Have We Selected for Higher Mesophyll Conductance in Domesticating Soybean?

Soybean (Glycine max) is the single most important global source of vegetable protein. Yield improvements per unit land area are needed to avoid further expansion onto natural systems. Mesophyll conductance (gm) quantifies the ease with which CO2 can diffuse from the sub-stomatal cavity to Rubisco. Increasing gm is attractive since it increases photosynthesis without increasing water use. Most measurements of gm have been made during steady-state light saturated photosynthesis. In field crop canopies, light fluctuations are frequent and the speed with which gm can increase following shade to sun transitions affects crop carbon gain. Is there variability in gm within soybean germplasm? If so, indirect selection may have indirectly increased gm during domestication and subsequent breeding for sustainability and yield. A modern elite cultivar (LD11) was compared with four ancestor accessions of Glycine soja from the assumed area of domestication by concurrent measurements of gas exchange and carbon isotope discrimination (∆13C). gm was a significant limitation to soybean photosynthesis both at steady state and through light induction but was twice the value of the ancestors in LD11. This corresponded to a substantial increase in leaf photosynthetic CO2 uptake and water use efficiency.

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.

European soybean to benefit people and the environment.

Europe imports large amounts of soybean that are predominantly used for livestock feed, mainly sourced from Brazil, USA and Argentina. In addition, the demand for GM-free soybean for human consumption is project to increase. Soybean has higher protein quality and digestibility than other legumes, along with high concentrations of isoflavones, phytosterols and minerals that enhance the nutritional value as a human food ingredient. Here, we examine the potential to increase soybean production across Europe for livestock feed and direct human consumption, and review possible effects on the environment and human health. Simulations and field data indicate rainfed soybean yields of 3.1 ± 1.2 t ha-1 from southern UK through to southern Europe (compared to a 3.5 t ha-1 average from North America). Drought-prone southern regions and cooler northern regions require breeding to incorporate stress-tolerance traits. Literature synthesized in this work evidenced soybean properties important to human nutrition, health, and traits related to food processing compared to alternative protein sources. While acknowledging the uncertainties inherent in any modelling exercise, our findings suggest that further integrating soybean into European agriculture could reduce GHG emissions by 37-291 Mt CO2e year-1 and fertiliser N use by 0.6-1.2 Mt year-1, concurrently improving human health and nutrition.

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.

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.

Impact of genotype-calling methodologies on genome-wide association and genomic prediction in polyploids.

Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost-efficient genotyping using next-generation sequencing. However, accurate genotype calling from next-generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome-wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype-calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum, and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype-calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost-efficiently implement GWAS and genomic prediction in polyploid crops.

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.

Two decades of fumigation data from the Soybean Free Air Concentration Enrichment facility.

The Soybean Free Air Concentration Enrichment (SoyFACE) facility is the longest running open-air carbon dioxide and ozone enrichment facility in the world. For over two decades, soybean, maize, and other crops have been exposed to the elevated carbon dioxide and ozone concentrations anticipated for late this century. The facility, located in East Central Illinois, USA, exposes crops to different atmospheric concentrations in replicated octagonal ~280 m2 Free Air Concentration Enrichment (FACE) treatment plots. Each FACE plot is paired with an untreated control (ambient) plot. The experiment provides important ground truth data for predicting future crop productivity. Fumigation data from SoyFACE were collected every four seconds throughout each growing season for over two decades. Here, we organize, quality control, and collate 20 years of data to facilitate trend analysis and crop modeling efforts. This paper provides the rationale for and a description of the SoyFACE experiments, along with a summary of the fumigation data and collation process, weather and ambient data collection procedures, and explanations of air pollution metrics and calculations.

Improving crop yield potential: Underlying biological processes and future prospects.

The growing world population and global increases in the standard of living both result in an increasing demand for food, feed and other plant-derived products. In the coming years, plant-based research will be among the major drivers ensuring food security and the expansion of the bio-based economy. Crop productivity is determined by several factors, including the available physical and agricultural resources, crop management, and the resource use efficiency, quality and intrinsic yield potential of the chosen crop. This review focuses on intrinsic yield potential, since understanding its determinants and their biological basis will allow to maximize the plant's potential in food and energy production. Yield potential is determined by a variety of complex traits that integrate strictly regulated processes and their underlying gene regulatory networks. Due to this inherent complexity, numerous potential targets have been identified that could be exploited to increase crop yield. These encompass diverse metabolic and physical processes at the cellular, organ and canopy level. We present an overview of some of the distinct biological processes considered to be crucial for yield determination that could further be exploited to improve future crop productivity.

Nutritional Modulation of Sleep Latency, Duration, and Efficiency: A Randomized, Repeated-Measures, Double-Blind Deception Study.

PURPOSE: This study aimed to test the hypothesis that a novel nutritional blend composed of tryptophan, glycine, magnesium, tart cherry powder, and l -theanine enhances subjective and objective measures of sleep during free living conditions. METHODS: In a randomized, repeated-measures crossover and double-blind deception design, participants ( n = 9 males and 7 females, age = 24 ± 3 yr, body mass = 69.8 ± 11.6 kg, stature = 170.8 ± 9.1 cm) completed a 3-d familiarization period, followed by 3-d intervention and placebo trials. Subjective Pittsburgh Quality Sleep Index, Core Consensus Sleep Diary, and Karolinska Sleepiness Scale survey tools, alongside objective actigraphy measures of sleep, were assessed, with daily nutritional intake, activity, and light exposure standardized between trials. Participants provided daily urine samples for assessment of targeted and untargeted metabolomes. RESULTS: The intervention trial reduced sleep onset latency (-24 ± 25 min; P = 0.002), increased total sleep time (22 ± 32 min; P = 0.01), and increased sleep efficiency (2.4% ± 3.9%; P = 0.03), while also reducing morning sleepiness ( P = 0.02). Throughout the study, 75% of participants remained blinded to sleep assessment as a primary outcome measure, with 56% subjectively indicating improved sleep during the intervention trial. Metabolomic analysis highlighted several significantly altered metabolomes related to sleep regulation between trials, inclusive of 6-sulfatoxymelatonin, d -serine, and l -glutamic acid. CONCLUSIONS: Data demonstrate that using the proposed blend of novel nutritional ingredients during free living conditions reduced sleep onset latency, increased total sleep duration, and increased sleep efficiency, leading to reduced perceptions of morning sleepiness. These effects may be mediated by the upregulation of key metabolites involved in the neurophysiological modulation of the sleep/wake cycle.

To have value, comparisons of high-throughput phenotyping methods need statistical tests of bias and variance.

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson's correlation coefficient (r) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method.

Mechanisms of ion selectivity and throughput in the mitochondrial calcium uniporter.

The mitochondrial calcium uniporter, which regulates aerobic metabolism by catalyzing mitochondrial Ca2+ influx, is arguably the most selective ion channel known. The mechanisms for this exquisite Ca2+ selectivity have not been defined. Here, using a reconstituted system, we study the electrical properties of the channel's minimal Ca2+-conducting complex, MCU-EMRE, from Tribolium castaneum to probe ion selectivity mechanisms. The wild-type TcMCU-EMRE complex recapitulates hallmark electrophysiological properties of endogenous Uniporter channels. Through interrogation of pore-lining mutants, we find that a ring of glutamate residues, the "E-locus," serves as the channel's selectivity filter. Unexpectedly, a nearby "D-locus" at the mouth of the pore has diminutive influence on selectivity. Anomalous mole fraction effects indicate that multiple Ca2+ ions are accommodated within the E-locus. By facilitating ion-ion interactions, the E-locus engenders both exquisite Ca2+ selectivity and high ion throughput. Direct comparison with structural information yields the basis for selective Ca2+ conduction by the channel.

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.

Soybean photosynthesis and crop yield are improved by accelerating recovery from photoprotection.

Crop leaves in full sunlight dissipate damaging excess absorbed light energy as heat. This protective dissipation continues after the leaf transitions to shade, reducing crop photosynthesis. A bioengineered acceleration of this adjustment increased photosynthetic efficiency and biomass in tobacco in the field. But could that also translate to increased yield in a food crop? Here we bioengineered the same change into soybean. In replicated field trials, photosynthetic efficiency in fluctuating light was higher and seed yield in five independent transformation events increased by up to 33%. Despite increased seed quantity, seed protein and oil content were unaltered. This validates increasing photosynthetic efficiency as a much needed strategy toward sustainably increasing crop yield in support of future global food security.

Severe Pertussis Infection With Hyperleukocytosis in a 10-Month-Old Unvaccinated Amish Female: A Case Report.

Bordetella pertussis (B. pertussis) commonly infects individuals of all ages. However, pertussis, the disease caused by B. pertussis infection, is most severe in young infants. Severe pertussis, defined by the presence of refractory hypoxemia, pneumonia, cardiogenic shock, and hyperleukocytosis, is associated with significant morbidity and mortality. Both hyperleukocytosis and pulmonary hypertension have been found to be predictive of mortality in young infants. Leukoreductive strategies such as leukapheresis and exchange transfusion have been employed to treat these complications. Pulmonary hypertension is thought to be a result of aggregation of white blood cells in pulmonary vasculature; however, studies have suggested that the mechanism of pulmonary hypertension is multifactorial. We report a case of a 10-month-old unvaccinated Amish female with pertussis complicated by an initial hyperleukocytosis of 204,900 103/uL successfully treated with leukapheresis in our pediatric intensive care unit. This infant never showed signs of pulmonary hypertension, which is often associated with hyperleukocytosis in severe or fatal cases of pertussis in infants and neonates. To our knowledge, this is the most significant degree of hyperleukocytosis reported in pertussis. The findings in this case support the clinical utility of leukoreductive therapy in severe pertussis and provide some evidence that the mechanism of pulmonary hypertension in these patients is multifactorial.

Drought imprints on crops can reduce yield loss: Nature's insights for food security.

The Midwestern "Corn-Belt" in the United States is the most productive agricultural region on the planet despite being predominantly rainfed. In this region, global climate change is driving precipitation patterns toward wetter springs and drier mid- to late-summers, a trend that is likely to intensify in the future. The lack of precipitation can lead to crop water limitations that ultimately impact growth and yields. Young plants exposed to water stress will often invest more resources into their root systems, possibly priming the crop for any subsequent mid- or late-season drought. The trend toward wetter springs, however, suggests that opportunities for crop priming may lessen in the future. Here, we test the hypothesis that early season dry conditions lead to drought priming in field-grown crops and this response will protect crops against growth and yield losses from late-season droughts. This hypothesis was tested for the two major Midwestern crop, maize and soybean, using high-resolution daily weather data, satellite-derived phenological metrics, field yield data, and ecosystem-scale model (Agricultural Production System Simulator) simulations. The results from this study showed that priming mitigated yield losses from a late season drought of up to 4.0% and 7.0% for maize and soybean compared with unprimed crops experiencing a late season drought. These results suggest that if the trend toward wet springs with drier summers continues, the relative impact of droughts on crop productivity is likely to worsen. Alternatively, identifying opportunities to breed or genetically modify pre-primed crop species may provide improved resilience to future climate change.