Phenylbutyric Acid Rescues Endoplasmic Reticulum Stress-Induced Suppression of APP Proteolysis and Prevents Apoptosis in Neuronal Cells

BACKGROUND: The familial and sporadic forms of Alzheimer's disease (AD) have an identical pathology with a severe disparity in the time of onset [1]. The pathological similarity suggests that epigenetic processes may phenocopy the Familial Alzheimer's disease (FAD) mutations within sporadic AD. Numerous groups have demonstrated that FAD mutations in presenilin result in 'loss of function' of gamma-secretase mediated APP cleavage [2], [3], [4], [5]. Accordingly, ER stress is prominent within the pathologically impacted brain regions in AD patients [6] and is reported to inhibit APP trafficking through the secretory pathway [7], [8]. As the maturation of APP and the cleaving secretases requires trafficking through the secretory pathway [9], [10], [11], we hypothesized that ER stress may block trafficking requisite for normal levels of APP cleavage and that the small molecular chaperone 4-phenylbutyrate (PBA) may rescue the proteolytic deficit. METHODOLOGY/PRINCIPAL FINDINGS: The APP-Gal4VP16/Gal4-reporter screen was stably incorporated into neuroblastoma cells in order to assay gamma-secretase mediated APP proteolysis under normal and pharmacologically induced ER stress conditions. Three unrelated pharmacological agents (tunicamycin, thapsigargin and brefeldin A) all repressed APP proteolysis in parallel with activation of unfolded protein response (UPR) signaling-a biochemical marker of ER stress. Co-treatment of the gamma-secretase reporter cells with PBA blocked the repressive effects of tunicamycin and thapsigargin upon APP proteolysis, UPR activation, and apoptosis. In unstressed cells, PBA stimulated gamma-secretase mediated cleavage of APP by 8-10 fold, in the absence of any significant effects upon amyloid production, by promoting APP trafficking through the secretory pathway and the stimulation of the non-pathogenic alpha/gamma-cleavage. CONCLUSIONS/SIGNIFICANCE: ER stress represses gamma-secretase mediated APP proteolysis, which replicates some of the proteolytic deficits associated with the FAD mutations. The small molecular chaperone PBA can reverse ER stress induced effects upon APP proteolysis, trafficking and cellular viability. Pharmaceutical agents, such as PBA, that stimulate alpha/gamma-cleavage of APP by modifying intracellular trafficking should be explored as AD therapeutics

Presenilin 2 Is the Predominant γ-Secretase in Microglia and Modulates Cytokine Release

Presenilin 1 (PS1) and Presenilin 2 (PS2) are the enzymatic component of the γ-secretase complex that cleaves amyloid precursor protein (APP) to release amyloid beta (Aβ) peptide. PS deficiency in mice results in neuroinflammation and neurodegeneration in the absence of accumulated Aβ. We hypothesize that PS influences neuroinflammation through its γ-secretase action in CNS innate immune cells. We exposed primary murine microglia to a pharmacological γ-secretase inhibitor which resulted in exaggerated release of TNFα and IL-6 in response to lipopolysaccharide. To determine if this response was mediated by PS1, PS2 or both we used shRNA to knockdown each PS in a murine microglia cell line. Knockdown of PS1 did not lead to decreased γ-secretase activity while PS2 knockdown caused markedly decreased γ-secretase activity. Augmented proinflammatory cytokine release was observed after knockdown of PS2 but not PS1. Proinflammatory stimuli increased microglial PS2 gene transcription and protein in vitro. This is the first demonstration that PS2 regulates CNS innate immunity. Taken together, our findings suggest that PS2 is the predominant γ-secretase in microglia and modulates release of proinflammatory cytokines. We propose PS2 may participate in a negative feedback loop regulating inflammatory behavior in microglia

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Pacific Symposium on Biocomputing 10:115-126(2005) INTEGRATING GENOMIC KNOWLEDGE SOURCES THROUGH AN ANATOMY ONTOLOGY

Modern genomic research has access to a plethora of knowledge sources. Often, it is imperative that researchers combine and integrate knowledge from multiple perspectives. Although some technology exists for connecting data and knowledge bases, these methods are only just beginning to be successfully applied to research in modern cell biology. In this paper, we argue that one way to integrate multiple knowledge sources is through anatomy—both generic cellular anatomy, as well as anatomic knowledge about the tissues and organs that may be studied via microarray gene expression experiments. We present two examples where we have combined a large ontology of human anatomy (the FMA) with other genomic knowledge sources: the gene ontology (GO) and the mouse genomic databases (MGD) of the Jackson Labs. These two initial examples of knowledge integration provide a proof of concept that anatomy can act as a hub through which we can usefully combine a variety of genomic knowledge and data. 1 The Problem: Overwhelming, Distributed Genomic Knowledge Modern biology researchers are hampered by the need to integrate information from rapidly developing and diverse knowledge sources. As a general problem, researchers in computer science and informatics have developed methods for combining and integratin

Genetic and multi‐omic risk assessment of Alzheimer's disease implicates core associated biological domains

Abstract INTRODUCTION Alzheimer's disease (AD) is the predominant dementia globally, with heterogeneous presentation and penetrance of clinical symptoms, variable presence of mixed pathologies, potential disease subtypes, and numerous associated endophenotypes. Beyond the difficulty of designing treatments that address the core pathological characteristics of the disease, therapeutic development is challenged by the uncertainty of which endophenotypic areas and specific targets implicated by those endophenotypes to prioritize for further translational research. However, publicly funded consortia driving large‐scale open science efforts have produced multiple omic analyses that address both disease risk relevance and biological process involvement of genes across the genome. METHODS Here we report the development of an informatic pipeline that draws from genetic association studies, predicted variant impact, and linkage with dementia associated phenotypes to create a genetic risk score. This is paired with a multi‐omic risk score utilizing extensive sets of both transcriptomic and proteomic studies to identify system‐level changes in expression associated with AD. These two elements combined constitute our target risk score that ranks AD risk genome‐wide. The ranked genes are organized into endophenotypic space through the development of 19 biological domains associated with AD in the described genetics and genomics studies and accompanying literature. The biological domains are constructed from exhaustive Gene Ontology (GO) term compilations, allowing automated assignment of genes into objectively defined disease‐associated biology. This rank‐and‐organize approach, performed genome‐wide, allows the characterization of aggregations of AD risk across biological domains. RESULTS The top AD‐risk‐associated biological domains are Synapse, Immune Response, Lipid Metabolism, Mitochondrial Metabolism, Structural Stabilization, and Proteostasis, with slightly lower levels of risk enrichment present within the other 13 biological domains. DISCUSSION This provides an objective methodology to localize risk within specific biological endophenotypes and drill down into the most significantly associated sets of GO terms and annotated genes for potential therapeutic targets