Meeting the global food demand of the future by engineering crop photosynthesis and yield potential.

Increase in demand for our primary foodstuffs is outstripping increase in yields, an expanding gap that indicates large potential food shortages by mid-century. This comes at a time when yield improvements are slowing or stagnating as the approaches of the Green Revolution reach their biological limits. Photosynthesis, which has been improved little in crops and falls far short of its biological limit, emerges as the key remaining route to increase the genetic yield potential of our major crops. Thus, there is a timely need to accelerate our understanding of the photosynthetic process in crops to allow informed and guided improvements via in-silico-assisted genetic engineering. Potential and emerging approaches to improving crop photosynthetic efficiency are discussed, and the new tools needed to realize these changes are presented.

Kinetic modeling identifies targets for engineering improved photosynthetic efficiency in potato (Solanum tuberosum cv. Solara).

Potato (Solanum tuberosum) is a significant non-grain food crop in terms of global production. However, its yield potential might be raised by identifying means to release bottlenecks within photosynthetic metabolism, from the capture of solar energy to the synthesis of carbohydrates. Recently, engineered increases in photosynthetic rates in other crops have been directly related to increased yield - how might such increases be achieved in potato? To answer this question, we derived the photosynthetic parameters Vcmax and Jmax to calibrate a kinetic model of leaf metabolism (e-Photosynthesis) for potato. This model was then used to simulate the impact of manipulating the expression of genes and their protein products on carbon assimilation rates in silico through optimizing resource investment among 23 photosynthetic enzymes, predicting increases in photosynthetic CO2 uptake of up to 67%. However, this number of manipulations would not be practical with current technologies. Given a limited practical number of manipulations, the optimization indicated that an increase in amounts of three enzymes - Rubisco, FBP aldolase, and SBPase - would increase net assimilation. Increasing these alone to the levels predicted necessary for optimization increased photosynthetic rate by 28% in potato.

Merlin/NF2 suppresses tumorigenesis by inhibiting the E3 ubiquitin ligase CRL4(DCAF1) in the nucleus.

Current models imply that the FERM domain protein Merlin, encoded by the tumor suppressor NF2, inhibits mitogenic signaling at or near the plasma membrane. Here, we show that the closed, growth-inhibitory form of Merlin accumulates in the nucleus, binds to the E3 ubiquitin ligase CRL4(DCAF1), and suppresses its activity. Depletion of DCAF1 blocks the promitogenic effect of inactivation of Merlin. Conversely, enforced expression of a Merlin-insensitive mutant of DCAF1 counteracts the antimitogenic effect of Merlin. Re-expression of Merlin and silencing of DCAF1 implement a similar, tumor-suppressive program of gene expression. Tumor-derived mutations invariably disrupt Merlin's ability to interact with or inhibit CRL4(DCAF1). Finally, depletion of DCAF1 inhibits the hyperproliferation of Schwannoma cells from NF2 patients and suppresses the oncogenic potential of Merlin-deficient tumor cell lines. We propose that Merlin suppresses tumorigenesis by translocating to the nucleus to inhibit CRL4(DCAF1).

Greater mesophyll conductance and leaf photosynthesis in the field through modified cell wall porosity and thickness via AtCGR3 expression in tobacco.

Mesophyll conductance (gm) describes the ease with which CO2 passes from the sub-stomatal cavities of the leaf to the primary carboxylase of photosynthesis, Rubisco. Increasing gm is suggested as a means to engineer increases in photosynthesis by increasing [CO2] at Rubisco, inhibiting oxygenation and accelerating carboxylation. Here, tobacco was transgenically up-regulated with Arabidopsis Cotton Golgi-related 3 (CGR3), a gene controlling methylesterification of pectin, as a strategy to increase CO2 diffusion across the cell wall and thereby increase gm. Across three independent events in tobacco strongly expressing AtCGR3, mesophyll cell wall thickness was decreased by 7%-13%, wall porosity increased by 75% and gm measured by carbon isotope discrimination increased by 28%. Importantly, field-grown plants showed an average 8% increase in leaf photosynthetic CO2 uptake. Up-regulating CGR3 provides a new strategy for increasing gm in dicotyledonous crops, leading to higher CO2 assimilation and a potential means to sustainable crop yield improvement.

Stomatal conductance reduction tradeoffs in maize leaves: A theoretical study.

As the leading global grain crop, maize significantly impacts agricultural water usage. Presently, photosynthesis ( A net ${A}_{\text{net}}$ ) in leaves of modern maize crops is saturated with CO 2 ${\text{CO}}_{2}$ , implying that reducing stomatal conductance ( g s ${g}_{{\rm{s}}}$ ) would not affect A net ${A}_{\text{net}}$ but reduce transpiration ( τ $\tau $ ), thereby increasing water use efficiency (WUE). While g s ${g}_{{\rm{s}}}$ reduction benefits upper canopy leaves under optimal conditions, the tradeoffs in low light and nitrogen-deficient leaves under nonoptimal microenvironments remain unexplored. Moreover, g s ${g}_{{\rm{s}}}$ reduction increases leaf temperature ( T leaf ${T}_{\text{leaf}}$ ) and water vapor pressure deficit, partially counteracting transpiratory water savings. Therefore, the overall impact of g s ${g}_{{\rm{s}}}$ reduction on water savings remains unclear. Here, we use a process-based leaf model to investigate the benefits of reduced g s ${g}_{{\rm{s}}}$ in maize leaves under different microenvironments. Our findings show that increases in T leaf ${T}_{\text{leaf}}$ due to g s ${g}_{{\rm{s}}}$ reduction can diminish WUE gains by up to 20%. However, g s ${g}_{{\rm{s}}}$ reduction still results in beneficial WUE tradeoffs, where a 29% decrease in g s ${g}_{{\rm{s}}}$ in upper canopy leaves results in a 28% WUE gain without loss in A net ${A}_{\text{net}}$ . Lower canopy leaves exhibit superior tradeoffs in g s ${g}_{{\rm{s}}}$ reduction with 178% gains in WUE without loss in A net ${A}_{\text{net}}$ . Our simulations show that these WUE benefits are resilient to climate change.

Cryo-EM structures of fungal and metazoan mitochondrial calcium uniporters.

The mitochondrial calcium uniporter (MCU) is a highly selective calcium channel and a major route of calcium entry into mitochondria. How the channel catalyses ion permeation and achieves ion selectivity are not well understood, partly because MCU is thought to have a distinct architecture in comparison to other cellular channels. Here we report cryo-electron microscopy reconstructions of MCU channels from zebrafish and Cyphellophora europaea at 8.5 Å and 3.2 Å resolutions, respectively. In contrast to a previous report of pentameric stoichiometry for MCU, both channels are tetramers. The atomic model of C. europaea MCU shows that a conserved WDXXEP signature sequence forms the selectivity filter, in which calcium ions are arranged in single file. Coiled-coil legs connect the pore to N-terminal domains in the mitochondrial matrix. In C. europaea MCU, the N-terminal domains assemble as a dimer of dimers; in zebrafish MCU, they form an asymmetric crescent. The structures define principles that underlie ion permeation and calcium selectivity in this unusual channel.

Atomic structure of the eukaryotic intramembrane RAS methyltransferase ICMT.

The maturation of RAS GTPases and approximately 200 other cellular CAAX proteins involves three enzymatic steps: addition of a farnesyl or geranylgeranyl prenyl lipid to the cysteine (C) in the C-terminal CAAX motif, proteolytic cleavage of the AAX residues and methylation of the exposed prenylcysteine residue at its terminal carboxylate. This final step is catalysed by isoprenylcysteine carboxyl methyltransferase (ICMT), a eukaryote-specific integral membrane enzyme that resides in the endoplasmic reticulum. ICMT is the only cellular enzyme that is known to methylate prenylcysteine substrates; methylation is important for the biological functions of these substrates, such as the membrane localization and subsequent activity of RAS, prelamin A and RAB. Inhibition of ICMT has potential for combating progeria and cancer. Here we present an X-ray structure of ICMT, in complex with its cofactor, an ordered lipid molecule and a monobody inhibitor, at 2.3 Å resolution. The active site spans cytosolic and membrane-exposed regions, indicating distinct entry routes for the cytosolic methyl donor, S-adenosyl-l-methionine, and for prenylcysteine substrates, which are associated with the endoplasmic reticulum membrane. The structure suggests how ICMT overcomes the topographical challenge and unfavourable energetics of bringing two reactants that have different cellular localizations together in a membrane environment-a relatively uncharacterized but defining feature of many integral membrane enzymes.

A hybrid kinetic and constraint-based model of leaf metabolism allows predictions of metabolic fluxes in different environments.

While flux balance analysis (FBA) provides a framework for predicting steady-state leaf metabolic network fluxes, it does not readily capture the response to environmental variables without being coupled to other modelling formulations. To address this, we coupled an FBA model of 903 reactions of soybean (Glycine max) leaf metabolism with e-photosynthesis, a dynamic model that captures the kinetics of 126 reactions of photosynthesis and associated chloroplast carbon metabolism. Successful coupling was achieved in an iterative formulation in which fluxes from e-photosynthesis were used to constrain the FBA model and then, in turn, fluxes computed from the FBA model used to update parameters in e-photosynthesis. This process was repeated until common fluxes in the two models converged. Coupling did not hamper the ability of the kinetic module to accurately predict the carbon assimilation rate, photosystem II electron flux, and starch accumulation of field-grown soybean at two CO2 concentrations. The coupled model also allowed accurate predictions of additional parameters such as nocturnal respiration, as well as analysis of the effect of light intensity and elevated CO2 on leaf metabolism. Predictions included an unexpected decrease in the rate of export of sucrose from the leaf at high light, due to altered starch-sucrose partitioning, and altered daytime flux modes in the tricarboxylic acid cycle at elevated CO2 . Mitochondrial fluxes were notably different between growing and mature leaves, with greater anaplerotic, tricarboxylic acid cycle and mitochondrial ATP synthase fluxes predicted in the former, primarily to provide carbon skeletons and energy for protein synthesis.

Rethinking the potential productivity of crassulacean acid metabolism by integrating metabolic dynamics with shoot architecture, using the example of Agave tequilana.

Terrestrial CAM plants typically occur in hot semiarid regions, yet can show high crop productivity under favorable conditions. To achieve a more mechanistic understanding of CAM plant productivity, a biochemical model of diel metabolism was developed and integrated with 3-D shoot morphology to predict the energetics of light interception and photosynthetic carbon assimilation. Using Agave tequilana as an example, this biochemical model faithfully simulated the four diel phases of CO2 and metabolite dynamics during the CAM rhythm. After capturing the 3-D form over an 8-yr production cycle, a ray-tracing method allowed the prediction of the light microclimate across all photosynthetic surfaces. Integration with the biochemical model thereby enabled the simulation of plant and stand carbon uptake over daily and annual courses. The theoretical maximum energy conversion efficiency of Agave spp. is calculated at 0.045-0.049, up to 7% higher than for C3 photosynthesis. Actual light interception, and biochemical and anatomical limitations, reduced this to 0.0069, or 15.6 Mg ha-1 yr-1 dry mass annualized over an 8-yr cropping cycle, consistent with observation. This is comparable to the productivity of many C3 crops, demonstrating the potential of CAM plants in climates where little else may be grown while indicating strategies that could raise their productivity.

A genome-scale metabolic reconstruction of soybean and Bradyrhizobium diazoefficiens reveals the cost-benefit of nitrogen fixation.

Nitrogen-fixing symbioses allow legumes to thrive in nitrogen-poor soils at the cost of diverting some photoassimilate to their microsymbionts. Effort is being made to bioengineer nitrogen fixation into nonleguminous crops. This requires a quantitative understanding of its energetic costs and the links between metabolic variations and symbiotic efficiency. A whole-plant metabolic model for soybean (Glycine max) with its associated microsymbiont Bradyrhizobium diazoefficiens was developed and applied to predict the cost-benefit of nitrogen fixation with varying soil nitrogen availability. The model predicted a nitrogen-fixation cost of c. 4.13 g C g-1 N, which when implemented into a crop scale model, translated to a grain yield reduction of 27% compared with a non-nodulating plant receiving its nitrogen from the soil. Considering the lower nitrogen content of cereals, the yield cost to a hypothetical N-fixing cereal is predicted to be less than half that of soybean. Soybean growth was predicted to be c. 5% greater when the nodule nitrogen export products were amides versus ureides. This is the first metabolic reconstruction in a tropical crop species that simulates the entire plant and nodule metabolism. Going forward, this model will serve as a tool to investigate carbon use efficiency and key mechanisms within N-fixing symbiosis in a tropical species forming determinate nodules.

Is chloroplast size optimal for photosynthetic efficiency?

Improving photosynthetic efficiency has recently emerged as a promising way to increase crop production in a sustainable manner. While chloroplast size may affect photosynthetic efficiency in several ways, we aimed to explore whether chloroplast size manipulation can be a viable approach to improving photosynthetic performance. Several tobacco (Nicotiana tabacum) lines with contrasting chloroplast sizes were generated via manipulation of chloroplast division genes to assess photosynthetic performance under steady-state and fluctuating light. A selection of lines was included in a field trial to explore productivity. Lines with enlarged chloroplasts underperformed in most of the measured traits. Lines with smaller and more numerous chloroplasts showed a similar efficiency compared with wild-type (WT) tobacco. Chloroplast size only weakly affected light absorptance and light profiles within the leaf. Increasing chloroplast size decreased mesophyll conductance (gm ) but decreased chloroplast size did not increase gm . Increasing chloroplast size reduced chloroplast movements and enhanced non-photochemical quenching. The chloroplast smaller than WT appeared to be no better than WT for photosynthetic efficiency and productivity under field conditions. The results indicate that chloroplast size manipulations are therefore unlikely to lead to higher photosynthetic efficiency or growth.

Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels.

Biofuel and bioenergy systems are integral to most climate stabilization scenarios for displacement of transport sector fossil fuel use and for producing negative emissions via carbon capture and storage (CCS). However, the net greenhouse gas mitigation benefit of such pathways is controversial due to concerns around ecosystem carbon losses from land use change and foregone sequestration benefits from alternative land uses. Here, we couple bottom-up ecosystem simulation with models of cellulosic biofuel production and CCS in order to track ecosystem and supply chain carbon flows for current and future biofuel systems, with comparison to competing land-based biological mitigation schemes. Analyzing three contrasting US case study sites, we show that on land transitioning out of crops or pasture, switchgrass cultivation for cellulosic ethanol production has per-hectare mitigation potential comparable to reforestation and severalfold greater than grassland restoration. In contrast, harvesting and converting existing secondary forest at those sites incurs large initial carbon debt requiring long payback periods. We also highlight how plausible future improvements in energy crop yields and biorefining technology together with CCS would achieve mitigation potential 4 and 15 times greater than forest and grassland restoration, respectively. Finally, we show that recent estimates of induced land use change are small relative to the opportunities for improving system performance that we quantify here. While climate and other ecosystem service benefits cannot be taken for granted from cellulosic biofuel deployment, our scenarios illustrate how conventional and carbon-negative biofuel systems could make a near-term, robust, and distinctive contribution to the climate challenge.

Towards a dynamic photosynthesis model to guide yield improvement in C4 crops.

The most productive C4 food and biofuel crops, such as Saccharum officinarum (sugarcane), Sorghum bicolor (sorghum) and Zea mays (maize), all use NADP-ME-type C4 photosynthesis. Despite high productivities, these crops fall well short of the theoretical maximum solar conversion efficiency of 6%. Understanding the basis of these inefficiencies is key for bioengineering and breeding strategies to increase the sustainable productivity of these major C4 crops. Photosynthesis is studied predominantly at steady state in saturating light. In field stands of these crops light is continually changing, and often with rapid fluctuations. Although light may change in a second, the adjustment of photosynthesis may take many minutes, leading to inefficiencies. We measured the rates of CO2 uptake and stomatal conductance of maize, sorghum and sugarcane under fluctuating light regimes. The gas exchange results were combined with a new dynamic photosynthesis model to infer the limiting factors under non-steady-state conditions. The dynamic photosynthesis model was developed from an existing C4 metabolic model for maize and extended to include: (i) post-translational regulation of key photosynthetic enzymes and their temperature responses; (ii) dynamic stomatal conductance; and (iii) leaf energy balance. Testing the model outputs against measured rates of leaf CO2 uptake and stomatal conductance in the three C4 crops indicated that Rubisco activase, the pyruvate phosphate dikinase regulatory protein and stomatal conductance are the major limitations to the efficiency of NADP-ME-type C4 photosynthesis during dark-to-high light transitions. We propose that the level of influence of these limiting factors make them targets for bioengineering the improved photosynthetic efficiency of these key crops.

Welder's Anthrax: A Tale of 2 Cases.

Bacillus anthracis has traditionally been considered the etiologic agent of anthrax. However, anthrax-like illness has been documented in welders and other metal workers infected with Bacillus cereus group spp. harboring pXO1 virulence genes that produce anthrax toxins. We present 2 recent cases of severe pneumonia in welders with B. cereus group infections and discuss potential risk factors for infection and treatment options, including antitoxin.

Increased bundle-sheath leakiness of CO2 during photosynthetic induction shows a lack of coordination between the C4 and C3 cycles.

Use of a complete dynamic model of NADP-malic enzyme C4 photosynthesis indicated that, during transitions from dark or shade to high light, induction of the C4 pathway was more rapid than that of C3 , resulting in a predicted transient increase in bundle-sheath CO2 leakiness (ϕ). Previously, ϕ has been measured at steady state; here we developed a new method, coupling a tunable diode laser absorption spectroscope with a gas-exchange system to track ϕ in sorghum and maize through the nonsteady-state condition of photosynthetic induction. In both species, ϕ showed a transient increase to > 0.35 before declining to a steady state of 0.2 by 1500 s after illumination. Average ϕ was 60% higher than at steady state over the first 600 s of induction and 30% higher over the first 1500 s. The transient increase in ϕ, which was consistent with model prediction, indicated that capacity to assimilate CO2 into the C3 cycle in the bundle sheath failed to keep pace with the rate of dicarboxylate delivery by the C4 cycle. Because nonsteady-state light conditions are the norm in field canopies, the results suggest that ϕ in these major crops in the field is significantly higher and energy conversion efficiency lower than previous measured values under steady-state conditions.

Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes.

Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.

Guard-cell-targeted overexpression of Arabidopsis Hexokinase 1 can improve water use efficiency in field-grown tobacco plants.

Water deficit currently acts as one of the largest limiting factors for agricultural productivity worldwide. Additionally, limitation by water scarcity is projected to continue in the future with the further onset of effects of global climate change. As a result, it is critical to develop or breed for crops that have increased water use efficiency and that are more capable of coping with water scarce conditions. However, increased intrinsic water use efficiency (iWUE) typically brings a trade-off with CO2 assimilation as all gas exchange is mediated by stomata, through which CO2 enters the leaf while water vapor exits. Previously, promising results were shown using guard-cell-targeted overexpression of hexokinase to increase iWUE without incurring a penalty in photosynthetic rates or biomass production. Here, two homozygous transgenic tobacco (Nicotiana tabacum) lines expressing Arabidopsis Hexokinase 1 (AtHXK1) constitutively (35SHXK2 and 35SHXK5) and a line that had guard-cell-targeted overexpression of AtHXK1 (GCHXK2) were evaluated relative to wild type for traits related to photosynthesis and yield. In this study, iWUE was significantly higher in GCHXK2 compared with wild type without negatively impacting CO2 assimilation, although results were dependent upon leaf age and proximity of precipitation event to gas exchange measurement.

Field-grown ictB tobacco transformants show no difference in photosynthetic efficiency for biomass relative to the wild type.

In this study, four tobacco transformants overexpressing the inorganic carbon transporter B gene (ictB) were screened for photosynthetic performance relative to the wild type (WT) in field-based conditions. The WT and transgenic tobacco plants were evaluated for photosynthetic performance to determine the maximum rate of carboxylation (Vc, max), maximum rate of electron transport (Jmax), the photosynthetic compensation point (Γ*), quantum yield of PSII (ΦPSII), and mesophyll conductance (gm). Additionally, all plants were harvested to compare differences in above-ground biomass. Overall, transformants did not perform better than the WT on photosynthesis-, biomass-, and leaf composition-related traits. This is in contrast to previous studies that have suggested significant increases in photosynthesis and yield with the overexpression of ictB, although not widely evaluated under field conditions. These findings suggest that the benefit of ictB is not universal and may only be seen under certain growth conditions. While there is certainly still potential benefit to utilizing ictB in the future, further effort must be concentrated on understanding the underlying function of the gene and in which environmental conditions it offers the greatest benefit to crop performance. As it stands at present, it is possible that ictB overexpression may be largely favorable in controlled environments, such as greenhouses.

Photosynthesis in the fleeting shadows: an overlooked opportunity for increasing crop productivity?

Photosynthesis measurements are traditionally taken under steady-state conditions; however, leaves in crop fields experience frequent fluctuations in light and take time to respond. This slow response reduces the efficiency of carbon assimilation. Transitions from low to high light require photosynthetic induction, including the activation of Rubisco and the opening of stomata, whereas transitions from high to low light require the relaxation of dissipative energy processes, collectively known as non-photochemical quenching (NPQ). Previous attempts to assess the impact of these delays on net carbon assimilation have used simplified models of crop canopies, limiting the accuracy of predictions. Here, we use ray tracing to predict the spatial and temporal dynamics of lighting for a rendered mature Glycine max (soybean) canopy to review the relative importance of these delays on net cumulative assimilation over the course of both a sunny and a cloudy summer day. Combined limitations result in a 13% reduction in crop carbon assimilation on both sunny and cloudy days, with induction being more important on cloudy than on sunny days. Genetic variation in NPQ relaxation rates and photosynthetic induction in parental lines of a soybean nested association mapping (NAM) population was assessed. Short-term NPQ relaxation (<30 min) showed little variation across the NAM lines, but substantial variation was found in the speeds of photosynthetic induction, attributable to Rubisco activation. Over the course of a sunny and an intermittently cloudy day these would translate to substantial differences in total crop carbon assimilation. These findings suggest an unexplored potential for breeding improved photosynthetic potential in our major crops.

Multiscale computational models can guide experimentation and targeted measurements for crop improvement.

Computational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ-level architecture to increase productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single-scale models are unable to capture the critical cross-scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.