The intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling

Abstract

Genome-scale metabolic network models can be used for various analyses including the prediction of metabolic responses to changes in the environment. Legumes are well known for their rhizobial symbiosis that introduces nitrogen into the global nutrient cycle. Here, we describe a fully compartmentalised, mass and charge-balanced, genome-scale model of the clover Medicago truncatula, which has been adopted as a model organism for legumes. We employed flux balance analysis to demonstrate that the network is capable of producing biomass components in experimentally observed proportions, during day and night. By connecting the plant model to a model of its rhizobial symbiont, Sinorhizobium meliloti, we were able to investigate the effects of the symbiosis on metabolic fluxes and plant growth and could demonstrate how oxygen availability influences metabolic exchanges between plant and symbiont, thus elucidating potential benefits of inter organism amino acid cycling. We thus provide a modelling framework, in which the interlinked metabolism of plants and nodules can be studied from a theoretical perspective.

A Virtual Nodule Environment (ViNE) for modelling the inter-kingdom metabolic integration during symbiotic nitrogen fixation

“…The published M. truncatula metabolic network reconstruction (40) was built based on the M. truncatula genome version Mt3.5v5 (51). Here, the gene associations were updated to correspond to the annotations of version 5.0, the most recent version of the M. truncatula genome (52).…”

“…Next, the published M. truncatula SBML model was imported into MATLAB with the ‘importMedicago’ function of Pfau et al . (40). After importing, for genes with a one-to-one match between genome versions, the existing gene name was replaced with the gene name in the version 5.0 genome annotation.…”

“…The updated M. truncatula reconstruction was used to generate a tissue-specific M. truncatula model containing shoot and root tissues using the ‘BuildTissueModel’ function of Pfau et al (40). Reactions to transfer metabolites between the root and shoot tissue were modified to require the hydrolysis of 0.25 mol of root ATP and 0.25 mol of shoot ATP per mol of transferred metabolite.…”

“…Finally, root import reactions for the following compounds were added in anticipation of integration with the S. meliloti model: Co 2+ , MoO 4 3 −, Mn 2+ , Zn 2+ , Ca 2+ , K + , and Na + . The final model encompassed root metabolism and shoot metabolism with appropriate cross-talk between the tissues (40), and all reactions, metabolites, and genes associated with the shoot contain the prefix ‘Leave_’, while those associated with the root contain the prefix ‘Root_’.…”

“…To date, GENREs of varying quality have been reported for only three rhizobia: Sinorhizobium meliloti (33–35), Rhizobium etli (36–38), and Bradyrhizobium diazoefficiens (39). Currently, M. truncatula (40) and Glycine max (41) are the only legumes with published GENREs. With the exception of the G. max GENRE, these GENREs have been used in preliminary analyses of SNF, providing results generally consistent with expectations.…”