PROTEOMICS

Cover image for Vol. 17 Issue 10

Editor-in-Chief: Lorna Stimson, Deputy Editor: Lucie Kalvodova

Impact Factor: 4.079

ISI Journal Citation Reports © Ranking: 2015: 13/77 (BIOCHEMICAL RESEARCH METHODS); 75/289 (Biochemistry & Molecular Biology)

Online ISSN: 1615-9861

Associated Title(s): PROTEOMICS - Clinical Applications

8_21/2008Cover Picture: Proteomics 21/2008

In this issue of Proteomics you will find the following highlighted articles:

When doing your best is too good

Sometimes it pays to go back and question your assumptions, particularly if you are about to embark on a project with a lot of samples to process and analyze and, more particularly, if the instrumentation has changed substantially in the mean time. Villén et al. found a surprise at the end of their reevaluation of phosphopeptide identification. To start, they thought that the availability of 2–D and 3–D ion traps and high accuracy, high sensitivity would speed the process along substantially. Not so. First, neutral losses threatened to swamp out the MS2 spectrum from the 3–D ion trap, then they almost washed out the b– and y–type ions that comprise a critical internal ruler. The overabundance could be attenuated by using a new data dependent neutral loss MS3 method with 3–D ion traps. However, switching to high resolution ion traps reduced spectrum collection speed. . . Compromise time.

Villén, J et al., Proteomics 2008, 8, 4444–4452.

TGFbeta: a triskadecapoidal growth/ungrowth factor?

One thing proteins do much more effectively than nucleic acids is multi–tasking. But they also start with a much larger tool chest – 20 amino acids vs. 4 nucleotides; dozens of post–translational modification possibilities vs. a few methylation sites. . . Transforming growth factor b takes advantage of its flexibility very effectively in regulating at least eight different cell functions simultaneously. Bhaskaran et al. applied proteomic analysis (2–DE) to a human breast epithelial cell line after exposure to TGFb for various periods. Changes were detected by monitoring incorporation of 35[S–]methionine and 35[S–]cysteine compared to silver stain. In MCF10A cells, 1200 proteins were identified by staining and 1400 spots by metabolic labeling. Interestingly, not just one regulatory protein was activated per pathway, asmany as 13 regulators from both positive and negative complimentary functions were activated (e.g. pro– and anti–proliferative). Fromhere the story just gets better. Erk! Src!

Bhaskaran,N. et al., Proteomics 2008, 8, 4507–4520.

Protein microarrays and stopwatches

Reality intrudes upon our research from time to time, like it or not, usually when someone from outside says “Really?” with a certain tone of voice that means “Can you prove that statement?” Korf et al. describe here a wellgrounded procedure for determining theamount and rate of phosphorylation of regulatory factors. The microarray format of the antibody capture probe assay minimizes the amount of protein required (about 5% of that needed for immunoblots) and the protocol assures reliable results through a careful matching of capture and reporter antibody pairs. The researchers estimate that less than 5 6 104 cells are required for phosphoprotein detection. Kinetics ofphosphorylationwere followedbysampling at intervalsof aminute. The systems analyzed were Erk1/2 and cell line BaF3, an erythropoetin receptor positive line, and fetal mouse liver erythroid colony forming cells. A software package based on R was customized for analysis of protocol data.

Korf, U. et al., Proteomics 2008, 8, 4603–4612.

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