In this issue: Proteomics 2/2009


Abstract

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

Spruce: things my father had taught and not taught me

Lesson No.1 “Never shake hands with a spruce” or more likely as a ten-year old, try to climb one. Spruce have more serious problems to deal with than little boys: bark beetles and the fungal pathogens that accompany them. Lippert et al. looked at both the proteomic and transcriptomic response to chitosan (fungal response elicitor analog) in cultured spruce cells (rather than in trees). Using iTRAQ for protein quantitation, the numbers and functions up- or down-regulated were very similar. The culture system gave a useful model in terms of the order and magnitude of responses. The statistical sampling model is carefully developed for maximum information from a minimum of replicate samples. It was surprising to learn that the first responses (calcium levels) occurred in less than 15 minutes. Fast response, trees!

Lippert, D. et al., Proteomics 2009, 9, 350–367.

(Pool vs. parts): sum of the differences

One of the more challenging problems in using 2-D DIGE for quantitative proteomics is determining the source of statistical variability: biological vs. technical. Karp and Lilley decouple the two by beginning with the assumption that measurements of the pool equal the average of measurements of the individuals. Furthermore, the SD of the biological noise will be greater than the SD of the technical noise because it includes the technical noise. Experimental tests were performed on a whole mouse brain/human brain prefrontal cortex system. They found that technical noise dominated mouse brain while biological noise dominated human brain samples. Sub-pooling is appropriate when samples will not be used again later for “unplanned questions”. It may not be useful if transformations are applied to deal with outliers or nonlinearities resulting from sample processing. Power analysis can also be used to judge effects and costs of experimental designs.

Karp, N. and Lilley, K., Proteomics 2009, 9, 388–397.

Improving our laser carving results

Laser microdissection enables you to subsection a cryosection to do nano-scale 2-D DIGE analysis on sub-fractions of organs, organelles and tumors. But there's not much left to look at in the end so Kirana et al. went looking for points to improve and found several. Substituting toluidine blue for H&E gave good structure visibility with the added benefits of washing out and improving protein recovery when preparing samples for 2-D DIGE. Labeling for DIGE with CyDyes was markedly improved by modifying the supplier's clean-up kit protocol from one cycle to two. Use of the kit post-labeling also enhanced basic protein separations.

Kirana, C. et al., Proteomics 2009, 9, 485–490.

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