Environment predicts repeated body size shifts in a recent radiation of Australian mammals*

Closely related species that occur across steep environmental gradients often display clear body size differences, and examining this pattern is crucial to understanding how environmental variation shapes diversity. Australian endemic rodents in the Pseudomys Division (Muridae: Murinae) have repeatedly colonized the arid, monsoon, and mesic biomes over the last 5 million years. Using occurrence records, body mass data, and Bayesian phylogenetic models, we test whether body mass of 31 species in the Pseudomys Division can be predicted by their biome association. We also model the effect of eight environmental variables on body mass. Despite high phylogenetic signal in body mass evolution across the phylogeny, we find that mass predictably increases in the mesic biome and decreases in arid and monsoon biomes. As per Bergmann's rule, temperature is strongly correlated with body mass, as well as several other variables. Our results highlight two important findings. First, body size in Australian rodents has tracked with climate through the Pleistocene, likely due to several environmental variables rather than a single factor. Second, support for both Brownian motion and predictable change at different taxonomic levels in the Pseudomys Division phylogeny demonstrates how the level at which we test hypotheses can alter interpretation of evolutionary processes.     

On evaluation of infection probabilities for different age groups

It is well known that evaluation of parameters for any mathematical model is always very important and often a very difficult problem. This is especially true for agents-based models because as a rule the evaluation of an agent's parameters can be made only based on available information from the higher levels of a complex system. Such problems can be ill-posed or even have a non-unique solution. That is why there is no general algorithm for solving these problems and a researcher has to search for it for every specific model type.     

A new fast algorithm for solving the minimum spanning tree problem based on DNA molecules computation

The minimum spanning tree (MST) problem is to find minimum edge connected subsets containing all the vertex of a given undirected graph. It is a vitally important NP-complete problem in graph theory and applied mathematics, having numerous real life applications. Moreover in previous studies, DNA molecular operations usually were used to solve NP-complete head-to-tail path search problems, rarely for NP-hard problems with multi-lateral path solutions result, such as the minimum spanning tree problem. In this paper, we present a new fast DNA algorithm for solving the MST problem using DNA molecular operations. For an undirected graph with n vertex and m edges, we reasonably design flexible length DNA strands representing the vertex and edges, take appropriate steps and get the solutions of the MST problem in proper length range and O(3m + n) time complexity. We extend the application of DNA molecular operations and simultaneity simplify the complexity of the computation. Results of computer simulative experiments show that the proposed method updates some of the best known values with very short time and that the proposed method provides a better performance with solution accuracy over existing algorithms.     

Ein bakterielles Kulturfiltrat mit antiphytoviraler Aktivität an Gurke/Gurkenmosaik-Virus (cucumber mosaic virus) und Tabak/Tabakmosaik-Virus (tobacco mosaic virus): (Kurze Mitteilung)

Es wurde die Intra‐ und Interpopulationsvariation untersucht, die durch Adaptationsreaktionen der Individuen (Klone) der Gemeinen Quecke (Elytrigia repens (L.) DESV.) am Versuchsort zum Ausdruck kommt. Die Klone stammten aus Populationen verschiedener Höhenlagen vom Territorium der östlichen Bundesländer Deutschlands. Die Ergebnisse zeigen, daß sich die Populationen in der Variabilität der Enzymaktivität (saure Phosphatase, Peroxidase, Polyphenoloxidase) sowie in der Variabilität der Isoenzymmuster (Peroxidase, Esterase) unterscheiden. Die höchste Variabilität der genannten Parameter wurde für Populationen nachgewiesen, die aus einer Höhenlage von ca. 400 m ü. NN stammten. Ausgehend von 400 m ü. NN nimmt die Variabilität in Richtung größerer und niedrigerer Höhenlagen von 400 m hin ab. Die Variabilitätsunterschiede, die unter gleichen Bedingungen nachgewiesen wurden, weisen auf die Existenz eines Zusammenhanges zwischen den typischen Adaptationsreaktionen von Populationen und der Gesamtheit der Selektionsfaktoren des natürlichen Milieus hin, von dem sie stammten. Es gibt einen Zusammenhang zwischen der nachgewiesenen Variabilität und der Überlebensrate nach einer Adaptationsdauer von fünf Jahren.     

Inverse Problem in Materials Science

Abstract

The importance of the inverse problem in materials science, that is, the determination of unknown parameters in the physico-chemical models from the experimental values is emphasized. The main attention is given to the problem of how to take into account experimental systematic errors during the inverse problem.     

BetaDock: Shape-Priority Docking Method Based on Beta-Complex

Abstract

This paper presents an approach and a software, BetaDock, to the docking problem by putting the priority on shape complementarity between a receptor and a ligand. The approach is based on the theory of the β-complex. Given the Voronoi diagram of the receptor whose topology is stored in the quasi-triangulation, the β-complex corresponding to water molecule is computed. Then, the boundary of the β-complex defines the β-shape which has the complete proximity information among all atoms on the receptor boundary. From the β-shape, we first compute pockets where the ligand may bind. Then, we quickly place the ligand within each pocket by solving the singular value decomposition problem and the assignment problem. Using the conformations of the ligands within the pockets as the initial solutions, we run the genetic algorithm to find the optimal solution for the docking problem. The performance of the proposed algorithm was verified through a benchmark test and showed that BetaDock is superior to a popular docking software AutoDock 4.     

Role of Central Metabolism in the Osmoadaptation of the Halophilic Bacterium Chromohalobacter salexigens

Bacterial osmoadaptation involves the cytoplasmic accumulation of compatible solutes to counteract extracellular osmolarity. The halophilic and highly halotolerant bacterium Chromohalobacter salexigens is able to grow up to 3 m NaCl in a minimal medium due to the de novo synthesis of ectoines. This is an osmoregulated pathway that burdens central metabolic routes by quantitatively drawing off TCA cycle intermediaries. Consequently, metabolism in C. salexigens has adapted to support this biosynthetic route. Metabolism of C. salexigens is more efficient at high salinity than at low salinity, as reflected by lower glucose consumption, lower metabolite overflow, and higher biomass yield. At low salinity, by-products (mainly gluconate, pyruvate, and acetate) accumulate extracellularly. Using [1-¹³C]-, [2-¹³C]-, [6-¹³C]-, and [U-¹³C₆]glucose as carbon sources, we were able to determine the main central metabolic pathways involved in ectoines biosynthesis from glucose. C. salexigens uses the Entner-Doudoroff pathway rather than the standard glycolytic pathway for glucose catabolism, and anaplerotic activity is high to replenish the TCA cycle with the intermediaries withdrawn for ectoines biosynthesis. Metabolic flux ratios at low and high salinity were similar, revealing a certain metabolic rigidity, probably due to its specialization to support high biosynthetic fluxes and partially explaining why metabolic yields are so highly affected by salinity. This work represents an important contribution to the elucidation of specific metabolic adaptations in compatible solute-accumulating halophilic bacteria.     

Probability in biology: Overview of a comprehensive theory of probability in living systems

Probability is closely related to biological organization and adaptation to the environment. Living systems need to maintain their organizational order by producing specific internal events non-randomly, and must cope with the uncertain environments. These processes involve increases in the probability of favorable events for these systems by reducing the degree of uncertainty of events. Systems with this ability will survive and reproduce more than those that have less of this ability. Probabilistic phenomena have been deeply explored using the mathematical theory of probability since Kolmogorov's axiomatization provided mathematical consistency for the theory. However, the interpretation of the concept of probability remains both unresolved and controversial, which creates problems when the mathematical theory is applied to problems in real systems. In this article, recent advances in the study of the foundations of probability from a biological viewpoint are reviewed, and a new perspective is discussed toward a comprehensive theory of probability for understanding the organization and adaptation of living systems.     

On the limitations of standard statistical modeling in biological systems: A full Bayesian approach for biology

One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist.     

TRADE‐OFFS,SPATIAL HETEROGENEITY,AND THE MAINTENANCE OF MICROBIAL DIVERSITY

Specialization and concomitant trade‐offs are assumed to underlie the non‐neutral coexistence of lineages. Trade‐offs across heterogeneous environments can promote diversity by preventing competitive exclusion. However, the importance of trade‐offs in maintaining diversity in natural microbial assemblages is unclear, as trade‐offs are frequently not detected in artificial evolution experiments. Stressful conditions associated with patches of heavy‐metal enriched serpentine soils provide excellent opportunities for examining how heterogeneity may foster genetic diversity. Using a spatially replicated design, we demonstrate that rhizobium bacteria symbiotic with legumes inhabiting contrasting serpentine and nonserpentine soils exhibit a trade‐off between a genotype's nickel tolerance and its ability to replicate rapidly. Furthermore, we detected adaptive divergence in rhizobial assemblages across soil type heterogeneity at multiple sites, suggesting that this trade‐off may promote the coexistence of phenotypically distinct bacterial lineages. Trade‐offs and adaptive divergence may be important factors maintaining the tremendous diversity within natural assemblages of bacteria.