Presenilin-1 regulates induction of hypoxia inducible factor-1α: altered activation by a mutation associated with familial Alzheimer's disease

<p>Abstract</p> <p>Background</p> <p>Mutations in presenilin-1 (<it>Psen1</it>) cause familial Alzheimer's disease (FAD). Both hypoxia and ischemia have been implicated in the pathological cascade that leads to amyloid deposition in AD. Here we investigated whether Psen1 might regulate hypoxic responses by modulating induction of the transcription factor hypoxia inducible factor 1-α (HIF-1α).</p> <p>Results</p> <p>In fibroblasts that lack Psen1 induction of HIF-1α was impaired in response to the hypoxia mimetic cobalt chloride, as well as was induction by insulin and calcium chelation. Reintroduction of human Psen1 using a lentiviral vector partially rescued the responsiveness of <it>Psen1-/- </it>fibroblasts to cobalt chloride induction. HIF-1α induction did not require Psen1's associated γ-secretase activity. In addition, the failure of insulin to induce HIF-1α was not explicable on the basis of failed activation of the phosphatidylinositol 3-kinase (PI3K/Akt) pathway which activated normally in <it>Psen1-/- </it>fibroblasts. Rather we found that basal levels of HIF-1α were lower in <it>Psen1-/- </it>fibroblasts and that the basis for lower constitutive levels of HIF-1α was best explained by accelerated HIF-1α degradation. We further found that Psen1 and HIF-1α physically interact suggesting that Psen1 may protect HIF-1α from degradation through the proteasome. In fibroblasts harboring the M146V Psen1 FAD mutation on a mouse Psen1 null background, metabolic induction of HIF-1α by insulin was impaired but not hypoxic induction by cobalt chloride. Unlike <it>Psen1-/- </it>fibroblasts, basal levels of HIF-1α were normal in FAD mutant fibroblasts but activation of the insulin-receptor pathway was impaired. Interestingly, in <it>Psen1-/- </it>primary neuronal cultures HIF-1α was induced normally in response to cobalt chloride but insulin induction of HIF-1α was impaired even though activation of the PI3K/Akt pathway by insulin proceeded normally in <it>Psen1-/- </it>neuronal cultures. Basal levels of HIF-1α were not significantly different in <it>Psen1-/- </it>neurons and HIF-1α levels were normal in <it>Psen1-/- </it>embryos.</p> <p>Conclusions</p> <p>Collectively these studies show that Psen1 regulates induction of HIF-1α although they indicate that cell type specific differences exist in the effect of Psen1 on induction. They also show that the M146V Psen1 FAD mutation impairs metabolic induction of HIF-1α, an observation that may have pathophysiological significance for AD.</p

The PsychENCODE project

Recent research on disparate psychiatric disorders has implicated rare variants in genes involved in global gene regulation and chromatin modification, as well as many common variants located primarily in regulatory regions of the genome. Understanding precisely how these variants contribute to disease will require a deeper appreciation for the mechanisms of gene regulation in the developing and adult human brain. The PsychENCODE project aims to produce a public resource of multidimensional genomic data using tissue- and cell type–specific samples from approximately 1,000 phenotypically well-characterized, high-quality healthy and disease-affected human post-mortem brains, as well as functionally characterize disease-associated regulatory elements and variants in model systems. We are beginning with a focus on autism spectrum disorder, bipolar disorder and schizophrenia, and expect that this knowledge will apply to a wide variety of psychiatric disorders. This paper outlines the motivation and design of PsychENCODE

Dependencies among Editing Sites in Serotonin 2C Receptor mRNA

<div><p>The serotonin 2C receptor (5-HT_2CR)–a key regulator of diverse neurological processes–exhibits functional variability derived from editing of its pre-mRNA by site-specific adenosine deamination (A-to-I pre-mRNA editing) in five distinct sites. Here we describe a statistical technique that was developed for analysis of the dependencies among the editing states of the five sites. The statistical significance of the observed correlations was estimated by comparing editing patterns in multiple individuals. For both human and rat 5-HT_2CR, the editing states of the physically proximal sites A and B were found to be strongly dependent. In contrast, the editing states of sites C and D, which are also physically close, seem not to be directly dependent but instead are linked through the dependencies on sites A and B, respectively. We observed pronounced differences between the editing patterns in humans and rats: in humans site A is the key determinant of the editing state of the other sites, whereas in rats this role belongs to site B. The structure of the dependencies among the editing sites is notably simpler in rats than it is in humans implying more complex regulation of 5-HT_2CR editing and, by inference, function in the human brain. Thus, exhaustive statistical analysis of the 5-HT_2CR editing patterns indicates that the editing state of sites A and B is the primary determinant of the editing states of the other three sites, and hence the overall editing pattern. Taken together, these findings allow us to propose a mechanistic model of concerted action of ADAR1 and ADAR2 in 5-HT_2CR editing. Statistical approach developed here can be applied to other cases of interdependencies among modification sites in RNA and proteins.</p> </div

BIC scores (dots) and pDAGs of human models <b> through </b><b>.</b>

<p>The BIC scores of the models are shown as dots, and the pDAGs of the models themselves are plotted next to each dot. These models represent relationship between sites rather than true causality, as indicated by the fact that some edges reverse their direction in different models. The number of parameters required to describe each of the models is 5 (), 6 (), 7 (), 8 (), 10 (), 14 (), 13 (), 17 (), 21 (), 29 (), and 31 ().</p

A hypothetical mechanistic model of concerted action of ADAR1 and ADAR2 in 5-HT_2CR mRNA editing.

<p>The squares denote the 5 distinct editing sites and the stars denote editing. The figure is not to scale.</p

Edges present in the best-fitting models in human (BIC scores).

<p>For each fixed number of <b>edges </b><b>, we report</b> the basic set of edges (the most supported edges), as well as additional edges that are not significantly less supported (at Bonferroni-corrected significance level 0.05).</p

Clustering of the five editing sites using Jaccard distance in (a) human and (b) rat.

<p>Each edge is assigned with a confidence level according to the fraction of times by which it was supported by the different individuals.</p

BIC scores (dots) and pDAGs of rat models <b> through </b><b>.</b>

<p>The designations are as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002663#pcbi-1002663-g002" target="_blank">Figure 2</a>. The number of parameters required to describe each of the models is 5 (), 6 (), 7 (), 9 (), 13 (), 15 (), 23 (), 20 (), 26 (), 30 (), and 31 ().</p

Level of support of each edge in all individual best-fitting models with fixed number of edges.

<p>The results are for BIC scores in rat.</p