The rate of nitrite reduction in leaves as indicated by O2 and CO2 exchange during photosynthesis

Light response (at 300 ppm CO2 and 10–50 ppm O2 in N2) and CO2 response curves [at absorbed photon fluence rate (PAD) of 550 μmol m−2 s−1] of O2 evolution and CO2 uptake were measured in tobacco (Nicotiana tabacum L.) leaves grown on either NO3− or NH4+ as N source and in potato (Solanum tuberosum L.), sorghum (Sorghum bicolor L. Moench), and amaranth (Amaranthus cruentus L.) leaves grown on NH4NO3. Photosynthetic O2 evolution in excess of CO2 uptake was measured with a stabilized zirconia O2 electrode and an infrared CO2 analyser, respectively, and the difference assumed to represent the rate of electron flow to acceptors alternative to CO2, mainly NO2−, SO42−, and oxaloacetate. In NO3−-grown tobacco, as well as in sorghum, amaranth, and young potato, the photosynthetic O2–CO2 flux difference rapidly increased to about 1 μmol m−2 s−1 at very low PADs and the process was saturated at 50 μmol quanta m−2 s−1. At higher PADs the O2–CO2 flux difference continued to increase proportionally with the photosynthetic rate to a maximum of about 2 μmol m−2 s−1. In NH4+-grown tobacco, as well as in potato during tuber filling, the low-PAD component of surplus O2 evolution was virtually absent. The low-PAD phase was ascribed to photoreduction of NO2− which successfully competes with CO2 reduction and saturates at a rate of about 1 μmol O2 m−2 s−1 (9% of the maximum O2 evolution rate). The high-PAD component of about 1 μmol O2 m−2 s−1, superimposed on NO2− reduction, may represent oxaloacetate reduction. The roles of NO2−, oxaloacetate, and O2 reduction in the regulation of ATP/NADPH balance are discussed

Systematic Analysis of Stability Patterns in Plant Primary Metabolism

Metabolic networks are characterized by complex interactions and regulatory mechanisms between many individual components. These interactions determine whether a steady state is stable to perturbations. Structural kinetic modeling (SKM) is a framework to analyze the stability of metabolic steady states that allows the study of the system Jacobian without requiring detailed knowledge about individual rate equations. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. Until now, SKM experiments applied univariate tests to detect the network components with the largest influence on stability. In this work, we present an extended SKM approach relying on supervised machine learning to detect patterns of enzyme-metabolite interactions that act together in an orchestrated manner to ensure stability. We demonstrate its application on a detailed SK-model of the Calvin-Benson cycle and connected pathways. The identified stability patterns are highly complex reflecting that changes in dynamic properties depend on concerted interactions between several network components. In total, we find more patterns that reliably ensure stability than patterns ensuring instability. This shows that the design of this system is strongly targeted towards maintaining stability. We also investigate the effect of allosteric regulators revealing that the tendency to stability is significantly increased by including experimentally determined regulatory mechanisms that have not yet been integrated into existing kinetic models

Advances in the Molecular Pathophysiology, Genetics, and Treatment of Primary Ovarian Insufficiency

Primary ovarian insufficiency (POI) affects similar to 1% of women before 40 years of age. The recent leap in genetic knowledge obtained by next generation sequencing (NGS) together with animal models has further elucidated its molecular pathogenesis, identifying novel genes/pathways. Mutations of > 60 genes emphasize high genetic heterogeneity. Genome-wide association studies have revealed a shared genetic background between POI and reproductive aging. NGS will provide a genetic diagnosis leading to genetic/therapeutic counseling: first, defects in meiosis or DNA repair genes may predispose to tumors; and second, specific gene defects may predict the risk of rapid loss of a persistent ovarian reserve, an important determinant in fertility preservation. Indeed, a recent innovative treatment of POI by in vitro activation of dormant follicles proved to be successful.Peer reviewe

Large-Scale Genome-Wide Meta-Analysis of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture for Different Diagnosis Criteria

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health

Overexpression of the Rieske FeS protein of the Cytochrome b 6 f complex increases C4 photosynthesis in Setaria viridis.

C4 photosynthesis is characterised by a CO2 concentrating mechanism that operates between mesophyll and bundle sheath cells increasing CO2 partial pressure at the site of Rubisco and photosynthetic efficiency. Electron transport chains in both cell types supply ATP and NADPH for C4 photosynthesis. Cytochrome b 6 f is a key control point of electron transport in C3 plants. To study whether C4 photosynthesis is limited by electron transport we constitutively overexpressed the Rieske FeS subunit in Setaria viridis. This resulted in a higher Cytochrome b 6 f content in mesophyll and bundle sheath cells without marked changes in the abundances of other photosynthetic proteins. Rieske overexpression plants showed better light conversion efficiency in both Photosystems and could generate higher proton-motive force across the thylakoid membrane underpinning an increase in CO2 assimilation rate at ambient and saturating CO2 and high light. Our results demonstrate that removing electron transport limitations can increase C4 photosynthesis

Global Biobank Meta-analysis Initiative:Powering genetic discovery across human disease

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.</p