Hfsp Journal最新文献

Propagating actin waves are dynamic supramolecular structures formed by the self-assembly of proteins within living cells. They are built from actin filaments together with single-headed myosin, the Arp23 complex, and coronin in a defined three-dimensional order. The function of these waves in structuring the cell cortex is studied on the substrate-attached surface of Dictyostelium cells by the use of total internal reflection fluorescence (TIRF) microscopy. Actin waves separate two areas of the cell cortex from each other, which are distinguished by the arrangement of actin filaments. The Arp23 complex dominates in the area enclosed by a wave, where it has the capacity of building dendritic structures, while the proteins prevailing in the external area, cortexillin I and myosin-II, bundle actin filaments and arrange them in antiparallel direction. Wave propagation is accompanied by transitions in the state of actin with a preferential period of 5 min. Wave generation is preceded by local fluctuations in actin assembly, some of the nuclei of polymerized actin emanating from clathrin-coated structures, others emerging independently. The dynamics of phase transitions has been analyzed to provide a basis for modeling the nonlinear interactions that produce spatio-temporal patterns in the actin system of living cells.

The T-cell is one of the main players in the mammalian immune response. It ensures antigen recognition at the surface of antigen-presenting cells in a complex and highly sensitive and specific process, in which the encounter of the T-cell receptor with the agonist peptide associated with the major histocompatibility complex triggers T-cell activation. While signaling pathways have been elucidated in increasing detail, the mechanism of TCR triggering remains highly controversial despite active research published in the past 10 years. In this paper, we present a short overview of pending questions on critical initial events associated with T-cell triggering. In particular, we examine biophysical approaches already in use, as well as future directions. We suggest that the most recent advances in fluorescence super-resolution imaging, coupled with the new classes of genetic fluorescent probes, will play an important role in elucidation of the T-cell triggering mechanism. Beyond this aspect, we predict that exploration of mechanical cues in the triggering process will provide new clues leading to clarification of the entire mechanism.

The mitogen-activated protein kinase (MAPK) cascade is a paradigmatic signaling cascade, which plays a crucial role in many aspects of cellular events. The main initiator of the cascade in Xenopus oocytes is the oncoprotein Mos. After activation of the cascade, Mos activity is stabilized by MAPK via a feedback loop. Mos concentration levels are, however, not controlled by MAPK alone. In this paper we show, by imposing either a sustained or a peaked activity of M-phase promoting factor (MPF) (Cdc2-cyclin B), how the latter regulates the dynamics of Mos. Our experiments are supported by a detailed kinetic model for the Mos-MPF-MAPK network, which takes into account the three different phosphorylation states of Mos and, as a consequence, allows us to determine the time evolution of Mos under control of MPF. Our work opens a path toward a more complete and biologically realistic quantitative understanding of the dynamic interdependence of Mos and MPF in Xenopus oocytes.

The release of transmitter-filled vesicles from presynaptic terminals is a key step of neurotransmission. Prior to release, synaptic vesicles get clustered at a specialized patch of the presynaptic membrane, here referred to as the active zone. So far, mainly biochemical regulations at the active zone were regarded as decisive for synaptic vesicle clustering and release. However, using biophysical approaches, a recent paper [Siechen, et al. (2009). Proc. Natl. Acad. Sci. U.S.A. 106, 12611-12616] indicated also that the micromechanical regulations within axon and terminal could be crucial for proper vesicle clustering. The authors demonstrated that the synaptic vesicle accumulations vanished after axotomy but were restored after the application of physical tension. Furthermore, axons seem to be under an intrinsic tension, which could be perceived and tuned by an axon-internal tension sensing mechanism. Therefore, mechanical force could steer vesicle clustering and consequently synapse function. Here, we review this interdisciplinary study of Siechen, et al. [Proc. Natl. Acad. Sci. U.S.A. 106, 12611-12616 (2009)] and discuss the significance of cellular mechanics on synaptic function.

Dorsal closure, a stage of Drosophila development, is a model system for cell sheet morphogenesis and wound healing. During closure, two flanks of epidermal tissue progressively advance to reduce the area of the eye-shaped opening in the dorsal surface, which contains amnioserosa tissue. To simulate the time evolution of the overall shape of the dorsal opening, we developed a mathematical model, in which contractility and elasticity are manifest in model force-producing elements that satisfy force-velocity relationships similar to muscle. The action of the elements is consistent with the force-producing behavior of actin and myosin in cells. The parameters that characterize the simulated embryos were optimized by reference to experimental observations on wild-type embryos and, to a lesser extent, on embryos whose amnioserosa was removed by laser surgery and on myospheroid mutant embryos. Simulations failed to reproduce the amnioserosa-removal protocol in either the elastic or the contractile limit, indicating that both elastic and contractile dynamics are essential components of the biological force-producing elements. We found it was necessary to actively upregulate forces to recapitulate both the double and single-canthus nick protocols, which did not participate in the optimization of parameters, suggesting the existence of additional key feedback mechanisms.

Chromatin structure is a powerful tool to regulate eukaryotic transcription. Moreover, nucleosomes are constantly remodeled, disassembled, and reassembled in the body of transcribed genes. Here we propose a general model that explains, in quantitative terms, how transcription elongation affects nucleosome structure at a distance as a result of the positive torque the polymerases create as they translocate along DNA templates.

Quantum physics and biology have long been regarded as unrelated disciplines, describing nature at the inanimate microlevel on the one hand and living species on the other hand. Over the past decades the life sciences have succeeded in providing ever more and refined explanations of macroscopic phenomena that were based on an improved understanding of molecular structures and mechanisms. Simultaneously, quantum physics, originally rooted in a world-view of quantum coherences, entanglement, and other nonclassical effects, has been heading toward systems of increasing complexity. The present perspective article shall serve as a "pedestrian guide" to the growing interconnections between the two fields. We recapitulate the generic and sometimes unintuitive characteristics of quantum physics and point to a number of applications in the life sciences. We discuss our criteria for a future "quantum biology," its current status, recent experimental progress, and also the restrictions that nature imposes on bold extrapolations of quantum theory to macroscopic phenomena.

Observed phenotype often fails to correspond with genotype. Although it is well established that uncontrolled genetic modifier effects and environmental variability can affect phenotype, stochastic variation in gene expression can also contribute to phenotypic differences. Here we examine recent work that has provided insights into how fundamental physical properties of living cells, and the probabilistic nature of the chemical reactions that underlie gene expression, introduce noise. We focus on instances in which a stochastic decision initiates an event in the development of a multicellular organism and how that decision can be subsequently fixed. We present an example indicating that a similar interplay between an initial stochastic decision and subsequent fixation may underlie the regulation of reproduction in social insects. We argue, therefore, that stochasticity affects biological processes from the single-gene scale through to the complex organization of an ant colony, and represents a largely neglected component of phenotypic variation and evolution.

Long-standing debates about the role of natural selection in the growth of biological complexity over geological time scales are difficult to resolve from the paleobiological record. Using an evolutionary model-a computational ecosystem subjected to natural selection-we investigate evolutionary trends in an information-theoretic measure of the complexity of the neural dynamics of artificial agents inhabiting the model. Our results suggest that evolution always guides complexity change, just not in a single direction. We also demonstrate that neural complexity correlates well with behavioral adaptation but only when complexity increases are achieved through natural selection (as opposed to increases generated randomly or optimized via a genetic algorithm). We conclude with a suggested research direction that might be able to use the artificial neural data generated in these experiments to determine which aspects of network structure give rise to evolutionarily meaningful neural complexity.