References of "Kolodkin, Alexey 50002121"
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See detailROS homeostasis in a dynamic model: How to save PD neuron?
Kolodkin, Alexey UL; Ignatenko, Andrew UL; Sangar, Vineet et al

Poster (2014, December)

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See detailMacromolecular networks and intelligence in microorganisms
Westerhoff, Hans V.; Brooks, Aaron; Simeonidis, Vangelis UL et al

in Frontiers in Microbiology (2014)

Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks ... [more ▼]

Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of Information and Communication Technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity – particularly activity of the human brain – with a phenomenon we call “intelligence”. Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as “human” and “brain” out of the defining features of “intelligence”, all forms of life – from microbes to humans – exhibit some or all characteristics consistent with “intelligence”. We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo. [less ▲]

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See detailROS-activated signaling network: dynamic modelling and design principles study
Kolodkin, Alexey UL; Ignatenko, Andrew UL; Sangar, Vineet et al

Poster (2014, June)

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See detailDynamic modelling of ROS management and ROS-induced mitophagy
Kolodkin, Alexey UL; Ignatenko, Andrew UL; Sangar, Vineet et al

Poster (2014, June)

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See detailComparison of ODE-based models for reactive oxygen species regulation system
Ignatenko, Andrew UL; Kolodkin, Alexey UL; Peters, Bernhard UL et al

in Proceedings of ICCSA 2014 (2014, June)

Reactive oxygen species (ROS) play important role in the functioning of any cell and especially in the lifecycle of mitochondria. Since the action of ROS can be both positive and negative then the ... [more ▼]

Reactive oxygen species (ROS) play important role in the functioning of any cell and especially in the lifecycle of mitochondria. Since the action of ROS can be both positive and negative then the remarkable role can be played by ROS regulation system. We constructed three different ODE based kinetic models of different complexity for the ROS management system and shown the difference in the dynamics of these systems under different conditions. Using results of numerical simulation we showed that extraction of some subsystems can make the model more unstable. We also introduced the objective function for comparison of the models with structure of different complexity [less ▲]

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See detailDesign principles study of ROS management and ROS-induced mitophagy with a kinetic model
Kolodkin, Alexey UL; Ignatenko, Andrew UL; Sangar, Vineet et al

Poster (2013, September 27)

In vivo evidence demonstrates three fundamental interconnected adaptive survival mechanisms , which protect against excessive ROS that is generated during mitochondrial dysfunction: (i) autophagy ... [more ▼]

In vivo evidence demonstrates three fundamental interconnected adaptive survival mechanisms , which protect against excessive ROS that is generated during mitochondrial dysfunction: (i) autophagy/mitophagy, (ii) adaptive antioxidant response and (iii) NFkB signaling in cancer and neurodegeneration. We have been expanding a kinetic model which recapitulates the consensus understanding of the mechanisms responsible for cellular ROS – management system and performed modular analysis to analyze emergent behavior. We started with the simplest model and added stepwise new modules. We identify the qualitative role (certain emergent behavior) attributed to each module and thus understand the design principles of the system. We propose a detailed, mechanistic, kinetic model for studying how mutations relevant for diseases such as PD and cancer affect the emergent behavior of ROS management network. [less ▲]

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See detailModeling cellular ROS defense in mitochondrial-related diseases
Simeonidis, Vangelis UL; Kolodkin, Alexey UL; Ignatenko, Andrew UL et al

Poster (2013, July 22)

Reactive Oxygen Species (ROS) generation is an unavoidable background process during normal cellular function. The main contributor to ROS production is the electron transport chain, which reduces oxygen ... [more ▼]

Reactive Oxygen Species (ROS) generation is an unavoidable background process during normal cellular function. The main contributor to ROS production is the electron transport chain, which reduces oxygen to water. Some incompletely-reduced oxygen species escape and oxidize a variety of organic molecules, leading to molecular dysfunction and initiating a positive feedback loop of ever increasing active radical production. The increased concentration of ROS damages the mitochondria, therefore further elevating the rate of ROS generation. Healthy cells manage ROS enzymatically and by mitophagy of damaged mitochondria. The precise tuning of the latter mechanism is crucial for cell survival and is controlled by a ROS-induced regulatory network. We have built a set of kinetic models of varying complexity, based on the current understanding of the mechanism of cellular ROS defense. Our models allow simulation of various patho-physiological scenarios related to mitochondrial dysfunction and the failure of the system of ROS regulation in human cells. We employ the models we have constructed to simulate the effects of diseases related to mitochondrial dysfunction and excessive ROS generation, such as Parkinson’s disease, Huntington’s disease and cancer. Experimental evidence is used for model fitting, and we propose model improvements based on incorporation of single-cell experimental measurements. Finally, we discuss the perspective of integrating our kinetic models with genome-scale, constraint-based, tissue-specific models of metabolism, in order to study the effect of ROS misregulation on metabolic phenotype. [less ▲]

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See detailROS-induced regulation of mitophagy and its failure in Parkinson’s disease
Kolodkin, Alexey UL; Ignatenko, Andrew UL; Simeonidis, Vangelis UL et al

Poster (2013, May)

Reactive Oxygen Species (ROS) generation is an unavoidable background process in the normal functioning of the cell. The greatest contributor to ROS production is the electron transport chain (ETC) where ... [more ▼]

Reactive Oxygen Species (ROS) generation is an unavoidable background process in the normal functioning of the cell. The greatest contributor to ROS production is the electron transport chain (ETC) where O2 is reduced to H2O. Some incompletely-reduced oxygen species escape and oxidize a variety of organic molecules (e.g. proteins and lipids in the mitochondrial membrane), leading to molecular dysfunction and initiating a positive feedback loop leading to generation of even more active radicals. Increased ROS concentration damages mitochondria and further increases ROS generation. Healthy cells manage ROS enzymatically with superoxide dismutase and other enzymes, various antioxidants, and ultimately through increased mitophagy of damaged mitochondria. The precise tuning of the latter mechanism is crucial for cell survival and is controlled in the cell by a ROS-induced regulatory network, which consists of many components such as Nrf2, Keap1, Parkin and p62 with a rather complicated cross-talk (Figure 1). In many diseases (cancer, Parkinson’s disease (PD), Huntington’s disease (HD), etc.), various components of the ROS management network are altered. Deconstructing the molecular mechanisms underlying or resulting from these alterations might contribute to better understanding of the dynamics of related pathophysiological processes. We have built a kinetics-based model which recapitulates the consensus understanding of the mechanism responsible for cellular ROS – managing system. [less ▲]

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See detailOptimization of stress response through the nuclear receptor-mediated cortisol signalling network
Kolodkin, Alexey UL; Sahin, Nilgun; Phillips, Anna et al

in Nature Communications (2013), 4

It is an accepted paradigm that extended stress predisposes an individual to pathophysiology. However, the biological adaptations to minimize this risk are poorly understood. Using a computational model ... [more ▼]

It is an accepted paradigm that extended stress predisposes an individual to pathophysiology. However, the biological adaptations to minimize this risk are poorly understood. Using a computational model based upon realistic kinetic parameters we are able to reproduce the interaction of the stress hormone cortisol with its two nuclear receptors, the high-affinity glucocorticoid receptor and the low-affinity pregnane X-receptor. We demonstrate that regulatory signals between these two nuclear receptors are necessary to optimize the body’s response to stress episodes, attenuating both the magnitude and duration of the biological response. In addition, we predict that the activation of pregnane X-receptor by multiple, low-affinity endobiotic ligands is necessary for the significant pregnane X-receptor-mediated transcriptional response observed following stress episodes. This integration allows responses mediated through both the high and low-affinity nuclear receptors, which we predict is an important strategy to minimize the risk of disease from chronic stress. [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 detailOn different aspects of network analysis in systems biology
Chaiboonchoe, Amphun; Jurkowski, Wiktor UL; Pellet, Johann et al

in Systems Biology (2013), 1

Network analysis is an essential component of systems biology approaches toward understanding the molecular and cellular interactions underlying biological systems functionalities and their perturbations ... [more ▼]

Network analysis is an essential component of systems biology approaches toward understanding the molecular and cellular interactions underlying biological systems functionalities and their perturbations in disease. Regulatory and signalling pathways involve DNA, RNA, proteins and metabolites as key elements to coordinate most aspects of cellular functioning. Cellular processes depend on the structure and dynamics of gene regulatory networks and can be studied by employing a network representation of molecular interactions. This chapter describes several types of biological networks, how combination of different analytic approaches can be used to study diseases, and provides a list of selected tools for network visualization and analysis. It also introduces protein-protein interaction networks, gene regulatory networks, signalling networks and metabolic networks to illustrate concepts underlying network representation of cellular processes and molecular interactions. It finally discusses how the level of accuracy in inferring functional relationships influences the choice of methods applied for the analysis of a particular biological network type. © Springer Science+Business Media Dordrecht 2013. All rights are reserved. [less ▲]

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See detailNetwork analysis for systems biology
Chaiboonchoe, A.; Jurkowski, Wiktor UL; Pellet, J. et al

in Prokop, Aleš; Csukás (Eds.) Springer book in Systems Biology, Vol.1: Systems Biology:, Integrative Biology and Simulation Tools (2013)

Network analysis is an essential component of systems biology approaches toward understanding the molecular and cellular interactions underlying biological systems functionalities and their perturbations ... [more ▼]

Network analysis is an essential component of systems biology approaches toward understanding the molecular and cellular interactions underlying biological systems functionalities and their perturbations in disease. Regulatory and signalling pathways, which involve DNA, RNA proteins and metabolites as key elements, coordinate most aspects of cellular functioning. Cellular processes, which are dependent on the structure and dynamics of gene regulatory networks, can be studied by employing a network representation of molecular interactions. In this chapter we describe several types of networks and how combination of different analytic approaches can be used to study diseases. We provide a list of selected tools for visualization and network analysis. We introduce protein-protein interaction networks, gene regulatory networks, signalling networks and metabolic networks. We then define concepts underlying network representation of cellular processes and molecular interactions. We finally discuss how the level of accuracy in inferring functional relationships influences the choice of methods applied for the analysis of a particular network type. [less ▲]

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See detailFunctional Genomics, Proteomics, Metabolomics and Bioinformatics for Systems Biology
Ballereau, S.; Glaab, Enrico UL; Kolodkin, Alexey UL et al

in Prokop, Ales; Csukás, Bela (Eds.) Systems Biology: Integrative Biology and Simulation Tools (2013)

This chapter introduces systems biology, its context, aims, concepts and strategies. It then describes approaches and methods used for collection of high-dimensional structural and functional genomics ... [more ▼]

This chapter introduces systems biology, its context, aims, concepts and strategies. It then describes approaches and methods used for collection of high-dimensional structural and functional genomics data, including epigenomics, transcriptomics, proteomics, metabolomics and lipidomics, and how recent technological advances in these fields have moved the bottleneck from data production to data analysis and bioinformatics. Finally, the most advanced mathematical and computational methods used for clustering, feature selection, prediction analysis, text mining and pathway analysis in functional genomics and systems biology are reviewed and discussed in the context of use cases. [less ▲]

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See detailComputing life: Add logos to biology and bios to physics
Kolodkin, Alexey UL; Simeonidis, Evangelos UL; Westerhoff, Hans V.

in Progress in Biophysics & Molecular Biology (2012), 111(2-3), 69-74

This paper discusses the interrelations between physics and biology. Particularly, we analyse the approaches for reconstructing the emergent properties of physical or biological systems. We propose ... [more ▼]

This paper discusses the interrelations between physics and biology. Particularly, we analyse the approaches for reconstructing the emergent properties of physical or biological systems. We propose approaches to scale emergence according to the degree of state-dependency of the system's component properties. Since the component properties of biological systems are state-dependent to a high extent, biological emergence should be considered as very strong emergence – i.e. its reconstruction would require a lot of information about state-dependency of its component properties. However, due to its complexity and volume, this information cannot be handled in the naked human brain, or on the back of an envelope. To solve this problem, biological emergence can be reconstructed in silico based on experimentally determined rate laws and parameter values of the living cell. According to some rough calculations, the silicon human might comprise the mathematical descriptions of around 105 interactions. This is not a small number, but taking into account the exponentially increase of computational power, it should not prove to be our principal limitation. The bigger challenges will be located in different areas. For example they may be related to the observer effect – the limitation to measuring a system's component properties without affecting the system. Another obstacle may be hidden in the tradition of "shaving away" all “unnecessary” assumptions (the so-called Occam's razor) that, in fact, reflects the intention to model the system as simply as possible and thus to deem the emergence to be less strong than it possibly is. We argue here that that Occam's razor should be replaced with the law of completeness. [less ▲]

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See detailA kinetic model and design principles study of cellular ROS defence and its failure in Parkinson’s disease
Kolodkin, Alexey UL; Simeonidis, Vangelis UL; Brady, Nathan et al

Poster (2012, August)

Mitochondrial generation of reactive oxygen species (ROS) is an unavoidable side effect of oxidative phosphorylation. To counteract the production of ROS, the cell employs two main strategies. The first ... [more ▼]

Mitochondrial generation of reactive oxygen species (ROS) is an unavoidable side effect of oxidative phosphorylation. To counteract the production of ROS, the cell employs two main strategies. The first one is to increase the consumption of ROS; this mechanism involves the superoxide dismutase enzyme and various antioxidants. The second strategy is to reduce the production of ROS by decreasing mitochondrial membrane potential and by increasing mitophagy. The precise tuning of the latter is crucial for cell survival: if mitophagy is too active, all mitochondria are lost and the cell suffers from reduced ATP capacity; if mitophagy is not active enough, dysfunctional mitochondria accumulate, more ROS is produced, and the cell undergoes unwanted programmed cell death. We hypothesize that a ROS-activated regulatory network is employed to coordinate the regulation of the rate of mitophagy, the expression of uncoupling proteins and the production of antioxidants, including SOD. In Parkinson’s disease (PD), the activities of several components of this regulatory network (e.g. KEAP1, PARK7, VDAC1, SQSTM1) are altered. This makes the cell susceptible to ROS damage. In the case of dopaminergic neurons, this effect can be particularly severe, because an additional pool of non-mitochondrial ROS generated during ROS-induced degradation of dopamine. In order to understand the functioning of the ROS-activated regulatory network in normal function and disease, we have built a kinetic model. Our model includes 39 species and 45 reactions, with 56 kinetic parameters, either fitted or obtained from literature. Our model allows the simulation of PD-related ROS generation and mitochondrial damage and the identification of the design principles underlying the functioning of the network; for example, showing and explaining the synergy between the down-regulation of both VDAC1 and PARK7 occurring during PD. The kinetic model has great potential use for better understanding of the pathophysiology of PD and for the suggestion of novel mitochondria-related PD treatments. [less ▲]

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See detailEmergence of the silicon human and network targeting drugs
Kolodkin, Alexey UL; Boogerda, Fred C.; Plantb, Nick et al

in European Journal of Pharmaceutical Sciences (2012), 46(4), 190-197

The development of disease may be characterized as a pathological shift of homeostasis; the main goal of contemporary drug treatment is, therefore, to return the pathological homeostasis back to the ... [more ▼]

The development of disease may be characterized as a pathological shift of homeostasis; the main goal of contemporary drug treatment is, therefore, to return the pathological homeostasis back to the normal physiological range. From the view point of systems biology, homeostasis emerges from the interactions within the network of biomolecules (e.g. DNA, mRNA, proteins), and, hence, understanding how drugs impact upon the entire network should improve their efficacy at returning the network (body) to physiological homeostasis. Large, mechanism-based computer models, such as the anticipated human whole body models (silicon or virtual human), may help in the development of such network-targeting drugs. Using the philosophical concept of weak and strong emergence, we shall here take a more general look at the paradigm of network-targeting drugs, and propose our approaches to scale the strength of strong emergence. We apply these approaches to several biological examples and demonstrate their utility to reveal principles of bio-modeling. We discuss this in the perspective of building the silicon human. [less ▲]

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See detailLow stress weekends promote adaptation to stressful weeks: The design principles of the biological response to stress
Yilmaz, Nilgun; Kolodkin, Alexey UL; Plant, Nick et al

Poster (2012)

Robustness is a fundamental and essential property of evolvable biological systems. It provides system to conserve its functionalities against internal/external perturbations and uncertainties. Product ... [more ▼]

Robustness is a fundamental and essential property of evolvable biological systems. It provides system to conserve its functionalities against internal/external perturbations and uncertainties. Product inhibition, feed-forward and feed-back inhibition and stimulation, and regulatory loops within signal transduction networks are a few of the approaches generated by biological systems to maintain both their robustness and adaptability. In this study, we are able to show the interaction of the stress hormone cortisol with its two nuclear receptors, the high affinity glucocorticoid receptor (GR) and the low affinity pregnane X-receptor (PXR) by using a mathematical model based on realistic kinetic parameters. We checked the importance of regulatory loops, within this network, in terms of pharmacodynamic and pharmacokinetic responses. Then, we demonstrate the alterations in the system response with respect to variable cortisol perturbations, such as initial single peak in cortisol, and repeated stimuli of cortisol with differing frequencies and time frames. As a conclusion, we reveal that the network is robust towards low frequency perturbations, shows adaptation at moderate stress frequencies, but transitions to an altered steady state at high frequency stimulation, which we believe is a predisposing factor towards stress-induced pathologies. [less ▲]

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See detailSulfolobus Systems Biology: Cool hot design for metabolic pathways
Kouril, T.; Kolodkin, Alexey UL; Zaparty, M. et al

in Systems Biology of Microorganisms (2012)

Life at high temperature challenges the stability of macromolecules and cellular components, but also the stability of metabolites, which has received little attention. For the cell, the thermal ... [more ▼]

Life at high temperature challenges the stability of macromolecules and cellular components, but also the stability of metabolites, which has received little attention. For the cell, the thermal instability of metabolites means it has to deal with the loss of free energy and carbon, or in more extremes, it might result in the accumulation of dead-end compounds. In order to elucidate the requirements and principles of metabolism at high temperature, we used a comparative blueprint modelling approach of the lower part of the glycolysis cycle. The conversion of glyceraldehyde 3-phosphate to pyruvate from the thermoacidophilic Crenarchaeon Sulfolobus solfataricus P2 (optimal growth-temperature 80ºC) was modelled based on the available blueprint model of the eukaryotic model organism Saccharomyces cerevisiae (optimal growth-temperature of 30ºC). In S. solfataricus only one reaction is different, namely glyceraldehyde-3-phosphate is directly converted into 3-phosphoglycerate by the non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase, omitting the extremely heat-instable 1,3-bisphosphoglycerate. By taking the temperature dependent non-enzymatic (spontaneous) degradation of 1,3-bisphosphoglycerate in account, modelling reveals that a hot lifestyle requires a cool design. [less ▲]

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