Hfsp Journal最新文献

The evolution of biocrystallography from the pioneers' time to the present era of global biology is presented in relation to the development of methodological and instrumental advances for molecular sample preparation and structure elucidation over the last 6 decades. The interdisciplinarity of the field that generated cross-fertilization between physics- and biology-focused themes is emphasized. In particular, strategies to circumvent the main bottlenecks of biocrystallography are discussed. They concern (i) the way macromolecular targets are selected, designed, and characterized, (ii) crystallogenesis and how to deal with physical and biological parameters that impact crystallization for growing and optimizing crystals, and (iii) the methods for crystal analysis and 3D structure determination. Milestones that have marked the history of biocrystallography illustrate the discussion. Finally, the future of the field is envisaged. Wide gaps of the structural space need to be filed and membrane proteins as well as intrinsically unstructured proteins still constitute challenging targets. Solving supramolecular assemblies of increasing complexity, developing a "4D biology" for decrypting the kinematic changes in macromolecular structures in action, integrating these structural data in the whole cell organization, and deciphering biomedical implications will represent the new frontiers.

We review modeling studies concerning cytoskeletal activity of fission yeast. Recent models vary in length and time scales, describing a range of phenomena from cellular morphogenesis to polymer assembly. The components of cytoskeleton act in concert to mediate cell-scale events and interactions such as polarization. The mathematical models reduce these events and interactions to their essential ingredients, describing the cytoskeleton by its bulk properties. On a smaller scale, models describe cytoskeletal subcomponents and how bulk properties emerge.

Despite significant progress in our understanding of the brain at both microscopic and macroscopic scales, the mechanisms by which low-level neuronal behavior gives rise to high-level mental processes such as memory still remain unknown. In this paper, we assess the plausibility and quantify the performance of polychronization, a newly proposed mechanism of neuronal encoding, which has been suggested to underlie a wide range of cognitive phenomena. We then investigate the effect of network topology on the reliability with which input stimuli can be distinguished based on their encoding in the form of so-called polychronous groups or spatiotemporal patterns of spikes. We find that small-world networks perform an order of magnitude better than random ones, enabling reliable discrimination between inputs even when prompted by increasingly incomplete recall cues. Furthermore, we show that small-world architectures operate at significantly reduced energetic costs and that their memory capacity scales favorably with network size. Finally, we find that small-world topologies introduce biologically realistic constraints on the optimal input stimuli, favoring especially the topographic inputs known to exist in many cortical areas. Our results suggest that mammalian cortical networks, by virtue of being both small-world and topographically organized, seem particularly well-suited to information processing through polychronization. This article addresses the fundamental question of encoding in neuroscience. In particular, evidence is presented in support of an emerging model of neuronal encoding in the neocortex based on spatiotemporal patterns of spikes.

The organization of biomotile systems possesses structural and functional hierarchy, building up from single molecules via protein assemblies and cells further up to an organ. A typical example is the hierarchy of cardiac muscle, on the top of which is the heart. The heartbeat is supported by the rhythmic contraction of the muscle cells that is controlled by the Ca(2+) oscillation triggered by periodic electrical excitation of pacemaker cells. Thus, it is usually believed that the heartbeat is governed by the control system based on a sequential one-way chain with the electrical∕chemical information transfer from the upper to the lower level of hierarchy. On the other hand, it has been known for many years that the contractile system of muscle, i.e., skinned muscle fibers and myofibrils, itself possesses the auto-oscillatory properties even in the constant chemical environment. A recent paper [Plaçais, et al. (2009), Phys. Rev. Lett. 103, 158102] demonstrated the auto-oscillatory movement∕tension development in an in vitro motility assay composed of a single actin filament and randomly distributed myosin II molecules, suggesting that the auto-oscillatory properties are inherent to the contractile proteins. Here we discuss how the molecular motors may acquire the higher-ordered auto-oscillatory properties while stepping up the staircase of hierarchy.

Aging affects all known organisms and has been studied extensively. Yet, the underlying mechanisms are insufficiently understood, possibly due to the multiscale complexity involved in this process: the aging of multicellular organisms depends on the aging of their cells, which depends on molecular events occurring in each cell. However, the aging of unicellular populations seeded in new niches and the aging of metazoans are surprisingly similar, indicating that the multiscale aspects of aging may have been conserved since the beginnings of cellular life on Earth. This underlines the importance of aging research in unicellular organisms such as a recent study by Lorenz et al., [(2009) Proc. Natl. Acad. Sci. U.S.A. 106, 1145-1150]. In their paper, the authors combine computational network identification with extensive experimentation and literature mining to discover and validate numerous regulatory interactions among ten genes involved in the cellular response to glucose starvation. Since low levels of glucose (calorie restriction) have been known to extend the longevity of various eukaryotes, the authors test the effect of Snf1 kinase overexpression on chronological aging and discover that this key regulator of glucose repression and two of its newly discovered synergistic repressors significantly affect the chronological lifespan of baker's yeast.

The morphogenetic movements, and the embryonic phenotypes they ultimately produce, are the consequence of a series of events that involve signaling pathways, cytoskeletal components, and cell- and tissue-level mechanical interactions. In order to better understand how these events work together in the context of amphibian neurulation, an existing multiscale computational model was augmented. Geometric data for this finite element-based mechanical model were obtained from 3D surface reconstructions of live axolotl embryos and serial sections of fixed specimens. Tissue mechanical properties were modeled using cell-based constitutive equations that include internal force generation and cell rearrangement, and equation parameters were adjusted manually to reflect biochemical changes including alterations in Shroom or the planar-cell-polarity pathway. The model indicates that neural tube defects can arise when convergent extension of the neural plate is reduced by as little as 20%, when it is eliminated on one side of the embryo, when neural ridge elevation is disrupted, when tension in the non-neural ectoderm is increased, or when the ectoderm thickness is increased. Where comparable conditions could be induced in Xenopus embryos, good agreement was found, an important step in model validation. The model reveals the neurulating embryo to be a finely tuned biomechanical system.

Evolvability is the property of a biological system to quickly adapt to new requirements. Robustness seems to be the opposite. Nonetheless many biological systems display both properties-a puzzling observation, which has caused many debates over the last decades. A recently published model by Draghi et al. [Nature 463, 353-355 (2010)] elegantly circumvents complications of earlier in silico studies of molecular systems and provides an analytical solution, which is surprisingly independent from parameter choice. Depending on the mutation rate and the number of accessible phenotypes at any given genotype, evolvability and robustness can be reconciled. Further research will need to investigate if these parameter settings adequately represent the range of degrees of freedom covered by natural systems and if natural systems indeed assume a state in which both properties, robustness and evolvability, are featured.