein Science, Helmholtz Zentrum München) uncover molecular mechanisms of autoimmune uveitis using Progenesis LC-MS

The paper also showed how the researchers have applied the quantify then identify workflow as well using inclusion lists generated by Progenesis LC-MS to build up proteome identification in a targeted way. Stephanie Hauk et al described this well in the methods section:

“After quantification of peptides, those features not having a MS/MS scan from the initial samples run were exported to Excel and used as an inclusion list for a replicate run of samples on the Orbitrap. Resulting raw data files were aligned to the experiments in Progenesis LC-MS and additional MS/MS scans resulting from these measurements were added to the previous ones; however the original quantifications and statistics were not changed.”

This is a neat workflow within Progenesis LC-MS that you can use to enhance your differential protein expression or protein characterisation analysis results. If you’re already a user and not sure how to do this, contact us, and if you haven’t seen Progenesis LC-MS before you can get an evaluation on your own data today.

Assessing technical reproducibility

An important aspect of any proteomic technique is how reproducible it is and, as founders of The Fixing Proteomics Campaign, it’s something we believe is important. So it was nice to see how the team in Munich had assessed this.

LC-MS analysis of three technical replicates from membrane enriched samples of retinal tissue from one healthy and one ERU subject was carried out. Variation between cumulative peptide intensities for each identified protein in those replicate measurements was “considered low” with CVs of 17.1% and 11.2% respectively. They also found high reproducibility of protein identifications. 885 proteins were identified in all three replicates (99.1% of all protein identifications) of healthy and 887 (99.3%) of ERU tissue.

To suggest the variation of peptide intensity measurement was low, the research team compared this variability to a recently published study involving enrichment strategies (1) that cited a CV of up to 30% as reproducible.

From reading this, I’d say the non-gel based proteomics community need to catch up with the success of 2D-gel proteomics, which has been shown to be highly reproducible within and across-labs using Progenesis SameSpots 🙂

 

(1) Albrethsen, J., Knol, J. C., Piersma, S., Pham, T. V., de Wit, M., Mongera, S., Carvalho, B., Verheul, H. M., Fijneman, R. J., Meijer, G. A., and Jimenez, C. R. (2010) Sub-nuclear proteomics in colorectal cancer: Identification of proteins enriched in the nuclear matrix fraction and regulation in adenoma to carcinoma progression. Mol Cell Proteomics 5, pp. 988-1005

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