ApoE4 disrupts interaction of sortilin with fatty acid-binding protein 7 essential to promote lipid signaling.

Sortilin is a neuronal receptor for apolipoprotein E (apoE). Sortilin-dependent uptake of lipidated apoE promotes conversion of polyunsaturated fatty acids (PUFA) into neuromodulators that induce anti-inflammatory gene expression in the brain. This neuroprotective pathway works with the apoE3 variant but is lost with the apoE4 variant, the main risk factor for Alzheimer's disease (AD). Here, we elucidated steps in cellular handling of lipids through sortilin, and why they are disrupted by apoE4. Combining unbiased proteome screens with analyses in mouse models, we uncover interaction of sortilin with fatty acid-binding protein 7 (FABP7), the intracellular carrier for PUFA in the brain. In the presence of apoE3, sortilin promotes functional expression of FABP7 and its ability to elicit lipid-dependent gene transcription. By contrast, apoE4 binding blocks sortilin-mediated sorting, causing catabolism of FABP7 and impairing lipid signaling. Reduced FABP7 levels in the brain of AD patients expressing apoE4 substantiate the relevance of these interactions for neuronal lipid homeostasis. Taken together, we document interaction of sortilin with mediators of extracellular and intracellular lipid transport that provides a mechanistic explanation for loss of a neuroprotective lipid metabolism in AD.

Phosphoproteomic insights into processes influenced by the kinase-like protein DIA1/C3orf58.

Many kinases are still 'orphans,' which means knowledge about their substrates, and often also about the processes they regulate, is lacking. Here, DIA1/C3orf58, a member of a novel predicted kinase-like family, is shown to be present in the endoplasmic reticulum and to influence trafficking via the secretory pathway. Subsequently, DIA1 is subjected to phosphoproteomics analysis to cast light on its signalling pathways. A liquid chromatography-tandem mass spectrometry proteomic approach with phosphopeptide enrichment is applied to membrane fractions of DIA1-overexpressing and control HEK293T cells, and phosphosites dependent on the presence of DIA1 are elucidated. Most of these phosphosites belonged to CK2- and proline-directed kinase types. In parallel, the proteomics of proteins immunoprecipitated with DIA1 reported its probable interactors. This pilot study provides the basis for deeper studies of DIA1 signalling.

Urine proteome of autosomal dominant polycystic kidney disease patients.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is responsible for 10% of cases of the end stage renal disease. Early diagnosis, especially of potential fast progressors would be of benefit for efficient planning of therapy. Urine excreted proteome has become a promising field of the search for marker patterns of renal diseases including ADPKD. Up to now however, only the low molecular weight fraction of ADPKD proteomic fingerprint was studied. The aim of our study was to characterize the higher molecular weight fraction of urinary proteome of ADPKD population in comparison to healthy controls as a part of a general effort aiming at exhaustive characterization of human urine proteome in health and disease, preceding establishment of clinically useful disease marker panel. RESULTS: We have analyzed the protein composition of urine retentate (>10 kDa cutoff) from 30 ADPKD patients and an appropriate healthy control group by means of a gel-free relative quantitation of a set of more than 1400 proteins. We have identified an ADPKD-characteristic footprint of 155 proteins significantly up- or downrepresented in the urine of ADPKD patients. We have found changes in proteins of complement system, apolipoproteins, serpins, several growth factors in addition to known collagens and extracellular matrix components. For a subset of these proteins we have confirmed the results using an alternative analytical technique. CONCLUSIONS: Obtained results provide basis for further characterization of pathomechanism underlying the observed differences and establishing the proteomic prognostic marker panel.

Diffprot - software for non-parametric statistical analysis of differential proteomics data.

Mass spectrometry-based global proteomics experiments generate large sets of data that can be converted into useful information only with an appropriate statistical approach. We present Diffprot - a software tool for statistical analysis of MS-derived quantitative data. With implemented resampling-based statistical test and local variance estimate, Diffprot allows to draw significant results from small scale experiments and effectively eliminates false positive results. To demonstrate the advantages of this software, we performed two spike-in tests with complex biological matrices, one label-free and one based on iTRAQ quantification; in addition, we performed an iTRAQ experiment on bacterial samples. In the spike-in tests, protein ratios were estimated and were in good agreement with theoretical values; statistical significance was assigned to spiked proteins and single or no false positive results were obtained with Diffprot. We compared the performance of Diffprot with other statistical tests - widely used t-test and non-parametric Wilcoxon test. In contrast to Diffprot, both generated many false positive hits in the spike-in experiment. This proved the superiority of the resampling-based method in terms of specificity, making Diffprot a rational choice for small scale high-throughput experiments, when the need to control the false positive rate is particularly pressing.

Classification of peptide mass fingerprint data by novel no-regret boosting method.

We have developed an integrated tool for statistical analysis of large-scale LC-MS profiles of complex protein mixtures comprising a set of procedures for data processing, selection of biomarkers used in early diagnostic and classification of patients based on their peptide mass fingerprints. Here, a novel boosting technique is proposed, which is embedded in our framework for MS data analysis. Our boosting scheme is based on Hannan-consistent game playing strategies. We analyze boosting from a game-theoretic perspective and define a new class of boosting algorithms called H-boosting methods. In the experimental part of this work we apply the new classifier together with classical and state-of-the-art algorithms to classify ovarian cancer and cystic fibrosis patients based on peptide mass spectra. The methods developed here provide automatic, general, and efficient means for processing of large scale LC-MS datasets. Good classification results suggest that our approach is able to uncover valuable information to support medical diagnosis.

An integrated LC-ESI-MS platform for quantitation of serum peptide ladders. Application for colon carcinoma study.

Mounting evidence indicates that MS analysis of the human blood peptidome allows to distinguish between cancer and non-cancer samples, giving promise for a new MS-based diagnostic tool. However, several aspects of already published work have been criticized and demand for more methodical approach has been formulated. Motivated by this we undertook a systematic study of the plasma and serum peptidome using an integrated ESI-LC-MS-based platform, equipped with new data analysis tools for relative and absolute peptide quantitation. We used a high resolution LC-ESI-MS to analyze well-separated MS signals corresponding to peptides, and measured the variability of >1000 peptide signal amplitudes across a set of plasma and serum samples from healthy individuals. By spiking serum samples with known amounts of isotopically labeled versions of a selected set of peptides we measured the variability of their absolute concentration in this sample set and demonstrated a strong influence of clotting time on the concentration of these peptides in serum. Finally, we used this new LC-ESI-MS analytical platform for the differential analysis of healthy versus colon cancer serum samples and found that it was possible to distinguish the two groups with 89.8% sensitivity and 94.6% specificity.