Working at the interface of phylogenetics and population genetics: a biogeographical analysis of Triaenops spp. (Chiroptera: Hipposideridae).

New applications of genetic data to questions of historical biogeography have revolutionized our understanding of how organisms have come to occupy their present distributions. Phylogenetic methods in combination with divergence time estimation can reveal biogeographical centres of origin, differentiate between hypotheses of vicariance and dispersal, and reveal the directionality of dispersal events. Despite their power, however, phylogenetic methods can sometimes yield patterns that are compatible with multiple, equally well-supported biogeographical hypotheses. In such cases, additional approaches must be integrated to differentiate among conflicting dispersal hypotheses. Here, we use a synthetic approach that draws upon the analytical strengths of coalescent and population genetic methods to augment phylogenetic analyses in order to assess the biogeographical history of Madagascar's Triaenops bats (Chiroptera: Hipposideridae). Phylogenetic analyses of mitochondrial DNA sequence data for Malagasy and east African Triaenops reveal a pattern that equally supports two competing hypotheses. While the phylogeny cannot determine whether Africa or Madagascar was the centre of origin for the species investigated, it serves as the essential backbone for the application of coalescent and population genetic methods. From the application of these methods, we conclude that a hypothesis of two independent but unidirectional dispersal events from Africa to Madagascar is best supported by the data.

Suppression of conformational heterogeneity at a protein-protein interface.

Staphylococcal protein A (SpA) is an important virulence factor from Staphylococcus aureus responsible for the bacterium's evasion of the host immune system. SpA includes five small three-helix-bundle domains that can each bind with high affinity to many host proteins such as antibodies. The interaction between a SpA domain and the Fc fragment of IgG was partially elucidated previously in the crystal structure 1FC2. Although informative, the previous structure was not properly folded and left many substantial questions unanswered, such as a detailed description of the tertiary structure of SpA domains in complex with Fc and the structural changes that take place upon binding. Here we report the 2.3-Å structure of a fully folded SpA domain in complex with Fc. Our structure indicates that there are extensive structural rearrangements necessary for binding Fc, including a general reduction in SpA conformational heterogeneity, freezing out of polyrotameric interfacial residues, and displacement of a SpA side chain by an Fc side chain in a molecular-recognition pocket. Such a loss of conformational heterogeneity upon formation of the protein-protein interface may occur when SpA binds its multiple binding partners. Suppression of conformational heterogeneity may be an important structural paradigm in functionally plastic proteins.

VizMaps: A Bayesian Topic Modeling Based PubMed Search Interface

A common challenge that users of academic databases face is making sense of their query outputs for knowledge discovery. This is exacerbated by the size and growth of modern databases. PubMed, a central index of biomedical literature, contains over 25 million citations, and can output search results containing hundreds of thousands of citations. Under these conditions, efficient knowledge discovery requires a different data structure than a chronological list of articles. It requires a method of conveying what the important ideas are, where they are located, and how they are connected; a method of allowing users to see the underlying topical structure of their search. This paper presents VizMaps, a PubMed search interface that addresses some of these problems. Given search terms, our main backend pipeline extracts relevant words from the title and abstract, and clusters them into discovered topics using Bayesian topic models, in particular the Latent Dirichlet Allocation (LDA). It then outputs a visual, navigable map of the query results.