Belowground plant development measured with magnetic resonance imaging (MRI): exploiting the potential for non-invasive trait quantification using sugar beet as a proxy

Understanding role of roots in plant response to drought: Way forward to climate-resilient crops

Drought stress leads to a significant amount of agricultural crop loss. Thus, with changing climatic conditions, it is important to develop resilience measures in agricultural systems against drought stress. Roots play a crucial role in regulating plant development under drought stress. In this review, we have summarized the studies on the role of roots and root-mediated plant responses. We have also discussed the importance of root system architecture (RSA) and the various structural and anatomical changes that it undergoes to increase survival and productivity under drought. Various genes, transcription factors, and quantitative trait loci involved in regulating root growth and development are also discussed. A summarization of various instruments and software that can be used for high-throughput phenotyping in the field is also provided in this review. More comprehensive studies are required to help build a detailed understanding of RSA and associated traits for breeding drought-resilient cultivars.

Plant Nutrition-New Methods Based on the Lessons of History: A Review

As with new technologies, plant nutrition has taken a big step forward in the last two decades. The main objective of this review is to briefly summarise the main pathways in modern plant nutrition and attract potential researchers and publishers to this area. First, this review highlights the importance of long-term field experiments, which provide us with valuable information about the effects of different applied strategies. The second part is dedicated to the new analytical technologies (tomography, spectrometry, and chromatography), intensively studied environments (rhizosphere, soil microbial communities, and enzymatic activity), nutrient relationship indexes, and the general importance of proper data evaluation. The third section is dedicated to the strategies of plant nutrition, i.e., (i) plant breeding, (ii) precision farming, (iii) fertiliser placement, (iv) biostimulants, (v) waste materials as a source of nutrients, and (vi) nanotechnologies. Finally, the increasing environmental risks related to plant nutrition, including biotic and abiotic stress, mainly the threat of soil salinity, are mentioned. In the 21st century, fertiliser application trends should be shifted to local application, precise farming, and nanotechnology; amended with ecofriendly organic fertilisers to ensure sustainable agricultural practices; and supported by new, highly effective crop varieties. To optimise agriculture, only the combination of the mentioned modern strategies supported by a proper analysis based on long-term observations seems to be a suitable pathway.

3D U-Net Segmentation Improves Root System Reconstruction from 3D MRI Images in Automated and Manual Virtual Reality Work Flows

Magnetic resonance imaging (MRI) is used to image root systems grown in opaque soil. However, reconstruction of root system architecture (RSA) from 3-dimensional (3D) MRI images is challenging. Low resolution and poor contrast-to-noise ratios (CNRs) hinder automated reconstruction. Hence, manual reconstruction is still widely used. Here, we evaluate a novel 2-step work flow for automated RSA reconstruction. In the first step, a 3D U-Net segments MRI images into root and soil in super-resolution. In the second step, an automated tracing algorithm reconstructs the root systems from the segmented images. We evaluated the merits of both steps for an MRI dataset of 8 lupine root systems, by comparing the automated reconstructions to manual reconstructions of unaltered and segmented MRI images derived with a novel virtual reality system. We found that the U-Net segmentation offers profound benefits in manual reconstruction: reconstruction speed was doubled (+97%) for images with low CNR and increased by 27% for images with high CNR. Reconstructed root lengths were increased by 20% and 3%, respectively. Therefore, we propose to use U-Net segmentation as a principal image preprocessing step in manual work flows. The root length derived by the tracing algorithm was lower than in both manual reconstruction methods, but segmentation allowed automated processing of otherwise not readily usable MRI images. Nonetheless, model-based functional root traits revealed similar hydraulic behavior of automated and manual reconstructions. Future studies will aim to establish a hybrid work flow that utilizes automated reconstructions as scaffolds that can be manually corrected.

Seeing plants as never before

Imaging has long supported our ability to understand the inner life of plants, their development, and response to a dynamic environment. While optical microscopy remains the core tool for imaging, a suite of novel technologies is now beginning to make a significant contribution to visualize plant metabolism. The purpose of this review was to provide the scientific community with an overview of current imaging methods, which rely variously on either nuclear magnetic resonance (NMR), mass spectrometry (MS) or infrared (IR) spectroscopy, and to present some examples of their application in order to illustrate their utility. In addition to providing a description of the basic principles underlying these technologies, the review discusses their various advantages and limitations, reveals the current state of the art, and suggests their potential application to experimental practice. Finally, a view is presented as to how the technologies will likely develop, how these developments may encourage the formulation of novel experimental strategies, and how the enormous potential of these technologies can contribute to progress in plant science.

Rice immediately adapts the dynamics of photosynthates translocation to roots in response to changes in soil water environment

Rice is susceptible to abiotic stresses such as drought stress. To enhance drought resistance, elucidating the mechanisms by which rice plants adapt to intermittent drought stress that may occur in the field is an important requirement. Roots are directly exposed to changes in the soil water condition, and their responses to these environmental changes are driven by photosynthates. To visualize the distribution of photosynthates in the root system of rice plants under drought stress and recovery from drought stress, we combined X-ray computed tomography (CT) with open type positron emission tomography (OpenPET) and positron-emitting tracer imaging system (PETIS) with ¹¹C tracer. The short half-life of ¹¹C (20.39 min) allowed us to perform multiple experiments using the same plant, and thus photosynthate translocation was visualized as the same plant was subjected to drought stress and then re-irrigation for recovery. The results revealed that when soil is drier, ¹¹C-photosynthates mainly translocated to the seminal roots, likely to promote elongation of the root with the aim of accessing water stored in the lower soil layers. The photosynthates translocation to seminal roots immediately stopped after rewatering then increased significantly in crown roots. We suggest that when rice plant experiencing drought is re-irrigated from the bottom of pot, the destination of ¹¹C-photosynthates translocation immediately switches from seminal root to crown roots. We reveal that rice roots are responsive to changes in soil water conditions and that rice plants differentially adapts the dynamics of photosynthates translocation to crown roots and seminal roots depending on soil conditions.

Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives

Plant phenomics (PP) has been recognized as a bottleneck in studying the interactions of genomics and environment on plants, limiting the progress of smart breeding and precise cultivation. High-throughput plant phenotyping is challenging owing to the spatio-temporal dynamics of traits. Proximal and remote sensing (PRS) techniques are increasingly used for plant phenotyping because of their advantages in multi-dimensional data acquisition and analysis. Substantial progress of PRS applications in PP has been observed over the last two decades and is analyzed here from an interdisciplinary perspective based on 2972 publications. This progress covers most aspects of PRS application in PP, including patterns of global spatial distribution and temporal dynamics, specific PRS technologies, phenotypic research fields, working environments, species, and traits. Subsequently, we demonstrate how to link PRS to multi-omics studies, including how to achieve multi-dimensional PRS data acquisition and processing, how to systematically integrate all kinds of phenotypic information and derive phenotypic knowledge with biological significance, and how to link PP to multi-omics association analysis. Finally, we identify three future perspectives for PRS-based PP: (1) strengthening the spatial and temporal consistency of PRS data, (2) exploring novel phenotypic traits, and (3) facilitating multi-omics communication.

Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway

Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.

Recent advances in methods for in situ root phenotyping

Roots assist plants in absorbing water and nutrients from soil. Thus, they are vital to the survival of nearly all land plants, considering that plants cannot move to seek optimal environmental conditions. Crop species with optimal root system are essential for future food security and key to improving agricultural productivity and sustainability. Root systems can be improved and bred to acquire soil resources efficiently and effectively. This can also reduce adverse environmental impacts by decreasing the need for fertilization and fresh water. Therefore, there is a need to improve and breed crop cultivars with favorable root system. However, the lack of high-throughput root phenotyping tools for characterizing root traits in situ is a barrier to breeding for root system improvement. In recent years, many breakthroughs in the measurement and analysis of roots in a root system have been made. Here, we describe the major advances in root image acquisition and analysis technologies and summarize the advantages and disadvantages of each method. Furthermore, we look forward to the future development direction and trend of root phenotyping methods. This review aims to aid researchers in choosing a more appropriate method for improving the root system.

Specialized Plant Growth Chamber Designs to Study Complex Rhizosphere Interactions

The rhizosphere is a dynamic ecosystem shaped by complex interactions between plant roots, soil, microbial communities and other micro- and macro-fauna. Although studied for decades, critical gaps exist in the study of plant roots, the rhizosphere microbiome and the soil system surrounding roots, partly due to the challenges associated with measuring and parsing these spatiotemporal interactions in complex heterogeneous systems such as soil. To overcome the challenges associated with in situ study of rhizosphere interactions, specialized plant growth chamber systems have been developed that mimic the natural growth environment. This review discusses the currently available lab-based systems ranging from widely known rhizotrons to other emerging devices designed to allow continuous monitoring and non-destructive sampling of the rhizosphere ecosystems in real-time throughout the developmental stages of a plant. We categorize them based on the major rhizosphere processes it addresses and identify their unique challenges as well as advantages. We find that while some design elements are shared among different systems (e.g., size exclusion membranes), most of the systems are bespoke and speaks to the intricacies and specialization involved in unraveling the details of rhizosphere processes. We also discuss what we describe as the next generation of growth chamber employing the latest technology as well as the current barriers they face. We conclude with a perspective on the current knowledge gaps in the rhizosphere which can be filled by innovative chamber designs.

Cold-Triggered Induction of ROS- and Raffinose Metabolism in Freezing-Sensitive Taproot Tissue of Sugar Beet

Sugar beet (Beta vulgaris subsp. vulgaris) is the exclusive source of sugar in the form of sucrose in temperate climate zones. Sugar beet is grown there as an annual crop from spring to autumn because of the damaging effect of freezing temperatures to taproot tissue. A collection of hybrid and non-hybrid sugar beet cultivars was tested for winter survival rates and freezing tolerance. Three genotypes with either low or high winter survival rates were selected for detailed study of their response to frost. These genotypes differed in the severity of frost injury in a defined inner region in the upper part of the taproot, the so-called pith. We aimed to elucidate genotype- and tissue-dependent molecular processes during freezing and combined analyses of sugar beet anatomy and physiology with transcriptomic and metabolite profiles of leaf and taproot tissues at low temperatures. Freezing temperatures induced strong downregulation of photosynthesis in leaves, generation of reactive oxygen species (ROS), and ROS-related gene expression in taproots. Simultaneously, expression of genes involved in raffinose metabolism, as well as concentrations of raffinose and its intermediates, increased markedly in both leaf and taproot tissue at low temperatures. The accumulation of raffinose in the pith tissue correlated with freezing tolerance of the three genotypes. We discuss a protective role for raffinose and its precursors against freezing damage of sugar beet taproot tissue.

Low-field magnetic resonance imaging of roots in intact clayey and silty soils

The development of a robust method to non-invasively visualize root morphology in natural soils has been hampered by the opaque, physical, and structural properties of soils. In this work we describe a novel technology, low field magnetic resonance imaging (LF-MRI), for imaging energy sorghum (Sorghum bicolor (L.) Moench) root morphology and architecture in intact soils. The use of magnetic fields much weaker than those used with traditional MRI experiments reduces the distortion due to magnetic material naturally present in agricultural soils. A laboratory based LF-MRI operating at 47 mT magnetic field strength was evaluated using two sets of soil cores: 1) soil/root cores of Weswood silt loam (Udifluventic Haplustept) and a Belk clay (Entic Hapluderts) from a conventionally tilled field, and 2) soil/root cores from rhizotrons filled with either a Houston Black (Udic Haplusterts) clay or a sandy loam purchased from a turf company. The maximum soil water nuclear magnetic resonance (NMR) relaxation time T₂ (4 ms) and the typical root water relaxation time T₂ (100 ms) are far enough apart to provide a unique contrast mechanism such that the soil water signal has decayed to the point of no longer being detectable during the data collection time period. 2-D MRI projection images were produced of roots with a diameter range of 1.5-2.0 mm using an image acquisition time of 15 min with a pixel resolution of 1.74 mm in four soil types. Additionally, we demonstrate the use of a data-driven machine learning reconstruction approach, Automated Transform by Manifold Approximation (AUTOMAP) to reconstruct raw data and improve the quality of the final images. The application of AUTOMAP showed a SNR (Signal to Noise Ratio) improvement of two fold on average. The use of low field MRI presented here demonstrates the possibility of applying low field MRI through intact soils to root phenotyping and agronomy to aid in understanding of root morphology and the spatial arrangement of roots in situ.

A small-scale MRI scanner and complementary imaging method to visualize and quantify xylem embolism formation

Magnetic resonance imaging (MRI) is a useful tool to image xylem embolism formation in plants. MRI scanners configured to accept intact plants are rare and expensive. Here, we investigate if affordable small-scale, custom-built low-field MRI scanners would suffice for the purpose. A small-scale, C-shaped permanent magnet was paired with open, plane parallel imaging gradients. The setup was small enough to fit between leaves or branches and offered open access for plant stems of arbitrary length. To counter the two main drawbacks of the system, low signal to noise and reduced magnetic field homogeneity, a multi-spin echo (MSE) pulse sequence was implemented, allowing efficient signal acquisition and quantitative imaging of water content and T₂ signal relaxation. The system was tested visualizing embolism formation in Fagus sylvatica during bench dehydration. High-quality images of water content and T₂ were readily obtained, which could be utilized to detect the cavitation of vessels smaller than could be spatially resolved. A multiplication of both map types yielded images in which filled xylem appeared with even greater contrast. T₂ imaging with small-scale MRI devices allows straightforward visualization of the spatial and temporal dynamics of embolism formation and the derivation of vulnerability curves.

Novel Imaging Modalities Shedding Light on Plant Biology: Start Small and Grow Big

The acquisition of quantitative information on plant development across a range of temporal and spatial scales is essential to understand the mechanisms of plant growth. Recent years have shown the emergence of imaging methodologies that enable the capture and analysis of plant growth, from the dynamics of molecules within cells to the measurement of morphometricand physiological traits in field-grown plants. In some instances, these imaging methods can be parallelized across multiple samples to increase throughput. When high throughput is combined with high temporal and spatial resolution, the resulting image-derived data sets could be combined with molecular large-scale data sets to enable unprecedented systems-level computational modeling. Such image-driven functional genomics studies may be expected to appear at an accelerating rate in the near future given the early success of the foundational efforts reviewed here. We present new imaging modalities and review how they have enabled a better understanding of plant growth from the microscopic to the macroscopic scale.

Magnetic Resonance Microscopy at Cellular Resolution and Localised Spectroscopy of Medicago truncatula at 22.3 Tesla

Interactions between plants and the soil’s microbial & fungal flora are crucial for the health of soil ecosystems and food production. Microbe-plant interactions are difficult to investigate in situ due to their intertwined relationship involving morphology and metabolism. Here, we describe an approach to overcome this challenge by elucidating morphology and the metabolic profile of Medicago truncatula root nodules using Magnetic Resonance (MR) Microscopy, at the highest magnetic field strength (22.3 T) currently available for imaging. A home-built solenoid RF coil with an inner diameter of 1.5 mm was used to study individual root nodules. A 3D imaging sequence with an isotropic resolution of (7 μm)³ was able to resolve individual cells, and distinguish between cells infected with rhizobia and uninfected cells. Furthermore, we studied the metabolic profile of cells in different sections of the root nodule using localised MR spectroscopy and showed that several metabolites, including betaine, asparagine/aspartate and choline, have different concentrations across nodule zones. The metabolite spatial distribution was visualised using chemical shift imaging. Finally, we describe the technical challenges and outlook towards future in vivo MR microscopy of nodules and the plant root system.

The biochemistry underpinning industrial seed technology and mechanical processing of sugar beet

Seed-processing technologies such as polishing and washing enhance crop seed quality by limited removal of the outer layers and by leaching. Combined, this removes chemical compounds that inhibit germination. Industrial processing to deliver high-quality commercial seed includes removing chemical inhibitors of germination, and is essential to produce fresh sprouts, achieve vigorous crop establishment, and high yield potential in the field. Sugar beet (Beta vulgaris subsp. vulgaris var. altissima Doell.), the main sugar source of the temperate agricultural zone, routinely undergoes several processing steps during seed production to improve germination performance and seedling growth. Germination assays and seedling phenotyping was carried out on unprocessed, and processed (polished and washed) sugar beet fruits. Pericarp-derived solutes, known to inhibit germination, were tested in germination assays and their osmolality and conductivity assessed (ions). Abscisic acid (ABA) and ABA metabolites were quantified in both the true seed and pericarp tissue using UPLC-ESI(+)-MS/MS. Physical changes in the pericarp structures were assessed using scanning electron microscopy (SEM). We found that polishing and washing of the sugar beet fruits both had a positive effect on germination performance and seedling phenotype, and when combined, this positive effect was stronger. The mechanical action of polishing removed the outer pericarp (fruit coat) tissue (parenchyma), leaving the inner tissue (sclerenchyma) unaltered, as revealed by SEM. Polishing as well as washing removed germination inhibitors from the pericarp, specifically, ABA, ABA metabolites, and ions. Understanding the biochemistry underpinning the effectiveness of these processing treatments is key to driving further innovations in commercial seed quality.

Uncovering the hidden half of plants using new advances in root phenotyping

Major increases in crop yield are required to keep pace with population growth and climate change. Improvements to the architecture of crop roots promise to deliver increases in water and nutrient use efficiency but profiling the root phenome (i.e. its structure and function) represents a major bottleneck. We describe how advances in imaging and sensor technologies are making root phenomic studies possible. However, methodological advances in acquisition, handling and processing of the resulting 'big-data' is becoming increasingly important. Advances in automated image analysis approaches such as Deep Learning promise to transform the root phenotyping landscape. Collectively, these innovations are helping drive the selection of the next-generation of crops to deliver real world impact for ongoing global food security efforts.

A new method for the rapid characterization of root growth and distribution using digital image correlation

Rapidly determining root growth patterns is biologically important and technically challenging. Current methods focus on direct observation of roots and require destructive excavations or time-consuming root tracing. We developed a novel methodology based on analyzing soil particle displacement, rather than direct observation of roots. This inferred root growth method uses digital image correlation (DIC) analysis, an established and high-throughput method used in many engineering and science disciplines. By applying DIC analyses to repeated images of plants grown in clear window boxes, we produced visually intuitive and quantifiable strain maps, indicating the magnitude and direction of soil movement. From this, we could infer root growth and rapidly quantify root system metrics. Strain measures were closely associated with the spatial distribution of roots and correlated with root length measured using conventional approaches. The method also allowed for the detection of root proliferation in nutrient-enriched soil patches, indicating its suitability for quantifying biological patterns. This novel application of DIC in root biology is effective, scalable, low cost, flexible and complementary to existing technologies. This method offers a new tool for answering questions in plant biology and will be particularly useful in studies involving temporal dynamics of root processes.

New live screening of plant-nematode interactions in the rhizosphere

Free living nematodes (FLN) are microscopic worms found in all soils. While many FLN species are beneficial to crops, some species cause significant damage by feeding on roots and vectoring viruses. With the planned legislative removal of traditionally used chemical treatments, identification of new ways to manage FLN populations has become a high priority. For this, more powerful screening systems are required to rapidly assess threats to crops and identify treatments efficiently. Here, we have developed new live assays for testing nematode responses to treatment by combining transparent soil microcosms, a new light sheet imaging technique termed Biospeckle Selective Plane Illumination Microscopy (BSPIM) for fast nematode detection, and Confocal Laser Scanning Microscopy for high resolution imaging. We show that BSPIM increased signal to noise ratios by up to 60 fold and allowed the automatic detection of FLN in transparent soil samples of 1.5 mL. Growing plant root systems were rapidly scanned for nematode abundance and activity, and FLN feeding behaviour and responses to chemical compounds observed in soil-like conditions. This approach could be used for direct monitoring of FLN activity either to develop new compounds that target economically damaging herbivorous nematodes or ensuring that beneficial species are not negatively impacted.

Investigating the microstructure of plant leaves in 3D with lab-based X-ray computed tomography

BACKGROUND

Leaf cellular architecture plays an important role in setting limits for carbon assimilation and, thus, photosynthetic performance. However, the low density, fine structure, and sensitivity to desiccation of plant tissue has presented challenges to its quantification. Classical methods of tissue fixation and embedding prior to 2D microscopy of sections is both laborious and susceptible to artefacts that can skew the values obtained. Here we report an image analysis pipeline that provides quantitative descriptors of plant leaf intercellular airspace using lab-based X-ray computed tomography (microCT). We demonstrate successful visualisation and quantification of differences in leaf intercellular airspace in 3D for a range of species (including both dicots and monocots) and provide a comparison with a standard 2D analysis of leaf sections.

RESULTS

We used the microCT image pipeline to obtain estimates of leaf porosity and mesophyll exposed surface area (S_mes) for three dicot species (Arabidopsis, tomato and pea) and three monocot grasses (barley, oat and rice). The imaging pipeline consisted of (1) a masking operation to remove the background airspace surrounding the leaf, (2) segmentation by an automated threshold in ImageJ and then (3) quantification of the extracted pores using the ImageJ 'Analyze Particles' tool. Arabidopsis had the highest porosity and lowest S_mes for the dicot species whereas barley had the highest porosity and the highest S_mes for the grass species. Comparison of porosity and S_mes estimates from 3D microCT analysis and 2D analysis of sections indicates that both methods provide a comparable estimate of porosity but the 2D method may underestimate S_mes by almost 50%. A deeper study of porosity revealed similarities and differences in the asymmetric distribution of airspace between the species analysed.

CONCLUSIONS

Our results demonstrate the utility of high resolution imaging of leaf intercellular airspace networks by lab-based microCT and provide quantitative data on descriptors of leaf cellular architecture. They indicate there is a range of porosity and S_mes values in different species and that there is not a simple relationship between these parameters, suggesting the importance of cell size, shape and packing in the determination of cellular parameters proposed to influence leaf photosynthetic performance.

Roots-eye view: Using microdialysis and microCT to non-destructively map root nutrient depletion and accumulation zones

Improvement in fertilizer use efficiency is a key aspect for achieving sustainable agriculture in order to minimize costs, greenhouse gas emissions, and pollution from nutrient run-off. To optimize root architecture for nutrient uptake and efficiency, we need to understand what the roots encounter in their environment. Traditional methods of nutrient sampling, such as salt extractions can only be done at the end of an experiment, are impractical for sampling locations precisely and give total nutrient values that can overestimate the nutrients available to the roots. In contrast, microdialysis provides a non-invasive, continuous method for sampling available nutrients in the soil. Here, for the first time, we have used microCT imaging to position microdialysis probes at known distances from the roots and then measured the available nitrate and ammonium. We found that nitrate accumulated close to roots whereas ammonium was depleted demonstrating that this combination of complementary techniques provides a unique ability to measure root-available nutrients non-destructively and in almost real time.

Macro optical projection tomography for large scale 3D imaging of plant structures and gene activity

Optical projection tomography (OPT) is a well-established method for visualising gene activity in plants and animals. However, a limitation of conventional OPT is that the specimen upper size limit precludes its application to larger structures. To address this problem we constructed a macro version called Macro OPT (M-OPT). We apply M-OPT to 3D live imaging of gene activity in growing whole plants and to visualise structural morphology in large optically cleared plant and insect specimens up to 60 mm tall and 45 mm deep. We also show how M-OPT can be used to image gene expression domains in 3D within fixed tissue and to visualise gene activity in 3D in clones of growing young whole Arabidopsis plants. A further application of M-OPT is to visualise plant-insect interactions. Thus M-OPT provides an effective 3D imaging platform that allows the study of gene activity, internal plant structures and plant-insect interactions at a macroscopic scale.

Effects of Secondary Plant Metabolites on Microbial Populations: Changes in Community Structure and Metabolic Activity in Contaminated Environments

Secondary plant metabolites (SPMEs) play an important role in plant survival in the environment and serve to establish ecological relationships between plants and other organisms. Communication between plants and microorganisms via SPMEs contained in root exudates or derived from litter decomposition is an example of this phenomenon. In this review, the general aspects of rhizodeposition together with the significance of terpenes and phenolic compounds are discussed in detail. We focus specifically on the effect of SPMEs on microbial community structure and metabolic activity in environments contaminated by polychlorinated biphenyls (PCBs) and polyaromatic hydrocarbons (PAHs). Furthermore, a section is devoted to a complex effect of plants and/or their metabolites contained in litter on bioremediation of contaminated sites. New insights are introduced from a study evaluating the effects of SPMEs derived during decomposition of grapefruit peel, lemon peel, and pears on bacterial communities and their ability to degrade PCBs in a long-term contaminated soil. The presented review supports the "secondary compound hypothesis" and demonstrates the potential of SPMEs for increasing the effectiveness of bioremediation processes.

Quantitative 3D Analysis of Plant Roots Growing in Soil Using Magnetic Resonance Imaging

Precise measurements of root system architecture traits are an important requirement for plant phenotyping. Most of the current methods for analyzing root growth require either artificial growing conditions (e.g. hydroponics), are severely restricted in the fraction of roots detectable (e.g. rhizotrons), or are destructive (e.g. soil coring). On the other hand, modalities such as magnetic resonance imaging (MRI) are noninvasive and allow high-quality three-dimensional imaging of roots in soil. Here, we present a plant root imaging and analysis pipeline using MRI together with an advanced image visualization and analysis software toolbox named NMRooting. Pots up to 117 mm in diameter and 800 mm in height can be measured with the 4.7 T MRI instrument used here. For 1.5 l pots (81 mm diameter, 300 mm high), a fully automated system was developed enabling measurement of up to 18 pots per day. The most important root traits that can be nondestructively monitored over time are root mass, length, diameter, tip number, and growth angles (in two-dimensional polar coordinates) and spatial distribution. Various validation measurements for these traits were performed, showing that roots down to a diameter range between 200 μm and 300 μm can be quantitatively measured. Root fresh weight correlates linearly with root mass determined by MRI. We demonstrate the capabilities of MRI and the dedicated imaging pipeline in experimental series performed on soil-grown maize (Zea mays) and barley (Hordeum vulgare) plants.

Assessing potato tuber diel growth by means of X-ray computed tomography

The formation and development of belowground organs is difficult to study. X-ray computed tomography (CT) provides the possibility to analyse and interpret subtle volumetric changes of belowground organs such as tubers, storage roots and nodules. Here, we report on the establishment of a method based on a voxel dimension of 240 μm and precision (standard deviation) of 30 μL that allows interpreting growth differences among potato tubers happening within 3 h. Plants were not stressed by the application of X-ray radiation, which was shown both by morphological comparison with control plants and by analysis of lipid peroxidation as a measure of oxidative stress. Diel (24 h) tuber growth fluctuations of three potato genotypes were monitored in soil-filled pots of 10 L. In contrast to the results from previous reports, most tubers grew at similar rates during day and night. Tuber growth was not related to the developmental stage of plants and tubers. Pronounced differences were observed between average growth rates in different tubers within a plant. These results are discussed in the context of restrictions of past methods to study tuber growth and in the context of their potential for the characterization of the formation and development of other belowground plant organs.

Metabolic Architecture of the Cereal Grain and Its Relevance to Maximize Carbon Use Efficiency

Here, we have characterized the spatial heterogeneity of the cereal grain's metabolism and demonstrated how, by integrating a distinct set of metabolic strategies, the grain has evolved to become an almost perfect entity for carbon storage. In vivo imaging revealed light-induced cycles in assimilate supply toward the ear/grain of barley (Hordeum vulgare) and wheat (Triticum aestivum). In silico modeling predicted that, in the two grain storage organs (the endosperm and embryo), the light-induced shift in solute influx does cause adjustment in metabolic flux without changes in pathway utilization patterns. The enveloping, leaf-like pericarp, in contrast, shows major shifts in flux distribution (starch metabolism, photosynthesis, remobilization, and tricarboxylic acid cycle activity) allow to refix 79% of the CO2 released by the endosperm and embryo, allowing the grain to achieve an extraordinary high carbon conversion efficiency of 95%. Shading experiments demonstrated that ears are autonomously able to raise the influx of solutes in response to light, but with little effect on the steady-state levels of metabolites or transcripts or on the pattern of sugar distribution within the grain. The finding suggests the presence of a mechanism(s) able to ensure metabolic homeostasis in the face of short-term environmental fluctuation. The proposed multicomponent modeling approach is informative for predicting the metabolic effects of either an altered level of incident light or a momentary change in the supply of sucrose. It is therefore of potential value for assessing the impact of either breeding and/or biotechnological interventions aimed at increasing grain yield.

Hormone-mediated growth dynamics of the barley pericarp as revealed by magnetic resonance imaging and transcript profiling

The shape of the maternal pericarp affects cereal grain mass and yield. Pericarp growth was analysed by magnetic resonance imaging (MRI), revealing topological maps of mobile water in developing pericarp of barley (Hordeum vulgare) and displaying tissue regions actively elongating in specific temporal-spatial patterns. Correlation analysis of MRI signals and growth rates reveals that growth in length is mediated by dorsal and also lateral rather than ventral regions. Growth in thickness is related to ventral regions. Switching from dorsal to ventral growth is associated with differential expression of axial regulators of the HD-ZipIII and Kanadi/Ettin types, and NPH3 photoreceptors, suggesting light-mediated auxin re-distribution. Auxin increases with the highest levels in the basal pericarp at 6 days after fertilization (DAF), together with transcriptionally up-regulated auxin transport and signalling. Gibberellin biosynthesis is transcriptionally up-regulated only later, and levels of bioactive gibberellins increase from 7 to 13 DAF, with higher levels in ventral than dorsal regions. Differential gene expression related to cell expansion indicates genes related to apoplast acidification, wall relaxation, sugar cleavage, water transport, and cell wall biosynthesis. Candidate genes potentially involved in pericarp extension are distinguished by their temporal expression, representing potential isoforms responsible for dorsal-mediated early growth in length or ventral-mediated late growth in thickness.

ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging

Imaging techniques for visualizing and analyzing precise morphology and gene expression patterns are essential for understanding biological processes during development in all organisms. With the aid of chemical screening, we developed a clearing method using chemical solutions, termed ClearSee, for deep imaging of morphology and gene expression in plant tissues. ClearSee rapidly diminishes chlorophyll autofluorescence while maintaining fluorescent protein stability. By adjusting the refractive index mismatch, whole-organ and whole-plant imaging can be performed by both confocal and two-photon excitation microscopy in ClearSee-treated samples. Moreover, ClearSee is applicable to multicolor imaging of fluorescent proteins to allow structural analysis of multiple gene expression. Given that ClearSee is compatible with staining by chemical dyes, the technique is useful for deep imaging in conjunction with genetic markers and for plant species not amenable to transgenic approaches. This method is useful for whole imaging for intact morphology and will help to accelerate the discovery of new phenomena in plant biological research.

Summary: The optical clearing reagent ClearSee improves the multicolor imaging of fluorescent proteins and dyes and allows the structural analysis of gene expression patterns in multiple plant tissues.

Magnetic resonance imaging of sugar beet taproots in soil reveals growth reduction and morphological changes during foliar Cercospora beticola infestation

Cercospora leaf spot (CLS) infection can cause severe yield loss in sugar beet. Introduction of Cercospora-resistant varieties in breeding programmes is important for plant protection to reduce both fungicide applications and the risk of the development of fungal resistance. However, in vivo monitoring of the sugar-containing taproots at early stages of foliar symptoms and the characterization of the temporal development of disease progression has proven difficult. Non-invasive magnetic resonance imaging (MRI) measurements were conducted to quantify taproot development of genotypes with high (HS) and low (LS) levels of susceptibility after foliar Cercospora inoculation. Fourteen days post-inoculation (dpi) the ratio of infected leaf area was still low (~7%) in both the HS and LS genotypes. However, during this period, the volumetric growth of the taproot had already started to decrease. Additionally, inoculated plants showed a reduction of the increase in width of inner cambial rings while the width of outer rings increased slightly compared with non-inoculated plants. This response partly compensated for the reduced development of inner rings that had a vascular connection with Cercospora-inoculated leaves. Hence, alterations in taproot anatomical features such as volume and cambial ring development can be non-invasively detected already at 14 dpi, providing information on the early impact of the infection on whole-plant performance. All these findings show that MRI is a suitable tool to identify promising candidate parent lines with improved resistance to Cercospora, for example with comparatively lower taproot growth reduction at early stages of canopy infection, for future introduction into breeing programmes.

Direct comparison of MRI and X-ray CT technologies for 3D imaging of root systems in soil: potential and challenges for root trait quantification

BACKGROUND

Roots are vital to plants for soil exploration and uptake of water and nutrients. Root performance is critical for growth and yield of plants, in particular when resources are limited. Since roots develop in strong interaction with the soil matrix, tools are required that can visualize and quantify root growth in opaque soil at best in 3D. Two modalities that are suited for such investigations are X-ray Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Due to the different physical principles they are based on, these modalities have their specific potentials and challenges for root phenotyping. We compared the two methods by imaging the same root systems grown in 3 different pot sizes with inner diameters of 34 mm, 56 mm or 81 mm.

RESULTS

Both methods successfully visualized roots of two weeks old bean plants in all three pot sizes. Similar root images and almost the same root length were obtained for roots grown in the small pot, while more root details showed up in the CT images compared to MRI. For the medium sized pot, MRI showed more roots and higher root lengths whereas at some spots thin roots were only found by CT and the high water content apparently affected CT more than MRI. For the large pot, MRI detected much more roots including some laterals than CT.

CONCLUSIONS

Both techniques performed equally well for pots with small diameters which are best suited to monitor root development of seedlings. To investigate specific root details or finely graduated root diameters of thin roots, CT was advantageous as it provided the higher spatial resolution. For larger pot diameters, MRI delivered higher fractions of the root systems than CT, most likely because of the strong root-to-soil contrast achievable by MRI. Since complementary information can be gathered with CT and MRI, a combination of the two modalities could open a whole range of additional possibilities like analysis of root system traits in different soil structures or under varying soil moisture.

Plant phenotyping: from bean weighing to image analysis

Plant phenotyping refers to a quantitative description of the plant's anatomical, ontogenetical, physiological and biochemical properties. Today, rapid developments are taking place in the field of non-destructive, image-analysis -based phenotyping that allow for a characterization of plant traits in high-throughput. During the last decade, 'the field of image-based phenotyping has broadened its focus from the initial characterization of single-plant traits in controlled conditions towards 'real-life' applications of robust field techniques in plant plots and canopies. An important component of successful phenotyping approaches is the holistic characterization of plant performance that can be achieved with several methodologies, ranging from multispectral image analyses via thermographical analyses to growth measurements, also taking root phenotypes into account.