Journal
MOLECULAR PLANT PATHOLOGY
Volume 22, Issue 3, Pages 348-360Publisher
WILEY
DOI: 10.1111/mpp.13032
Keywords
Agrobacterium tumefaciens; crown gall; genome-scale metabolic model; plant pathogen; systems biology
Categories
Funding
- China Postdoctoral Science Foundation [2018M632389]
- National Natural Science Foundation of China [21808196, 31870118]
- Natural Science Foundation of the Jiangsu Higher Education Institutions of China [18KJB180030]
Ask authors/readers for more resources
This study utilized a genome-scale metabolic model to investigate the metabolic characteristics of Agrobacterium tumefaciens and found differences in metabolic activity in different ecological niches. By integrating transcriptome data under tumor conditions, significant changes in metabolic pathways were identified.
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available