Uptake and metabolism of sulphated steroids by the blood-brain barrier in the adult male rat.

Little is known about the origin of the neuroactive steroids dehydroepiandrosterone sulphate (DHEAS) and pregnenolone sulphate (PregS) in the brain or of their subsequent metabolism. Using rat brain perfusion in situ, we have found H-PregS to enter more rapidly than H-DHEAS and both to undergo extensive (> 50%) desulphation within 0.5 min of uptake.

(1)H-NMR screening for the high-throughput determination of genotype and environmental effects on the content of asparagine in wheat grain.

Free asparagine in cereals is known to be the precursor of acrylamide, a neurotoxic and carcinogenic product formed during cooking processes. Thus, the development of crops with lower asparagine is of considerable interest to growers and the food industry. In this study, we describe the development and application of a rapid (1)H-NMR-based analysis of cereal flour, that is, suitable for quantifying asparagine levels, and hence acrylamide-forming potential, across large numbers of samples.

An efficient high throughput metabotyping platform for screening of biomass willows.

Future improvement of woody biomass crops such as willow and poplar relies on our ability to select for metabolic traits that sequester more atmospheric carbon into biomass, or into useful products to replace petrochemical streams. We describe the development of metabotyping screens for willow, using combined 1D 1H-NMR-MS. A protocol was developed to overcome 1D 1H-NMR spectral alignment problems caused by variable pH and peak broadening arising from high organic acid levels and metal cations.

A genome-wide metabolomic resource for tomato fruit from Solanum pennellii.

Tomato and its processed products are one of the most widely consumed fruits. Its domestication, however, has resulted in the loss of some 95% of the genetic and chemical diversity of wild relatives. In order to elucidate this diversity, exploit its potential for plant breeding, as well as understand its biological significance, analytical approaches have been developed, alongside the production of genetic crosses of wild relatives with commercial varieties.

Enhancement of plant metabolite fingerprinting by machine learning.

Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by (1)H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.