Towards a genome-scale kinetic model of cellular metabolism

<p>Abstract</p> <p>Background</p> <p>Advances in bioinformatic techniques and analyses have led to the availability of genome-scale metabolic reconstructions. The size and complexity of such networks often means that their potential behaviour can only be analysed with constraint-based methods. Whilst requiring minimal experimental data, such methods are unable to give insight into cellular substrate concentrations. Instead, the long-term goal of systems biology is to use kinetic modelling to characterize fully the mechanics of each enzymatic reaction, and to combine such knowledge to predict system behaviour.</p> <p>Results</p> <p>We describe a method for building a parameterized genome-scale kinetic model of a metabolic network. Simplified linlog kinetics are used and the parameters are extracted from a kinetic model repository. We demonstrate our methodology by applying it to yeast metabolism. The resultant model has 956 metabolic reactions involving 820 metabolites, and, whilst approximative, has considerably broader remit than any existing models of its type. Control analysis is used to identify key steps within the system.</p> <p>Conclusions</p> <p>Our modelling framework may be considered a stepping-stone toward the long-term goal of a fully-parameterized model of yeast metabolism. The model is available in SBML format from the BioModels database (BioModels ID: MODEL1001200000) and at <url>http://www.mcisb.org/resources/genomescale/</url>.</p

Further developments towards a genome-scale metabolic model of yeast

BACKGROUND: To date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to constraint-based analyses because of lack of pathway connectivity. RESULTS: We have expanded the yeast network reconstruction to incorporate many new reactions from the literature and represented these in a well-annotated and standards-compliant manner. The new reconstruction comprises 1102 unique metabolic reactions involving 924 unique metabolites - significantly larger in scope than any previous reconstruction. The representation of lipid metabolism in particular has improved, with 234 out of 268 enzymes linked to lipid metabolism now present in at least one reaction. Connectivity is emphatically improved, with more than 90% of metabolites now reachable from the growth medium constituents. The present updates allow constraint-based analyses to be performed; viability predictions of single knockouts are comparable to results from in vivo experiments and to those of previous reconstructions. CONCLUSIONS: We report the development of the most complete reconstruction of yeast metabolism to date that is based upon reliable literature evidence and richly annotated according to MIRIAM standards. The reconstruction is available in the Systems Biology Markup Language (SBML) and via a publicly accessible database http://www.comp-sys-bio.org/yeastnet/

Achaiki Iatriki : official publication of the medical society of western Greece and Peloponnesus

In the current issue, the editorial by Cauchi et al. argues for eco-friendly measures in endoscopy and emphasies the role of healthcare providers in reducing waste. The editorial adeptly employs the three Rs (Reduce, Reuse, Recycle) framework to tackle waste management, offering practical solutions. The editorial by Milionis et al. focuses on the reverse cascade screening for paediatric familial hypercholesterolaemia (FH), which is an upcoming tool for public health. Advantages, practices, and challenges regarding FH are thoroughly discussed. Lastly, the editorial by Fousekis et al. presents the main aspects of a chronic immune-mediated cutaneous disease, dermatitis herpetiformis (DH), which constitutes an extraintestinal manifestation of celiac disease, including its diagnosis, pathogenesis, and management. Moreover, this issue includes three review articles. The review article by Krontira et al. discusses the evolving data on the epidemiology, diagnostic approach and appropriate management of foreign body and caustic substance ingestion, based on updated guidelines published by gastroenterological and endoscopic societies. The review by Halliasos et al. provides data on the clinical presentation, diagnosis, and management of metastatic acute spinal cord compression, focusing on the importance of a multidisciplinary team approach, including spine surgeons, radiation oncologists, medical oncologists, palliative care clinicians, physiotherapists, and psychologists. Lastly, the review by Schinas et al. outlines the potential of immune modulation in the treatment of infections and the need for individualised approaches in the modern world of personalised medicine by examining some of the key strategies and immune-based therapies being developed to combat infectious diseases.peer-reviewe

Integrating food webs with metabolic networks: modeling contaminant degradation in marine ecosystems

Georg Basler is supported by a Marie Curie Intra European Fellowship within the 7th European Community Framework Programme, ERC grant agreement number 329682. Evangelos Simeonidis is supported by the Luxembourg Centre for Systems Biomedicine.Peer reviewedPeer Reviewe

Optimisation of biochemical systems

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Flux balance analysis: A geometric perspective

Advances in the field of bioinformatics have led to reconstruction of genome-scale networks for a number of key organisms. The application of physicochemical constraints to these stoichiometric networks allows researchers, through methods such as flux balance analysis, to highlight key sets of reactions necessary to achieve particular objectives. The key benefits of constraint-based analysis lie in the minimal knowledge required to infer systemic properties. However, network degeneracy leads to a large number of flux distributions that satisfy any objective; moreover, these distributions may be dominated by biologically irrelevant internal cycles. By examining the geometry underlying the problem, we define two methods for finding a unique solution within the space of all possible flux distributions; such a solution contains no internal cycles, and is representative of the space as a whole. The first method draws on typical geometric knowledge, but cannot be applied to large networks because of the high computational complexity of the problem. Thus a second method, an iteration of linear programs which scales easily to the genome scale, is defined. The algorithm is run on four recent genome-scale models, and unique flux solutions are found. The algorithm set out here will allow researchers in flux balance analysis to exchange typical solutions to their models in a reproducible format. Moreover, having found a single solution, statistical analyses such as correlations may be performed