Heat-stabilized rice bran (SRB) has been shown to regulate blood lipids and glucose, modulate gut mucosal immunity and inhibit colorectal cancer in animal and human studies. However, SRB’s effects on gut microbial composition and metabolism and the resulting implications for health remain largely unknown. A pilot, randomized-controlled trial was developed to investigate the effects of eating 30 g/day SRB on the stool microbiome and metabolome. Seven healthy participants consumed a study meal and snack daily for 28 days. The microbiome and metabolome were characterized using 454 pyrosequencing and gas chromatography-mass spectrometry (GC-MS) at baseline, two and four weeks post-intervention. Increases in eight operational taxonomic units (OTUs), including three from Bifidobacterium and Ruminococcus genera, were observed after two and four weeks of SRB consumption (p < 0.01). Branched chain fatty acids, secondary bile acids and eleven other putative microbial metabolites were significantly elevated in the SRB group after four weeks. The largest metabolite change was a rice bran component, indole-2-carboxylic acid, which showed a mean 12% increase with SRB consumption. These data support the feasibility of dietary SRB intervention in adults and support that SRB consumption can affect gut microbial metabolism. These findings warrant future investigations of larger cohorts evaluating SRB’s effects on intestinal health.

Metabolic processes in plants are key components of physiological and biochemical disease resistance. Metabolomics, the analysis of a broad range of small molecule compounds in a biological system, has been used to provide a systems-wide overview of plant metabolism associated with defense responses. Plant immunity has been examined using multiple metabolomics workflows that vary in methods of detection, annotation, and interpretation, and the choice of workflow can significantly impact the conclusions inferred from a metabolomics investigation. The broad range of metabolites involved in plant defense often supports the need for multiple chemical detection platforms and implementation of a non-targeted approach. A review of the current literature reveals a wide range of workflows that are currently used in plant metabolomics, and new methods for analyzing and reporting mass spectrometry data can improve the ability to translate investigative findings among different plant-pathogen systems.

Background: Soybean cyst nematode (Heterodera glycines, SCN) is the most economically damaging pathogen of soybean (Glycine max) in the U.S. The Rhg1 locus is repeatedly observed as the quantitative trait locus with the greatest impact on SCN resistance. The Glyma18g02680.1 gene at the Rhg1 locus that encodes an apparent leucine-rich repeat transmembrane receptor-kinase (LRR-kinase) has been proposed to be the SCN resistance gene, but its function has not been confirmed. Generation of fertile transgenic soybean lines is difficult but methods have been published that test SCN resistance in transgenic roots generated with Agrobacterium rhizogenes. Results: We report use of artificial microRNA (amiRNA) for gene silencing in soybean, refinements to transgenic root SCN resistance assays, and functional tests of the Rhg1 locus LRR-kinase gene. A nematode demographics assay monitored infecting nematode populations for their progress through developmental stages two weeks after inoculation, as a metric for SCN resistance. Significant differences were observed between resistant and susceptible control genotypes. Introduction of the Rhg1 locus LRR-kinase gene (genomic promoter/coding region/terminator; Peking/PI 437654-derived SCN-resistant source), into rhg1 ^- SCN-susceptible plant lines carrying the resistant-source Rhg4 ⁺ locus, provided no significant increases in SCN resistance. Use of amiRNA to reduce expression of the LRR-kinase gene from the Rhg1 locus of Fayette (PI 88788 source of Rhg1) also did not detectably alter resistance to SCN. However, silencing of the LRR-kinase gene did have impacts on root development. Conclusion: The nematode demographics assay can expedite testing of transgenic roots for SCN resistance. amiRNAs and the pSM103 vector that drives interchangeable amiRNA constructs through a soybean polyubiqutin promoter (Gmubi), with an intron-GFP marker for detection of transgenic roots, may have widespread use in legume biology. Studies in which expression of the Rhg1 locus LRR-kinase gene from different resistance sources was either reduced or complemented did not reveal significant impacts on SCN resistance.

Root exudation is an important plant process by which roots release small molecules into the rhizosphere that serve in overall plant functioning. Yet, there is a major gap in our knowledge in translating plant root exudation in artificial systems (i.e., hydroponics, sterile media) to crops, specifically for soils expected in field conditions. Sorghum (Sorghum bicolor L. Moench) root exudation was determined using both ultra-performance liquid chromatography and gas chromatography mass spectrometry-based non-targeted metabolomics to evaluate variation in exudate composition of two sorghum genotypes among three substrates (sand, clay, and soil). Above and belowground plant traits were measured to determine the interaction between sorghum genotype and belowground substrate. Plant growth and quantitative exudate composition were found to vary largely by substrate. Two types of changes to rhizosphere metabolites were observed: rhizosphere-enhanced metabolites (REMs) and rhizosphere-abated metabolites (RAMs). More REMs and RAMs were detected in sand and clay substrates compared to the soil substrate. This study demonstrates that belowground substrate influences the root exudate profile in sorghum, and that two sorghum genotypes exuded metabolites at different magnitudes. However, metabolite identification remains a major bottleneck in non-targeted metabolite profiling of the rhizosphere.

Wheat (Triticum aestivum L.) is an important food crop, and biotic and abiotic stresses significantly impact grain yield. Wheat leaf and stem surface waxes are associated with traits of biological importance, including stress resistance. Past studies have characterized the composition of wheat cuticular waxes, however protocols can be relatively low-throughput and narrow in the range of metabolites detected. Here, gas chromatography-mass spectrometry (GC-MS) metabolomics methods were utilized to provide a comprehensive characterization of the chemical composition of cuticular waxes in wheat leaves and stems. Further, waxes from four wheat cultivars were assayed to evaluate the potential for GC-MS metabolomics to describe wax composition attributed to differences in wheat genotype. A total of 263 putative compounds were detected and included 58 wax compounds that can be classified (e.g., alkanes and fatty acids). Many of the detected wax metabolites have known associations to important biological functions. Principal component analysis and ANOVA were used to evaluate metabolite distribution, which was attributed to both tissue type (leaf, stem) and cultivar differences. Leaves contained more primary alcohols than stems such as 6-methylheptacosan-1-ol and octacosan-1-ol. The metabolite data were validated using scanning electron microscopy of epicuticular wax crystals which detected wax tubules and platelets. Conan was the only cultivar to display alcohol-associated platelet-shaped crystals on its abaxial leaf surface. Taken together, application of GC-MS metabolomics enabled the characterization of cuticular wax content in wheat tissues and provided relative quantitative comparisons among sample types, thus contributing to the understanding of wax composition associated with important phenotypic traits in a major crop.