22 research outputs found

    Scaling properties of protein family phylogenies

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    One of the classical questions in evolutionary biology is how evolutionary processes are coupled at the gene and species level. With this motivation, we compare the topological properties (mainly the depth scaling, as a characterization of balance) of a large set of protein phylogenies with a set of species phylogenies. The comparative analysis shows that both sets of phylogenies share remarkably similar scaling behavior, suggesting the universality of branching rules and of the evolutionary processes that drive biological diversification from gene to species level. In order to explain such generality, we propose a simple model which allows us to estimate the proportion of evolvability/robustness needed to approximate the scaling behavior observed in the phylogenies, highlighting the relevance of the robustness of a biological system (species or protein) in the scaling properties of the phylogenetic trees. Thus, the rules that govern the incapability of a biological system to diversify are equally relevant both at the gene and at the species level.Comment: Replaced with final published versio

    Flower Bats (Glossophaga soricina) and Fruit Bats (Carollia perspicillata) Rely on Spatial Cues over Shapes and Scents When Relocating Food

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    Natural selection can shape specific cognitive abilities and the extent to which a given species relies on various cues when learning associations between stimuli and rewards. Because the flower bat Glossophaga soricina feeds primarily on nectar, and the locations of nectar-producing flowers remain constant, G. soricina might be predisposed to learn to associate food with locations. Indeed, G. soricina has been observed to rely far more heavily on spatial cues than on shape cues when relocating food, and to learn poorly when shape alone provides a reliable cue to the presence of food.Here we determined whether G. soricina would learn to use scent cues as indicators of the presence of food when such cues were also available. Nectar-producing plants fed upon by G. soricina often produce distinct, intense odors. We therefore expected G. soricina to relocate food sources using scent cues, particularly the flower-produced compound, dimethyl disulfide, which is attractive even to G. soricina with no previous experience of it. We also compared the learning of associations between cues and food sources by G. soricina with that of a related fruit-eating bat, Carollia perspicillata. We found that (1) G. soricina did not learn to associate scent cues, including dimethyl disulfide, with feeding sites when the previously rewarded spatial cues were also available, and (2) both the fruit-eating C. perspicillata and the flower-feeding G. soricina were significantly more reliant on spatial cues than associated sensory cues for relocating food.These findings, taken together with past results, provide evidence of a powerful, experience-independent predilection of both species to rely on spatial cues when attempting to relocate food

    Density functional theory

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    Density functional theory (DFT) finds increasing use in applications related to biological systems. Advancements in methodology and implementations have reached a point where predicted properties of reasonable to high quality can be obtained. Thus, DFT studies can complement experimental investigations, or even venture with some confidence into experimentally unexplored territory. In the present contribution, we provide an overview of the properties that can be calculated with DFT, such as geometries, energies, reaction mechanisms, and spectroscopic properties. A wide range of spectroscopic parameters is nowadays accessible with DFT, including quantities related to infrared and optical spectra, X-ray absorption and Mössbauer, as well as all of the magnetic properties connected with electron paramagnetic resonance spectroscopy except relaxation times. We highlight each of these fields of application with selected examples from the recent literature and comment on the capabilities and limitations of current methods
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