Regulation of growth by the trehalose pathway: Relationship to temperature and sucrose

Carbon signaling can override carbon supply in the regulation of growth. At least some of this regulation is imparted by the sugar signal trehalose 6-phosphate (T6P) through the protein kinase, SnRK1. This signaling pathway regulates biosynthetic processes involved in growth under optimal growing conditions. Recently, using a seedling system we showed that under sub-optimal conditions, such as cold, carbon signaling by T6P/ SnRK1 enables recovery of growth following relief of the stress. The T6P/ SnRK1 mechanism thus could be selected as a means of improving low temperature tolerance. High-throughput automated Fv/Fm measurements provide a potential means to screen for T6P/ SnRK1, and here we confirm through measurements of Fv/Fm in rosettes that T6P promotes low temperature tolerance and recovery during cold to warm transfer. Further, to better understand the coordination between sugars, trehalose pathway, and temperature-dependent growth, we examine the interrelationship between sugars, trehalose phosphate synthase (TPS), and trehalose phosphate phosphatase (TPP) gene expression and T6P content in seedlings. Sucrose, particularly when fed exogenously, correlated well with TPS1 and TPPB gene expression, suggesting that these enzymes are involved in maintaining carbon flux through the pathway in relation to sucrose supply. However, when sucrose accumulated to higher levels under low temperature and low N, TPS1 and TPPB expression were less directly related to sucrose; other factors may also contribute to regulation of TPS1 and TPPB expression under these conditions. TPPA expression was not related to sucrose content and all genes were not well correlated with endogenous glucose. Our work has implications for understanding acclimation to sink-limited growth conditions such as low temperature and for screening cold-tolerant genotypes with altered T6P/ SnRK1 signaling.     

Aerobic Fitness in Children and Young Adults with Primary Ciliary Dyskinesia

Background

Although aerobic fitness is regarded as an overall prognostic measure of morbidity and mortality, its evaluation in the chronic progressive sinopulmonary disease primary ciliary dyskinesia (PCD) has been infrequently and inconsistently reported. Here we assessed peak oxygen uptake (VO_2peak) in a large well-characterized cohort of PCD patients, and explored whether VO_2peak was associated with parameters of pulmonary function, self-reported physical limitations, and physical activity level.

Methods

VO_2peak, spirometry, diffusing capacity, whole-body plethysmography, and nitrogen multiple breath inert gas washout (N₂ MBW) were assessed in a cross-sectional, single-occasion study of clinically stable children and young adults with PCD. We used a questionnaire including self-reported physical limitations in everyday life or in vigorous activities, and estimation of weekly hours of strenuous physical activity. VO_2peak in PCD patients was compared with that in matched, healthy control subjects and a national reference.

Results

Forty-four PCD patients aged 6–29 years exhibited reduced VO_2peak compared to healthy controls (P<0.001) and the national reference. VO_2peak was abnormal (z-score <–1.96) in 34% of PCD patients. Spirometric values, RV/TLC, and indices of N₂ MBW were significantly abnormal, but VO_2peak only correlated with FEV₁ and DL_CO/V_A. VO_2peak correlated with complaints of moderate or significant limitations in vigorous activities (P = 0.0001), exhibited by 39% of PCD patients.

Conclusion

One-third of PCD patients exhibited substantially lower aerobic fitness than healthy subjects. Aerobic fitness correlated with FEV₁, DL_CO/V_A and self-reported complaints of limitations in vigorous physical activity. These findings are most likely explained by PCD pulmonary disease and its impact on pulmonary function and physical ability. Considering fitness as an important outcome and including regular strenuous physical activity in PCD treatment would probably altogether increase pulmonary clearance, lung function, aerobic fitness, and quality of life, and prevent lifestyle-related diseases.     

Galectin-4 Reduces Migration and Metastasis Formation of Pancreatic Cancer Cells

Galectin-4 (Gal-4) is a member of the galectin family of glycan binding proteins that shows a significantly higher expression in cystic tumors of the human pancreas and in pancreatic adenocarcinomas compared to normal pancreas. However, the putative function of Gal-4 in tumor progression of pancreatic cancer is still incompletely understood. In this study the role of Gal-4 in cancer progression was investigated, using a set of defined pancreatic cancer cell lines, Pa-Tu-8988S (PaTu-S) and Pa-Tu-8988T (PaTu-T), as a model. These two cell lines are derived from the same liver metastasis of a human primary pancreatic adenocarcinoma, but differ in their growth characteristics and metastatic capacity. We demonstrated that Gal-4 expression is high in PaTu-S, which shows poor migratory properties, whereas much lower Gal-4 levels are observed in the highly metastatic cell line PaTu-T. In PaTu-S, Gal-4 is found in the cytoplasm, but it is also secreted and accumulates at the membrane at sites of contact with neighboring cells. Moreover, we show that Gal-4 inhibits metastasis formation by delaying migration of pancreatic cancer cells in vitro using a scratch assay, and in vivo using zebrafish (Danio rerio) as an experimental model. Our data suggest that Gal-4 may act at the cell-surface of PaTu-S as an adhesion molecule to prevent release of the tumor cells, but has in addition a cytosolic function by inhibiting migration via a yet unknown mechanism.     

Measurement,model prediction and uncertainty quantification of plasma clearance of cerium citrate in humans

Radiation and Environmental Biophysics - Double tracer studies in healthy human volunteers with stable isotopes of cerium citrate were performed with the aim of investigating the gastro-intestinal...     

Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale

Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement.Plants are of vital significance as a source of food (Grusak and DellaPenna, 1999; Rogalski and Carrer, 2011), feed (Lu et al., 2011), energy (Tilman et al., 2006; Parmar et al., 2011), and feedstocks for the chemical industry (Metzger and Bornscheuer, 2006; Kinghorn et al., 2011). Given the close connection between plant metabolism and the usability of plant products, there is a growing interest in understanding and predicting the behavior and regulation of plant metabolic processes. In order to increase crop quality and yield, there is a need for methods guiding the rational redesign of the plant metabolic network (Schwender, 2009).Mathematical modeling of plant metabolism offers new approaches to understand, predict, and modify complex plant metabolic processes. In plant research, the issue of metabolic modeling is constantly gaining attention, and different modeling approaches applied to plant metabolism exist, ranging from highly detailed quantitative to less complex qualitative approaches (for review, see Giersch, 2000; Morgan and Rhodes, 2002; Poolman et al., 2004; Rios-Estepa and Lange, 2007).A widely used modeling approach is flux balance analysis (FBA), which allows the prediction of metabolic capabilities and steady-state fluxes under different environmental and genetic backgrounds using (non)linear optimization (Orth et al., 2010). Assuming steady-state conditions, FBA has the advantage of not requiring the knowledge of kinetic parameters and, therefore, can be applied to model detailed, large-scale systems. In recent years, the FBA approach has been applied to several different plant species, such as maize (Zea mays; Dal’Molin et al., 2010; Saha et al., 2011), barley (Hordeum vulgare; Grafahrend-Belau et al., 2009b; Melkus et al., 2011; Rolletschek et al., 2011), rice (Oryza sativa; Lakshmanan et al., 2013), Arabidopsis (Arabidopsis thaliana; Poolman et al., 2009; de Oliveira Dal’Molin et al., 2010; Radrich et al., 2010; Williams et al., 2010; Mintz-Oron et al., 2012; Cheung et al., 2013), and rapeseed (Brassica napus; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011), as well as algae (Boyle and Morgan, 2009; Cogne et al., 2011; Dal’Molin et al., 2011) and photoautotrophic bacteria (Knoop et al., 2010; Montagud et al., 2010; Boyle and Morgan, 2011). These models have been used to study different aspects of metabolism, including the prediction of optimal metabolic yields and energy efficiencies (Dal’Molin et al., 2010; Boyle and Morgan, 2011), changes in flux under different environmental and genetic backgrounds (Grafahrend-Belau et al., 2009b; Dal’Molin et al., 2010; Melkus et al., 2011), and nonintuitive metabolic pathways that merit subsequent experimental investigations (Poolman et al., 2009; Knoop et al., 2010; Rolletschek et al., 2011). Although FBA of plant metabolic models was shown to be capable of reproducing experimentally determined flux distributions (Williams et al., 2010; Hay and Schwender, 2011b) and generating new insights into metabolic behavior, capacities, and efficiencies (Sweetlove and Ratcliffe, 2011), challenges remain to advance the utility and predictive power of the models.Given that many plant metabolic functions are based on interactions between different subcellular compartments, cell types, tissues, and organs, the reconstruction of organ-specific models and the integration of these models into interacting multiorgan and/or whole-plant models is a prerequisite to get insight into complex plant metabolic processes organized on a whole-plant scale (e.g. source-sink interactions). Almost all FBA models of plant metabolism are restricted to one cell type (Boyle and Morgan, 2009; Knoop et al., 2010; Montagud et al., 2010; Cogne et al., 2011; Dal’Molin et al., 2011), one tissue or one organ (Grafahrend-Belau et al., 2009b; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011; Mintz-Oron et al., 2012), and only one model exists taking into account the interaction between two cell types by specifying the interaction between mesophyll and bundle sheath cells in C4 photosynthesis (Dal’Molin et al., 2010). So far, no model representing metabolism at the whole-plant scale exists.Considering whole-plant metabolism raises the problem of taking into account temporal and environmental changes in metabolism during plant development and growth. Although classical static FBA is unable to predict the dynamics of metabolic processes, as the network analysis is based on steady-state solutions, time-dependent processes can be taken into account by extending the classical static FBA to a dynamic flux balance analysis (dFBA), as proposed by Mahadevan et al. (2002). The static (SOA) and dynamic optimization approaches introduced in this work provide a framework for analyzing the transience of metabolism by integrating kinetic expressions to dynamically constrain exchange fluxes. Due to the requirement of knowing or estimating a large number of kinetic parameters, so far dFBA has only been applied to a plant metabolic model once, to study the photosynthetic metabolism in the chloroplasts of C3 plants by a simplified model of five biochemical reactions (Luo et al., 2009). Integrating a dynamic model into a static FBA model is an alternative approach to perform dFBA.In this study, a multiscale metabolic modeling (MMM) approach was applied with the aim of achieving a spatiotemporal resolution of cereal crop plant metabolism. To provide a framework for the in silico analysis of the metabolic dynamics of barley on a whole-plant scale, the MMM approach integrates a static multiorgan FBA model and a dynamic whole-plant multiscale functional plant model (FPM) to perform dFBA. The performance of the novel whole-plant MMM approach was tested by studying source-sink interactions during the seed developmental phase of barley plants.     

Polymorphisms and genetic linkage of histamine receptors

Histamine is a biogenic amine that plays an essential role in controlling many physiological functions, both in the central nervous system (CNS) and the peripheral nervous system (PNS). Most of these physiological effects are mediated through interactions with four histamine receptor subtypes, all of which are members of the larger family of rhodopsin-like class A G-protein coupled receptors (GPCRs) (Leurs et al., 2011; Lim et al., 2009). Here, we focus on the genetic variations and polymorphisms localized on the genes encoding for human histamine receptors where it provides an up to date collection of all polymorphisms found on genes encoding the histamine receptor subtypes and their association to diseases.     

Feeding the Probiotic Enterococcus faecium Strain NCIMB 10415 to Piglets Specifically Reduces the Number of Escherichia coli Pathotypes That Adhere to the Gut Mucosa

Feed supplementation with the probiotic Enterococcus faecium for piglets has been found to reduce pathogenic gut microorganisms. Since Escherichia coli is among the most important pathogens in pig production, we performed comprehensive analyses to gain further insight into the influence of E. faecium NCIMB 10415 on porcine intestinal E. coli. A total of 1,436 E. coli strains were isolated from three intestinal habitats (mucosa, digesta, and feces) of probiotic-supplemented and nonsupplemented (control) piglets. E. coli bacteria were characterized via pulsed-field gel electrophoresis (PFGE) for clonal analysis. The high diversity of E. coli was reflected by 168 clones. Multilocus sequence typing (MLST) was used to determine the phylogenetic backgrounds, revealing 79 sequence types (STs). Pathotypes of E. coli were further defined using multiplex PCR for virulence-associated genes. While these analyses discerned only a few significant differences in the E. coli population between the feeding groups, analyses distinguishing clones that were uniquely isolated in either the probiotic group only, the control group only, or both groups (shared group) revealed clear effects at the habitat level. Interestingly, extraintestinal pathogenic E. coli (ExPEC)-typical clones adhering to the mucosa were significantly reduced in the probiotic group. Our data show a minor influence of E. faecium on the overall population of E. coli in healthy piglets. In contrast, this probiotic has a profound effect on mucosa-adherent E. coli. This finding further substantiates a specific effect of E. faecium strain NCIMB 10415 in piglets against pathogenic E. coli in the intestine. In addition, these data question the relevance of data based on sampling fecal E. coli only.     

The WISER metadatabase: the key to more than 100 ecological datasets from European rivers, lakes and coastal waters

In ecological sciences, the role of metadata (i.e. key information about a dataset) to make existing datasets visible and discoverable has become increasingly important. Within the EU-funded WISER project (Water bodies in Europe: Integrative Systems to assess Ecological status and Recovery), we designed a metadatabase to allow scientists to find the optimal data for their analyses. An online questionnaire helped to collect metadata from the data providers and an online query tool (http://www.wiser.eu/results/meta-database/) facilitated data evaluation. The WISER metadatabase currently holds information on 114 datasets (22 river, 71 lake, 1 general freshwater and 20 coastal/transitional datasets), which also can be accessed by external scientists. We evaluate if generally used metadata standards (e.g. Darwin Core, ISO 19115, CSDGM, EML) are suitable for such specific purposes as WISER and suggest at least the linkage with standard metadata fields. Furthermore, we discuss whether the simple metadata documentation is enough for others to reuse a dataset and why there is still reluctance to publish both metadata and primary research data (i.e. time and financial constraints, misuse of data, abandoning intellectual property rights). We emphasise that metadata publication has major advantages as it makes datasets detectable by other scientists and generally makes a scientist’s work more visible.     

Synthesis of DNA oligonucleotides containing C5-ethynylbenzenesulfonamide-modified nucleotides (EBNA) by polymerases towards the construction of base functionalized nucleic acids

C5-Ethynylbenzenesulfonamide-modified nucleotide (EBNA) was investigated as substrate of various DNA polymerases. The experiments revealed that KOD, Phusion and Klenow DNA polymerases successfully accepted EBNA-T nucleotide as a substrate and yielded the fully extended DNA. KOD DNA polymerase was found to be the most efficient enzyme to furnish EBNA-T containing DNA in good yields. Phusion DNA polymerase efficiently amplified the template containing EBNA-T nucleotides by PCR.