Beta-helical catalytic domains in glycoside hydrolase families 49, 55 and 87: domain architecture,modelling and assignment of catalytic residues

X-ray crystallography and bioinformatics studies reveal a tendency for the right-handed β-helix domain architecture to be associated with carbohydrate binding proteins. Here we demonstrate the presence of catalytic β-helix domains in glycoside hydrolase (GH) families 49, 55 and 87 and provide evidence for their sharing a common evolutionary ancestor with two structurally characterized GH families, numbers 28 and 82. This domain assignment helps assign catalytic residues to each family. Further analysis of domain architecture reveals the association of carbohydrate binding modules with catalytic GH β-helices, as well as an unexpected pair of β-helix domains in GH family 55.     

Protein sequential resonance assignments by combinatorial enumeration using 13C alpha chemical shifts and their (i,i-1) sequential connectivities

The need for the structural characterization of proteins on a genomic scale has brought with it demands for new technology to speed the structure determination process. In NMR, one bottleneck is the sequential assignment of backbone resonances. In this paper, we explore the computational complexity of the sequential assignment problem using only ¹³C chemical shift data and C (i,i–1) sequential connectivity information, all of which can potentially be obtained from a single three-dimensional NMR spectrum. Although it is generally believed that there is too much ambiguity in such data to provide sufficient information for sequential assignment, we show that a straightforward combinatorial search algorithm can be used to find correct and unambiguous sequential assignments in a reasonable amount of CPU time for small proteins (approximately 80 residues or smaller) when there is little missing data. The deleterious effect of missing or spurious peaks and the dependence on match tolerances is also explored. This simple algorithm could be used as part of a semi-automated, interactive assignment procedure, e.g., to test partial manually determined solutions fo uniqueness and to extend these solutions.     

The cisproline(i - 1)-aromatic(i) interaction: folding of the Ala-cisPro-Tyr peptide characterized by NMR and theoretical approaches

Cisproline(i - 1)-aromatic(i) interactions have been detected in several short peptides in aqueous solution by analysis of anomalous chemical shifts measured by 1H-NMR spectroscopy. This formation of local structure is of importance for protein folding and binding properties. To obtain an atomic-detail characterisation of the cisproline(i - 1)-aromatic(i) interaction in terms of structure, energetics and dynamics, we studied the minimal peptide unit, blocked Ala-cisPro-Tyr, using computational and experimental techniques. Structural database analyses and a systematic search revealed two groups of conformations displaying a cisproline(i - 1)-aromatic(i) interaction. These conformations were taken as seeds for molecular dynamics simulations in explicit solvent at 278 K. During a total of 33.6 ns of simulation, all the 'folded' conformations and some 'unfolded' states were sampled. 1H- and 13C-chemical shifts and 3J-coupling constants were measured for the Ala-Pro-Tyr peptide. Excellent agreement was found between all the measured and computed NMR properties, showing the good quality of the force field. We find that under the experimental and simulation conditions, the Ala-cisPro-Tyr peptide is folded 90% of the time and displays two types of folded conformation which we denote 'a' and 'b'. The type a conformations are twice as populated as the type b conformations. The former have the tyrosine ring interacting with the alanine alpha proton and are enthalpically stabilised. The latter have the aromatic ring interacting with the proline side chain and are entropically stabilised. The combined and complementary use of computational and experimental techniques permitted derivation of a detailed scenario of the 'folding' of this peptide.     

Distributed torsion angle grid search in high dimensions: A systematic approach to NMR structure determination

Two complementary approaches for systematic search in torsion angle space are described for the generation of all conformations of polypeptides which satisfy experimental NMR restraints, hard-sphere van der Waals radii, and rigid covalent geometry. The first procedure is based on a recursive, tree search algorithm for the examination of linear chains of torsion angles, and uses a novel treatment to propagate the search results to neighboring regions so that the structural consequences of the restraints are fully realized. The second procedure is based on a binary combination of torsion vector spaces for connected submolecules, and produces intermediate results in Cartesian space for a more robust restraint analysis. Restraints for NMR applications include bounds on torsion angles and internuclear distances, including relational and degenerate restraints involving equivalent and nonstereoassigned protons. To illustrate these methods, conformation search results are given for the tetrapeptide APGA restrained to an idealized -turn conformation, an alanine octapeptide restrained to a right-handed helical conformation, and the structured region of the peptide SYPFDV.     

The consequences of partially directed search effort

Search effort is undirected when a forager has a stereotypical searching behaviour that results in fixed encounter rates with its prey (e.g. diet choice models), and is directed when the forager can bias its encounter with a ‘chosen’ prey. If the bias is complete, search is totally directed (e.g. habitat selection models). When the bias is incomplete (i.e. search modes are not exclusive to a single prey type), search is partially directed. The inclusion of a prey type in the diet is then the result of two decisions: (1) which prey to search for and (2) which prey to handle. The latter decision is determined by the ratio of energy to handling time and the abundance of the preferred prey. The former decision is a function of the encounter probabilities and densities of all potential prey types in addition to their ratio of energy to handling time. Assuming two prey types, there are three distinct behavioural strategies: (1) search for the preferred prey/forage selectively; (2) search for the preferred prey/forage opportunistically; and (3) search for the non-preferred prey/forage opportunistically. If prey are depletable (i.e. prey occur in resource patches), the forager may switch search modes such that prey are depleted to the point where the marginal values of the search modes are equalized. This revised version was published online in July 2006 with corrections to the Cover Date.     

Foraging distribution overlap and marine reserve usage amongst sub-Antarctic predators inferred from a multi-species satellite tagging experiment

Satellite telemetry data was used to predict at sea spatial usage of five top order and meso-predators; Antarctic fur seals (Arctocephalus gazella), macaroni penguins (Eudyptes chrysolophus), king penguins (Aptenodytes patagonicus), black browed albatross (Diomedea melanophrys), and light mantled albatross (Phoebetria palpebrata). All were tagged at Heard Island in the Southern Ocean over a single summer season collecting over 5000 tracking days for 178 individuals. We aimed to predict areas of likely high foraging value from tracking environmental data and also to quantify overlap in foraging range between species. Hidden Markov models were used to differentiate between bouts of Area Restricted Search (ARS) assumed to be associated with areas of higher foraging value, and transit behaviours. Oceanographic and distance metrics associated with ARS activity were then used to calculate a habitat electivity index. A combined bootstrap/Monte Carlo scheme was employed to propagate uncertainty from the Hidden Markov models into the habitat prediction scheme. Distinct differences were predicted in the spatial distribution of foraging locations in different species, reflecting different dispersive abilities and foraging strategy. The extent of usage and foraging distribution was largely contained within Australian the Economic Exclusion Zone (EEZ). In comparison, the smaller Australian Commonwealth Marine Protected Areas (MPAs) contained <20% of the predicted foraging distributions.     

HomeRange: A global database of mammalian home ranges

Motivation

Home range is a common measure of use of space by animals because it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of use of space by animals. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has historically been biased towards terrestrial mammals. The use of aggregated numbers and the terrestrial focus limit our ability to examine home-range patterns across different environments, their variation in time and variation between different levels of organization. Here, we introduce HomeRange, a global database with 75,611 home-range values across 960 different species of mammals, including terrestrial, aquatic and aerial species.

Main types of variables contained

The dataset contains estimates of home ranges of mammals, species names, methodological information on data collection, method of home-range estimation, period of data collection, study coordinates and name of location, in addition to species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit.

Spatial location and grain

The collected data are distributed globally. Across studies, the spatial accuracy varies, with the coarsest resolution being 1°.

Time period and grain

The data represent information published between 1939 and 2022. Across studies, the temporal accuracy varies; some studies report start and end dates specific to the day, whereas for other studies only the month or year is reported.

Major taxa and level of measurement

Mammalian species from 24 of the 27 different taxonomic orders. Home-range estimates range from individual-level values to population-level averages.

Software format

Data are supplied as a comma-delimited text file (.csv) and can be loaded directly into R using the “HomeRange” R package ( https://github.com/SHoeks/HomeRange ).     

A computational model to link psychophysics and cortical cell activation patterns in human texture processing

The human visual system uses texture information to automatically, or pre-attentively, segregate parts of the visual scene. We investigate the neural substrate underlying human texture processing using a computational model that consists of a hierarchy of bi-directionally linked model areas. The model builds upon two key hypotheses, namely that (i) texture segregation is based on boundary detection--rather than clustering of homogeneous items--and (ii) texture boundaries are detected mainly on the basis of a large scenic context that is analyzed by higher cortical areas within the ventral visual pathway, such as area V4. Here, we focus on the interpretation of key results from psychophysical studies on human texture segmentation. In psychophysical studies, texture patterns were varied along several feature dimensions to systematically characterize human performance. We use simulations to demonstrate that the activation patterns of our model directly correlate with the psychophysical results. This allows us to identify the putative neural mechanisms and cortical key areas which underlie human behavior. In particular, we investigate (i) the effects of varying texture density on target saliency, and the impact of (ii) element alignment and (iii) orientation noise on the detectability of a pop-out bar. As a result, we demonstrate that the dependency of target saliency on texture density is linked to a putative receptive field organization of orientation-selective neurons in V4. The effect of texture element alignment is related to grouping mechanisms in early visual areas. Finally, the modulation of cell activity by feedback activation from higher model areas, interacting with mechanisms of intra-areal center-surround competition, is shown to result in the specific suppression of noise-related cell activities and to improve the overall model capabilities in texture segmentation. In particular, feedback interaction is crucial to raise the model performance to the level of human observers.     

An assessment of the DNA barcodes of Indian freshwater fishes

Freshwater fishes in India are poorly known and plagued by many unresolved cryptic species complexes that masks some latent and endemic species. Limitations in traditional taxonomy have resulted in this crypticism. Hence, molecular approaches like DNA barcoding, are needed to diagnose these latent species. We have analyzed 1383 barcode sequences of 175 Indian freshwater fish species available in the databases, of which 172 sequences of 70 species were generated. The congeneric and conspecific genetic divergences were calculated using Kimura's 2 parameter distance model followed by the construction of a Neighbor Joining tree using the MEGA 5.1. DNA barcoding principle at its first hand approach, led to the straightforward identification of 82% of the studied species with 2.9% (S.E = 0.2) divergence between the nearest congeners. However, after validating some cases of synonymy and mislabeled sequences, 5% more species were found to be valid. Sequences submitted to the database under different names were found to represent single species. On the other hand, some sequences of the species like Barilius barna, Barilius bendelisis and Labeo bata were submitted to the database under a single name but were found to represent either some unexplored species or latent species. Overall, 87% of the available Indian freshwater fish barcodes were diagnosed as true species in parity with the existing checklist and can act as reference barcode for the particular taxa. For the remaining 13% (21 species) the correct species name was difficult to assign as they depicted some erroneous identification and cryptic species complex. Thus, these barcodes will need further assay and inclusion of barcodes of more specimens from same and sister species.