Solitary and repetitive binding motifs for the AP2 complex alpha-appendage in amphiphysin and other accessory proteins

Adaptor protein (AP) complexes bind to transmembrane proteins destined for internalization and to membrane lipids, so linking cargo to the accessory internalization machinery. This machinery interacts with the appendage domains of APs, which have platform and beta-sandwich subdomains, forming the binding surfaces for interacting proteins. Proteins that interact with the subdomains do so via short motifs, usually found in regions of low structural complexity of the interacting proteins. So far, up to four motifs have been identified that bind to and partially compete for at least two sites on each of the appendage domains of the AP2 complex. Motifs in individual accessory proteins, their sequential arrangement into motif domains, and partial competition for binding sites on the appendage domains coordinate the formation of endocytic complexes in a temporal and spatial manner. In this work, we examine the dominant interaction sequence in amphiphysin, a synapse-enriched accessory protein, which generates membrane curvature and recruits the scission protein dynamin to the necks of coated pits, for the platform subdomain of the alpha-appendage. The motif domain of amphiphysin1 contains one copy of each of a DX(F/W) and FXDXF motif. We find that the FXDXF motif is the main determinant for the high affinity interaction with the alpha-adaptin appendage. We describe the optimal sequence of the FXDXF motif using thermodynamic and structural data and show how sequence variation controls the affinities of these motifs for the alpha-appendage.

Whole Genome Sequencing Reveals Local Transmission Patterns of Mycobacterium bovis in Sympatric Cattle and Badger Populations

Whole genome sequencing (WGS) technology holds great promise as a tool for the forensic epidemiology of bacterial pathogens. It is likely to be particularly useful for studying the transmission dynamics of an observed epidemic involving a largely unsampled 'reservoir' host, as for bovine tuberculosis (bTB) in British and Irish cattle and badgers. BTB is caused by Mycobacterium bovis, a member of the M. tuberculosis complex that also includes the aetiological agent for human TB. In this study, we identified a spatio-temporally linked group of 26 cattle and 4 badgers infected with the same Variable Number Tandem Repeat (VNTR) type of M. bovis. Single-nucleotide polymorphisms (SNPs) between sequences identified differences that were consistent with bacterial lineages being persistent on or near farms for several years, despite multiple clear whole herd tests in the interim. Comparing WGS data to mathematical models showed good correlations between genetic divergence and spatial distance, but poor correspondence to the network of cattle movements or within-herd contacts. Badger isolates showed between zero and four SNP differences from the nearest cattle isolate, providing evidence for recent transmissions between the two hosts. This is the first direct genetic evidence of M. bovis persistence on farms over multiple outbreaks with a continued, ongoing interaction with local badgers. However, despite unprecedented resolution, directionality of transmission cannot be inferred at this stage. Despite the often notoriously long timescales between time of infection and time of sampling for TB, our results suggest that WGS data alone can provide insights into TB epidemiology even where detailed contact data are not available, and that more extensive sampling and analysis will allow for quantification of the extent and direction of transmission between cattle and badgers. © 2012 Biek et al.

Forecasting invasions: resource use by mussels informs invasion patterns along the South African coast

Invasive species are often more able to rapidly and efficiently utilise resources than natives, and comparing per capita resource use at different resource densities among invaders and trophically analogous natives could allow for reliable predictions of invasiveness. In South Africa, invasion by the Mediterranean mussel Mytilus galloprovincialis has transformed wave-exposed shores, negatively affecting native mussel species. Currently, South Africa is experiencing a second mussel invasion with the recent detection of the South American Semimytilus algosus. We tested per capita uptake of an algal resource by invading M. galloprovincialis, S. algosus, and the native Aulacomya atra at different algal concentrations and temperatures, representing the west and south coasts of South Africa, to examine whether their per capita resource use could be a predictor of their spread and subsequent invasiveness. Regardless of temperature, M. galloprovincialis was the most efficient consumer, significantly reducing algal cells compared to the other species when the resource was presented in both low and high starting densities. Furthermore, these findings aligned with a greater biomass of M. galloprovincialis on the shore in comparison with the other species. Resource use by the new invader S. algosus was dependent on the density of resource and, although this species was efficient at low algal concentrations at cooler temperatures, this pattern broke down at higher algal densities. This was once more reflected in lower biomass in surveys of this species along the cool west coast. We therefore forecast that S. algosus will be become established along the south coast; however, we also predict that M. galloprovincialis will maintain dominance on these shores.

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.