Down-regulation of four putative arabinoxylan feruloyl transferase genes from family PF02458 reduces ester-linked ferulate content in rice cell walls

Industrial processes to produce ethanol from lignocellulosic materials are available, but improved efficiency is necessary to make them economically viable. One of the limitations for lignocellulosic conversion to ethanol is the inaccessibility of the cellulose and hemicelluloses within the tight cell wall matrix. Ferulates (FA) can cross-link different arabinoxylan molecules in the cell wall of grasses via diferulate and oligoferulate bridges. This complex cross-linking is thought to be a key factor in limiting the biodegradability of grass cell walls and, therefore, the reduction in FA is an attractive target to improve enzyme accessibility to cellulose and hemicelluloses. Unfortunately, our knowledge of the genes responsible for the incorporation of FA to the cell wall is limited. A bioinformatics prediction based on the gene similarities and higher transcript abundance in grasses relative to dicot species suggested that genes from the pfam family PF02458 may act as arabinoxylan feruloyl transferases. We show here that the FA content in the cell walls and the transcript levels of rice genes Os05g08640, Os06g39470, Os01g09010 and Os06g39390, are both higher in the stems than in the leaves. In addition, an RNA interference (RNAi) construct that simultaneously down-regulates transcript levels of these four genes is associated with a significant reduction in FA of the cell walls from the leaves of the transgenic plants relative to the control (19% reduction, P < 0.0001). Therefore, our experimental results in rice support the bioinformatics prediction that members of family PF02458 are involved in the incorporation of FA into the cell wall in grasses

Dietary manipulation in dairy cattle: Laboratory experiments to assess the influence on ammonia emissions

Improvements to the efficiency of dietary nitrogen use by lactating dairy cattle can be made by altering the concentration and form of protein in the diet. This study collected urine and feces from dairy cows from selected crude protein (CP) treatments of 2 lactation studies. In the first trial, collections were made from cattle fed a diet with high (19.4%) or low (13.6%) CP content (HCP and LCP, respectively). In the second trial, collections were made from cattle fed diets in which the forage legume component was alfalfa (ALF) or birdsfoot trefoil with a low (BFTL) or high (BFTH) concentration of condensed tannins (CT). A system of small laboratory chambers was used to measure NH3 emissions over 48 h from applications of equal quantities of urine and feces to cement (simulating a barn floor) and from applications of slurries, made by combining feces and urine in the proportions in which they were excreted for each treatment, to soil. Reducing dietary CP content resulted in less total N excretion and a smaller proportion of the excreted N being present in urine; urine N concentration was 90% greater for HCP than LCP. Surprisingly, NH3 emissions from the barn floor were similar in absolute terms despite the great differences in urine urea-N concentrations, presumably because urease activity was limiting. Cumulative emissions from fresh slurries applied to soil represented 18% of applied N for both HCP and LCP. Following storage at 20°C for 2 wk, cumulative emissions from LCP were much lower than for HCP, representing 9 and 25% of applied N, respectively. Emissions were also lower when expressed as a proportion of slurry total ammoniacal N (TAN) content (24 and 31%, respectively) because of treatment differences in slurry pH. Increasing CT content of the dietary forage legume component resulted in a shift in N excretion from urine to feces. Cumulative NH3 emissions from the barn floor were greater for ALF than for BFTL or BFTH. Emissions from fresh and stored slurries were in proportion to slurry TAN contents, with approximately 35% of applied TAN being lost for all treatments. Emissions expressed as a proportion of total N applied were consistently lower for BFTH than for ALF

A cognitive forcing tool to mitigate cognitive bias:A randomised control trial

Abstract Background Cognitive bias is an important source of diagnostic error yet is a challenging area to understand and teach. Our aim was to determine whether a cognitive forcing tool can reduce the rates of error in clinical decision making. A secondary objective was to understand the process by which this effect might occur. Methods We hypothesised that using a cognitive forcing tool would reduce diagnostic error rates. To test this hypothesis, a novel online case-based approach was used to conduct a single blinded randomized clinical trial conducted from January 2017 to September 2018. In addition, a qualitative series of “think aloud” interviews were conducted with 20 doctors from a UK teaching hospital in 2018. The primary outcome was the diagnostic error rate when solving bias inducing clinical vignettes. A volunteer sample of medical professionals from across the UK, Republic of Ireland and North America. They ranged in seniority from medical student to Attending Physician. Results Seventy six participants were included in the study. The data showed doctors of all grades routinely made errors related to cognitive bias. There was no difference in error rates between groups (mean 2.8 cases correct in intervention vs 3.1 in control group, 95% CI -0.94 – 0.45 P = 0.49). The qualitative protocol revealed that the cognitive forcing strategy was well received and a produced a subjectively positive impact on doctors’ accuracy and thoughtfulness in clinical cases. Conclusions The quantitative data failed to show an improvement in accuracy despite a positive qualitative experience. There is insufficient evidence to recommend this tool in clinical practice, however the qualitative data suggests such an approach has some merit and face validity to users

Genetic complexity of miscanthus cell wall composition and biomass quality for biofuels

BACKGROUND: Miscanthus sinensis is a high yielding perennial grass species with great potential as a bioenergy feedstock. One of the challenges that currently impedes commercial cellulosic biofuel production is the technical difficulty to efficiently convert lignocellulosic biomass into biofuel. The development of feedstocks with better biomass quality will improve conversion efficiency and the sustainability of the value-chain. Progress in the genetic improvement of biomass quality may be substantially expedited by the development of genetic markers associated to quality traits, which can be used in a marker-assisted selection program. RESULTS: To this end, a mapping population was developed by crossing two parents of contrasting cell wall composition. The performance of 182 F1 offspring individuals along with the parents was evaluated in a field trial with a randomized block design with three replicates. Plants were phenotyped for cell wall composition and conversion efficiency characters in the second and third growth season after establishment. A new SNP-based genetic map for M. sinensis was built using a genotyping-by-sequencing (GBS) approach, which resulted in 464 short-sequence uniparental markers that formed 16 linkage groups in the male map and 17 linkage groups in the female map. A total of 86 QTLs for a variety of biomass quality characteristics were identified, 20 of which were detected in both growth seasons. Twenty QTLs were directly associated to different conversion efficiency characters. Marker sequences were aligned to the sorghum reference genome to facilitate cross-species comparisons. Analyses revealed that for some traits previously identified QTLs in sorghum occurred in homologous regions on the same chromosome. CONCLUSION: In this work we report for the first time the genetic mapping of cell wall composition and bioconversion traits in the bioenergy crop miscanthus. These results are a first step towards the development of marker-assisted selection programs in miscanthus to improve biomass quality and facilitate its use as feedstock for biofuel production

Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism

The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species