Consistent parameter sets for large kinetic models.

<p>(A) The metabolic network provides a frame for formulating parameter dependencies. Stationary fluxes , concentrations <i>c</i>, and equilibrium constants must be thermodynamically consistent. (B) For each reaction, the Michaelis constants and need to agree with the predefined quantities , , and . (C) Given a consistent parameter set, enzymatic reactions can be safely connected. The resulting model will actualise a predefined steady state, with rate laws satisfying the following conditions: (i) Quantities shared by several reactions – for instance, metabolite concentrations – have the same values in each of them. (ii) For internal metabolites, incoming and outgoing fluxes are balanced. (iii) Quantities that arise from differences along reactions satisfy the Wegscheider conditions: for instance, their sums over closed loops vanish. (iv) The kinetic constants satisfy the Haldane relationships, which relate the kinetic constants of a rate law to the equilibrium constant of the reaction. (v) Flux directions agree with thermodynamic forces, given by the negative differences of chemical potentials.</p

Stages of data addition (+) and method runs ([>]) in the workflow.

<p>Letters and numbers in parentheses refer, respectively, to input data and to the stages of the workflow. (1) Geometric FBA <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079195#pone.0079195-Smallbone4" target="_blank">[32]</a> is run, yielding a thermodynamically feasible, stationary flux distribution matching the flux data; (2) a sub-network of flux-carrying reactions is exported, (3) consistent values of all metabolite concentrations and equilibrium constants are determined, (4) kinetic constants appearing in the sub-network are balanced, (5) kinetic rate laws and associated kinetic constants are inserted into the model, and (6) the maximal reaction rates are adjusted to reproduce the steady-state fluxes calculated before. The laboratory data feeding into “Flux” can include quantitative metabolomic measurements of metabolites, and also dynamically calculated flux values for the network. The lower half of the diagram shows a cycle of experimentation and modelling: here the result of the MCA can be used to target which rate laws should be measured <i>in vitro</i> after measurement, this rate law can be substituted into the model, with a view to better fit the observed perturbation behaviour. All grey arrows refer to aspects of the workflow where additional data can be added in as knowledge increases. The pathway shown is a truncated version of the trehalose pathway. Abbreviations: T6P = trehalose 6-phosphate; aaT = - trehalase; Glu = Glucose; G6P = glucose 6-phosphate.</p

Overall flux control exerted by different enzymes in glycolysis.

<p>The general flux control exerted by a reaction is quantified by , the sum of squared scaled control coefficients. Control coefficients were calculated at the operating state from the large-scale yeast model and from the five original models<i>^a</i> used to define the flux and concentration values. Only a selection of enzymes appearing in the original models are shown<i>^b</i>.</p>a<p>Model references are as follows BM:61 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079195#pone.0079195-Hynne1" target="_blank">[43]</a>, BM:64 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079195#pone.0079195-Teusink2" target="_blank">[44]</a>, BM:172 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079195#pone.0079195-Pritchard1" target="_blank">[45]</a>, BM:176 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079195#pone.0079195-Conant1" target="_blank">[46]</a>, and BM:177 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079195#pone.0079195-Conant1" target="_blank">[46]</a></p>b<p>Abbreviations as follows: ADH, alcohol dehydrogenase, reverse reaction; ATPase, cytosolic ATPase; Eno, enolase; FBPA, fructose-bisphosphate aldolase; G3PDH, glycerol-3-phosphate dehydrogenase; GAL3PD, glyceraldehyde-3-phosphate dehydrogenase; GluT, glucose transport; HXK, hexokinase; PFK, phosphofructokinase; PGK, phosphoglycerate kinase; PGM, phosphoglycerate mutase.</p

Fluxes and control coefficients in the yeast metabolic model.

<p>(A) Fluxes obtained from Geometric FBA. Only selected reactions with large fluxes are depicted, co-substrates are not shown (flux directions and magnitudes shown by arrows). (B) Flux control coefficients. Top: Control exerted by the glucose transporter (GluT). Unscaled flux control coefficients are shown in shades of blue (positive values) and red (negative values). Bottom: control exerted by the biomass production reaction. High-flux reactions respond most strongly: an increased glucose import increases the glycolytic flux, while increased biomass production directs fluxes to other pathways and thereby decreases the glycolytic flux. Flux control coefficients for a model with allosteric regulation are shown in Figures G and H in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079195#pone.0079195.s001" target="_blank">File S1</a>.</p

Record-level versioning and release-level versioning.

<p>Record-level versioning and release-level versioning.</p

Contributions and roles related to content as they correspond to identifier creation versus identifier reuse.

<p>The decision about whether to create a new identifier or reuse an existing one depends on the role you play in the creation, editing, and republishing of content; for certain roles (and when several roles apply) that decision is a judgement call. Asterisks convey cases in which the best course of action is often to correct/improve the original record in collaboration with the original source; the guidance about identifier creation versus reuse is meant to apply only when such collaboration is not practicable (and an alternate record is created). It is common that a given actor may have multiple roles along this spectrum; for instance, a given record in monarchinitiative.org may reflect a combination of (a) corrections Monarch staff made in collaboration with the original data source, (b) post-ingest curation by Monarch staff, (c) expanded content integrated from multiple sources.</p

A summary of the 10 recommendations and their direct or indirect impact on different kinds of identifier roles.

<p>A summary of the 10 recommendations and their direct or indirect impact on different kinds of identifier roles.</p

Anatomy of a web-based identifier.

<p>An example of an exemplary unique resource identifier (URI) is below; it is comprised of American Standard Code for Information Interchange (ASCII) characters and follows a pattern that starts with a fixed set of characters (URI pattern). That URI pattern is followed by a local identifier (local ID)—an identifier which, by itself, is only guaranteed to be locally unique within the database or source. A local ID is sometimes referred to as an “accession.” Note this figure illustrates the simplest representation; nuances regarding versioning are covered in Lesson 6 and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001414#pbio.2001414.g005" target="_blank">Fig 5</a>.</p

Desirable characteristics for database identifiers in the life sciences.

<p>Desirable characteristics for database identifiers in the life sciences.</p

Eagle-i record-level citation widget.

<p>Eagle-i record-level citation widget.</p