Glucosinolates, myrosinase hydrolysis products, and flavonols found in rocket (Eruca sativa and Diplotaxis tenuifolia)

Rocket species have been shown to have very high concentrations of glucosinolates and flavonols, which have numerous positive health benefits with regular consumption. In this review we highlight how breeders and processors of rocket species can utilize genomic and phytochemical research to improve varieties and enhance the nutritive benefits to consumers. Plant breeders are increasingly looking to new technologies such as HPLC, UPLC, LC-MS and GC-MS to screen populations for their phytochemical content to inform plant selections. Here we collate the research that has been conducted to-date in rocket, and summarise all glucosinolate and flavonol compounds identified in the species. We emphasize the importance of the broad screening of populations for phytochemicals and myrosinase degradation products, as well as unique traits that may be found in underutilized gene bank resources. We also stress that collaboration with industrial partners is becoming essential for long-term plant breeding goals through research

Biochemical­­– and biophysical–induced barriergenesis in the blood brain barrier: a review of barriergenic factors for use in in vitro models

Central nervous system (CNS) pathologies are a prevalent problem in aging populations, creating a need to understand the underlying events in these diseases and develop efficient CNS‐targeting drugs. The importance of the blood‐brain barrier (BBB) has become evident, acting both as a physical barrier to drug entry into the CNS, and potentially as the cause or aggravator of CNS diseases. The development of a biomimetic BBB in vitro model is required for the understanding of BBB‐related pathologies and in the screening of drugs targeting the CNS. There is currently a great interest in understanding the influence of biochemical and biophysical factors, as these have the potential to greatly improve the barrier function of brain microvascular endothelial cells (BMECs). Recent advances in understanding how these may regulate barriergenesis in BMECs can help promote the development of improved BBB in vitro models, and therefore novel interventional therapies for pathologies related to its disruption. This review provides an overview of specific biochemical and biomechanical cues in the formation of the BBB, with a focus on in vitro models and how these might recapitulate BBB function

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Functional analysis of a caffeic acid o-methyltransferase from perennial ryegrass

Cinnamoyl CoA-reductase (CCR) and caffeic acid O-methyltransferase (COMT) catalyze key steps in the biosynthesis of monolignols, which serve as building blocks in the formation of plant lignin. We identified candidate genes encoding these two enzymes in perennial ryegrass (Lolium perenne) and show that the spatio-temporal expression patterns of these genes in planta correlate well with the developmental profile of lignin deposition. Downregulation of CCR1 and caffeic acid O-methyltransferase 1 (OMT1) using an RNA interference-mediated silencing strategy caused dramatic changes in lignin level and composition in transgenic perennial ryegrass plants grown under both glasshouse and field conditions. In CCR1-deficient perennial ryegrass plants, metabolic profiling indicates the redirection of intermediates both within and beyond the core phenylpropanoid pathway. The combined results strongly support a key role for the OMT1 gene product in the biosynthesis of both syringyl- and guaiacyl-lignin subunits in perennial ryegrass. Both field-grown OMT1-deficient and CCR1-deficient perennial ryegrass plants showed enhanced digestibility without obvious detrimental effects on either plant fitness or biomass production. This highlights the potential of metabolic engineering not only to enhance the forage quality of grasses but also to produce optimal feedstock plants for biofuel production

Reduced lignin content and altered lignin composition in the warm season forage grass Paspalum dilatatum by down-regulation of a Cinnamoyl CoA Reductase Gene

C4 grasses are favoured as forage crops in warm, humid climates. The use of C4 grasses in pastures is expected to increase because the tropical belt is widening due to global climate change. While the forage quality of Paspalum dilatatum (dallisgrass) is higher than that of other C4 forage grass species, digestibility of warm-season grasses is, in general, poor compared with most temperate grasses. The presence of thick-walled parenchyma bundle-sheath cells around the vascular bundles found in the C4 forage grasses are associated with the deposition of lignin polymers in cell walls. High lignin content correlates negatively with digestibility, which is further reduced by a high ratio of syringyl (S) to guaiacyl (G) lignin subunits. Cinnamoyl-CoA reductase (CCR) catalyses the conversion of cinnamoyl CoA to cinnemaldehyde in the monolignol biosynthetic pathway and is considered to be the first step in the lignin-specific branch of the phenylpropanoid pathway. We have isolated three putative CCR1 cDNAs from P. dilatatum and demonstrated that their spatio-temporal expression pattern correlates with the developmental profile of lignin deposition. Further, transgenic P. dilatatum plants were produced in which a sense-suppression gene cassette, delivered free of vector backbone and integrated separately to the selectable marker, reduced CCR1 transcript levels. This resulted in the reduction of lignin, largely attributable to a decrease in G lignin

Accelerating wheat breeding for end-use quality with multi-trait genomic predictions incorporating near infrared and nuclear magnetic resonance-derived phenotypes

Key message: Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection to accelerate improvement in grain end-use quality traits of wheat. Abstract: Grain end-use quality traits are among the most important in wheat breeding. These traits are difficult to breed for, as their assays require flour quantities only obtainable late in the breeding cycle, and are expensive. These traits are therefore an ideal target for genomic selection. However, large reference populations are required for accurate genomic predictions, which are challenging to assemble for these traits for the same reasons they are challenging to breed for. Here, we use predictions of end-use quality derived from near infrared (NIR) or nuclear magnetic resonance (NMR), that require very small amounts of flour, as well as end-use quality measured by industry standard assay in a subset of accessions, in a multi-trait approach for genomic prediction. The NIR and NMR predictions were derived for 19 end-use quality traits in 398 accessions, and were then assayed in 2420 diverse wheat accessions. The accessions were grown out in multiple locations and multiple years, and were genotyped for 51208 SNP. Incorporating NIR and NMR phenotypes in the multi-trait approach increased the accuracy of genomic prediction for most quality traits. The accuracy ranged from 0 to 0.47 before the addition of the NIR/NMR data, while after these data were added, it ranged from 0 to 0.69. Genomic predictions were reasonably robust across locations and years for most traits. Using NIR and NMR predictions of quality traits overcomes a major barrier for the application of genomic selection for grain end-use quality traits in wheat breeding