ArticleBMC systems biology2009
Proteomic and network analysis characterize stage-specific metabolism in Trypanosoma cruzi.
Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed, 46 citations in OpenAlex.
- A Data-Driven Approach to Construct a Molecular Map ofVaccines · 2023Article
- Modulation of Virulence Factors duringPathogens (Basel, Switzerland) · 2022Review
- Tryp-ing Up Metabolism: Role of Metabolic Adaptations in Kinetoplastid Disease Pathogenesis.Infection and immunity · 2021Review
- Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey.IEEE access : practical innovations, open solutions · 2021Article
- Genome-scale metabolic models highlight stage-specific differences in essential metabolic pathways in Trypanosoma cruzi.PLoS neglected tropical diseases · 2020Article
- Review
- Efflux pumps and antimicrobial resistance: Paradoxical components in systems genomics.Progress in biophysics and molecular biology · 2019Review
- A Brief View of the Surface Membrane Proteins fromJournal of parasitology research · 2017Review
- Article
- Proteomics-based metabolic modeling and characterization of the cellulolytic bacterium Thermobifida fusca.BMC systems biology · 2014Article
- Functional genomics of Plasmodium falciparum using metabolic modelling and analysis.Briefings in functional genomics · 2013Article
- What mRNA Abundances Can Tell us about Metabolism.Metabolites · 2012Article
- A metabolic network approach for the identification and prioritization of antimicrobial drug targets.Trends in microbiology · 2012Review
- A new metabolomics analysis technique: steady-state metabolic network dynamics analysis.Journal of bioinformatics and computational biology · 2012Article
- Gap detection for genome-scale constraint-based models.Advances in bioinformatics · 2012Article
- Individualized therapy of HHT driven by network analysis of metabolomic profiles.BMC systems biology · 2011Article
- Eating at the table of another: metabolomics of host-parasite interactions.Cell host & microbe · 2010Review
- Systems analysis of host-parasite interactions.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.