ArticleMolecular plant pathology2021
Reconstruction and analysis of a genome-scale metabolic model for Agrobacterium tumefaciens.
Article in Molecular plant pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Synthetic Biology of Plants and Microbes for Agriculture, Environment, and Future Applications.Chemical reviews · 2026Review
- Review
- Climate change impacts on plant pathogens, food security and paths forward.Nature reviews. Microbiology · 2023Review
- Carbohydrate Metabolism in Bacteria: Alternative Specificities in ADP-Glucose Pyrophosphorylases Open Novel Metabolic Scenarios and Biotechnological Tools.Frontiers in microbiology · 2022Article
- Reconstruction and analysis of a genome-scale metabolic model for Agrobacterium tumefaciens.Molecular plant pathology · 2021Article
- Three overlooked key functional classes for building up minimal synthetic cells.Synthetic biology (Oxford, England) · 2021Article
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Authors and funding
5 authors.
Funding
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Abstract
The plant pathogen Agrobacterium tumefaciens causes crown gall disease and is a widely used tool for generating transgenic plants owing to its virulence. The pathogenic process involves a shift from an independent to a living form within a host plant. However, comprehensive analyses of metabolites, genes, and reactions contributing to this complex process are lacking. To gain new insights about the pathogenicity from the viewpoints of physiology and cellular metabolism, a genome-scale metabolic model (GSMM) was reconstructed for A. tumefaciens. The model, referred to as iNX1344, contained 1,344 genes, 1,441 reactions, and 1,106 metabolites. It was validated by analyses of in silico cell growth on 39 unique carbon or nitrogen sources and the flux distribution of carbon metabolism. A. tumefaciens metabolic characteristics under three ecological niches were modelled. A high capacity to access and metabolize nutrients is more important for rhizosphere colonization than in the soil, and substantial metabolic changes were detected during the shift from the rhizosphere to tumour environments. Furthermore, by integrating transcriptome data for tumour conditions, significant alterations in central metabolic pathways and secondary metabolite metabolism were identified. Overall, the GSMM and constraint-based analysis could decode the physiological and metabolic features of A. tumefaciens as well as interspecific interactions with hosts, thereby improving our understanding of host adaptation and infection mechanisms.
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