A dolabralexin-deficient mutant provides insight into specialized diterpenoid metabolism in maize.

Two major groups of specialized metabolites in maize (Zea mays), termed kauralexins and dolabralexins, serve as known or predicted diterpenoid defenses against pathogens, herbivores, and other environmental stressors. To consider the physiological roles of the recently discovered dolabralexin pathway, we examined dolabralexin structural diversity, tissue-specificity, and stress-elicited production in a defined biosynthetic pathway mutant. Metabolomics analyses support a larger number of dolabralexin pathway products than previously known. We identified dolabradienol as a previously undetected pathway metabolite and characterized its enzymatic production. Transcript and metabolite profiling showed that dolabralexin biosynthesis and accumulation predominantly occur in primary roots and show quantitative variation across genetically diverse inbred lines. Generation and analysis of CRISPR-Cas9-derived loss-of-function Kaurene Synthase-Like 4 (Zmksl4) mutants demonstrated dolabralexin production deficiency, thus supporting ZmKSL4 as the diterpene synthase responsible for the conversion of geranylgeranyl pyrophosphate precursors into dolabradiene and downstream pathway products. Zmksl4 mutants further display altered root-to-shoot ratios and root architecture in response to water deficit. Collectively, these results demonstrate dolabralexin biosynthesis via ZmKSL4 as a committed pathway node biochemically separating kauralexin and dolabralexin metabolism, and suggest an interactive role of maize dolabralexins in plant vigor during abiotic stress.

Abnormal paraoxonase-1 (PON1) enzyme activity in idiopathic inflammatory myopathies.

OBJECTIVES: Patients with idiopathic inflammatory myopathies (IIM) have severe vascular involvement, which contributes to disease morbidity and mortality. Paraoxonase-1 (PON1) is a high-density lipoprotein (HDL) associated protein that protects the vascular endothelium from oxidative injury and damage. The current work assessed the functional and genetic determinants of PON1 activity in IIM patients. METHODS: A total of 184 IIM patients and 112 healthy controls (HC) were included. PON1 enzyme activity was assessed by paraoxonase, arylesterase and lactonase assays, and the Q192R PON1 single nucleotide polymorphism (SNP) was analysed. Multivariate regression models examined associations of PON1 activity with IIM diagnosis and myositis disease outcomes. RESULTS: The arylesterase and lactonase activities of PON1 were significantly lower in IIM patients compared with HC. Higher myositis disease activity, the presence of severe IIM-associated interstitial lung disease (ILD), and the presence of MDA5 or anti-synthetase antibodies were significantly associated with lower PON1 activity. The PON1 Q192R polymorphism was strongly linked to the paraoxonase activity of PON1 in IIM, and patients with the PON1 QQ genotype had better IIM disease outcomes compared with patients with the QR or RR genotypes. CONCLUSIONS: The arylesterase and lactonase activities of PON1 are significantly impaired in IIM patients compared with HC, and inversely associate with IIM disease activity and the presence of severe ILD. The PON1 QQ genotype associates with more favourable disease outcomes in IIM patients. Large prospective studies are needed to further evaluate the role of PON1 and PON1 genetic polymorphisms in the development and propagation of IIM and IIM-ILD.

Optimisation of root traits to provide enhanced ecosystem services in agricultural systems: A focus on cover crops.

Roots are the interface between the plant and the soil and play a central role in multiple ecosystem processes. With intensification of agricultural practices, rhizosphere processes are being disrupted and are causing degradation of the physical, chemical and biotic properties of soil. However, cover crops, a group of plants that provide ecosystem services, can be utilised during fallow periods or used as an intercrop to restore soil health. The effectiveness of ecosystem services provided by cover crops varies widely as very little breeding has occurred in these species. Improvement of ecosystem service performance is rarely considered as a breeding trait due to the complexities and challenges of belowground evaluation. Advancements in root phenotyping and genetic tools are critical in accelerating ecosystem service improvement in cover crops. In this study, we provide an overview of the range of belowground ecosystem services provided by cover crop roots: (1) soil structural remediation, (2) capture of soil resources and (3) maintenance of the rhizosphere and building of organic matter content. Based on the ecosystem services described, we outline current and promising phenotyping technologies and breeding strategies in cover crops that can enhance agricultural sustainability through improvement of root traits.

High- density lipoprotein function is abnormal in idiopathic inflammatory myopathies.

OBJECTIVE: Damage to the vascular endothelium is strongly implicated in the pathogenesis of idiopathic inflammatory myopathies (IIM). Normally, high-density lipoprotein (HDL) protects the vascular endothelium from damage from oxidized phospholipids, which accumulate under conditions of oxidative stress. The current work evaluated the antioxidant function of HDL in IIM patients. METHODS: HDL's antioxidant function was measured in IIM patients using a cell-free assay, which assesses the ability of isolated patient HDL to inhibit oxidation of low-density lipoproteins and is reported as the HDL inflammatory index (HII). Cholesterol profiles were measured for all patients, and subgroup analysis included assessment of oxidized fatty acids in HDL and plasma MPO activity. A subgroup of IIM patients was compared with healthy controls. RESULTS: The antioxidant function of HDL was significantly worse in patients with IIM (n = 95) compared with healthy controls (n = 41) [mean (S.d.) HII 1.12 (0.61) vs 0.82 (0.13), P < 0.0001]. Higher HII associated with higher plasma MPO activity [mean (S.d.) 13.2 (9.1) vs 9.1 (4.6), P = 0.0006] and higher oxidized fatty acids in HDL. Higher 5-hydroxyeicosatetraenoic acid in HDL correlated with worse diffusion capacity in patients with interstitial lung disease (r = -0.58, P = 0.02), and HDL's antioxidant function was most impaired in patients with autoantibodies against melanoma differentiation-associated protein 5 (MDA5) or anti-synthetase antibodies. In multivariate analysis including 182 IIM patients, higher HII was associated with higher disease activity and DM diagnosis. CONCLUSION: The antioxidant function of HDL is abnormal in IIM patients and may warrant further investigation for its role in propagating microvascular inflammation and damage in this patient population.

Maize lateral root developmental plasticity induced by mild water stress. II: Genotype-specific spatio-temporal effects on determinate development.

Maize lateral roots exhibit determinate growth, whereby the meristem is genetically programmed to stop producing new cells. To explore whether lateral root determinacy is modified under water deficits, we studied two maize genotypes (B73 and FR697) with divergent responses of lateral root growth to mild water stress using an experimental system that provided near-stable water potential environments throughout lateral root development. First-order laterals of the primary root system of FR697 exhibited delayed determinacy when grown at a water potential of -0.28 MPa, resulting in longer and wider roots than in well-watered (WW) controls. In B73, in contrast, neither the length nor width of lateral roots was affected by water deficit. In water-stressed FR697, root elongation continued at or above the maximum rate in WW roots for 3 days longer, and was still 45% of maximum when WW roots approached their determinate length. Maintenance of root elongation was associated with sustained rates of cell production. In addition, kinematic analyses showed that reductions in tissue expansion rates with aging were delayed in the longitudinal, radial and tangential planes throughout the root growth zone. Thus, this study reveals large genotypic differences in the interaction of water stress with developmental determinacy of maize lateral roots.

Maize lateral root developmental plasticity induced by mild water stress. I: Genotypic variation across a high-resolution series of water potentials.

Lateral root developmental plasticity induced by mild water stress was examined across a high-resolution series of growth media water potentials (Ψw ) in two genotypes of maize. The suitability of several media for imposing near-stable Ψw treatments on transpiring plants over prolonged growth periods was assessed. Genotypic differences specific to responses of lateral root growth from the primary root system occurred between cultivars FR697 and B73 over a narrow series of water stress treatments ranging in Ψw from -0.25 to -0.40 MPa. In FR697, both the average length and number of first-order lateral roots were substantially enhanced at a Ψw of -0.25 MPa compared with well-watered controls. These effects were separated spatially, occurring primarily in the upper and lower regions of the axial root, respectively. Furthermore, first-order lateral roots progressively increased in diameter with increasing water stress, resulting in a maximum 2.3-fold increase in root volume at a Ψw of -0.40 MPa. In B73, in contrast, the length, diameter, nor number of lateral roots was increased in any of the water stress treatments. The genotype-specific responses observed over this narrow range of Ψw demonstrate the necessity of high-resolution studies at mild stress levels for characterization of lateral root developmental plasticity.

Root system architecture and environmental flux analysis in mature crops using 3D root mesocosms.

Current methods of root sampling typically only obtain small or incomplete sections of root systems and do not capture their true complexity. To facilitate the visualization and analysis of full-sized plant root systems in 3-dimensions, we developed customized mesocosm growth containers. While highly scalable, the design presented here uses an internal volume of 45 ft3 (1.27 m3), suitable for large crop and bioenergy grass root systems to grow largely unconstrained. Furthermore, they allow for the excavation and preservation of 3-dimensional root system architecture (RSA), and facilitate the collection of time-resolved subterranean environmental data. Sensor arrays monitoring matric potential, temperature and CO2 levels are buried in a grid formation at various depths to assess environmental fluxes at regular intervals. Methods of 3D data visualization of fluxes were developed to allow for comparison with root system architectural traits. Following harvest, the recovered root system can be digitally reconstructed in 3D through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. We developed a pipeline to extract features from the 3D point clouds, or from derived skeletons that include point cloud voxel number as a proxy for biomass, total root system length, volume, depth, convex hull volume and solidity as a function of depth. Ground-truthing these features with biomass measurements from manually dissected root systems showed a high correlation. We evaluated switchgrass, maize, and sorghum root systems to highlight the capability for species wide comparisons. We focused on two switchgrass ecotypes, upland (VS16) and lowland (WBC3), in identical environments to demonstrate widely different root system architectures that may be indicative of core differences in their rhizoeconomic foraging strategies. Finally, we imposed a strong physiological water stress and manipulated the growth medium to demonstrate whole root system plasticity in response to environmental stimuli. Hence, these new "3D Root Mesocosms" and accompanying computational analysis provides a new paradigm for study of mature crop systems and the environmental fluxes that shape them.

Rated-M for mesocosm: allowing the multimodal analysis of mature root systems in 3D.

A plants' water and nutrients are primarily absorbed through roots, which in a natural setting is highly dependent on the 3-dimensional configuration of the root system, collectively known as root system architecture (RSA). RSA is difficult to study due to a variety of factors, accordingly, an arsenal of methods have been developed to address the challenges of both growing root systems for imaging, and the imaging methods themselves, although there is no 'best' method as each has its own spectrum of trade-offs. Here, we describe several methods for plant growth or imaging. Then, we introduce the adaptation and integration of three complementary methods, root mesocosms, photogrammetry, and electrical resistance tomography (ERT). Mesocosms can allow for unconstrained root growth, excavation and preservation of 3-dimensional RSA, and modularity that facilitates the use of a variety of sensors. The recovered root system can be digitally reconstructed through photogrammetry, which is an inexpensive method requiring only an appropriate studio space and a digital camera. Lastly, we demonstrate how 3-dimensional water availability can be measured using ERT inside of root mesocosms.

Super resolution for root imaging.

PREMISE: High-resolution cameras are very helpful for plant phenotyping as their images enable tasks such as target vs. background discrimination and the measurement and analysis of fine above-ground plant attributes. However, the acquisition of high-resolution images of plant roots is more challenging than above-ground data collection. An effective super-resolution (SR) algorithm is therefore needed for overcoming the resolution limitations of sensors, reducing storage space requirements, and boosting the performance of subsequent analyses. METHODS: We propose an SR framework for enhancing images of plant roots using convolutional neural networks. We compare three alternatives for training the SR model: (i) training with non-plant-root images, (ii) training with plant-root images, and (iii) pretraining the model with non-plant-root images and fine-tuning with plant-root images. The architectures of the SR models were based on two state-of-the-art deep learning approaches: a fast SR convolutional neural network and an SR generative adversarial network. RESULTS: In our experiments, we observed that the SR models improved the quality of low-resolution images of plant roots in an unseen data set in terms of the signal-to-noise ratio. We used a collection of publicly available data sets to demonstrate that the SR models outperform the basic bicubic interpolation, even when trained with non-root data sets. DISCUSSION: The incorporation of a deep learning-based SR model in the imaging process enhances the quality of low-resolution images of plant roots. We demonstrate that SR preprocessing boosts the performance of a machine learning system trained to separate plant roots from their background. Our segmentation experiments also show that high performance on this task can be achieved independently of the signal-to-noise ratio. We therefore conclude that the quality of the image enhancement depends on the desired application.