Cover Picture: Proteomics 10'11

Been workin' on the concatenation gang, all the live‐long day Givin' the man 15 for 1 throughput as I sweat away… I hope you aren't working too far from the air conditioner because this proteomic 2‐D LC procedure is smokin' hot. In brief, Wang et al. re‐examined the selection of first‐dimension RPLC buffers to come up with one with markedly improved resolution properties. In particular, it was the pH that mattered most – substituting a high pH RPLC (pH 7.5) identified 30% more phosphopeptides than conventionally detected with a strong cation exchanger. Then they found that they could concatenate first‐dimension fractions with second‐dimension buffers for more efficient use for chromatography space. Plus, there's a fringe benefit – no sample desalting is required for the high pH RPLC buffer – a great time‐saver for shotgun proteome researchers. Wang, Y. et al., Proteomics 2011, 11 , 2019–2026. A self‐starting, spot‐spotting, mixture‐modeling package released It sounds ominous, but there are no reports of terabytes terrorizing the people of Athens. There is some talk among the petabytes of picketing the pedestrian path from the port to the Parthenon – the pickpockets can't keep up with the parade of passengers seeking Drs Tsakanikas and Manolakos. These two have taken a different approach to matching spots from 2‐DE gels – a protocol that, after initialization, does not require manual calibration or adjustment for successive scans – it teaches itself in an unsupervised learning mode. (Warning: equations ahead.) An intensity histogram identifies the number of mixture models required. Pixels are sorted by mode level and Bayes thresholding. This eliminates local background streaks and non‐informative pixels and, after agglomerative hierarchical clustering (!), yields a dendrogram that is then trimmed and pruned. Unique is the use of random sampling of model data rather than raw peak data for analysis. This new procedure was tested against PDQuest. Tsakanikas, P. and Manolakos, E. S., Proteomics 2011, 11 , 2038–2050. Raw, raw, raw. Sis, boom, bah… ( basketball cheer, ca. 1918 ) Cheering for one's favorite team is thought to improve performance. It would be interesting to test the hypothesis...on someone else's nickel. Here we have a technical brief on a software package from Holenya et al. that conveniently accepts .raw data for analysis. Where does the data come from? From a multiplex array procedure for analysis of protein phosphorylation sites, using a very sensitive modified kinetic ELISA procedure. With a 1 pg lower limit of detection and 20 000 pg upper limit of detection (depending on the protein), the detection curve was non‐linear. The non‐parametric regression model Gaussian Random Process Regression was applied for calibration surface generation. Holenya, P. et al., Proteomics 2011, 11 , 2129–2133.