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

Sortilin is a neuronal receptor for apolipoprotein E. 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 apoE3 but is lost with apoE4, 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 (FABP) 7, 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 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

Comparative kinome analysis to identify putative colon tumor biomarkers

Kinase domains are the type of protein domain most commonly found in genes associated with tumorigenesis. Because of this, the human kinome (the protein kinase component of the genome) represents a promising source of cancer biomarkers and potential targets for novel anti-cancer therapies. Alterations in the human colon kinome during the progression from normal colon (NC) through adenoma (AD) to adenocarcinoma (AC) were investigated using integrated transcriptomic and proteomic datasets. Two hundred thirty kinase genes and 42 kinase proteins showed differential expression patterns (fold change ≥ 1.5) in at least one tissue pair-wise comparison (AD vs. NC, AC vs. NC, and/or AC vs. AD). Kinases that exhibited similar trends in expression at both the mRNA and protein levels were further analyzed in individual samples of NC (n = 20), AD (n = 39), and AC (n = 24) by quantitative reverse transcriptase PCR. Individual samples of NC and tumor tissue were distinguishable based on the mRNA levels of a set of 20 kinases. Altered expression of several of these kinases, including chaperone activity of bc1 complex-like (CABC1) kinase, bromodomain adjacent to zinc finger domain protein 1B (BAZ1B) kinase, calcium/calmodulin-dependent protein kinase type II subunit delta (CAMK2D), serine/threonine-protein kinase 24 (STK24), vaccinia-related kinase 3 (VRK3), and TAO kinase 3 (TAOK3), has not been previously reported in tumor tissue. These findings may have diagnostic potential and may lead to the development of novel targeted therapeutic interventions for colorectal cancer

The trace fossil Lepidenteron lewesiensis: a taphonomic window on diversity of Late Cretaceous fishes

The trace fossil Lepidenteron lewesiensis (Mantell 1822) provides an exceptional taphonomic window to diversity of fishes as shown for the Upper Cretaceous of Poland, in the Middle Turonian–Lower Maastrichtian deposits of the Opole Trough, Miechów Trough, Mazury-Podlasie Homocline, and SE part of the Border Synclinorium. Lepidenteron lewesiensis is an unbranched burrow lined with small fish scales and bones, without a constructed wall. It contains scales, vertebrae, and bones of the head belonging to ten taxa of teleostean fishes: two undetermined teleosteans, six undetermined Clupeocephala, one Dercetidae, and one undetermined euteleostean. The preservation of fish remains suggests that fishes were pulled down into the burrow by an animal, probably by eunicid polychaetes.Das Spurenfossil Lepidenteron lewesiensis (Mantell 1822) ermöglicht einen biostratinomischen Einblick in die Diversität von Fischen, wie Fossilmaterial aus der Oberkreide von Polen zeigt. Es stammt aus dem Mittelturonium bis Untermaastrichtium des südöstlichen Abschnittes der Grenz-Synklinale, dem Opolen-Trog, dem Miechów-Trog und der Masuren-Podlachien-Homoklinale. L. lewesiensis ist ein unverzweigter Grabgang ohne ausgekleidete Wände, dessen Ränder von kleinen Fischschuppen und—knochen gebildet werden. Diese setzen sich aus Schuppen, Wirbel und Schädelknochen von zehn Teleostei-Taxa zusammen und zwar aus zwei unbestimmte Teleosteer, sechs unbestimmten Clupeocephala, einem Dercetidae und einem unbestimmten Euteleostei. Die Erhaltung der Fischüberreste deutet darauf hin, dass die Fische von einem Tier, wahrscheinlich einem Polychaeten der Familie Eunicidae, in den Bau gezogen wurden.We are very grateful to Dr. Lionel Cavin (Geneva) and the anonymous reviewer for constructive comments on an earlier version of the manuscript. Additional support was provided by the Jagiellonian University (DS funds), National Science Center (Grant Number: PRO-2011/01/N/ST10/07717), and the Laboratory of Geology (University of Lodz) BSt Grant No. 560/844. We are grateful to Dr. Johann Egger (Wien) and Kilian Eichenseer M.Sc. (Erlangen) for help with translating the abstract into German. We are grateful to Dr. Ursula Göhlich (Wien) for access to the Dercetis specimen

Comput. Biol. Med.

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