The nematode resistance allele at the rhg1 locus alters the proteome and primary metabolism of soybean roots.

Heterodera glycines, the soybean cyst nematode (SCN), causes the most damaging chronic disease of soybean (Glycine max). Host resistance requires the resistance allele at rhg1. Resistance destroys the giant cells created in the plant's roots by the nematodes about 24 to 48 h after commencement of feeding. In addition, 4 to 8 d later, a systemic acquired resistance develops that discourages later infestations. The molecular mechanisms that control the rhg1-mediated resistance response appear to be multigenic and complex, as judged by transcript abundance changes, even in near isogenic lines (NILs). This study aimed to focus on key posttranscriptional changes by identifying proteins and metabolites that were increased in abundance in both resistant and susceptible NILs. Comparisons were made among NILs 10 d after SCN infestation and without SCN infestation. Two-dimensional gel electrophoresis resolved more than 1,000 protein spots on each gel. Only 30 protein spots with a significant (P < 0.05) difference in abundance of 1.5-fold or more were found among the four treatments. The proteins in these spots were picked, trypsin digested, and analyzed using quadrupole time-of-flight tandem mass spectrometry. Protein identifications could be made for 24 of the 30 spots. Four spots contained two proteins, so that 28 distinct proteins were identified. The proteins were grouped into six functional categories. Metabolite analysis by gas chromatography-mass spectrometry identified 131 metabolites, among which 58 were altered by one or more treatment; 28 were involved in primary metabolism. Taken together, the data showed that 17 pathways were altered by the rhg1 alleles. Pathways altered were associated with systemic acquired resistance-like responses, including xenobiotic, phytoalexin, ascorbate, and inositol metabolism, as well as primary metabolisms like amino acid synthesis and glycolysis. The pathways impacted by the rhg1 allelic state and SCN infestation agreed with transcript abundance analyses but identified a smaller set of key proteins. Six of the proteins lay within the same small region of the interactome identifying a key set of 159 interacting proteins involved in transcriptional control, nuclear localization, and protein degradation. Finally, two proteins (glucose-6-phosphate isomerase [EC 5.3.1.9] and isoflavone reductase [EC 1.3.1.45]) and two metabolites (maltose and an unknown) differed in resistant and susceptible NILs without SCN infestation and may form the basis of a new assay for the selection of resistance to SCN in soybean.

Metabolic profiling of laser microdissected vascular bundles of Arabidopsis thaliana.

BACKGROUND: Laser microdissection is a useful tool for collecting tissue-specific samples or even single cells from animal and plant tissue sections. This technique has been successfully employed to study cell type-specific expression at the RNA, and more recently also at the protein level. However, metabolites were not amenable to analysis after laser microdissection, due to the procedures routinely applied for sample preparation. Using standard tissue fixation and embedding protocols to prepare histological sections, metabolites are either efficiently extracted by dehydrating solvents, or washed out by embedding agents. RESULTS: In this study, we used cryosectioning as an alternative method that preserves sufficient cellular structure while minimizing metabolite loss by excluding any solute exchange steps. Using this pre-treatment procedure, Arabidopsis thaliana stem sections were prepared for laser microdissection of vascular bundles. Collected samples were subsequently analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS) to obtain metabolite profiles. From 100 collected vascular bundles (approximately 5,000 cells), 68 metabolites could be identified. More than half of the identified metabolites could be shown to be enriched or depleted in vascular bundles as compared to the surrounding tissues. CONCLUSION: This study uses the example of vascular bundles to demonstrate for the first time that it is possible to analyze a comprehensive set of metabolites from laser microdissected samples at a tissue-specific level, given that a suitable sample preparation procedure is used.