Local temperatures inferred from plant communities suggest strong spatial buffering of climate warming across Northern Europe

Recent studies from mountainous areas of small spatial extent (<2500 km²) suggest that fine‐grained thermal variability over tens or hundreds of metres exceeds much of the climate warming expected for the coming decades. Such variability in temperature provides buffering to mitigate climate‐change impacts. Is this local spatial buffering restricted to topographically complex terrains? To answer this, we here study fine‐grained thermal variability across a 2500‐km wide latitudinal gradient in Northern Europe encompassing a large array of topographic complexities. We first combined plant community data, Ellenberg temperature indicator values, locally measured temperatures (LmT) and globally interpolated temperatures (GiT) in a modelling framework to infer biologically relevant temperature conditions from plant assemblages within <1000‐m² units (community‐inferred temperatures: CiT). We then assessed: (1) CiT range (thermal variability) within 1‐km² units; (2) the relationship between CiT range and topographically and geographically derived predictors at 1‐km resolution; and (3) whether spatial turnover in CiT is greater than spatial turnover in GiT within 100‐km² units. Ellenberg temperature indicator values in combination with plant assemblages explained 46–72% of variation in LmT and 92–96% of variation in GiT during the growing season (June, July, August). Growing‐season CiT range within 1‐km² units peaked at 60–65°N and increased with terrain roughness, averaging 1.97 °C (SD = 0.84 °C) and 2.68 °C (SD = 1.26 °C) within the flattest and roughest units respectively. Complex interactions between topography‐related variables and latitude explained 35% of variation in growing‐season CiT range when accounting for sampling effort and residual spatial autocorrelation. Spatial turnover in growing‐season CiT within 100‐km² units was, on average, 1.8 times greater (0.32 °C km^?1) than spatial turnover in growing‐season GiT (0.18 °C km^?1). We conclude that thermal variability within 1‐km² units strongly increases local spatial buffering of future climate warming across Northern Europe, even in the flattest terrains.     

Contrasting demographic histories of the neighboring bonobo and chimpanzee

The Pleistocene epoch was a period of dramatic climate change that had profound impacts on the population sizes of many animal species. How these species were shaped by past events is often unclear, hindering our understanding of the population dynamics resulting in present day populations. We analyzed complete mitochondrial genomes representing all four recognized chimpanzee subspecies and the bonobo to infer the recent demographic history and used simulations to exclude a confounding effect of population structure. Our genus-wide Bayesian coalescent-based analysis revealed surprisingly dissimilar demographic histories of the chimpanzee subspecies and the bonobo, despite their overlapping habitat requirements. Whereas the central and eastern chimpanzee subspecies were inferred to have expanded tenfold between around 50,000 and 80,000 years ago and today, the population size of the neighboring bonobo remained constant. The changes in population size are likely linked to changes in habitat area due to climate oscillations during the late Pleistocene. Furthermore, the timing of population expansion for the rainforest-adapted chimpanzee is concurrent with the expansion of the savanna-adapted human, which could suggest a common response to changed climate conditions around 50,000–80,000 years ago.     

Design of a data model for developing laboratory information management and analysis systems for protein production

Data management has emerged as one of the central issues in the high-throughput processes of taking a protein target sequence through to a protein sample. To simplify this task, and following extensive consultation with the international structural genomics community, we describe here a model of the data related to protein production. The model is suitable for both large and small facilities for use in tracking samples, experiments, and results through the many procedures involved. The model is described in Unified Modeling Language (UML). In addition, we present relational database schemas derived from the UML. These relational schemas are already in use in a number of data management projects.     

Cyclic AMP (cAMP)-mediated stimulation of adipocyte differentiation requires the synergistic action of Epac- and cAMP-dependent protein kinase-dependent processes

Cyclic AMP (cAMP)-dependent processes are pivotal during the early stages of adipocyte differentiation. We show that exchange protein directly activated by cAMP (Epac), which functions as a guanine nucleotide exchange factor for the Ras-like GTPases Rap1 and Rap2, was required for cAMP-dependent stimulation of adipocyte differentiation. Epac, working via Rap, acted synergistically with cAMP-dependent protein kinase (protein kinase A [PKA]) to promote adipogenesis. The major role of PKA was to down-regulate Rho and Rho-kinase activity, rather than to enhance CREB phosphorylation. Suppression of Rho-kinase impaired proadipogenic insulin/insulin-like growth factor 1 signaling, which was restored by activation of Epac. This interplay between PKA and Epac-mediated processes not only provides novel insight into the initiation and tuning of adipocyte differentiation, but also demonstrates a new mechanism of cAMP signaling whereby cAMP uses both PKA and Epac to achieve an appropriate cellular response.     

Identification of anticancer drugs for hepatocellular carcinoma through personalized genome‐scale metabolic modeling

Genome‐scale metabolic models (GEMs) have proven useful as scaffolds for the integration of omics data for understanding the genotype–phenotype relationship in a mechanistic manner. Here, we evaluated the presence/absence of proteins encoded by 15,841 genes in 27 hepatocellular carcinoma (HCC) patients using immunohistochemistry. We used this information to reconstruct personalized GEMs for six HCC patients based on the proteomics data, HMR 2.0, and a task‐driven model reconstruction algorithm (tINIT). The personalized GEMs were employed to identify anticancer drugs using the concept of antimetabolites; i.e., drugs that are structural analogs to metabolites. The toxicity of each antimetabolite was predicted by assessing the in silico functionality of 83 healthy cell type‐specific GEMs, which were also reconstructed with the tINIT algorithm. We predicted 101 antimetabolites that could be effective in preventing tumor growth in all HCC patients, and 46 antimetabolites which were specific to individual patients. Twenty‐two of the 101 predicted antimetabolites have already been used in different cancer treatment strategies, while the remaining antimetabolites represent new potential drugs. Finally, one of the identified targets was validated experimentally, and it was confirmed to attenuate growth of the HepG2 cell line.     

Population coding in somatosensory cortex

Computational analyses have begun to elucidate which components of somatosensory cortical population activity may encode basic stimulus features. Recent results from rat barrel cortex suggest that the essence of this code is not synergistic spike patterns, but rather the precise timing of single neuron's first post-stimulus spikes. This may form the basis for a fast, robust population code.     

Multi-scale phylogenetic structure in coastal dune plant communities across the globe

Aims Studies integrating phylogenetic history and large-scale community assembly are few, and many questions remain unanswered. Here, we use a global coastal dune plant data set to uncover the important factors in community assembly across scales from the local filtering processes to the global long-term diversification and dispersal dynamics. Coastal dune plant communities occur worldwide under a wide range of climatic and geologic conditions as well as in all biogeographic regions. However, global patterns in the phylogenetic composition of coastal dune plant communities have not previously been studied.Methods The data set comprised vegetation data from 18463 plots in New Zealand, South Africa, South America, North America and Europe. The phylogenetic tree comprised 2241 plant species from 149 families. We calculated phylogenetic clustering (Net Relatedness Index, NRI, and Nearest Taxon Index, NTI) of regional dune floras to estimate the amount of in situ diversification relative to the global dune species pool and evaluated the relative importance of land and climate barriers for these diversification patterns by geographic analyses of phylogenetic similarity. We then tested whether dune plant communities exhibit similar patterns of phylogenetic structure within regions. Finally, we calculated NRI for local communities relative to the regional species pool and tested for an association with functional traits (plant height and seed mass) thought to vary along sea–inland gradients.Important findings Regional species pools were phylogenetically clustered relative to the global pool, indicating regional diversification. NTI showed stronger clustering than NRI pointing to the importance of especially recent diversifications within regions. The species pools grouped phylogenetically into two clusters on either side of the tropics suggesting greater dispersal rates within hemispheres than between hemispheres. Local NRI plot values confirmed that most communities were also phylogenetically clustered within regions. NRI values decreased with increasing plant height and seed mass, indicating greater phylogenetic clustering in communities with short maximum height and good dispersers prone to wind and tidal disturbance as well as salt spray, consistent with environmental filtering along sea–inland gradients. Height and seed mass both showed significant phylogenetic signal, and NRI tended to correlate negatively with both at the plot level. Low NRI plots tended to represent coastal scrub and forest, whereas high NRI plots tended to represent herb-dominated vegetation. We conclude that regional diversification processes play a role in dune plant community assembly, with convergence in local phylogenetic community structure and local variation in community structure probably reflecting consistent coastal-inland gradients. Our study contributes to a better understanding of the globally distributed dynamic coastal ecosystems and the structuring factors working on dune plant communities across spatial scales and regions.     

Dimerization of ADAR2 is mediated by the double-stranded RNA binding domain

Members of the family of adenosine deaminases acting on RNA (ADARs) can catalyze the hydrolytic deamination of adenosine to inosine and thereby change the sequence of specific mRNAs with highly double-stranded structures. The ADARs all contain one or more repeats of the double-stranded RNA binding motif (DRBM). By both in vitro and in vivo assays, we show that the DRBMs of rat ADAR2 are necessary and sufficient for dimerization of the enzyme. Bioluminescence resonance energy transfer (BRET) demonstrates that ADAR2 also exists as dimers in living mammalian cells and that mutation of DRBM1 lowers the dimerization affinity while mutation of DRBM2 does not. Nonetheless, the editing efficiency of the GluR2 Q/R site depends on a functional DRBM2. The ADAR2 DRBMs thus serve differential roles in RNA dimerization and GluR2 Q/R editing, and we propose a model for RNA editing that incorporates the new findings.     

Characterization of glucagon-like peptide-1 receptor beta-arrestin 2 interaction: a high-affinity receptor phenotype

To dissect the interaction between beta-arrestin ((beta)arr) and family B G protein-coupled receptors, we constructed fusion proteins between the glucagon-like peptide 1 receptor and (beta)arr2. The fusion constructs had an increase in apparent affinity selectively for glucagon, suggesting that (beta)arr2 interaction locks the receptor in a high-affinity conformation, which can be explored by some, but not all, ligands. The fusion constructs adopted a signaling phenotype governed by the tethered (beta)arr2 with an attenuated G protein-mediated cAMP signal and a higher maximal internalization compared with wild-type receptors. This distinct phenotype of the fusion proteins can not be mimicked by coexpressing wild-type receptor with (beta)arr2. However, when the wild-type receptor was coexpressed with both (beta)arr2 and G protein-coupled receptor kinase 5, a phenotype similar to that observed for the fusion constructs was observed. We conclude that the glucagon-like peptide 1 fusion construct mimics the natural interaction of the receptor with (beta)arr2 with respect to binding peptide ligands, G protein-mediated signaling and internalization, and that this distinct molecular phenotype is reminiscent of that which has previously been characterized for family A G protein-coupled receptors, suggesting similarities in the effect of (beta)arr interaction between family A and B receptors also at the molecular level.