EnzymeML: seamless data flow and modeling of enzymatic data.

The design of biocatalytic reaction systems is highly complex owing to the dependency of the estimated kinetic parameters on the enzyme, the reaction conditions, and the modeling method. Consequently, reproducibility of enzymatic experiments and reusability of enzymatic data are challenging. We developed the XML-based markup language EnzymeML to enable storage and exchange of enzymatic data such as reaction conditions, the time course of the substrate and the product, kinetic parameters and the kinetic model, thus making enzymatic data findable, accessible, interoperable and reusable (FAIR). The feasibility and usefulness of the EnzymeML toolbox is demonstrated in six scenarios, for which data and metadata of different enzymatic reactions are collected and analyzed. EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling of enzyme kinetics, publication platforms and enzymatic reaction databases. EnzymeML is open and transparent, and invites the community to contribute. All documents and codes are freely available at https://enzymeml.org .

Deoxyxylulose 5-Phosphate Synthase Does Not Play a Major Role in Regulating the Methylerythritol 4-Phosphate Pathway in Poplar.

The plastidic 2-C-methylerythritol 4-phosphate (MEP) pathway supplies the precursors of a large variety of essential plant isoprenoids, but its regulation is still not well understood. Using metabolic control analysis (MCA), we examined the first enzyme of this pathway, 1-deoxyxylulose 5-phosphate synthase (DXS), in multiple grey poplar (Populus × canescens) lines modified in their DXS activity. Single leaves were dynamically labeled with 13CO2 in an illuminated, climate-controlled gas exchange cuvette coupled to a proton transfer reaction mass spectrometer, and the carbon flux through the MEP pathway was calculated. Carbon was rapidly assimilated into MEP pathway intermediates and labeled both the isoprene released and the IDP+DMADP pool by up to 90%. DXS activity was increased by 25% in lines overexpressing the DXS gene and reduced by 50% in RNA interference lines, while the carbon flux in the MEP pathway was 25-35% greater in overexpressing lines and unchanged in RNA interference lines. Isoprene emission was also not altered in these different genetic backgrounds. By correlating absolute flux to DXS activity under different conditions of light and temperature, the flux control coefficient was found to be low. Among isoprenoid end products, isoprene itself was unchanged in DXS transgenic lines, but the levels of the chlorophylls and most carotenoids measured were 20-30% less in RNA interference lines than in overexpression lines. Our data thus demonstrate that DXS in the isoprene-emitting grey poplar plays only a minor part in controlling flux through the MEP pathway.

Functional Characterisation of Three Glycine N-Acyltransferase Variants and the Effect on Glycine Conjugation to Benzoyl-CoA.

The glycine conjugation pathway in humans is involved in the metabolism of natural substrates and the detoxification of xenobiotics. The interactions between the various substrates in this pathway and their competition for the pathway enzymes are currently unknown. The pathway consists of a mitochondrial xenobiotic/medium-chain fatty acid: coenzyme A (CoA) ligase (ACSM2B) and glycine N-acyltransferase (GLYAT). The catalytic mechanism and substrate specificity of both of these enzymes have not been thoroughly characterised. In this study, the level of evolutionary conservation of GLYAT missense variants and haplotypes were analysed. From these data, haplotype variants were selected (156Asn > Ser, [17Ser > Thr,156Asn > Ser] and [156Asn > Ser,199Arg > Cys]) in order to characterise the kinetic mechanism of the enzyme over a wide range of substrate concentrations. The 156Asn > Ser haplotype has the highest frequency and the highest relative enzyme activity in all populations studied, and hence was used as the reference in this study. Cooperative substrate binding was observed, and the kinetic data were fitted to a two-substrate Hill equation. The coding region of the GLYAT gene was found to be highly conserved and the rare 156Asn > Ser,199Arg > Cys variant negatively affected the relative enzyme activity. Even though the 156Asn > Ser,199Arg > Cys variant had a higher affinity for benzoyl-CoA (s0.5,benz = 61.2 µM), kcat was reduced to 9.8% of the most abundant haplotype 156Asn > Ser (s0.5,benz = 96.6 µM), while the activity of 17Ser > Thr,156Asn > Ser (s0.5,benz = 118 µM) was 73% of 156Asn > Ser. The in vitro kinetic analyses of the effect of the 156Asn > Ser,199Arg > Cys variant on human GLYAT enzyme activity indicated that individuals with this haplotype might have a decreased ability to metabolise benzoate when compared to individuals with the 156Asn > Ser variant. Furthermore, the accumulation of acyl-CoA intermediates can inhibit ACSM2B leading to a reduction in mitochondrial energy production.

The thioredoxin redox potential and redox charge are surrogate measures for flux in the thioredoxin system.

The thioredoxin system plays a central role in intracellular redox regulation and its dysregulation is associated with a number of pathologies. However, the connectivity within this system poses a significant challenge for quantification and consequently several disparate measures have been used to characterize the system. For in vitro studies, the thioredoxin system flux has been measured by NADPH oxidation while the thioredoxin redox state has been used to estimate the activity of the system in vivo. The connection between these measures has been obscure although substrate saturation in the thioredoxin system results from the saturation of the thioredoxin redox cycle. We used computational modeling and in vitro kinetic assays to clarify the relationship between flux and the current in vivo measures of the thioredoxin system together with a novel measure, the thioredoxin redox charge (reduced thioredoxin/total thioredoxin). Our results revealed that the thioredoxin redox potential and redox charge closely tracked flux perturbations showing that these indices could be used as surrogate measures of the flux in vivo and, provide a mechanistic explanation for the previously observed correlations between thioredoxin oxidation and certain pathologies. While we found no significant difference in the linear correlations obtained for the thioredoxin redox potential and redox charge with the flux, the redox charge may be preferred because it is bounded between zero and one and can be determined over a wider range of conditions allowing for quantitative flux comparisons between cell types and conditions.

PySCeSToolbox: a collection of metabolic pathway analysis tools.

Summary: PySCeSToolbox is an extension to the Python Simulator for Cellular Systems (PySCeS) that includes tools for performing generalized supply-demand analysis, symbolic metabolic control analysis, and a framework for investigating the kinetic and thermodynamic aspects of enzyme-catalyzed reactions. Each tool addresses a different aspect of metabolic behaviour, control, and regulation; the tools complement each other and can be used in conjunction to better understand higher level system behaviour. Availability and implementation: PySCeSToolbox is available on Linux, Mac OS X and Windows. It is licensed under the BSD 3-clause licence. Code, setup instructions and a link to documentation can be found at https://github.com/PySCeS/PyscesToolbox. Contact: jr@sun.ac.za. Supplementary information: Supplementary data are available at Bioinformatics online.

Deoxyxylulose 5-Phosphate Synthase Controls Flux through the Methylerythritol 4-Phosphate Pathway in Arabidopsis.

The 2-C-methylerythritol 4-phosphate (MEP) pathway supplies precursors for plastidial isoprenoid biosynthesis including carotenoids, redox cofactor side chains, and biogenic volatile organic compounds. We examined the first enzyme of this pathway, 1-deoxyxylulose 5-phosphate synthase (DXS), using metabolic control analysis. Multiple Arabidopsis (Arabidopsis thaliana) lines presenting a range of DXS activities were dynamically labeled with 13CO2 in an illuminated, climate-controlled, gas exchange cuvette. Carbon was rapidly assimilated into MEP pathway intermediates, but not into the mevalonate pathway. A flux control coefficient of 0.82 was calculated for DXS by correlating absolute flux to enzyme activity under photosynthetic steady-state conditions, indicating that DXS is the major controlling enzyme of the MEP pathway. DXS manipulation also revealed a second pool of a downstream metabolite, 2-C-methylerythritol-2,4-cyclodiphosphate (MEcDP), metabolically isolated from the MEP pathway. DXS overexpression led to a 3- to 4-fold increase in MEcDP pool size but to a 2-fold drop in maximal labeling. The existence of this pool was supported by residual MEcDP levels detected in dark-adapted transgenic plants. Both pools of MEcDP are closely modulated by DXS activity, as shown by the fact that the concentration control coefficient of DXS was twice as high for MEcDP (0.74) as for 1-deoxyxylulose 5-phosphate (0.35) or dimethylallyl diphosphate (0.34). Despite the high flux control coefficient for DXS, its overexpression led to only modest increases in isoprenoid end products and in the photosynthetic rate. Diversion of flux via MEcDP may partly explain these findings and suggests new opportunities to engineer the MEP pathway.

Incorporating covalent and allosteric effects into rate equations: the case of muscle glycogen synthase.

Several enzymes have been described that undergo both allosteric and covalent regulation, but, to date, there exists no succinct kinetic description that is able to account for both of these mechanisms of regulation. Muscle glycogen synthase, an enzyme implicated in the pathogenesis of several metabolic diseases, is activated by glucose 6-phosphate and inhibited by ATP and phosphorylation at multiple sites. A kinetic description of glycogen synthase could provide insight into the relative importance of these modifiers. In the present study we show, using non-linear parameter optimization with robust weight estimation, that a Monod-Wyman-Changeux model in which phosphorylation favours the inactive T conformation provides a satisfactory description of muscle glycogen synthase kinetics. The best-fit model suggests that glucose 6-phosphate and ATP compete for the same allosteric site, but that ATP also competes with the substrate UDP-glucose for the active site. The novelty of our approach lies in treating covalent modification as equivalent to allosteric modification. Using the obtained rate equation, the relationship between enzyme activity and phosphorylation state is explored and shown to agree with experimental results. The methodology we propose could also be applied to other enzymes that undergo both allosteric and covalent modification.

A special issue of Essays in Biochemistry on computational biology.

Computational biology is a diverse research field that has gained increasing importance over the last two decades. Broadly, it aims to apply computational approaches to advance our understanding of biological systems. This can take place on multiple levels, for example, by creating computational models of specific biological systems, by developing algorithms that assist in the analysis of experimental data, or by investigating fundamental biological design principles through modelling. The articles in this special issue highlight and review four such distinct applications of computational biology.

Computational models as catalysts for investigating redoxin systems.

Thioredoxin, glutaredoxin and peroxiredoxin systems play central roles in redox regulation, signaling and metabolism in cells. In these systems, reducing equivalents from NAD(P)H are transferred by coupled thiol-disulfide exchange reactions to redoxins which then reduce a wide array of targets. However, the characterization of redoxin activity has been unclear, with redoxins regarded as enzymes in some studies and redox metabolites in others. Consequently, redoxin activities have been quantified by enzyme kinetic parameters in vitro, and redox potentials or redox ratios within cells. By analyzing all the reactions within these systems, computational models showed that many kinetic properties attributed to redoxins were due to system-level effects. Models of cellular redoxin networks have also been used to estimate intracellular hydrogen peroxide levels, analyze redox signaling and couple omic and kinetic data to understand the regulation of these networks in disease. Computational modeling has emerged as a powerful complementary tool to traditional redoxin enzyme kinetic and cellular assays that integrates data from a number of sources into a single quantitative framework to accelerate the analysis of redoxin systems.

Quantifying redox transcription factor dynamics as a tool to investigate redox signalling.

A critical feature of the cellular antioxidant response is the induction of gene expression by redox-sensitive transcription factors. In many cells, activating these transcription factors is a dynamic process involving multiple redox steps, but it is unclear how these dynamics should be measured. Here, we show how the dynamic profile of the Schizosaccharomyces pombe Pap1 transcription factor is quantifiable by three parameters: signal amplitude, signal time and signal duration. In response to increasing hydrogen peroxide concentrations, the Pap1 amplitude decreased while the signal time and duration showed saturable increases. In co-response plots, these parameters showed a complex, non-linear relationship to the mRNA levels of four Pap1-regulated genes. We also demonstrate that hydrogen peroxide and tert-butyl hydroperoxide trigger quantifiably distinct Pap1 activation profiles and transcriptional responses. Based on these findings, we propose that different oxidants and oxidant concentrations modulate the Pap1 dynamic profile, leading to specific transcriptional responses. We further show how the effect of combination and pre-exposure stresses on Pap1 activation dynamics can be quantified using this approach. This method is therefore a valuable addition to the redox signalling toolbox that may illuminate the role of dynamics in determining appropriate responses to oxidative stress.

Network analysis of enzyme activities and metabolite levels and their relationship to biomass in a large panel of Arabidopsis accessions.

Natural genetic diversity provides a powerful resource to investigate how networks respond to multiple simultaneous changes. In this work, we profile maximum catalytic activities of 37 enzymes from central metabolism and generate a matrix to investigate species-wide connectivity between metabolites, enzymes, and biomass. Most enzyme activities change in a highly coordinated manner, especially those in the Calvin-Benson cycle. Metabolites show coordinated changes in defined sectors of metabolism. Little connectivity was observed between maximum enzyme activities and metabolites, even after applying multivariate analysis methods. Measurements of posttranscriptional regulation will be required to relate these two functional levels. Individual enzyme activities correlate only weakly with biomass. However, when they are used to estimate protein abundances, and the latter are summed and expressed as a fraction of total protein, a significant positive correlation to biomass is observed. The correlation is additive to that obtained between starch and biomass. Thus, biomass is predicted by two independent integrative metabolic biomarkers: preferential investment in photosynthetic machinery and optimization of carbon use.

Modelling the Decamerisation Cycle of PRDX1 and the Inhibition-like Effect on Its Peroxidase Activity.

Peroxiredoxins play central roles in the detoxification of reactive oxygen species and have been modelled across multiple organisms using a variety of kinetic methods. However, the peroxiredoxin dimer-to-decamer transition has been underappreciated in these studies despite the 100-fold difference in activity between these forms. This is due to the lack of available kinetics and a theoretical framework for modelling this process. Using published isothermal titration calorimetry data, we obtained association and dissociation rate constants of 0.050 µM-4·s-1 and 0.055 s-1, respectively, for the dimer-decamer transition of human PRDX1. We developed an approach that greatly reduces the number of reactions and species needed to model the peroxiredoxin decamer oxidation cycle. Using these data, we simulated horse radish peroxidase competition and NADPH-oxidation linked assays and found that the dimer-decamer transition had an inhibition-like effect on peroxidase activity. Further, we incorporated this dimer-decamer topology and kinetics into a published and validated in vivo model of PRDX2 in the erythrocyte and found that it almost perfectly reconciled experimental and simulated responses of PRDX2 oxidation state to hydrogen peroxide insult. By accounting for the dimer-decamer transition of peroxiredoxins, we were able to resolve several discrepancies between experimental data and available kinetic models.

Atypical network topologies enhance the reductive capacity of pathogen thiol antioxidant defense networks.

Infectious diseases are a significant health burden for developing countries, particularly with the rise of multidrug resistance. There is an urgent need to elucidate the factors underlying the persistence of pathogens such as Mycobacterium tuberculosis, Plasmodium falciparum and Trypanosoma brucei. In contrast to host cells, these pathogens traverse multiple and varied redox environments during their infectious cycles, including exposure to high levels of host-derived reactive oxygen species. Pathogen antioxidant defenses such as the peroxiredoxin and thioredoxin systems play critical roles in the redox stress tolerance of these cells. However, many of the kinetic rate constants obtained for the pathogen peroxiredoxins are broadly similar to their mammalian homologs and therefore, their contributions to the redox tolerances within these cells are enigmatic. Using graph theoretical analysis, we show that compared to a canonical Escherichia coli redoxin network, pathogen redoxin networks contain unique network connections (motifs) between their thioredoxins and peroxiredoxins. Analysis of these motifs reveals that they increase the hydroperoxide reduction capacity of these networks and, in response to an oxidative insult, can distribute fluxes into specific thioredoxin-dependent pathways. Our results emphasize that the high oxidative stress tolerance of these pathogens depends on both the kinetic parameters for hydroperoxide reduction and the connectivity within their thioredoxin/peroxiredoxin systems.

Reuteran and levan as carbohydrate sinks in transgenic sugarcane.

The present study reports the effect of high molecular weight bacterial fructan (levan) and glucan (reuteran) on growth and carbohydrate partitioning in transgenic sugarcane plants. These biopolymers are products of bacterial glycosyltransferases, enzymes that catalyze the polymerization of glucose or fructose residues from sucrose. Constructs, targeted to different subcellular compartments (cell wall and cytosol) and driven by the Cauliflower mosaic virus-35S: maize-ubiquitin promoter, were introduced into sugarcane by biolistic transformation. Polysaccharide accumulation severely affected growth of callus suspension cultures. Regeneration of embryonic callus tissue into plants proved problematic for cell wall-targeted lines. When targeted to the cytosol, only plants with relative low levels of biopolymer accumulation survived. In internodal stalk tissue that accumulate reuteran (max 0.03 mg/g FW), sucrose content (ca 60 mg/g FW) was not affected, while starch content (<0.4 mg/g FW) was increased up to four times. Total carbohydrate content was not significantly altered. On the other hand, starch and sucrose levels were significantly reduced in plants accumulating levan (max 0.01 mg/g FW). Heterologous expression resulted in a reduction in total carbohydrate assimilation rather than a simple diversion by competition for substrate.

Kinetic modelling of plant metabolic pathways.

This paper provides a review of kinetic modelling of plant metabolic pathways as a tool for analysing their control and regulation. An overview of different modelling strategies is presented, starting with those approaches that only require a knowledge of the network stoichiometry; these are referred to as structural. Flux-balance analysis, metabolic flux analysis using isotope labelling, and elementary mode analysis are briefly mentioned as three representative examples. The main focus of this paper, however, is a discussion of kinetic modelling, which requires, in addition to the stoichiometry, a knowledge of the kinetic properties of the constituent pathway enzymes. The different types of kinetic modelling analysis, namely time-course simulation, steady-state analysis, and metabolic control analysis, are explained in some detail. An overview is presented of strategies for obtaining model parameters, as well as software tools available for simulation of such models. The kinetic modelling approach is exemplified with discussion of three models from the general plant physiology literature. With the aid of kinetic modelling it is possible to perform a control analysis of a plant metabolic system, to identify potential targets for biotechnological manipulation, as well as to ascertain the regulatory importance of different enzymes (including isoforms of the same enzyme) in a pathway. Finally, a framework is presented for extending metabolic models to the whole-plant scale by linking biochemical reactions with diffusion and advective flow through the phloem. Future challenges include explicit modelling of subcellular compartments, as well as the integration of kinetic models on the different levels of the cellular and organizational hierarchy.

Enzymes or redox couples? The kinetics of thioredoxin and glutaredoxin reactions in a systems biology context.

Systems biology approaches, such as kinetic modelling, could provide valuable insights into how thioredoxins, glutaredoxins and peroxiredoxins (here collectively called redoxins), and the systems that reduce these molecules are regulated. However, it is not clear whether redoxins should be described as redox couples (with redox potentials) or as enzymes (with Michaelis-Menten parameters) in such approaches. We show that in complete redoxin systems, redoxin substrate saturation and other purported enzymatic behaviours result from limitations in the redoxin redox cycles in these systems. Michaelis-Menten parameters are therefore inappropriate descriptors of redoxin activity; data from redoxin kinetic experiments should rather be interpreted in terms of the complete system of reactions under study. These findings were confirmed by fitting kinetic models of the thioredoxin and glutaredoxin systems to in vitro datasets. This systems approach clarifies the inconsistencies with the descriptions of redoxins and emphasizes the roles of redoxin systems in redox regulation.

Identifying and characterising regulatory metabolites with generalised supply-demand analysis.

We present the framework of generalised supply-demand analysis (SDA) of a kinetic model of a cellular system, which can be applied to networks of arbitrary complexity. By fixing the concentrations of each of the variable species in turn and varying them in a parameter scan, rate characteristics of supply-demand are constructed around each of these species. By inspecting the shapes of the rate characteristic patterns and comparing the flux-response coefficients of the supply and demand blocks with the elasticities of the enzymes that interact directly with the fixed metabolite, regulatory metabolites in the system can be identified and characterised. The analysis provides information on whether and where the system is functionally differentiated and which of its species are homeostatically buffered. The novelty in our proposed method lies in the fact that all metabolites are considered for SDA (hence the term "generalised"), which removes investigator bias. It supplies an entry point for the further analysis and detailed characterisation of large models of cellular systems, in which the choice of metabolite around which to perform a SDA is not always obvious.

Delving deeper: Relating the behaviour of a metabolic system to the properties of its components using symbolic metabolic control analysis.

High-level behaviour of metabolic systems results from the properties of, and interactions between, numerous molecular components. Reaching a complete understanding of metabolic behaviour based on the system's components is therefore a difficult task. This problem can be tackled by constructing and subsequently analysing kinetic models of metabolic pathways since such models aim to capture all the relevant properties of the system components and their interactions. Symbolic control analysis is a framework for analysing pathway models in order to reach a mechanistic understanding of their behaviour. By providing algebraic expressions for the sensitivities of system properties, such as metabolic flux or steady-state concentrations, in terms of the properties of individual reactions it allows one to trace the high level behaviour back to these low level components. Here we apply this method to a model of pyruvate branch metabolism in Lactococcus lactis in order to explain a previously observed negative flux response towards an increase in substrate concentration. With this method we are able to show, first, that the sensitivity of flux towards changes in reaction rates (represented by flux control coefficients) is determined by the individual metabolic branches of the pathway, and second, how the sensitivities of individual reaction rates towards their substrates (represented by elasticity coefficients) contribute to this flux control. We also quantify the contributions of enzyme binding and mass-action to enzyme elasticity separately, which allows for an even finer-grained understanding of flux control. These analytical tools allow us to analyse the control properties of a metabolic model and to arrive at a mechanistic understanding of the quantitative contributions of each of the enzymes to this control. Our analysis provides an example of the descriptive power of the general principles of symbolic control analysis.

STRENDA DB: enabling the validation and sharing of enzyme kinetics data.

Standards for reporting enzymology data (STRENDA) DB is a validation and storage system for enzyme function data that incorporates the STRENDA Guidelines. It provides authors who are preparing a manuscript with a user-friendly, web-based service that checks automatically enzymology data sets entered in the submission form that they are complete and valid before they are submitted as part of a publication to a journal.

Kinetic model of sucrose accumulation in maturing sugarcane culm tissue.

Biochemically, it is not completely understood why or how commercial varieties of sugarcane (Saccharum officinarum) are able to accumulate sucrose in high concentrations. Such concentrations are obtained despite the presence of sucrose synthesis/breakdown cycles (futile cycling) in the culm of the storage parenchyma. Given the complexity of the process, kinetic modelling may help to elucidate the factors governing sucrose accumulation or direct the design of experimental optimisation strategies. This paper describes the extension of an existing model of sucrose accumulation (Rohwer, J.M., Botha, F.C., 2001. Analysis of sucrose accumulation in the sugar cane culm on the basis of in vitro kinetic data. Biochem. J. 358, 437-445) to account for isoforms of sucrose synthase and fructokinase, carbon partitioning towards fibre formation, and the glycolytic enzymes phosphofructokinase (PFK), pyrophosphate-dependent PFK and aldolase. Moreover, by including data on the maximal activity of the enzymes as measured in different internodes, a growth model was constructed that describes the metabolic behaviour as sugarcane parenchymal tissue matures from internodes 3-10. While there was some discrepancy between modelled and experimentally determined steady-state sucrose concentrations in the cytoplasm, steady-state fluxes showed a better fit. The model supports a hypothesis of vacuolar sucrose accumulation against a concentration gradient. A detailed metabolic control analysis of sucrose synthase showed that each isoform has a unique control profile. Fructose uptake by the cell and sucrose uptake by the vacuole had a negative control on the futile cycling of sucrose and a positive control on sucrose accumulation, while the control profile for neutral invertase was reversed. When the activities of these three enzymes were changed from their reference values, the effects on futile cycling and sucrose accumulation were amplified. The model can be run online at the JWS Online database (http://jjj.biochem.sun.ac.za/database/uys).