References of "Simeonidis, Vangelis 50003096"
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See detailIntegrating food webs with metabolic networks: modeling contaminant degradation in marine ecosystems
Basler, George; Simeonidis, Vangelis UL

in Frontiers in Genetics (2015), 6

A commentary on: Bioremediation in marine ecosystems: a computational study combining ecological modeling and flux balance analysis by Taffi, M., Paoletti, N., Angione, C., Pucciarelli, S., Marini, M. and ... [more ▼]

A commentary on: Bioremediation in marine ecosystems: a computational study combining ecological modeling and flux balance analysis by Taffi, M., Paoletti, N., Angione, C., Pucciarelli, S., Marini, M. and Liò, P. (2014). Front Genet 5:319. doi: 10.3389/fgene.2014.00319 [less ▲]

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See detailGenome-scale modeling for metabolic engineering
Simeonidis, Vangelis UL; Price, Nathan

in Journal of Industrial Microbiology & Biotechnology (2015), 42(3), 327338

We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the ... [more ▼]

We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information—an area which we expect will become increasingly important for metabolic engineering—and present recent developments in the field of metabolic and regulatory integration. [less ▲]

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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 detailMediaDB: A Database of Microbial Growth Conditions in Defined Media
Richards, Matthew A.; Cassen, Victor; Heavner, Benjamin D. et al

in PLoS ONE (2014), 9(8), 103548

Isolating pure microbial cultures and cultivating them in the laboratory on defined media is used to more fully characterize the metabolism and physiology of organisms. However, identifying an appropriate ... [more ▼]

Isolating pure microbial cultures and cultivating them in the laboratory on defined media is used to more fully characterize the metabolism and physiology of organisms. However, identifying an appropriate growth medium for a novel isolate remains a challenging task. Even organisms with sequenced and annotated genomes can be difficult to grow, despite our ability to build genome-scale metabolic networks that connect genomic data with metabolic function. The scientific literature is scattered with information about defined growth media used successfully for cultivating a wide variety of organisms, but to date there exists no centralized repository to inform efforts to cultivate less characterized organisms by bridging the gap between genomic data and compound composition for growth media. Here we present MediaDB, a manually curated database of defined media that have been used for cultivating organisms with sequenced genomes, with an emphasis on organisms with metabolic network models. The database is accessible online, can be queried by keyword searches or downloaded in its entirety, and can generate exportable individual media formulation files. The data assembled in MediaDB facilitate comparative studies of organism growth media, serve as a starting point for formulating novel growth media, and contribute to formulating media for in silico investigation of metabolic networks. MediaDB is freely available for public use at https://mediadb.systemsbiology.net. [less ▲]

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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 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 detailA model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes
Smallbone, Kieran; Messiha, Hanan L.; Carroll, Kathleen M. et al

in FEBS Letters (2013), 587(17), 2832-2841

We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an ... [more ▼]

We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a ‘‘cycle of knowledge’’ strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought. [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 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 detailCandidate mutations for early-onset lung cancer by family genome sequencing
Simeonidis, Vangelis UL; Roach, Jared; Brunkow, Mary et al

Poster (2011, July)

Early-onset lung cancer has been studied as a rare, but distinct, sub-type of lung cancer. Genome-wide association studies (GWAS) have linked several genes with this form of malignancy. We sequenced the ... [more ▼]

Early-onset lung cancer has been studied as a rare, but distinct, sub-type of lung cancer. Genome-wide association studies (GWAS) have linked several genes with this form of malignancy. We sequenced the genomes of a family quartet in which one of the offspring was diagnosed with early-onset lung cancer at about 48 years of age. The family has a history of heavy smoking and the father had in the past been diagnosed with head and neck cancer. The DNA source was blood, which leads us to concentrate our analysis on Mendelian inheritance models. To make the inheritance pattern explicit, we establish the parental origin of the offspring’s genomes through phasing of their chromosomes. This helps identify whether mutations in the proband came from the father or the mother. More than 18 million sequence variants were initially identified in the proband through comparison to the hg19 reference genome. We reduce this list to fewer than 200 potentially functional variants (e.g. single nucleotide variations and short indels) present in the genomes of the proband and at least one parent, by applying a series of filters. We refine the list of candidate mutations further by comparison to gene candidates from GWAS studies and genes that are mutated in lung cancer tissue as recorded by The Cancer Genome Atlas. The results of our analysis are discussed and conclusions about possible causative mutations for early-onset lung cancer are drawn. [less ▲]

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See detailChasing the flux: selecting target pathways through flux analysis of carbon metabolism
Simeonidis, Vangelis UL; Murabito, Ettore; Smallbone, Kieran et al

Poster (2011, June 26)

One of the goals of Systems Biology is to develop and utilise high-throughput methods for the measurement of parameters and concentrations on a genome-wide scale, while at the same time generating ... [more ▼]

One of the goals of Systems Biology is to develop and utilise high-throughput methods for the measurement of parameters and concentrations on a genome-wide scale, while at the same time generating predictive models for system behaviour. In studying genome-scale metabolic networks, the task of exhaustively assaying and measuring all reaction components can be daunting, because hundreds or even thousands of enzymes (activities and concentrations) need to be considered for the construction of a full-scale, detailed model. There is a clear need for strategies that allow us to systematically select the subsets of pathways and reactions which should be prioritized when studying metabolism. We present a methodology for selecting those reactions that carry the overwhelming majority of the carbon flux through the metabolic network. The recent community-driven reconstruction of the metabolic network of baker’s yeast [1] provides the basis for our analysis. Flux Balance Analysis provides a theoretical flux distribution. Results are constrained with GC-MS exometabolomic measurements of the carbon flux. Flux calculations can also be improved by using 13C measurements to determine intracellular metabolic fluxes. The solution of the constrained FBA problem gives us a ranked list of reactions, based on the amount of carbon flux through each reaction. We improve the specificity of the method further by performing an Elementary Flux Mode analysis, which provides us with target pathways consisting of the reactions that carry the most carbon flux. Our methodology allows us to cover more than 95% of the carbon flux by studying but a small subset of the reactions of the genome-scale metabolic network of baker’s yeast. [less ▲]

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See detailAnalysis of biochemical networks using linear programming
Simeonidis, Vangelis UL; Dartnell, Lewis; Bogle, I. David L. et al

in Proceedings of the 7th World Congress of Chemical Engineering on CD-ROM (2005, December)

The application of mathematical programming methodologies to biochemical systems is demonstrated with the presentation of a linear programming (LP) algorithm for calculating minimal pathway distances in ... [more ▼]

The application of mathematical programming methodologies to biochemical systems is demonstrated with the presentation of a linear programming (LP) algorithm for calculating minimal pathway distances in biochemical networks. Minimal pathway distances are identified as the smallest number of steps separating two nodes in the network. Two case studies are examined: 1) the minimal distances for Escherichia coli Small Molecule Metabolism (SMM) enzymes are calculated and their correlations with genome distance and enzyme function are considered; 2) a study of the p53 cell cycle and apoptosis control network is performed in order to assess the survivability of the network to both random node failures and a directed assault, by studying the modification of the network’s diameter for successive protein knockouts. The results verify the applicability of the algorithm to problems of biochemical nature. [less ▲]

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