Proteomic and network analysis characterize stage-specific metabolism in Trypanosoma cruzi

Abstract

BackgroundTrypanosoma cruzi is a Kinetoplastid parasite of humans and is the cause of Chagas disease, a potentially lethal condition affecting the cardiovascular, gastrointestinal, and nervous systems of the human host. Constraint-based modeling has emerged in the last decade as a useful approach to integrating genomic and other high-throughput data sets with more traditional, experimental data acquired through decades of research and published in the literature.ResultsWe present a validated, constraint-based model of the core metabolism of Trypanosoma cruzi strain CL Brener. The model includes four compartments (extracellular space, cytosol, mitochondrion, glycosome), 51 transport reactions, and 93 metabolic reactions covering carbohydrate, amino acid, and energy metabolism. In addition, we make use of several replicate high-throughput proteomic data sets to specifically examine metabolism of the morphological form of T. cruzi in the insect gut (epimastigote stage).ConclusionThis work demonstrates the utility of constraint-based models for integrating various sources of data (e.g., genomics, primary biochemical literature, proteomics) to generate testable hypotheses. This model represents an approach for the systematic study of T. cruzi metabolism under a wide range of conditions and perturbations, and should eventually aid in the identification of urgently needed novel chemotherapeutic targets.

Functional genomics of Plasmodium falciparum using metabolic modelling and analysis

“…99%Used to constrain CBMs [12, 13]; reviewed in [44]Proteomics2D LC-MS/MS [45], nano-LC-MS/MS [46]ca. 45%Used to constrain CBMs [47]MetabolomicsHPLC-MS/MS [30, 48], 1 H-NMR [49]ca. 15-20%Used to constrain CBMs [32, 34], reviewed in [33]Fluxomics 13 C-NMR [50, 51], 14 C-NMR [52]Less than 1%Used to constrain CBMs, reviewed in [53, 54]…”

A New Metabolomics Analysis Technique: Steady-State Metabolic Network Dynamics Analysis

“…Figure 1 and Example 1 are from a manually constructed mammalian network database, available at PathCase-MAW site. 14 All other examples and visualizations in figures of this paper are obtained from the PathCase-RCMN (ReConstructed genome-scale Metabolic Network) application, 15 which is, in turn, built by importing the SBML of reconstructed metabolic network of Trypanosoma cruzi bacteria: 16 The SMDA tool, an evolution of the OMA Tool, 17 is currently being beta-tested in cystic fibrosis metabolomics data analysis.…”

Stochastic Simulation for Biochemical Reaction Networks in Infectious Disease

“…The integration of genomic and physiological information is now increasingly important with the emergence of "systems biology", which attempts to simultaneously study the expression patterns and activity of all genes, together with proteomic and metabolomic data [Cavalieri and Filippo, 2005]. When combined with a specific method of analysis like flux balance analysis (FBA), constraint-based models can be used to generate quantitative predictions (e.g., growth rate of an organism) and yield testable hypotheses for future experimental investigations [Roberts et al, 2009;Lee et al, 2006]. This permits an iterative process of model development, hypothesis generation and testing, and further model development and refinement [Reed et al, 2006].…”