The mechanism of protein kinase C regulation

Protein kinase C (PKC) is a family of serine/threonine protein kinases that plays a central role in transducing extracellular signals into a variety of intracellular responses ranging from cell proliferation to apoptosis. Nine PKC genes have been identified in the human genome, which encode 10 proteins. Each member of this protein kinase family displays distinct biochemical characteristics and is enriched in different cellular and subcellular locations. Activation of PKC has been implicated in the regulation of cell growth and differentiation. This review summarizes works of the past years in the field of PKC biochemistry that covers regulation and activation mechanism of different PKC isoforms.     

Synthesis,preferred conformation,protease stability,and membrane activity of heptaibin,a medium‐length peptaibiotic

The medium‐length peptaibiotics are characterized by a primary structure of 14–16 amino acid residues. Despite the interesting antibiotic and antifungal properties exhibited by these membrane‐active peptides, their exact mechanism of action is still unknown. Here, we present our results on heptaibin, a 14‐amino acid peptaibiotic found to exhibit antimicrobial activity against Staphylococcus aureus. We carried out the very challenging synthesis of heptaibin on solid phase and a detailed conformational analysis in solution. The peptaibiotic is folded in a mixed 3₁₀‐/α‐helix conformation which exhibits a remarkable amphiphilic character. We also find that it is highly stable toward degradation by proteolytic enzymes and nonhemolytic. Finally, fluorescence leakage experiments using small unilamellar vesicles of three different compositions revealed that heptaibin, although uncharged, is a selective compound for permeabilization of model membranes mimicking the overall negatively charged surface of Gram‐positive bacteria. This latter finding is in agreement with the originally published antimicrobial activity data. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.     

Wealth, status, and fitness: a historical study of Norwegians in variable environments

Wealth and status covary with lifetime reproductive success in preindustrial human populations. Local ecology is likely to modify this association, but details of this presumed relationship are not yet known. We sought to determine whether local ecology modifies the relationship between status and fitness (number of grandchildren). Our approach to the problem was to measure variation in fitness relative to status (landless or with land) and to local ecology (inland versus coastal communities). We also analyzed life history traits that might explain observed variations in fitness. Our results confirm previous findings that both status (landless=9.9 vs. with land=16.5) and ecology (inland=12.3 vs. coast=14.1) affect the number of grandchildren produced by a female in pre-industrial society. We also found that the differences in number of children between the status groups were less pronounced on the coast (landless=12.0 vs. with land=16.1) than inland (landless=7.8 vs. with land=16.8). Our findings are novel because they suggest that the fitness consequences of human status may depend on details of local ecology. We discuss four different mechanisms that could account for these fitness differences: (1) differential reproductive rate of mothers, (2) differential marriage rate of children (3) differential survival rate of children, and (4) different social practices (breastfeeding, inheritance of property and diet).     

Statistical mechanics analysis of sparse data

Inferential structure determination uses Bayesian theory to combine experimental data with prior structural knowledge into a posterior probability distribution over protein conformational space. The posterior distribution encodes everything one can say objectively about the native structure in the light of the available data and additional prior assumptions and can be searched for structural representatives. Here an analogy is drawn between the posterior distribution and the canonical ensemble of statistical physics. A statistical mechanics analysis assesses the complexity of a structure calculation globally in terms of ensemble properties. Analogs of the free energy and density of states are introduced; partition functions evaluate the consistency of prior assumptions with data. Critical behavior is observed with dwindling restraint density, which impairs structure determination with too sparse data. However, prior distributions with improved realism ameliorate the situation by lowering the critical number of observations. An in-depth analysis of various experimentally accessible structural parameters and force field terms will facilitate a statistical approach to protein structure determination with sparse data that avoids bias as much as possible.     

Clonal Diversity and Fine‐scale Genetic Structure in a High Andean Treeline Population

Clonal propagation becomes more abundant with increasing altitudes as environmental conditions worsen. To date, little attention has been paid to the way in which clonal propagation affects genetic diversity and the fine‐scale spatial genetic structure (FSGS) of clonal alpine trees. An AFLP study was undertaken to quantify the clonal and genetic diversity and FSGS of the vulnerable treeline species Polylepis reticulata in Ecuador. We successfully genotyped 32 and 75 ramets within 4 m × 100 m (coarse scale) and 4 m × 4 m (fine scale) transects of one population, respectively. Higher genotypic diversity was detected at the coarse scale than at the fine scale, while lower genetic diversity was detected for P. reticulata than other Polylepis spp. at both scales. Significantly stronger FSGS was detected at the ramet level than the genet level for P. reticulata within a spatial distance of 3 m. The studied P. reticulata population showed pronounced FSGS (Sp = 0.012 at the genet level, a statistic reflecting declining pairwise kinship with distance) revealed restricted gene dispersal, which implies restricted seed dispersal for this population, assuming pollen flow is as extensive as that described for other wind‐pollinated tree species. Our results revealed that clonal diversity is a function of both sample size and the spatial scale of the sampling area. The findings highlights that clonal propagation has affected FSGS within a spatial distance of 3 m for this species.     

Evaluating methods for estimating local effective population size with and without migration

Effective population size is a fundamental parameter in population genetics, evolutionary biology, and conservation biology, yet its estimation can be fraught with difficulties. Several methods to estimate N_e from genetic data have been developed that take advantage of various approaches for inferring N_e. The ability of these methods to accurately estimate N_e, however, has not been comprehensively examined. In this study, we employ seven of the most cited methods for estimating N_e from genetic data (Colony2, CoNe, Estim, MLNe, ONeSAMP, TMVP, and NeEstimator including LDNe) across simulated datasets with populations experiencing migration or no migration. The simulated population demographies are an isolated population with no immigration, an island model metapopulation with a sink population receiving immigrants, and an isolation by distance stepping stone model of populations. We find considerable variance in performance of these methods, both within and across demographic scenarios, with some methods performing very poorly. The most accurate estimates of N_e can be obtained by using LDNe, MLNe, or TMVP; however each of these approaches is outperformed by another in a differing demographic scenario. Knowledge of the approximate demography of population as well as the availability of temporal data largely improves N_e estimates.     

The effective founder effect in a spatially expanding population

The gradual loss of diversity and the establishment of clines in allele frequencies associated with range expansions are patterns observed in many species, including humans. These patterns can result from a series of founder events occurring as populations colonize previously unoccupied areas. We develop a model of an expanding population and, using a branching process approximation, show that spatial gradients reflect different amounts of genetic drift experienced by different subpopulations. We then use this model to measure the net average strength of the founder effect, and we demonstrate that the predictions from the branching process model fit simulation results well. We further show that estimates of the effective founder size are robust to potential confounding factors such as migration between subpopulations. We apply our method to data from Arabidopsis thaliana. We find that the average founder effect is approximately three times larger in the Americas than in Europe, possibly indicating that a more recent, rapid expansion occurred.