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Abstract Background Quantitative measurements of specific protein phosphorylation sites, as presented here, can be used to investigate signal transduction pathways, which is an important aspect of cell dynamics. The presented method quantitatively compares peptide abundances from experiments using 18O/16O labeling starting from elaborated MS spectra. It was originally developed to study signaling cascades activated by amyloid-β treatment of neurons used as a cellular model system with relevance to Alzheimer's disease, but is generally applicable. Results The presented method assesses, in complete cell lysates, the degree of phosphorylation of specific peptide residues from MS spectra using 18O/16O labeling. The abundance of each observed phospho-peptide from two cell states was estimated from three overlapping isotope contours. The influence of peptide-specific labeling efficiency was removed by performing a label swapped experiment and assuming that the labeling efficiency was unchanged upon label swapping. Different degrees of phosphorylation were reported using the fold change measure which was extended with a confidence interval found to reflect the quality of the underlying spectra. Furthermore a new way of method assessment using simulated data is presented. Using simulated data generated in a manner mimicking real data it was possible to show the method's robustness both with increasing noise levels and with decreasing labeling efficiency. Conclusion The fold change error assessable on simulated data was on average 0.16 (median 0.10) with an error-to-signal ratio and labeling efficiency distributions similar to the ones found in the experimentally observed spectra. Applied to experimentally observed spectra a very good match was found to the model (

Protein acetylation, which is central to transcriptional control as well as other cellular processes, is disrupted in Huntington's disease (HD). Treatments that restore global acetylation levels, such as inhibiting histone deacetylases (HDACs), are effective in suppressing HD pathology in model organisms. However, agents that selectively target the disease-relevant HDACs have not been available. SirT1 (Sir2 in Drosophila melanogaster) deacetylates histones and other proteins including transcription factors. Genetically reducing, but not eliminating, Sir2 has been shown to suppress HD pathology in model organisms. To date, small molecule inhibitors of sirtuins have exhibited low potency and unattractive pharmacological and biopharmaceutical properties. Here, we show that highly selective pharmacological inhibition of Drosophila Sir2 and mammalian SirT1 using the novel inhibitor selisistat (selisistat; 6-chloro-2,3,4,9-tetrahydro-1H-carbazole-1-carboxamide) can suppress HD pathology caused by mutant huntingtin exon 1 fragments in Drosophila, mammalian cells and mice. We have validated Sir2 as the in vivo target of selisistat by showing that genetic elimination of Sir2 eradicates the effect of this inhibitor in Drosophila. The specificity of selisistat is shown by its effect on recombinant sirtuins in mammalian cells. Reduction of HD pathology by selisistat in Drosophila, mammalian cells and mouse models of HD suggests that this inhibitor has potential as an effective therapeutic treatment for human disease and may also serve as a tool to better understand the downstream pathways of SirT1/Sir2 that may be critical for HD.

Pancreatic cancer stem-like cells are described by membrane expression of CD24, CD44 and ESA (epithelial-specific antigen) and their capacity to grow as spheres in a serum-free medium containing well-defined growth factors. The capacity of a panel of four pancreatic cancer cell lines (PANC-1, CFPAC-1, PancTu-1 and PSN-1) to form spheres was tested. All cell lines with the exception of PancTu-1 developed spheres. Phenotypically, the sphere-growing cells showed an increased in vitro invasion capability. Both gene and protein expressions of markers of metastases [CXCR4 (CXC chemokine receptor 4), OPN (osteopontin) and CD44v6] and components of active hedgehog pathway signalling were assessed. Spheres clearly demonstrated increased expression of the above-mentioned markers when compared with their adherent counterpart. With the aim of identifying a minimum set of markers able to separate cells that have the capacity to form spheres from those incapable of forming spheres, a PCA (principal component analysis) of the multidimensional dataset was performed. Although PCA of the 'accepted' stemness genes was unable to separate sphere-forming from sphere-incapable cell lines, the addition of the 'aggressiveness' marker CD44v6 allowed a clear differentiation. Moreover, inoculation of the spheres and the adherent cells in vivo confirmed the superior aggressiveness (proliferation and metastasis) of the spheres over the adherent cells. In conclusion, the present study suggests that the sphere-growing cell population is not only composed of cells displaying classical stem membrane markers but also needs CD44v6-positive cells to successfully form spheres. Our results also emphasize the potential therapeutic importance of pathways such as CXCR4 and hedgehog for pancreatic cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Quantitative measurements of specific protein phosphorylation sites, as presented here, can be used to investigate signal transduction pathways, which is an important aspect of cell dynamics. The presented method quantitatively compares peptide abundances from experiments using 18O/16O labeling starting from elaborated MS spectra. It was originally developed to study signaling cascades activated by amyloid-β treatment of neurons used as a cellular model system with relevance to Alzheimer's disease, but is generally applicable. Results: The presented method assesses, in complete cell lysates, the degree of phosphorylation of specific peptide residues from MS spectra using 18O/16O labeling. The abundance of each observed phospho-peptide from two cell states was estimated from three overlapping isotope contours. The influence of peptide-specific labeling efficiency was removed by performing a label swapped experiment and assuming that the labeling efficiency was unchanged upon label swapping. Different degrees of phosphorylation were reported using the fold change measure which was extended with a confidence interval found to reflect the quality of the underlying spectra. Furthermore a new way of method assessment using simulated data is presented. Using simulated data generated in a manner mimicking real data it was possible to show the method's robustness both with increasing noise levels and with decreasing labeling efficiency. Conclusion: The fold change error assessable on simulated data was on average 0.16 (median 0.10) with an error-to-signal ratio and labeling efficiency distributions similar to the ones found in the experimentally observed spectra. Applied to experimentally observed spectra a very good match was found to the model (<10% error for 85% of spectra) with a high degree of robustness, as assessed by data removal. This new method can thus be used for quantitative signal cascade analysis of total cell extracts in a high throughput mode. [ABSTRACT FROM AUTHOR]