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Showing papers by "Douglas B. Kell published in 2009"


Journal ArticleDOI
TL;DR: The Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists, believes that it will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge.
Abstract: Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.

880 citations


Journal ArticleDOI
10 Apr 2009-Science
TL;DR: Altering the stimulation intervals gave different patterns of NF-κB–dependent gene expression, which supports the idea that oscillation frequency has a functional role in nuclear factor κB regulation.
Abstract: The nuclear factor kappa B (NF-kappa B) transcription factor regulates cellular stress responses and the immune response to infection. NF-kappa B activation results in oscillations in nuclear NF-kappa B abundance. To define the function of these oscillations, we treated cells with repeated short pulses of tumor necrosis factor-alpha at various intervals to mimic pulsatile inflammatory signals. At all pulse intervals that were analyzed, we observed synchronous cycles of NF-kappa B nuclear translocation. Lower frequency stimulations gave repeated full-amplitude translocations, whereas higher frequency pulses gave reduced translocation, indicating a failure to reset. Deterministic and stochastic mathematical models predicted how negative feedback loops regulate both the resetting of the system and cellular heterogeneity. Altering the stimulation intervals gave different patterns of NF-kappa B-dependent gene expression, which supports the idea that oscillation frequency has a functional role.

541 citations


Journal ArticleDOI
TL;DR: The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular reactive oxygen species (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive as discussed by the authors.
Abstract: The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular 'reactive oxygen species' (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation.

452 citations


Journal ArticleDOI
TL;DR: The observed drift in instrumental performance over time and its improvement with adjustment of the length of analytical block are described and allowed the authors to prepare SOPs for "fit for purpose" long-term UPLC-MS metabolomic studies, such as are being employed in the HUSERMET project.
Abstract: A method for performing untargeted metabolomic analysis of human serum has been developed based on protein precipitation followed by Ultra Performance Liquid Chromatography and Time-of-Flight mass spectrometry (UPLC−TOF-MS). This method was specifically designed to fulfill the requirements of a long-term metabolomic study, spanning more than 3 years, and it was subsequently thoroughly evaluated for robustness and repeatability. We describe here the observed drift in instrumental performance over time and its improvement with adjustment of the length of analytical block. The optimal setup for our purpose was further validated against a set of serum samples from 30 healthy individuals. We also assessed the reproducibility of chromatographic columns with the same chemistry of stationary phase from the same manufacturer but from different production batches. The results have allowed the authors to prepare SOPs for “fit for purpose” long-term UPLC−MS metabolomic studies, such as are being employed in the HUSER...

416 citations


Journal ArticleDOI
22 Jun 2009-Analyst
TL;DR: The combination of accurate mass data for a large collection of metabolites, theoretical isotope abundance data and knowledge of the different ion types detected provided a greater number of electrospray mass spectrometric signals which were putatively identified and with greater confidence in the samples studied.
Abstract: The chemical identification of mass spectrometric signals in metabolomic applications is important to provide conversion of analytical data to biological knowledge about metabolic pathways. The complexity of electrospray mass spectrometric data acquired from a range of samples (serum, urine, yeast intracellular extracts, yeast metabolic footprints, placental tissue metabolic footprints) has been investigated and has defined the frequency of different ion types routinely detected. Although some ion types were expected (protonated and deprotonated peaks, isotope peaks, multiply charged peaks) others were not expected (sodium formate adduct ions). In parallel, the Manchester Metabolomics Database (MMD) has been constructed with data from genome scale metabolic reconstructions, HMDB, KEGG, Lipid Maps, BioCyc and DrugBank to provide knowledge on 42,687 endogenous and exogenous metabolite species. The combination of accurate mass data for a large collection of metabolites, theoretical isotope abundance data and knowledge of the different ion types detected provided a greater number of electrospray mass spectrometric signals which were putatively identified and with greater confidence in the samples studied. To provide definitive identification metabolite-specific mass spectral libraries for UPLC-MS and GC-MS have been constructed for 1,065 commercially available authentic standards. The MMD data are available at http://dbkgroup.org/MMD/.

263 citations


Journal ArticleDOI
TL;DR: A method for the preparation and GC-TOF-MS analysis of human serum samples has been developed and evaluated for application in long-term metabolomic studies and showed the ability to define metabolite differences between samples from a population and samples spiked with metabolites standards.
Abstract: A method for the preparation and GC-TOF-MS analysis of human serum samples has been developed and evaluated for application in long-term metabolomic studies. Serum samples were deproteinized using 3:1 methanol/serum, dried in a vacuum concentrator, and chemically derivatized in a two-stage process. Samples were analyzed by GC-TOF-MS with a 25 min analysis time. In addition, quality control (QC) samples were used to quantify process variability. Optimization of chemical derivatization was performed. Products were found to be stable for 30 h after derivatization. An assessment of within-day repeatability and within-week reproducibility demonstrates that excellent performance is observed with our developed method. Analyses were consistent over a 5 month period. Additional method testing, using spiked serum samples, showed the ability to define metabolite differences between samples from a population and samples spiked with metabolites standards. This methodology allows the continuous acquisition and application of data acquired over many months in long-term metabolomic studies, including the HUSERMET project (http://www.husermet.org/).

187 citations


Journal ArticleDOI
TL;DR: The predictive ability and speed of two additional machine learning methods, radial basis function neural networks (RBFNN) and Kriging, are assessed with respect to previous MLP based polarisable water models, and combinations are found that are no less accurate, yet are 58% faster for the dimer, and 26% slower for the pentamer.
Abstract: To model liquid water correctly and to reproduce its structural, dynamic and thermodynamic properties warrants models that account accurately for electronic polarisation. We have previously demonstrated that polarisation can be represented by fluctuating multipole moments (derived by quantum chemical topology) predicted by multilayer perceptrons (MLPs) in response to the local structure of the cluster. Here we further develop this methodology of modeling polarisation enabling control of the balance between accuracy, in terms of errors in Coulomb energy and computing time. First, the predictive ability and speed of two additional machine learning methods, radial basis function neural networks (RBFNN) and Kriging, are assessed with respect to our previous MLP based polarisable water models, for water dimer, trimer, tetramer, pentamer and hexamer clusters. Compared to MLPs, we find that RBFNNs achieve a 14–26% decrease in median Coulomb energy error, with a factor 2.5–3 slowdown in speed, whilst Kriging achieves a 40–67% decrease in median energy error with a 6.5–8.5 factor slowdown in speed. Then, these compromises between accuracy and speed are improved upon through a simple multi-objective optimisation to identify Pareto-optimal combinations. Compared to the Kriging results, combinations are found that are no less accurate (at the 90th energy error percentile), yet are 58% faster for the dimer, and 26% faster for the pentamer.

128 citations


Journal ArticleDOI
TL;DR: This work compares the similarity of known drugs and library compounds to naturally occurring metabolites (endogenites) using relevant cheminformatics molecular descriptor spaces in which known drugs are more akin to such endogenites than are most library compounds.

123 citations


Journal ArticleDOI
TL;DR: This approach reveals a complex sequence-fitness mapping, and hypotheses for the physical basis of aptameric binding, and enables rapid design of novel aptamers with desired binding properties, and demonstrates an extension to the approach by incorporating prior knowledge into CLADE, resulting in some of the tightest binding sequences.
Abstract: Mapping the landscape of possible macromolecular polymer sequences to their fitness in performing biological functions is a challenge across the biosciences A paradigm is the case of aptamers, nucleic acids that can be selected to bind particular target molecules We have characterized the sequence-fitness landscape for aptamers binding allophycocyanin (APC) protein via a novel Closed Loop Aptameric Directed Evolution (CLADE) approach In contrast to the conventional SELEX methodology, selection and mutation of aptamer sequences was carried out in silico, with explicit fitness assays for 44,131 aptamers of known sequence using DNA microarrays in vitro We capture the landscape using a predictive machine learning model linking sequence features and function and validate this model using 5500 entirely separate test sequences, which give a very high observed versus predicted correlation of 087 This approach reveals a complex sequence-fitness mapping, and hypotheses for the physical basis of aptameric binding; it also enables rapid design of novel aptamers with desired binding properties We demonstrate an extension to the approach by incorporating prior knowledge into CLADE, resulting in some of the tightest binding sequences

112 citations


Journal ArticleDOI
01 Nov 2009-Placenta
TL;DR: Differences in the factors released from villous trophoblast from uncomplicated pregnancies and those with PE are investigated, suggesting that hypoxia may have a role in the placental pathogenesis of PE.

87 citations


Journal ArticleDOI
TL;DR: Drug uptake is understood to be mainly transporter-mediated, which suggests that uptake transporters may be a major determinant of idiosyncratic drug response and a site at which drug-drug interactions occur.
Abstract: Drug entry into cells was previously believed to be via diffusion through the lipid bilayer of the cell membrane, with the contribution to uptake by transporter proteins being of only marginal importance. Now, however, drug uptake is understood to be mainly transporter-mediated. This suggests that uptake transporters may be a major determinant of idiosyncratic drug response and a site at which drug-drug interactions occur. Accurately modelling drug pharmacokinetics is a problem of Systems Biology and requires knowledge of both the transporters with which a drug interacts and where those transporters are expressed in the body. Current physiology-based pharmacokinetic models mostly attempt to model drug disposition from the biophysical properties of the drug, drug uptake by diffusion being thereby an implicit assumption. It is clear that the incorporation of transporter proteins and their drug interactions into such models will greatly improve them. We discuss methods by which tissue localisations and transporter interactions can be determined. We propose a yeast-based transporter expression system for the initial screening of drugs for their cognate transporters. Finally, the central importance of computational modelling of transporter substrate preferences by structure-activity relationships is discussed.

Journal ArticleDOI
TL;DR: A whirlwind tour of recent projects to transform scholarly publishing paradigms, culminating in Utopia and the Semantic Biochemical Journal experiment, and an experiment to rescue data from the dormant pages of published documents.
Abstract: We live in interesting times. Portents of impending catastrophe pervade the literature, calling us to action in the face of unmanageable volumes of scientific data. But it isn't so much data generation per se, but the systematic burial of the knowledge embodied in those data that poses the problem: there is so much information available that we simply no longer know what we know, and finding what we want is hard – too hard. The knowledge we seek is often fragmentary and disconnected, spread thinly across thousands of databases and millions of articles in thousands of journals. The intellectual energy required to search this array of data-archives, and the time and money this wastes, has led several researchers to challenge the methods by which we traditionally commit newly acquired facts and knowledge to the scientific record. We present some of these initiatives here – a whirlwind tour of recent projects to transform scholarly publishing paradigms, culminating in Utopia and the Semantic Biochemical Journal experiment. With their promises to provide new ways of interacting with the literature, and new and more powerful tools to access and extract the knowledge sequestered within it, we ask what advances they make and what obstacles to progress still exist? We explore these questions, and, as you read on, we invite you to engage in an experiment with us, a real-time test of a new technology to rescue data from the dormant pages of published documents. We ask you, please, to read the instructions carefully. The time has come: you may turn over your papers…

Journal ArticleDOI
TL;DR: Starting from a random population, in four generations CLADE produced a new aptamer to thrombin with high specificity and affinity, and the best aptameric sequence was void of the set of four guanine repeats typifyingThrombin aptamers and highlights the benefits of evolution performed in an environment closely mimicking the final diagnostic application.

Journal ArticleDOI
TL;DR: This study demonstrates that arrays of OFETs, when combined with a data analysis technique using Genetic Programming (GP), can selectively detect airborne analytes in real time.
Abstract: Electronic noses (e-noses) are increasingly being used as vapour sensors in a range of application areas. E-noses made up of arrays of organic field-effect transistors (OFETs) are particularly valuable due the range and diversity of the information which they provide concerning analyte binding. This study demonstrates that arrays of OFETs, when combined with a data analysis technique using Genetic Programming (GP), can selectively detect airborne analytes in real time. The use of multiple parameters – on resistance, off current and mobility – collected from multiple transistors coated with different semiconducting polymers gives dramatic improvements in the sensitivity (true positive rate), specificity (true negative rate) and speed of sensing. Computer-controlled data collection allows the identification of analytes in real-time, with a time-lag between exposure and detection of the order of 4 s.

Journal ArticleDOI
TL;DR: Key to the system's usability is its direct exploitation of semantics, which gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.
Abstract: In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are ad hoc collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research. To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks. The toolkit, named Utopia, is freely available from http://utopia.cs.man.ac.uk/ .

Journal ArticleDOI
TL;DR: To calibrate the system, known thrombin binding aptamers (TBAs) have been mutated systematically, producing large populations that allow exploration of key structural aspects of the overall binding motif, creating a detailed model based on over 40 000 analyses, describing key features for quadruplex-forming sequences.
Abstract: DNA sequences that can bind selectively and specifically to target molecules are known as aptamers. Normally such binding analyses are performed using soluble aptamers. However, there is much to be gained by using an on-chip or microarray format, where a large number of aptameric DNA sequences can be interrogated simultaneously. To calibrate the system, known thrombin binding aptamers (TBAs) have been mutated systematically, producing large populations that allow exploration of key structural aspects of the overall binding motif. The ability to discriminate between background noise and low affinity binding aptamers can be problematic on arrays, and we use the mutated sequences to establish appropriate experimental conditions and their limitations for two commonly used fluorescence-based detection methods. Having optimized experimental conditions, high-density oligonucleotide microarrays were used to explore the entire loop–sequence–functionality relationship creating a detailed model based on over 40 000 analyses, describing key features for quadruplex-forming sequences.

Journal ArticleDOI
TL;DR: In this article, the authors demonstrate a cost-effective but fast multiparameter data acquisition system for odour sensors based on low threshold organic field effect transistors (OFETs) with an amorphous methoxy-derivative of poly(triaryl amine) (PTA-OMe) as semiconductor.
Abstract: We demonstrate a cost-effective but fast multiparameter data acquisition system for odour sensors based on low threshold organic field effect transistors (OFETs) with an amorphous methoxy-derivative of poly(triaryl amine) (PTA-OMe) as semiconductor. The system applies a simple algorithm to measure OFET saturated transfer characteristics with a tailored operational amplifier circuit that is interfaced to a laptop that controls the circuit and analyses data with bespoke software. Despite the semiconductor's low charge carrier mobility μ ∼ 5 × 10 −5 Vs/cm 2 , the system returns multiparameter OFET data: OFET source–drain current I SD in both the ‘on’ and ‘off’ state, carrier mobility μ , and threshold ( V T ), in real time (resolution PrOH > EtOH > MeOH.

Journal ArticleDOI
TL;DR: Making use of the NK fitness landscape model, the effects of mutation rate, crossover and selection pressure on the performance of directed evolution are analysed and it is found that purely evolutionary techniques fare better than do model-based approaches across all but the smoothest landscapes.

Journal ArticleDOI
TL;DR: It is suggested that the lower number of reactions and parameters makes these models suitable for integrating them with models of metabolism or of the cell cycle in S. cerevisiae and for studies in the human pathogen Candida albicans as well as other less well-characterized fungal species.
Abstract: Cyclic adenosine monophosphate (cAMP) has a key signaling role in all eukaryotic organisms. In Saccharomyces cerevisiae, it is the second messenger in the Ras/PKA pathway which regulates nutrient sensing, stress responses, growth, cell cycle progression, morphogenesis, and cell wall biosynthesis. A stochastic model of the pathway has been reported. We have created deterministic mathematical models of the PKA module of the pathway, as well as the complete cAMP pathway. First, a simplified conceptual model was created which reproduced the dynamics of changes in cAMP levels in response to glucose addition in wild-type as well as cAMP phosphodiesterase deletion mutants. This model was used to investigate the role of the regulatory Krh proteins that had not been included previously. The Krh-containing conceptual model reproduced very well the experimental evidence supporting the role of Krh as a direct inhibitor of PKA. These results were used to develop the Complete cAMP Model. Upon simulation it illustrated several important features of the yeast cAMP pathway: Pde1p is more important than is Pde2p for controlling the cAMP levels following glucose pulses; the proportion of active PKA is not directly proportional to the cAMP level, allowing PKA to exert negative feedback; negative feedback mechanisms include activating Pde1p and deactivating Ras2 via phosphorylation of Cdc25. The Complete cAMP model is easier to simulate, and although significantly simpler than the existing stochastic one, it recreates cAMP levels and patterns of changes in cAMP levels observed experimentally in vivo in response to glucose addition in wild-type as well as representative mutant strains such as pde1Δ, pde2Δ, cyr1Δ, and others. The complete model is made available in SBML format. We suggest that the lower number of reactions and parameters makes these models suitable for integrating them with models of metabolism or of the cell cycle in S. cerevisiae. Similar models could be also useful for studies in the human pathogen Candida albicans as well as other less well-characterized fungal species.

16 Mar 2009
TL;DR: Carrier-mediated and active uptake of drugs is far more common than is usually assumed and has considerable implications for the design of libraries for drug discovery and development, as well as for chemical genetics/genomics and systems chemistry.
Abstract: It is widely believed that most drug molecules are transported across the phospholipid bilayer portion of biological membranes via passive diffusion at a rate related to their lipophilicity (expressed as log P, a calculated c log P or as log D, the octanol:water partition coefficient). However, studies of this using purely phospholipid bilayer membranes have been very misleading since transfer across these typically occurs via the solvent reservoirs or via aqueous pore defects, neither of which are prevalent in biological cells. Since the types of biophysical forces involved in the interaction of drugs with lipid membrances are no different from those involved in their interaction with proteins, arguments based on lipophilicity also apply to drug uptake by membrane transporters or carriers. A similar story attaches to the history of mechanistic explanations of the mode of action of general anaesthetics (narcotics). Carrier-mediated and active uptake of drugs is far more common than is usually assumed. This has considerable implications for the design of libraries for drug discovery and development, as well as for chemical genetics/genomics and systems chemistry.

Journal ArticleDOI
TL;DR: In the version of this article initially published, the wrong versions of Figures 1, 2 and 3 were used, which has been corrected in the HTML and PDF versions of the article.
Abstract: Nat. Biotechnol. 27 735–741 (2009); published online 7 August 2009; corrected after print 11 August 2009 In the version of this article initially published, the wrong versions of Figures 1, 2 and 3 were used. The error has been corrected in the HTML and PDF versions of the article.

Journal ArticleDOI
TL;DR: KiPar is a dedicated information retrieval system designed to facilitate access to the literature relevant for kinetic modelling of a given metabolic pathway in yeast, and develops an integrative approach, combining public data and software resources for the rapid development of large-scale text mining tools targeting complex biological information.
Abstract: Motivation: Most experimental evidence on kinetic parameters is buried in the literature, whose manual searching is complex, time consuming and partial. These shortcomings become particularly acute in systems biology, where these parameters need to be integrated into detailed, genome-scale, metabolic models. These problems are addressed by KiPar, a dedicated information retrieval system designed to facilitate access to the literature relevant for kinetic modelling of a given metabolic pathway in yeast. Searching for kinetic data in the context of an individual pathway offers modularity as a way of tackling the complexity of developing a full metabolic model. It is also suitable for large-scale mining, since multiple reactions and their kinetic parameters can be specified in a single search request, rather than one reaction at a time, which is unsuitable given the size of genome-scale models. Results: We developed an integrative approach, combining public data and software resources for the rapid development of large-scale text mining tools targeting complex biological information. The user supplies input in the form of identifiers used in relevant data resources to refer to the concepts of interest, e.g. EC numbers, GO and SBO identifiers. By doing so, the user is freed from providing any other knowledge or terminology concerned with these concepts and their relations, since they are retrieved from these and cross-referenced resources automatically. The terminology acquired is used to index the literature by mapping concepts to their synonyms, and then to textual documents mentioning them. The indexing results and the previously acquired knowledge about relations between concepts are used to formulate complex search queries aiming at documents relevant to the user's information needs. The conceptual approach is demonstrated in the implementation of KiPar. Evaluation reveals that KiPar performs better than a Boolean search. The precision achieved for abstracts (60%) and full-text articles (48%) is considerably better than the baseline precision (44% and 24%, respectively). The baseline recall is improved by 36% for abstracts and by 100% for full text. It appears that full-text articles are a much richer source of information on kinetic data than are their abstracts. Finally, the combined results for abstracts and full text compared with the curated literature provide high values for relative recall (88%) and novelty ratio (92%), suggesting that the system is able to retrieve a high proportion of new documents. Availability: Source code and documentation are available at: http://www.mcisb.org/resources/kipar/ Contact:i.spasic@manchester.ac.uk; dbk@manchester.ac.uk Supplementary information:Supplementary data are available at Bioinformatics online.

Journal ArticleDOI
TL;DR: A data model and information management solution for the data gathered through high content live cell imaging experiments, and an algorithm that automatically annotates results of these experiments with the timings of translocations and periods of any oscillatory translocations as they are uploaded to the repository.
Abstract: Background: High content live cell imaging experiments are able to track the cellular localisation of labelled proteins in multiple live cells over a time course. Experiments using high content live cell imaging will generate multiple large datasets that are often stored in an ad-hoc manner. This hinders identification of previously gathered data that may be relevant to current analyses. Whilst solutions exist for managing image data, they are primarily concerned with storage and retrieval of the images themselves and not the data derived from the images. There is therefore a requirement for an information management solution that facilitates the indexing of experimental metadata and results of high content live cell imaging experiments. Results: We have designed and implemented a data model and information management solution for the data gathered through high content live cell imaging experiments. Many of the experiments to be stored measure the translocation of fluorescently labelled proteins from cytoplasm to nucleus in individual cells. The functionality of this database has been enhanced by the addition of an algorithm that automatically annotates results of these experiments with the timings of translocations and periods of any oscillatory translocations as they are uploaded to the repository. Testing has shown the algorithm to perform well with a variety of previously unseen data. Conclusion: Our repository is a fully functional example of how high throughput imaging data may be effectively indexed and managed to address the requirements of end users. By implementing the automated analysis of experimental results, we have provided a clear impetus for individuals to ensure that their data forms part of that which is stored in the repository. Although focused on imaging, the solution provided is sufficiently generic to be applied to other functional proteomics and genomics experiments. The software is available from: fhttp://code.google.com/p/livecellim/


Journal ArticleDOI
06 Aug 2009-Nature
TL;DR: PrP can sequester cellular iron in insoluble PrP– ferritin complexes, making it biounavailable, leading to increased iron uptake and an overall excess of iron in brain tissue, and recognition of this could have a colossal effect on thinking and provide new therapeutic options based on iron chelation for these and other syndromes.
Abstract: If X alone and Y alone cannot explain a phenomenon, sometimes together they can. As the late biochemist Henrik Kacser remarked: “To understand the whole you must look at the whole.” Prion diseases, for example, are closely associated with the conformational change of the prion protein PrP from its normal form to an aggregating, autocatalysing, pathologic form, PrP. But clumping prions don’t tell the whole story. Their levels often correlate poorly with disease progression, and it is far from clear how a simple conformational change leads to the holes in brain tissue seen in late-stage disease. It is also clear that poorly liganded iron is highly neurotoxic, mainly because it can spur the production of the highly reactive and toxic hydroxyl radical OH — heavily involved in the progression of many other degenerative diseases and ageing. Neena Singh at Case Western Reserve University in Cleveland, Ohio, and her colleagues have now tied these two disparate threads together. PrP , they found, can sequester cellular iron in insoluble PrP– ferritin complexes, making it biounavailable, leading to increased iron uptake and an overall excess of iron in brain tissue (A. Singh et al., PLoS Pathog. 5, e1000336; 2009). Modified iron metabolism is found in both scrapie and sporadic Creutzfeldt–Jakob disease, and such work stresses that it is not only the total amount of Fe(ii) and Fe(iii) that matters but their speciation. It is yet to be shown whether PrP–ferritin complexes catalyse OH production directly, but if they do, this could account for the massive damage observed. Recognition of this could have a colossal effect on our thinking and provide new therapeutic (and dietary) options based on iron chelation for these and other syndromes. INVERTEBRATE IMMUNITY

01 Jan 2009
TL;DR: Numerical simulations of the NF-κB system suggest that the entrainment phenomena observed in pulse-stimulated experiments is a consequence of the high intensity of the stimulation.
Abstract: Background: Sustained stimulation with tumour necrosis factor α (TNFα) induces substantial oscillations—observed at both the single cell and population levels—in the nuclear factor κB (NF-κB) system. Although the mechanism has not yet been elucidated fully, a core system has been identified consisting of a negative feedback loop involving NF-κB (RelA:p50 hetero-dimer) and its inhibitor IκBα. Many authors have suggested that this core oscillator should couple to other oscillatory pathways. Results: First we analyse single-cell data from experiments in which the NF-κB system is forced by short trains of strong pulses of TNFα. Power spectra of the ratio of nuclear to cytoplasmic concentration of NF-κB suggest that the cells' responses are entrained by the pulsing frequency. Using a recent model of the NF-κB system due to Caroline Horton, we carried out extensive numerical simulations to analyze the response frequencies induced by trains of pulses of TNFα stimulation having a wide range of frequencies and amplitudes. These studies suggest that for sufficiently weak stimulation, various nonlinear resonances should be observable. To explore further the possibility of probing alternative feedback mechanisms, we also coupled the model to sinusoidal signals signals with a wide range of strengths and frequencies. Our results show that, at least in simulation, frequencies other than those of the forcing and the main NF-κB oscillator can be excited via sub- and superharmonic resonance, producing quasiperiodic and even chaotic dynamics. Conclusions: Our numerical results suggest that the entrainment phenomena observed in pulse-stimulated experiments is a consequence of the high intensity of the stimulation. Computational studies based on current models suggest that resonant interactions between periodoc pulsatile forcing and the system's natural frequencies may become evident for sufficiently weak stimulation. Further simulations suggest that the nonlinearities of the NF-κB feedback oscillator mean that even sinusoidally modulated forcing can induce a rich variety of nonlinear interactions.


01 Aug 2009
TL;DR: Systems Biology is chosen as an exemplar with which to illustrate some of the challenges the authors face in biology, and how mathematics can assist us in meeting them and thereby helping us to understand biological systems in a quantitative and predictive manner.
Abstract: Douglas B. Kell, School of Chemistry and The Manchester Interdisciplinary Biocentre, University of Manchester and Chief Executive of the BBSRC Modern biology is predictive and quantitative, and thereby necessarily mathematical [1]. Even the largely qualitative era of molecular biology and genetics could not have happened without mathematics and computation – witness the importance of the Fourier transform in X-ray crystallography [2] and indeed in modern mass spectrometries (see e.g.[3]). Modern genetics is highly quantitative (e.g. [4; 5] – and needs to be [6] http://blogs.bbsrc.ac.uk/index.php/2008/12/when-genetics -meets-the-environment/). As part of this special issue on ‘Whither Mathematics in the UK?’, I have chosen to pick Systems Biology as an exemplar with which to illustrate some of the challenges we face in biology, and how mathematics (which I take to include related numerical disciplines such as statistics, probability, computation, algorithmics and so on) can assist us in meeting them and thereby helping us to understand biological systems in a quantitative and predictive manner. Note the existence of chemometrics (e.g. [7; 8]) as an entire field that covers the application of mathematical methods to problems of (bio)chemistry. The balkanisation of the science and its literature [9-13] means that chem(o)informatics [14; 15] is seen (and has developed) as a discipline largely separate from chemometrics!

18 Dec 2009
TL;DR: In this paper, the Hoffmann model was used to analyze the dynamical properties of Hoffmann's large computational model (containing 24 variables and 64 parameters) by using computational and analytical methods and give an explanation of the source of oscillations.
Abstract: NF-κB oscillations were suggested by Hoffmann et al from electro-mobility shift assays (EMSA) in population studies of IκBα-/- embryonic fibroblasts and simulated in a computational model. NF-κB oscillations were also observed by Nelson et al at the single cell level. The Hoffmann model gave a fairly good pre- diction of Nelson et al oscillatory experimental data using fluorescent proteins. A common comment on the source of oscillations is the existence of negative feedback loops. Just from the point of mathematics, we can set up a simple system containing a negative feedback loop that possesses oscillating behaviour resembling the ones observed in the experiments like Fonslet et al did. However, different models with similar structures can have dramatically different dynam- ical behaviour. In order to understand biological mechanisms, it is necessary to work on those real models that are based on experimental data even though models may be very large. In this paper, we are able to analyze the dynamical properties of Hoffmann’s large computational model (containing 24 variables and 64 parameters) by using computational and analytical methods and give an explanation of the source of oscillations. We find that the computational model can be treated as a fast-slow system where the level of total IκB Kinase (IKK) is treated as a slow variable. If we consider the limit in which the level of total IKK does not change at all, then we can take the level of total IKK as a parameter. Since the total NF-κB is conserved in the model, we can also view the total NF-κB as a parameter. If the actual variation of IKK is sufficiently slow, then orbits in the true system trace attractors in the reduced model. We find that for some range of the level of NF-κB, the reduced system experiences Hopf bifurcation twice while varying the level of total IKK. The damped oscillations observed in the computational system come from the existence of stable limit cycles and stable spirals in the reduced system family.