High Flux Through the Oxidative Pentose Phosphate Pathway Lowers Efficiency in Developing Camelina Seeds.

Many seeds are green during development, and light has been shown to play a role in the efficiency with which maternally supplied substrates are converted into storage compounds. However, the effects of light on the fluxes through central metabolism that determine this efficiency are poorly understood. Here, we used metabolic flux analysis to determine the effects of light on central metabolism in developing embryos of false flax (Camelina sativa). Metabolic efficiency in C. sativa is of interest because, despite its growing importance as a model oilseed and engineering target and its potential as a biofuel crop, its yields are lower than other major oilseed species. Culture conditions under which steady-state growth and composition of developing embryos match those in planta were used to quantify substrate uptake and respiration rates. The carbon conversion efficiency (CCE) was 21% ± 3% in the dark and 42% ± 4% under high light. Under physiological illumination, the CCE (32% ± 2%) was substantially lower than in green and nongreen oilseeds studied previously. 13C and 14C isotopic labeling experiments were used together with computer-aided modeling to map fluxes through central metabolism. Fluxes through the oxidative pentose phosphate pathway (OPPP) were the principal source of CO2 production and strongly negatively correlated with CCE across light levels. OPPP fluxes were greatly in excess of demand for NAD(P)H for biosynthesis and larger than those measured in other systems. Excess reductant appears to be dissipated via cyanide-insensitive respiration. OPPP enzymes therefore represent a potential target for increasing efficiency and yield in C. sativa.

Correction: Genome, Functional Gene Annotation, and Nuclear Transformation of the Heterokont Oleaginous Alga Nannochloropsis oceanica CCMP1779.

[This corrects the article DOI: 10.1371/journal.pgen.1003064.].

Unfair trade underground revealed by integrating data with Nash bargaining models.

Mutually beneficial resource exchange is fundamental to global biogeochemical cycles and plant and animal nutrition. However, there is inherent potential conflict in mutualisms, as each organism benefits more when the exchange ratio ('price') minimizes its own costs and maximizes its benefits. Understanding the bargaining power that each partner has in these interactions is key to our ability to predict the exchange ratio and therefore the functionality of the cell, organism, community and ecosystem. We tested whether partners have symmetrical ('fair') or asymmetrical ('unfair') bargaining power in a legume-rhizobia nitrogen-fixing symbiosis using measurements of carbon and nitrogen dynamics in a mathematical modeling framework derived from economic theory. A model of symmetric bargaining power was not consistent with our data. Instead, our data indicate that the growth benefit to the plant (Medicago truncatula) has greater weight in determining trade dynamics than the benefit to the bacteria. Quantitative estimates of the relative power of the plant revealed that the plant's influence rises as soil nitrogen availability decreases and trade benefits to both partners increase. Our finding that M. truncatula legumes have more bargaining power than their rhizobial partner at lower nitrogen availabilities highlights the importance of context-dependence for the evolution of mutualism with increasing nutrient deposition.

Modelling nutritional mutualisms: challenges and opportunities for data integration.

Nutritional mutualisms are ancient, widespread, and profoundly influential in biological communities and ecosystems. Although much is known about these interactions, comprehensive answers to fundamental questions, such as how resource availability and structured interactions influence mutualism persistence, are still lacking. Mathematical modelling of nutritional mutualisms has great potential to facilitate the search for comprehensive answers to these and other fundamental questions by connecting the physiological and genomic underpinnings of mutualisms with ecological and evolutionary processes. In particular, when integrated with empirical data, models enable understanding of underlying mechanisms and generalisation of principles beyond the particulars of a given system. Here, we demonstrate how mathematical models can be integrated with data to address questions of mutualism persistence at four biological scales: cell, individual, population, and community. We highlight select studies where data has been or could be integrated with models to either inform model structure or test model predictions. We also point out opportunities to increase model rigour through tighter integration with data, and describe areas in which data is urgently needed. We focus on plant-microbe systems, for which a wealth of empirical data is available, but the principles and approaches can be generally applied to any nutritional mutualism.

Analysis of Loss-of-Function Mutants in Aspartate Kinase and Homoserine Dehydrogenase Genes Points to Complexity in the Regulation of Aspartate-Derived Amino Acid Contents.

Biosynthesis of aspartate (Asp)-derived amino acids lysine (Lys), methionine (Met), threonine (Thr), and isoleucine involves monofunctional Asp kinases (AKs) and dual-functional Asp kinase-homoserine dehydrogenases (AK-HSDHs). Four-week-old loss-of-function Arabidopsis (Arabidopsis thaliana) mutants in the AK-HSDH2 gene had increased amounts of Asp and Asp-derived amino acids, especially Thr, in leaves. To explore mechanisms behind this phenotype, we obtained single mutants for other AK and AK-HSDH genes, generated double mutants from ak-hsdh2 and ak mutants, and performed free and protein-bound amino acid profiling, transcript abundance, and activity assays. The increases of Asp, Lys, and Met in ak-hsdh2 were also observed in ak1-1, ak2-1, ak3-1, and ak-hsdh1-1. However, the Thr increase in ak-hsdh2 was observed in ak-hsdh1-1 but not in ak1-1, ak2-1, or ak3-1. Activity assays showed that AK2 and AK-HSDH1 are the major contributors to overall AK and HSDH activities, respectively. Pairwise correlation analysis revealed positive correlations between the amount of AK transcripts and Lys-sensitive AK activity and between the amount of AK-HSDH transcripts and both Thr-sensitive AK activity and total HSDH activity. In addition, the ratio of total AK activity to total HSDH activity negatively correlates with the ratio of Lys to the total amount of Met, Thr, and isoleucine. These data led to the hypothesis that the balance between Lys-sensitive AKs and Thr-sensitive AK-HSDHs is important for maintaining the amounts and ratios of Asp-derived amino acids.

Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779.

Unicellular marine algae have promise for providing sustainable and scalable biofuel feedstocks, although no single species has emerged as a preferred organism. Moreover, adequate molecular and genetic resources prerequisite for the rational engineering of marine algal feedstocks are lacking for most candidate species. Heterokonts of the genus Nannochloropsis naturally have high cellular oil content and are already in use for industrial production of high-value lipid products. First success in applying reverse genetics by targeted gene replacement makes Nannochloropsis oceanica an attractive model to investigate the cell and molecular biology and biochemistry of this fascinating organism group. Here we present the assembly of the 28.7 Mb genome of N. oceanica CCMP1779. RNA sequencing data from nitrogen-replete and nitrogen-depleted growth conditions support a total of 11,973 genes, of which in addition to automatic annotation some were manually inspected to predict the biochemical repertoire for this organism. Among others, more than 100 genes putatively related to lipid metabolism, 114 predicted transcription factors, and 109 transcriptional regulators were annotated. Comparison of the N. oceanica CCMP1779 gene repertoire with the recently published N. gaditana genome identified 2,649 genes likely specific to N. oceanica CCMP1779. Many of these N. oceanica-specific genes have putative orthologs in other species or are supported by transcriptional evidence. However, because similarity-based annotations are limited, functions of most of these species-specific genes remain unknown. Aside from the genome sequence and its analysis, protocols for the transformation of N. oceanica CCMP1779 are provided. The availability of genomic and transcriptomic data for Nannochloropsis oceanica CCMP1779, along with efficient transformation protocols, provides a blueprint for future detailed gene functional analysis and genetic engineering of Nannochloropsis species by a growing academic community focused on this genus.

Enhancing Trifocal Leadership Practices Using Simulation in a Pediatric Charge Nurse Orientation Program.

A well-established charge nurse orientation program was enhanced with the addition of a simulation, addressing three primary populations (the trifocus) with whom charge nurses interact: patients, patients' parents, and other staff members. In this pilot quality improvement project, 20 staff nurses enrolled in the orientation program and were assigned a mentor. Only one participant used the mentorship opportunity; therefore, it is not discussed here. Twelve nurses completed all charge nurse classes and a simulation scenario of caring for a deteriorating infant. The nurses were given an opportunity to reflect on leadership practices after the simulation. Thematic analysis from qualitative, reflective data supported the enhanced understanding of managing complex patients, a code situation, and teams; guiding a team's novice nurse; leading as a charge nurse; and using clinical and critical thinking skills. All nurses reported that the simulation as experiential learning helped them to meet their leadership goals.

Elucidation of Triacylglycerol Overproduction in the C4 Bioenergy Crop Sorghum bicolor by Constraint-Based Analysis.

Upregulation of triacylglycerols (TAGs) in vegetative plant tissues such as leaves has the potential to drastically increase the energy density and biomass yield of bioenergy crops. In this context, constraint-based analysis has the promise to improve metabolic engineering strategies. Here we present a core metabolism model for the C4 biomass crop Sorghum bicolor (iTJC1414) along with a minimal model for photosynthetic CO2 assimilation, sucrose and TAG biosynthesis in C3 plants. Extending iTJC1414 to a four-cell diel model we simulate C4 photosynthesis in mature leaves with the principal photo-assimilatory product being replaced by TAG produced at different levels. Independent of specific pathways and per unit carbon assimilated, energy content and biosynthetic demands in reducing equivalents are about 1.3 to 1.4 times higher for TAG than for sucrose. For plant generic pathways, ATP- and NADPH-demands per CO2 assimilated are higher by 1.3- and 1.5-fold, respectively. If the photosynthetic supply in ATP and NADPH in iTJC1414 is adjusted to be balanced for sucrose as the sole photo-assimilatory product, overproduction of TAG is predicted to cause a substantial surplus in photosynthetic ATP. This means that if TAG synthesis was the sole photo-assimilatory process, there could be an energy imbalance that might impede the process. Adjusting iTJC1414 to a photo-assimilatory rate that approximates field conditions, we predict possible daily rates of TAG accumulation, dependent on varying ratios of carbon partitioning between exported assimilates and accumulated oil droplets (TAG, oleosin) and in dependence of activation of futile cycles of TAG synthesis and degradation. We find that, based on the capacity of leaves for photosynthetic synthesis of exported assimilates, mature leaves should be able to reach a 20% level of TAG per dry weight within one month if only 5% of the photosynthetic net assimilation can be allocated into oil droplets. From this we conclude that high TAG levels should be achievable if TAG synthesis is induced only during a final phase of the plant life cycle.

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models.

Mathematical modeling of plant metabolism enables the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In the many studies using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For 13C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.