Multilab EcoFAB study shows highly reproducible physiology and depletion of soil metabolites by a model grass

There is a dynamic reciprocity between plants and their environment: soil physiochemical properties influence plant morphology and metabolism, and root morphology and exudates shape the environment surrounding roots. Here, we investigate the reproducibility of plant trait changes in response to three growth environments. We utilized fabricated ecosystem (EcoFAB) devices to grow the model grass Brachypodium distachyon in three distinct media across four laboratories: phosphate-sufficient and -deficient mineral media allowed assessment of the effects of phosphate starvation, and a complex, sterile soil extract represented a more natural environment with yet uncharacterized effects on plant growth and metabolism. Tissue weight and phosphate content, total root length, and root tissue and exudate metabolic profiles were consistent across laboratories and distinct between experimental treatments. Plants grown in soil extract were morphologically and metabolically distinct, with root hairs four times longer than with other growth conditions. Further, plants depleted half of the metabolites investigated from the soil extract. To interact with their environment, plants not only adapt morphology and release complex metabolite mixtures, but also selectively deplete a range of soil-derived metabolites. The EcoFABs utilized here generated high interlaboratory reproducibility, demonstrating their value in standardized investigations of plant traits

Selenium, Selenoenzymes, Oxidative Stress and Risk of Neoplastic Progression from Barrett's Esophagus: Results from Biomarkers and Genetic Variants

Clinical trials have suggested a protective effect of selenium supplementation on the risk of esophageal cancer, which may be mediated through the antioxidant activity of selenoenzymes. We investigated whether serum selenium concentrations, selenoenzyme activity, oxidative stress and genetic variation in selenoenzymes were associated with the risk of neoplastic progression to esophageal adenocarcinoma (EA) and two intermediate endpoints, aneuploidy and tetraploidy. In this prospective cohort study, during an average follow-up of 7.3 years, 47 EA cases, 41 aneuploidy cases and 51 tetraploidy cases accrued among 361 participants from the Seattle Barrett's Esophagus Research Study who were free of EA at the time of blood draw and had at least one follow-up visit. Development to EA was assessed histologically and aneuploidy and tetraploidy by DNA content flow cytometry. Serum selenium concentrations were measured using atomic absorption spectrometry, activity of glutathione peroxidase (GPX) 1 and GPX3 by substrate-specific coupled test procedures, selenoprotein P (SEPP1) concentrations and protein carbonyl content by ELISA method and malondialdehyde concentrations by HPLC. Genetic variants in GPX1-4 and SEPP1 were genotyped. Serum selenium was not associated with the risk of neoplastic progression to EA, aneuploidy or tetraploidy (P for trend = 0.25 to 0.85). SEPP1 concentrations were positively associated with the risk of EA [hazard ratio (HR) = 3.95, 95% confidence intervals (CI) = 1.42–10.97 comparing the third tertile with the first] and with aneuploidy (HR = 6.53, 95% CI = 1.31–32.58), but not selenoenzyme activity or oxidative stress markers. No genetic variants, overall, were associated with the risk of neoplastic progression to EA (global p = 0.12–0.69). Our results do not support a protective effect of selenium on risk of neoplastic progression to EA. Our study is the first to report positive associations of plasma SEPP1 concentrations with the risk of EA and aneuploidy, which warrants further investigation

Precision, proteome coverage, and dynamic range of Arabidopsis proteome profiling using (15)N metabolic labeling and label-free approaches

This study reports the comprehensive comparison of (15)N metabolic labeling and label free proteomic strategies for quantitation, with particular focus on plant proteomics. Our investigation of proteome coverage, dynamic range and quantitative precision for a wide range of mixing ratios and protein loadings aim to aid the investigators in the decision making process during experimental design. One of the main characteristics of the label free strategy is the applicability to all starting material, which is a limitation to the metabolic labeling. However, particularly at mixing ratios up to 10-fold the (15)N metabolic labeling proved to be more precise. Contrary to usual practice based on the results from this study, we suggest that nonequal mixing ratios in metabolic labeling could further increase the proteome coverage for quantitation. On the other hand, the label free strategy, in combination with low protein loading allows the extension of the dynamic range for quantitation and it is more precise at very high ratios, which could be important for certain types of experiments

Design of Steel Beam-Column Connections

In this paper a theoretical and experimental research of the steel beam-column connections is presented. Eight types of specimens were being researched, composed of rigid and semi-rigid connections from which 4 connections are with IPE - profile and 4 connections with tube's section for the beam. From the numerical analysis of the researched models, and especially from the experimental research at the Laboratory for Structures in the Faculty of Mechanical Engineering - Skopje, specific conclusions were received that ought to have theoretical and practical usage for researchers in this area of interest

Dynamics in plant roots and shoots minimize stress, save energy and maintain water and nutrient uptake

Plants are inherently dynamic. Dynamics minimize stress while enabling plants to flexibly acquire resources. Three examples are presented for plants tolerating saline soil: transport of sodium chloride (NaCl), water and macronutrients is nonuniform along a branched root; water and NaCl redistribute between shoot and soil at night-time; and ATP for salt exclusion is much lower in thinner branch roots than main roots, quantified using a biophysical model and geometry from anatomy. Noninvasive phenotyping and precision agriculture technologies can be used together to harness plant dynamics, but analytical methods are needed. A plant advancing in time through a soil and atmosphere space is proposed as a framework for dynamic data and their relationship to crop improvement.Borjana Arsova, Kylie J. Foster, Megan C. Shelden, Helen Bramley and Michelle Wat

Time-resolution of the shoot and root growth of the model cereal Brachypodium in response to inoculation with Azospirillum bacteria at low phosphorus and temperature

A non-invasive plant phenotyping platform, GrowScreen-PaGe, was used to resolve the dynamics of shoot and root growth of the model cereal Brachypodium (Brachypodium distachyon Bd21-3) in response to the plant growth promoting (PGP) bacteria Azospirillum (Azospirillum brasilense Sp245). Inoculated Brachypodium plants had greater early vigor and higher P use efficiency than non-inoculated Brachypodium at low P and low temperature conditions. Root systems were imaged non-invasively at eight time points and data combined with leaf area, shoot biomass and nutrient content from destructive subsamples at 7, 14 and 21 days after inoculation (DAI). Azospirillum colonisation of roots improved Brachypodium shoot and, to a greater degree, root growth in three independent experiments. Inoculation promoted P use efficiency in shoots but not P concentration or uptake, despite increased total root length. Longer roots in inoculated plants arose from twofold faster branch root growth but slower axile root growth, detected at 11 DAI. Analysis of the spatio-temporal phenotypes indicated that the effects of Azospirillum inoculation increased as shoot P concentration declined, but the magnitude depended on the time after inoculation and growth rate of branch roots compared to axile roots. High throughput plant phenotyping platforms allow the details of plant-microorganism symbioses to be resolved, offering insights into the timing of changes in different tissues to allow molecular mechanisms to be determined

MapMan4: A Refined Protein Classification and Annotation Framework Applicable to Multi-Omics Data Analysis

Genome sequences from over 200 plant species have already been published, with this number expected to increase rapidly due to advances in sequencing technologies. Once a new genome has been assembled and the genes identified, the functional annotation of their proteins using ontologies is of key importance as it places the sequencing data in a biological context. Furthermore, in order to keep pace with rapid production of genome sequences, this functional annotation process must be fully automated.Here we present a redesigned and significantly enhanced MapMan4 framework, together with a revised version of the associated online Mercator annotation tool. Compared to the original MapMan, the new ontology has been expanded almost threefold and now enforces stricter assignment rules. This ontology has been incorporated into Mercator4, which has been upgraded to reflect current knowledge across the land plant group and thus provides protein annotations for all embryophytes with a comparably high quality. The annotation process has been optimized to allow a plant genome to be annotated in a matter of minutes. The output results continue to be compatible with the established MapMan desktop application