61 research outputs found
Amyloid-β(1-42) Aggregation Initiates Its Cellular Uptake and Cytotoxicity
The accumulation of amyloid β peptide(1-42) (Aβ(1-42)) in extracellular plaques is one of the pathological hallmarks of Alzheimer disease (AD). Several studies have suggested that cellular reuptake of Aβ(1-42) may be a crucial step in its cytotoxicity, but the uptake mechanism is not yet understood. Aβ may be present in an aggregated form prior to cellular uptake. Alternatively, monomeric peptide may enter the endocytic pathway and conditions in the endocytic compartments may induce the aggregation process. Our study aims to answer the question whether aggregate formation is a prerequisite or a consequence of Aβ endocytosis. We visualized aggregate formation of fluorescently labeled Aβ(1-42) and tracked its internalization by human neuroblastoma cells and neurons. β-Sheet-rich Aβ(1-42) aggregates entered the cells at low nanomolar concentration of Aβ(1-42). In contrast, monomer uptake faced a concentration threshold and occurred only at concentrations and time scales that allowed Aβ(1-42) aggregates to form. By uncoupling membrane binding from internalization, we found that Aβ(1-42) monomers bound rapidly to the plasma membrane and formed aggregates there. These structures were subsequently taken up and accumulated in endocytic vesicles. This process correlated with metabolic inhibition. Our data therefore imply that the formation of β-sheet-rich aggregates is a prerequisite for Aβ(1-42) uptake and cytotoxicity
Amyloid-β(1-42) Aggregation Initiates Its Cellular Uptake and Cytotoxicity
The accumulation of amyloid β peptide(1-42) (Aβ(1-42)) in extracellular plaques is one of the pathological hallmarks of Alzheimer disease (AD). Several studies have suggested that cellular reuptake of Aβ(1-42) may be a crucial step in its cytotoxicity, but the uptake mechanism is not yet understood. Aβ may be present in an aggregated form prior to cellular uptake. Alternatively, monomeric peptide may enter the endocytic pathway and conditions in the endocytic compartments may induce the aggregation process. Our study aims to answer the question whether aggregate formation is a prerequisite or a consequence of Aβ endocytosis. We visualized aggregate formation of fluorescently labeled Aβ(1-42) and tracked its internalization by human neuroblastoma cells and neurons. β-Sheet-rich Aβ(1-42) aggregates entered the cells at low nanomolar concentration of Aβ(1-42). In contrast, monomer uptake faced a concentration threshold and occurred only at concentrations and time scales that allowed Aβ(1-42) aggregates to form. By uncoupling membrane binding from internalization, we found that Aβ(1-42) monomers bound rapidly to the plasma membrane and formed aggregates there. These structures were subsequently taken up and accumulated in endocytic vesicles. This process correlated with metabolic inhibition. Our data therefore imply that the formation of β-sheet-rich aggregates is a prerequisite for Aβ(1-42) uptake and cytotoxicity
Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions.
Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner
Polyglutamine Expansion Accelerates the Dynamics of Ataxin-1 and Does Not Result in Aggregate Formation
Polyglutamine expansion disorders are caused by an expansion of the polyglutamine (polyQ) tract in the disease related protein, leading to severe neurodegeneration. All polyQ disorders are hallmarked by the presence of intracellular aggregates containing the expanded protein in affected neurons. The polyQ disorder SpinoCerebellar Ataxia 1 (SCA1) is caused by a polyQ-expansion in the ataxin-1 protein, which is thought to lead to nuclear aggregates.Using advanced live cell fluorescence microscopy and a filter retardation assay we show that nuclear accumulations formed by polyQ-expanded ataxin-1 do not resemble aggregates of other polyQ-expanded proteins. Instead of being static, insoluble aggregates, nuclear accumulations formed by the polyQ-expanded ataxin-1 showed enhanced intracellular kinetics as compared to wild-type ataxin-1. During mitosis, ataxin-1 accumulations redistributed equally among daughter cells, in contrast to polyQ aggregates. Interestingly, polyQ expansion did not affect the nuclear-cytoplasmic shuttling of ataxin-1 as proposed before.These results indicate that polyQ expansion does not necessarily lead to aggregate formation, and that the enhanced kinetics may affect the nuclear function of ataxin-1. The unexpected findings for a polyQ-expanded protein and their consequences for ongoing SCA1 research are discussed
When Cytokinin, a Plant Hormone, Meets the Adenosine A2A Receptor: A Novel Neuroprotectant and Lead for Treating Neurodegenerative Disorders?
It is well known that cytokinins are a class of phytohormones that promote cell division in plant roots and shoots. However, their targets, biological functions, and implications in mammalian systems have rarely been examined. In this study, we show that one cytokinin, zeatin riboside, can prevent pheochromocytoma (PC12) cells from serum deprivation-induced apoptosis by acting on the adenosine A2A receptor (A2A-R), which was blocked by an A2A-R antagonist and a protein kinase A (PKA) inhibitor, demonstrating the functional ability of zeatin riboside by mediating through A2A-R signaling event. Since the A2A-R was implicated as a therapeutic target in treating Huntington’s disease (HD), a cellular model of HD was applied by transfecting mutant huntingtin in PC12 cells. By using filter retardation assay and confocal microscopy we found that zeatin riboside reversed mutant huntingtin (Htt)-induced protein aggregations and proteasome deactivation through A2A-R signaling. PKA inhibitor blocked zeatin riboside-induced suppression of mutant Htt aggregations. In addition, PKA activated proteasome activity and reduced mutant Htt protein aggregations. However, a proteasome inhibitor blocked both zeatin riboside-and PKA activator-mediated suppression of mutant Htt aggregations, confirming mediation of the A2A-R/PKA/proteasome pathway. Taken together, zeatin riboside might have therapeutic potential as a novel neuroprotectant and a lead for treating neurodegenerative disorders
Detection of Alpha-Rod Protein Repeats Using a Neural Network and Application to Huntingtin
A growing number of solved protein structures display an elongated structural
domain, denoted here as alpha-rod, composed of stacked pairs of anti-parallel
alpha-helices. Alpha-rods are flexible and expose a large surface, which makes
them suitable for protein interaction. Although most likely originating by
tandem duplication of a two-helix unit, their detection using sequence
similarity between repeats is poor. Here, we show that alpha-rod repeats can be
detected using a neural network. The network detects more repeats than are
identified by domain databases using multiple profiles, with a low level of
false positives (<10%). We identify alpha-rod repeats in
approximately 0.4% of proteins in eukaryotic genomes. We then
investigate the results for all human proteins, identifying alpha-rod repeats
for the first time in six protein families, including proteins STAG1-3, SERAC1,
and PSMD1-2 & 5. We also characterize a short version of these repeats
in eight protein families of Archaeal, Bacterial, and Fungal species. Finally,
we demonstrate the utility of these predictions in directing experimental work
to demarcate three alpha-rods in huntingtin, a protein mutated in
Huntington's disease. Using yeast two hybrid analysis and an
immunoprecipitation technique, we show that the huntingtin fragments containing
alpha-rods associate with each other. This is the first definition of domains in
huntingtin and the first validation of predicted interactions between fragments
of huntingtin, which sets up directions toward functional characterization of
this protein. An implementation of the repeat detection algorithm is available
as a Web server with a simple graphical output: http://www.ogic.ca/projects/ard. This can be further visualized
using BiasViz, a graphic tool for representation of multiple sequence
alignments
Complete Genome Sequence of Mycoplasma suis and Insights into Its Biology and Adaption to an Erythrocyte Niche
Mycoplasma suis, the causative agent of porcine infectious anemia, has never been cultured in vitro and mechanisms by which it causes disease are poorly understood. Thus, the objective herein was to use whole genome sequencing and analysis of M. suis to define pathogenicity mechanisms and biochemical pathways. M. suis was harvested from the blood of an experimentally infected pig. Following DNA extraction and construction of a paired end library, whole-genome sequencing was performed using GS-FLX (454) and Titanium chemistry. Reads on paired-end constructs were assembled using GS De Novo Assembler and gaps closed by primer walking; assembly was validated by PFGE. Glimmer and Manatee Annotation Engine were used to predict and annotate protein-coding sequences (CDS). The M. suis genome consists of a single, 742,431 bp chromosome with low G+C content of 31.1%. A total of 844 CDS, 3 single copies, unlinked rRNA genes and 32 tRNAs were identified. Gene homologies and GC skew graph show that M. suis has a typical Mollicutes oriC. The predicted metabolic pathway is concise, showing evidence of adaptation to blood environment. M. suis is a glycolytic species, obtaining energy through sugars fermentation and ATP-synthase. The pentose-phosphate pathway, metabolism of cofactors and vitamins, pyruvate dehydrogenase and NAD+ kinase are missing. Thus, ribose, NADH, NADPH and coenzyme A are possibly essential for its growth. M. suis can generate purines from hypoxanthine, which is secreted by RBCs, and cytidine nucleotides from uracil. Toxins orthologs were not identified. We suggest that M. suis may cause disease by scavenging and competing for host' nutrients, leading to decreased life-span of RBCs. In summary, genome analysis shows that M. suis is dependent on host cell metabolism and this characteristic is likely to be linked to its pathogenicity. The prediction of essential nutrients will aid the development of in vitro cultivation systems
Celastrol inhibits polyglutamine aggregation and toxicity though induction of the heat shock response
The disruption of proteostasis in neurodegenerative diseases
Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio
The structure of a polyQ–anti-polyQ complex reveals binding according to a linear lattice model
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