Month: November 2022

The viewing surfaces were covered with opaque material to stop the light from affecting the development of the roots. The back viewing surface was removable, allowing homogeneous soil packing for the plant experiments and convenient access to the electrodes. Besides the top opening, the rhizotrons were waterproof to enable hydroponic experiments and controlled evapotranspiration conditions during the soil experiments and plant growth. All the experiments were performed in a growth chamber equipped with automatic growth lights and controlled temperature and humidity. The temperature varied with a day/night temperature regime of 25/20 °C. The humidity ranged from 45 to 60%. For both ERT and MALM methods, the electrical potential field is characterized by a set of potential differences measured between pairs of electrodes. It is important to properly arrange the electrodes on the rhizotron viewing surface and design a suitable acquisition sequence to obtain a good sensitivity coverage of the investigated system . This is particularly true for the iCSD, as both ERT and MALM acquisitions affect its result. The 64 electrodes were arranged in a 8 by 8 grid on the back viewing surface of the rhizotron, leaving the front surface clear for the observation . For the ERT, the designed arrangement of the electrodes offers a good compromise between a high coverage on the central part of the rhizotron, which encompasses the root zone,flood table and a sufficient coverage on the rhizotron sides to avoid an excessive ERT inversion smoothness. For the MALM, the arrangement of the electrodes is highly sensitive to the position of the investigated current sources. Because of their central positions, the electrodes are closer to the expected sources of current and thus in the region of maximum potential gradient. Hence, this electrode configuration maximizes the changes in both magnitude and sign of the measured ΔV associated with a change in the CSD distribution.

The electrode diameter was 1.5 mm. The penetration of the electrodes into the rhizotron was 4 mm ± 1 mm. To evaluate the possible distorting effects of the densely populated electrodes on the potential field distribution, a test was performed with low conductivity water . The test showed no resistivity anomalies, which may be caused by the presence of the electrodes . Therefore, while rhizotron setups with electrodes only on the sides were successfully adopted , we found that the current setup represents a better solution for iCSD experiments . Data were acquired with a MTP DAS-1 resistivity meter with 8 potential channels. For the ERT acquisition over the 2D grid of electrodes, we chose a dipole-dipole skip 2 configuration. For each skip 2-couple of injection electrodes the remaining skip-2 couples of electrodes were used as potential dipoles . The associated complete set of reciprocals was also acquired, the resulting acquisition sequence contained 3904 data points . Following the ERT data acquisition, the MALM data acquisition required little setup adjustments and time. As the two current electrodes are fixed, the use of a multichannel resistivity meter significantly reduced the acquisition time and, consequently, supported the acquisition of more robust data sets. Electrode 1 was used to inject the current into the plant stem, while electrode 64 was used as a return electrode in the growing medium . The remaining 62 electrodes were used to map the resulting potential field. A sequence with 204 ΔVs was used. Considering the grid in Fig. 2a, the sequence included the vertical, horizontal, and diagonal ΔVs between adjacent electrodes. While 61 ΔVs would provide all the independent differences, the 204 ΔV sequence was preferred because of its redundancy and consequent lower sensitivity to acquisition errors. The acquisition time remained relatively short as the multichannel instrument was optimized with fixed current electrodes that allowed 8 ΔVs to be measured at once.

The iCSD inversion that we developed was based on the physical principles of a bounded system in which linearity and charge conservation were applied to decompose the investigated CSD distribution into the sum of point current sources. This provided a discrete representation of the root system portions where the current leaks from the roots into the surrounding medium. Because of the linearity of the problem, the collective potential field from multiple current sources is the linear combination of their individual potential fields. As such, the measured ΔV can be viewed as and decomposed into the sum of multiple ΔVs from a set of possible current sources. These possible current sources are named ViRTual electrodes . As purely numerical electrodes, they are simulated by mesh nodes representing possible current sources, but with no direct correlation with the real electrodes used during data acquisition. Basically, the VRTe were distributed to represent a grid over which the true CSD distribution is discretized. In order to account for any possible CSD, a 2D grid of 306 VRTe was arranged to cover the entire rhizotron . The charge conservation law implies that the sum of the current fractions associated with the VRTe has to be equal to the overall injected current, which is provided by the resistivity meter. If we normalize the injected current to be equal to 1, the sum of the VRTe weights has to be 1 as well. Briefly, for Ohm’s law, normalizing the current to 1 is equivalent to calculating the resistance, R, from ΔV. Then, the use of R simplifies the presentation of the numerical problem. Once the VRTe nodes are added to the ERT-based ρmed structure, the potential field associated with each of the VRTes is simulated with BERT. From these simulated potential fields, the same sequence of 204 R is extracted, each corresponding to a single VRTe. Each extracted sequence contains the resistances that would be measured in the laboratory if all the current sources were concentrated at the VRTe point .Once the VRTe weights are estimated and associated with the respective VRTe coordinates, they provide a discrete visualization of the investigated CSD.The linear problem formulation is conducive to the inversion optimization during the calculation of the pareto front.

The calculation time of the Pareto front can be further reduced by code optimization as the calculations that do not depend on the regulation weights can separated from the inversion routine and performed only once during the initialization of the linear problem. The initialization phase includes the processing of the MALM experimental data, forward calculation of the VRTe responses for the given ρmed, inclusion of the continuity constraint, and construction of the matrices. Continuity constraint, bounded-value constraint, and first-order spatial regularization stabilize the inversion while limiting the impact of the spatial regularization strategy. The impact of the spatial regularization was evaluated by monitoring the relative components of the misfit and the resulting distribution of the current source. In both synthetic and laboratory tests, as well as in plant experiments the iCSD results are often limited to few current sources .Synthetic numerical and laboratory experimental tests were performed in order to evaluate the capabilities of the setup and inversion routine to couple the ERT and MALM approaches for the iCSD. In the numerical tests both the true source response and VRTe responses were calculated with BERT. Figure 3 shows an explanatory numerical test with inversion of a point source, and the associated Pareto front that was used to select the optimum regularization strength. As this first experiment was performed to specifically test the inversion routine, a homogeneous ρmed was used in order to avoid influence from the baseline resistivity distribution complexity. For the second experiment, the laboratory tests were conducted. Because of the ρmed heterogeneity of any experimental system, these laboratory tests need to include the ERT inversion,rolling bench and the use of the obtained ρmed as input in the iCSD. The true current sources were obtained using insulated metallic wires inserted into the rhizotron . The insulating plastic cover was removed at the tips of the metallic wires to obtain the desired current sources. Six experimental tests were performed using different numbers and positions of these current sources. The rhizotron was filled with tap water and left to equilibrate to achieve steady state conditions of water temperature and salinity, thus minimizing ρmed heterogeneity and changes during the experiment. Changes in ρmed during the ERT and MALM acquisition periods would make the ERT-based ρmed less accurate and compromise the iCSD. To make sure ρmed was stable, a second ERT was performed after the MALM acquisition and compared with the initial measurement. The conductivity of the solution was also measured in several locations of the rhizotron with a conductivity meter to validate the ρmed obtained from the ERT inversion. This setup allowed the acquisition of good quality data sets since less than 5% of the data were discharged during the data processing. Because of the controlled laboratory conditions, the ρmed obtained with the ERT was stable and consistent with the direct conductivity measurements. The quality of the ERT inversion was also confirmed by comparing the model responses with the acquired data . Similarly, the acquired iCSD data were plotted against the resistances calculated with the CSD distribution obtained from the iCSD. The tests also allowed a more informed definition of the VRTe grid. For our setup, a spacing of 3 cm provided a good compromise between resolution, stability, and duration of the iCSD routine. The 3-cm spacing also agrees with the ERT resolution, which would not support a higher iCSD resolution. Successive numerical tests were based on the 8- source laboratory tests shown in Fig. 4. These tests aimed to 1) link laboratory and numerical tests to evaluate the influence of the numerical iCSD routine and laboratory setup on the overall iCSD stability and resolution; 2) account for a more complex CSD, given by the 8 wire-tip sources that were used to simulate distal current pathways; and 3) account for possible ρmed heterogeneity. To address goals 1 and 2, the position of the 8 sources was replicated in the numerical tests and a test with homogeneous ρmed was included to simulate the water resistivity of the laboratory tests.

To address goal 3, heterogeneous ρmed were tested.In order to account for the heterogeneous ρmed the following modeling steps were carried out. First, a true ρmed was assigned to the mesh cells of the rhizotron ERT model. We included homogeneous, linear, and quadratic resistivity profiles in the y direction, see Fig. 5. Second, the ERT acquisition was simulated with the ERT laboratory sequence and 3% of Gaussian error, in line with reciprocal and stacking errors observed in the laboratory data sets. Third, the forwarded ERT data sets were inverted following the exact laboratory procedure. A refined and different mesh was used for forward and inverse problems to, respectively, increase the simulation accuracy and avoid the inverse crime . The ERT forward calculation was then repeated over the inverted ρmed. The obtained inverted responses were compared with the responses of the true models. As for ERT, we compared true and inverted MALM responses. First, the true response was simulated with the 8 current sources overt the true ρmed. Second, a MALM response was calculated over the inverted ρmed and inverted to obtained the inverted CSD. Third, the obtained inverted CSD was used to forward calculate the inverted MALM response over the inverted ρmed. True and inverted MALM responses were then compared.e performed hydroponic and soil experiments using maize and cotton plants. In all the plant experiments, the injection electrode was positioned in the plant stem at a height of 1 cm from the surface of the growth media. For the hydroponic experiments, the plants were first grown in columns with aerated nutrient solution . They were then moved to the rhizotron for the experiments. As in the metallic roots test, the rhizotron was filled 1 day before the experiment to reach stable and homogeneous temperature and salinity conditions. The plant was positioned at the center of the rhizotron with soft rubber supports. The plants were submerged at the same level as in the growing column to avoid discrepancies caused by the plant tissue adaptation to the submerged and aerated conditions, as discussed above with regard to the growing conditions. Consequently, the root crown was approximately 3 cm below the water surface. For the soil experiments, seedlings were grown directly in the rhizotron to avoid damaging the roots and altering the root-soil interface. The soil was prepared by mixing equal volumes of sandy and clay natural soils acquired from an agricultural study site run by U.C. Davis, CA .

Understanding these intricate rhizosphere relationships is vital in devising strategies to increase plant productivity and comprehend localized biogeochemical processes. In many rhizosphere studies, the use of pots and containers is predominant as it allows the plants to be cultivated under controlled conditions and at low cost. Compared to field studies, growth of plants in defined spaces also offers advantages in ease of handling, monitoring and sampling . Much of what we know of the rhizosphere microbiome has resulted from such pot-grown plants. However, since the rhizosphere and roots are still out of view in the soil, destructive sampling of the root is required prior to analysis. Destructive sampling may result in the loss of three-dimensional spatial information on rhizosphere processes over time, which is increasingly being recognized as a critical parameter. On the other hand, soil free techniques such as hydroponics and aeroponics can provide visual access to the rhizosphere circumventing the need for destructive sampling. Other alternatives are gel-based substrates which can maintain rhizosphere transparency as well as the 3D architecture of roots and have been applied successfully in high throughput imaging, phenotyping and trait mapping platforms . Nonetheless, the root phenotype and traits of plants grown under soil-free conditions are known to differ from those of soil-grown plants . These soil substitutes do not also accurately simulate the heterogeneous nature of soil aggregates, thus complicating extrapolations for field relevance. Sophisticated imaging approaches such as magnetic resonance imaging and X-ray computer tomography can be used to analyze root systems in the soil with minimal disturbance but they are low throughput,led grow lights expensive and may not be easily accessible . It is apparent that structural changes in design catered to solving specific challenges in the rhizosphere are indeed necessary. To overcome these challenges relating to the rhizosphere in soil, specialized plant growth chamber systems have been designed, and successful implementation has led to multiple variations of similar designs.

These specialized systems often have a visible rhizosphere which enables coupling with other technologies thereby increasing the breadth of experimental techniques applicable to the rhizosphere system. This review discusses representative growth chamber systems designed to study major rhizosphere processes and interactions in soil. Growth platforms resembling conventional containers such as pots and tubes are not covered. specifically, the reviewed growth systems are selected based on the following criteria: the growth chamber is amenable for use with soil/soil-like substrates and therefore, hydroponics, aeroponics and agar/gel-based systems are not discussed except in microfluidic-based platforms, it is built with the intention to maintain growth of the plant and has architectural features distinct from conventional pots, and lastly it is able to be set up in a laboratory; i.e., field measurement systems and observation platforms are not included. For instance, a minirhizotron, consisting of a camera mounted in a glass tube submerged in the soil which provides non-destructive root imaging over time will not be discussed as it is out of the scope of this review. Through our assessment of lab-based chamber systems, we identify unique advantages and challenges associated with each system . We hope that future fabrication designs can benefit and improve on designs that work well. Lastly, we offer our perspectives on areas in which technological advances are needed to fill current knowledge gaps.In studying rhizosphere processes, the myriad of complex interactions among members of the rhizosphere are often dissected to two interacting variables such as root-and-soil or root-and-microbes, etc. Each of these interactions inherently operates under distinct parameters and requires specifically designed platforms to effectively answer different research questions. This review is structured in a way that first describes each rhizosphere process briefly and then reports on the specific growth chamber systems designed to facilitate experiments for answering related research questions.

The major rhizosphere processes discussed below include root system architecture, physicochemical gradients in the soil, exudation patterns by the roots and interactions between roots and nematodes, fungi or bacteria. Root system architecture encompasses structural features that provide spatial configuration such as root length, width, spread and number and is an important rhizosphere parameter in regulating soil porosity, and nutrient and water uptake efficiency by plants . Plants have been observed to “sense” and direct root growth toward nutrient sources in soil, and the RSA of a plant exhibits great malleability in response to environmental stimuli which in turn, influences microbial communities . For instance, bean plants grew deeper roots under drought conditions to enhance water foraging capabilities while low phosphate conditions stimulated the formation of dense lateral roots involved in P uptake from upper soil layers . Given that most soils are heterogenous, understanding the RSA of plants becomes critical in improving resource use efficiency and agricultural yields . Often, RSA in pot-grown plants is investigated by excising the roots via mechanical means such as root washing or blowing with compressed air . These methods are, however, time-consuming, cause inevitable damage of fine root hairs and result in loss of spatial and temporal information . An appealing alternative for studying RSA is the use of rhizotrons. Rhizotrons were initially constructed as underground facilities designed for viewing and measuring roots in the field . In the lab, the rhizotron implies a chamber constructed using two vertical sheets with at least one or both of the sheets being transparent and/or removable . This allows repeated visual inspections of individual roots; a feature unachievable with destructive sampling. In some cases, the word “rhizobox” is used for a similar set up although this was first introduced in as compartmentalized systems to separate the root and soil compartments . Rhizotrons/rhizoboxes are often constructed with PVC or acrylic materials and come in many sizes to accommodate different plants with soil or soil-less substrates .

Root growth and morphology in the rhizotron can be tracked by a variety of methods ranging from manual tracing onto a plastic sheet, using handheld or flatbed scanners to fully automated time-lapse imaging camera systems .Data can be subsequently analyzed with a wide range of software packages . Affordable and robust RSA imaging platforms using rhizotrons have also been developed for increased accessibility in low-income countries . The versatile construction of a rhizotron design for RSA studies has inspired many variations. For instance, ara-rhizotrons were designed to enable the study of 3D canopy competition with simultaneous root growth observation in an Arabidopsis plant population . The horizontal and radial design of HorhizotronTM and mini-Horhizotron consisting of transparent quadrants attached to a central chamber were developed to study lateral growth of roots in a semi-3D space and to perform post-transplant assessment . The separated quadrants can also be used with different soil substrates simultaneously to study substrate effects on root growth . A rhizotron fitted with water-tight gasket seals has also been used successfully to investigate the RSA of plants under water-logged conditions . Despite the continuous real-time visual read-out, most rhizotron designs suffer from inevitable loss of information from roots occluded by soil particles. The GLO-Roots system overcomes this by imaging from both sides of the rhizotron while using bioluminescent roots to create higher contrast against the soil, enabling quantitative studies on RSA . Following advances in engineering and device fabrication, more rhizotron variants adapted to specific plant growth conditions can be envisioned. In a typical topsoil, approximately half is composed of solid minerals and organic matter while the rest is a fluctuating composition of water and gas filled spaces influenced by environmental conditions and uptake/release of solutes from plants . Changes in gaseous and hydrologic parameters, such as ions, O2 and moisture among others, create a spatially complex environment that influences microbial communities and overall plant health. These physicochemical fluxes are heterogeneously distributed along roots and vary with root types and zones . Often, they exist as gradients in the rhizosphere , thus emphasizing the need for non-destructive sampling in order to accurately capture processes occurring at biologically relevant times and scales. Rhizotron chambers with a visually accessible rhizosphere allows in situ and continuous mapping of these gradients in the soil through the use of different types of imaging methods. For instance, photo luminescence-based optical sensors enable in situ,vertical grow system repeated detection of small molecule analytes in addition to pH , O2 and NH4 . Methods like zymography to detect enzyme activity and diffusive gradients in thin film can be used to map solute concentrations in the soil down to sub-mm scales with high spatial resolution more realistically than traditional destructive approaches.

For example, transport and distribution of water in the rhizosphere soil has been imaged on both 2D and 3D planes by coupling a rhizotron with neutron radiography and tomography, respectively and showed varying moisture gradients along the root system with higher water uptake at the rhizosphere compared to bulk soil. On the other hand, if the rhizotron slabs are thin enough , even simple imaging solutions based on light transmission can be set up to capture water uptake by roots in sand . Despite trade-offs in method sensitivity between these two studies, a rhizotron set up is critical in both designs and illustrates its adaptability to multiple equipment.Roots exude a substantial amount of photosynthetically fixed organic carbon into the soil consisting of a wide variety of compounds such as sugars, organic acids, and primary and secondary metabolites . Together with mucilage and border cells , root exudates provide a major source of nutrients for the rhizosphere microbiome . Root exudation is regulated under genetic control as well as in response to environmental conditions in the soil such as nutrient limitations or increase in toxicity.As a central player in the rhizosphere ecosystem, it is imperative to understand root exudation patterns to unravel subsequent impacts to the surrounding soil and microbial community. Improvements in analytical instrumentation have made it possible to move from targeted to untargeted explorations with mass spectrometry to create root exudate fingerprints in its entire complexity . Regardless, the impact of such techniques relies partly on our exudate sampling techniques. Detection of exudates in real-time is difficult due to rapid biotransformation and sorption to the soil matrix. As such, common collection methods rely on root washing in hydroponic systems to overcome complications in the soil matrix and preserve native exudation profiles. However, a comparison between a soil-based collection method and hydroponic methods showed varied responses particularly in amino acid exudation although the underlying cause was not elucidated . It is possible that the differing growth conditions between hydroponics and soil, which include differences in gas concentrations, mechanical impedance and microbial spatial composition, can elicit differing root exudation responses to the same environmental stimuli. Rhizoboxes offer the advantage of localized sampling in soil using sorption media such as paper and membrane filters, compound specific ion exchange binding resin or micro-suction cups placed closed to root zones of interest to collect exudates . Moreover, in a rhizobox fitted at the bottom with a porous root impenetrable membrane, a root mat is allowed to be formed which is then further transferred onto a collection compartment . The collection compartment containing soil could then be cut into thin slices parallel to the membrane to represent differing distances from the rhizosphere . While this approach can be used to investigate exudate release and sorption under soil conditions, the root mat growth generalizes exudate production in terms of the whole root system and occludes spatial exudation patterns. In a hybrid set up by Oburger et al. , the rhizobox is transplanted to a second specialized rhizobox for continued vertical root growth. This specialized rhizobox consists of a nylon membrane close to the transparent side to restrict root growth into the soil except for root hairs . This creates a vertical flat root mat onto which localized exudate samples can be collected. A comparison of this novel set up to conventional collection methods showed that amino acid exudation rates were most varied among the different methods , further highlighting the need for specialized chambers. Nonetheless, successful implementation of these chambers is still limited to fast-growing plants which can form active root mats. The high density of root mats could also lead to unnatural root exudate levels and an overestimation of rhizosphere effects. In addition, care has to be given to the choice of membrane as selective sorption of certain root exudates onto the membrane may also occur .

Previous studies reported photolysis half-lives of 10-20 days in soil surface under continuous UV radiation . Under field conditions however, there won’t be continuous exposure to sunlight, and photolytic degradation will probably be much slower than reported values, especially in winter months. Another factor that potentially affected the observed degradation rates was pesticide exposure histories at the study sites. According to data from the California Department of Pesticide Regulation , the Hospital Creek watershed had a higher use of chlorpyrifos than the other study sites and chlorpyrifos use in this watershed consistently increased between 2007 to 2010 . Although the SJRNWR site is downstream, at the confluence of Hospital Creek and Ingram Creek, it is less susceptible to chlorpyrifos exposure because the compound is deposited to sediments upstream. When soils are repeatedly exposed to chlorpyrifos, some microorganisms may gain an enhanced capability to degrade the compound, a phenomenon called enhanced biodegradation . For example, Singh et al. observed rapid degradation of both chlorpyrifos and the transformation product TCP in an Australian soil collected from a site where chlorpyrifos had been used continuously for more than 14 years. It has also been reported in some other studies, however,hydroponic dutch buckets that chlorpyrifos was resistant to enhanced biodegradation . Additional research is needed to assess the differences in microbial communities among the study sites and their link to the pesticide exposure history. The functionality of the study sites as riparian buffers was assessed using the California Rapid Assessment Method for Wetlands . Results of the CRAM analysis indicate that these riparian areas range from very low functionality , to high functionality.

The finding of higher chlorpyrifos degradation capacity of sites with low functionality may be related to the fact that healthy wetlands often contain large areas of anaerobic sediments that may not be conducive to microbial communities that rapidly degrade chlorpyrifos. As a result, strategies intended to increase wetland functionality alone may not be conducive to pesticide degradation. The hydrolysis of the P-O linkage of organophosphate insecticides is catalyzed by phosphotriesterase , a zinc metalloenzyme capable of hydrolyzing organophosphate compounds including agricultural pesticides and chemical warfare agents . This enzyme reportedly has been responsible for the biodegradation of organophosphate insecticides in previous studies. Phosphomonoesterase and phosphodiesterase enzymes were involved in chlorpyrifos mineralization making phosphorus available for uptake by microorganisms . To investigate the relationship between different types of phosphoesterase enzymes and observed chlorpyrifos degradation rates, enzyme activities were measured and compared to the biodegradation rates. A positive correlation between PTE enzyme activities and chlorpyrifos degradation rates was observed, however, the relationship differed for each site . These results suggest that the PTE enzyme assay may be useful as a tool for assessing temporal variations at individual sites after PTE enzyme activities are calibrated to the site-specific degradation rates. No correlation was observed between chlorpyrifos degradation rates and phosphomonoesterase and phosphodiesterase activities .The engineering module simulates the hydrology and water quality for the landscape of a river basin. A river basin has tributary lands, rivers, and reservoirs. To capture the spatial variations within a river basin, the WARMF model divides the basin into a hydrologic network of land catchments, stream segments, and lake layers.

Physical dimensions of the hydrologic components are prescribed by digital elevation map data, which can be downloaded from the website of US Geological Survey . By selecting a specific land catchment, stream segment, or reservoir on the basin map, dialog boxes for physical, chemical, and biological characteristics of a location can be displayed with the description of variable names and their units. Values for model coefficients can be modified by the user during model calibration. The model allows the user to include atmospheric deposition from precipitation and dry dust, point source discharges and fertilizers applied to farm lands. Hydrology, non-point load and water quality are simulated in all sections of the waterway. Simulated parameters include flow, water depth, and an array of water quality parameters including pH, temperature, dissolved oxygen, ammonia, nitrate, phosphate, suspended sediments, fecal coliforms, major cations and anions, and pesticides. The time step of simulations is typically one day. The model’s database contains default input data and data to evaluate simulation results. The model also uses input including digital elevation maps, land use, fertilizer application, air quality, meteorology, and point source discharges. A variety of model outputs are automatically saved for graphical, tabular or GIS displays. The sub-models embedded in WARMF are adapted from many well established algorithms, such as sediment erosion and pollutant transport algorithms in ANSWERS , and pollutant accumulation and wash off algorithms in SWMM .To simulate the dynamics of a river basin, WARMF uses a number of time series data sets in modeling. Meteorology, air quality, precipitation quality, point source discharge, and reservoir flow release data are used to drive the model. Hydrology and water quality data are used to check model results. The data module allows users to review the input data sets and make changes. The time series data sets are stored in ASCII text files, one file per monitoring station . Each row of a data file contains a date and a series of numerical values for monitored parameters in separate columns. As a part of continuous planning process, new data may be collected after the planning is completed.

When there is a need to extend the time period of old data sets to include the new data, the data module allows users to enter new data as they become available. The knowledge module can include reservoir operation rules, water quality standards, rate coefficients, and other items. The reservoir operation rules are replaced by an input file that contains the specified flow releases from various outlets. Water quality standards are included in the water quality criteria for various designated uses. The knowledge module can be used to store files used to process input data for a site-specific application, spreadsheets used to calculate the cost of best management practices, references, applicable laws, and relevant case studies.Consensus and TMDL modules are road maps that provide guidance for stakeholders during the decision-making process. Through the TMDL Module, calculations are made for a series of control points throughout the river basin. A road map is provided for the step-by-step procedure. An iterative set of simulations is performed to calculate various combinations of point and non-point loads that the water body can accept and meet the water quality criteria of the designated uses. The water quality criteria can be specified for multiple parameters and based on percent compliance. The consensus module is an application tool embedded in WARMF. The purpose of the module is to guide stakeholders to a general agreement on a watershed management plan. It relies on the engineering models to furnish technical information for stakeholders to make decisions.The San Joaquin River Model Interface is a WARMF version developed to simulate the San Joaquin River and its watershed . The section of the San Joaquin River within the watershed was divided into 93 river segments. The irrigated lands were divided into 17 land catchments. The model simulates natural storm water runoff, irrigation return flow, groundwater table of land catchments, and groundwater lateral flow from land catchments to the receiving river segments. There are gauge stations that provide measured inflows as inputs to the model. For example, there are three gauges for the three major east-side tributaries . For the agricultural lands, the model inputs includes daily diversions, locations of diversions, and areas upon which the irrigation water was applied. Based on the locations of diversions, the model uses the water quality of the source water when applying that water for irrigation.The model simulates the hydrological processes of snow pack accumulation, snow melt, canopy interception, through fall, evaporation and transpiration, infiltration, percolation, groundwater lateral flow, and surface runoff. These processes are simulated based on water balance and physics of flow . Precipitation and irrigation water can percolate into the soil. Within the soil, water increases the moisture level in each soil layer. After the field capacity is exceeded, water percolates down to the water table,bato bucket where it flows laterally out of the land catchment according to Darcy’s Law. Water on the soil or within the soil is subject to evapotranspiration, which is calculated based on temperature, humidity, and season. The amount of water entering and leaving each soil layer is tracked by the model. If the amount of water entering the soil layer is greater than the amount leaving the soil layer, the water table rises. If the water table reaches the surface, the soil is saturated and overland flow occurs, which is calculated by Manning’s equation . Rivers accept the subsurface and overland flow from linked catchments. They also receive point source discharges and flow from upstream river segments. Diversion flows are removed from river segments. The remaining water in the river is routed downstream using the kinematic wave algorithm. The channel geometry, Manning’s roughness coefficient, and bed slope are used to calculate depth, velocity, and flow. The velocity is a measure of the travel time down the river, which in turn affects the water quality simulation.The fundamental principle which guides the model’s simulation of water quality is heat and mass balance. Heat is transferred to the soil via precipitation and irrigation. Heat exchange occurs between catchments and the atmosphere based on the thermal conductivity of the soil. Temperature is then calculated by heat balance throughout the model. There are various ways by which chemical constituents can enter the model domain.

They can enter the land surface via irrigation water, land application, atmospheric deposition or point source discharge. Chemical species move with water by percolation between soil layers, groundwater lateral flow to rivers, and surface runoff. Each soil layer is modeled as a completely mixed reactor, as is the land surface within each land use . Competitive cation exchange between the major cations are simulated on the available soil exchange sites. Anions and optional metals partition between dissolved and adsorbed phases in the soil based on an adsorption isotherm. Nutrient cycling between soil and vegetation is simulated for each land use. The model simulates the soil erosion of sand, clay, and silts from the land surface, and sedimentation and resuspension of particles in streams. A dynamic equilibrium is maintained between dissolved and adsorbed phases of each ion. The dissolved oxygen concentration is tracked during the simulations, and anoxic reactions take place as DO is depleted. When overland flow takes place, sediment is eroded from the catchment surface according to the modified universal soil loss equation. Adsorbed ions are carried on soil particles to the river. Each river segment is modeled as a completely mixed reactor. Sediment can settle into the river bed and is scoured from the river bed when velocity is high enough. Chemical reactions take place in the canopy, soil surface, soil layers, and surface waters. Reaction rates are based on first-order decay with reaction-specific rates. .The model requires six categories of input data: geometric dimensions of land catchments and river segments and their elevations, soil characteristics of the watersheds, model coefficients, land uses, meteorological conditions, and operating conditions. The first 4 categories of data are time invariant variables, which remain constant during the model simulation. Their input values are set only once during model setup. The model coefficients include reaction rates and their temperature correction factors. The model allows for land use changes, which can occur once every few years. In that case, the model uses a “warm start” procedure to run the simulation in sequence. In this procedure, the model uses a set of land use data to perform a simulation for a period of a few years. It saves the results at the end of the simulation and uses them as the initial condition to start the simulation for the next few years with the new land use data. The last two categories of data vary with time. These are sometimes referred to as “driving variables” . The meteorology affects the annual and seasonal variations of hydrology and water quality . The operating conditions include human activities such as fertilizer applications, reservoir releases, diversions, irrigation and waste discharges, which can be modified by management alternatives to improve water quality.

The translocation of the short arm of rye chromosome 1 from the cultivar Petkus into the long arm of wheat chromosome 1B confers improved tolerance to several abiotic and biotic stresses. Although several genes for resistance to biotic stresses are no longer effective, the1RS.1BL translocation is still widely used because of its beneficial effects on grain yield and improved abiotic stress tolerance . We have previously shown that the presence of a short segment of wheat 1BS chromosome from cultivar Pavon in the distal region of the 1RS translocation was associated with reduced grain yield, biomass, and canopy water status relative to near-isogenic lines carrying the complete 1RS chromosome arm . Carbon isotope discrimination data showed that the lines with the complete 1RS chromosome arm achieve higher yields and better water status through increased access to water throughout the season, rather than through water conservation . A subsequent field study showed that the improved water status of the isogenic lines with the 1RS chromosome was associated with enhanced root density below 20 cm relative to the lines with the 1RSRW chromosome . Changes in root architecture in the field were correlated with drastic changes in root development in hydroponic growth systems, where the 1RSRW line showed a regulated arrest of the seminal root apical meristem ∼2 wk after germination. By the same time, the 1RSRW plants displayed altered gradients of reactive oxygen species in the root tips and emergence of lateral roots close to the RAM . In this study, we performed exome captures for 1RS, 1RSRW, ebb flow tray and its parental lines T-9 and 1B+40 . We show that, as a result of a distal inversion between 1RS and 1BS chromosome arms, T-9 and 1B+40 have duplicated 1BS and 1RS orthologous regions in opposite orientations and that a crossover between these chromosomes resulted in a duplicated 1RS region colinear to the inserted 1BS segment in 1RSRW.

Using these genetic stocks, we demonstrate that the dosage of the genes in the duplicated region plays an important role in the regulation of the seminal root growth. We also describe a radiation mutant with a deletion in the inserted 1BS segment and the adjacent 1RS region that restored long roots, confirming the importance of the dosage of the genes in this region on root development. Finally, we identified 38 genes within this deletion and used published RNA-sequencing data and annotation to discuss their potential as candidates for the genes regulating seminal root elongation in wheat.The genetic stocks including the 1RS and 1RSRW chromosome arms were initially generated in the cultivar Pavon 76 , a spring wheat developed at the International Maize and Wheat Improvement Center . The 1RS chromosome arm translocation in Pavon was introgressed from the CIMMYT cultivar Genaro, which, in turn, received the translocation from the cultivar Kavkaz . The donor of the 1RS arm in Kavkaz was the rye cultivar Petkus, one of the leading rye cultivars in the 20th century.To name the different chromosome constitutions we used two superscripts, with the first superscript indicating the proximal position and the second superscript the distal position. The 1RSRW chromosome arm was generated by homologous crossover in overlapping wheat segments of the primary 1BS–1RS recombinant T-9, which possessed a distal wheat 1BS segment, and 1B+40, which possessed a distal 1RS segment . The 1RSWR arm was generated by a crossover in overlapping wheat segments in primary 1BS–1RS recombinants T-38, which possessed a large distal wheat 1BS segment, and 1B+44, which possessed a long distal 1RS segment . The 1RSWW chromosome was generated by a crossover between 1RSRW and 1RSWR chromosomes and was designated as chromosome MA1 in Lukaszewski . The lines carrying the 1RSRW, 1RSWR, and 1RSWW chromosomes were previously back crossed into the CIMMYT common wheat cultivar Hahn, which has the 1RS.1BL translocation, with 1RS also originating from cultivar Kavkaz, the same as in Pavon-1RS.

The introgressions involved six marker-assisted back crosses, resulting in near-isogenic lines that were deposited in the National Small Grains Collection as accessions PI 672839 , PI 672838 , and PI 672837 . We have previously shown that the 1RSRW chromosome results in short roots in the Hahn background but not in the Pavon background. Therefore, to analyze the effects of different 1RS/1BS recombinant chromosomes on root length, we back crossed primary recombinants with varying lengths of wheat and rye segments—T-9, T-18, T-21, and 1B+40 —four times into Hahn. Line T-21 is identical to T-9 and line T-18 carries a large distal 1BS segment on its 1RS arm and was used as 1BS reference in the calculation of ratios for copy number determination. Line 1B+37, which carries a large distal 1RS segment on its 1BS arm , was used as 1RS reference in the exome capture comparisons but was not used in the hydroponic experiments.To dissect the chromosome region affecting root length, we irradiated 5,000 wheat F2 seeds from the cross between Hahn × Hahn-1RSWW with 300 Gy . This mutant population was established in 1RSWW before we knew which wheat segment was affecting root length. The objective of mutagenizing F2 plants rather than homozygous plants was to detect deletion mutants in the heterozygous plants of the first generation without having to wait for progeny tests. We extracted DNA from the 2,200 mutagenized plants that survived and used a dominant wheat marker and a dominant rye molecular marker to eliminate plants that were homozygous for the 1RS or 1BS segments. We identified 907 plants that were heterozygous for the proximal segment, of which, we expected the majority to also be heterozygous for the distal 1BS segment. We then screened the selected plants with multiple markers for the distal 1BS insertion and identified one mutant . From the progeny of this plant, we selected two sister homozygous plants, designated hereafter as 1RSWW-del-8 and 1RSWW-del-10. We then back crossed these two deletions independently to Hahn-1RSRW and to Hahn four times to reduce background mutations and to test the effect of the deletion on the root length in both backgrounds. Although the two lines carry the same deletion, independent back crosses increase chances of eliminating different background mutations, and they served as biological replicates in the root length experiments.We performed two exome capture experiments using different platforms. In the wheat exome capture using the assay developed by Arbor Bio-sciences, we included lines T-9, T- 18, T-21, 1B+37, 1B+40, and 1RSRW ethyl methanesulfonate mutant lines RW_M4_43_11 and RW_M4_47_12 . In the wheat exome capture using the assay developed by NimbleGen , we included lines 1RS, 1RSRW, and deletion lines 1RSWW-del-8 and 1RSWW-del-10. Based on the average similarity between the wheat and rye genes and the hybridization conditions used in the capture, we expect most of the rye genes to be captured with both wheat exome capture assays. The exome captures were sequenced using the Illumina platform and 150 bp paired-end reads at the University of California, Genome Center.

The sequencing reads were preprocessed to trim adapters with Trimmomatic v0.39 . Since the capture included both wheat and rye reads, we mapped the reads to a combined reference including wheat Chinese Spring RefSeq v1.0 chromosome 1B and the rye chromosome arm 1RSAK58 from the 1RS.1BL translocation in cultivar Aikang58 . To minimize off-target mapping, we mapped the reads at high-stringency with ‘bwa aln’ v0.7.16a-r1181 , allowing only perfectly mapped reads . Alignments were sorted by using samtools v1.7 , and duplicate reads were removed with Picard tools v2.7.1 . We normalized the number of mapped reads so that all lines have the same total number of reads mapped to the chromosome arm 1BL. We selected the 1BL arm as reference because 1RS/1BS recombinant lines differ in their short arm constitutions, but all share identical 1BL arms. We then calculated normalized read number ratios using a common reference line . We generated heat maps for these ratios and visually determined the borders of duplication, recombination, and deletion events. We then validated these borders using t tests of the ratios at both sides of the border . For these analyses we excluded genes with less than six reads in the accessions used as denominator for normalization. We report wheat gene coordinates using CS RefSeq v1.1 and rye gene coordinates using the 1RSAK58 genome as references , which is almost identical to our 1RS sequence. The other available genome reference for rye inbred line Lo7 is less similar to the 1RS sequences from Hahn 1RS.1BL translocation.Hydroponic experiments were performed in growth chambers at 22–23 ˚C with a photoperiod of 16 h light vs. 8 h dark . In all experiments, grains were imbibed at 4 ˚C for 4 d and then placed at room temperature. Once the coleoptiles emerged, seedlings were floated on a mesh to develop roots for 4 d. After removing the grain, seedlings were wrapped at the crown with foam and inserted in holes precut in a foam core board placed on top of the solution. The detail protocols and solutions are described in our previous paper . As in our previous study,flood and drain tray experiments in this study were performed in two different laboratories in Argentina and the United States using tanks of 0.35 and 13 L, respectively. As a result of the different conditions, final root lengths differed across experiments. However, differences among genotypes were consistent across experiments, and all statistical comparisons among genotypes were performed within experiment or using experiments as blocks. In experiments performed in 13-L tanks, we changed nutrient solution every 3 d and we included all genotypes in each tank. When necessary, we used multiple tanks as blocks. In experiments performed in 0.35- L tanks, we changed nutrient solution every 2 d, and a single genotype was included per pot, with multiple pots used as replications. To determine the effect of the 1RSWW-del-8 and 1RSWW-del-10 deletions on root development, we evaluated the segregating plants in the BC2F2 and BC4F2 generations to account for potential random effects of residual deletions in other chromosomes.To define the borders of the inserted 1BS region, we used the Arbor Biosciences exome capture to characterize the 1RSRW line and its two parental lines 1B+40 and T-9 .

We also included line T- 21 that appears to be identical to T-9 , line T-18 that has a distal 1BS segment longer than T-9/T-21 and was used as a wheat reference, and line 1B+37 that has a longer distal 1RS segment than 1B+40 and was used as a rye reference. We mapped the reads of each capture to a combined reference without allowing any SNP and then normalized the counts to a similar number of mapped reads per capture in the 1BL arm.The recent sequencing of the 1RS arm revealed the presence of a large inversion between the distal region of chromosome arms 1RS and 1BS , which suggests that lines with breakpoints within this region, such as T-9, T-21 and 1B+40, may be more complex than originally thought. The 1RSRW line was generated by a crossover of the primary recombinant lines T-9 and 1B+40 , and the previous results indicate that 1RSRW has retained the 1RS-1BS breakpoints of T-9 and 1B+40 . The 1RSRW chromosome arm also has the same strong telomeric C-band as 1RS and 1B+40, indicating that it has retained the complete 1RS segment present in 1B+40 . We initially assumed that the 1BS segment in 1RSRW replaced the orthologous rye genes and that the loss of these genes could be responsible for the shorter roots of Hahn- 1RSRW. However, the codominant marker THdw11 has both the 1RS and 1BS bands in T-9, 1B+40, and 1RSRW but not in T-18 or 1B+37 , suggesting a duplication rather than a replacement in the lines with distal crossover events. To investigate the extent of this duplication, we first identified 14 orthologous 1BS-1RS gene pairs including high-confidence wheat genes located within the 1BS insertion and rye 1RSAK58 genes that were at least 90% identical with an aligned region covering >90% of the gene . Surprisingly, all 14 ryeorthologues were present in the exome capture of T-9, 1B+40, and 1RSRW , which indicated that the complete rye region orthologous to the 1BS insertion was present in these lines. Since no 1RS gene was missing in the 1BS orthologous region, we rejected the hypothesis that lost rye genes were responsible for the differences in root length between Hahn- 1RS and Hahn-1RSRW isogenic lines.

Plants have evolved a powerful immune system to resist their potential colonization by microbial pathogens and parasites. Over the past decade, it has become increasingly clear that this innate immunity is, in essence, composed of two interconnected branches, termed PAMP-triggered immunity and effector-triggered immunity. PTI is triggered by recognition of pathogen- or microbial-associated molecular patterns , which are conserved molecular signatures decorating many classes of microbes, including non-pathogens. Perception of MAMPs by pattern recognition receptorsat the cell surface activates a battery of host defense responses leading to a basal level of resistance. As a result of the evolutionary arms-race between plants and their intruders, many microbial pathogens acquired the ability to dodge PTI-based host surveillance via secretion of effector molecules that intercept MAMP triggered defense signals. In turn, plants have adapted to produce cognate R- proteins by which they recognize, either directly or indirectly, these pathogen specific effector proteins, resulting in a superimposed layer of defense variably termed effector-triggered immunity , gene-for-gene resistance or R-gene-dependent resistance. In many cases, effector recognition culminates in the programmed suicide of a limited number of challenged host cells, clearly delimited from the surrounding healthy tissue. This hypersensitive responseis thought to benefit the plant by restricting pathogen access to water and nutrients and is correlated with an integrated set of physiological and metabolic alterations that are instrumental in impeding further pathogen ingress, among which a burst of oxidative metabolism leading to the massive generation of reactive oxygen species. Apart from local immune responses, ETI-associated HR formation also mounts a long-distance immune response termed systemic acquired resistance , in which naïve tissues become resistant to a broad spectrum of otherwise virulent pathogens.

It should be noted, however, that PTI, when activated by PAMPs that activate the SA signaling pathway,ebb and flow bench can trigger SAR as well. An archetypal inducible plant defense response, SAR requires endogenous accumulation of the signal molecule salicylic acidand is marked by the transcriptional reprogramming of a battery of SA-inducible genes encoding pathogenesis-related proteins. By contrast, there is ample evidence for induced disease resistance conditioned by molecules other than SA, as illustrated by rhizobacteria-mediated induced systemic resistance [ISR; [9]]. ISR, which delivers systemic protection without the customary pathogenesis-related protein induction, is a resistance activated upon root colonization by specific strains of plant growth-promoting rhizobacteria. In a series of seminal studies using the reference strain Pseudomonas fluorescens WCS417r, Pieterse and associates demonstrated that, at least in Arabidopsis, ISR functions independently of SA, but requires components of the jasmonic acidand ethylene response pathways. Even though colonization of the roots by ISR-triggering bacteria leads to a heightened level of resistance against a diverse set of intruders, often no defense mechanisms are activated in above ground plant tissues upon perception of the resistance-inducing signal. Rather, these tissues are sensitized to express basal defense responses faster and/or more strongly in response to pathogen attack, a phenomenon known as priming. As demonstrated recently, priming of the plant’s innate immune system confers broad-spectrum resistance with minimal impact on seed set and plant growth. Hence, priming offers a cost-efficient resistance strategy, enabling the plant to react more effectively to any invader encountered by boosting infection-induced cellular defense responses. In contrast to the overwhelming amount of information on inducible defenses in dicotyledonous plant species, our understanding of the molecular mechanisms underpinning induced disease resistance in rice and other cereals is still in its infancy.

Evidence demonstrating that central components of the induced resistance circuitry, including the master regulatory protein NPR1, are conserved in rice has only recently been presented. Moreover, reports on SAR-like phenomena in rice are scarce. Most tellingly in this regard, a 17- year-old report of systemically enhanced resistance against the rice blast pathogen M. oryzae triggered by a localized infection with the non-rice pathogen P. syringae pv. syringae remains one of the most compelling examples of a SAR-like response in rice to date. In contrast, there is a sizeable body of evidence demonstrating systemic protection against various rice pathogens resulting from ISR elicited by, amongst others, Pseudomonas, Bacillus and Serratia strains. However, in most if not all cases, still very little is known about the basic mechanisms governing this ISR response. In a previous report, we demonstrated that rice plants of which the roots were colonized by the fluorescent pseudomonad P. aeruginosa 7NSK2 developed an enhanced defensive capacity against infection with M. oryzae. Bacterial mutant analysis revealed that this 7NSK2-mediated ISR is based on secretion of the redox-active pigment pyocyanin. Perception of pyocyanin by the plant roots was shown to cue the formation of reiterative micro-oxidative bursts in naïve leaves, thereby priming these leaves for accelerated expression of HR-like cell death upon pathogen attack. Aiming to gain further insight into themolecular mechanisms underpinning rhizobacteria-modulated ISR in rice, we tested the ability of the biocontrol agent Serratia plymuthica IC1270 to induce systemic resistance against various rice pathogens with different modes of infection. Originally isolated from the rhizosphere of grapes,S. plymuthica IC1270 is a well-characterized PGPR strain producing a broad palette of antimicrobial compounds. In addition to its potential as a direct antagonist of a wide array of plant pathogens, preliminary experiments in bean and tomato revealed that IC1270 is equally capable of reducing disease through activation of a plant-mediated defense response. Here, we demonstrate that colonization of rice roots by IC1270 renders foliar tissues more resistant to M. oryzae.

Using a combined cytological and pharmacological approach, evidence is provided that IC1270 locks plants into a pathogen-inducible program of boosted ROS formation, culminating in the prompt execution of HR cell death at sites of attempted pathogen entry. Similar, yet even more pronounced, phenotypes of hypersensitively dying cells in the vicinity of fungal hyphae were observed in a genetically incompatible rice-M. oryzae interaction, suggesting that IC1270-mediated ISR and R-gene-mediated ETI involve similar defense mechanisms. Bacterial strains used in this study were Serratia plymuthica IC1270, which was originally described as Enterobacter agglomerans, and Pseudomonas aeruginosa 7NSK2. For inoculation experiments, IC1270 and 7NSK2 were grown on iron-limiting King’s B medium [KB; [34]] for 24 h at 28°C and 37°C, respectively. Bacterial cells were scraped off the plates and suspended in sterile saline . Densities of the bacterial suspensions were adjusted to the desired concentration based on their optical density at 620 nm. Magnaporthe oryzae isolate VT7, a field isolate from rice in Vietnam, was grown at 28°C on half-strength oatmeal agar . Seven-day-old mycelium was flattened onto the medium using a sterile spoon and exposed to blue light for seven days to induce sporulation. Conidia were harvested as described in De Vleesschauwer et al., and inoculum concentration was adjusted to a final density of 1 × 104 spores ml-1 in 0.5% gelatin .Rhizoctonia solani isolate MAN-86, belonging to anastomosis group AG-1 IA, was maintained on potato dextrose agar . Inoculum was obtained according to Rodrigues et al. with minor modifications. After autoclaving, 15 toothpicks, 1 cm in length, and five agar plugs , obtained from the margin of an actively growing colony of R. solani, were transferred to PDA plates. These plates were then incubated for 8 days at 28°C so R. solani could colonize the toothpicks. Cochliobolus miyabeanus strain 988, obtained from diseased rice in field plots at the International Rice Research Institute , was grown for sporulation at 28°C on PDA. Seven-day-old mycelium was flattened onto the medium using a sterile spoon and exposed to blue light for three days under the same conditions mentioned above. Upon sporulation, conidia were harvested exactly as stated in Thuan et al. and re-suspended in 0.5% gelatin to a final density of 1 × 104 conidia ml-1.Four-week-old rice seedlings were challenge inoculated with Magnaporthe oryzae as described in De Vleesschauwer et al.. Six days after inoculation, disease severity on the fourth leaves of each plant was rated by counting the number of elliptical to round-shaped lesions with a sporulating gray center, and expressed relative to non-induced control plants. R. solani bioassays were performed essentially as described in Rodrigues et al.. Plants were challenged when four weeks old by placing a 1-cm toothpick colonized by R. solani inside the sheath of the second youngest fully expanded leaf. Inoculated plants were maintained inside humid inoculation chambersfor 72 h, and, thereafter,4x8ft rolling benches transferred to greenhouse conditions. Four days after challenge infection, disease severity was assessed by measuring the length of the water-soaked lesions. C. miyabeanus bio-assays were performed as described in Ahn et al. with minor modifications. Five-week-old seedlings were misted with a C. miyabeanus spore suspension containing 1 × 104 conidia ml-1 in 0.5% gelatin. Inoculated plants were kept in a dew chamber for 18 h to facilitate fungal penetration, and subsequently transferred to greenhouse conditions for disease development. Disease symptoms were scored at four days after inoculation for about 48 leaves per treatment. Disease ratings were expressed on the basis of diseased leaf area and lesion type: I, no infection or less than 2% of leaf area infected with small brown specs less than 1 mm in diameter; II,less than 10% of leaf area infected with brown spot lesions with gray to white center, about 1–3 mm in diameter; III, average of about 25% of leaf area infected with brown spot lesions with gray to white center, about 1–3 mm in diameter; IV, average of about 50% of leaf area infected with typical spindle-shaped lesions, 3 mm or longer with necrotic gray center and water-soaked or reddish brown margins, little or no coalescence of lesions; V, more than 75% of leaf area infected with coalescing spindle-shaped lesions.Induced systemic resistance assays were performed as described in De Vleesschauwer et al. with minor modifications.

Briefly, rice plants were grown under greenhouse conditions in commercial potting soil that had been autoclaved twice on alternate days for 21 min. Rice seeds first were surface sterilized with 1% sodium hypochlorite for two min, rinsed three times with sterile, demineralized water and incubated for five days on a wet sterile filter paper in sealed Petri dishes at 28°C. Prior to sowing in perforated plastic trays , roots of germinated seeds were dipped in a bacterial suspension of the ISR-inducing strains [5 × 107 colony-forming unitsml-1] for 10 min. The auto claved soil was thoroughly mixed with bacterial inoculum to a final density of 5 × 107 cfu ml-1. To ensure consistent root colonization by the eliciting bacteria, rice plants were soil-drenched a second time with bacterial inoculumat ten days after sowing. In control treatments, soil and rice plants were treated with equal volumes of sterilized saline. For experiments in which purified pyocyanin was applied to the roots of rice seedlings, plants were grown in a hydroponic gnotobiotic system as described before. In this system, plants were fed with various concentrations of pyocyanin and ascorbate 4 days before challenge inoculation by adding the desired concentration to the half-strength Hoagland nutrient solution. Pyocyanin extraction, quantification and application were performed exactly as stated in De Vleesschauwer et al..To gain more insight into the nature of IC1270-mediated ISR against M. oryzae, cytological studies were performed at sites of pathogen entry. To this purpose, we adopted the intact leaf sheath assay previously described by Koga et al.. Briefly, leaf sheaths of the fifth leaf of rice plants at the 5.5 leaf stage were peeled off with leaf blades and roots. The leaf sheath was laid horizontally on a support in plastic trays containing wet filter paper, and the hollow space enclosed by the sides of the leaf sheaths above the mid vein was filled with a suspension of sporesof M. oryzae. Inoculated leaf sheaths were then incubated at 25°C with a 16-h photoperiod. When ready for microscopy, the sheaths were hand-trimmed to remove the sides and expose the epidermal layer above the mid vein. At least five trimmed sheath tissue sections originating from different control and IC1270-treated plants were used for each sampling point. Phenolic compounds were visualized as autofluorescence under blue light epifluorescence . To detect H2O2 accumulation, staining was performed according to the protocol of Thordal-Christensen et al. with minor modifications. Six hours before each time point, trimmed sheath segments were vacuum-infiltrated with an aqueous solution of 1 mg ml-1 3,3′-diaminobenzidine-HCLfor 30 min. Thereafter, infiltrated segments were incubated in fresh DAB solution until sampling.

To determine the importance of PPD1 for the NB response, we compared wild-type and ppd1-null mutant lines lacking all functional copies of PPD1 in the photoperiod-sensitive hexaploid variety Paragon and in the tetraploid line Kronos-PS . We first measured heading date in these lines when grown in SD or LD conditions since germination. Under SD conditions, neither the wild type nor the ppd1-null mutants of either variety flowered within 150 d, when the experiment was terminated . Under LD conditions, the ppd1-null mutants headed 60 d and 34 d later than the wild type Kronos-PS and Paragon-PS lines respectively . In a separate experiment using slightly different conditions , we compared the effect of NBmax in photoperiod-sensitive and ppd1-null mutant lines. Kronos-PS and Paragon-PS plants headed on average at 73 d and 91 d under NB, respectively, but neither ppd1-null line flowered within 150 d, when the experiment was terminated . These results demonstrated that PPD1 plays a major role in the effect of NB and LD on heading time. We next assayed PPD-B1 and FT1 transcript levels in Kronos-PS and ppd1-null plants at four time points, including dusk, when these flowering time genes are normally expressed at high levels under LD . Plants were grown in SDs for 4 weeks, then either maintained in SD conditions or moved to NBmax conditions for 6 weeks. In Kronos-PS plants, PPD-B1 transcript levels were upregulated 1 h and 3 h after the start of the NB and to even higher levels at dusk . In the Kronos-PS plants kept under SD, PPD-B1 transcript levels were not upregulated during the night but showed an increase at dusk, although the levels were significantly lower than in plants that were exposed to multiple NBs . As expected, PPD-B1 transcripts in the Kronos ppd1-null mutants were not detected in either SD or NB conditions, confirming the specificity of the qRT-PCR primers used in this assay .

Consistent with previous results, FT1 transcripts were undetected in Kronos-PS plants under SD but were highly upregulated in NB conditions at all time points . However, in the ppd1-null mutant, FT1 transcripts were not detected in any sampled time points, including dusk,indoor garden under either SD or NB conditions.We next tested the effect of the timing of the NB on PPD-B1 induction by exposing SD-grown plants to a single NB at different times of the night. We hypothesized that maximal induction of PPD-B1 would coincide with the strongest acceleration of heading date . This hypothesis proved to be incorrect and, instead, we found that PPD-B1 was induced to progressively higher levels in accordance with the duration of the dark period preceding the NB . We first thought that the gradual accumulation of inactive Pr phytochromes in the nucleus resulting from dark reversion could explain the increased PPD-B1 induction with longer periods of darkness. However, plants treated with FR light immediately before a NB applied after 2 h of darkness did not exhibit increased PPD-B1 expression . This result suggested that the accumulation of Pr phytochromes in the nucleus was not responsible for the progressive induction of PPD-B1 with extended dark periods. We then thought that PPD-B1 induction could be associated with the de novo synthesis of phytochromes or other intermediate proteins during darkness. To test this hypothesis, we grew Kronos-PS plants in hydroponic solution and treated half of them with cycloheximide to block protein synthesis and left half of the plants untreated as a control. Consistent with previous results, control plants maintained in darkness showed noinduction of PPD-B1, whereas those exposed to a single NB exhibited strong up-regulation of PPD-B1 expression 2 h after the NB . The induction of PPD-B1 in response to NB was abolished in plants treated with cycloheximide , which demonstrates that the expression of PPD1 in response to light requires active protein synthesis during darkness. This experiment was performed twice with identical results.Many studies using NBs to characterize the effects of changing photoperiods on flowering time focused on SD plants, mainly because the inhibition of flowering by NB was found to be a simpler system of study than the acceleration of flowering by NB in LD plants .

Our characterization of the NB response in wheat highlights some of the similarities and differences between these two systems. In many SD plants, flowering is inhibited by NB and in rice; this effect is associated with the suppression of Hd3a transcription . When rice plants are moved from NB back to inductive SD photoperiods, this inhibition is lost and Hd3a expression returns to high levels. In wheat, NBs also affect the expression of FT1 and flowering time, although these responses are reversed. These results suggest SD and LD plants both respond to NB through regulatory mechanisms acting on FT expression. The opposite effect of NB on FT expression and flowering in rice and wheat is likely determined by the opposite roles of PPD1 in different grass species. In LD grasses, such as wheat and barley, PPD1 induces FT1 and accelerates flowering , whereas in SD grasses, such as sorghum and rice, PRR37 suppresses FT-like genes and delays flowering .In some SD plants, the suppression of flowering by a single R light NB is completely reversible by immediate exposure to FR light . In wheat, we found that a single FR exposure after NB had a limited effect on heading time . One-minute pulses of FR after 1-min pulses of white light were more effective , but did not completely abolish the acceleration of heading by NB . The partial effect of FR light on the NB acceleration of flowering is consistent with previous results in the LD grass barley . Finally, rice and wheat differ in the role of PHYC in the NB response. In rice, the NB response is completely abolished in plants carrying PHYB loss-of-function mutations but is unaffected by similar mutations in PHYC . By contrast, the NB response in wheat is abolished in both the phyB-null and phyC-null mutants . The different roles of PHYC on NB parallel the different roles played by this phytochrome in the photoperiodic response in wheat and rice. PHYC is a positive regulator of flowering time in some temperate grasses such as wheat, barley, and Brachypodium distachyon but has limited or no effect on flowering time in rice and Arabidopsis . These results suggest PHYC plays a more critical role in the photoperiod and NB response in the LD temperate grasses than in other plant species.Whereas a single NB is sufficient to repress flowering in rice and promote flowering in Lolium temulentum cv Ceres , multiple LDs are required to accelerate flowering in many temperate grasses .

Most temperate grasses show some acceleration of flowering after being exposed to 4 to 8 LD photoperiods, but full saturation of this response requires 12 to 16 d of exposure to LD . These results are consistent with our observations for wheat, where 6 to 10 LDs induced a mild acceleration in flowering, but the greatest acceleration in flowering was seen in plants exposed to 12 or more LDs . The acceleration in heading time in response to increasing numbers of NBs was similar to that observed in response to increasing numbers of LDs,but the effects were smaller and at least 15 NBs were required to initiate the acceleration of flowering . These results are consistent with the existence of a PPD1- independent photoperiod pathway, which may be more responsive to LDs than to NBs. In Arabidopsis, the induction of the transition from the vegetative to the reproductive apex also requires cycles of FT induction repeated over several days. However, while 4 to 5 LDs are sufficient to saturate the acceleration of flowering in Arabidopsis more than 20 LDs are required in wheat . Possible explanations for the requirement of multiple NBs or LDs to induce FT1 in wheat include a gradual accumulation of a flowering promoter, a gradual reduction of a flowering repressor, or a gradual change in epigenetic marks in some of the involved genes. No correlation was detected between the number of NBs and transcript levels of ZCCT2 , suggesting that this gene is not critical for the observed changes in FT1 in this genetic background . Similarly,hydroponic farming PPD1 transcript levels did not increase in response to multiple NBs, indicating that the putative accumulating factor is unlikely to be a regulator of PPD1 transcription. However, it is still possible that the number of NBs affect the levels of active PPD1 protein. To test this hypothesis, we have initiated the generation of transgenic wheat plants expressing an HA-tagged PPD1 protein. It is also possible that proteins other than PPD1 also play a role in the regulation of FT1 in response to multiple NBs.Interestingly, we found that the magnitude of PPD-B1 induction by NBs was proportional to the length of darkness preceding the NB. This phenomenon appears to be unrelated to the accumulation of Pr phytochrome protein arising from dark reversion, since exposure to FR light prior to NBs had no effect on the subsequent induction of PPD1 by light . Instead, we found that treating plants with cycloheximide during the night abolished the NB up-regulation of PPD1 , which suggests that the induction of PPD1 by light is dependent on active protein synthesis during darkness.

One possibility is that the de novo synthesis of Pr isoforms of PHYB and/or PHYC during darkness is correlated with the strength of PPD1 induction. During longer periods of darkness, newly synthesized PHYB and PHYC proteins would accumulate to higher levels, so that subsequent light signals would result in stronger induction of PPD1. An alternative possibility is the de novo synthesis and dark accumulation of a PHYB/PHYC-induced transcription factor required for the activation of PPD1. This may include one or more PIFs, which have been shown to act as coactivators of light-induced genes in some cases . Additional experiments will be required to test these hypotheses and to identify the darksynthesized protein responsible for the increased activation of PPD1 with longer periods of darkness.Despite the stronger NB induction of PPD1 following longer periods of darkness, PPD1 transcript levels were not directly correlated with heading date. The greatest effect of NB on heading date was observed when the NB was timed to coincide with the middle of the night, even though PPD1 transcript levels were lower at this point than after NBs applied later in the night. This dependence on the time of the night suggests that PPD1 activity may be gated by circadian clock-regulated genes. The existence of a gating mechanism is also supported by the fact that although PPD1 transcription is induced during the light phases of both SD and LD, FT1 transcription is only observed under LD photoperiods . Furthermore, rhythmic sensitivities for NB-induced flowering have been observed in other LD grasses . L. temulentum cv Ceres plants, which are induced to flower by a single LD cycle, showed two phases of high sensitivity to NB when SD-grown plants were moved to constant darkness. The first phase occurred between 4 and 8 h from the start of the darkness period, and the second one was approximately 20 to 24 h later, suggesting the involvement of a circadian rhythm in the control of flowering in L. temulentum . Similar experiments would be challenging to perform in wheat because of the requirement for multiple NBs to induce flowering. It is tempting to speculate that the regulation of FT1 expression by PPD1 may function in a manner analogous to the regulation of FT by CO in Arabidopsis. In Arabidopsis, FT is induced only in LD conditions when the transcriptional peak of CO coincides with light, which is required to stabilize the CO protein . In wheat, FT1 induction and flowering may be determined by the coincidence of an external signal with an internal rhythm mediated by the circadian clock. In addition to this putative role in gating the effect of PPD1, the circadian clock is known to be involved in the regulation of PPD1 expression . Plants carrying loss-of function mutations in EARLY FLOWERING3 exhibited elevated expression of PPD1 and earlier flowering under both LD and SD .

Extensive literature is available documenting many aspects of wastewater treatment using aquatic plants as sum marized, e.g., by Moshiri , Heavy metal uptake be wetland plants was documented by Simmers et al. , Jamil et at, , Lyngby , Shutes et al. , etc. Examples of storm water runoff treatment using wetlands are less numerous. Among the successful ones we can cite an artificial marsh constructed to remove suspended solids and nutrients from storm water runoff from the city of Tallahassee, FL . Many communities outside California already use constructed wetlands for treatment of storm water effluent. Wetland systems are used for a number of reasons, including low maintenance costs and the potential to combine water treatment with habitat creation. However, regulatory agencies that would permit or comment on the establishment of these constructed wetlands are concerned about the potential for bio-accumulation of urban runoff pollutants. If wetlands are to be used for the treatment of urban runoff, an understanding of nutrient and pollutant cycling within wetland plants during the year is crucial. It will help wetland managers to design proper harvesting schemes for removing pollutants from the wetland environment. While many states and communities have experimented with urban effluent and wetlands to determine the most appropriate plant species and management, little work has been completed in California. Results obtained outside of the state can only partially assist in designing California storm water wetlands as plants, weather,indoor vertical farming and soil conditions differ significantly from those of other states. Consequently, significant interest has been generated in developing a useable information base which would be available to both communities and the state regulatory agencies when making decisions regarding storm water wetland management and design. Another important aspect of this problem is that urban runoff currently drains into existing wetlands, which are protected as waters of the United States by the Clean Water Act.

It is important to know the effects and potential impacts that storm water is or may have on naturally occurring wetlands and to what extent pollutants are being concentrated in parts of plants that will be consumed by migratory or resident animals in the wetland environment. In our project we focused primarily on obtaining data on seasonal dynamics of growth and resource allocation including heavy metals allocation in selected wetland plant species grown under conditions of elevated heavy metals. The obtained results provide a basis for using these species for wetland construction. Hydrocotyle verticillata, Ludwigia pep/oides, Nasturtium aquaticum, Sagitta ria latitolia and Polygonum hydropiperoides, all representing a group of soft and/or creeping emergent macrophytes, and Scirpus ecutus, S. celitomicus. S. robustus, Typha letitolie, T. domingensis and Phragmites australis, representing a group of erect emergent macrophytes. These species were selected because they are native to California with the exception of Nasturtium aquaticum, which is naturalized. According to our previous research and the literature data, they are robust primary producers and posses excellent reproductive capabilities. To obtain data on biomass production, the representative species were sampled at various location in the Central Valley. The above ground biomass was harvested from a 50 x 50 cm quadrat, dried and weighed. The rhizome propagation requires close monitoring of soil water as the rhizome cuttings are highly susceptible to both desiccation and drowning. A greenhouse experiment was carried out to determine the dependence of growth characteristics on water level. Three species, Hydrocotyle verticil/ata, Ludwigia pep/aides and Nasturtium aquaticum were tested. Five different water depth in relation to soil surface were used: -10cm, -Scm, Oem, -scm, and +10 cm, each in five replicates. Individual plants were planted in pots with sand and placed in a large metal container with nutrient solution. Nitrogen concentration in the solution was checked at four day intervals and readjusted to 50ppm. The experiment lasted four weeks, at the end plants were harvested, divided into leaves, shoots and roots, dried and weighed.

To determine the dependence of growth of Hydrocotyle verticil/ata and Nasturtium aquaticum and its tissue nitrogen concentration on the concentration of nitrogen in water, we planted individual plants in 500 ml Erlenmeyer flasks or plastic holders placed in buckets in 1/2-strength Hoagland nutrient solution with 1.4, 7, 14, 35, 70, and 140 ppm of nitrogen added as CaN03′ The nutrient solution was changed every second day. The experiment lasted 25 days.In the second year of the project, four wetlands receiving urban runoff and two control sites were selected for analyses. Two of the runoff retention basins, Octo Inn and Rancho Solano , are located in Fairfield, California, two, the North Pond and West Pond are in Davis, California. A small natural wetland in the Cosumnes River Preserve , together with a marsh at Calhoun Slough at the Jepson Prairie Reserve represent the non-polluted habitats. Plant and sediments were collected in the fall and winter. Water was sampled in January, February and March, 1992, following the rain events. All samples were analyzed for lead, zinc, and copper; sediment samples were also analyzed for molybdenum and cadmium. Metals analysis was conducted using Ionized Coupled Plasma Atomic Emission Spectroscopy . During winter and spring of 1992 a wetland cultivation facility was built in the Putah Creek Reserve area adjacent to the Institute of Ecology, UCD. It includes three sets of fiberglass or plastic containers. The first set consists of 24 round fiberglass tanks . Each tank is divided into four compartments by plywood partitions and filled with soil. These tanks were used for studying the effect of different water levels on the growth of wetland plants. The second set includes 80 small plastic containers that were used for experiments assessing the effect of elevated concentrations of heavy metals on plant growth. Propagules of five wetland plant species, native to California’s Central Valley, were collected in the winter of 1991-1992. Scirpus acutus , S. calffornicus , and Typha domfngensis , were collected and propagated from rhizomes. Ludwigia pep/oideswas propagated from stem cuttings and Sagittaria latifoliawas propagated by tubers. Each plant propagule was planted individually into a #6 nursery pOL Washed sand was used as a substrate. A pot with each species was then put into a large tub and the water level was raised to saturation .

Once the plants had sprouted and established themselves, Hoagland’s nutrient solution, without micro-nutrients, was added and nitrate levels were kept as close to 40 ppm as possible. This was to ensure good plant growth at the time of exposure to the metals. The tubs were then flooded with another 10 L of water to ensure flooded conditions. A randomized complete block design was used for the layout. There were five blocks, each with twelve tubs. Treatments were randomly assigned to the twelve tubs. The four metal salts, mentioned above , were administered at three treatment levels: 0.1, 1.0 and 10.0 parts per million .. There were ten control tubs that had no metals added to the water. Prior to treatment, all plants were measured for length or leaf area. The tubs were treated as batch reactors, according to the design layout. The plants were allowed to grow for an additional two weeks after metal treatment. After this time, the plants were harvested, remeasured, separated into leaves, rhizomes, roots,best indoor vertical garden system adventitious roots, tubers and the original propagule stock. Each part was dried at 80° C for 48 hours and then weighed. Once weighed, the samples were ground and submitted to the University of California’s Department of Agriculture and Natural Resources Laboratory for metals analysis. Metals analysis was conducted using Ionized Coupled Plasma Atomic Emission Spectroscopy . Growth, as a function of biomass increase was determined by using correlations of shoot length to dry weight biomass for Scirpus acutus, S. californicus and Typha domingensis, Stem length and number of branches over 10 cm were used to get relationships for biomass in Ludwigia peploides, and leaf area was used for biomass correlations in Sagitta ria latifalia. These correlation relationships were obtained by destructive sampling in accordance with Vymazal et al. 1993.Evaluating the effect of water level on the growth and biomass allocation of eight species of emergent macrophytes was conducted in the 24 round fiberglass tanks . Each tank was divided into four compartments by plywood partitions and filled with soil. Eight plant species, Scirpus californicus, S. acutus, S. robustus, Typha domingensis, Phragmites australis, Ludwigia pep/oides, Po/ygonum hydropiperoides and Sagittaria latifolia were planted in the late summer of 1992. They were initially kept at the same water level until established, after which, four different flooding regimes, +30, +10, 0, and -20 cm, each in three replicates, were initiated by the end of June 1993. Plants in 40 cm x 40 cm grid placed in each compartment were measured biweekly and the allometric correlations established previously were used for assessing the biomass changes. In September, all the above ground biomass was collected from the grid, separated into leaves, stems, adventitious roots and litter. These plant parts were dried and weighed. In one tank from each replicate, the below ground biomass was collected from the following layers: 0 to -5cm, -5 to -tocrn, -10 to -15 em, -15 to – 25cm, -25 to -35 cm and -35 to -50cm . Below ground harvest turned out to be much more time consuming than expected and teams of people were working on it almost non-stop for 12 weeks. To better quantify standing biomass, obvious features such as stem length or plant height were measured on individual harvested plants and related to the dry weight of each plant respectively. Field recorded measurements of plant height and density can then give estimates of standing biomass over larger areas. We used simple stem length to determine biomass for Phragmites australis, Scirpus acutus, S. californicus and S. robustus. The biomass of Typha spp. was best correlated with a “leaf length index.” This index was calculated as the average length of the four tallest leaves of Typha multiplied by the total number of leaves. Biomass of leaves of Sagittaria fatifolia was determined by measuring the leaf length and width and correlating the index CxD with weight. CxD index showed very close correlastion with the leaf area mesured by the L1COR-L13000A leaf area meter.

The biomass of petioles estimated from the regression of petiole length on its weight was added to leaf biomass. Due to the creeping nature of Ludwigia pep/oides and Po/ygonum sp. allometric correlations were not very accurate. Table 1 presents examples of the biomass and tissue nitrogen ranges for several types of wetland macrophytes from natural habitats. The time course of decomposition for of some of these species is shown in Fig. 4. The survey of heavy metals in water from several runoff retention basins sampled in January, February and March, 1992, following rain events did, not reveal any increased metal concentrations. Except for Zn, no detectable levels of heavy metals were found in water samples. Of the plant samples from polluted sites, Nasturtium aquaticum was found to contain the highest levels of Zn . Surprisingly, Sagittaria latifolia from Cosumnes Preserve, our control site, also contained high levels of Zn. If we divide all the plant species tested into two groups based on their growth form, t.e., erect emergent macrophytes and creeping emergent macrophytes, the group of creeping macrophytes, represented by species such as Nasturtium aquaticum, have significantly higher levels of Cu and Zn in their tissues than does the group of erect emergents . Heavy metal concentrations in sediments were not as high as we expected; samples from Octo Inn Basin showed the highest levels of plant available Zn, Pb and Cu among the “polluted” sites. Sediments from the Cosumnes Preserve had the overall highest metals concentrations . However, the levels of lead were generally quite low at all sites. The heavy metal content in plant biomass was not correlated with the concentrations of individual elements in sediments. While the Cosumnes Preserve sediments had the highest concentrations of metals, the highest metal concentrations in plants were found at Rancho Solano. Cadmium is one of the major environmental pollutants and a potential hazard to worldwide agriculture.

Most of the variation for in situ exudates was explained by differences between exudates collected in clay, compared with other conditions, which is evident from a principal component analysis . Similarly, in pairwise comparisons, clay-collected exudates showed the most distinct metabolites , followed by 250 µm sand-collected exudates with 5%–18% distinct metabolites . In contrast to in situ exudates, in vitro exudates exhibited similar metabolite profiles when analyzed with a principal component analysis , and fewer metabolites had statistically significant abundances in pairwise comparisons . Notably, in vitro exudates of clay-grown plants showed a comparable number of distinct metabolites in pairwise comparisons with plants grown in other substrates, suggesting that the in situ differences observed between exudate profiles of clay grown plants and plants grown in other conditions resulted from the presence of the clay, and not from an altered plant metabolism.To further investigate differences in in situ-collected exudates, exudate profiles of the groups by their particle sizes and “big beads,” “small beads,” “big sand,” and “small sand” were compared . In a principal component analysis, exudate profiles of hydroponic and “big beads” exudates overlapped, whereas “big beads” versus “small beads” and “big sand” versus “small sand” separated . Pairwise comparisons showed thirteen distinct metabolites between “big beads” and “small beads,”vertical indoor farming and three distinct metabolites between “big sand” and “small sand.” Two thirds of metabolites were more abundant in “big beads” than “small beads,” among them nucleobases and derivatives, as well as organic acids. Four phenolic acids were more abundant in “small beads” versus “big beads.” In “small sand,” two nitrogenous compounds were higher abundance than in “big sand,” a nucleobase, , and an amino acid derivative .

To further examine the differences between clay-grown and hydroponically grown in situ exudates, a multi-variant test was used to compare metabolite abundances between the two conditions. Most of these metabolites were nitrogenous, with more than half containing a heterocyclic nitrogen group. Among these metabolites were nucleic bases, nucleosides and derivatives with acidic groups, amino acids with acidic and/or basic groups, and linear as well as phenolic organic acids. Two nitrogenous metabolites, an organic acid and choline-O-sulfate with an acidic and a basic group, were more abundant in clay-collected exudates . These compounds were not detected in exudates of hydroponically grown plants, in in vitro-collected exudates of clay-grown plants, or in clay control samples without plants , which suggests that these compounds were released from clay only in the presence of plants.Since clay particles were found to strongly sorb exudate metabolites, we wondered whether the sorbed metabolites were accessible to a plant-associated bacterium, supporting microbial growth. Thus, we first determined the desorption rate of metabolites from the various substrates by determining the metabolite recovery rate from glass beads, sand, and clay incubated with defined medium. As shown previously , the metabolite recovery rate was comparable between the no substrate control and glass beads , lower in sand , and the lowest for clay . The metabolite recovery from washes was 4%–14% for all substrates, indicating all substrates had similar desorption rates. Growth of the rhizobacterium Pseudomonas fluorescens on sand or glass beads pre-incubated with defined medium resulted in the same optical density change as growth on particles pre-incubated with water , indicating that these substrates did not retain metabolites supporting growth. Incubation of the bacterium with clay pre-incubated with defined medium however did result in bacterial growth. As the control incubation of clay with defined medium also showed a small increase in OD, presumably as a result of fine particles, the data presented in Figure 6 are normalized by no-bacterial clay control samples .

These data show an increase in OD of bacteria grown on clay pre-incubated with defined medium, indicating that the bacteria are able to utilize the sorbed metabolites for growth. As an additional control experiment, the pre-incubated clay was incubated with water for three days under sterile conditions , allowing for desorption of metabolites from clay particles. The supernatant was subsequently pipetted into a new well, and bacteria were added and allowed to grow for another three days. This experiment resulted in no-bacterial growth , suggesting that bacterial presence is needed to desorb metabolites from clay particles. We conclude that this particular rhizobacterium is capable of desorbing exudate metabolites from clay to support growth.Growth of B. distachyon in particles with different sizes resulted in various morphological changes. A decrease in particle size resulted in decreased root weight, total root length, and in total root number, although the last parameter correlated less strongly . Root weight correlated positively with shoot weight, total root length, and total root number, indicating a dependency of the different parameters. Notably, the morphology of B. distachyon grown in glass beads or sand was not directly comparable: Plants grown in 5-µm sand had higher root weight and total root length than plants grown in 0.5-mm glass beads. The three-dimensional particle arrangement and other differences between the substrates, such as texture, might account for root morphological differences observed between glass bead and sand-grown plants. For glass bead-grown plants, the reduction in total root length was caused by a reduction in second-order root length, whereas the primary order root length was reduced in all sizes smaller than 3 mm. These trends for reduced root weight and root length but not root number are in line with observations made for maize grown in 1 mm versus hydroponic conditions . However, these previous studies noted an even larger decrease in shoot than in root weight, whereas B. distachyon shoot weight did not change significantly in our experimental conditions. Similar results were found for lettuce grown in three different soils, where root fresh weight and morphology changed, but shoot weight was not affected . The constant B. distachyon shoot weight might indicate sufficient nutrient uptake even by smaller root systems in the environments investigated. Thus, in future studies, it might be interesting to evaluate how the different root systems as generated herewith different substrate sizes further respond to altered nutrient levels.

One could expect an additional change in root morphology with different nutrient starvation conditions, for example, root systems optimized for phosphate scavenging form numerous, short lateral roots, whereas roots optimized for nitrogen uptake exhibit fewer, but long lateral roots . Phosphate movement is hindered by particles with a charged substrate, whereas nitrate movement is less affected by soil chemistry . Thus, changes in root morphology of plants grown in phosphate-limited clay might be distinct from plants grown in phosphate-limited sand or glass beads. Plants grown in soil may exhibit additional changes in root morphology and metabolism, as shown for B. distachyon grown in a sterile soil extract, which showed reduced root length, and elongated root hairs and which depleted a variety of metabolites from soil extract . Root systems further respond to local alterations in soil structure, such as to the presence of micro- or macropores, or to air pockets . Investigations of local root morphology responses in heterogeneous settings with multiple, defined substrate sizes and chemistries will thus shed more light onto how plants respond to soil physiochemistry on a spatial and time scale. Multiple systems exist in which such experiments could be attempted, ranging from EcoFAB model systems to rhizotron designs .B. distachyon exhibited significantly altered root morphology when grown in particles with various sizes, with root weight, and root lengths differing between conditions. The exudate profile however was very similar for these plants when collected in vitro , and exudate extraction volumes were normalized by root fresh weight before measurement. Thus indicating that exudation per root fresh weight is constant. As root weight correlated with both, total root length and with total root number, an additional method was needed to determine whether the number of roots or the root length was important for exudation. In the literature, root tips are often mentioned as predominant sites of exudation for several reasons: a) cell wall suberization of this young tissue is still low , b) exudates have been imaged around root tips , and c) more microbes associate with tips compared with other root sections . Few studies exist investigating spatial patterning of exudation, but some examples suggest that other tissues besides root tips might be involved in exudation. For example, vertical growing towers the localization of the malate transporter ALMT1 in Arabidopsis is confined to the root tip in untreated roots, but expands to the entire root system when treated with an activator, aluminum . This suggests differential malate exudation from different parts of the root, depending on the environment. Similarly, strigolactone exudation is environment-dependent, with its transporter PDR1 expressed in single cells along most of the roots . In addition, microbes do not only colonize root tips, but also prominently sites of lateral root emergence, and are found throughout the root system of plants . Distinct microbial populations, associated with B. distachyon seminal and nodal roots, as well as for nodal root tips versus nodal root bases , could be influenced by differential exudation by these organs. We used mass spectrometry imaging to investigate exudation across roots. These data cannot directly be compared to the root morphology and LC/MS data for technical reasons and the fact that the exudates were collected from three-week-old plants, whereas the imaging experiment was performed with seedlings due to technical limitations. Some ions were observed to be most abundant around the root tip, whereas others were also found in the root elongation and maturation zone, or all along the root axis. In addition, some ions were detected on the root itself, which could mean that they are part of the cell wall, or that they have a low diffusion speed.

Despite these limitations, our data suggest that root exudation is a spatially complex process. Exudation might take place in different ways: Root tip-exuded metabolites might diffuse, due to the absence of Casparian strips or secondary cell walls, or might be actively transported. Metabolites exuded from older root tissues are more likely to be transported, either by channels facilitating diffusion, or by active transport proteins. Future studies are needed to investigate the role of various root zones in exudation to determine which tissues are involved in exudation of various compounds and if exudation differs between root types.Root exudate metabolite profiles were unaltered when plants were grown in different particle sizes. As the root weight, root number, and root length correlated and the exudation of compounds was spatially complex, we conclude that exudation profiles are similar across different root morphologies. However, these investigations were limited and may be better informed by comparison of exudation profiles in plants with more radically altered root morphologies, in plants without secondary roots or root hairs. Exudation profiles were also comparable between plants grown in clay, sand, or glass beads, when collected in vitro. This suggests that the physiochemical environment does not alter plant metabolism, as long as other factors such as nutrient levels, light intensity, and humidity, remain unchanged. However, the exudate metabolite profile of clay- versus sand- or glass bead-grown plants was clearly different for in situ exudates . A recent study found differences in sorghum exudates of plants grown in clay, sand, and soil . In this study, exudates were collected from roots with rhizosphere substrate still attached. The largest difference in this dataset was observed between soilgrown and sand- or clay-grown plants, which might be explained by soil-derived metabolites co-extracted with root exudates . The authors showed some ions to be specifically up- or down-regulated in exudates of clay- versus sand grown plants, but their effect was not strong enough to separate the two conditions in a principal component analysis . This may be explained by their exudate collection method, which was a mixture between the in situ and in vitro conditions utilized here. Recently, it was suggested that root tips might detect the concentration of rhizosphere metabolites, altering root morphology and exudation accordingly . Thus, clay-grown plants should exhibit an altered root morphology compared to hydroponically grown plants, as clay sorbs a significant amount of exudates, changing the metabolite concentration around the root tip. However, the root morphology of clay-grown plants is statistically not different from hydroponically grown plants .

Wheat can utilize either form alone , but mixed N nutrition typically produces the best grain yields and quality in hydroponically grown and field-grown plants .Ammonium requires less energy to assimilate into organic compounds , but can prove toxic if it accumulates to high concentrations within plant tissues . Nitrate is generally the predominant form available in aerated, temperate agricultural soils , and may accumulate within plant tissues to high concentrations without toxicity . In wheat, the N form supplied has been found to influence many physiological parameters profoundly including biomass , leaf area , tillering , seed mass , protein content , and mineral nutrient acquisition and distribution , although such differences can vary among cultivars . The presence of NH4 + , as either a sole N source or in mixed N nutrition, increased organic N concentration in shoots, roots, and grain and decreased partitioning of dry matter to the roots in wheat . Decreased cation uptake has been found in wheat under NH4 + nutrition , although results varied among cultivars . For example, NH4 + nutrition decreased whole plant and shoot accumulations of K, Cu, Ca, Mg, Fe, Mn, and Zn . Nutrient allocation to plant tissues also varied between N forms. NH4 + -fed plants distributed a smaller percentage of total P, K, Cu, and B to roots relative to NO3 + -fed plants . Also, a greater percentage of reduced N was allocated to the shoots in NH4 + -fed plants . Elevated atmospheric concentrations of CO2 alter growth and N dynamics of wheat and other C3 plants. Under elevated CO2, wheat has lower protein and N concentrations ,vertical grow racks and lower macro- and micro-nutrients concentrations . Grain phytate concentrations are also thought to increase or remain the same under elevated CO2,and in conjunction with decreased concentrations of micro-nutrients, bio-available Zn and Fe are expected to decrease even further under elevated CO2 , as these micro-nutrients form indigestible complexes with phytate.

By contrast, wheat yields , harvest index , whole plant biomass , shoot biomass , and root biomass typically increase under CO2 enrichment. In addition, elevated CO2 concentration can increase tillering , nitrogen use efficiency , and micro/macro-nutrient use efficiencies. The influence of elevated CO2 on many of these characteristics may vary among cultivars and research protocols . Wheat grown under CO2 enrichment behaves differently under NO− 3 and NH4 + nutrition. Exposure to elevated CO2 inhibits NO− 3 photoassimilation in wheat as well as in all other C3 and C3– C4 intermediate plants tested . At elevated CO2, NH4 + -fed plants showed greater increases in leaf area and smaller decreases in shoot protein concentration than NO− 3 -fed plants , which could have consequences for human nutrition. Vegetative plants receiving NH4 + had greater shoot, stem, and root biomass at elevated CO2 . Wheat receiving NO− 3 grew slower at elevated CO2 than at ambient CO2 . Shoot NO− 3 concentrations in NH4 + -fed plants were undetectable while those in NO− 3 -fed plants increased by 62% with CO2 enrichment . This increase was associated with an inhibition in NO− 3 and NO− 2 reductase activities under elevated CO2 . The interaction between atmospheric CO2 concentration and inorganic N form and how it influences plant growth and nutrient concentrations has not been examined in wheat or any other crop species grown to senescence. Here, we grew wheat hydroponically in controlled environment chambers and measured mineral nutrition, biomass, and nutrient allocation in response to three concentrations of atmospheric CO2 and two forms of N nutrition . We tested the following hypotheses: plant nutrient concentrations and allocation patterns will respond differently to CO2 enrichment under the two N forms, and NO− 3 -fed plants will show a smaller biomass and yield enhancement in response to CO2 enrichment than NH4 + -fed plants as a result of CO2 inhibition of shoot NO− 3 assimilation. Also, we observed both differences in the Zn concentration between plants grown on NH4 + and NO− 3 and a strong dependence of Zn absorption on Zn and phytate concentration, indicating that phytate and bio-available Zn are affected by N form and CO2. Therefore, we used the well supported Miller equation to estimate how N and CO2 might impact a hypothetical human population. Iron, another important micro-nutrient that forms complexes with phytate, was not analyzed because we observed no significant differences in iron concentrations between the N forms and because how best to estimate Fe absorption in humans is still uncertain . Wheat seeds were surface sterilized for one minute in 2.6% sodium hypochlorite solution and thoroughly rinsed with DDI water.

The seeds were then rolled up in germination paper saturated with 10 mM CaSO4. The germination paper was placed in a 400 mL beaker with approximately 75 mL of 10 mM CaSO4 solution, covered with a plastic bag and placed in an incubator for four days. Seedlings were transplanted into 20 L tubs filled with an aerated nutrient solution that contained 1 mM CaSO4, 1 mM K2HPO4, 1 mM KH2PO4, 2 mM MgSO4, and 0.2 g L−1 Fe-NaEDTA and micro-nutrients 2HPO4 as the N source, Epstein and Bloom, 2005. The nutrient solution was replaced weekly and an additional 0.2 mM of NO− 3 – or NH4 + − N was added midweek until harvest. The solution volume was maintained by daily addition of deionized water. Solution pH varied between 6.8 and 7.0 for both of the N forms, and the NH4 + and the NO− 3 solutions did not differ by more than 0.1 pH units. The plants were grown in controlled environment chambers set at 23/20˚C day/night at 60–70% relative humidity with a photoperiod of 15 h. The photosynthetic flux density was 375µmol m−2 s −1 at plant height. Plants were subjected to one of three CO2 concentrations: “sub-ambient” , “ambient” , and “elevated” . Sub-ambient CO2 concentrations were maintained by passing air that entered the growth chamber through wet soda lime, a mixture of KOH, NaOH, and Ca2 that was replaced as needed. The elevated CO2 conditions were maintained in an environmental chamber equipped with non-dispersive infrared analyzers for CO2 and valves that added pure CO2 to the incoming air stream to hold the chamber concentration at 720 ppm. The wheat was grown until all above ground parts turned completely yellow. Plant matter was sorted into grain, chaff, shoots, and roots and dried for 48 h at 55˚C. Data on kernel number , kernel mass, number of heads, kernels head−1 , and HI were collected prior to sample preparation for nutrient analysis. A portion of the grain was analyzed for phytate using a modification of the method as described by Haug and Lantzsch . The remainder of the grain as well as the shoots and chaff was bulked into five repetitions per treatment and sent to the UC Davis Analytical Laboratory for nutrient analysis.

The roots of plants for each CO2 × N treatment became entangled within the same tub; therefore, we were unable to separate the roots of the individual plants for analysis. Root data are thus presented as means for each treatment with no standard errors or confidence intervals. Data were analyzed using PROC MIXED . Nitrogen form and CO2 factors were treated as fixed independent variables. We used the Tukey–Kramer Honestly Significant Difference test for mean separation. Probabilities less than 0.05 were considered significant. Because some of the transformed variables did not meet the assumption of homogeneity of variances,vertical farming in shipping containers but one-way ANOVAs met the ANOVA assumptions, we analyzed the results via one-way ANOVAs to gain some information on the interactions between CO2 and N form.We used a database derived from the United Nation’s Food and Agriculture Organization ’s national food balance sheets to estimate the average daily per capita dietary intake of zinc and phytate from 95 different food commodities in each of 176 countries. This database combines FAO data on per capita intake of food commodities with USDA data on the nutrient or phytate content of each of these commodities. More detailed discussion of the creation of this database for the International Zinc Collaborative Group may be found in Wuehler et al. . Using this database, we produced two data sheets: one containing per capita daily dietary intake of zinc from each food commodity for each country and another containing per capita phytate intake from each food commodity for each country. To calculate total dietary zinc and total dietary phytate per country, we summed across the rows of all food commodities for each respective country. To determine the proportion of a population at risk for zinc deficiency from a hypothetical least developed country , we first calculated TDP and TDZ values for a set of 44 countries defined by the United Nations as being least developed. We took the mean TDP and TDZ values for these countries to represent a hypothetical “less developed country.” To calculate the bio-available zinc portion we used the Miller equation . Mean TDZ and TDP values were converted to mg mmol−1 and put into the Miller equation to compute the average per capita TAZ in our hypothetical LDC. The variables TDZ, TDP, and TAZ are described above, and Amax, KP, and KR are constants as described in Miller et al. . We made an assumption that our hypothetical LDC receives half of its phytate and half of its zinc from wheat, which is roughly consistent with many of the LDCs in the FAO database. We analyzed the effect of elevated carbon dioxide levels on TDP, TDZ, and TAZ concentrations in a hypothetical LDC population for both NH4 + and NO− 3 -supplied wheat. To calculate a new TAZ for wheat grown under elevated CO2 conditions, we first calculated the percent change in TAZ from ambient to elevated levels for wheat receiving NH4 + or NO− 3 .

This computed percent change was then applied to half of the hypothetical TDZ and TDP; meanwhile, the other half of the hypothetical TDZ and TDP remained unmodified. Thus, the total new TDP and TDZ is the sum of the unmodified and modified portions. These new TDP and TDZ values for both NH4 + and NO− 3 -supplied wheat were then put into the Miller equation to compute new hypothetical TAZ values for an LDC. Differences and corresponding percent changes between the new TAZ values and the original TAZ value for a LDC were computed to determine the overall affect of elevated CO2 on TAZ in NH4 + and NO− 3 -supplied wheat for an average developing world population. TAZ, TDP, and TDZ concentrations can only be compared within a single N form across the CO2 concentrations due to methodological constraints of the model. Plants supplied NH4 + vs. NO− 3 nutrition reacted differently to CO2 enrichment . Plants supplied NH4 + differed across CO2 treatments for most of the yield and biomass measurements. The greatest values typically were found at ambient CO2 concentrations. Shoot, chaff, grain yield, number of heads, and KN were greatest at ambient CO2 levels. Individual kernel mass was greatest under both ambient and elevated CO2 treatments. HI and kernels head−1 showed no change across CO2 treatments. In contrast, biomass and yield measures of NO− 3 -supplied plants did not differ among the three CO2 concentrations. At sub-ambient CO2, differences between the NH4 + and NO− 3 treatments occurred in shoot biomass and three of the yield components: kernel mass, head number, and kernels head−1 . Ammonium-supplied plants had a larger number of heads while NO− 3 -supplied plants had greater shoot biomass, kernel mass, and kernels head−1 . At ambient CO2, NH4 + -supplied plants had a greater number of heads and greater chaff biomass. Plants supplied NO− 3 had a larger number of kernels head−1 . At elevated CO2, biomass and yield measures did not differ with N treatment. The distribution of nutrients and micro-nutrients among plant parts followed similar patterns in both the NH4 + and NO− 3 – supplied plants, although the NH4 + -supplied plant distributions were slightly more variable .

The Darroch and Frost analysis was conducted nearly 20 years ago, and the interviews were limited to women practicing vaginal intercourse. To our knowledge, a more recent study linking likelihood of product use and price sensitivity has not been conducted, or at least not reported, to include other populations of potential microbicide users such as heterosexual couples practicing anal sex or gay men practicing unprotected rectal intercourse. Nevertheless, the 1999 study established an initial price point and price sensitivity for potential users of microbicides in the USA. Griffithsin has a broader spectrum of antiviral activity than HIV-specific PrEP agents, including activity against HSV-2 and HCV, which are co-transmitted with HIV-1 . Hence, Griffithsin might command a higher price due to its broader antiviral activity and its potential to obviate prevention and treatment costs for co-transmitted viruses. In the USA, the cost of the oral PrEP drug Truvada ranges from $1,300 to over $1,700 per month for the uninsured, but treatment is typically covered by insurance with user co-payments of $80–$150 per month. So even if a Griffithsin-containing microbicide sold for $5 per application , a user of 2 packs per month would pay $100 for the microbicide, which is in the range of PrEP, with the potential added benefit of controlling co-transmitted viruses. Consumers in wealthier economies might be receptive to microbicides costing $1–2 or even more per dose; however, consumers in lesser-developed economies might find $1–2/dose to be prohibitive. Hence, absent subsidies, there exists a continuing need to lower COGS for APIs such as Griffithsin. We can conclude that a COGS of <$0.40/dose of Griffithsin DS as determined in this study, and an estimated user cost of $1– 2/dose, mobile vertical grow racks might enable at least some simpler formulations of the drug to be economically marketed.

For more complex formulations and delivery systems, or for higher doses of the drug, lower COGS for bulk Griffithsin would be desirable.The environmental assessment of the plant-based production of Griffithsin indicates low impact, particularly if the plant nutrient solutions are recycled in a hydroponic system and if waste streams containing TMV are treated in a bio-waste heat or chemical treatment process. The assessment method used, although semi-quantitative, utilizes mass input and output stream data generated by SuperPro, along with independent assessment of compound toxicity and/or environmental impact , and allows comparison between alternative production strategies, process configurations or chemical components used in the manufacturing process. Our low environmental impact assessment for plant-based manufacturing should compare favorably with fermentation based approaches to producing Griffithsin. In the latter, the complexities of purification suggest less efficient utilization of materials and higher disposal volumes, although a side-by-side environmental analysis between the two platforms was not conducted in this study.Upstream, Griffithsin expression rates were based on empirical findings using TMV whole virion as the expression vector, which can achieve typically 0.5–1.0 g Griffithsin/kg plant biomass . An average pilot-scale expression rate of0.52 g/kg was used in our model . Although this expression level is quite good for TMV, higher Griffithsin expression levels can be achieved with different technology. For example, Nomad Bioscience GmbH has achieved Griffithsin expression in N. benthamiana exceeding 2.5 g Griffithsin/kg FW biomass using NomadicTM agrobacterial vectors applied to plants either through vacuum infiltration or agrospray , albeit these results were obtained in small-scale studies. For example, even with the same recovery efficiency of 70% assumed in the current model, the output of Griffithsin at the higher expression level would be 1.75 g API/kg plant material, instead of the current 0.37 g/kg; this represents more than 4.7- times the modeled output of protein per kg biomass.

Under such conditions, the costliest parts of the current process, namely biomass production and upstream procedures, would be lowered by the reduced biomass needs to produce the required 20 kg/year of API. Although a full analysis of the cost of agrobacterial inoculation for Griffithsin production needs to be conducted, we know from similar analyses that economics can be favorably impacted by higher expression efficiencies. We can therefore envision that by using a more efficient induction process the per-dose production cost could be less than the current $0.32. Still other gene expression methods can be considered, including using transgenic plants expressing Griffithsin either in constitutive or inducible systems , which could also lead to higher API accumulation in host plant biomass and potentially lower COGS . Increasing expression yield upstream might shift costs to downstream operations to handle process streams with higher concentrations of API. Definition of the comparative cost benefits of these improvements relative to the current process modeled awaits a subsequent evaluation. From a process standpoint, improvements in the efficiency of lighting technologies and/or incorporating solar panels would reduce upstream utilities costs, one of the major contributors to the upstream operating costs. Improving hydroponic nutrient utilization through recycling and minimizing runoff in the simulation model will reduce raw material costs as well as aqueous waste disposal costs, thereby reducing the COGS. In the downstream portion of the process consumables play a major role, particularly dead-end filters and plate-and frame filters; if these could be replaced with tangential flow filtration systems that utilize reusable, cleanable ceramic filters, downstream operating costs could be further reduced. At the time of this writing, such systems were being considered and their impact on Griffithsin COGS will be the subject of a future analysis. Nitrogen is a vital macro-nutrient for plant growth and development. Plants have evolved a range of mechanisms to adapt to imbalanced nitrogen conditions. In agricultural systems, high-yield of crops relies on application of nitrogen fertilizers. But a large part of nitrogen deposited in the soil can’t be absorbed by plants and is lost to the environment, resulting in severe environmental and ecological pollution. Improving the nitrogen use effciency of crops is the key to solve these problems. Studying the genes and mechanisms involved in regulating nitrogen uptake and assimilation can be a prerequisite for improving NUE of crops, therefore it is of great importance for sustaining agriculture.

Nitrate and ammonium are the main nitrogen forms used by plants and most crops, like maize and wheat, take up nitrate as the major nitrogen source. In addition to its nutrient role, nitrate acts also as a signaling molecule for plants. It regulates the expression levels of many genes, including genes directly involved in nitrate assimilation, namely NIAs, NiR, and some NRTs. It is also involved in many adaptive responses of plants, such as root development and architecture, seed dormancy, fowering time, circadian system, leaf development, stomatal movements, and auxin transportation. Nitrate is taken up into plants by nitrate transporters and high afinity and low afinity nitrate uptake systems have been identified. Four gene families have been identified that encode nitrate transporters in Arabidopsis: NRT1/PTR , NRT2 , CLC , and SLAC1/SLAH. Among these families, NRT1/PTR belongs to the low afinity transport system, and NRT2 belongs to the high afinity transport system. NRT1.1 , which belongs to NRT/PTR family, functions in nitrate uptake as both high afinity and low afinity transporter.In addition to the nitrate transport systems, genes involved in nitrate signaling have also been identified. Most of these genes were found to function in root architecture or primary nitrate responses. Te genes functioning in root architecture include the ANR1, the first molecular component isolated by classic molecular genetics approach, is a MADS box transcription factor and positively regulates lateral root branching under sufficient nitrate condition. miR393/AFB3 and NAC4 have been demonstrated to regulate the root system architecture in nitrate signaling using systems approach. Te split-root assays indicated that TCP20 was involved in systemic nitrate signaling for root foraging. Recently, TCP20 was found to regulate root meristem growth under nitrogen starvation and to interact with NLP6&7. HHO1 and HRS1 are two nitrate-responsive transcription factors isolated by genome-wide analyses. They function in the repression of primary root growth under both phosphate starvation and nitrate supply conditions. During last several years,vertical garden growing the nitrate regulatory factors involved in the primary nitrate response have been identified. NRT1.1, in addition to its transport function, was identified to work as a nitrate sensor. Te study on the crystal structure of NRT1.1 has demonstrated that Tr101 phosphorylation is essential for nitrate transport rate and provides further insights into its transport mechanisms. CIPK8 and CIPK23 which belong to CBL-interacting protein kinase family are important players in responding to primary nitrate. CIPK8 works positively while CIPK23 functions negatively in nitrate regulation. Te expression of both CIPK8 and CIPK23 is regulated by NRT1.1. Recently, NRG2 which is an essential nitrate regulatory gene was isolated by forward genetics screen. NRG2 acts as a positive nitrate regulatory factor and modulates NRT1.1 expression and can interact with NLP7. Additionally, several transcription factors were identified to be involved in primary nitrate response, for example, NLP6, NLP7, LBD37/38/39, TGA1, TGA4, and SPL9. NLP7 is NIN-like protein and acts as an important nitrate positive regulator. NLP7 was isolated by reverse genetics strategy and the nlp7 mutants exhibit a nitrogen-starved phenotype. Te nitrate condition can affect the NLP7′s nuclear retention. Previous studies have demonstrated that the nitrate response cis-element NRE can be bound by NLPs and contain a DNA-binding domain RWP-PK and protein-protein interaction domains typeI/II Phox and Ben1p. ChIP-chip assays showed that NLP7 could bind 851 genes containing NRT1.1, NRT2.1, LBD37/38. In addition, over expression of NLP7 can increase plant biomass, nitrogen uptake, total nitrogen content, and expression levels of genes involved in nitrogen assimilation and signaling.

Moreover, NLP7 can control plant root growth under both N-limited and N-rich conditions. NLP6 also functions positively in nitrate regulation, is retained in the nucleus in nitrate-treated plants and can activate the expression of nitrate-responsive genes. LBD37/38/39 are negative regulators in nitrate signaling. Tey are involved in primary nitrate response and can affect nitrogen status, growth, and nitrogen-dependent shoot branching. TGA1, TGA4, and SPL9 were isolated by systems approach. TGA1 and TGA4 belong to bZIP transcription factor family and TGA1 can bind to the promoters of NRT2.1 and NRT2.2. SPL9 is demonstrated to be a nitrate regulatory hub. Although these nitrate regulatory genes have been identified, our understanding of the nitrate regulatory gene network is still incomplete. For example, both NLP7 and NRT1.1 play essential roles in regulating nitrate signaling and ChIP-chip assay showed that NLP7 might bind NRT1.1, however, their relationship and underlining mechanism remain unclear. In this paper, we investigated the relationship between NRT1.1 and NLP7 in nitrate regulation. Our analyses reveal that NLP7 acts as a positive regulatory factor upstream of NRT1.1 when NH4 + is present and modulates the nitrate signaling function of NRT1.1. NLP7 might function in another pathway to regulate nitrate signaling independent of NRT1.1. In addition, transcriptome data showed that four GO terms related to nitrogen were regulated by NRT1.1 as well as NLP7 in nitrate signaling, providing more evidence to support our above conclusion. Furthermore, the ChIP and EMSA assays indicated that NLP7 could bind to specific regions of the NRT1.1 promoter. Our findings not only further elucidate the relationship between NRT1.1 and NLP7, but also provide insights into the network of the nitrate regulatory genes.To study the relationship between NLP7 and NRT1.1, the expression levels of NRT1.1 was detected firstly under potassium nitrate and ammonium nitrate conditions. Figure 1a showed that the transcript levels of NRT1.1 in the nlp7 mutants were not notably changed under potassium nitrate condition, but was significantly decreased in mutant plants under ammonium nitrate condition . This indicates that the expression levels of NRT1.1 can be modulated by NLP7 in the presence of NH4 +. In order to test if NLP7 is regulated by NRT1.1, we tested NLP7 expression in chl1-5 and chl1-13 mutants in potassium nitrate and ammonium nitrate mediums. Te expression of NLP7 was not changed in the nrt1.1 mutants . This result indicates that NRT1.1 may not regulate the expression of NLP7. We also tested the NRT1.1 expression response to nitrate in WT and the nlp7 mutants. qPCR results showed that the induction of NRT1.1 by nitrate was notably decreased in the nlp7 mutants, indicating that NLP7 affects the response of NRT1.1 to nitrate .To elucidate the relationship between NLP7 and NRT1.1, the single mutants: nlp7-4 and chl1-13 which contain the nitrate-responsive NRP-YFP transgene, both of which were isolated by our mutant screens described previously were crossed to obtain the double mutant chl1-13 nlp7-4.