Explore the vast range of titles available.

Constrained to develop within the seed, the plant embryo must adapt its shape and size to fit the space available. Here, we demonstrate how this adjustment shapes metabolism of photosynthetic embryo. Noninvasive NMR-based imaging of the developing oilseed rape (Brassica napus) seed illustrates that, following embryo bending, gradients in lipid concentration became established. These were correlated with the local photosynthetic electron transport rate and the accumulation of storage products. Experimentally induced changes in embryo morphology and/or light supply altered these gradients and were accompanied by alterations in both proteome and metabolome. Tissue-specific metabolic models predicted that the outer cotyledon and hypocotyl/radicle generate the bulk of plastidic reductant/ATP via photosynthesis, while the inner cotyledon, being enclosed by the outer cotyledon, is forced to grow essentially heterotrophically. Under field-relevant highlight conditions, major contribution of the ribulose-1,5-bisphosphate carboxylase/oxygenase—bypass to seed storage metabolism is predicted for the outer cotyledon and the hypocotyl/radicle only. Differences between in vitro— versus in planta—grown embryos suggest that metabolic heterogeneity of embryo is not observable by in vitro approaches. We conclude that in vivo metabolic fluxes are locally regulated and connected to seed architecture, driving the embryo toward an efficient use of available light and space.

An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism, some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. This limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.

Seed oil content is a key agronomical trait, while the control of carbon allocation into different seed storage compounds is still poorly understood and hard to manipulate. Using bna572, a large-scale model of cellular metabolism in developing embryos of rapeseed (Brassica napus) oilseeds, we present an in silico approach for the analysis of carbon allocation into seed storage products. Optimal metabolic flux states were obtained by flux variability analysis based on minimization of the uptakes of substrates in the natural environment of the embryo. For a typical embryo biomass composition, flux sensitivities to changes in different storage components were derived. Upper and lower flux bounds of each reaction were categorized as oil or protein responsive. Among the most oil-responsive reactions were glycolytic reactions, while reactions related to mitochondrial ATP production were most protein responsive. To assess different biomass compositions, a tradeoff between the fractions of oil and protein was simulated. Based on flux-bound discontinuities and shadow prices along the tradeoff, three main metabolic phases with distinct pathway usage were identified. Transitions between the phases can be related to changing modes of the tricarboxylic acid cycle, reorganizing the usage of organic carbon and nitrogen sources for protein synthesis and acetylcoenzyme A for cytosol-localized fatty acid elongation. The phase close to equal oil and protein fractions included an unexpected pathway bypassing a-ketoglutarate-oxidizing steps in the tricarboxylic acid cycle. The in vivo relevance of the findings is discussed based on literature on seed storage metabolism.

The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) model and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for (13)C-Metabolic Flux Analysis ((13)C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from (13)C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). Using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content.

The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape ( Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) model and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis (13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). Using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content.

The processes involved in rice (Oryza sativa L.) panicle ripening vary with time and topological grain position. Methods to describe the functioning and connectivity of the grains on a panicle could aid the analysis of these processes. Hence, we addressed the difficulty of encoding and representing panicle topology. Array-based decomposition and computational methods were developed to encode and analyse panicle topology and grain traits. The technique, applied to the analysis of dry matter accumulation, clearly represented the basipetal succession of asynchronous grain ripening on a panicle. These methods should be useful for the spatial and temporal analysis of a number of panicle processes and attributes, including molecular ones, involved with ripening.

The ripening rice (Oryza sativa L.) caryopsis contains several maternal and embryonic tissues that transport assimilates along the partitioning pathway. Experimental access to transport steps in the pathway is limited by the separability of the tissues. Hence, the extent to which tissues can be mechanically and enzymatically separated was assessed. The caryopsis coat was isolated during mid-ripening, dissected and microscopically characterized. In centripetal order, the pericarp (epidermis, parenchyma-cell layer, cross-cell layer, tube-cell layer), inner integument, nucellar epidermis, aleurone layer and subaleurone layer adhered to each other. There was mechanical separation at the tube-cell layer, but not at the maternal/embryonic interface. Aleurone- and subaleurone-layer cells exposed on the inner surface of isolated caryopsis coats were macerated with Pectolyase Y-23 and manually sheared, which freed the endosperm and exposed the nucellar epidermis. Yield of endosperm cells increased linearly with the number of coats and reached a maximum after 1 h. The proportion of cells that were viable was approximately 10%. Subaleurone-layer cells contributed less than 25% to the yield. These results suggest that pectin polymers are necessary for adherence between the nucellar epidermis and the aleurone layer, and that enzymatic maceration is useful for separating the tissues at the maternal/embryonic interface.

The pleiotropic effects of the Rld1-O/+ mutation of Zea mays (Poaceae) on leaf phenotype include a suppression of normal transverse unrolling, a reversed top/bottom epidermal polarity, and an apparently straighter longitudinal shape. According to engineering shell theory, there might be mechanical coupling between transverse and longitudinal habit, i.e., the leaf rolling itself might produce the longitudinal straightening. We tested this possibility with quantitative curvature measurements and mechanical uncoupling experiments. The contributions of elastic bending under self weight, mechanical coupling, and rest state of leaf parts to the longitudinal and transverse habit were assessed in Rld1-O/+ mutants and a population of sibling +/+ segregants. Elastic bending and curvature coupling are shown to be relatively unimportant. The Rld1-O/+ mutation is shown to alter not only the unrolling process, but also the developmental longitudinal curving in the growing leaf, leading to a straighter midrib and a rolled lamina. The Rld1-O/+ mutant is thus a suitable model to study the relation between tissue polarity and differential curvature development in the maize leaf. Since on the abaxial side of the leaf, more abundant sclerenchyma is found in +/+ than in Rld1-O/+, a gradient in sclerification may contribute to the development of midrib curvature.

Introduction Dementia is currently one of the leading causes of mortality globally, and mortality due to dementia will likely increase in the future along with corresponding increases in population growth and population aging. However, large inconsistencies in coding practices in vital registration systems over time and between countries complicate the estimation of global dementia mortality. Methods We meta‐analyzed the excess risk of death in those with dementia and multiplied these estimates by the proportion of dementia deaths occurring in those with severe, end‐stage disease to calculate the total number of deaths that could be attributed to dementia. Results We estimated that there were 1.62 million (95% uncertainty interval [UI]: 0.41–4.21) deaths globally due to dementia in 2019. More dementia deaths occurred in women (1.06 million [0.27–2.71]) than men (0.56 million [0.14–1.51]), largely but not entirely due to the higher life expectancy in women (age‐standardized female‐to‐male ratio 1.19 [1.10–1.26]). Due to population aging, there was a large increase in all‐age mortality rates from dementia between 1990 and 2019 (100.1% [89.1–117.5]). In 2019, deaths due to dementia ranked seventh globally in all ages and fourth among individuals 70 and older compared to deaths from other diseases estimated in the Global Burden of Disease (GBD) study. Discussion Mortality due to dementia represents a substantial global burden, and is expected to continue to grow into the future as an older, aging population expands globally.

Background Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study ( n  = 744) and the 2000 wave of the HRS study ( n  = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys.