Hanan L. Messiha

Systems Biology: The elements and principles of Life

Systems Biology has a mission that puts it at odds with traditional paradigms of physics and molecular biology, such as the simplicity requested by Occams razor and minimum energy/maximal efficiency. By referring to biochemical experiments on control and regulation, and on flux balancing in yeast, we show that these paradigms are inapt. Systems Biology does not quite converge with biology either: Although it certainly requires accurate ‘stamp collecting’, it discovers quantitative laws. Systems Biology is a science of its own, discovering own fundamental principles, some of which we identify here.

A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes

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.

Systematic integration of experimental data and models in systems biology

BackgroundThe behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources.ResultsTaverna workflows have been developed for the automated assembly of quantitative parameterised metabolic networks in the Systems Biology Markup Language (SBML). A SBML model is built in a systematic fashion by the workflows which starts with the construction of a qualitative network using data from a MIRIAM-compliant genome-scale model of yeast metabolism. This is followed by parameterisation of the SBML model with experimental data from two repositories, the SABIO-RK enzyme kinetics database and a database of quantitative experimental results. The models are then calibrated and simulated in workflows that call out to COPASIWS, the web service interface to the COPASI software application for analysing biochemical networks. These systems biology workflows were evaluated for their ability to construct a parameterised model of yeast glycolysis.ConclusionsDistributed information about metabolic reactions that have been described to MIRIAM standards enables the automated assembly of quantitative systems biology models of metabolic networks based on user-defined criteria. Such data integration processes can be implemented as Taverna workflows to provide a rapid overview of the components and their relationships within a biochemical system.

Enzyme kinetics and computational modeling for systems biology.

Enzyme kinetics is a century-old area of biochemical research which is regaining popularity due to its use in systems biology. Computational models of biochemical networks depend on rate laws and kinetic parameter values that describe the behavior of enzymes in the cellular milieu. While there is a considerable body of enzyme kinetic data available from the past several decades, a large number of enzymes of specific organisms were never assayed or were assayed in conditions that are irrelevant to those models. The result is that systems biology projects are having to carry out large numbers of enzyme kinetic assays. This chapter reviews the main methodologies of enzyme kinetic data analysis and proposes using computational modeling software for that purpose. It applies the biochemical network modeling software COPASI to data from enzyme assays of yeast triosephosphate isomerase (EC 5.3.1.1).

The photochemical mechanism of a B12-dependent photoreceptor protein.

The coenzyme B12-dependent photoreceptor protein, CarH, is a bacterial transcriptional regulator that controls the biosynthesis of carotenoids in response to light. On binding of coenzyme B12 the monomeric apoprotein forms tetramers in the dark, which bind operator DNA thus blocking transcription. Under illumination the CarH tetramer dissociates, weakening its affinity for DNA and allowing transcription. The mechanism by which this occurs is unknown. Here we describe the photochemistry in CarH that ultimately triggers tetramer dissociation; it proceeds via a cob(III)alamin intermediate, which then forms a stable adduct with the protein. This pathway is without precedent and our data suggest it is independent of the radical chemistry common to both coenzyme B12 enzymology and its known photochemistry. It provides a mechanistic foundation for the emerging field of B12 photobiology and will serve to inform the development of a new class of optogenetic tool for the control of gene expression.

Enzyme kinetics informatics: from instrument to browser

A limited number of publicly available resources provide access to enzyme kinetic parameters. These have been compiled through manual data mining of published papers, not from the original, raw experimental data from which the parameters were calculated. This is largely due to the lack of software or standards to support the capture, analysis, storage and dissemination of such experimental data. Introduced here is an integrative system to manage experimental enzyme kinetics data from instrument to browser. The approach is based on two interrelated databases: the existing SABIO‐RK database, containing kinetic data and corresponding metadata, and the newly introduced experimental raw data repository, MeMo‐RK. Both systems are publicly available by web browser and web service interfaces and are configurable to ensure privacy of unpublished data. Users of this system are provided with the ability to view both kinetic parameters and the experimental raw data from which they are calculated, providing increased confidence in the data. A data analysis and submission tool, the kineticswizard, has been developed to allow the experimentalist to perform data collection, analysis and submission to both data resources. The system is designed to be extensible, allowing integration with other manufacturer instruments covering a range of analytical techniques.

Reaction of Morphinone Reductase with 2-Cyclohexen-1-one and 1-Nitrocyclohexene PROTON DONATION, LIGAND BINDING, AND THE ROLE OF RESIDUES HISTIDINE 186 AND ASPARAGINE 189

Morphinone reductase (MR) catalyzes the NADH-dependent reduction of α/β unsaturated carbonyl compounds in a reaction similar to that catalyzed by Old Yellow Enzyme (OYE1). The two enzymes are related at the sequence and structural levels, but key differences in active site architecture exist which have major implications for the reaction mechanism. We report detailed kinetic and solution NMR data for wild-type MR and two mutant forms in which residues His-186 and Asn-189 have been exchanged for alanine residues. We show that both residues are involved in the binding of the reducing nicotinamide coenzyme NADH and also the binding of the oxidizing substrates 2-cyclohexen-1-one and 1-nitrocyclohexene. Reduction of 2-cyclohexen-1-one by FMNH2 is concerted with proton transfer from an unknown proton donor in the active site. NMR spectroscopy and flavin reoxidation studies with 2-cyclohexen-1-one are consistent with His-186 being unprotonated in oxidized, reduced, and ligand-bound MR, suggesting that His-186 is not the key proton donor required for the reduction of 2-cyclohexen-1-one. Hydride transfer is decoupled from proton transfer with 1-nitrocyclohexene as oxidizing substrate, and unlike with OYE1 the intermediate nitronate species produced after hydride transfer from FMNH2 is not converted to 1-nitrocyclohexane. The work highlights key mechanistic differences in the reactions catalyzed by MR and OYE1 and emphasizes the need for caution in inferring mechanistic similarities in structurally related proteins.

Regulation of the activity of lactate dehydrogenases from four lactic acid bacteria

Background: Lactate dehydrogenases (LDHs) are key metabolic enzymes in lactic acid bacteria (LAB). Results: The effects of fructose 1,6-bisphosphate, phosphate, pH, and ionic strength on enzyme activity differ for six LDHs from four LAB. Conclusion: The regulation of LDH activity differs among LAB. Significance: These results have implications for understanding enzyme evolutionary adaptation, for quantitative comparative modeling, and for biotechnological application of LAB. Despite high similarity in sequence and catalytic properties, the l-lactate dehydrogenases (LDHs) in lactic acid bacteria (LAB) display differences in their regulation that may arise from their adaptation to different habitats. We combined experimental and computational approaches to investigate the effects of fructose 1,6-bisphosphate (FBP), phosphate (Pi), and ionic strength (NaCl concentration) on six LDHs from four LABs studied at pH 6 and pH 7. We found that 1) the extent of activation by FBP (Kact) differs. Lactobacillus plantarum LDH is not regulated by FBP, but the other LDHs are activated with increasing sensitivity in the following order: Enterococcus faecalis LDH2 ≤ Lactococcus lactis LDH2 < E. faecalis LDH1 < L. lactis LDH1 ≤ Streptococcus pyogenes LDH. This trend reflects the electrostatic properties in the allosteric binding site of the LDH enzymes. 2) For L. plantarum, S. pyogenes, and E. faecalis, the effects of Pi are distinguishable from the effect of changing ionic strength by adding NaCl. 3) Addition of Pi inhibits E. faecalis LDH2, whereas in the absence of FBP, Pi is an activator of S. pyogenes LDH, E. faecalis LDH1, and L. lactis LDH1 and LDH2 at pH 6. These effects can be interpreted by considering the computed binding affinities of Pi to the catalytic and allosteric binding sites of the enzymes modeled in protonation states corresponding to pH 6 and pH 7. Overall, the results show a subtle interplay among the effects of Pi, FBP, and pH that results in different regulatory effects on the LDHs of different LABs.

KiPar, a tool for systematic information retrieval regarding parameters for kinetic modelling of yeast metabolic pathways

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 users 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/).

A new regulatory principle for in vivo biochemistry: Pleiotropic low affinity regulation by the adenine nucleotides – Illustrated for the glycolytic enzymes of Saccharomyces cerevisiae

We test this hypothesis in terms of the effect that ATP, ADP, and AMP might have on the major free‐energy delivering pathway of the yeast Saccharomyces cerevisiae. Assaying cell‐free extracts, we collected a comprehensive set of quantitative kinetic data concerning the enzymes of the glycolytic and the ethanol fermentation pathways. We determined systematically the extent to which the enzyme activities depend on the concentrations of the adenine nucleotides. We found that the effects of the adenine nucleotides on enzymes catalysing reactions in which they are not directly involved as substrate or product, are substantial. This includes effects on the Michaelis–Menten constants, adding new perspective on these, 100 years after their introduction.