Microscopic Factors that Control β-Sheet Registry in Amyloid Fibrils Formed by Fragment 11-25 of Amyloid β Peptide: Insights from Computer Simulations

Short fragments of amyloidogenic proteins are widely used as model systems in studies of amyloid formation. Fragment 11-25 of the amyloid β protein involved in Alzheimer's disease (Aβ11-25) was recently shown to form amyloid fibrils composed of anti-parallel β-sheets. Interestingly, fibrils grown under neutral and acidic conditions were seen to possess different registries of their inter-β-strand hydrogen bonds. In an effort to explain the microscopic origin of this pH dependence, we studied Aβ11-25 fibrils using methods of theoretical modeling. Several structural models were built for fibrils at low and neutral pH levels and these were examined in short molecular dynamics simulations in explicit water. The models that displayed the lowest free energy, as estimated using an implicit solvent model, were selected as representative of the true fibrillar structure. It was shown that the registry of these models agrees well with the experimental results. At neutral pH, the main contribution to the free energy difference between the two registries comes from the electrostatic interactions. The charge group of the carboxy terminus makes a large contribution to these interactions and thus appears to have a critical role in determining the registry.     

Calculation of Proteins’ Total Side-Chain Torsional Entropy and Its Influence on Protein-Ligand Interactions

Despite the high density within a typical protein fold, the ensemble of sterically permissible side-chain repackings is vast. Here, we examine the extent of this variability that survives energetic biases due to van der Waals interactions, hydrogen bonding, salt bridges, and solvation. Monte Carlo simulations of an atomistic model exhibit thermal fluctuations among a diverse set of side-chain arrangements, even with the peptide backbone fixed in its crystallographic conformation. We have quantified the torsional entropy of this native-state ensemble, relative to that of a noninteracting reference system, for 12 small proteins. The reduction in entropy per rotatable bond due to each kind of interaction is remarkably consistent across this set of molecules. To assess the biophysical importance of these fluctuations, we have estimated side-chain entropy contributions to the binding affinity of several peptide ligands with calmodulin. Calculations for our fixed-backbone model correlate very well with experimentally determined binding entropies over a range spanning more than 80 kJ/(mol·308 K).     

X-ray Crystallographic Study of an HIV-1 Fusion Inhibitor with the gp41 S138A Substitution

The S138A substitution of fusion inhibitory peptides derived from the C-terminal heptad repeat (C-HR) of the human immunodeficiency virus type 1 (HIV-1) gp41 leads to enhanced binding affinity to the N-terminal heptad repeat (N-HR). As such, these peptides exhibit highly potent anti-HIV-1 activity. X-ray crystallographic analysis was performed to understand the effect of the substitution on binding affinity. The comparison of the native and S138A crystal structures indicated that the increase in the hydrophobicity of the S138A substitution may aid the stabilization of the N-HR/C-HR complex through additional hydrophobic contacts. Free-energy calculations suggest that the difference between the desolvation free energies of the C-HR-derived peptides with and without the S138A mutation dominates the observed difference in anti-HIV-1 activity.     

Edge Effect on Density Estimates of a Radiotracked Population of Yellow-Necked Mice

ABSTRACT Density estimates for small-mammal populations from capture-mark-recapture (CMR) data have played an important role in many studies of theoretical and applied ecology. Defining effective trapping area (ETA) is one of the main issues affecting accuracy of density estimates. Our objective was to assess sensitivity of CMR density estimates to correctors based on movement parameters calculated from trapping and radiotelemetry data. From May to November 2005, we conducted monthly CMR trapping in a beech (Fagus sylvaticus) forest of the province of Trento, northern Italy. In conjunction with CMR, we radio-marked 32 yellow-necked mice (Apodemus flavicollis) captured from July to October and located them daily using radiotelemetry. We estimated population size (N) by model averaging with Program MARK. We calculated ETA using several definitions of the boundary strip, including full and half mean maximum distance moved (MMDM) from capture-recapture and telemetry data and mean radius of mean monthly home ranges. The boundary strip (W) increased with the amount of behavioral information embodied in the estimates. The largest W and lowest density values were based on radius of mean home ranges followed by MMDM calculated from telemetry data. The ETA based on movement distances increased more than proportionally when N decreased, suggesting that low population density combined with scarce resources results in rodents moving more in search of food, thus leading to overestimated ETA and underestimated density values. Although robust behavioral information would certainly improve density estimates, we suggest caution in relating ranging movements to capture probability and hence in using correctors based on movement distances to infer density values.     

The role of the catalytic domain of E. coli GluRS in tRNA discrimination

Discrimination of tRNA^Gln is an integral function of several bacterial glutamyl-tRNA synthetases (GluRS). The origin of the discrimination is thought to arise from unfavorable interactions between tRNA^Gln and the anticodon-binding domain of GluRS. From experiments on an anticodon-binding domain truncated Escherichia coli (E. coli) GluRS (catalytic domain) and a chimeric protein, constructed from the catalytic domain of E. coli GluRS and the anticodon-binding domain of E. coli glutaminyl-tRNA synthetase (GlnRS), we show that both proteins discriminate against E. coli tRNA^Gln. Our results demonstrate that in addition to the anticodon-binding domain, tRNA^Gln discriminatory elements may be present in the catalytic domain in E. coli GluRS as well.     

How many Eurasian badgers <Emphasis Type="Italic">Meles meles</Emphasis> L. are there in the Republic of Ireland?

In Ireland, the badger Meles meles L is a reservoir species for Mycobacterium bovis and, as such, contributes to the maintenance of bovine tuberculosis in cattle. A previous estimate of the badger population in the Republic was 200,000 badgers. In the current study, we obtained data on badger numbers from a large-scale badger removal project (the Four-Area project). The removal areas of the Four-Area Project were surrounded by barriers (either water or buffer areas where removals were also conducted) to prevent badger immigration. Within these areas, a grid of 0.25 km² was created within which we knew the badger numbers and habitat types (based on Corine data). Associations between badger numbers and habitat type were investigated using negative binomial modeling. Extrapolations from the model yielded an estimated badger population in the Republic of approximately 84,000 badgers. The implications of these findings are discussed.     

Biodiversity scales from plots to biomes with a universal species–area curve

Classic theory predicts species richness scales as the quarter-power of area, yet species–area relationships (SAR) vary widely depending on habitat, taxa, and scale range. Because power-law SAR are used to predict species loss under habitat loss, and to scale species richness from plots to biomes, insight into the wide variety of observed SAR and the conditions under which power-law behavior should be observed is needed. Here we derive from the maximum entropy principle, a new procedure for upscaling species richness data from small census plots to larger areas, and test empirically, using multiple data sets, the prediction that up to an overall scale displacement, nested SAR lie along a universal curve, with average abundance per species at each scale determining the local slope of the curve. Power-law behaviour only arises in the limit of increasing average abundance, and in that limit, the slope approaches zero, not ¼. An extrapolation of tree species richness in the Western Ghats to biome scale (60 000 km²) using only census data at plot scale (¼ ha) is presented to illustrate the potential for applications of our theory.     

A flexible multi-scale approach for standardised recording of plant species richness patterns

A sound monitoring of appropriate biodiversity indicators is necessary in order to assess the progress towards the internationally agreed target of halting the loss of biodiversity by 2010. However, existing monitoring schemes often do not address species richness as a key component of biodiversity directly or do so with insufficient methods. I provide an overview and assessment of the large variety of different sampling approaches for small-scale plant species richness. Major shortcomings of many of these are (i) non-uniform plot sizes or shapes; (ii) analysis of only one spatial scale despite the scale dependence of nearly all biodiversity parameters; (iii) lack of replication of smaller subplots; and (iv) exclusion of bryophytes and lichens despite their often large contribution to total plant diversity. Based on this review, I propose a new standardised sampling approach for plant diversity patterns at small scales that is applicable for a multitude of purposes and in any biome. In its basic variant, species composition is recorded on nested squares of 0.01 m², 0.1 m², 1 m², 10 m², and 100 m², with all smaller subplots being replicated at least 3-fold and evenly spaced within the next larger plot. Not only terricolous vascular plants, but also bryophytes, lichens, macro-algae as well as non-terricolous taxa should be recorded with the any-part system, i.e. those plants are counted within a plot whose superficial parts reach over it. This approach can be used to assess plant diversity patterns (i) of individual plots of interest, (ii) along environmental gradients, (iii) within specific vegetation types, or (iv) for landscape sectors. In the latter case, the series of nested plots must be placed randomly or systematically, but irrespective of plot homogeneity. The proposed approach allows the calculation of many meaningful biodiversity indicators, while being well compatible with a range of other sampling schemes, but avoiding their shortcomings. As this approach is not very time-consuming in its basic variant, but can easily be extended for specific purposes, I suggest its use for any kind of biodiversity studies and particularly for monitoring.     

Drivers of moth species richness on tropical altitudinal gradients: a cross-regional comparison

Aims We examine the role of species–area relationships (SARs), climatic parameters and phylogeny in shaping the altitudinal species richness patterns of moths. With respect to SARs, we investigate whether habitat heterogeneity is a probable mechanism for mediating area effects. We investigate the consistency of patterns by comparing several discrete regions. Location Nine mountainous regions in tropical Asia and the Malay Archipelago. Methods Presence‐only records for 292 species of the Lepidopteran family Sphingidae were used to measure interpolated species richness in 200‐m altitudinal bands. Species richness was correlated with area measures, which were calculated from both two‐dimensional map projections and three‐dimensional digital elevation models (DEMs). We used data simulations of homogeneous communities to test for effects of sample (i.e. habitat) heterogeneity as a mechanism causing SARs. Species richness patterns were compared among regions and between the two major sphingid clades, and were related to regional climatic characteristics. Results The area of altitudinal bands was a strong (statistical) explanation of species richness, particularly if area was calculated from three‐dimensional DEMs, but SARs often over‐predict species richness in lowland areas. There was no evidence for habitat heterogeneity as a mechanism of altitudinal SARs (tested for Borneo only). Species richness patterns varied considerably between the nine regions, which may, as an alternative to SARs, be explained by climatic differences such as (temperature) seasonality. Phylogenetic clades differed in species richness patterns exhibited. Main conclusion SARs provide strong empirical explanations for (regional) altitudinal patterns of species richness, but lack of evidence for the most likely mechanism cautions against a priori ‘corrections’ of species richness data for area. Furthermore, SARs are often not a sufficient explanation for the drop in species richness towards lowlands. Climate, or other collinear variables, may offer alternative explanations for altitudinal SARs. More research is needed to understand the mechanisms for SARs in an altitudinal context in order to evaluate their importance in the face of parameter collinearity.