A Unifying Hypothesis for Familial and Sporadic Alzheimer's Disease

Alzheimer's disease (AD) is characterised by the aggregation of two quite different proteins, namely, amyloid-beta (Aβ), which forms extracellular plaques, and tau, the main component of cytoplasmic neurofibrillary tangles. The amyloid hypothesis proposes that Aβ plaques precede tangle formation but there is still much controversy concerning the order of events and the linkage between Aβ and tau alterations is still unknown. Mathematical modelling has become an essential tool for generating and evaluating hypotheses involving complex systems. We have therefore used this approach to discover the most probable pathway linking Aβ and tau. The model supports a complex pathway linking Aβ and tau via GSK3β, p53, and oxidative stress. Importantly, the pathway contains a cycle with multiple points of entry. It is this property of the pathway which enables the model to be consistent with both the amyloid hypothesis for familial AD and a more complex pathway for sporadic forms

Modelling the Role of UCH-L1 on Protein Aggregation in Age-Related Neurodegeneration

Overexpression of the de-ubiquitinating enzyme UCH-L1 leads to inclusion formation in response to proteasome impairment. These inclusions contain components of the ubiquitin-proteasome system and α-synuclein confirming that the ubiquitin-proteasome system plays an important role in protein aggregation. The processes involved are very complex and so we have chosen to take a systems biology approach to examine the system whereby we combine mathematical modelling with experiments in an iterative process. The experiments show that cells are very heterogeneous with respect to inclusion formation and so we use stochastic simulation. The model shows that the variability is partly due to stochastic effects but also depends on protein expression levels of UCH-L1 within cells. The model also indicates that the aggregation process can start even before any proteasome inhibition is present, but that proteasome inhibition greatly accelerates aggregation progression. This leads to less efficient protein degradation and hence more aggregation suggesting that there is a vicious cycle. However, proteasome inhibition may not necessarily be the initiating event. Our combined modelling and experimental approach show that stochastic effects play an important role in the aggregation process and could explain the variability in the age of disease onset. Furthermore, our model provides a valuable tool, as it can be easily modified and extended to incorporate new experimental data, test hypotheses and make testable predictions

Experimental and Computational Analysis of Polyglutamine-Mediated Cytotoxicity

Expanded polyglutamine (polyQ) proteins are known to be the causative agents of a number of human neurodegenerative diseases but the molecular basis of their cytoxicity is still poorly understood. PolyQ tracts may impede the activity of the proteasome, and evidence from single cell imaging suggests that the sequestration of polyQ into inclusion bodies can reduce the proteasomal burden and promote cell survival, at least in the short term. The presence of misfolded protein also leads to activation of stress kinases such as p38MAPK, which can be cytotoxic. The relationships of these systems are not well understood. We have used fluorescent reporter systems imaged in living cells, and stochastic computer modeling to explore the relationships of polyQ, p38MAPK activation, generation of reactive oxygen species (ROS), proteasome inhibition, and inclusion body formation. In cells expressing a polyQ protein inclusion, body formation was preceded by proteasome inhibition but cytotoxicity was greatly reduced by administration of a p38MAPK inhibitor. Computer simulations suggested that without the generation of ROS, the proteasome inhibition and activation of p38MAPK would have significantly reduced toxicity. Our data suggest a vicious cycle of stress kinase activation and proteasome inhibition that is ultimately lethal to cells. There was close agreement between experimental data and the predictions of a stochastic computer model, supporting a central role for proteasome inhibition and p38MAPK activation in inclusion body formation and ROS-mediated cell death

Systems biology reveals how altered TGF beta signalling with age reduces protection against pro-inflammatory stimuli

<div><p>Osteoarthritis (OA) is a degenerative condition caused by dysregulation of multiple molecular signalling pathways. Such dysregulation results in damage to cartilage, a smooth and protective tissue that enables low friction articulation of synovial joints. Matrix metalloproteinases (MMPs), especially MMP-13, are key enzymes in the cleavage of type II collagen which is a vital component for cartilage integrity. Transforming growth factor beta (TGFβ) can protect against pro-inflammatory cytokine-mediated MMP expression. With age there is a change in the ratio of two TGFβ type I receptors (Alk1/Alk5), a shift that results in TGFβ losing its protective role in cartilage homeostasis. Instead, TGFβ promotes cartilage degradation which correlates with the spontaneous development of OA in murine models. However, the mechanism by which TGFβ protects against pro-inflammatory responses and how this changes with age has not been extensively studied. As TGFβ signalling is complex, we used systems biology to combine experimental and computational outputs to examine how the system changes with age. Experiments showed that the repressive effect of TGFβ on chondrocytes treated with a pro-inflammatory stimulus required Alk5. Computational modelling revealed two independent mechanisms were needed to explain the crosstalk between TGFβ and pro-inflammatory signalling pathways. A novel meta-analysis of microarray data from OA patient tissue was used to create a Cytoscape network representative of human OA and revealed the importance of inflammation. Combining the modelled genes with the microarray network provided a global overview into the crosstalk between the different signalling pathways involved in OA development. Our results provide further insights into the mechanisms that cause TGFβ signalling to change from a protective to a detrimental pathway in cartilage with ageing. Moreover, such a systems biology approach may enable restoration of the protective role of TGFβ as a potential therapy to prevent age-related loss of cartilage and the development of OA.</p></div

Aggregation, impaired degradation and immunization targeting of amyloid-beta dimers in Alzheimer’s disease: a stochastic modelling approach

Background Alzheimer’s disease (AD) is the most frequently diagnosed neurodegenerative disorder affecting humans, with advanced age being the most prominent risk factor for developing AD. Despite intense research efforts aimed at elucidating the precise molecular underpinnings of AD, a definitive answer is still lacking. In recent years, consensus has grown that dimerisation of the polypeptide amyloid-beta (Aß), particularly Aß42, plays a crucial role in the neuropathology that characterise AD-affected post-mortem brains, including the large-scale accumulation of fibrils, also referred to as senile plaques. This has led to the realistic hope that targeting Aß42 immunotherapeutically could drastically reduce plaque burden in the ageing brain, thus delaying AD onset or symptom progression. Stochastic modelling is a useful tool for increasing understanding of the processes underlying complex systems-affecting disorders such as AD, providing a rapid and inexpensive strategy for testing putative new therapies. In light of the tool’s utility, we developed computer simulation models to examine Aß42 turnover and its aggregation in detail and to test the effect of immunization against Aß dimers. Results Our model demonstrates for the first time that even a slight decrease in the clearance rate of Aß42 monomers is sufficient to increase the chance of dimers forming, which could act as instigators of protofibril and fibril formation, resulting in increased plaque levels. As the process is slow and levels of Aβ are normally low, stochastic effects are important. Our model predicts that reducing the rate of dimerisation leads to a significant reduction in plaque levels and delays onset of plaque formation. The model was used to test the effect of an antibody mediated immunological response. Our results showed that plaque levels were reduced compared to conditions where antibodies are not present. Conclusion Our model supports the current thinking that levels of dimers are important in initiating the aggregation process. Although substantial knowledge exists regarding the process, no therapeutic intervention is on offer that reliably decreases disease burden in AD patients. Computer modelling could serve as one of a number of tools to examine both the validity of reliable biomarkers and aid the discovery of successful intervention strategies

TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

Motivation: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. Results: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction

第1071回千葉医学会例会・第5回環境生命医学研究会

Showing a Venn diagram of the ECM proteins identified in constructs using MatrisomeDB. (DOCX 100 kb

Systems analysis of miR-199a/b-5p and multiple miR-199a/b-5p targets during chondrogenesis

Changes in chondrocyte gene expression can contribute to the development of osteoarthritis (OA), and so recognition of the regulative processes during chondrogenesis can lead to a better understanding of OA. microRNAs (miRNAs) are key regulators of gene expression in chondrocytes/OA, and we have used a combined experimental, bioinformatic, and systems biology approach to explore the multiple miRNA–mRNA interactions that regulate chondrogenesis. A longitudinal chondrogenesis bioinformatic analysis identified paralogues miR-199a-5p and miR-199b-5p as pro-chondrogenic regulators. Experimental work in human cells demonstrated alteration of miR199a-5p or miR-199b-5p expression led to significant inverse modulation of key chondrogenic genes and extracellular matrix production. miR-199a/b-5p targets FZD6, ITGA3 and CAV1 were identified by inhibition experiments and verified as direct targets by luciferase assay. The experimental work was used to generate and parameterise a multi-miRNA 14-day chondrogenesis kinetic model to be used as a repository for the experimental work and as a resource for further investigation of this system. This is the first multi-miRNA model of a chondrogenesis-based system, and highlights the complex relationships between regulatory miRNAs, and their target mRNA