The silicon trypanosome: a test case of iterative model extension in systems biology

Abstract

The African trypanosome, Trypanosoma brucei, is a unicellular parasite causing African Trypanosomiasis (sleeping sickness in humans and nagana in animals). Due to some of its unique properties, it has emerged as a popular model organism in systems biology. A predictive quantitative model of glycolysis in the bloodstream form of the parasite has been constructed and updated several times. The Silicon Trypanosome is a project that brings together modellers and experimentalists to improve and extend this core model with new pathways and additional levels of regulation. These new extensions and analyses use computational methods that explicitly take different levels of uncertainty into account. During this project, numerous tools and techniques have been developed for this purpose, which can now be used for a wide range of different studies in systems biology.

Keywords: Differential equations; Dynamic modelling; Metabolomics; Systems biology; Transcriptomics; Trypanosoma brucei; Uncertainty.

Figure 1. General Bayesian framework for explicitly handling uncertainty in the SilicoTryp project.

Figure 2. Glycolysis in T. brucei as previously published [7].

Abbreviations: Glc-6-P = glucose 6-phosphate, Fru-6-P = fructose 6-phosphate, Fru-1,6-BP = fructose 1,6-bisphosphate, DHAP = dihydroxyacetone phosphate, GA-3-P = glyceraldehyde 3-phosphate, Gly-3-P = glycerol 3-phosphate, 1,3-BPGA = 1,3-bisphosphoglycerate, 3-PGA = 3-phosphoglycerate, 2-PGA = 2-phosphoglycerate, PEP = phosphoenolpyruvate. Reprinted from [15], under the Creative Commons Attribution License.

Figure 3. Example page of the SilicoTryp wiki.

Chemical and rate equations are described, and sources for each parameter are documented in detail.

Figure 4. Evaluation of parameter uncertainties and their effect on the model results.

. Reprinted with permission from [17]. Copyright 2013 American Chemical Society.

Figure 5. Log-likelihood (goodness of fit to experimental data) of models with increasing glycosome permeability and cytosolic activities of the glycosomal enzymes.

The higher the log-likelihood, the better the match between simulations and experimental results. Each model is simulated with a range of parameter sets that describes our uncertainty about the parameter values. See [21] for details. Modified with permission from [21]. Copyright 2013 John Wiley and Sons.

Figure 6. Two hypotheses tested to solve the topology of the pentose phosphate pathway.

In black, the reactions of the glycolysis model, in green the reactions introduced to model the pentose phosphate pathway. Abbreviations not present in Figure 2: 6-PGl = 6-phosphogluconolactone, 6-PG = 6-phosphogluconate, Rul-5-P = ribulose 5-phosphate, Rib-5-P = ribose 5-phosphate, TS₂ = trypanothione disulfide, T(SH)₂ = trypanothione.

Figure 7. Stochiometric map of the trypanothione pathway.

The blue asterisks indicate which metabolites are found C13-labelled when all glucose carbons are ¹³C-labelled. The turquoise asterisks indicate which metabolites are labelled when glutamine is labelled. The methionine salvage pathway, marked as 1, does not seem to be active in T. brucei (see text). The origin of ornithine, marked as 2, remains uncertain. Abbreviations: Orn = ornithine, Gly = glycine, Met = Methionine, γ-GC = γ-glutamylcysteine, SAM = S-adenosylmethionine, dcSAM = decarboxylated S-adenosylmethonine, Spd = spermidine, GSp = glutathionylspermidine, MTA = methylthioadenosine, MTR-1P = methylthioribose 1-phosphate, Glc = glucose, G6P = glucose 6-phosphate, Pyr = pyruvate, TS₂ = trypanothione disulfide, T(SH)₂ = trypanothione.

Figure 8. Workflow applied for dissecting the kinetics mechanism of trypanothione synthetase.

Modified with permission from [10]. Copyright 2013 American Society for Biochemistry and Molecular Biology.

Figure 9. Transcription/Translation module that will be added for every enzyme of the model.

The module is based on the model published by Haanstra et al. [12]. The rate constants of the various processes involved are indicated by k, μ is the specific growth rate of the trypanosomes, and ribosomes represents the number of ribosomes per molecule of mRNA.