Iterative reconstruction of a global metabolic model of Acinetobacter baylyi ADP1 using high-throughput growth phenotype and gene essentiality data

Autor: Jean Weissenbach, Annett Kreimeyer, Véronique de Berardinis, David Vallenet, Serge Smidtas, Vincent Schächter, Cyril Combe, Marcel Salanoubat, François Le Fèvre, Maxime Durot
Přispěvatelé: Genoscope - Centre national de séquençage [Evry] (GENOSCOPE), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Département Ingénierie Logiciels et Systèmes (DILS), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Génomique métabolique (UMR 8030), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université d'Évry-Val-d'Essonne (UEVE), VisAge (VisAge), VisAge, Structure et évolution des génomes (SEG), CNS-Université d'Évry-Val-d'Essonne (UEVE)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université d'Évry-Val-d'Essonne (UEVE)-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Technologique (CEA) (DRT (CEA))
Jazyk: angličtina
Předmět:
Systems biology
[SDV]Life Sciences [q-bio]
Mutant
Iterative reconstruction
Computational biology
Biology
computer.software_genre
Models
Biological
Sensitivity and Specificity
User-Computer Interface
03 medical and health sciences
Structural Biology
Modelling and Simulation
Throughput (business)
Gene
lcsh:QH301-705.5
Molecular Biology
ComputingMilieux_MISCELLANEOUS
030304 developmental biology
Internet
0303 health sciences
Genes
Essential
Acinetobacter
030306 microbiology
Applied Mathematics
Reproducibility of Results
Genome project
Phenotype
[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]
Computer Science Applications
lcsh:Biology (General)
Genes
Bacterial
Modeling and Simulation
Mutation
Mutation (genetic algorithm)
Data mining
computer
Metabolic Networks and Pathways
Software
Research Article
Zdroj: BMC Systems Biology, Vol 2, Iss 1, p 85 (2008)
BMC Systems Biology
BMC Systems Biology, BioMed Central, 2008, 2 (1), pp.85. ⟨10.1186/1752-0509-2-85⟩
BMC Systems Biology, 2008, 2 (1), pp.85. ⟨10.1186/1752-0509-2-85⟩
ISSN: 1752-0509
DOI: 10.1186/1752-0509-2-85
Popis: Background Genome-scale metabolic models are powerful tools to study global properties of metabolic networks. They provide a way to integrate various types of biological information in a single framework, providing a structured representation of available knowledge on the metabolism of the respective species. Results We reconstructed a constraint-based metabolic model of Acinetobacter baylyi ADP1, a soil bacterium of interest for environmental and biotechnological applications with large-spectrum biodegradation capabilities. Following initial reconstruction from genome annotation and the literature, we iteratively refined the model by comparing its predictions with the results of large-scale experiments: (1) high-throughput growth phenotypes of the wild-type strain on 190 distinct environments, (2) genome-wide gene essentialities from a knockout mutant library, and (3) large-scale growth phenotypes of all mutant strains on 8 minimal media. Out of 1412 predictions, 1262 were initially consistent with our experimental observations. Inconsistencies were systematically examined, leading in 65 cases to model corrections. The predictions of the final version of the model, which included three rounds of refinements, are consistent with the experimental results for (1) 91% of the wild-type growth phenotypes, (2) 94% of the gene essentiality results, and (3) 94% of the mutant growth phenotypes. To facilitate the exploitation of the metabolic model, we provide a web interface allowing online predictions and visualization of results on metabolic maps. Conclusion The iterative reconstruction procedure led to significant model improvements, showing that genome-wide mutant phenotypes on several media can significantly facilitate the transition from genome annotation to a high-quality model.
Databáze: OpenAIRE
Externí odkaz: