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See detailGene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages
Antony, Paul UL; Tallam, Aravind UL; Perumal, Thanneer Malai UL et al

in PLoS ONE (2016)

Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions. Its function has been recently described: it codes for immune-responsive gene 1 protein ... [more ▼]

Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions. Its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalysing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. To this end, we studied IRG1 expression in human immune cells under different inflammatory stimuli, such as TNFα and IFNγ, in addition to lipopolysaccharides. Under these conditions, as previously shown in mouse macrophages, IRG1/CAD accumulates in mitochondria. Furthermore, using literature information and transcription factor prediction models, we re-constructed raw gene regulatory networks (GRNs) for IRG1 in mouse and human macrophages. We further implemented a contextualization algorithm that relies on genome-wide gene expression data to infer putative cell type-specific gene regulatory interactions in mouse and human macrophages, which allowed us to predict potential transcriptional regulators of IRG1. Among the computationally identified regulators, siRNA-mediated gene silencing of interferon regulatory factor 1 (IRF1) in macrophages significantly decreased the expression of IRG1/CAD at the gene and protein level, which correlated with a reduced production of itaconic acid. Using a synergistic approach of both computational and experimental methods, we here shed more light on the transcriptional machinery of IRG1 expression and could pave the way to therapeutic approaches targeting itaconic acid levels. [less ▲]

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See detailpathPSA: A Dynamical Pathway-Based Parametric Sensitivity
Perumal, Thanneer Malai UL; Gunawan, Rudiyanto

in Industrial and Engineering Chemistry (2014)

Normal functioning of biological systems relies on coordinated activities of biomolecules participating in a complex network of biological interactions. As human intuition is often incapable in analyzing ... [more ▼]

Normal functioning of biological systems relies on coordinated activities of biomolecules participating in a complex network of biological interactions. As human intuition is often incapable in analyzing how biological functions emerge from such complex interactions, the use of mathematical models and systems analysis tools has become critical in understanding biological system behavior. While biological functions have been associated with the connectivity (structure) and pathways of the network and the kinetics of the processes involved, most model analyses address each of these aspects separately. In contrast, we present a novel sensitivity analysis, called pathway-based parametric sensitivity analysis (pathPSA), which combines the analysis of both network structure and kinetics. Unlike existing sensitivity analyses, pathPSA relies on perturbing the kinetics of pathways in the network, using persistent perturbations or impulse perturbations at varying time. Consequently, the sensitivity coefficients can give insights on the dominant pathways in a network and any transient shift in the rate controlling mechanism. The efficacy of pathPSA is demonstrated through an application to understand competing signaling pathways in programmed cell death network. [less ▲]

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See detailIntegrating Pathways of Parkinson's Disease in a Molecular Interaction Map
Fujita, Kazuhiro A.; Ostaszewski, Marek UL; Matsuoka, Yukiko et al

in Molecular Neurobiology (2014)

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is ... [more ▼]

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at http://minerva.uni.lu/pd_map . [less ▲]

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See detailThe Parkinson's Disease Map: A Framework for Integration, Curation and Exploration of Disease-related Pathways
Ostaszewski, Marek UL; Fujita, Kazuhiro; Matsuoka, Yukiko et al

Poster (2013, March 09)

Objectives: The pathogenesis of Parkinson's Disease (PD) is multi-factorial and age-related, implicating various genetic and environmental factors. It becomes increasingly important to develop new ... [more ▼]

Objectives: The pathogenesis of Parkinson's Disease (PD) is multi-factorial and age-related, implicating various genetic and environmental factors. It becomes increasingly important to develop new approaches to organize and explore the exploding knowledge of this field. Methods: The published knowledge on pathways implicated in PD, such as synaptic and mitochondrial dysfunction, alpha-synuclein pathobiology, failure of protein degradation systems and neuroinflammation has been organized and represented using CellDesigner. This repository has been linked to a framework of bioinformatics tools including text mining, database annotation, large-scale data integration and network analysis. The interface for online curation of the repository has been established using Payao tool. Results: We present the PD map, a computer-based knowledge repository, which includes molecular mechanisms of PD in a visually structured and standardized way. A bioinformatics framework that facilitates in-depth knowledge exploration, extraction and curation supports the map. We discuss the insights gained from PD map-driven text mining of a corpus of over 50 thousands full text PD-related papers, integration and visualization of gene expression in post mortem brain tissue of PD patients with the map, as well as results of network analysis. Conclusions: The knowledge repository of disease-related mechanisms provides a global insight into relationships between different pathways and allows considering a given pathology in a broad context. Enrichment with available text and bioinformatics databases as well as integration of experimental data supports better understanding of complex mechanisms of PD and formulation of novel research hypotheses. [less ▲]

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See detailUnderstanding dynamics using sensitivity analysis: caveat and solution
Perumal, Thanneer Malai UL; Gunawan, Rudiyanto

in BMC Systems Biology (2011), 5

BACKGROUND: Parametric sensitivity analysis (PSA) has become one of the most commonly used tools in computational systems biology, in which the sensitivity coefficients are used to study the parametric ... [more ▼]

BACKGROUND: Parametric sensitivity analysis (PSA) has become one of the most commonly used tools in computational systems biology, in which the sensitivity coefficients are used to study the parametric dependence of biological models. As many of these models describe dynamical behaviour of biological systems, the PSA has subsequently been used to elucidate important cellular processes that regulate this dynamics. However, in this paper, we show that the PSA coefficients are not suitable in inferring the mechanisms by which dynamical behaviour arises and in fact it can even lead to incorrect conclusions. RESULTS: A careful interpretation of parametric perturbations used in the PSA is presented here to explain the issue of using this analysis in inferring dynamics. In short, the PSA coefficients quantify the integrated change in the system behaviour due to persistent parametric perturbations, and thus the dynamical information of when a parameter perturbation matters is lost. To get around this issue, we present a new sensitivity analysis based on impulse perturbations on system parameters, which is named impulse parametric sensitivity analysis (iPSA). The inability of PSA and the efficacy of iPSA in revealing mechanistic information of a dynamical system are illustrated using two examples involving switch activation. CONCLUSIONS: The interpretation of the PSA coefficients of dynamical systems should take into account the persistent nature of parametric perturbations involved in the derivation of this analysis. The application of PSA to identify the controlling mechanism of dynamical behaviour can be misleading. By using impulse perturbations, introduced at different times, the iPSA provides the necessary information to understand how dynamics is achieved, i.e. which parameters are essential and when they become important. [less ▲]

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See detailImpulse parametric sensitivity analysis
Perumal, Thanneer Malai UL; Gunawan, R.

Scientific Conference (2011)

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See detailDynamical analysis of cellular networks based on the Green's function matrix
Perumal, Thanneer Malai UL; Wu, Yan; Gunawan, Rudiyanto

in Journal of Theoretical Biology (2009), 261(2), 248-59

The complexity of cellular networks often limits human intuition in understanding functional regulations in a cell from static network diagrams. To this end, mathematical models of ordinary differential ... [more ▼]

The complexity of cellular networks often limits human intuition in understanding functional regulations in a cell from static network diagrams. To this end, mathematical models of ordinary differential equations (ODEs) have commonly been used to simulate dynamical behavior of cellular networks, to which a quantitative model analysis can be applied in order to gain biological insights. In this paper, we introduce a dynamical analysis based on the use of Green's function matrix (GFM) as sensitivity coefficients with respect to initial concentrations. In contrast to the classical (parametric) sensitivity analysis, the GFM analysis gives a dynamical, molecule-by-molecule insight on how system behavior is accomplished and complementarily how (impulse) signal propagates through the network. The knowledge gained will have application from model reduction and validation to drug discovery research in identifying potential drug targets, studying drug efficacy and specificity, and optimizing drug dosing and timing. The efficacy of the method is demonstrated through applications to common network motifs and a Fas-induced programmed cell death model in Jurkat T cell line. [less ▲]

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See detailRobustness analysis of cellular systems for in silico drug discovery
Perumal, Thanneer Malai UL; Wu, Y.; Gunawan, R.

Scientific Conference (2008)

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