Metabolite Profiles of Nodulated Alfalfa Plants Indicate That Distinct Stages of Nodule Organogenesis Are Accompanied by Global Physiological Adaptations

Abstract

An effective symbiosis between Sinorhizobium meliloti and its host plant Medicago sativa is dependent on a balanced physiological interaction enabling the microsymbiont to fix atmospheric nitrogen. Maintenance of the symbiotic interaction is regulated by still poorly understood control mechanisms. A first step toward a better understanding of nodule metabolism was the determination of characteristic metabolites for alfalfa root nodules. Furthermore, nodules arrested at different developmental stages were analyzed in order to address metabolic changes induced during the progression of nodule formation. Metabolite profiles of bacteroid-free pseudonodule extracts indicated that early nodule developmental processes are accompanied by photosynthate translocation but no massive organic acid formation. To determine metabolic adaptations induced by the presence of nonfixing bacteroids, nodules induced by mutant S. meliloti strains lacking the nitrogenase protein were analyzed. The bacteroids are unable to provide ammonium to the host plant, which is metabolically reflected by reduced levels of characteristic amino acids involved in ammonium fixation. Elevated levels of starch and sugars in Fix¯ nodules provide strong evidence that plant sanctions preventing a transformation from a symbiotic to a potentially parasitic interaction are not strictly realized via photo-synthate supply. Instead, metabolic and gene expression data indicate that alfalfa plants react to nitrogen-fixation-deficient bacteroids with a decreased organic acid synthesis and an early induction of senescence. Noneffective symbiotic interactions resulting from plants nodulated by mutant rhizobia also are reflected in characteristic metabolic changes in leaves. These are typical for nitrogen deficiency, but also highlight metabolites potentially involved in sensing the N status.

Keywords

• GC-MS
• gene expression profiles
• metabolite profiling