Compositional protein analysis of high density lipoproteins in hypercholesterolemia by shotgun LC-MS/MS and probabilistic peptide scoring

A protein of a biological sample is usually quantified by immunological techniques based on antibodies. Mass spectrometry offers alternative approaches that are not dependent on antibody affinity and avidity, protein isoforms, quaternary structures, or steric hindrance of antibody-antigen recognition in case of multiprotein complexes. One approach is the use of stable isotope-labeled internal standards; another is the direct exploitation of mass spectrometric signals recorded by LC-MS/MS analysis of protein digests. Here we assessed the peptide match score summation index based on probabilistic peptide scores calculated by the PHENYX protein identification engine for absolute protein quantification in accordance with the protein abundance index as proposed by Mann and co-workers (Rappsilber, J., Ryder, U., Lamond, A. I., and Mann, M. (2002) Large-scale proteomic analysis of the human spliceosome. Genome Res. 12, 1231-1245). Using synthetic protein mixtures, we demonstrated that this approach works well, although proteins can have different response factors. Applied to high density lipoproteins (HDLs), this new approach compared favorably to alternative protein quantitation methods like UV detection of protein peaks separated by capillary electrophoresis or quantitation of protein spots on SDS-PAGE. We compared the protein composition of a well defined HDL density class isolated from plasma of seven hypercholesterolemia subjects having low or high HDL cholesterol with HDL from nine normolipidemia subjects. The quantitative protein patterns distinguished individuals according to the corresponding concentration and distribution of cholesterol from serum lipid measurements of the same samples and revealed that hypercholesterolemia in unrelated individuals is the result of different deficiencies. The presented approach is complementary to HDL lipid analysis; does not rely on complicated sample treatment, e.g. chemical reactions, or antibodies; and can be used for projective clinical studies of larger patient groups.

Novel prognostic markers revealed by a proteomic approach separating benign from malignant insulinomas.

The prognosis of pancreatic neuroendocrine tumors is related to size, histology and proliferation rate. However, this stratification needs to be refined further. We conducted a proteome study on insulinomas, a well-defined pancreatic neuroendocrine tumor entity, in order to identify proteins that can be used as biomarkers for malignancy. Based on a long follow-up, insulinomas were divided into those with metastases (malignant) and those without (benign). Microdissected cells from six benign and six malignant insulinomas were subjected to a procedure combining fluorescence dye saturation labeling with high-resolution two-dimensional gel electrophoresis. Differentially expressed proteins were identified using nano liquid chromatography-electrospray ionization/multi-stage mass spectrometry and validated by immunohistochemistry on tissue microarrays containing 62 insulinomas. Sixteen differentially regulated proteins were identified among 3000 protein spots. Immunohistochemical validation revealed that aldehyde dehydrogenase 1A1 and voltage-dependent anion-selective channel protein 1 showed significantly stronger expression in malignant insulinomas than in benign insulinomas, whereas tumor protein D52 (TPD52) binding protein was expressed less strongly in malignant insulinomas than in benign insulinomas. Using multivariate analysis, low TPD52 expression was identified as a strong independent prognostic factor for both recurrence-free and overall disease-related survival.

Identification of a new genomic hot spot of evolutionary diversification of protein function.

Establishment of phylogenetic relationships remains a challenging task because it is based on computational analysis of genomic hot spots that display species-specific sequence variations. Here, we identify a species-specific thymine-to-guanine sequence variation in the Glrb gene which gives rise to species-specific splice donor sites in the Glrb genes of mouse and bushbaby. The resulting splice insert in the receptor for the inhibitory neurotransmitter glycine (GlyR) conveys synaptic receptor clustering and specific association with a particular synaptic plasticity-related splice variant of the postsynaptic scaffold protein gephyrin. This study identifies a new genomic hot spot which contributes to phylogenetic diversification of protein function and advances our understanding of phylogenetic relationships.