Although the mechanism of Aβ action in the pathogenesis of Alzheimer's disease (AD) has remained elusive, it is known to increase the expression of the antagonist of canonical wnt signalling, Dickkopf-1 (Dkk1), whereas the silencing of Dkk1 blocks Aβ neurotoxicity. We asked if clusterin, known to be regulated by wnt, is part of an Aβ/Dkk1 neurotoxic pathway. Knockdown of clusterin in primary neurons reduced Aβ toxicity and DKK1 upregulation and, conversely, Aβ increased intracellular clusterin and decreased clusterin protein secretion, resulting in the p53-dependent induction of DKK1. To further elucidate how the clusterin-dependent induction of Dkk1 by Aβ mediates neurotoxicity, we measured the effects of Aβ and Dkk1 protein on whole-genome expression in primary neurons, finding a common pathway suggestive of activation of wnt–planar cell polarity (PCP)–c-Jun N-terminal kinase (JNK) signalling leading to the induction of genes including EGR1 (early growth response-1), NAB2 (Ngfi-A-binding protein-2) and KLF10 (Krüppel-like factor-10) that, when individually silenced, protected against Aβ neurotoxicity and/or tau phosphorylation. Neuronal overexpression of Dkk1 in transgenic mice mimicked this Aβ-induced pathway and resulted in age-dependent increases in tau phosphorylation in hippocampus and cognitive impairment. Furthermore, we show that this Dkk1/wnt–PCP–JNK pathway is active in an Aβ-based mouse model of AD and in AD brain, but not in a tau-based mouse model or in frontotemporal dementia brain. Thus, we have identified a pathway whereby Aβ induces a clusterin/p53/Dkk1/wnt–PCP–JNK pathway, which drives the upregulation of several genes that mediate the development of AD-like neuropathologies, thereby providing new mechanistic insights into the action of Aβ in neurodegenerative diseases.
More than 100 point mutations spanning the 153 amino acid SOD1 sequence have been identified in individuals with ALS. In 1999 the Amyotrophic Lateral Sclerosis Database (ALSOD) was generated to store these mutations along with ALS patient information to facilitate the identification of a correlation between the SOD1 genotype with the ALS phenotype. Here we report our ongoing development and redesign of the ALSOD database and its automated procedures. The significant new features have improved ALSOD, helping link the mutations of the SOD1 gene to the hypothetical three-dimensional protein structural rearrangement, and the resulting ALS phenotype. Additionally, ALSOD now provides a more comprehensive knowledge base for ALS, detailing genetic, proteomic, and bioinformatics information associated with the disease. ALSOD can be accessed at http://alsod.iop.kcl.ac.uk/als/.
Understanding the evolution of biopolymers is a key element in rationalizing their structures and functions. Simple exact models (SEMs) are well-positioned to address general principles of evolution as they permit the exhaustive enumeration of both sequence and structure (conformational) spaces. The physics-based models of the complete mapping between genotypes and phenotypes afforded by SEMs have proven valuable for gaining insight into how adaptation and selection operate among large collections of sequences and structures. This study compares the properties of evolutionary landscapes of a variety of SEMs to delineate robust predictions and possible model-specific artifacts. Among the models studied, the ruggedness of evolutionary landscape is significantly model-dependent; those derived from more protein-like models appear to be smoother. We found that a common practice of restricting protein structure space to maximally compact lattice conformations results in (i.e., "designs in") many encodable (designable) structures that are not otherwise encodable in the corresponding unrestrained structure space. This discrepancy is especially severe for model potentials that seek to mimic the major role of hydrophobic interactions in protein folding. In general, restricting conformations to be maximally compact leads to larger changes in the model genotype-phenotype mapping than a moderate shifting of reference state energy of the model potential function to allow for more specific encoding via the "designing out" effects of repulsive interactions. Despite these variations, the superfunnel paradigm applies to all SEMs we have tested: For a majority of neutral nets across different models, there exists a funnel-like organization of native stabilities for the sequences in a neutral net encoding for the same structure, and the thermodynamically most stable sequence is also the most robust against mutation.
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