Simultaneous detection of monomers associated with resin-based dental composites using SPME and HPLC.

As resin-based composites (RBC) replace dental amalgam for environmental reasons, there is a requirement to understand the environmental impact of this alternative dental restorative material. In this study we standardize the simultaneous detection of five monomeric components associated with RBCs using high performance liquid chromatography (HPLC) coupled with solid-phase microextraction (SPME). Factors affecting method performance (detection wavelength, calibration conditions, method sensitivity/accuracy/precision, extraction time/efficiency) are evaluated using standard solutions containing the mixture of TEGDMA, UDMA, Bis-GMA, BPA and HEMA. Detection sensitivity and analytical efficiency of the method is optimized for these compounds using 200 nm detection wavelength, PDMS/DVB fiber and extraction time of 90 min. Analytical accuracy of the HPLC is >95% for all monomers, with precision of 2.3-5.1%. Detection limits under the conditions described are 25 µg/L for HEMA, BPA, UDMA, Bis-GMA, and 100 µg/L for TEGDMA. The extraction time is governed by the largest molecular weight compounds.

A non-targeted metabolomics approach to quantifying differences in root storage between fast- and slow-growing plants.

Life history theory posits that slower-growing species should invest proportionally more resources to storage, structural (e.g. stems) or defence traits than fast-growing species. Previously, we showed that the slower-growing monocarpic plants had lower mortality rates and higher bolting probabilities after two defoliation events. Here, we consider a mechanistic explanation, that the slower-growing species invested relatively more resources to storage. We compared the relative levels of root storage compounds between eight monocarpic species using metabolomic profiling, and characterized plant growth using a size-corrected estimate of relative growth rate (RGR). Growth rate was negatively correlated with the proportional allocation of root metabolites identified as sucrose, raffinose and stachyose and with amino acids known for their roles in nitrogen storage, particularly proline and arginine. The total amount and concentration of energy-corrected carbohydrates were also negatively correlated with RGR. Our results show for the first time that slower-growing species invest proportionally more of their total root metabolites in carbon- and nitrogen-storage compounds. We conclude that the increased investment in these reserves is an important resource allocation strategy underlying the growth-survival trade-off in plants.

Population-specific metabolic phenotypes of Arabidopsis lyrata ssp. petraea.

Plant populations growing at the margin of their range may exhibit traits that indicate genetic differentiation and adaptation to their local abiotic environment. Here, it was investigated whether geographically separated marginal populations of Arabidopsis lyrata ssp. petraea have distinct metabolic phenotypes within the plant foliage. Seeds of A. petraea were obtained from populations along a latitudinal gradient (49-64 N), namely Germany, Wales, Sweden and Iceland and grown in a controlled cabinet environment. Targeted metabolic profiles and fingerprints were obtained at the same initial developmental stage. The free amino acid compositions were population specific, with fold differences in arginine, aspartic acid, asparagines, glycine, phenylalanine, alanine, threonine, histidine, serine and gamma-aminobutyric acid (GABA) concentrations. Sucrose, mannose and fructose concentrations were also different between populations but polyhydric alcohol concentrations were not. Principal component analysis (PCA) of metabolite fingerprints revealed metabolic phenotypes for each population. It is suggested that glucosinolates were responsible for discriminating populations within the PCA. Metabolite fingerprinting and profiling has proved to be sufficiently sensitive to identify metabolic differences between plant populations. These findings show that there is significant natural variation in metabolism among populations of A. petraea.