Protein kinase-A-mediated secretion of mucin from human colonic epithelial cells

Both Ca(2+)- and cAMP-mediated second messenger cascades acutely regulate mucin secretion from human colonic epithelial cells. To better understand the cAMP-dependent regulation of mucin secretion we have characterized the complement of cAMP-dependent protein kinase (PKA) isoforms in mucus-secreting T84 cells, and determined which of these isoforms is responsible for agonist-stimulated mucin secretion. Our results show the presence of both type I and type II PKA in cells that also contain large mucin granules. Forskolin caused a rapid and sustained increase in PKA activity that reached a maximum 5-10 min following its addition. Secretion of mucin was detected 15 min following exposure to forskolin, and continued to increase for a further 15 min before reaching a plateau. Mucin secretion was also measured in the presence of combinations of site-selective cAMP analog pairs, which preferentially activate either type I or type II PKA. Similar levels of mucin secretion were observed for both type I and type II PKA-selective analog pairs. Subsequent addition of forskolin was unable to further increase mucin secretion. Thus, activation of either type I or type II PKA is able to maximally stimulate secretion of mucins from T84 human colonic epithelial cells.     

The neuronal microtubule-associated protein tau is a substrate for caspase-3 and an effector of apoptosis

We have identified a class of tau fragments inducing apoptosis in different cellular contexts, including a human teratocarcinoma-derived cell line (NT2 cells) representing committed human neuronal precursors. We have found a transition point inside the tau molecule beyond which the fragments lose their ability to induce apoptosis. This transition point is located around one of the putative caspase-3 cleavage sites. This is the only site that can be effectively used by caspase-3 in vitro, releasing the C-terminal 19 amino acids of tau. These results establish tau as a substrate for an apoptotic protease that turns tau itself into an effector of apoptosis. Accordingly, tau may be involved in a self-propagating process like what has been predicted for the pathogenesis of different neurodegenerative disorders.     

Improved tests for heterogeneity across a region of DNA sequence in the ratio of polymorphism to divergence

The neutral theory of molecular evolution predicts that the ratio of polymorphisms to fixed differences should be fairly uniform across a region of DNA sequence. Significant heterogeneity in this ratio can indicate the effects of balancing selection, selective sweeps, mildly deleterious mutations, or background selection. Comparing an observed heterogeneity statistic with simulations of the heterogeneity resulting from random phylogenetic and sampling variation provides a test of the statistical significance of the observed pattern. When simulated data sets containing heterogeneity in the polymorphism-to-divergence ratio are examined, different statistics are most powerful for detecting different patterns of heterogeneity. The number of runs is most powerful for detecting patterns containing several peaks of polymorphism; the Kolmogorov-Smirnov statistic is most powerful for detecting patterns in which one end of the gene has high polymorphism and the other end has low polymorphism; and a newly developed statistic, the mean sliding G statistic, is most powerful for detecting patterns containing one or two peaks of polymorphism with reduced polymorphism on either side. Nine out of 27 genes from the Drosophila melanogaster subgroup exhibit heterogeneity that is significant under at least one of these three tests, with five of the nine remaining significant after a correction for multiple comparisons, suggesting that detectable evidence for the effects of some kind of selection is fairly common.      

Rapid Assessment of Ecosystem Services Provided by Two Mineral Extraction Sites Restored for Nature Conservation in an Agricultural Landscape in Eastern England

Despite growing recognition that mineral sites restored for nature conservation can enhance local biodiversity, the wider societal benefits provided by this type of restoration relative to alternative options are not well understood. This study addresses this research gap by quantifying differences in ecosystem services provision under two common mineral site after-uses: nature conservation and agriculture. Using a combination of site-specific primary field data, benefits transfer and modelling, we show that for our sites restoration for nature conservation provides a more diverse array of ecosystem services than would be delivered under an agricultural restoration scenario. We also explore the effects of addressing different conservation targets, which we find alter the provision of ecosystem services on a service-specific basis. Highly species-focused intervention areas are associated with increased carbon storage and livestock grazing provision, whereas non-intervention areas are important for carbon sequestration, fishing, recreation and flood risk mitigation. The results of this study highlight the wider societal importance of restored mineral sites and may help conservation managers and planners to develop future restoration strategies that provide benefits for both biodiversity and human well-being.     

Novel benzothiophene H1-antihistamines for the treatment of insomnia

SAR of lead benzothiophene H₁-antihistamine 2 was explored to identify backup candidates with suitable pharmacokinetic profiles for an insomnia program. Several potent and selective H₁-antihistamines with a range of projected half-lives in humans were identified. Compound 16d had a suitable human half-life as demonstrated in a human microdose study, but variability in pharmacokinetic profile, attributed to metabolic clearance, prevented further development of this compound. Compound 28b demonstrated lower predicted clearance in preclinical studies, and may represent a more suitable backup compound.     

Identification of a novel selective H1-antihistamine with optimized pharmacokinetic properties for clinical evaluation in the treatment of insomnia

Analogs of the known H₁-antihistamine R-dimethindene with suitable selectivity for key GPCRs, P450 enzymes and hERG channel were assessed for metabolism profile and in vivo properties. Several analogs were determined to exhibit diverse metabolism. One of these compounds, 10a, showed equivalent efficacy in a rat EEG/EMG model to a previously identified clinical candidate and a potentially superior pharmacokinetic profile as determined from a human microdose study.     

Genome-Wide Association of Carbon and Nitrogen Metabolism in the Maize Nested Association Mapping Population

Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C₄ metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.Carbon (C) and nitrogen (N) metabolism are the basis for life on Earth. The production, balance, and tradeoffs of C and N metabolism are critical to all plant growth, yield, and local adaptation (Coruzzi and Bush, 2001; Coruzzi et al., 2007). In plants, there is a critical balance between the tissues that are producing energy (sources) and those using it (sinks), as the identities and locations of these vary through time and developmental stage (Smith et al., 2004). While a great deal of research has focused on the key genes and proteins involved in these processes (Wang et al., 1993; Kim et al., 2000; Takahashi et al., 2009), relatively little is known about the natural variation within a species that fine-tunes these processes in individual plants.In addition, a key aspect of core C metabolism involves the nature of plant photosynthesis. While the majority of plants use standard C₃ photosynthetic pathways, some, including maize (Zea mays) and many other grasses, use C₄ photosynthesis to concentrate CO₂ in bundle sheath cells to avoid wasteful photorespiration (Sage, 2004). Under some conditions (such as drought or high temperatures), C₄ photosynthesis is much more efficient than C₃ photosynthesis. Since these conditions are expected to become more prevalent in the near future due to climate change, various research groups are working to convert C₃ crop species to C₄ metabolism in order to boost crop production and food security (Sage and Zhu, 2011). Beyond this, better understanding of both C₃ and C₄ metabolic pathways will aid efforts to breed crops for superior yield, N-use efficiency, and other traits important for global food production.In the last two decades, quantitative trait locus (QTL) mapping, first with linkage analysis and later with association mapping, has been used to dissect C and N metabolism in several species, including Arabidopsis (Arabidopsis thaliana; Mitchell-Olds and Pedersen, 1998; Keurentjes et al., 2008; Lisec et al., 2008; Sulpice et al., 2009), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Hirel et al., 2001; Limami et al., 2002; Zhang et al., 2006, 2010a, 2010b). These studies identified key genetic regions underlying variation in core C and N metabolism, many of which include candidate genes known to be involved in these processes.Previous studies of genetic variation for C and N metabolism are limited by the fact that they identified trait loci only through linkage mapping in artificial families or through association mapping across populations of unrelated individuals. Linkage mapping benefits from high statistical power due to many individuals sharing the same genotype at any given location, but it suffers from low resolution due to the limited number of generations (and hence recombination events) since the initial founders. Association mapping, in turn, enjoys high resolution due to the long recombination histories of natural populations but suffers from low power, since most genotypes occur in only a few individuals. In addition, many of these studies focused on C and N in artificial settings (e.g. greenhouses or growth chambers) instead of field conditions, running the risk that important genetic loci could be missed if the conditions do not include important (and potentially unknown) natural environmental variables.To address these issues and improve our understanding of C and N metabolism in maize, we used a massive and diverse germplasm resource, the maize nested association mapping (NAM) population (Buckler et al., 2009; McMullen et al., 2009), to evaluate genetic variation underlying the accumulation of 12 targeted metabolites in maize leaf tissue under field conditions. This population was formed by mating 25 diverse maize lines to the reference line, B73, and creating a 200-member biparental family from each of these crosses. The entire 5,000-member NAM population thus combines the strengths of both linkage and association mapping (McMullen et al., 2009), and it has been used to identify QTLs for important traits such as flowering time (Buckler et al., 2009), disease resistance (Kump et al., 2011; Poland et al., 2011), and plant architecture (Tian et al., 2011; Peiffer et al., 2013). Most importantly, this combination of power and resolution frequently resolves associations down to the single-gene level, even when using field-based data.The metabolites we profiled are key indicators of photosynthesis, respiration, glycolysis, and protein and sugar metabolism in the plant (Sulpice et al., 2009). By taking advantage of a robotized metabolic phenotyping platform (Gibon et al., 2004), we performed more than 100,000 assays across 12,000 samples, with two independent samples per experimental plot. Raw data and the best linear unbiased predictors (BLUPs) of these data were included as part of a study of general functional variation in maize (Wallace et al., 2014), but, to our knowledge, this is the first in-depth analysis of these metabolic data. We find strong correlations among several of the metabolites, and we also find extensive pleiotropy among the different traits. Many of the top QTLs are also near or within candidate genes relating to C and N metabolism, thus identifying targets for future breeding and selection. These results provide a powerful resource for those working with core C and N metabolism in plants and for improving maize performance in particular.